Update autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/Flow/Flow.tsx

Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>

.claude/skills/open-pr/SKILL.md

@@ -1,106 +0,0 @@
----
-name: open-pr
-description: Open a pull request with proper PR template, test coverage, and review workflow. Guides agents through creating a PR that follows repo conventions, ensures existing behaviors aren't broken, covers new behaviors with tests, and handles review via bot when local testing isn't possible. TRIGGER when user asks to "open a PR", "create a PR", "make a PR", "submit a PR", "open pull request", "push and create PR", or any variation of opening/submitting a pull request.
-user-invocable: true
-args: "[base-branch] — optional target branch (defaults to dev)."
-metadata:
-  author: autogpt-team
-  version: "1.0.0"
----
-
-# Open a Pull Request
-
-## Step 1: Pre-flight checks
-
-Before opening the PR:
-
-1. Ensure all changes are committed
-2. Ensure the branch is pushed to the remote (`git push -u origin <branch>`)
-3. Run linters/formatters across the whole repo (not just changed files) and commit any fixes
-
-## Step 2: Test coverage
-
-**This is critical.** Before opening the PR, verify:
-
-### Existing behavior is not broken
-- Identify which modules/components your changes touch
-- Run the existing test suites for those areas
-- If tests fail, fix them before opening the PR — do not open a PR with known regressions
-
-### New behavior has test coverage
-- Every new feature, endpoint, or behavior change needs tests
-- If you added a new block, add tests for that block
-- If you changed API behavior, add or update API tests
-- If you changed frontend behavior, verify it doesn't break existing flows
-
-If you cannot run the full test suite locally, note which tests you ran and which you couldn't in the test plan.
-
-## Step 3: Create the PR using the repo template
-
-Read the canonical PR template at `.github/PULL_REQUEST_TEMPLATE.md` and use it **verbatim** as your PR body:
-
-1. Read the template: `cat .github/PULL_REQUEST_TEMPLATE.md`
-2. Preserve the exact section titles and formatting, including:
-   - `### Why / What / How`
-   - `### Changes 🏗️`
-   - `### Checklist 📋`
-3. Replace HTML comment prompts (`<!-- ... -->`) with actual content; do not leave them in
-4. **Do not pre-check boxes** — leave all checkboxes as `- [ ]` until each step is actually completed
-5. Do not alter the template structure, rename sections, or remove any checklist items
-
-**PR title must use conventional commit format** (e.g., `feat(backend): add new block`, `fix(frontend): resolve routing bug`, `dx(skills): update PR workflow`). See CLAUDE.md for the full list of scopes.
-
-Use `gh pr create` with the base branch (defaults to `dev` if no `[base-branch]` was provided). Use `--body-file` to avoid shell interpretation of backticks and special characters:
-
-```bash
-BASE_BRANCH="${BASE_BRANCH:-dev}"
-PR_BODY=$(mktemp)
-cat > "$PR_BODY" << 'PREOF'
-<filled-in template from .github/PULL_REQUEST_TEMPLATE.md>
-PREOF
-gh pr create --base "$BASE_BRANCH" --title "<type>(scope): short description" --body-file "$PR_BODY"
-rm "$PR_BODY"
-```
-
-## Step 4: Review workflow
-
-### If you have a workspace that allows testing (docker, running backend, etc.)
-- Run `/pr-test` to do E2E manual testing of the PR using docker compose, agent-browser, and API calls. This is the most thorough way to validate your changes before review.
-- After testing, run `/pr-review` to self-review the PR for correctness, security, code quality, and testing gaps before requesting human review.
-
-### If you do NOT have a workspace that allows testing
-This is common for agents running in worktrees without a full stack. In this case:
-
-1. Run `/pr-review` locally to catch obvious issues before pushing
-2. **Comment `/review` on the PR** after creating it to trigger the review bot
-3. **Poll for the review** rather than blindly waiting — check for new review comments every 30 seconds using `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews --paginate` and the GraphQL inline threads query. The bot typically responds within 30 minutes, but polling lets the agent react as soon as it arrives.
-4. Do NOT proceed or merge until the bot review comes back
-5. Address any issues the bot raises — use `/pr-address` which has a full polling loop with CI + comment tracking
-
-```bash
-# After creating the PR:
-PR_NUMBER=$(gh pr view --json number -q .number)
-gh pr comment "$PR_NUMBER" --body "/review"
-# Then use /pr-address to poll for and address the review when it arrives
-```
-
-## Step 5: Address review feedback
-
-Once the review bot or human reviewers leave comments:
-- Run `/pr-address` to address review comments. It will loop until CI is green and all comments are resolved.
-- Do not merge without human approval.
-
-## Related skills
-
-| Skill | When to use |
-|---|---|
-| `/pr-test` | E2E testing with docker compose, agent-browser, API calls — use when you have a running workspace |
-| `/pr-review` | Review for correctness, security, code quality — use before requesting human review |
-| `/pr-address` | Address reviewer comments and loop until CI green — use after reviews come in |
-
-## Step 6: Post-creation
-
-After the PR is created and review is triggered:
-- Share the PR URL with the user
-- If waiting on the review bot, let the user know the expected wait time (~30 min)
-- Do not merge without human approval

.claude/skills/pr-address/SKILL.md

@@ -2,7 +2,7 @@
 name: pr-address
 description: Address PR review comments and loop until CI green and all comments resolved. TRIGGER when user asks to address comments, fix PR feedback, respond to reviewers, or babysit/monitor a PR.
 user-invocable: true
-argument-hint: "[PR number or URL] — if omitted, finds PR for current branch."
+args: "[PR number or URL] — if omitted, finds PR for current branch."
 metadata:
   author: autogpt-team
   version: "1.0.0"
@@ -17,70 +17,18 @@ gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoG
 gh pr view {N}
 ```
 
-## Read the PR description
-
-Understand the **Why / What / How** before addressing comments — you need context to make good fixes:
-
-```bash
-gh pr view {N} --json body --jq '.body'
-```
-
 ## Fetch comments (all sources)
 
-### 1. Inline review threads — GraphQL (primary source of actionable items)
-
-Use GraphQL to fetch inline threads. It natively exposes `isResolved`, returns threads already grouped with all replies, and paginates via cursor — no manual thread reconstruction needed.
-
 ```bash
-gh api graphql -f query='
-{
-  repository(owner: "Significant-Gravitas", name: "AutoGPT") {
-    pullRequest(number: {N}) {
-      reviewThreads(first: 100) {
-        pageInfo { hasNextPage endCursor }
-        nodes {
-          id
-          isResolved
-          path
-          comments(last: 1) {
-            nodes { databaseId body author { login } createdAt }
-          }
-        }
-      }
-    }
-  }
-}'
+gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews       # top-level reviews
+gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments      # inline review comments
+gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments     # PR conversation comments
 ```
 
-If `pageInfo.hasNextPage` is true, fetch subsequent pages by adding `after: "<endCursor>"` to `reviewThreads(first: 100, after: "...")` and repeat until `hasNextPage` is false.
-
-**Filter to unresolved threads only** — skip any thread where `isResolved: true`. `comments(last: 1)` returns the most recent comment in the thread — act on that; it reflects the reviewer's final ask. Use the thread `id` (Relay global ID) to track threads across polls.
-
-### 2. Top-level reviews — REST (MUST paginate)
-
-```bash
-gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews --paginate
-```
-
-**CRITICAL — always `--paginate`.** Reviews default to 30 per page. PRs can have 80–170+ reviews (mostly empty resolution events). Without pagination you miss reviews past position 30 — including `autogpt-reviewer`'s structured review which is typically posted after several CI runs and sits well beyond the first page.
-
-Two things to extract:
-- **Overall state**: look for `CHANGES_REQUESTED` or `APPROVED` reviews.
-- **Actionable feedback**: non-empty bodies only. Empty-body reviews are thread-resolution events — they indicate progress but have no feedback to act on.
-
-**Where each reviewer posts:**
-- `autogpt-reviewer` — posts detailed structured reviews ("Blockers", "Should Fix", "Nice to Have") as **top-level reviews**. Not present on every PR. Address ALL items.
-- `sentry[bot]` — posts bug predictions as **inline threads**. Fix real bugs, explain false positives.
-- `coderabbitai[bot]` — posts summaries as **top-level reviews** AND actionable items as **inline threads**. Address actionable items.
-- Human reviewers — can post in any source. Address ALL non-empty feedback.
-
-### 3. PR conversation comments — REST
-
-```bash
-gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments --paginate
-```
-
-Mostly contains: bot summaries (`coderabbitai[bot]`), CI/conflict detection (`github-actions[bot]`), and author status updates. Scan for non-empty messages from non-bot human reviewers that aren't the PR author — those are the ones that need a response.
+**Bots to watch for:**
+- `autogpt-reviewer` — posts "Blockers", "Should Fix", "Nice to Have". Address ALL of them.
+- `sentry[bot]` — bug predictions. Fix real bugs, explain false positives.
+- `coderabbitai[bot]` — automated review. Address actionable items.
 
 ## For each unaddressed comment
 
@@ -92,8 +40,8 @@ Address comments **one at a time**: fix → commit → push → inline reply →
 
 | Comment type | How to reply |
 |---|---|
-| Inline review (`pulls/{N}/comments`) | `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments/{ID}/replies -f body="🤖 Fixed in <commit-sha>: <description>"` |
-| Conversation (`issues/{N}/comments`) | `gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments -f body="🤖 Fixed in <commit-sha>: <description>"` |
+| Inline review (`pulls/{N}/comments`) | `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments/{ID}/replies -f body="Fixed in <commit-sha>: <description>"` |
+| Conversation (`issues/{N}/comments`) | `gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments -f body="Fixed in <commit-sha>: <description>"` |
 
 ## Format and commit
 
@@ -113,9 +61,7 @@ kill $REST_PID 2>/dev/null; trap - EXIT
 ```
 Never manually edit files in `src/app/api/__generated__/`.
 
-Then commit and **push immediately** — never batch commits without pushing. Each fix should be visible on GitHub right away so CI can start and reviewers can see progress.
-
-**Never push empty commits** (`git commit --allow-empty`) to re-trigger CI or bot checks. When a check fails, investigate the root cause (unchecked PR checklist, unaddressed review comments, code issues) and fix those directly. Empty commits add noise to git history.
+Then commit and **push immediately** — never batch commits without pushing.
 
 For backend commits in worktrees: `poetry run git commit` (pre-commit hooks).
 
@@ -123,88 +69,11 @@ For backend commits in worktrees: `poetry run git commit` (pre-commit hooks).
 
 ```text
 address comments → format → commit → push
-→ wait for CI (while addressing new comments) → fix failures → push
-→ re-check comments after CI settles
+→ re-check comments → fix new ones → push
+→ wait for CI → re-check comments after CI settles
 → repeat until: all comments addressed AND CI green AND no new comments arriving
 ```
 
-### Polling for CI + new comments
+While CI runs, stay productive: run local tests, address remaining comments.
 
-After pushing, poll for **both** CI status and new comments in a single loop. Do not use `gh pr checks --watch` — it blocks the tool and prevents reacting to new comments while CI is running.
-
-> **Note:** `gh pr checks --watch --fail-fast` is tempting but it blocks the entire Bash tool call, meaning the agent cannot check for or address new comments until CI fully completes. Always poll manually instead.
-
-**Polling loop — repeat every 30 seconds:**
-
-1. Check CI status:
-```bash
-gh pr checks {N} --repo Significant-Gravitas/AutoGPT --json bucket,name,link
-```
-   Parse the results: if every check has `bucket` of `"pass"` or `"skipping"`, CI is green. If any has `"fail"`, CI has failed. Otherwise CI is still pending.
-
-2. Check for merge conflicts:
-```bash
-gh pr view {N} --repo Significant-Gravitas/AutoGPT --json mergeable --jq '.mergeable'
-```
-   If the result is `"CONFLICTING"`, the PR has a merge conflict — see "Resolving merge conflicts" below. If `"UNKNOWN"`, GitHub is still computing mergeability — wait and re-check next poll.
-
-3. Check for new/changed comments (all three sources):
-
-   **Inline threads** — re-run the GraphQL query from "Fetch comments". For each unresolved thread, record `{thread_id, last_comment_databaseId}` as your baseline. On each poll, action is needed if:
-   - A new thread `id` appears that wasn't in the baseline (new thread), OR
-   - An existing thread's `last_comment_databaseId` has changed (new reply on existing thread)
-
-   **Conversation comments:**
-   ```bash
-   gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments --paginate
-   ```
-   Compare total count and newest `id` against baseline. Filter to non-empty, non-bot, non-author-update messages.
-
-   **Top-level reviews:**
-   ```bash
-   gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews --paginate
-   ```
-   Watch for new non-empty reviews (`CHANGES_REQUESTED` or `COMMENTED` with body). Compare total count and newest `id` against baseline.
-
-4. **React in this precedence order (first match wins):**
-
-| What happened | Action |
-|---|---|
-| Merge conflict detected | See "Resolving merge conflicts" below. |
-| Mergeability is `UNKNOWN` | GitHub is still computing mergeability. Sleep 30 seconds, then restart polling from the top. |
-| New comments detected | Address them (fix → commit → push → reply). After pushing, re-fetch all comments to update your baseline, then restart this polling loop from the top (new commits invalidate CI status). |
-| CI failed (bucket == "fail") | Get failed check links: `gh pr checks {N} --repo Significant-Gravitas/AutoGPT --json bucket,link --jq '.[] \| select(.bucket == "fail") \| .link'`. Extract run ID from link (format: `.../actions/runs/<run-id>/job/...`), read logs with `gh run view <run-id> --repo Significant-Gravitas/AutoGPT --log-failed`. Fix → commit → push → restart polling. |
-| CI green + no new comments | **Do not exit immediately.** Bots (coderabbitai, sentry) often post reviews shortly after CI settles. Continue polling for **2 more cycles (60s)** after CI goes green. Only exit after 2 consecutive green+quiet polls. |
-| CI pending + no new comments | Sleep 30 seconds, then poll again. |
-
-**The loop ends when:** CI fully green + all comments addressed + **2 consecutive polls with no new comments after CI settled.**
-
-### Resolving merge conflicts
-
-1. Identify the PR's target branch and remote:
-```bash
-gh pr view {N} --repo Significant-Gravitas/AutoGPT --json baseRefName --jq '.baseRefName'
-git remote -v   # find the remote pointing to Significant-Gravitas/AutoGPT (typically 'upstream' in forks, 'origin' for direct contributors)
-```
-
-2. Pull the latest base branch with a 3-way merge:
-```bash
-git pull {base-remote} {base-branch} --no-rebase
-```
-
-3. Resolve conflicting files, then verify no conflict markers remain:
-```bash
-if grep -R -n -E '^(<<<<<<<|=======|>>>>>>>)' <conflicted-files>; then
-  echo "Unresolved conflict markers found — resolve before proceeding."
-  exit 1
-fi
-```
-
-4. Stage and push:
-```bash
-git add <conflicted-files>
-git commit -m "Resolve merge conflicts with {base-branch}"
-git push
-```
-
-5. Restart the polling loop from the top — new commits reset CI status.
+**The loop ends when:** CI fully green + all comments addressed + no new comments since CI settled.

.claude/skills/pr-review/SKILL.md

@@ -17,16 +17,6 @@ gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoG
 gh pr view {N}
 ```
 
-## Read the PR description
-
-Before reading code, understand the **why**, **what**, and **how** from the PR description:
-
-```bash
-gh pr view {N} --json body --jq '.body'
-```
-
-Every PR should have a Why / What / How structure. If any of these are missing, note it as feedback.
-
 ## Read the diff
 
 ```bash
@@ -38,14 +28,12 @@ gh pr diff {N}
 Before posting anything, fetch existing inline comments to avoid duplicates:
 
 ```bash
-gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments --paginate
+gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments
 gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews
 ```
 
 ## What to check
 
-**Description quality:** Does the PR description cover Why (motivation/problem), What (summary of changes), and How (approach/implementation details)? If any are missing, request them — you can't judge the approach without understanding the problem and intent.
-
 **Correctness:** logic errors, off-by-one, missing edge cases, race conditions (TOCTOU in file access, credit charging), error handling gaps, async correctness (missing `await`, unclosed resources).
 
 **Security:** input validation at boundaries, no injection (command, XSS, SQL), secrets not logged, file paths sanitized (`os.path.basename()` in error messages).

.claude/skills/pr-test/SKILL.md

@@ -1,754 +0,0 @@
----
-name: pr-test
-description: "E2E manual testing of PRs/branches using docker compose, agent-browser, and API calls. TRIGGER when user asks to manually test a PR, test a feature end-to-end, or run integration tests against a running system."
-user-invocable: true
-argument-hint: "[worktree path or PR number] — tests the PR in the given worktree. Optional flags: --fix (auto-fix issues found)"
-metadata:
-  author: autogpt-team
-  version: "2.0.0"
----
-
-# Manual E2E Test
-
-Test a PR/branch end-to-end by building the full platform, interacting via browser and API, capturing screenshots, and reporting results.
-
-## Critical Requirements
-
-These are NON-NEGOTIABLE. Every test run MUST satisfy ALL the following:
-
-### 1. Screenshots at Every Step
-- Take a screenshot at EVERY significant test step — not just at the end
-- Every test scenario MUST have at least one BEFORE and one AFTER screenshot
-- Name screenshots sequentially: `{NN}-{action}-{state}.png` (e.g., `01-credits-before.png`, `02-credits-after.png`)
-- If a screenshot is missing for a scenario, the test is INCOMPLETE — go back and take it
-
-### 2. Screenshots MUST Be Posted to PR
-- Push ALL screenshots to a temp branch `test-screenshots/pr-{N}`
-- Post a PR comment with ALL screenshots embedded inline using GitHub raw URLs
-- This is NOT optional — every test run MUST end with a PR comment containing screenshots
-- If screenshot upload fails, retry. If it still fails, list failed files and require manual drag-and-drop/paste attachment in the PR comment
-
-### 3. State Verification with Before/After Evidence
-- For EVERY state-changing operation (API call, user action), capture the state BEFORE and AFTER
-- Log the actual API response values (e.g., `credits_before=100, credits_after=95`)
-- Screenshot MUST show the relevant UI state change
-- Compare expected vs actual values explicitly — do not just eyeball it
-
-### 4. Negative Test Cases Are Mandatory
-- Test at least ONE negative case per feature (e.g., insufficient credits, invalid input, unauthorized access)
-- Verify error messages are user-friendly and accurate
-- Verify the system state did NOT change after a rejected operation
-
-### 5. Test Report Must Include Full Evidence
-Each test scenario in the report MUST have:
-- **Steps**: What was done (exact commands or UI actions)
-- **Expected**: What should happen
-- **Actual**: What actually happened
-- **API Evidence**: Before/after API response values for state-changing operations
-- **Screenshot Evidence**: Before/after screenshots with explanations
-
-## State Manipulation for Realistic Testing
-
-When testing features that depend on specific states (rate limits, credits, quotas):
-
-1. **Use Redis CLI to set counters directly:**
-   ```bash
-   # Find the Redis container
-   REDIS_CONTAINER=$(docker ps --format '{{.Names}}' | grep redis | head -1)
-   # Set a key with expiry
-   docker exec $REDIS_CONTAINER redis-cli SET key value EX ttl
-   # Example: Set rate limit counter to near-limit
-   docker exec $REDIS_CONTAINER redis-cli SET "rate_limit:user:test@test.com" 99 EX 3600
-   # Example: Check current value
-   docker exec $REDIS_CONTAINER redis-cli GET "rate_limit:user:test@test.com"
-   ```
-
-2. **Use API calls to check before/after state:**
-   ```bash
-   # BEFORE: Record current state
-   BEFORE=$(curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/credits | jq '.credits')
-   echo "Credits BEFORE: $BEFORE"
-
-   # Perform the action...
-
-   # AFTER: Record new state and compare
-   AFTER=$(curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/credits | jq '.credits')
-   echo "Credits AFTER: $AFTER"
-   echo "Delta: $(( BEFORE - AFTER ))"
-   ```
-
-3. **Take screenshots BEFORE and AFTER state changes** — the UI must reflect the backend state change
-
-4. **Never rely on mocked/injected browser state** — always use real backend state. Do NOT use `agent-browser eval` to fake UI state. The backend must be the source of truth.
-
-5. **Use direct DB queries when needed:**
-   ```bash
-   # Query via Supabase's PostgREST or docker exec into the DB
-   docker exec supabase-db psql -U supabase_admin -d postgres -c "SELECT credits FROM user_credits WHERE user_id = '...';"
-   ```
-
-6. **After every API test, verify the state change actually persisted:**
-   ```bash
-   # Example: After a credits purchase, verify DB matches API
-   API_CREDITS=$(curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/credits | jq '.credits')
-   DB_CREDITS=$(docker exec supabase-db psql -U supabase_admin -d postgres -t -c "SELECT credits FROM user_credits WHERE user_id = '...';" | tr -d ' ')
-   [ "$API_CREDITS" = "$DB_CREDITS" ] && echo "CONSISTENT" || echo "MISMATCH: API=$API_CREDITS DB=$DB_CREDITS"
-   ```
-
-## Arguments
-
-- `$ARGUMENTS` — worktree path (e.g. `$REPO_ROOT`) or PR number
-- If `--fix` flag is present, auto-fix bugs found and push fixes (like pr-address loop)
-
-## Step 0: Resolve the target
-
-```bash
-# If argument is a PR number, find its worktree
-gh pr view {N} --json headRefName --jq '.headRefName'
-# If argument is a path, use it directly
-```
-
-Determine:
-- `REPO_ROOT` — the root repo directory: `git -C "$WORKTREE_PATH" worktree list | head -1 | awk '{print $1}'` (or `git rev-parse --show-toplevel` if not a worktree)
-- `WORKTREE_PATH` — the worktree directory
-- `PLATFORM_DIR` — `$WORKTREE_PATH/autogpt_platform`
-- `BACKEND_DIR` — `$PLATFORM_DIR/backend`
-- `FRONTEND_DIR` — `$PLATFORM_DIR/frontend`
-- `PR_NUMBER` — the PR number (from `gh pr list --head $(git branch --show-current)`)
-- `PR_TITLE` — the PR title, slugified (e.g. "Add copilot permissions" → "add-copilot-permissions")
-- `RESULTS_DIR` — `$REPO_ROOT/test-results/PR-{PR_NUMBER}-{slugified-title}`
-
-Create the results directory:
-```bash
-PR_NUMBER=$(cd $WORKTREE_PATH && gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT --json number --jq '.[0].number')
-PR_TITLE=$(cd $WORKTREE_PATH && gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT --json title --jq '.[0].title' | tr '[:upper:]' '[:lower:]' | sed 's/[^a-z0-9]/-/g' | sed 's/--*/-/g' | sed 's/^-//;s/-$//' | head -c 50)
-RESULTS_DIR="$REPO_ROOT/test-results/PR-${PR_NUMBER}-${PR_TITLE}"
-mkdir -p $RESULTS_DIR
-```
-
-**Test user credentials** (for logging into the UI or verifying results manually):
-- Email: `test@test.com`
-- Password: `testtest123`
-
-## Step 1: Understand the PR
-
-Before testing, understand what changed:
-
-```bash
-cd $WORKTREE_PATH
-
-# Read PR description to understand the WHY
-gh pr view {N} --json body --jq '.body'
-
-git log --oneline dev..HEAD | head -20
-git diff dev --stat
-```
-
-Read the PR description (Why / What / How) and changed files to understand:
-0. **Why** does this PR exist? What problem does it solve?
-1. **What** feature/fix does this PR implement?
-2. **How** does it work? What's the approach?
-3. What components are affected? (backend, frontend, copilot, executor, etc.)
-4. What are the key user-facing behaviors to test?
-
-## Step 2: Write test scenarios
-
-Based on the PR analysis, write a test plan to `$RESULTS_DIR/test-plan.md`:
-
-```markdown
-# Test Plan: PR #{N} — {title}
-
-## Scenarios
-1. [Scenario name] — [what to verify]
-2. ...
-
-## API Tests (if applicable)
-1. [Endpoint] — [expected behavior]
-   - Before state: [what to check before]
-   - After state: [what to verify changed]
-
-## UI Tests (if applicable)
-1. [Page/component] — [interaction to test]
-   - Screenshot before: [what to capture]
-   - Screenshot after: [what to capture]
-
-## Negative Tests (REQUIRED — at least one per feature)
-1. [What should NOT happen] — [how to trigger it]
-   - Expected error: [what error message/code]
-   - State unchanged: [what to verify did NOT change]
-```
-
-**Be critical** — include edge cases, error paths, and security checks. Every scenario MUST specify what screenshots to take and what state to verify.
-
-## Step 3: Environment setup
-
-### 3a. Copy .env files from the root worktree
-
-The root worktree (`$REPO_ROOT`) has the canonical `.env` files with all API keys. Copy them to the target worktree:
-
-```bash
-# CRITICAL: .env files are NOT checked into git. They must be copied manually.
-cp $REPO_ROOT/autogpt_platform/.env $PLATFORM_DIR/.env
-cp $REPO_ROOT/autogpt_platform/backend/.env $BACKEND_DIR/.env
-cp $REPO_ROOT/autogpt_platform/frontend/.env $FRONTEND_DIR/.env
-```
-
-### 3b. Configure copilot authentication
-
-The copilot needs an LLM API to function. Two approaches (try subscription first):
-
-#### Option 1: Subscription mode (preferred — uses your Claude Max/Pro subscription)
-
-The `claude_agent_sdk` Python package **bundles its own Claude CLI binary** — no need to install `@anthropic-ai/claude-code` via npm. The backend auto-provisions credentials from environment variables on startup.
-
-Run the helper script to extract tokens from your host and auto-update `backend/.env` (works on macOS, Linux, and Windows/WSL):
-
-```bash
-# Extracts OAuth tokens and writes CLAUDE_CODE_OAUTH_TOKEN + CLAUDE_CODE_REFRESH_TOKEN into .env
-bash $BACKEND_DIR/scripts/refresh_claude_token.sh --env-file $BACKEND_DIR/.env
-```
-
-**How it works:** The script reads the OAuth token from:
-- **macOS**: system keychain (`"Claude Code-credentials"`)
-- **Linux/WSL**: `~/.claude/.credentials.json`
-- **Windows**: `%APPDATA%/claude/.credentials.json`
-
-It sets `CLAUDE_CODE_OAUTH_TOKEN`, `CLAUDE_CODE_REFRESH_TOKEN`, and `CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=true` in the `.env` file. On container startup, the backend auto-provisions `~/.claude/.credentials.json` inside the container from these env vars. The SDK's bundled CLI then authenticates using that file. No `claude login`, no npm install needed.
-
-**Note:** The OAuth token expires (~24h). If copilot returns auth errors, re-run the script and restart: `$BACKEND_DIR/scripts/refresh_claude_token.sh --env-file $BACKEND_DIR/.env && docker compose up -d copilot_executor`
-
-#### Option 2: OpenRouter API key mode (fallback)
-
-If subscription mode doesn't work, switch to API key mode using OpenRouter:
-
-```bash
-# In $BACKEND_DIR/.env, ensure these are set:
-CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=false
-CHAT_API_KEY=<value of OPEN_ROUTER_API_KEY from the same .env>
-CHAT_BASE_URL=https://openrouter.ai/api/v1
-CHAT_USE_CLAUDE_AGENT_SDK=true
-```
-
-Use `sed` to update these values:
-```bash
-ORKEY=$(grep "^OPEN_ROUTER_API_KEY=" $BACKEND_DIR/.env | cut -d= -f2)
-[ -n "$ORKEY" ] || { echo "ERROR: OPEN_ROUTER_API_KEY is missing in $BACKEND_DIR/.env"; exit 1; }
-perl -i -pe 's/CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=true/CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=false/' $BACKEND_DIR/.env
-# Add or update CHAT_API_KEY and CHAT_BASE_URL
-grep -q "^CHAT_API_KEY=" $BACKEND_DIR/.env && perl -i -pe "s|^CHAT_API_KEY=.*|CHAT_API_KEY=$ORKEY|" $BACKEND_DIR/.env || echo "CHAT_API_KEY=$ORKEY" >> $BACKEND_DIR/.env
-grep -q "^CHAT_BASE_URL=" $BACKEND_DIR/.env && perl -i -pe 's|^CHAT_BASE_URL=.*|CHAT_BASE_URL=https://openrouter.ai/api/v1|' $BACKEND_DIR/.env || echo "CHAT_BASE_URL=https://openrouter.ai/api/v1" >> $BACKEND_DIR/.env
-```
-
-### 3c. Stop conflicting containers
-
-```bash
-# Stop any running app containers (keep infra: supabase, redis, rabbitmq, clamav)
-docker ps --format "{{.Names}}" | grep -E "rest_server|executor|copilot|websocket|database_manager|scheduler|notification|frontend|migrate" | while read name; do
-  docker stop "$name" 2>/dev/null
-done
-```
-
-### 3e. Build and start
-
-```bash
-cd $PLATFORM_DIR && docker compose build --no-cache 2>&1 | tail -20
-if [ ${PIPESTATUS[0]} -ne 0 ]; then echo "ERROR: Docker build failed"; exit 1; fi
-
-cd $PLATFORM_DIR && docker compose up -d 2>&1 | tail -20
-if [ ${PIPESTATUS[0]} -ne 0 ]; then echo "ERROR: Docker compose up failed"; exit 1; fi
-```
-
-**Note:** If the container appears to be running old code (e.g. missing PR changes), use `docker compose build --no-cache` to force a full rebuild. Docker BuildKit may sometimes reuse cached `COPY` layers from a previous build on a different branch.
-
-**Expected time: 3-8 minutes** for build, 5-10 minutes with `--no-cache`.
-
-### 3f. Wait for services to be ready
-
-```bash
-# Poll until backend and frontend respond
-for i in $(seq 1 60); do
-  BACKEND=$(curl -s -o /dev/null -w "%{http_code}" http://localhost:8006/docs 2>/dev/null)
-  FRONTEND=$(curl -s -o /dev/null -w "%{http_code}" http://localhost:3000 2>/dev/null)
-  if [ "$BACKEND" = "200" ] && [ "$FRONTEND" = "200" ]; then
-    echo "Services ready"
-    break
-  fi
-  sleep 5
-done
-```
-
-
-### 3h. Create test user and get auth token
-
-```bash
-ANON_KEY=$(grep "NEXT_PUBLIC_SUPABASE_ANON_KEY=" $FRONTEND_DIR/.env | sed 's/.*NEXT_PUBLIC_SUPABASE_ANON_KEY=//' | tr -d '[:space:]')
-
-# Signup (idempotent — returns "User already registered" if exists)
-RESULT=$(curl -s -X POST 'http://localhost:8000/auth/v1/signup' \
-  -H "apikey: $ANON_KEY" \
-  -H 'Content-Type: application/json' \
-  -d '{"email":"test@test.com","password":"testtest123"}')
-
-# If "Database error finding user", restart supabase-auth and retry
-if echo "$RESULT" | grep -q "Database error"; then
-  docker restart supabase-auth && sleep 5
-  curl -s -X POST 'http://localhost:8000/auth/v1/signup' \
-    -H "apikey: $ANON_KEY" \
-    -H 'Content-Type: application/json' \
-    -d '{"email":"test@test.com","password":"testtest123"}'
-fi
-
-# Get auth token
-TOKEN=$(curl -s -X POST 'http://localhost:8000/auth/v1/token?grant_type=password' \
-  -H "apikey: $ANON_KEY" \
-  -H 'Content-Type: application/json' \
-  -d '{"email":"test@test.com","password":"testtest123"}' | jq -r '.access_token // ""')
-```
-
-**Use this token for ALL API calls:**
-```bash
-curl -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/...
-```
-
-## Step 4: Run tests
-
-### Service ports reference
-
-| Service | Port | URL |
-|---------|------|-----|
-| Frontend | 3000 | http://localhost:3000 |
-| Backend REST | 8006 | http://localhost:8006 |
-| Supabase Auth (via Kong) | 8000 | http://localhost:8000 |
-| Executor | 8002 | http://localhost:8002 |
-| Copilot Executor | 8008 | http://localhost:8008 |
-| WebSocket | 8001 | http://localhost:8001 |
-| Database Manager | 8005 | http://localhost:8005 |
-| Redis | 6379 | localhost:6379 |
-| RabbitMQ | 5672 | localhost:5672 |
-
-### API testing
-
-Use `curl` with the auth token for backend API tests. **For EVERY API call that changes state, record before/after values:**
-
-```bash
-# Example: List agents
-curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/graphs | jq . | head -20
-
-# Example: Create an agent
-curl -s -X POST http://localhost:8006/api/graphs \
-  -H "Authorization: Bearer $TOKEN" \
-  -H 'Content-Type: application/json' \
-  -d '{...}' | jq .
-
-# Example: Run an agent
-curl -s -X POST "http://localhost:8006/api/graphs/{graph_id}/execute" \
-  -H "Authorization: Bearer $TOKEN" \
-  -H 'Content-Type: application/json' \
-  -d '{"data": {...}}'
-
-# Example: Get execution results
-curl -s -H "Authorization: Bearer $TOKEN" \
-  "http://localhost:8006/api/graphs/{graph_id}/executions/{exec_id}" | jq .
-```
-
-**State verification pattern (use for EVERY state-changing API call):**
-```bash
-# 1. Record BEFORE state
-BEFORE_STATE=$(curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/{resource} | jq '{relevant_fields}')
-echo "BEFORE: $BEFORE_STATE"
-
-# 2. Perform the action
-ACTION_RESULT=$(curl -s -X POST ... | jq .)
-echo "ACTION RESULT: $ACTION_RESULT"
-
-# 3. Record AFTER state
-AFTER_STATE=$(curl -s -H "Authorization: Bearer $TOKEN" http://localhost:8006/api/{resource} | jq '{relevant_fields}')
-echo "AFTER: $AFTER_STATE"
-
-# 4. Log the comparison
-echo "=== STATE CHANGE VERIFICATION ==="
-echo "Before: $BEFORE_STATE"
-echo "After: $AFTER_STATE"
-echo "Expected change: {describe what should have changed}"
-```
-
-### Browser testing with agent-browser
-
-```bash
-# Close any existing session
-agent-browser close 2>/dev/null || true
-
-# Use --session-name to persist cookies across navigations
-# This means login only needs to happen once per test session
-agent-browser --session-name pr-test open 'http://localhost:3000/login' --timeout 15000
-
-# Get interactive elements
-agent-browser --session-name pr-test snapshot | grep "textbox\|button"
-
-# Login
-agent-browser --session-name pr-test fill {email_ref} "test@test.com"
-agent-browser --session-name pr-test fill {password_ref} "testtest123"
-agent-browser --session-name pr-test click {login_button_ref}
-sleep 5
-
-# Dismiss cookie banner if present
-agent-browser --session-name pr-test click 'text=Accept All' 2>/dev/null || true
-
-# Navigate — cookies are preserved so login persists
-agent-browser --session-name pr-test open 'http://localhost:3000/copilot' --timeout 10000
-
-# Take screenshot
-agent-browser --session-name pr-test screenshot $RESULTS_DIR/01-page.png
-
-# Interact with elements
-agent-browser --session-name pr-test fill {ref} "text"
-agent-browser --session-name pr-test press "Enter"
-agent-browser --session-name pr-test click {ref}
-agent-browser --session-name pr-test click 'text=Button Text'
-
-# Read page content
-agent-browser --session-name pr-test snapshot | grep "text:"
-```
-
-**Key pages:**
-- `/copilot` — CoPilot chat (for testing copilot features)
-- `/build` — Agent builder (for testing block/node features)
-- `/build?flowID={id}` — Specific agent in builder
-- `/library` — Agent library (for testing listing/import features)
-- `/library/agents/{id}` — Agent detail with run history
-- `/marketplace` — Marketplace
-
-### Checking logs
-
-```bash
-# Backend REST server
-docker logs autogpt_platform-rest_server-1 2>&1 | tail -30
-
-# Executor (runs agent graphs)
-docker logs autogpt_platform-executor-1 2>&1 | tail -30
-
-# Copilot executor (runs copilot chat sessions)
-docker logs autogpt_platform-copilot_executor-1 2>&1 | tail -30
-
-# Frontend
-docker logs autogpt_platform-frontend-1 2>&1 | tail -30
-
-# Filter for errors
-docker logs autogpt_platform-executor-1 2>&1 | grep -i "error\|exception\|traceback" | tail -20
-```
-
-### Copilot chat testing
-
-The copilot uses SSE streaming. To test via API:
-
-```bash
-# Create a session
-SESSION_ID=$(curl -s -X POST 'http://localhost:8006/api/chat/sessions' \
-  -H "Authorization: Bearer $TOKEN" \
-  -H 'Content-Type: application/json' \
-  -d '{}' | jq -r '.id // .session_id // ""')
-
-# Stream a message (SSE - will stream chunks)
-curl -N -X POST "http://localhost:8006/api/chat/sessions/$SESSION_ID/stream" \
-  -H "Authorization: Bearer $TOKEN" \
-  -H 'Content-Type: application/json' \
-  -d '{"message": "Hello, what can you help me with?"}' \
-  --max-time 60 2>/dev/null | head -50
-```
-
-Or test via browser (preferred for UI verification):
-```bash
-agent-browser --session-name pr-test open 'http://localhost:3000/copilot' --timeout 10000
-# ... fill chat input and press Enter, wait 20-30s for response
-```
-
-## Step 5: Record results and take screenshots
-
-**Take a screenshot at EVERY significant test step** — before and after interactions, on success, and on failure. This is NON-NEGOTIABLE.
-
-**Required screenshot pattern for each test scenario:**
-```bash
-# BEFORE the action
-agent-browser --session-name pr-test screenshot $RESULTS_DIR/{NN}-{scenario}-before.png
-
-# Perform the action...
-
-# AFTER the action
-agent-browser --session-name pr-test screenshot $RESULTS_DIR/{NN}-{scenario}-after.png
-```
-
-**Naming convention:**
-```bash
-# Examples:
-# $RESULTS_DIR/01-login-page-before.png
-# $RESULTS_DIR/02-login-page-after.png
-# $RESULTS_DIR/03-credits-page-before.png
-# $RESULTS_DIR/04-credits-purchase-after.png
-# $RESULTS_DIR/05-negative-insufficient-credits.png
-# $RESULTS_DIR/06-error-state.png
-```
-
-**Minimum requirements:**
-- At least TWO screenshots per test scenario (before + after)
-- At least ONE screenshot for each negative test case showing the error state
-- If a test fails, screenshot the failure state AND any error logs visible in the UI
-
-## Step 6: Show results to user with screenshots
-
-**CRITICAL: After all tests complete, you MUST show every screenshot to the user using the Read tool, with an explanation of what each screenshot shows.** This is the most important part of the test report — the user needs to visually verify the results.
-
-For each screenshot:
-1. Use the `Read` tool to display the PNG file (Claude can read images)
-2. Write a 1-2 sentence explanation below it describing:
-   - What page/state is being shown
-   - What the screenshot proves (which test scenario it validates)
-   - Any notable details visible in the UI
-
-Format the output like this:
-
-```markdown
-### Screenshot 1: {descriptive title}
-[Read the PNG file here]
-
-**What it shows:** {1-2 sentence explanation of what this screenshot proves}
-
----
-```
-
-After showing all screenshots, output a **detailed** summary table:
-
-| # | Scenario | Result | API Evidence | Screenshot Evidence |
-|---|----------|--------|-------------|-------------------|
-| 1 | {name} | PASS/FAIL | Before: X, After: Y | 01-before.png, 02-after.png |
-| 2 | ... | ... | ... | ... |
-
-**IMPORTANT:** As you show each screenshot and record test results, persist them in shell variables for Step 7:
-
-```bash
-# Build these variables during Step 6 — they are required by Step 7's script
-# NOTE: declare -A requires Bash 4.0+. This is standard on modern systems (macOS ships zsh
-# but Homebrew bash is 5.x; Linux typically has bash 5.x). If running on Bash <4, use a
-# plain variable with a lookup function instead.
-declare -A SCREENSHOT_EXPLANATIONS=(
-  ["01-login-page.png"]="Shows the login page loaded successfully with SSO options visible."
-  ["02-builder-with-block.png"]="The builder canvas displays the newly added block connected to the trigger."
-  # ... one entry per screenshot, using the same explanations you showed the user above
-)
-
-TEST_RESULTS_TABLE="| 1 | Login flow | PASS | N/A | 01-login-before.png, 02-login-after.png |
-| 2 | Credits purchase | PASS | Before: 100, After: 95 | 03-credits-before.png, 04-credits-after.png |
-| 3 | Insufficient credits (negative) | PASS | Credits: 0, rejected | 05-insufficient-credits-error.png |"
-# ... one row per test scenario with actual results
-```
-
-## Step 7: Post test report as PR comment with screenshots
-
-Upload screenshots to the PR using the GitHub Git API (no local git operations — safe for worktrees), then post a comment with inline images and per-screenshot explanations.
-
-**This step is MANDATORY. Every test run MUST post a PR comment with screenshots. No exceptions.**
-
-```bash
-# Upload screenshots via GitHub Git API (creates blobs, tree, commit, and ref remotely)
-REPO="Significant-Gravitas/AutoGPT"
-SCREENSHOTS_BRANCH="test-screenshots/pr-${PR_NUMBER}"
-SCREENSHOTS_DIR="test-screenshots/PR-${PR_NUMBER}"
-
-# Step 1: Create blobs for each screenshot and build tree JSON
-# Retry each blob upload up to 3 times. If still failing, list them at end of report.
-shopt -s nullglob
-SCREENSHOT_FILES=("$RESULTS_DIR"/*.png)
-if [ ${#SCREENSHOT_FILES[@]} -eq 0 ]; then
-  echo "ERROR: No screenshots found in $RESULTS_DIR. Test run is incomplete."
-  exit 1
-fi
-TREE_JSON='['
-FIRST=true
-FAILED_UPLOADS=()
-for img in "${SCREENSHOT_FILES[@]}"; do
-  BASENAME=$(basename "$img")
-  B64=$(base64 < "$img")
-  BLOB_SHA=""
-  for attempt in 1 2 3; do
-    BLOB_SHA=$(gh api "repos/${REPO}/git/blobs" -f content="$B64" -f encoding="base64" --jq '.sha' 2>/dev/null || true)
-    [ -n "$BLOB_SHA" ] && break
-    sleep 1
-  done
-  if [ -z "$BLOB_SHA" ]; then
-    FAILED_UPLOADS+=("$img")
-    continue
-  fi
-  if [ "$FIRST" = true ]; then FIRST=false; else TREE_JSON+=','; fi
-  TREE_JSON+="{\"path\":\"${SCREENSHOTS_DIR}/${BASENAME}\",\"mode\":\"100644\",\"type\":\"blob\",\"sha\":\"${BLOB_SHA}\"}"
-done
-TREE_JSON+=']'
-
-# Step 2: Create tree, commit, and branch ref
-TREE_SHA=$(echo "$TREE_JSON" | jq -c '{tree: .}' | gh api "repos/${REPO}/git/trees" --input - --jq '.sha')
-COMMIT_SHA=$(gh api "repos/${REPO}/git/commits" \
-  -f message="test: add E2E test screenshots for PR #${PR_NUMBER}" \
-  -f tree="$TREE_SHA" \
-  --jq '.sha')
-gh api "repos/${REPO}/git/refs" \
-  -f ref="refs/heads/${SCREENSHOTS_BRANCH}" \
-  -f sha="$COMMIT_SHA" 2>/dev/null \
-  || gh api "repos/${REPO}/git/refs/heads/${SCREENSHOTS_BRANCH}" \
-    -X PATCH -f sha="$COMMIT_SHA" -f force=true
-```
-
-Then post the comment with **inline images AND explanations for each screenshot**:
-
-```bash
-REPO_URL="https://raw.githubusercontent.com/${REPO}/${SCREENSHOTS_BRANCH}"
-
-# Build image markdown using uploaded image URLs; skip FAILED_UPLOADS (listed separately)
-
-IMAGE_MARKDOWN=""
-for img in "${SCREENSHOT_FILES[@]}"; do
-  BASENAME=$(basename "$img")
-  TITLE=$(echo "${BASENAME%.png}" | sed 's/^[0-9]*-//' | sed 's/-/ /g' | awk '{for(i=1;i<=NF;i++) $i=toupper(substr($i,1,1)) tolower(substr($i,2))}1')
-  # Skip images that failed to upload — they will be listed at the end
-  IS_FAILED=false
-  for failed in "${FAILED_UPLOADS[@]}"; do
-    [ "$(basename "$failed")" = "$BASENAME" ] && IS_FAILED=true && break
-  done
-  if [ "$IS_FAILED" = true ]; then
-    continue
-  fi
-  EXPLANATION="${SCREENSHOT_EXPLANATIONS[$BASENAME]}"
-  if [ -z "$EXPLANATION" ]; then
-    echo "ERROR: Missing screenshot explanation for $BASENAME. Add it to SCREENSHOT_EXPLANATIONS in Step 6."
-    exit 1
-  fi
-  IMAGE_MARKDOWN="${IMAGE_MARKDOWN}
-### ${TITLE}
-![${BASENAME}](${REPO_URL}/${SCREENSHOTS_DIR}/${BASENAME})
-${EXPLANATION}
-"
-done
-
-# Write comment body to file to avoid shell interpretation issues with special characters
-COMMENT_FILE=$(mktemp)
-# If any uploads failed, append a section listing them with instructions
-FAILED_SECTION=""
-if [ ${#FAILED_UPLOADS[@]} -gt 0 ]; then
-  FAILED_SECTION="
-## ⚠️ Failed Screenshot Uploads
-The following screenshots could not be uploaded via the GitHub API after 3 retries.
-**To add them:** drag-and-drop or paste these files into a PR comment manually:
-"
-  for failed in "${FAILED_UPLOADS[@]}"; do
-    FAILED_SECTION="${FAILED_SECTION}
-- \`$(basename "$failed")\` (local path: \`$failed\`)"
-  done
-  FAILED_SECTION="${FAILED_SECTION}
-
-**Run status:** INCOMPLETE until the files above are manually attached and visible inline in the PR."
-fi
-
-cat > "$COMMENT_FILE" <<INNEREOF
-## E2E Test Report
-
-| # | Scenario | Result | API Evidence | Screenshot Evidence |
-|---|----------|--------|-------------|-------------------|
-${TEST_RESULTS_TABLE}
-
-${IMAGE_MARKDOWN}
-${FAILED_SECTION}
-INNEREOF
-
-gh api "repos/${REPO}/issues/$PR_NUMBER/comments" -F body=@"$COMMENT_FILE"
-rm -f "$COMMENT_FILE"
-```
-
-**The PR comment MUST include:**
-1. A summary table of all scenarios with PASS/FAIL and before/after API evidence
-2. Every successfully uploaded screenshot rendered inline; any failed uploads listed with manual attachment instructions
-3. A 1-2 sentence explanation below each screenshot describing what it proves
-
-This approach uses the GitHub Git API to create blobs, trees, commits, and refs entirely server-side. No local `git checkout` or `git push` — safe for worktrees and won't interfere with the PR branch.
-
-## Fix mode (--fix flag)
-
-When `--fix` is present, the standard is HIGHER. Do not just note issues — FIX them immediately.
-
-### Fix protocol for EVERY issue found (including UX issues):
-
-1. **Identify** the root cause in the code — read the relevant source files
-2. **Write a failing test first** (TDD): For backend bugs, write a test marked with `pytest.mark.xfail(reason="...")`. For frontend/Playwright bugs, write a test with `.fixme` annotation. Run it to confirm it fails as expected.
-3. **Screenshot** the broken state: `agent-browser screenshot $RESULTS_DIR/{NN}-broken-{description}.png`
-4. **Fix** the code in the worktree
-5. **Rebuild** ONLY the affected service (not the whole stack):
-   ```bash
-   cd $PLATFORM_DIR && docker compose up --build -d {service_name}
-   # e.g., docker compose up --build -d rest_server
-   # e.g., docker compose up --build -d frontend
-   ```
-6. **Wait** for the service to be ready (poll health endpoint)
-7. **Re-test** the same scenario
-8. **Screenshot** the fixed state: `agent-browser screenshot $RESULTS_DIR/{NN}-fixed-{description}.png`
-9. **Remove the xfail/fixme marker** from the test written in step 2, and verify it passes
-10. **Verify** the fix did not break other scenarios (run a quick smoke test)
-11. **Commit and push** immediately:
-   ```bash
-   cd $WORKTREE_PATH
-   git add -A
-   git commit -m "fix: {description of fix}"
-   git push
-   ```
-12. **Continue** to the next test scenario
-
-### Fix loop (like pr-address)
-
-```text
-test scenario → find issue (bug OR UX problem) → screenshot broken state
-→ fix code → rebuild affected service only → re-test → screenshot fixed state
-→ verify no regressions → commit + push
-→ repeat for next scenario
-→ after ALL scenarios pass, run full re-test to verify everything together
-```
-
-**Key differences from non-fix mode:**
-- UX issues count as bugs — fix them (bad alignment, confusing labels, missing loading states)
-- Every fix MUST have a before/after screenshot pair proving it works
-- Commit after EACH fix, not in a batch at the end
-- The final re-test must produce a clean set of all-passing screenshots
-
-## Known issues and workarounds
-
-### Problem: "Database error finding user" on signup
-**Cause:** Supabase auth service schema cache is stale after migration.
-**Fix:** `docker restart supabase-auth && sleep 5` then retry signup.
-
-### Problem: Copilot returns auth errors in subscription mode
-**Cause:** `CHAT_USE_CLAUDE_CODE_SUBSCRIPTION=true` but `CLAUDE_CODE_OAUTH_TOKEN` is not set or expired.
-**Fix:** Re-extract the OAuth token from macOS keychain (see step 3b, Option 1) and recreate the container (`docker compose up -d copilot_executor`). The backend auto-provisions `~/.claude/.credentials.json` from the env var on startup. No `npm install` or `claude login` needed — the SDK bundles its own CLI binary.
-
-### Problem: agent-browser can't find chromium
-**Cause:** The Dockerfile auto-provisions system chromium on all architectures (including ARM64). If your branch is behind `dev`, this may not be present yet.
-**Fix:** Check if chromium exists: `which chromium || which chromium-browser`. If missing, install it: `apt-get install -y chromium` and set `AGENT_BROWSER_EXECUTABLE_PATH=/usr/bin/chromium` in the container environment.
-
-### Problem: agent-browser selector matches multiple elements
-**Cause:** `text=X` matches all elements containing that text.
-**Fix:** Use `agent-browser snapshot` to get specific `ref=eNN` references, then use those: `agent-browser click eNN`.
-
-### Problem: Frontend shows cookie banner blocking interaction
-**Fix:** `agent-browser click 'text=Accept All'` before other interactions.
-
-### Problem: Container loses npm packages after rebuild
-**Cause:** `docker compose up --build` rebuilds the image, losing runtime installs.
-**Fix:** Add packages to the Dockerfile instead of installing at runtime.
-
-### Problem: Services not starting after `docker compose up`
-**Fix:** Wait and check health: `docker compose ps`. Common cause: migration hasn't finished. Check: `docker logs autogpt_platform-migrate-1 2>&1 | tail -5`. If supabase-db isn't healthy: `docker restart supabase-db && sleep 10`.
-
-### Problem: Docker uses cached layers with old code (PR changes not visible)
-**Cause:** `docker compose up --build` reuses cached `COPY` layers from previous builds. If the PR branch changes Python files but the previous build already cached that layer from `dev`, the container runs `dev` code.
-**Fix:** Always use `docker compose build --no-cache` for the first build of a PR branch. Subsequent rebuilds within the same branch can use `--build`.
-
-### Problem: `agent-browser open` loses login session
-**Cause:** Without session persistence, `agent-browser open` starts fresh.
-**Fix:** Use `--session-name pr-test` on ALL agent-browser commands. This auto-saves/restores cookies and localStorage across navigations. Alternatively, use `agent-browser eval "window.location.href = '...'"` to navigate within the same context.
-
-### Problem: Supabase auth returns "Database error querying schema"
-**Cause:** The database schema changed (migration ran) but supabase-auth has a stale schema cache.
-**Fix:** `docker restart supabase-db && sleep 10 && docker restart supabase-auth && sleep 8`. If user data was lost, re-signup.

.claude/skills/setup-repo/SKILL.md

@@ -1,195 +0,0 @@
----
-name: setup-repo
-description: Initialize a worktree-based repo layout for parallel development. Creates a main worktree, a reviews worktree for PR reviews, and N numbered work branches. Handles .env creation, dependency installation, and branchlet config. TRIGGER when user asks to set up the repo from scratch, initialize worktrees, bootstrap their dev environment, "setup repo", "setup worktrees", "initialize dev environment", "set up branches", or when a freshly cloned repo has no sibling worktrees.
-user-invocable: true
-args: "No arguments — interactive setup via prompts."
-metadata:
-  author: autogpt-team
-  version: "1.0.0"
----
-
-# Repository Setup
-
-This skill sets up a worktree-based development layout from a freshly cloned repo. It creates:
-- A **main** worktree (the primary checkout)
-- A **reviews** worktree (for PR reviews)
-- **N work branches** (branch1..branchN) for parallel development
-
-## Step 1: Identify the repo
-
-Determine the repo root and parent directory:
-
-```bash
-ROOT=$(git rev-parse --show-toplevel)
-REPO_NAME=$(basename "$ROOT")
-PARENT=$(dirname "$ROOT")
-```
-
-Detect if the repo is already inside a worktree layout by counting sibling worktrees (not just checking the directory name, which could be anything):
-
-```bash
-# Count worktrees that are siblings (live under $PARENT but aren't $ROOT itself)
-SIBLING_COUNT=$(git worktree list --porcelain 2>/dev/null | grep "^worktree " | grep -c "$PARENT/" || true)
-if [ "$SIBLING_COUNT" -gt 1 ]; then
-  echo "INFO: Existing worktree layout detected at $PARENT ($SIBLING_COUNT worktrees)"
-  # Use $ROOT as-is; skip renaming/restructuring
-else
-  echo "INFO: Fresh clone detected, proceeding with setup"
-fi
-```
-
-## Step 2: Ask the user questions
-
-Use AskUserQuestion to gather setup preferences:
-
-1. **How many parallel work branches do you need?** (Options: 4, 8, 16, or custom)
-   - These become `branch1` through `branchN`
-2. **Which branch should be the base?** (Options: origin/master, origin/dev, or custom)
-   - All work branches and reviews will start from this
-
-## Step 3: Fetch and set up branches
-
-```bash
-cd "$ROOT"
-git fetch origin
-
-# Create the reviews branch from base (skip if already exists)
-if git show-ref --verify --quiet refs/heads/reviews; then
-  echo "INFO: Branch 'reviews' already exists, skipping"
-else
-  git branch reviews <base-branch>
-fi
-
-# Create numbered work branches from base (skip if already exists)
-for i in $(seq 1 "$COUNT"); do
-  if git show-ref --verify --quiet "refs/heads/branch$i"; then
-    echo "INFO: Branch 'branch$i' already exists, skipping"
-  else
-    git branch "branch$i" <base-branch>
-  fi
-done
-```
-
-## Step 4: Create worktrees
-
-Create worktrees as siblings to the main checkout:
-
-```bash
-if [ -d "$PARENT/reviews" ]; then
-  echo "INFO: Worktree '$PARENT/reviews' already exists, skipping"
-else
-  git worktree add "$PARENT/reviews" reviews
-fi
-
-for i in $(seq 1 "$COUNT"); do
-  if [ -d "$PARENT/branch$i" ]; then
-    echo "INFO: Worktree '$PARENT/branch$i' already exists, skipping"
-  else
-    git worktree add "$PARENT/branch$i" "branch$i"
-  fi
-done
-```
-
-## Step 5: Set up environment files
-
-**Do NOT assume .env files exist.** For each worktree (including main if needed):
-
-1. Check if `.env` exists in the source worktree for each path
-2. If `.env` exists, copy it
-3. If only `.env.default` or `.env.example` exists, copy that as `.env`
-4. If neither exists, warn the user and list which env files are missing
-
-Env file locations to check (same as the `/worktree` skill — keep these in sync):
-- `autogpt_platform/.env`
-- `autogpt_platform/backend/.env`
-- `autogpt_platform/frontend/.env`
-
-> **Note:** This env copying logic intentionally mirrors the `/worktree` skill's approach. If you update the path list or fallback logic here, update `/worktree` as well.
-
-```bash
-SOURCE="$ROOT"
-WORKTREES="reviews"
-for i in $(seq 1 "$COUNT"); do WORKTREES="$WORKTREES branch$i"; done
-
-FOUND_ANY_ENV=0
-for wt in $WORKTREES; do
-  TARGET="$PARENT/$wt"
-  for envpath in autogpt_platform autogpt_platform/backend autogpt_platform/frontend; do
-    if [ -f "$SOURCE/$envpath/.env" ]; then
-      FOUND_ANY_ENV=1
-      cp "$SOURCE/$envpath/.env" "$TARGET/$envpath/.env"
-    elif [ -f "$SOURCE/$envpath/.env.default" ]; then
-      FOUND_ANY_ENV=1
-      cp "$SOURCE/$envpath/.env.default" "$TARGET/$envpath/.env"
-      echo "NOTE: $wt/$envpath/.env was created from .env.default — you may need to edit it"
-    elif [ -f "$SOURCE/$envpath/.env.example" ]; then
-      FOUND_ANY_ENV=1
-      cp "$SOURCE/$envpath/.env.example" "$TARGET/$envpath/.env"
-      echo "NOTE: $wt/$envpath/.env was created from .env.example — you may need to edit it"
-    else
-      echo "WARNING: No .env, .env.default, or .env.example found at $SOURCE/$envpath/"
-    fi
-  done
-done
-
-if [ "$FOUND_ANY_ENV" -eq 0 ]; then
-  echo "WARNING: No environment files or templates were found in the source worktree."
-  # Use AskUserQuestion to confirm: "Continue setup without env files?"
-  # If the user declines, stop here and let them set up .env files first.
-fi
-```
-
-## Step 6: Copy branchlet config
-
-Copy `.branchlet.json` from main to each worktree so branchlet can manage sub-worktrees:
-
-```bash
-if [ -f "$ROOT/.branchlet.json" ]; then
-  for wt in $WORKTREES; do
-    cp "$ROOT/.branchlet.json" "$PARENT/$wt/.branchlet.json"
-  done
-fi
-```
-
-## Step 7: Install dependencies
-
-Install deps in all worktrees. Run these sequentially per worktree:
-
-```bash
-for wt in $WORKTREES; do
-  TARGET="$PARENT/$wt"
-  echo "=== Installing deps for $wt ==="
-  (cd "$TARGET/autogpt_platform/autogpt_libs" && poetry install) &&
-  (cd "$TARGET/autogpt_platform/backend" && poetry install && poetry run prisma generate) &&
-  (cd "$TARGET/autogpt_platform/frontend" && pnpm install) &&
-  echo "=== Done: $wt ===" ||
-  echo "=== FAILED: $wt ==="
-done
-```
-
-This is slow. Run in background if possible and notify when complete.
-
-## Step 8: Verify and report
-
-After setup, verify and report to the user:
-
-```bash
-git worktree list
-```
-
-Summarize:
-- Number of worktrees created
-- Which env files were copied vs created from defaults vs missing
-- Any warnings or errors encountered
-
-## Final directory layout
-
-```
-parent/
-  main/              # Primary checkout (already exists)
-  reviews/           # PR review worktree
-  branch1/           # Work branch 1
-  branch2/           # Work branch 2
-  ...
-  branchN/           # Work branch N
-```

.github/PULL_REQUEST_TEMPLATE.md

@@ -1,12 +1,8 @@
-### Why / What / How
-
-<!-- Why: Why does this PR exist? What problem does it solve, or what's broken/missing without it? -->
-<!-- What: What does this PR change? Summarize the changes at a high level. -->
-<!-- How: How does it work? Describe the approach, key implementation details, or architecture decisions. -->
+<!-- Clearly explain the need for these changes: -->
 
 ### Changes 🏗️
 
-<!-- List the key changes. Keep it higher level than the diff but specific enough to highlight what's new/modified. -->
+<!-- Concisely describe all of the changes made in this pull request: -->
 
 ### Checklist 📋
 

.github/workflows/platform-backend-ci.yml

@@ -27,91 +27,10 @@ defaults:
     working-directory: autogpt_platform/backend
 
 jobs:
-  lint:
-    permissions:
-      contents: read
-    timeout-minutes: 10
-    runs-on: ubuntu-latest
-
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v6
-
-      - name: Set up Python 3.12
-        uses: actions/setup-python@v5
-        with:
-          python-version: "3.12"
-
-      - name: Set up Python dependency cache
-        uses: actions/cache@v5
-        with:
-          path: ~/.cache/pypoetry
-          key: poetry-${{ runner.os }}-py3.12-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
-
-      - name: Install Poetry
-        run: |
-          HEAD_POETRY_VERSION=$(python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
-          echo "Using Poetry version ${HEAD_POETRY_VERSION}"
-          curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
-
-      - name: Install Python dependencies
-        run: poetry install
-
-      - name: Run Linters
-        run: poetry run lint --skip-pyright
-
-    env:
-      CI: true
-      PLAIN_OUTPUT: True
-
-  type-check:
-    permissions:
-      contents: read
-    timeout-minutes: 10
-    strategy:
-      fail-fast: false
-      matrix:
-        python-version: ["3.11", "3.12", "3.13"]
-    runs-on: ubuntu-latest
-
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v6
-
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v5
-        with:
-          python-version: ${{ matrix.python-version }}
-
-      - name: Set up Python dependency cache
-        uses: actions/cache@v5
-        with:
-          path: ~/.cache/pypoetry
-          key: poetry-${{ runner.os }}-py${{ matrix.python-version }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
-
-      - name: Install Poetry
-        run: |
-          HEAD_POETRY_VERSION=$(python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
-          echo "Using Poetry version ${HEAD_POETRY_VERSION}"
-          curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
-
-      - name: Install Python dependencies
-        run: poetry install
-
-      - name: Generate Prisma Client
-        run: poetry run prisma generate && poetry run gen-prisma-stub
-
-      - name: Run Pyright
-        run: poetry run pyright --pythonversion ${{ matrix.python-version }}
-
-    env:
-      CI: true
-      PLAIN_OUTPUT: True
-
   test:
     permissions:
       contents: read
-    timeout-minutes: 15
+    timeout-minutes: 30
     strategy:
       fail-fast: false
       matrix:
@@ -179,9 +98,9 @@ jobs:
         uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
-          key: poetry-${{ runner.os }}-py${{ matrix.python-version }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
+          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
 
-      - name: Install Poetry
+      - name: Install Poetry (Unix)
         run: |
           # Extract Poetry version from backend/poetry.lock
           HEAD_POETRY_VERSION=$(python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
@@ -239,22 +158,22 @@ jobs:
           echo "Waiting for ClamAV daemon to start..."
           max_attempts=60
           attempt=0
-
+          
           until nc -z localhost 3310 || [ $attempt -eq $max_attempts ]; do
             echo "ClamAV is unavailable - sleeping (attempt $((attempt+1))/$max_attempts)"
             sleep 5
             attempt=$((attempt+1))
           done
-
+          
           if [ $attempt -eq $max_attempts ]; then
             echo "ClamAV failed to start after $((max_attempts*5)) seconds"
             echo "Checking ClamAV service logs..."
             docker logs $(docker ps -q --filter "ancestor=clamav/clamav-debian:latest") 2>&1 | tail -50 || echo "No ClamAV container found"
             exit 1
           fi
-
+          
           echo "ClamAV is ready!"
-
+          
           # Verify ClamAV is responsive
           echo "Testing ClamAV connection..."
           timeout 10 bash -c 'echo "PING" | nc localhost 3310' || {
@@ -269,13 +188,18 @@ jobs:
           DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
           DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}
 
-      - name: Run pytest
+      - id: lint
+        name: Run Linter
+        run: poetry run lint
+
+      - name: Run pytest with coverage
         run: |
           if [[ "${{ runner.debug }}" == "1" ]]; then
             poetry run pytest -s -vv -o log_cli=true -o log_cli_level=DEBUG
           else
             poetry run pytest -s -vv
           fi
+        if: success() || (failure() && steps.lint.outcome == 'failure')
         env:
           LOG_LEVEL: ${{ runner.debug && 'DEBUG' || 'INFO' }}
           DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
@@ -287,12 +211,6 @@ jobs:
           REDIS_PORT: "6379"
           ENCRYPTION_KEY: "dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw=" # DO NOT USE IN PRODUCTION!!
 
-      # - name: Upload coverage reports to Codecov
-      #   uses: codecov/codecov-action@v4
-      #   with:
-      #     token: ${{ secrets.CODECOV_TOKEN }}
-      #     flags: backend,${{ runner.os }}
-
     env:
       CI: true
       PLAIN_OUTPUT: True
@@ -306,3 +224,9 @@ jobs:
       # the backend service, docker composes, and examples
       RABBITMQ_DEFAULT_USER: "rabbitmq_user_default"
       RABBITMQ_DEFAULT_PASS: "k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7"
+
+      # - name: Upload coverage reports to Codecov
+      #   uses: codecov/codecov-action@v4
+      #   with:
+      #     token: ${{ secrets.CODECOV_TOKEN }}
+      #     flags: backend,${{ runner.os }}

.github/workflows/platform-fullstack-ci.yml

@@ -294,7 +294,7 @@ jobs:
         uses: actions/upload-artifact@v4
         with:
           name: playwright-report
-          path: autogpt_platform/frontend/playwright-report
+          path: playwright-report
           if-no-files-found: ignore
           retention-days: 3
 
@@ -303,7 +303,7 @@ jobs:
         uses: actions/upload-artifact@v4
         with:
           name: playwright-test-results
-          path: autogpt_platform/frontend/test-results
+          path: test-results
           if-no-files-found: ignore
           retention-days: 3
 

README.md

@@ -83,13 +83,13 @@ The AutoGPT frontend is where users interact with our powerful AI automation pla
 
    **Agent Builder:** For those who want to customize, our intuitive, low-code interface allows you to design and configure your own AI agents. 
    
-   **Workflow Management:** Build, modify, and optimize your automation workflows with ease. You build your agent by connecting blocks, where each block performs a single action.
+   **Workflow Management:** Build, modify, and optimize your automation workflows with ease. You build your agent by connecting blocks, where each block     performs a single action.
    
    **Deployment Controls:** Manage the lifecycle of your agents, from testing to production.
    
    **Ready-to-Use Agents:** Don't want to build? Simply select from our library of pre-configured agents and put them to work immediately.
    
-   **Agent Interaction:** Whether you've built your own or are using pre-configured agents, easily run and interact with them through our user-friendly interface.
+   **Agent Interaction:** Whether you've built your own or are using pre-configured agents, easily run and interact with them through our user-friendly      interface.
 
    **Monitoring and Analytics:** Keep track of your agents' performance and gain insights to continually improve your automation processes.
 

autogpt_platform/CLAUDE.md

@@ -53,40 +53,18 @@ AutoGPT Platform is a monorepo containing:
 ### Creating Pull Requests
 
 - Create the PR against the `dev` branch of the repository.
-- **Split PRs by concern** — each PR should have a single clear purpose. For example, "usage tracking" and "credit charging" should be separate PRs even if related. Combining multiple concerns makes it harder for reviewers to understand what belongs to what.
 - Ensure the branch name is descriptive (e.g., `feature/add-new-block`)
 - Use conventional commit messages (see below)
-- **Structure the PR description with Why / What / How** — Why: the motivation (what problem it solves, what's broken/missing without it); What: high-level summary of changes; How: approach, key implementation details, or architecture decisions. Reviewers need all three to judge whether the approach fits the problem.
 - Fill out the .github/PULL_REQUEST_TEMPLATE.md template as the PR description
-- Always use `--body-file` to pass PR body — avoids shell interpretation of backticks and special characters:
-  ```bash
-  PR_BODY=$(mktemp)
-  cat > "$PR_BODY" << 'PREOF'
-  ## Summary
-  - use `backticks` freely here
-  PREOF
-  gh pr create --title "..." --body-file "$PR_BODY" --base dev
-  rm "$PR_BODY"
-  ```
 - Run the github pre-commit hooks to ensure code quality.
 
-### Test-Driven Development (TDD)
-
-When fixing a bug or adding a feature, follow a test-first approach:
-
-1. **Write a failing test first** — create a test that reproduces the bug or validates the new behavior, marked with `@pytest.mark.xfail` (backend) or `.fixme` (Playwright). Run it to confirm it fails for the right reason.
-2. **Implement the fix/feature** — write the minimal code to make the test pass.
-3. **Remove the xfail marker** — once the test passes, remove the `xfail`/`.fixme` annotation and run the full test suite to confirm nothing else broke.
-
-This ensures every change is covered by a test and that the test actually validates the intended behavior.
-
 ### Reviewing/Revising Pull Requests
 
 Use `/pr-review` to review a PR or `/pr-address` to address comments.
 
 When fetching comments manually:
-- `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews --paginate` — top-level reviews
-- `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments --paginate` — inline review comments (always paginate to avoid missing comments beyond page 1)
+- `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews` — top-level reviews
+- `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments` — inline review comments
 - `gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments` — PR conversation comments
 
 ### Conventional Commits

autogpt_platform/autogpt_libs/poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand.
 
 [[package]]
 name = "annotated-doc"
@@ -67,7 +67,7 @@ description = "Backport of asyncio.Runner, a context manager that controls event
 optional = false
 python-versions = "<3.11,>=3.8"
 groups = ["dev"]
-markers = "python_version == \"3.10\""
+markers = "python_version < \"3.11\""
 files = [
     {file = "backports_asyncio_runner-1.2.0-py3-none-any.whl", hash = "sha256:0da0a936a8aeb554eccb426dc55af3ba63bcdc69fa1a600b5bb305413a4477b5"},
     {file = "backports_asyncio_runner-1.2.0.tar.gz", hash = "sha256:a5aa7b2b7d8f8bfcaa2b57313f70792df84e32a2a746f585213373f900b42162"},
@@ -541,7 +541,7 @@ description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 groups = ["main", "dev"]
-markers = "python_version == \"3.10\""
+markers = "python_version < \"3.11\""
 files = [
     {file = "exceptiongroup-1.3.0-py3-none-any.whl", hash = "sha256:4d111e6e0c13d0644cad6ddaa7ed0261a0b36971f6d23e7ec9b4b9097da78a10"},
     {file = "exceptiongroup-1.3.0.tar.gz", hash = "sha256:b241f5885f560bc56a59ee63ca4c6a8bfa46ae4ad651af316d4e81817bb9fd88"},
@@ -2181,14 +2181,14 @@ testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
 
 [[package]]
 name = "pytest-cov"
-version = "7.1.0"
+version = "7.0.0"
 description = "Pytest plugin for measuring coverage."
 optional = false
 python-versions = ">=3.9"
 groups = ["dev"]
 files = [
-    {file = "pytest_cov-7.1.0-py3-none-any.whl", hash = "sha256:a0461110b7865f9a271aa1b51e516c9a95de9d696734a2f71e3e78f46e1d4678"},
-    {file = "pytest_cov-7.1.0.tar.gz", hash = "sha256:30674f2b5f6351aa09702a9c8c364f6a01c27aae0c1366ae8016160d1efc56b2"},
+    {file = "pytest_cov-7.0.0-py3-none-any.whl", hash = "sha256:3b8e9558b16cc1479da72058bdecf8073661c7f57f7d3c5f22a1c23507f2d861"},
+    {file = "pytest_cov-7.0.0.tar.gz", hash = "sha256:33c97eda2e049a0c5298e91f519302a1334c26ac65c1a483d6206fd458361af1"},
 ]
 
 [package.dependencies]
@@ -2342,30 +2342,30 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "ruff"
-version = "0.15.7"
+version = "0.15.0"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 groups = ["dev"]
 files = [
-    {file = "ruff-0.15.7-py3-none-linux_armv6l.whl", hash = "sha256:a81cc5b6910fb7dfc7c32d20652e50fa05963f6e13ead3c5915c41ac5d16668e"},
-    {file = "ruff-0.15.7-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:722d165bd52403f3bdabc0ce9e41fc47070ac56d7a91b4e0d097b516a53a3477"},
-    {file = "ruff-0.15.7-py3-none-macosx_11_0_arm64.whl", hash = "sha256:7fbc2448094262552146cbe1b9643a92f66559d3761f1ad0656d4991491af49e"},
-    {file = "ruff-0.15.7-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6b39329b60eba44156d138275323cc726bbfbddcec3063da57caa8a8b1d50adf"},
-    {file = "ruff-0.15.7-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:87768c151808505f2bfc93ae44e5f9e7c8518943e5074f76ac21558ef5627c85"},
-    {file = "ruff-0.15.7-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:fb0511670002c6c529ec66c0e30641c976c8963de26a113f3a30456b702468b0"},
-    {file = "ruff-0.15.7-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e0d19644f801849229db8345180a71bee5407b429dd217f853ec515e968a6912"},
-    {file = "ruff-0.15.7-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4806d8e09ef5e84eb19ba833d0442f7e300b23fe3f0981cae159a248a10f0036"},
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-    {file = "ruff-0.15.7-py3-none-manylinux_2_31_riscv64.whl", hash = "sha256:1852ce241d2bc89e5dc823e03cff4ce73d816b5c6cdadd27dbfe7b03217d2a12"},
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-    {file = "ruff-0.15.7-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:b15e48602c9c1d9bdc504b472e90b90c97dc7d46c7028011ae67f3861ceba7b4"},
-    {file = "ruff-0.15.7-py3-none-musllinux_1_2_i686.whl", hash = "sha256:1b4705e0e85cedc74b0a23cf6a179dbb3df184cb227761979cc76c0440b5ab0d"},
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-    {file = "ruff-0.15.7-py3-none-win32.whl", hash = "sha256:6d39e2d3505b082323352f733599f28169d12e891f7dd407f2d4f54b4c2886de"},
-    {file = "ruff-0.15.7-py3-none-win_amd64.whl", hash = "sha256:4d53d712ddebcd7dace1bc395367aec12c057aacfe9adbb6d832302575f4d3a1"},
-    {file = "ruff-0.15.7-py3-none-win_arm64.whl", hash = "sha256:18e8d73f1c3fdf27931497972250340f92e8c861722161a9caeb89a58ead6ed2"},
-    {file = "ruff-0.15.7.tar.gz", hash = "sha256:04f1ae61fc20fe0b148617c324d9d009b5f63412c0b16474f3d5f1a1a665f7ac"},
+    {file = "ruff-0.15.0-py3-none-linux_armv6l.whl", hash = "sha256:aac4ebaa612a82b23d45964586f24ae9bc23ca101919f5590bdb368d74ad5455"},
+    {file = "ruff-0.15.0-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:dcd4be7cc75cfbbca24a98d04d0b9b36a270d0833241f776b788d59f4142b14d"},
+    {file = "ruff-0.15.0-py3-none-macosx_11_0_arm64.whl", hash = "sha256:d747e3319b2bce179c7c1eaad3d884dc0a199b5f4d5187620530adf9105268ce"},
+    {file = "ruff-0.15.0-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:650bd9c56ae03102c51a5e4b554d74d825ff3abe4db22b90fd32d816c2e90621"},
+    {file = "ruff-0.15.0-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a6664b7eac559e3048223a2da77769c2f92b43a6dfd4720cef42654299a599c9"},
+    {file = "ruff-0.15.0-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6f811f97b0f092b35320d1556f3353bf238763420ade5d9e62ebd2b73f2ff179"},
+    {file = "ruff-0.15.0-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:761ec0a66680fab6454236635a39abaf14198818c8cdf691e036f4bc0f406b2d"},
+    {file = "ruff-0.15.0-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:940f11c2604d317e797b289f4f9f3fa5555ffe4fb574b55ed006c3d9b6f0eb78"},
+    {file = "ruff-0.15.0-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bcbca3d40558789126da91d7ef9a7c87772ee107033db7191edefa34e2c7f1b4"},
+    {file = "ruff-0.15.0-py3-none-manylinux_2_31_riscv64.whl", hash = "sha256:9a121a96db1d75fa3eb39c4539e607f628920dd72ff1f7c5ee4f1b768ac62d6e"},
+    {file = "ruff-0.15.0-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:5298d518e493061f2eabd4abd067c7e4fb89e2f63291c94332e35631c07c3662"},
+    {file = "ruff-0.15.0-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:afb6e603d6375ff0d6b0cee563fa21ab570fd15e65c852cb24922cef25050cf1"},
+    {file = "ruff-0.15.0-py3-none-musllinux_1_2_i686.whl", hash = "sha256:77e515f6b15f828b94dc17d2b4ace334c9ddb7d9468c54b2f9ed2b9c1593ef16"},
+    {file = "ruff-0.15.0-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:6f6e80850a01eb13b3e42ee0ebdf6e4497151b48c35051aab51c101266d187a3"},
+    {file = "ruff-0.15.0-py3-none-win32.whl", hash = "sha256:238a717ef803e501b6d51e0bdd0d2c6e8513fe9eec14002445134d3907cd46c3"},
+    {file = "ruff-0.15.0-py3-none-win_amd64.whl", hash = "sha256:dd5e4d3301dc01de614da3cdffc33d4b1b96fb89e45721f1598e5532ccf78b18"},
+    {file = "ruff-0.15.0-py3-none-win_arm64.whl", hash = "sha256:c480d632cc0ca3f0727acac8b7d053542d9e114a462a145d0b00e7cd658c515a"},
+    {file = "ruff-0.15.0.tar.gz", hash = "sha256:6bdea47cdbea30d40f8f8d7d69c0854ba7c15420ec75a26f463290949d7f7e9a"},
 ]
 
 [[package]]
@@ -2564,7 +2564,7 @@ description = "A lil' TOML parser"
 optional = false
 python-versions = ">=3.8"
 groups = ["dev"]
-markers = "python_version == \"3.10\""
+markers = "python_version < \"3.11\""
 files = [
     {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"},
     {file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"},
@@ -2912,4 +2912,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<4.0"
-content-hash = "e0936a065565550afed18f6298b7e04e814b44100def7049f1a0d68662624a39"
+content-hash = "9619cae908ad38fa2c48016a58bcf4241f6f5793aa0e6cc140276e91c433cbbb"

autogpt_platform/autogpt_libs/pyproject.toml

@@ -26,8 +26,8 @@ pyright = "^1.1.408"
 pytest = "^8.4.1"
 pytest-asyncio = "^1.3.0"
 pytest-mock = "^3.15.1"
-pytest-cov = "^7.1.0"
-ruff = "^0.15.7"
+pytest-cov = "^7.0.0"
+ruff = "^0.15.0"
 
 [build-system]
 requires = ["poetry-core"]

autogpt_platform/backend/.env.default

@@ -37,6 +37,10 @@ JWT_VERIFY_KEY=your-super-secret-jwt-token-with-at-least-32-characters-long
 ENCRYPTION_KEY=dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw=
 UNSUBSCRIBE_SECRET_KEY=HlP8ivStJjmbf6NKi78m_3FnOogut0t5ckzjsIqeaio=
 
+## ===== SIGNUP / INVITE GATE ===== ##
+# Set to true to require an invite before users can sign up
+ENABLE_INVITE_GATE=false
+
 ## ===== IMPORTANT OPTIONAL CONFIGURATION ===== ##
 # Platform URLs (set these for webhooks and OAuth to work)
 PLATFORM_BASE_URL=http://localhost:8000
@@ -178,7 +182,6 @@ SMTP_USERNAME=
 SMTP_PASSWORD=
 
 # Business & Marketing Tools
-AGENTMAIL_API_KEY=
 APOLLO_API_KEY=
 ENRICHLAYER_API_KEY=
 AYRSHARE_API_KEY=

autogpt_platform/backend/CLAUDE.md

@@ -61,13 +61,12 @@ poetry run pytest path/to/test.py --snapshot-update
 ## Code Style
 
 - **Top-level imports only** — no local/inner imports (lazy imports only for heavy optional deps like `openpyxl`)
-- **Absolute imports** — use `from backend.module import ...` for cross-package imports. Single-dot relative (`from .sibling import ...`) is acceptable for sibling modules within the same package (e.g., blocks). Avoid double-dot relative imports (`from ..parent import ...`) — use the absolute path instead
 - **No duck typing** — no `hasattr`/`getattr`/`isinstance` for type dispatch; use typed interfaces/unions/protocols
 - **Pydantic models** over dataclass/namedtuple/dict for structured data
 - **No linter suppressors** — no `# type: ignore`, `# noqa`, `# pyright: ignore`; fix the type/code
 - **List comprehensions** over manual loop-and-append
 - **Early return** — guard clauses first, avoid deep nesting
-- **f-strings vs printf syntax in log statements** — Use `%s` for deferred interpolation in `debug` statements, f-strings elsewhere for readability: `logger.debug("Processing %s items", count)`, `logger.info(f"Processing {count} items")`
+- **Lazy `%s` logging** — `logger.info("Processing %s items", count)` not `logger.info(f"Processing {count} items")`
 - **Sanitize error paths** — `os.path.basename()` in error messages to avoid leaking directory structure
 - **TOCTOU awareness** — avoid check-then-act patterns for file access and credit charging
 - **`Security()` vs `Depends()`** — use `Security()` for auth deps to get proper OpenAPI security spec
@@ -76,7 +75,6 @@ poetry run pytest path/to/test.py --snapshot-update
 - **SSE protocol** — `data:` lines for frontend-parsed events (must match Zod schema), `: comment` lines for heartbeats/status
 - **File length** — keep files under ~300 lines; if a file grows beyond this, split by responsibility (e.g. extract helpers, models, or a sub-module into a new file). Never keep appending to a long file.
 - **Function length** — keep functions under ~40 lines; extract named helpers when a function grows longer. Long functions are a sign of mixed concerns, not complexity.
-- **Top-down ordering** — define the main/public function or class first, then the helpers it uses below. A reader should encounter high-level logic before implementation details.
 
 ## Testing Approach
 
@@ -86,30 +84,6 @@ poetry run pytest path/to/test.py --snapshot-update
 - After refactoring, update mock targets to match new module paths
 - Use `AsyncMock` for async functions (`from unittest.mock import AsyncMock`)
 
-### Test-Driven Development (TDD)
-
-When fixing a bug or adding a feature, write the test **before** the implementation:
-
-```python
-# 1. Write a failing test marked xfail
-@pytest.mark.xfail(reason="Bug #1234: widget crashes on empty input")
-def test_widget_handles_empty_input():
-    result = widget.process("")
-    assert result == Widget.EMPTY_RESULT
-
-# 2. Run it — confirm it fails (XFAIL)
-# poetry run pytest path/to/test.py::test_widget_handles_empty_input -xvs
-
-# 3. Implement the fix
-
-# 4. Remove xfail, run again — confirm it passes
-def test_widget_handles_empty_input():
-    result = widget.process("")
-    assert result == Widget.EMPTY_RESULT
-```
-
-This catches regressions and proves the fix actually works. **Every bug fix should include a test that would have caught it.**
-
 ## Database Schema
 
 Key models (defined in `schema.prisma`):

autogpt_platform/backend/Dockerfile

@@ -50,7 +50,7 @@ RUN poetry install --no-ansi --no-root
 # Generate Prisma client
 COPY autogpt_platform/backend/schema.prisma ./
 COPY autogpt_platform/backend/backend/data/partial_types.py ./backend/data/partial_types.py
-COPY autogpt_platform/backend/scripts/gen_prisma_types_stub.py ./scripts/
+COPY autogpt_platform/backend/gen_prisma_types_stub.py ./
 RUN poetry run prisma generate && poetry run gen-prisma-stub
 
 # =============================== DB MIGRATOR =============================== #
@@ -82,7 +82,7 @@ RUN pip3 install prisma>=0.15.0 --break-system-packages
 
 COPY autogpt_platform/backend/schema.prisma ./
 COPY autogpt_platform/backend/backend/data/partial_types.py ./backend/data/partial_types.py
-COPY autogpt_platform/backend/scripts/gen_prisma_types_stub.py ./scripts/
+COPY autogpt_platform/backend/gen_prisma_types_stub.py ./
 COPY autogpt_platform/backend/migrations ./migrations
 
 # ============================== BACKEND SERVER ============================== #
@@ -121,21 +121,19 @@ RUN ln -s ../lib/node_modules/npm/bin/npm-cli.js /usr/bin/npm \
     && ln -s ../lib/node_modules/npm/bin/npx-cli.js /usr/bin/npx
 COPY --from=builder /root/.cache/prisma-python/binaries /root/.cache/prisma-python/binaries
 
-# Install agent-browser (Copilot browser tool) using the system chromium package.
-# Chrome for Testing (the binary agent-browser downloads via `agent-browser install`)
-# has no ARM64 builds, so we use the distro-packaged chromium instead — verified to
-# work with agent-browser via Docker tests on arm64; amd64 is validated in CI.
-# Note: system chromium tracks the Debian package schedule rather than a pinned
-# Chrome for Testing release. If agent-browser requires a specific Chrome version,
-# verify compatibility against the chromium package version in the base image.
-RUN apt-get update \
-    && apt-get install -y --no-install-recommends chromium fonts-liberation \
+# Install agent-browser (Copilot browser tool) + Chromium runtime dependencies.
+# These are the runtime libraries Chromium/Playwright needs on Debian 13 (trixie).
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    libnss3 libnspr4 libatk1.0-0 libatk-bridge2.0-0 libcups2 libdrm2 \
+    libdbus-1-3 libxkbcommon0 libatspi2.0-0t64 libxcomposite1 libxdamage1 \
+    libxfixes3 libxrandr2 libgbm1 libasound2t64 libpango-1.0-0 libcairo2 \
+    libx11-6 libx11-xcb1 libxcb1 libxext6 libglib2.0-0t64 \
+    fonts-liberation libfontconfig1 \
     && rm -rf /var/lib/apt/lists/* \
     && npm install -g agent-browser \
+    && agent-browser install \
     && rm -rf /tmp/* /root/.npm
 
-ENV AGENT_BROWSER_EXECUTABLE_PATH=/usr/bin/chromium
-
 WORKDIR /app/autogpt_platform/backend
 
 # Copy only the .venv from builder (not the entire /app directory)

autogpt_platform/backend/backend/api/external/v1/integrations.py

@@ -18,22 +18,14 @@ from pydantic import BaseModel, Field, SecretStr
 
 from backend.api.external.middleware import require_permission
 from backend.api.features.integrations.models import get_all_provider_names
-from backend.api.features.integrations.router import (
-    CredentialsMetaResponse,
-    to_meta_response,
-)
 from backend.data.auth.base import APIAuthorizationInfo
 from backend.data.model import (
     APIKeyCredentials,
     Credentials,
     CredentialsType,
     HostScopedCredentials,
+    OAuth2Credentials,
     UserPasswordCredentials,
-    is_sdk_default,
-)
-from backend.integrations.credentials_store import (
-    is_system_credential,
-    provider_matches,
 )
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.integrations.oauth import CREDENTIALS_BY_PROVIDER, HANDLERS_BY_NAME
@@ -99,6 +91,18 @@ class OAuthCompleteResponse(BaseModel):
     )
 
 
+class CredentialSummary(BaseModel):
+    """Summary of a credential without sensitive data."""
+
+    id: str
+    provider: str
+    type: CredentialsType
+    title: Optional[str] = None
+    scopes: Optional[list[str]] = None
+    username: Optional[str] = None
+    host: Optional[str] = None
+
+
 class ProviderInfo(BaseModel):
     """Information about an integration provider."""
 
@@ -469,12 +473,12 @@ async def complete_oauth(
     )
 
 
-@integrations_router.get("/credentials", response_model=list[CredentialsMetaResponse])
+@integrations_router.get("/credentials", response_model=list[CredentialSummary])
 async def list_credentials(
     auth: APIAuthorizationInfo = Security(
         require_permission(APIKeyPermission.READ_INTEGRATIONS)
     ),
-) -> list[CredentialsMetaResponse]:
+) -> list[CredentialSummary]:
     """
     List all credentials for the authenticated user.
 
@@ -482,19 +486,28 @@ async def list_credentials(
     """
     credentials = await creds_manager.store.get_all_creds(auth.user_id)
     return [
-        to_meta_response(cred) for cred in credentials if not is_sdk_default(cred.id)
+        CredentialSummary(
+            id=cred.id,
+            provider=cred.provider,
+            type=cred.type,
+            title=cred.title,
+            scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
+            username=cred.username if isinstance(cred, OAuth2Credentials) else None,
+            host=cred.host if isinstance(cred, HostScopedCredentials) else None,
+        )
+        for cred in credentials
     ]
 
 
 @integrations_router.get(
-    "/{provider}/credentials", response_model=list[CredentialsMetaResponse]
+    "/{provider}/credentials", response_model=list[CredentialSummary]
 )
 async def list_credentials_by_provider(
     provider: Annotated[str, Path(title="The provider to list credentials for")],
     auth: APIAuthorizationInfo = Security(
         require_permission(APIKeyPermission.READ_INTEGRATIONS)
     ),
-) -> list[CredentialsMetaResponse]:
+) -> list[CredentialSummary]:
     """
     List credentials for a specific provider.
     """
@@ -502,7 +515,16 @@ async def list_credentials_by_provider(
         auth.user_id, provider
     )
     return [
-        to_meta_response(cred) for cred in credentials if not is_sdk_default(cred.id)
+        CredentialSummary(
+            id=cred.id,
+            provider=cred.provider,
+            type=cred.type,
+            title=cred.title,
+            scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
+            username=cred.username if isinstance(cred, OAuth2Credentials) else None,
+            host=cred.host if isinstance(cred, HostScopedCredentials) else None,
+        )
+        for cred in credentials
     ]
 
 
@@ -575,11 +597,11 @@ async def create_credential(
     # Store credentials
     try:
         await creds_manager.create(auth.user_id, credentials)
-    except Exception:
-        logger.exception("Failed to store credentials")
+    except Exception as e:
+        logger.error(f"Failed to store credentials: {e}")
         raise HTTPException(
             status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-            detail="Failed to store credentials",
+            detail=f"Failed to store credentials: {str(e)}",
         )
 
     logger.info(f"Created {request.type} credentials for provider {provider}")
@@ -617,23 +639,15 @@ async def delete_credential(
     use the main API's delete endpoint which handles webhook cleanup and
     token revocation.
     """
-    if is_sdk_default(cred_id):
-        raise HTTPException(
-            status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
-        )
-    if is_system_credential(cred_id):
-        raise HTTPException(
-            status_code=status.HTTP_403_FORBIDDEN,
-            detail="System-managed credentials cannot be deleted",
-        )
     creds = await creds_manager.store.get_creds_by_id(auth.user_id, cred_id)
     if not creds:
         raise HTTPException(
             status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
         )
-    if not provider_matches(creds.provider, provider):
+    if creds.provider != provider:
         raise HTTPException(
-            status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail="Credentials do not match the specified provider",
         )
 
     await creds_manager.delete(auth.user_id, cred_id)

autogpt_platform/backend/backend/api/features/admin/model.py

@@ -1,8 +1,17 @@
-from pydantic import BaseModel
+from __future__ import annotations
+
+from datetime import datetime
+from typing import TYPE_CHECKING, Any, Literal, Optional
+
+import prisma.enums
+from pydantic import BaseModel, EmailStr
 
 from backend.data.model import UserTransaction
 from backend.util.models import Pagination
 
+if TYPE_CHECKING:
+    from backend.data.invited_user import BulkInvitedUsersResult, InvitedUserRecord
+
 
 class UserHistoryResponse(BaseModel):
     """Response model for listings with version history"""
@@ -14,3 +23,70 @@ class UserHistoryResponse(BaseModel):
 class AddUserCreditsResponse(BaseModel):
     new_balance: int
     transaction_key: str
+
+
+class CreateInvitedUserRequest(BaseModel):
+    email: EmailStr
+    name: Optional[str] = None
+
+
+class InvitedUserResponse(BaseModel):
+    id: str
+    email: str
+    status: prisma.enums.InvitedUserStatus
+    auth_user_id: Optional[str] = None
+    name: Optional[str] = None
+    tally_understanding: Optional[dict[str, Any]] = None
+    tally_status: prisma.enums.TallyComputationStatus
+    tally_computed_at: Optional[datetime] = None
+    tally_error: Optional[str] = None
+    created_at: datetime
+    updated_at: datetime
+
+    @classmethod
+    def from_record(cls, record: InvitedUserRecord) -> InvitedUserResponse:
+        return cls.model_validate(record.model_dump())
+
+
+class InvitedUsersResponse(BaseModel):
+    invited_users: list[InvitedUserResponse]
+    pagination: Pagination
+
+
+class BulkInvitedUserRowResponse(BaseModel):
+    row_number: int
+    email: Optional[str] = None
+    name: Optional[str] = None
+    status: Literal["CREATED", "SKIPPED", "ERROR"]
+    message: str
+    invited_user: Optional[InvitedUserResponse] = None
+
+
+class BulkInvitedUsersResponse(BaseModel):
+    created_count: int
+    skipped_count: int
+    error_count: int
+    results: list[BulkInvitedUserRowResponse]
+
+    @classmethod
+    def from_result(cls, result: BulkInvitedUsersResult) -> BulkInvitedUsersResponse:
+        return cls(
+            created_count=result.created_count,
+            skipped_count=result.skipped_count,
+            error_count=result.error_count,
+            results=[
+                BulkInvitedUserRowResponse(
+                    row_number=row.row_number,
+                    email=row.email,
+                    name=row.name,
+                    status=row.status,
+                    message=row.message,
+                    invited_user=(
+                        InvitedUserResponse.from_record(row.invited_user)
+                        if row.invited_user is not None
+                        else None
+                    ),
+                )
+                for row in result.results
+            ],
+        )

autogpt_platform/backend/backend/api/features/admin/rate_limit_admin_routes.py

@@ -1,146 +0,0 @@
-"""Admin endpoints for checking and resetting user CoPilot rate limit usage."""
-
-import logging
-from typing import Optional
-
-from autogpt_libs.auth import get_user_id, requires_admin_user
-from fastapi import APIRouter, Body, HTTPException, Security
-from pydantic import BaseModel
-
-from backend.copilot.config import ChatConfig
-from backend.copilot.rate_limit import (
-    get_global_rate_limits,
-    get_usage_status,
-    reset_user_usage,
-)
-from backend.data.user import get_user_by_email, get_user_email_by_id
-
-logger = logging.getLogger(__name__)
-
-config = ChatConfig()
-
-router = APIRouter(
-    prefix="/admin",
-    tags=["copilot", "admin"],
-    dependencies=[Security(requires_admin_user)],
-)
-
-
-class UserRateLimitResponse(BaseModel):
-    user_id: str
-    user_email: Optional[str] = None
-    daily_token_limit: int
-    weekly_token_limit: int
-    daily_tokens_used: int
-    weekly_tokens_used: int
-
-
-async def _resolve_user_id(
-    user_id: Optional[str], email: Optional[str]
-) -> tuple[str, Optional[str]]:
-    """Resolve a user_id and email from the provided parameters.
-
-    Returns (user_id, email). Accepts either user_id or email; at least one
-    must be provided.  When both are provided, ``email`` takes precedence.
-    """
-    if email:
-        user = await get_user_by_email(email)
-        if not user:
-            raise HTTPException(
-                status_code=404, detail="No user found with the provided email."
-            )
-        return user.id, email
-
-    if not user_id:
-        raise HTTPException(
-            status_code=400,
-            detail="Either user_id or email query parameter is required.",
-        )
-
-    # We have a user_id; try to look up their email for display purposes.
-    # This is non-critical -- a failure should not block the response.
-    try:
-        resolved_email = await get_user_email_by_id(user_id)
-    except Exception:
-        logger.warning("Failed to resolve email for user %s", user_id, exc_info=True)
-        resolved_email = None
-    return user_id, resolved_email
-
-
-@router.get(
-    "/rate_limit",
-    response_model=UserRateLimitResponse,
-    summary="Get User Rate Limit",
-)
-async def get_user_rate_limit(
-    user_id: Optional[str] = None,
-    email: Optional[str] = None,
-    admin_user_id: str = Security(get_user_id),
-) -> UserRateLimitResponse:
-    """Get a user's current usage and effective rate limits. Admin-only.
-
-    Accepts either ``user_id`` or ``email`` as a query parameter.
-    When ``email`` is provided the user is looked up by email first.
-    """
-    resolved_id, resolved_email = await _resolve_user_id(user_id, email)
-
-    logger.info("Admin %s checking rate limit for user %s", admin_user_id, resolved_id)
-
-    daily_limit, weekly_limit = await get_global_rate_limits(
-        resolved_id, config.daily_token_limit, config.weekly_token_limit
-    )
-    usage = await get_usage_status(resolved_id, daily_limit, weekly_limit)
-
-    return UserRateLimitResponse(
-        user_id=resolved_id,
-        user_email=resolved_email,
-        daily_token_limit=daily_limit,
-        weekly_token_limit=weekly_limit,
-        daily_tokens_used=usage.daily.used,
-        weekly_tokens_used=usage.weekly.used,
-    )
-
-
-@router.post(
-    "/rate_limit/reset",
-    response_model=UserRateLimitResponse,
-    summary="Reset User Rate Limit Usage",
-)
-async def reset_user_rate_limit(
-    user_id: str = Body(embed=True),
-    reset_weekly: bool = Body(False, embed=True),
-    admin_user_id: str = Security(get_user_id),
-) -> UserRateLimitResponse:
-    """Reset a user's daily usage counter (and optionally weekly). Admin-only."""
-    logger.info(
-        "Admin %s resetting rate limit for user %s (reset_weekly=%s)",
-        admin_user_id,
-        user_id,
-        reset_weekly,
-    )
-
-    try:
-        await reset_user_usage(user_id, reset_weekly=reset_weekly)
-    except Exception as e:
-        logger.exception("Failed to reset user usage")
-        raise HTTPException(status_code=500, detail="Failed to reset usage") from e
-
-    daily_limit, weekly_limit = await get_global_rate_limits(
-        user_id, config.daily_token_limit, config.weekly_token_limit
-    )
-    usage = await get_usage_status(user_id, daily_limit, weekly_limit)
-
-    try:
-        resolved_email = await get_user_email_by_id(user_id)
-    except Exception:
-        logger.warning("Failed to resolve email for user %s", user_id, exc_info=True)
-        resolved_email = None
-
-    return UserRateLimitResponse(
-        user_id=user_id,
-        user_email=resolved_email,
-        daily_token_limit=daily_limit,
-        weekly_token_limit=weekly_limit,
-        daily_tokens_used=usage.daily.used,
-        weekly_tokens_used=usage.weekly.used,
-    )

autogpt_platform/backend/backend/api/features/admin/rate_limit_admin_routes_test.py

@@ -1,263 +0,0 @@
-import json
-from types import SimpleNamespace
-from unittest.mock import AsyncMock
-
-import fastapi
-import fastapi.testclient
-import pytest
-import pytest_mock
-from autogpt_libs.auth.jwt_utils import get_jwt_payload
-from pytest_snapshot.plugin import Snapshot
-
-from backend.copilot.rate_limit import CoPilotUsageStatus, UsageWindow
-
-from .rate_limit_admin_routes import router as rate_limit_admin_router
-
-app = fastapi.FastAPI()
-app.include_router(rate_limit_admin_router)
-
-client = fastapi.testclient.TestClient(app)
-
-_MOCK_MODULE = "backend.api.features.admin.rate_limit_admin_routes"
-
-_TARGET_EMAIL = "target@example.com"
-
-
-@pytest.fixture(autouse=True)
-def setup_app_admin_auth(mock_jwt_admin):
-    """Setup admin auth overrides for all tests in this module"""
-    app.dependency_overrides[get_jwt_payload] = mock_jwt_admin["get_jwt_payload"]
-    yield
-    app.dependency_overrides.clear()
-
-
-def _mock_usage_status(
-    daily_used: int = 500_000, weekly_used: int = 3_000_000
-) -> CoPilotUsageStatus:
-    from datetime import UTC, datetime, timedelta
-
-    now = datetime.now(UTC)
-    return CoPilotUsageStatus(
-        daily=UsageWindow(
-            used=daily_used, limit=2_500_000, resets_at=now + timedelta(hours=6)
-        ),
-        weekly=UsageWindow(
-            used=weekly_used, limit=12_500_000, resets_at=now + timedelta(days=3)
-        ),
-    )
-
-
-def _patch_rate_limit_deps(
-    mocker: pytest_mock.MockerFixture,
-    target_user_id: str,
-    daily_used: int = 500_000,
-    weekly_used: int = 3_000_000,
-):
-    """Patch the common rate-limit + user-lookup dependencies."""
-    mocker.patch(
-        f"{_MOCK_MODULE}.get_global_rate_limits",
-        new_callable=AsyncMock,
-        return_value=(2_500_000, 12_500_000),
-    )
-    mocker.patch(
-        f"{_MOCK_MODULE}.get_usage_status",
-        new_callable=AsyncMock,
-        return_value=_mock_usage_status(daily_used=daily_used, weekly_used=weekly_used),
-    )
-    mocker.patch(
-        f"{_MOCK_MODULE}.get_user_email_by_id",
-        new_callable=AsyncMock,
-        return_value=_TARGET_EMAIL,
-    )
-
-
-def test_get_rate_limit(
-    mocker: pytest_mock.MockerFixture,
-    configured_snapshot: Snapshot,
-    target_user_id: str,
-) -> None:
-    """Test getting rate limit and usage for a user."""
-    _patch_rate_limit_deps(mocker, target_user_id)
-
-    response = client.get("/admin/rate_limit", params={"user_id": target_user_id})
-
-    assert response.status_code == 200
-    data = response.json()
-    assert data["user_id"] == target_user_id
-    assert data["user_email"] == _TARGET_EMAIL
-    assert data["daily_token_limit"] == 2_500_000
-    assert data["weekly_token_limit"] == 12_500_000
-    assert data["daily_tokens_used"] == 500_000
-    assert data["weekly_tokens_used"] == 3_000_000
-
-    configured_snapshot.assert_match(
-        json.dumps(data, indent=2, sort_keys=True) + "\n",
-        "get_rate_limit",
-    )
-
-
-def test_get_rate_limit_by_email(
-    mocker: pytest_mock.MockerFixture,
-    target_user_id: str,
-) -> None:
-    """Test looking up rate limits via email instead of user_id."""
-    _patch_rate_limit_deps(mocker, target_user_id)
-
-    mock_user = SimpleNamespace(id=target_user_id, email=_TARGET_EMAIL)
-    mocker.patch(
-        f"{_MOCK_MODULE}.get_user_by_email",
-        new_callable=AsyncMock,
-        return_value=mock_user,
-    )
-
-    response = client.get("/admin/rate_limit", params={"email": _TARGET_EMAIL})
-
-    assert response.status_code == 200
-    data = response.json()
-    assert data["user_id"] == target_user_id
-    assert data["user_email"] == _TARGET_EMAIL
-    assert data["daily_token_limit"] == 2_500_000
-
-
-def test_get_rate_limit_by_email_not_found(
-    mocker: pytest_mock.MockerFixture,
-) -> None:
-    """Test that looking up a non-existent email returns 404."""
-    mocker.patch(
-        f"{_MOCK_MODULE}.get_user_by_email",
-        new_callable=AsyncMock,
-        return_value=None,
-    )
-
-    response = client.get("/admin/rate_limit", params={"email": "nobody@example.com"})
-
-    assert response.status_code == 404
-
-
-def test_get_rate_limit_no_params() -> None:
-    """Test that omitting both user_id and email returns 400."""
-    response = client.get("/admin/rate_limit")
-    assert response.status_code == 400
-
-
-def test_reset_user_usage_daily_only(
-    mocker: pytest_mock.MockerFixture,
-    configured_snapshot: Snapshot,
-    target_user_id: str,
-) -> None:
-    """Test resetting only daily usage (default behaviour)."""
-    mock_reset = mocker.patch(
-        f"{_MOCK_MODULE}.reset_user_usage",
-        new_callable=AsyncMock,
-    )
-    _patch_rate_limit_deps(mocker, target_user_id, daily_used=0, weekly_used=3_000_000)
-
-    response = client.post(
-        "/admin/rate_limit/reset",
-        json={"user_id": target_user_id},
-    )
-
-    assert response.status_code == 200
-    data = response.json()
-    assert data["daily_tokens_used"] == 0
-    # Weekly is untouched
-    assert data["weekly_tokens_used"] == 3_000_000
-
-    mock_reset.assert_awaited_once_with(target_user_id, reset_weekly=False)
-
-    configured_snapshot.assert_match(
-        json.dumps(data, indent=2, sort_keys=True) + "\n",
-        "reset_user_usage_daily_only",
-    )
-
-
-def test_reset_user_usage_daily_and_weekly(
-    mocker: pytest_mock.MockerFixture,
-    configured_snapshot: Snapshot,
-    target_user_id: str,
-) -> None:
-    """Test resetting both daily and weekly usage."""
-    mock_reset = mocker.patch(
-        f"{_MOCK_MODULE}.reset_user_usage",
-        new_callable=AsyncMock,
-    )
-    _patch_rate_limit_deps(mocker, target_user_id, daily_used=0, weekly_used=0)
-
-    response = client.post(
-        "/admin/rate_limit/reset",
-        json={"user_id": target_user_id, "reset_weekly": True},
-    )
-
-    assert response.status_code == 200
-    data = response.json()
-    assert data["daily_tokens_used"] == 0
-    assert data["weekly_tokens_used"] == 0
-
-    mock_reset.assert_awaited_once_with(target_user_id, reset_weekly=True)
-
-    configured_snapshot.assert_match(
-        json.dumps(data, indent=2, sort_keys=True) + "\n",
-        "reset_user_usage_daily_and_weekly",
-    )
-
-
-def test_reset_user_usage_redis_failure(
-    mocker: pytest_mock.MockerFixture,
-    target_user_id: str,
-) -> None:
-    """Test that Redis failure on reset returns 500."""
-    mocker.patch(
-        f"{_MOCK_MODULE}.reset_user_usage",
-        new_callable=AsyncMock,
-        side_effect=Exception("Redis connection refused"),
-    )
-
-    response = client.post(
-        "/admin/rate_limit/reset",
-        json={"user_id": target_user_id},
-    )
-
-    assert response.status_code == 500
-
-
-def test_get_rate_limit_email_lookup_failure(
-    mocker: pytest_mock.MockerFixture,
-    target_user_id: str,
-) -> None:
-    """Test that failing to resolve a user email degrades gracefully."""
-    mocker.patch(
-        f"{_MOCK_MODULE}.get_global_rate_limits",
-        new_callable=AsyncMock,
-        return_value=(2_500_000, 12_500_000),
-    )
-    mocker.patch(
-        f"{_MOCK_MODULE}.get_usage_status",
-        new_callable=AsyncMock,
-        return_value=_mock_usage_status(),
-    )
-    mocker.patch(
-        f"{_MOCK_MODULE}.get_user_email_by_id",
-        new_callable=AsyncMock,
-        side_effect=Exception("DB connection lost"),
-    )
-
-    response = client.get("/admin/rate_limit", params={"user_id": target_user_id})
-
-    assert response.status_code == 200
-    data = response.json()
-    assert data["user_id"] == target_user_id
-    assert data["user_email"] is None
-
-
-def test_admin_endpoints_require_admin_role(mock_jwt_user) -> None:
-    """Test that rate limit admin endpoints require admin role."""
-    app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
-
-    response = client.get("/admin/rate_limit", params={"user_id": "test"})
-    assert response.status_code == 403
-
-    response = client.post(
-        "/admin/rate_limit/reset",
-        json={"user_id": "test"},
-    )
-    assert response.status_code == 403

autogpt_platform/backend/backend/api/features/admin/store_admin_routes.py

@@ -7,8 +7,6 @@ import fastapi
 import fastapi.responses
 import prisma.enums
 
-import backend.api.features.library.db as library_db
-import backend.api.features.library.model as library_model
 import backend.api.features.store.cache as store_cache
 import backend.api.features.store.db as store_db
 import backend.api.features.store.model as store_model
@@ -134,40 +132,3 @@ async def admin_download_agent_file(
         return fastapi.responses.FileResponse(
             tmp_file.name, filename=file_name, media_type="application/json"
         )
-
-
-@router.get(
-    "/submissions/{store_listing_version_id}/preview",
-    summary="Admin Preview Submission Listing",
-)
-async def admin_preview_submission(
-    store_listing_version_id: str,
-) -> store_model.StoreAgentDetails:
-    """
-    Preview a marketplace submission as it would appear on the listing page.
-    Bypasses the APPROVED-only StoreAgent view so admins can preview pending
-    submissions before approving.
-    """
-    return await store_db.get_store_agent_details_as_admin(store_listing_version_id)
-
-
-@router.post(
-    "/submissions/{store_listing_version_id}/add-to-library",
-    summary="Admin Add Pending Agent to Library",
-    status_code=201,
-)
-async def admin_add_agent_to_library(
-    store_listing_version_id: str,
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-) -> library_model.LibraryAgent:
-    """
-    Add a pending marketplace agent to the admin's library for review.
-    Uses admin-level access to bypass marketplace APPROVED-only checks.
-
-    The builder can load the graph because get_graph() checks library
-    membership as a fallback: "you added it, you keep it."
-    """
-    return await library_db.add_store_agent_to_library_as_admin(
-        store_listing_version_id=store_listing_version_id,
-        user_id=user_id,
-    )

autogpt_platform/backend/backend/api/features/admin/store_admin_routes_test.py

@@ -1,335 +0,0 @@
-"""Tests for admin store routes and the bypass logic they depend on.
-
-Tests are organized by what they protect:
-- SECRT-2162: get_graph_as_admin bypasses ownership/marketplace checks
-- SECRT-2167 security: admin endpoints reject non-admin users
-- SECRT-2167 bypass: preview queries StoreListingVersion (not StoreAgent view),
-  and add-to-library uses get_graph_as_admin (not get_graph)
-"""
-
-from datetime import datetime, timezone
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import fastapi
-import fastapi.responses
-import fastapi.testclient
-import pytest
-import pytest_mock
-from autogpt_libs.auth.jwt_utils import get_jwt_payload
-
-from backend.data.graph import get_graph_as_admin
-from backend.util.exceptions import NotFoundError
-
-from .store_admin_routes import router as store_admin_router
-
-# Shared constants
-ADMIN_USER_ID = "admin-user-id"
-CREATOR_USER_ID = "other-creator-id"
-GRAPH_ID = "test-graph-id"
-GRAPH_VERSION = 3
-SLV_ID = "test-store-listing-version-id"
-
-
-def _make_mock_graph(user_id: str = CREATOR_USER_ID) -> MagicMock:
-    graph = MagicMock()
-    graph.userId = user_id
-    graph.id = GRAPH_ID
-    graph.version = GRAPH_VERSION
-    graph.Nodes = []
-    return graph
-
-
-# ---- SECRT-2162: get_graph_as_admin bypasses ownership checks ---- #
-
-
-@pytest.mark.asyncio
-async def test_admin_can_access_pending_agent_not_owned() -> None:
-    """get_graph_as_admin must return a graph even when the admin doesn't own
-    it and it's not APPROVED in the marketplace."""
-    mock_graph = _make_mock_graph()
-    mock_graph_model = MagicMock(name="GraphModel")
-
-    with (
-        patch("backend.data.graph.AgentGraph.prisma") as mock_prisma,
-        patch(
-            "backend.data.graph.GraphModel.from_db",
-            return_value=mock_graph_model,
-        ),
-    ):
-        mock_prisma.return_value.find_first = AsyncMock(return_value=mock_graph)
-
-        result = await get_graph_as_admin(
-            graph_id=GRAPH_ID,
-            version=GRAPH_VERSION,
-            user_id=ADMIN_USER_ID,
-            for_export=False,
-        )
-
-    assert result is mock_graph_model
-
-
-@pytest.mark.asyncio
-async def test_admin_download_pending_agent_with_subagents() -> None:
-    """get_graph_as_admin with for_export=True must call get_sub_graphs
-    and pass sub_graphs to GraphModel.from_db."""
-    mock_graph = _make_mock_graph()
-    mock_sub_graph = MagicMock(name="SubGraph")
-    mock_graph_model = MagicMock(name="GraphModel")
-
-    with (
-        patch("backend.data.graph.AgentGraph.prisma") as mock_prisma,
-        patch(
-            "backend.data.graph.get_sub_graphs",
-            new_callable=AsyncMock,
-            return_value=[mock_sub_graph],
-        ) as mock_get_sub,
-        patch(
-            "backend.data.graph.GraphModel.from_db",
-            return_value=mock_graph_model,
-        ) as mock_from_db,
-    ):
-        mock_prisma.return_value.find_first = AsyncMock(return_value=mock_graph)
-
-        result = await get_graph_as_admin(
-            graph_id=GRAPH_ID,
-            version=GRAPH_VERSION,
-            user_id=ADMIN_USER_ID,
-            for_export=True,
-        )
-
-    assert result is mock_graph_model
-    mock_get_sub.assert_awaited_once_with(mock_graph)
-    mock_from_db.assert_called_once_with(
-        graph=mock_graph,
-        sub_graphs=[mock_sub_graph],
-        for_export=True,
-    )
-
-
-# ---- SECRT-2167 security: admin endpoints reject non-admin users ---- #
-
-app = fastapi.FastAPI()
-app.include_router(store_admin_router)
-
-
-@app.exception_handler(NotFoundError)
-async def _not_found_handler(
-    request: fastapi.Request, exc: NotFoundError
-) -> fastapi.responses.JSONResponse:
-    return fastapi.responses.JSONResponse(status_code=404, content={"detail": str(exc)})
-
-
-client = fastapi.testclient.TestClient(app)
-
-
-@pytest.fixture(autouse=True)
-def setup_app_admin_auth(mock_jwt_admin):
-    """Setup admin auth overrides for all route tests in this module."""
-    app.dependency_overrides[get_jwt_payload] = mock_jwt_admin["get_jwt_payload"]
-    yield
-    app.dependency_overrides.clear()
-
-
-def test_preview_requires_admin(mock_jwt_user) -> None:
-    """Non-admin users must get 403 on the preview endpoint."""
-    app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
-    response = client.get(f"/admin/submissions/{SLV_ID}/preview")
-    assert response.status_code == 403
-
-
-def test_add_to_library_requires_admin(mock_jwt_user) -> None:
-    """Non-admin users must get 403 on the add-to-library endpoint."""
-    app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
-    response = client.post(f"/admin/submissions/{SLV_ID}/add-to-library")
-    assert response.status_code == 403
-
-
-def test_preview_nonexistent_submission(
-    mocker: pytest_mock.MockerFixture,
-) -> None:
-    """Preview of a nonexistent submission returns 404."""
-    mocker.patch(
-        "backend.api.features.admin.store_admin_routes.store_db"
-        ".get_store_agent_details_as_admin",
-        side_effect=NotFoundError("not found"),
-    )
-    response = client.get(f"/admin/submissions/{SLV_ID}/preview")
-    assert response.status_code == 404
-
-
-# ---- SECRT-2167 bypass: verify the right data sources are used ---- #
-
-
-@pytest.mark.asyncio
-async def test_preview_queries_store_listing_version_not_store_agent() -> None:
-    """get_store_agent_details_as_admin must query StoreListingVersion
-    directly (not the APPROVED-only StoreAgent view). This is THE test that
-    prevents the bypass from being accidentally reverted."""
-    from backend.api.features.store.db import get_store_agent_details_as_admin
-
-    mock_slv = MagicMock()
-    mock_slv.id = SLV_ID
-    mock_slv.name = "Test Agent"
-    mock_slv.subHeading = "Short desc"
-    mock_slv.description = "Long desc"
-    mock_slv.videoUrl = None
-    mock_slv.agentOutputDemoUrl = None
-    mock_slv.imageUrls = ["https://example.com/img.png"]
-    mock_slv.instructions = None
-    mock_slv.categories = ["productivity"]
-    mock_slv.version = 1
-    mock_slv.agentGraphId = GRAPH_ID
-    mock_slv.agentGraphVersion = GRAPH_VERSION
-    mock_slv.updatedAt = datetime(2026, 3, 24, tzinfo=timezone.utc)
-    mock_slv.recommendedScheduleCron = "0 9 * * *"
-
-    mock_listing = MagicMock()
-    mock_listing.id = "listing-id"
-    mock_listing.slug = "test-agent"
-    mock_listing.activeVersionId = SLV_ID
-    mock_listing.hasApprovedVersion = False
-    mock_listing.CreatorProfile = MagicMock(username="creator", avatarUrl="")
-    mock_slv.StoreListing = mock_listing
-
-    with (
-        patch(
-            "backend.api.features.store.db.prisma.models" ".StoreListingVersion.prisma",
-        ) as mock_slv_prisma,
-        patch(
-            "backend.api.features.store.db.prisma.models.StoreAgent.prisma",
-        ) as mock_store_agent_prisma,
-    ):
-        mock_slv_prisma.return_value.find_unique = AsyncMock(return_value=mock_slv)
-
-        result = await get_store_agent_details_as_admin(SLV_ID)
-
-    # Verify it queried StoreListingVersion (not the APPROVED-only StoreAgent)
-    mock_slv_prisma.return_value.find_unique.assert_awaited_once()
-    await_args = mock_slv_prisma.return_value.find_unique.await_args
-    assert await_args is not None
-    assert await_args.kwargs["where"] == {"id": SLV_ID}
-
-    # Verify the APPROVED-only StoreAgent view was NOT touched
-    mock_store_agent_prisma.assert_not_called()
-
-    # Verify the result has the right data
-    assert result.agent_name == "Test Agent"
-    assert result.agent_image == ["https://example.com/img.png"]
-    assert result.has_approved_version is False
-    assert result.runs == 0
-    assert result.rating == 0.0
-
-
-@pytest.mark.asyncio
-async def test_resolve_graph_admin_uses_get_graph_as_admin() -> None:
-    """resolve_graph_for_library(admin=True) must call get_graph_as_admin,
-    not get_graph. This is THE test that prevents the add-to-library bypass
-    from being accidentally reverted."""
-    from backend.api.features.library._add_to_library import resolve_graph_for_library
-
-    mock_slv = MagicMock()
-    mock_slv.AgentGraph = MagicMock(id=GRAPH_ID, version=GRAPH_VERSION)
-    mock_graph_model = MagicMock(name="GraphModel")
-
-    with (
-        patch(
-            "backend.api.features.library._add_to_library.prisma.models"
-            ".StoreListingVersion.prisma",
-        ) as mock_prisma,
-        patch(
-            "backend.api.features.library._add_to_library.graph_db"
-            ".get_graph_as_admin",
-            new_callable=AsyncMock,
-            return_value=mock_graph_model,
-        ) as mock_admin,
-        patch(
-            "backend.api.features.library._add_to_library.graph_db.get_graph",
-            new_callable=AsyncMock,
-        ) as mock_regular,
-    ):
-        mock_prisma.return_value.find_unique = AsyncMock(return_value=mock_slv)
-
-        result = await resolve_graph_for_library(SLV_ID, ADMIN_USER_ID, admin=True)
-
-    assert result is mock_graph_model
-    mock_admin.assert_awaited_once_with(
-        graph_id=GRAPH_ID, version=GRAPH_VERSION, user_id=ADMIN_USER_ID
-    )
-    mock_regular.assert_not_awaited()
-
-
-@pytest.mark.asyncio
-async def test_resolve_graph_regular_uses_get_graph() -> None:
-    """resolve_graph_for_library(admin=False) must call get_graph,
-    not get_graph_as_admin. Ensures the non-admin path is preserved."""
-    from backend.api.features.library._add_to_library import resolve_graph_for_library
-
-    mock_slv = MagicMock()
-    mock_slv.AgentGraph = MagicMock(id=GRAPH_ID, version=GRAPH_VERSION)
-    mock_graph_model = MagicMock(name="GraphModel")
-
-    with (
-        patch(
-            "backend.api.features.library._add_to_library.prisma.models"
-            ".StoreListingVersion.prisma",
-        ) as mock_prisma,
-        patch(
-            "backend.api.features.library._add_to_library.graph_db"
-            ".get_graph_as_admin",
-            new_callable=AsyncMock,
-        ) as mock_admin,
-        patch(
-            "backend.api.features.library._add_to_library.graph_db.get_graph",
-            new_callable=AsyncMock,
-            return_value=mock_graph_model,
-        ) as mock_regular,
-    ):
-        mock_prisma.return_value.find_unique = AsyncMock(return_value=mock_slv)
-
-        result = await resolve_graph_for_library(SLV_ID, "regular-user-id", admin=False)
-
-    assert result is mock_graph_model
-    mock_regular.assert_awaited_once_with(
-        graph_id=GRAPH_ID, version=GRAPH_VERSION, user_id="regular-user-id"
-    )
-    mock_admin.assert_not_awaited()
-
-
-# ---- Library membership grants graph access (product decision) ---- #
-
-
-@pytest.mark.asyncio
-async def test_library_member_can_view_pending_agent_in_builder() -> None:
-    """After adding a pending agent to their library, the user should be
-    able to load the graph in the builder via get_graph()."""
-    mock_graph = _make_mock_graph()
-    mock_graph_model = MagicMock(name="GraphModel")
-    mock_library_agent = MagicMock()
-    mock_library_agent.AgentGraph = mock_graph
-
-    with (
-        patch("backend.data.graph.AgentGraph.prisma") as mock_ag_prisma,
-        patch(
-            "backend.data.graph.StoreListingVersion.prisma",
-        ) as mock_slv_prisma,
-        patch("backend.data.graph.LibraryAgent.prisma") as mock_lib_prisma,
-        patch(
-            "backend.data.graph.GraphModel.from_db",
-            return_value=mock_graph_model,
-        ),
-    ):
-        mock_ag_prisma.return_value.find_first = AsyncMock(return_value=None)
-        mock_slv_prisma.return_value.find_first = AsyncMock(return_value=None)
-        mock_lib_prisma.return_value.find_first = AsyncMock(
-            return_value=mock_library_agent
-        )
-
-        from backend.data.graph import get_graph
-
-        result = await get_graph(
-            graph_id=GRAPH_ID,
-            version=GRAPH_VERSION,
-            user_id=ADMIN_USER_ID,
-        )
-
-    assert result is mock_graph_model, "Library membership should grant graph access"

autogpt_platform/backend/backend/api/features/admin/user_admin_routes.py

@@ -0,0 +1,137 @@
+import logging
+import math
+
+from autogpt_libs.auth import get_user_id, requires_admin_user
+from fastapi import APIRouter, File, Query, Security, UploadFile
+
+from backend.data.invited_user import (
+    bulk_create_invited_users_from_file,
+    create_invited_user,
+    list_invited_users,
+    retry_invited_user_tally,
+    revoke_invited_user,
+)
+from backend.data.tally import mask_email
+from backend.util.models import Pagination
+
+from .model import (
+    BulkInvitedUsersResponse,
+    CreateInvitedUserRequest,
+    InvitedUserResponse,
+    InvitedUsersResponse,
+)
+
+logger = logging.getLogger(__name__)
+
+
+router = APIRouter(
+    prefix="/admin",
+    tags=["users", "admin"],
+    dependencies=[Security(requires_admin_user)],
+)
+
+
+@router.get(
+    "/invited-users",
+    response_model=InvitedUsersResponse,
+    summary="List Invited Users",
+)
+async def get_invited_users(
+    admin_user_id: str = Security(get_user_id),
+    page: int = Query(1, ge=1),
+    page_size: int = Query(50, ge=1, le=200),
+) -> InvitedUsersResponse:
+    logger.info("Admin user %s requested invited users", admin_user_id)
+    invited_users, total = await list_invited_users(page=page, page_size=page_size)
+    return InvitedUsersResponse(
+        invited_users=[InvitedUserResponse.from_record(iu) for iu in invited_users],
+        pagination=Pagination(
+            total_items=total,
+            total_pages=max(1, math.ceil(total / page_size)),
+            current_page=page,
+            page_size=page_size,
+        ),
+    )
+
+
+@router.post(
+    "/invited-users",
+    response_model=InvitedUserResponse,
+    summary="Create Invited User",
+)
+async def create_invited_user_route(
+    request: CreateInvitedUserRequest,
+    admin_user_id: str = Security(get_user_id),
+) -> InvitedUserResponse:
+    logger.info(
+        "Admin user %s creating invited user for %s",
+        admin_user_id,
+        mask_email(request.email),
+    )
+    invited_user = await create_invited_user(request.email, request.name)
+    logger.info(
+        "Admin user %s created invited user %s",
+        admin_user_id,
+        invited_user.id,
+    )
+    return InvitedUserResponse.from_record(invited_user)
+
+
+@router.post(
+    "/invited-users/bulk",
+    response_model=BulkInvitedUsersResponse,
+    summary="Bulk Create Invited Users",
+    operation_id="postV2BulkCreateInvitedUsers",
+)
+async def bulk_create_invited_users_route(
+    file: UploadFile = File(...),
+    admin_user_id: str = Security(get_user_id),
+) -> BulkInvitedUsersResponse:
+    logger.info(
+        "Admin user %s bulk invited users from %s",
+        admin_user_id,
+        file.filename or "<unnamed>",
+    )
+    content = await file.read()
+    result = await bulk_create_invited_users_from_file(file.filename, content)
+    return BulkInvitedUsersResponse.from_result(result)
+
+
+@router.post(
+    "/invited-users/{invited_user_id}/revoke",
+    response_model=InvitedUserResponse,
+    summary="Revoke Invited User",
+)
+async def revoke_invited_user_route(
+    invited_user_id: str,
+    admin_user_id: str = Security(get_user_id),
+) -> InvitedUserResponse:
+    logger.info(
+        "Admin user %s revoking invited user %s", admin_user_id, invited_user_id
+    )
+    invited_user = await revoke_invited_user(invited_user_id)
+    logger.info("Admin user %s revoked invited user %s", admin_user_id, invited_user_id)
+    return InvitedUserResponse.from_record(invited_user)
+
+
+@router.post(
+    "/invited-users/{invited_user_id}/retry-tally",
+    response_model=InvitedUserResponse,
+    summary="Retry Invited User Tally",
+)
+async def retry_invited_user_tally_route(
+    invited_user_id: str,
+    admin_user_id: str = Security(get_user_id),
+) -> InvitedUserResponse:
+    logger.info(
+        "Admin user %s retrying Tally seed for invited user %s",
+        admin_user_id,
+        invited_user_id,
+    )
+    invited_user = await retry_invited_user_tally(invited_user_id)
+    logger.info(
+        "Admin user %s retried Tally seed for invited user %s",
+        admin_user_id,
+        invited_user_id,
+    )
+    return InvitedUserResponse.from_record(invited_user)

autogpt_platform/backend/backend/api/features/admin/user_admin_routes_test.py

@@ -0,0 +1,168 @@
+from datetime import datetime, timezone
+from unittest.mock import AsyncMock
+
+import fastapi
+import fastapi.testclient
+import prisma.enums
+import pytest
+import pytest_mock
+from autogpt_libs.auth.jwt_utils import get_jwt_payload
+
+from backend.data.invited_user import (
+    BulkInvitedUserRowResult,
+    BulkInvitedUsersResult,
+    InvitedUserRecord,
+)
+
+from .user_admin_routes import router as user_admin_router
+
+app = fastapi.FastAPI()
+app.include_router(user_admin_router)
+
+client = fastapi.testclient.TestClient(app)
+
+
+@pytest.fixture(autouse=True)
+def setup_app_admin_auth(mock_jwt_admin):
+    app.dependency_overrides[get_jwt_payload] = mock_jwt_admin["get_jwt_payload"]
+    yield
+    app.dependency_overrides.clear()
+
+
+def _sample_invited_user() -> InvitedUserRecord:
+    now = datetime.now(timezone.utc)
+    return InvitedUserRecord(
+        id="invite-1",
+        email="invited@example.com",
+        status=prisma.enums.InvitedUserStatus.INVITED,
+        auth_user_id=None,
+        name="Invited User",
+        tally_understanding=None,
+        tally_status=prisma.enums.TallyComputationStatus.PENDING,
+        tally_computed_at=None,
+        tally_error=None,
+        created_at=now,
+        updated_at=now,
+    )
+
+
+def _sample_bulk_invited_users_result() -> BulkInvitedUsersResult:
+    return BulkInvitedUsersResult(
+        created_count=1,
+        skipped_count=1,
+        error_count=0,
+        results=[
+            BulkInvitedUserRowResult(
+                row_number=1,
+                email="invited@example.com",
+                name=None,
+                status="CREATED",
+                message="Invite created",
+                invited_user=_sample_invited_user(),
+            ),
+            BulkInvitedUserRowResult(
+                row_number=2,
+                email="duplicate@example.com",
+                name=None,
+                status="SKIPPED",
+                message="An invited user with this email already exists",
+                invited_user=None,
+            ),
+        ],
+    )
+
+
+def test_get_invited_users(
+    mocker: pytest_mock.MockerFixture,
+) -> None:
+    mocker.patch(
+        "backend.api.features.admin.user_admin_routes.list_invited_users",
+        AsyncMock(return_value=([_sample_invited_user()], 1)),
+    )
+
+    response = client.get("/admin/invited-users")
+
+    assert response.status_code == 200
+    data = response.json()
+    assert len(data["invited_users"]) == 1
+    assert data["invited_users"][0]["email"] == "invited@example.com"
+    assert data["invited_users"][0]["status"] == "INVITED"
+    assert data["pagination"]["total_items"] == 1
+    assert data["pagination"]["current_page"] == 1
+    assert data["pagination"]["page_size"] == 50
+
+
+def test_create_invited_user(
+    mocker: pytest_mock.MockerFixture,
+) -> None:
+    mocker.patch(
+        "backend.api.features.admin.user_admin_routes.create_invited_user",
+        AsyncMock(return_value=_sample_invited_user()),
+    )
+
+    response = client.post(
+        "/admin/invited-users",
+        json={"email": "invited@example.com", "name": "Invited User"},
+    )
+
+    assert response.status_code == 200
+    data = response.json()
+    assert data["email"] == "invited@example.com"
+    assert data["name"] == "Invited User"
+
+
+def test_bulk_create_invited_users(
+    mocker: pytest_mock.MockerFixture,
+) -> None:
+    mocker.patch(
+        "backend.api.features.admin.user_admin_routes.bulk_create_invited_users_from_file",
+        AsyncMock(return_value=_sample_bulk_invited_users_result()),
+    )
+
+    response = client.post(
+        "/admin/invited-users/bulk",
+        files={
+            "file": ("invites.txt", b"invited@example.com\nduplicate@example.com\n")
+        },
+    )
+
+    assert response.status_code == 200
+    data = response.json()
+    assert data["created_count"] == 1
+    assert data["skipped_count"] == 1
+    assert data["results"][0]["status"] == "CREATED"
+    assert data["results"][1]["status"] == "SKIPPED"
+
+
+def test_revoke_invited_user(
+    mocker: pytest_mock.MockerFixture,
+) -> None:
+    revoked = _sample_invited_user().model_copy(
+        update={"status": prisma.enums.InvitedUserStatus.REVOKED}
+    )
+    mocker.patch(
+        "backend.api.features.admin.user_admin_routes.revoke_invited_user",
+        AsyncMock(return_value=revoked),
+    )
+
+    response = client.post("/admin/invited-users/invite-1/revoke")
+
+    assert response.status_code == 200
+    assert response.json()["status"] == "REVOKED"
+
+
+def test_retry_invited_user_tally(
+    mocker: pytest_mock.MockerFixture,
+) -> None:
+    retried = _sample_invited_user().model_copy(
+        update={"tally_status": prisma.enums.TallyComputationStatus.RUNNING}
+    )
+    mocker.patch(
+        "backend.api.features.admin.user_admin_routes.retry_invited_user_tally",
+        AsyncMock(return_value=retried),
+    )
+
+    response = client.post("/admin/invited-users/invite-1/retry-tally")
+
+    assert response.status_code == 200
+    assert response.json()["tally_status"] == "RUNNING"

autogpt_platform/backend/backend/api/features/builder/db.py

@@ -4,12 +4,14 @@ from difflib import SequenceMatcher
 from typing import Any, Sequence, get_args, get_origin
 
 import prisma
+from prisma.enums import ContentType
 from prisma.models import mv_suggested_blocks
 
 import backend.api.features.library.db as library_db
 import backend.api.features.library.model as library_model
 import backend.api.features.store.db as store_db
 import backend.api.features.store.model as store_model
+from backend.api.features.store.hybrid_search import unified_hybrid_search
 from backend.blocks import load_all_blocks
 from backend.blocks._base import (
     AnyBlockSchema,
@@ -22,7 +24,6 @@ from backend.blocks.llm import LlmModel
 from backend.integrations.providers import ProviderName
 from backend.util.cache import cached
 from backend.util.models import Pagination
-from backend.util.text import split_camelcase
 
 from .model import (
     BlockCategoryResponse,
@@ -270,7 +271,7 @@ async def _build_cached_search_results(
 
     # Use hybrid search when query is present, otherwise list all blocks
     if (include_blocks or include_integrations) and normalized_query:
-        block_results, block_total, integration_total = await _text_search_blocks(
+        block_results, block_total, integration_total = await _hybrid_search_blocks(
             query=search_query,
             include_blocks=include_blocks,
             include_integrations=include_integrations,
@@ -382,75 +383,117 @@ def _collect_block_results(
     return results, block_count, integration_count
 
 
-async def _text_search_blocks(
+async def _hybrid_search_blocks(
     *,
     query: str,
     include_blocks: bool,
     include_integrations: bool,
 ) -> tuple[list[_ScoredItem], int, int]:
     """
-    Search blocks using in-memory text matching over the block registry.
+    Search blocks using hybrid search with builder-specific filtering.
 
-    All blocks are already loaded in memory, so this is fast and reliable
-    regardless of whether OpenAI embeddings are available.
+    Uses unified_hybrid_search for semantic + lexical search, then applies
+    post-filtering for block/integration types and scoring adjustments.
 
     Scoring:
-        - Base: text relevance via _score_primary_fields, plus BLOCK_SCORE_BOOST
+        - Base: hybrid relevance score (0-1) scaled to 0-100, plus BLOCK_SCORE_BOOST
           to prioritize blocks over marketplace agents in combined results
+        - +30 for exact name match, +15 for prefix name match
         - +20 if the block has an LlmModel field and the query matches an LLM model name
+
+    Args:
+        query: The search query string
+        include_blocks: Whether to include regular blocks
+        include_integrations: Whether to include integration blocks
+
+    Returns:
+        Tuple of (scored_items, block_count, integration_count)
     """
     results: list[_ScoredItem] = []
+    block_count = 0
+    integration_count = 0
 
     if not include_blocks and not include_integrations:
-        return results, 0, 0
+        return results, block_count, integration_count
 
     normalized_query = query.strip().lower()
 
-    all_results, _, _ = _collect_block_results(
-        include_blocks=include_blocks,
-        include_integrations=include_integrations,
+    # Fetch more results to account for post-filtering
+    search_results, _ = await unified_hybrid_search(
+        query=query,
+        content_types=[ContentType.BLOCK],
+        page=1,
+        page_size=150,
+        min_score=0.10,
     )
 
+    # Load all blocks for getting BlockInfo
     all_blocks = load_all_blocks()
 
-    for item in all_results:
-        block_info = item.item
-        assert isinstance(block_info, BlockInfo)
-        name = split_camelcase(block_info.name).lower()
+    for result in search_results:
+        block_id = result["content_id"]
 
-        # Build rich description including input field descriptions,
-        # matching the searchable text that the embedding pipeline uses
-        desc_parts = [block_info.description or ""]
-        block_cls = all_blocks.get(block_info.id)
-        if block_cls is not None:
-            block: AnyBlockSchema = block_cls()
-            desc_parts += [
-                f"{f}: {info.description}"
-                for f, info in block.input_schema.model_fields.items()
-                if info.description
-            ]
-        description = " ".join(desc_parts).lower()
+        # Skip excluded blocks
+        if block_id in EXCLUDED_BLOCK_IDS:
+            continue
 
-        score = _score_primary_fields(name, description, normalized_query)
+        metadata = result.get("metadata", {})
+        hybrid_score = result.get("relevance", 0.0)
+
+        # Get the actual block class
+        if block_id not in all_blocks:
+            continue
+
+        block_cls = all_blocks[block_id]
+        block: AnyBlockSchema = block_cls()
+
+        if block.disabled:
+            continue
+
+        # Check block/integration filter using metadata
+        is_integration = metadata.get("is_integration", False)
+
+        if is_integration and not include_integrations:
+            continue
+        if not is_integration and not include_blocks:
+            continue
+
+        # Get block info
+        block_info = block.get_info()
+
+        # Calculate final score: scale hybrid score and add builder-specific bonuses
+        # Hybrid scores are 0-1, builder scores were 0-200+
+        # Add BLOCK_SCORE_BOOST to prioritize blocks over marketplace agents
+        final_score = hybrid_score * 100 + BLOCK_SCORE_BOOST
 
         # Add LLM model match bonus
-        if block_cls is not None and _matches_llm_model(
-            block_cls().input_schema, normalized_query
-        ):
-            score += 20
+        has_llm_field = metadata.get("has_llm_model_field", False)
+        if has_llm_field and _matches_llm_model(block.input_schema, normalized_query):
+            final_score += 20
 
-        if score >= MIN_SCORE_FOR_FILTERED_RESULTS:
-            results.append(
-                _ScoredItem(
-                    item=block_info,
-                    filter_type=item.filter_type,
-                    score=score + BLOCK_SCORE_BOOST,
-                    sort_key=name,
-                )
+        # Add exact/prefix match bonus for deterministic tie-breaking
+        name = block_info.name.lower()
+        if name == normalized_query:
+            final_score += 30
+        elif name.startswith(normalized_query):
+            final_score += 15
+
+        # Track counts
+        filter_type: FilterType = "integrations" if is_integration else "blocks"
+        if is_integration:
+            integration_count += 1
+        else:
+            block_count += 1
+
+        results.append(
+            _ScoredItem(
+                item=block_info,
+                filter_type=filter_type,
+                score=final_score,
+                sort_key=name,
             )
+        )
 
-    block_count = sum(1 for r in results if r.filter_type == "blocks")
-    integration_count = sum(1 for r in results if r.filter_type == "integrations")
     return results, block_count, integration_count
 
 

autogpt_platform/backend/backend/api/features/chat/routes.py

@@ -30,14 +30,8 @@ from backend.copilot.model import (
 from backend.copilot.rate_limit import (
     CoPilotUsageStatus,
     RateLimitExceeded,
-    acquire_reset_lock,
     check_rate_limit,
-    get_daily_reset_count,
-    get_global_rate_limits,
     get_usage_status,
-    increment_daily_reset_count,
-    release_reset_lock,
-    reset_daily_usage,
 )
 from backend.copilot.response_model import StreamError, StreamFinish, StreamHeartbeat
 from backend.copilot.tools.e2b_sandbox import kill_sandbox
@@ -65,16 +59,10 @@ from backend.copilot.tools.models import (
     UnderstandingUpdatedResponse,
 )
 from backend.copilot.tracking import track_user_message
-from backend.data.credit import UsageTransactionMetadata, get_user_credit_model
 from backend.data.redis_client import get_redis_async
 from backend.data.understanding import get_business_understanding
 from backend.data.workspace import get_or_create_workspace
-from backend.util.exceptions import InsufficientBalanceError, NotFoundError
-from backend.util.settings import Settings
-
-settings = Settings()
-
-logger = logging.getLogger(__name__)
+from backend.util.exceptions import NotFoundError
 
 config = ChatConfig()
 
@@ -82,6 +70,8 @@ _UUID_RE = re.compile(
     r"^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$", re.I
 )
 
+logger = logging.getLogger(__name__)
+
 
 async def _validate_and_get_session(
     session_id: str,
@@ -432,187 +422,11 @@ async def get_copilot_usage(
     """Get CoPilot usage status for the authenticated user.
 
     Returns current token usage vs limits for daily and weekly windows.
-    Global defaults sourced from LaunchDarkly (falling back to config).
     """
-    daily_limit, weekly_limit = await get_global_rate_limits(
-        user_id, config.daily_token_limit, config.weekly_token_limit
-    )
     return await get_usage_status(
         user_id=user_id,
-        daily_token_limit=daily_limit,
-        weekly_token_limit=weekly_limit,
-        rate_limit_reset_cost=config.rate_limit_reset_cost,
-    )
-
-
-class RateLimitResetResponse(BaseModel):
-    """Response from resetting the daily rate limit."""
-
-    success: bool
-    credits_charged: int = Field(description="Credits charged (in cents)")
-    remaining_balance: int = Field(description="Credit balance after charge (in cents)")
-    usage: CoPilotUsageStatus = Field(description="Updated usage status after reset")
-
-
-@router.post(
-    "/usage/reset",
-    status_code=200,
-    responses={
-        400: {
-            "description": "Bad Request (feature disabled or daily limit not reached)"
-        },
-        402: {"description": "Payment Required (insufficient credits)"},
-        429: {
-            "description": "Too Many Requests (max daily resets exceeded or reset in progress)"
-        },
-        503: {
-            "description": "Service Unavailable (Redis reset failed; credits refunded or support needed)"
-        },
-    },
-)
-async def reset_copilot_usage(
-    user_id: Annotated[str, Security(auth.get_user_id)],
-) -> RateLimitResetResponse:
-    """Reset the daily CoPilot rate limit by spending credits.
-
-    Allows users who have hit their daily token limit to spend credits
-    to reset their daily usage counter and continue working.
-    Returns 400 if the feature is disabled or the user is not over the limit.
-    Returns 402 if the user has insufficient credits.
-    """
-    cost = config.rate_limit_reset_cost
-    if cost <= 0:
-        raise HTTPException(
-            status_code=400,
-            detail="Rate limit reset is not available.",
-        )
-
-    if not settings.config.enable_credit:
-        raise HTTPException(
-            status_code=400,
-            detail="Rate limit reset is not available (credit system is disabled).",
-        )
-
-    daily_limit, weekly_limit = await get_global_rate_limits(
-        user_id, config.daily_token_limit, config.weekly_token_limit
-    )
-
-    if daily_limit <= 0:
-        raise HTTPException(
-            status_code=400,
-            detail="No daily limit is configured — nothing to reset.",
-        )
-
-    # Check max daily resets.  get_daily_reset_count returns None when Redis
-    # is unavailable; reject the reset in that case to prevent unlimited
-    # free resets when the counter store is down.
-    reset_count = await get_daily_reset_count(user_id)
-    if reset_count is None:
-        raise HTTPException(
-            status_code=503,
-            detail="Unable to verify reset eligibility — please try again later.",
-        )
-    if config.max_daily_resets > 0 and reset_count >= config.max_daily_resets:
-        raise HTTPException(
-            status_code=429,
-            detail=f"You've used all {config.max_daily_resets} resets for today.",
-        )
-
-    # Acquire a per-user lock to prevent TOCTOU races (concurrent resets).
-    if not await acquire_reset_lock(user_id):
-        raise HTTPException(
-            status_code=429,
-            detail="A reset is already in progress. Please try again.",
-        )
-
-    try:
-        # Verify the user is actually at or over their daily limit.
-        usage_status = await get_usage_status(
-            user_id=user_id,
-            daily_token_limit=daily_limit,
-            weekly_token_limit=weekly_limit,
-        )
-        if daily_limit > 0 and usage_status.daily.used < daily_limit:
-            raise HTTPException(
-                status_code=400,
-                detail="You have not reached your daily limit yet.",
-            )
-
-        # If the weekly limit is also exhausted, resetting the daily counter
-        # won't help — the user would still be blocked by the weekly limit.
-        if weekly_limit > 0 and usage_status.weekly.used >= weekly_limit:
-            raise HTTPException(
-                status_code=400,
-                detail="Your weekly limit is also reached. Resetting the daily limit won't help.",
-            )
-
-        # Charge credits.
-        credit_model = await get_user_credit_model(user_id)
-        try:
-            remaining = await credit_model.spend_credits(
-                user_id=user_id,
-                cost=cost,
-                metadata=UsageTransactionMetadata(
-                    reason="CoPilot daily rate limit reset",
-                ),
-            )
-        except InsufficientBalanceError as e:
-            raise HTTPException(
-                status_code=402,
-                detail="Insufficient credits to reset your rate limit.",
-            ) from e
-
-        # Reset daily usage in Redis.  If this fails, refund the credits
-        # so the user is not charged for a service they did not receive.
-        if not await reset_daily_usage(user_id, daily_token_limit=daily_limit):
-            # Compensate: refund the charged credits.
-            refunded = False
-            try:
-                await credit_model.top_up_credits(user_id, cost)
-                refunded = True
-                logger.warning(
-                    "Refunded %d credits to user %s after Redis reset failure",
-                    cost,
-                    user_id[:8],
-                )
-            except Exception:
-                logger.error(
-                    "CRITICAL: Failed to refund %d credits to user %s "
-                    "after Redis reset failure — manual intervention required",
-                    cost,
-                    user_id[:8],
-                    exc_info=True,
-                )
-            if refunded:
-                raise HTTPException(
-                    status_code=503,
-                    detail="Rate limit reset failed — please try again later. "
-                    "Your credits have not been charged.",
-                )
-            raise HTTPException(
-                status_code=503,
-                detail="Rate limit reset failed and the automatic refund "
-                "also failed. Please contact support for assistance.",
-            )
-
-        # Track the reset count for daily cap enforcement.
-        await increment_daily_reset_count(user_id)
-    finally:
-        await release_reset_lock(user_id)
-
-    # Return updated usage status.
-    updated_usage = await get_usage_status(
-        user_id=user_id,
-        daily_token_limit=daily_limit,
-        weekly_token_limit=weekly_limit,
-        rate_limit_reset_cost=config.rate_limit_reset_cost,
-    )
-
-    return RateLimitResetResponse(
-        success=True,
-        credits_charged=cost,
-        remaining_balance=remaining,
-        usage=updated_usage,
+        daily_token_limit=config.daily_token_limit,
+        weekly_token_limit=config.weekly_token_limit,
     )
 
 
@@ -713,16 +527,12 @@ async def stream_chat_post(
 
     # Pre-turn rate limit check (token-based).
     # check_rate_limit short-circuits internally when both limits are 0.
-    # Global defaults sourced from LaunchDarkly, falling back to config.
     if user_id:
         try:
-            daily_limit, weekly_limit = await get_global_rate_limits(
-                user_id, config.daily_token_limit, config.weekly_token_limit
-            )
             await check_rate_limit(
                 user_id=user_id,
-                daily_token_limit=daily_limit,
-                weekly_token_limit=weekly_limit,
+                daily_token_limit=config.daily_token_limit,
+                weekly_token_limit=config.weekly_token_limit,
             )
         except RateLimitExceeded as e:
             raise HTTPException(status_code=429, detail=str(e)) from e
@@ -1088,17 +898,10 @@ async def session_assign_user(
 # ========== Suggested Prompts ==========
 
 
-class SuggestedTheme(BaseModel):
-    """A themed group of suggested prompts."""
-
-    name: str
-    prompts: list[str]
-
-
 class SuggestedPromptsResponse(BaseModel):
-    """Response model for user-specific suggested prompts grouped by theme."""
+    """Response model for user-specific suggested prompts."""
 
-    themes: list[SuggestedTheme]
+    prompts: list[str]
 
 
 @router.get(
@@ -1109,21 +912,17 @@ async def get_suggested_prompts(
     user_id: Annotated[str, Security(auth.get_user_id)],
 ) -> SuggestedPromptsResponse:
     """
-    Get LLM-generated suggested prompts grouped by theme.
+    Get LLM-generated suggested prompts for the authenticated user.
 
     Returns personalized quick-action prompts based on the user's
-    business understanding. Returns empty themes list if no custom
-    prompts are available.
+    business understanding. Returns an empty list if no custom prompts
+    are available.
     """
     understanding = await get_business_understanding(user_id)
-    if understanding is None or not understanding.suggested_prompts:
-        return SuggestedPromptsResponse(themes=[])
+    if understanding is None:
+        return SuggestedPromptsResponse(prompts=[])
 
-    themes = [
-        SuggestedTheme(name=name, prompts=prompts)
-        for name, prompts in understanding.suggested_prompts.items()
-    ]
-    return SuggestedPromptsResponse(themes=themes)
+    return SuggestedPromptsResponse(prompts=understanding.suggested_prompts)
 
 
 # ========== Configuration ==========

autogpt_platform/backend/backend/api/features/chat/routes_test.py

@@ -1,4 +1,4 @@
-"""Tests for chat API routes: session title update, file attachment validation, usage, and rate limiting."""
+"""Tests for chat API routes: session title update, file attachment validation, usage, rate limiting, and suggested prompts."""
 
 from datetime import UTC, datetime, timedelta
 from unittest.mock import AsyncMock, MagicMock
@@ -368,7 +368,6 @@ def test_usage_returns_daily_and_weekly(
         user_id=test_user_id,
         daily_token_limit=10000,
         weekly_token_limit=50000,
-        rate_limit_reset_cost=chat_routes.config.rate_limit_reset_cost,
     )
 
 
@@ -381,7 +380,6 @@ def test_usage_uses_config_limits(
 
     mocker.patch.object(chat_routes.config, "daily_token_limit", 99999)
     mocker.patch.object(chat_routes.config, "weekly_token_limit", 77777)
-    mocker.patch.object(chat_routes.config, "rate_limit_reset_cost", 500)
 
     response = client.get("/usage")
 
@@ -390,7 +388,6 @@ def test_usage_uses_config_limits(
         user_id=test_user_id,
         daily_token_limit=99999,
         weekly_token_limit=77777,
-        rate_limit_reset_cost=500,
     )
 
 
@@ -421,51 +418,44 @@ def _mock_get_business_understanding(
     )
 
 
-def test_suggested_prompts_returns_themes(
+def test_suggested_prompts_returns_prompts(
     mocker: pytest_mock.MockerFixture,
     test_user_id: str,
 ) -> None:
-    """User with themed prompts gets them back as themes list."""
+    """User with understanding and prompts gets them back."""
     mock_understanding = MagicMock()
-    mock_understanding.suggested_prompts = {
-        "Learn": ["L1", "L2"],
-        "Create": ["C1"],
-    }
+    mock_understanding.suggested_prompts = ["Do X", "Do Y", "Do Z"]
     _mock_get_business_understanding(mocker, return_value=mock_understanding)
 
     response = client.get("/suggested-prompts")
 
     assert response.status_code == 200
-    data = response.json()
-    assert "themes" in data
-    themes_by_name = {t["name"]: t["prompts"] for t in data["themes"]}
-    assert themes_by_name["Learn"] == ["L1", "L2"]
-    assert themes_by_name["Create"] == ["C1"]
+    assert response.json() == {"prompts": ["Do X", "Do Y", "Do Z"]}
 
 
 def test_suggested_prompts_no_understanding(
     mocker: pytest_mock.MockerFixture,
     test_user_id: str,
 ) -> None:
-    """User with no understanding gets empty themes list."""
+    """User with no understanding gets empty list."""
     _mock_get_business_understanding(mocker, return_value=None)
 
     response = client.get("/suggested-prompts")
 
     assert response.status_code == 200
-    assert response.json() == {"themes": []}
+    assert response.json() == {"prompts": []}
 
 
 def test_suggested_prompts_empty_prompts(
     mocker: pytest_mock.MockerFixture,
     test_user_id: str,
 ) -> None:
-    """User with understanding but empty prompts gets empty themes list."""
+    """User with understanding but no prompts gets empty list."""
     mock_understanding = MagicMock()
-    mock_understanding.suggested_prompts = {}
+    mock_understanding.suggested_prompts = []
     _mock_get_business_understanding(mocker, return_value=mock_understanding)
 
     response = client.get("/suggested-prompts")
 
     assert response.status_code == 200
-    assert response.json() == {"themes": []}
+    assert response.json() == {"prompts": []}

autogpt_platform/backend/backend/api/features/integrations/conftest.py

@@ -1,13 +0,0 @@
-"""Override session-scoped fixtures so unit tests run without the server."""
-
-import pytest
-
-
-@pytest.fixture(scope="session")
-def server():
-    yield None
-
-
-@pytest.fixture(scope="session", autouse=True)
-def graph_cleanup():
-    yield

autogpt_platform/backend/backend/api/features/integrations/router.py

@@ -34,21 +34,16 @@ from backend.data.model import (
     HostScopedCredentials,
     OAuth2Credentials,
     UserIntegrations,
-    is_sdk_default,
 )
 from backend.data.onboarding import OnboardingStep, complete_onboarding_step
 from backend.data.user import get_user_integrations
 from backend.executor.utils import add_graph_execution
 from backend.integrations.ayrshare import AyrshareClient, SocialPlatform
-from backend.integrations.credentials_store import (
-    is_system_credential,
-    provider_matches,
-)
+from backend.integrations.credentials_store import provider_matches
 from backend.integrations.creds_manager import (
     IntegrationCredentialsManager,
     create_mcp_oauth_handler,
 )
-from backend.integrations.managed_credentials import ensure_managed_credentials
 from backend.integrations.oauth import CREDENTIALS_BY_PROVIDER, HANDLERS_BY_NAME
 from backend.integrations.providers import ProviderName
 from backend.integrations.webhooks import get_webhook_manager
@@ -114,7 +109,6 @@ class CredentialsMetaResponse(BaseModel):
         default=None,
         description="Host pattern for host-scoped or MCP server URL for MCP credentials",
     )
-    is_managed: bool = False
 
     @model_validator(mode="before")
     @classmethod
@@ -144,19 +138,6 @@ class CredentialsMetaResponse(BaseModel):
         return None
 
 
-def to_meta_response(cred: Credentials) -> CredentialsMetaResponse:
-    return CredentialsMetaResponse(
-        id=cred.id,
-        provider=cred.provider,
-        type=cred.type,
-        title=cred.title,
-        scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
-        username=cred.username if isinstance(cred, OAuth2Credentials) else None,
-        host=CredentialsMetaResponse.get_host(cred),
-        is_managed=cred.is_managed,
-    )
-
-
 @router.post("/{provider}/callback", summary="Exchange OAuth code for tokens")
 async def callback(
     provider: Annotated[
@@ -223,20 +204,34 @@ async def callback(
         f"and provider {provider.value}"
     )
 
-    return to_meta_response(credentials)
+    return CredentialsMetaResponse(
+        id=credentials.id,
+        provider=credentials.provider,
+        type=credentials.type,
+        title=credentials.title,
+        scopes=credentials.scopes,
+        username=credentials.username,
+        host=(CredentialsMetaResponse.get_host(credentials)),
+    )
 
 
 @router.get("/credentials", summary="List Credentials")
 async def list_credentials(
     user_id: Annotated[str, Security(get_user_id)],
 ) -> list[CredentialsMetaResponse]:
-    # Fire-and-forget: provision missing managed credentials in the background.
-    # The credential appears on the next page load; listing is never blocked.
-    asyncio.create_task(ensure_managed_credentials(user_id, creds_manager.store))
     credentials = await creds_manager.store.get_all_creds(user_id)
 
     return [
-        to_meta_response(cred) for cred in credentials if not is_sdk_default(cred.id)
+        CredentialsMetaResponse(
+            id=cred.id,
+            provider=cred.provider,
+            type=cred.type,
+            title=cred.title,
+            scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
+            username=cred.username if isinstance(cred, OAuth2Credentials) else None,
+            host=CredentialsMetaResponse.get_host(cred),
+        )
+        for cred in credentials
     ]
 
 
@@ -247,11 +242,19 @@ async def list_credentials_by_provider(
     ],
     user_id: Annotated[str, Security(get_user_id)],
 ) -> list[CredentialsMetaResponse]:
-    asyncio.create_task(ensure_managed_credentials(user_id, creds_manager.store))
     credentials = await creds_manager.store.get_creds_by_provider(user_id, provider)
 
     return [
-        to_meta_response(cred) for cred in credentials if not is_sdk_default(cred.id)
+        CredentialsMetaResponse(
+            id=cred.id,
+            provider=cred.provider,
+            type=cred.type,
+            title=cred.title,
+            scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
+            username=cred.username if isinstance(cred, OAuth2Credentials) else None,
+            host=CredentialsMetaResponse.get_host(cred),
+        )
+        for cred in credentials
     ]
 
 
@@ -264,21 +267,18 @@ async def get_credential(
     ],
     cred_id: Annotated[str, Path(title="The ID of the credentials to retrieve")],
     user_id: Annotated[str, Security(get_user_id)],
-) -> CredentialsMetaResponse:
-    if is_sdk_default(cred_id):
-        raise HTTPException(
-            status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
-        )
+) -> Credentials:
     credential = await creds_manager.get(user_id, cred_id)
     if not credential:
         raise HTTPException(
             status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
         )
-    if not provider_matches(credential.provider, provider):
+    if credential.provider != provider:
         raise HTTPException(
-            status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail="Credentials do not match the specified provider",
         )
-    return to_meta_response(credential)
+    return credential
 
 
 @router.post("/{provider}/credentials", status_code=201, summary="Create Credentials")
@@ -288,22 +288,16 @@ async def create_credentials(
         ProviderName, Path(title="The provider to create credentials for")
     ],
     credentials: Credentials,
-) -> CredentialsMetaResponse:
-    if is_sdk_default(credentials.id):
-        raise HTTPException(
-            status_code=status.HTTP_403_FORBIDDEN,
-            detail="Cannot create credentials with a reserved ID",
-        )
+) -> Credentials:
     credentials.provider = provider
     try:
         await creds_manager.create(user_id, credentials)
-    except Exception:
-        logger.exception("Failed to store credentials")
+    except Exception as e:
         raise HTTPException(
             status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
-            detail="Failed to store credentials",
+            detail=f"Failed to store credentials: {str(e)}",
         )
-    return to_meta_response(credentials)
+    return credentials
 
 
 class CredentialsDeletionResponse(BaseModel):
@@ -338,29 +332,15 @@ async def delete_credentials(
         bool, Query(title="Whether to proceed if any linked webhooks are still in use")
     ] = False,
 ) -> CredentialsDeletionResponse | CredentialsDeletionNeedsConfirmationResponse:
-    if is_sdk_default(cred_id):
-        raise HTTPException(
-            status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
-        )
-    if is_system_credential(cred_id):
-        raise HTTPException(
-            status_code=status.HTTP_403_FORBIDDEN,
-            detail="System-managed credentials cannot be deleted",
-        )
     creds = await creds_manager.store.get_creds_by_id(user_id, cred_id)
     if not creds:
         raise HTTPException(
             status_code=status.HTTP_404_NOT_FOUND, detail="Credentials not found"
         )
-    if not provider_matches(creds.provider, provider):
+    if creds.provider != provider:
         raise HTTPException(
             status_code=status.HTTP_404_NOT_FOUND,
-            detail="Credentials not found",
-        )
-    if creds.is_managed:
-        raise HTTPException(
-            status_code=status.HTTP_403_FORBIDDEN,
-            detail="AutoGPT-managed credentials cannot be deleted",
+            detail="Credentials do not match the specified provider",
         )
 
     try:

autogpt_platform/backend/backend/api/features/integrations/router_test.py

@@ -1,570 +0,0 @@
-"""Tests for credentials API security: no secret leakage, SDK defaults filtered."""
-
-from contextlib import asynccontextmanager
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import fastapi
-import fastapi.testclient
-import pytest
-from pydantic import SecretStr
-
-from backend.api.features.integrations.router import router
-from backend.data.model import (
-    APIKeyCredentials,
-    HostScopedCredentials,
-    OAuth2Credentials,
-    UserPasswordCredentials,
-)
-
-app = fastapi.FastAPI()
-app.include_router(router)
-client = fastapi.testclient.TestClient(app)
-
-TEST_USER_ID = "test-user-id"
-
-
-def _make_api_key_cred(cred_id: str = "cred-123", provider: str = "openai"):
-    return APIKeyCredentials(
-        id=cred_id,
-        provider=provider,
-        title="My API Key",
-        api_key=SecretStr("sk-secret-key-value"),
-    )
-
-
-def _make_oauth2_cred(cred_id: str = "cred-456", provider: str = "github"):
-    return OAuth2Credentials(
-        id=cred_id,
-        provider=provider,
-        title="My OAuth",
-        access_token=SecretStr("ghp_secret_token"),
-        refresh_token=SecretStr("ghp_refresh_secret"),
-        scopes=["repo", "user"],
-        username="testuser",
-    )
-
-
-def _make_user_password_cred(cred_id: str = "cred-789", provider: str = "openai"):
-    return UserPasswordCredentials(
-        id=cred_id,
-        provider=provider,
-        title="My Login",
-        username=SecretStr("admin"),
-        password=SecretStr("s3cret-pass"),
-    )
-
-
-def _make_host_scoped_cred(cred_id: str = "cred-host", provider: str = "openai"):
-    return HostScopedCredentials(
-        id=cred_id,
-        provider=provider,
-        title="Host Cred",
-        host="https://api.example.com",
-        headers={"Authorization": SecretStr("Bearer top-secret")},
-    )
-
-
-def _make_sdk_default_cred(provider: str = "openai"):
-    return APIKeyCredentials(
-        id=f"{provider}-default",
-        provider=provider,
-        title=f"{provider} (default)",
-        api_key=SecretStr("sk-platform-secret-key"),
-    )
-
-
-@pytest.fixture(autouse=True)
-def setup_auth(mock_jwt_user):
-    from autogpt_libs.auth.jwt_utils import get_jwt_payload
-
-    app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
-    yield
-    app.dependency_overrides.clear()
-
-
-class TestGetCredentialReturnsMetaOnly:
-    """GET /{provider}/credentials/{cred_id} must not return secrets."""
-
-    def test_api_key_credential_no_secret(self):
-        cred = _make_api_key_cred()
-        with (
-            patch.object(router, "dependencies", []),
-            patch("backend.api.features.integrations.router.creds_manager") as mock_mgr,
-        ):
-            mock_mgr.get = AsyncMock(return_value=cred)
-            resp = client.get("/openai/credentials/cred-123")
-
-        assert resp.status_code == 200
-        data = resp.json()
-        assert data["id"] == "cred-123"
-        assert data["provider"] == "openai"
-        assert data["type"] == "api_key"
-        assert "api_key" not in data
-        assert "sk-secret-key-value" not in str(data)
-
-    def test_oauth2_credential_no_secret(self):
-        cred = _make_oauth2_cred()
-        with patch(
-            "backend.api.features.integrations.router.creds_manager"
-        ) as mock_mgr:
-            mock_mgr.get = AsyncMock(return_value=cred)
-            resp = client.get("/github/credentials/cred-456")
-
-        assert resp.status_code == 200
-        data = resp.json()
-        assert data["id"] == "cred-456"
-        assert data["scopes"] == ["repo", "user"]
-        assert data["username"] == "testuser"
-        assert "access_token" not in data
-        assert "refresh_token" not in data
-        assert "ghp_" not in str(data)
-
-    def test_user_password_credential_no_secret(self):
-        cred = _make_user_password_cred()
-        with patch(
-            "backend.api.features.integrations.router.creds_manager"
-        ) as mock_mgr:
-            mock_mgr.get = AsyncMock(return_value=cred)
-            resp = client.get("/openai/credentials/cred-789")
-
-        assert resp.status_code == 200
-        data = resp.json()
-        assert data["id"] == "cred-789"
-        assert "password" not in data
-        assert "username" not in data or data["username"] is None
-        assert "s3cret-pass" not in str(data)
-        assert "admin" not in str(data)
-
-    def test_host_scoped_credential_no_secret(self):
-        cred = _make_host_scoped_cred()
-        with patch(
-            "backend.api.features.integrations.router.creds_manager"
-        ) as mock_mgr:
-            mock_mgr.get = AsyncMock(return_value=cred)
-            resp = client.get("/openai/credentials/cred-host")
-
-        assert resp.status_code == 200
-        data = resp.json()
-        assert data["id"] == "cred-host"
-        assert data["host"] == "https://api.example.com"
-        assert "headers" not in data
-        assert "top-secret" not in str(data)
-
-    def test_get_credential_wrong_provider_returns_404(self):
-        """Provider mismatch should return generic 404, not leak credential existence."""
-        cred = _make_api_key_cred(provider="openai")
-        with patch(
-            "backend.api.features.integrations.router.creds_manager"
-        ) as mock_mgr:
-            mock_mgr.get = AsyncMock(return_value=cred)
-            resp = client.get("/github/credentials/cred-123")
-
-        assert resp.status_code == 404
-        assert resp.json()["detail"] == "Credentials not found"
-
-    def test_list_credentials_no_secrets(self):
-        """List endpoint must not leak secrets in any credential."""
-        creds = [_make_api_key_cred(), _make_oauth2_cred()]
-        with patch(
-            "backend.api.features.integrations.router.creds_manager"
-        ) as mock_mgr:
-            mock_mgr.store.get_all_creds = AsyncMock(return_value=creds)
-            resp = client.get("/credentials")
-
-        assert resp.status_code == 200
-        raw = str(resp.json())
-        assert "sk-secret-key-value" not in raw
-        assert "ghp_secret_token" not in raw
-        assert "ghp_refresh_secret" not in raw
-
-
-class TestSdkDefaultCredentialsNotAccessible:
-    """SDK default credentials (ID ending in '-default') must be hidden."""
-
-    def test_get_sdk_default_returns_404(self):
-        with patch(
-            "backend.api.features.integrations.router.creds_manager"
-        ) as mock_mgr:
-            mock_mgr.get = AsyncMock()
-            resp = client.get("/openai/credentials/openai-default")
-
-        assert resp.status_code == 404
-        mock_mgr.get.assert_not_called()
-
-    def test_list_credentials_excludes_sdk_defaults(self):
-        user_cred = _make_api_key_cred()
-        sdk_cred = _make_sdk_default_cred("openai")
-        with patch(
-            "backend.api.features.integrations.router.creds_manager"
-        ) as mock_mgr:
-            mock_mgr.store.get_all_creds = AsyncMock(return_value=[user_cred, sdk_cred])
-            resp = client.get("/credentials")
-
-        assert resp.status_code == 200
-        data = resp.json()
-        ids = [c["id"] for c in data]
-        assert "cred-123" in ids
-        assert "openai-default" not in ids
-
-    def test_list_by_provider_excludes_sdk_defaults(self):
-        user_cred = _make_api_key_cred()
-        sdk_cred = _make_sdk_default_cred("openai")
-        with patch(
-            "backend.api.features.integrations.router.creds_manager"
-        ) as mock_mgr:
-            mock_mgr.store.get_creds_by_provider = AsyncMock(
-                return_value=[user_cred, sdk_cred]
-            )
-            resp = client.get("/openai/credentials")
-
-        assert resp.status_code == 200
-        data = resp.json()
-        ids = [c["id"] for c in data]
-        assert "cred-123" in ids
-        assert "openai-default" not in ids
-
-    def test_delete_sdk_default_returns_404(self):
-        with patch(
-            "backend.api.features.integrations.router.creds_manager"
-        ) as mock_mgr:
-            mock_mgr.store.get_creds_by_id = AsyncMock()
-            resp = client.request("DELETE", "/openai/credentials/openai-default")
-
-        assert resp.status_code == 404
-        mock_mgr.store.get_creds_by_id.assert_not_called()
-
-
-class TestCreateCredentialNoSecretInResponse:
-    """POST /{provider}/credentials must not return secrets."""
-
-    def test_create_api_key_no_secret_in_response(self):
-        with patch(
-            "backend.api.features.integrations.router.creds_manager"
-        ) as mock_mgr:
-            mock_mgr.create = AsyncMock()
-            resp = client.post(
-                "/openai/credentials",
-                json={
-                    "id": "new-cred",
-                    "provider": "openai",
-                    "type": "api_key",
-                    "title": "New Key",
-                    "api_key": "sk-newsecret",
-                },
-            )
-
-        assert resp.status_code == 201
-        data = resp.json()
-        assert data["id"] == "new-cred"
-        assert "api_key" not in data
-        assert "sk-newsecret" not in str(data)
-
-    def test_create_with_sdk_default_id_rejected(self):
-        with patch(
-            "backend.api.features.integrations.router.creds_manager"
-        ) as mock_mgr:
-            mock_mgr.create = AsyncMock()
-            resp = client.post(
-                "/openai/credentials",
-                json={
-                    "id": "openai-default",
-                    "provider": "openai",
-                    "type": "api_key",
-                    "title": "Sneaky",
-                    "api_key": "sk-evil",
-                },
-            )
-
-        assert resp.status_code == 403
-        mock_mgr.create.assert_not_called()
-
-
-class TestManagedCredentials:
-    """AutoGPT-managed credentials cannot be deleted by users."""
-
-    def test_delete_is_managed_returns_403(self):
-        cred = APIKeyCredentials(
-            id="managed-cred-1",
-            provider="agent_mail",
-            title="AgentMail (managed by AutoGPT)",
-            api_key=SecretStr("sk-managed-key"),
-            is_managed=True,
-        )
-        with patch(
-            "backend.api.features.integrations.router.creds_manager"
-        ) as mock_mgr:
-            mock_mgr.store.get_creds_by_id = AsyncMock(return_value=cred)
-            resp = client.request("DELETE", "/agent_mail/credentials/managed-cred-1")
-
-        assert resp.status_code == 403
-        assert "AutoGPT-managed" in resp.json()["detail"]
-
-    def test_list_credentials_includes_is_managed_field(self):
-        managed = APIKeyCredentials(
-            id="managed-1",
-            provider="agent_mail",
-            title="AgentMail (managed)",
-            api_key=SecretStr("sk-key"),
-            is_managed=True,
-        )
-        regular = APIKeyCredentials(
-            id="regular-1",
-            provider="openai",
-            title="My Key",
-            api_key=SecretStr("sk-key"),
-        )
-        with patch(
-            "backend.api.features.integrations.router.creds_manager"
-        ) as mock_mgr:
-            mock_mgr.store.get_all_creds = AsyncMock(return_value=[managed, regular])
-            resp = client.get("/credentials")
-
-        assert resp.status_code == 200
-        data = resp.json()
-        managed_cred = next(c for c in data if c["id"] == "managed-1")
-        regular_cred = next(c for c in data if c["id"] == "regular-1")
-        assert managed_cred["is_managed"] is True
-        assert regular_cred["is_managed"] is False
-
-
-# ---------------------------------------------------------------------------
-# Managed credential provisioning infrastructure
-# ---------------------------------------------------------------------------
-
-
-def _make_managed_cred(
-    provider: str = "agent_mail", pod_id: str = "pod-abc"
-) -> APIKeyCredentials:
-    return APIKeyCredentials(
-        id="managed-auto",
-        provider=provider,
-        title="AgentMail (managed by AutoGPT)",
-        api_key=SecretStr("sk-pod-key"),
-        is_managed=True,
-        metadata={"pod_id": pod_id},
-    )
-
-
-def _make_store_mock(**kwargs) -> MagicMock:
-    """Create a store mock with a working async ``locks()`` context manager."""
-
-    @asynccontextmanager
-    async def _noop_locked(key):
-        yield
-
-    locks_obj = MagicMock()
-    locks_obj.locked = _noop_locked
-
-    store = MagicMock(**kwargs)
-    store.locks = AsyncMock(return_value=locks_obj)
-    return store
-
-
-class TestEnsureManagedCredentials:
-    """Unit tests for the ensure/cleanup helpers in managed_credentials.py."""
-
-    @pytest.mark.asyncio
-    async def test_provisions_when_missing(self):
-        """Provider.provision() is called when no managed credential exists."""
-        from backend.integrations.managed_credentials import (
-            _PROVIDERS,
-            _provisioned_users,
-            ensure_managed_credentials,
-        )
-
-        cred = _make_managed_cred()
-        provider = MagicMock()
-        provider.provider_name = "test_provider"
-        provider.is_available = AsyncMock(return_value=True)
-        provider.provision = AsyncMock(return_value=cred)
-
-        store = _make_store_mock()
-        store.has_managed_credential = AsyncMock(return_value=False)
-        store.add_managed_credential = AsyncMock()
-
-        saved = dict(_PROVIDERS)
-        _PROVIDERS.clear()
-        _PROVIDERS["test_provider"] = provider
-        _provisioned_users.pop("user-1", None)
-        try:
-            await ensure_managed_credentials("user-1", store)
-        finally:
-            _PROVIDERS.clear()
-            _PROVIDERS.update(saved)
-            _provisioned_users.pop("user-1", None)
-
-        provider.provision.assert_awaited_once_with("user-1")
-        store.add_managed_credential.assert_awaited_once_with("user-1", cred)
-
-    @pytest.mark.asyncio
-    async def test_skips_when_already_exists(self):
-        """Provider.provision() is NOT called when managed credential exists."""
-        from backend.integrations.managed_credentials import (
-            _PROVIDERS,
-            _provisioned_users,
-            ensure_managed_credentials,
-        )
-
-        provider = MagicMock()
-        provider.provider_name = "test_provider"
-        provider.is_available = AsyncMock(return_value=True)
-        provider.provision = AsyncMock()
-
-        store = _make_store_mock()
-        store.has_managed_credential = AsyncMock(return_value=True)
-
-        saved = dict(_PROVIDERS)
-        _PROVIDERS.clear()
-        _PROVIDERS["test_provider"] = provider
-        _provisioned_users.pop("user-1", None)
-        try:
-            await ensure_managed_credentials("user-1", store)
-        finally:
-            _PROVIDERS.clear()
-            _PROVIDERS.update(saved)
-            _provisioned_users.pop("user-1", None)
-
-        provider.provision.assert_not_awaited()
-
-    @pytest.mark.asyncio
-    async def test_skips_when_unavailable(self):
-        """Provider.provision() is NOT called when provider is not available."""
-        from backend.integrations.managed_credentials import (
-            _PROVIDERS,
-            _provisioned_users,
-            ensure_managed_credentials,
-        )
-
-        provider = MagicMock()
-        provider.provider_name = "test_provider"
-        provider.is_available = AsyncMock(return_value=False)
-        provider.provision = AsyncMock()
-
-        store = _make_store_mock()
-        store.has_managed_credential = AsyncMock()
-
-        saved = dict(_PROVIDERS)
-        _PROVIDERS.clear()
-        _PROVIDERS["test_provider"] = provider
-        _provisioned_users.pop("user-1", None)
-        try:
-            await ensure_managed_credentials("user-1", store)
-        finally:
-            _PROVIDERS.clear()
-            _PROVIDERS.update(saved)
-            _provisioned_users.pop("user-1", None)
-
-        provider.provision.assert_not_awaited()
-        store.has_managed_credential.assert_not_awaited()
-
-    @pytest.mark.asyncio
-    async def test_provision_failure_does_not_propagate(self):
-        """A failed provision is logged but does not raise."""
-        from backend.integrations.managed_credentials import (
-            _PROVIDERS,
-            _provisioned_users,
-            ensure_managed_credentials,
-        )
-
-        provider = MagicMock()
-        provider.provider_name = "test_provider"
-        provider.is_available = AsyncMock(return_value=True)
-        provider.provision = AsyncMock(side_effect=RuntimeError("boom"))
-
-        store = _make_store_mock()
-        store.has_managed_credential = AsyncMock(return_value=False)
-
-        saved = dict(_PROVIDERS)
-        _PROVIDERS.clear()
-        _PROVIDERS["test_provider"] = provider
-        _provisioned_users.pop("user-1", None)
-        try:
-            await ensure_managed_credentials("user-1", store)
-        finally:
-            _PROVIDERS.clear()
-            _PROVIDERS.update(saved)
-            _provisioned_users.pop("user-1", None)
-
-        # No exception raised — provisioning failure is swallowed.
-
-
-class TestCleanupManagedCredentials:
-    """Unit tests for cleanup_managed_credentials."""
-
-    @pytest.mark.asyncio
-    async def test_calls_deprovision_for_managed_creds(self):
-        from backend.integrations.managed_credentials import (
-            _PROVIDERS,
-            cleanup_managed_credentials,
-        )
-
-        cred = _make_managed_cred()
-        provider = MagicMock()
-        provider.provider_name = "agent_mail"
-        provider.deprovision = AsyncMock()
-
-        store = MagicMock()
-        store.get_all_creds = AsyncMock(return_value=[cred])
-
-        saved = dict(_PROVIDERS)
-        _PROVIDERS.clear()
-        _PROVIDERS["agent_mail"] = provider
-        try:
-            await cleanup_managed_credentials("user-1", store)
-        finally:
-            _PROVIDERS.clear()
-            _PROVIDERS.update(saved)
-
-        provider.deprovision.assert_awaited_once_with("user-1", cred)
-
-    @pytest.mark.asyncio
-    async def test_skips_non_managed_creds(self):
-        from backend.integrations.managed_credentials import (
-            _PROVIDERS,
-            cleanup_managed_credentials,
-        )
-
-        regular = _make_api_key_cred()
-        provider = MagicMock()
-        provider.provider_name = "openai"
-        provider.deprovision = AsyncMock()
-
-        store = MagicMock()
-        store.get_all_creds = AsyncMock(return_value=[regular])
-
-        saved = dict(_PROVIDERS)
-        _PROVIDERS.clear()
-        _PROVIDERS["openai"] = provider
-        try:
-            await cleanup_managed_credentials("user-1", store)
-        finally:
-            _PROVIDERS.clear()
-            _PROVIDERS.update(saved)
-
-        provider.deprovision.assert_not_awaited()
-
-    @pytest.mark.asyncio
-    async def test_deprovision_failure_does_not_propagate(self):
-        from backend.integrations.managed_credentials import (
-            _PROVIDERS,
-            cleanup_managed_credentials,
-        )
-
-        cred = _make_managed_cred()
-        provider = MagicMock()
-        provider.provider_name = "agent_mail"
-        provider.deprovision = AsyncMock(side_effect=RuntimeError("boom"))
-
-        store = MagicMock()
-        store.get_all_creds = AsyncMock(return_value=[cred])
-
-        saved = dict(_PROVIDERS)
-        _PROVIDERS.clear()
-        _PROVIDERS["agent_mail"] = provider
-        try:
-            await cleanup_managed_credentials("user-1", store)
-        finally:
-            _PROVIDERS.clear()
-            _PROVIDERS.update(saved)
-
-        # No exception raised — cleanup failure is swallowed.

autogpt_platform/backend/backend/api/features/library/_add_to_library.py

@@ -1,120 +0,0 @@
-"""Shared logic for adding store agents to a user's library.
-
-Both `add_store_agent_to_library` and `add_store_agent_to_library_as_admin`
-delegate to these helpers so the duplication-prone create/restore/dedup
-logic lives in exactly one place.
-"""
-
-import logging
-
-import prisma.errors
-import prisma.models
-
-import backend.api.features.library.model as library_model
-import backend.data.graph as graph_db
-from backend.data.graph import GraphModel, GraphSettings
-from backend.data.includes import library_agent_include
-from backend.util.exceptions import NotFoundError
-from backend.util.json import SafeJson
-
-logger = logging.getLogger(__name__)
-
-
-async def resolve_graph_for_library(
-    store_listing_version_id: str,
-    user_id: str,
-    *,
-    admin: bool,
-) -> GraphModel:
-    """Look up a StoreListingVersion and resolve its graph.
-
-    When ``admin=True``, uses ``get_graph_as_admin`` to bypass the marketplace
-    APPROVED-only check.  Otherwise uses the regular ``get_graph``.
-    """
-    slv = await prisma.models.StoreListingVersion.prisma().find_unique(
-        where={"id": store_listing_version_id}, include={"AgentGraph": True}
-    )
-    if not slv or not slv.AgentGraph:
-        raise NotFoundError(
-            f"Store listing version {store_listing_version_id} not found or invalid"
-        )
-
-    ag = slv.AgentGraph
-    if admin:
-        graph_model = await graph_db.get_graph_as_admin(
-            graph_id=ag.id, version=ag.version, user_id=user_id
-        )
-    else:
-        graph_model = await graph_db.get_graph(
-            graph_id=ag.id, version=ag.version, user_id=user_id
-        )
-
-    if not graph_model:
-        raise NotFoundError(f"Graph #{ag.id} v{ag.version} not found or accessible")
-    return graph_model
-
-
-async def add_graph_to_library(
-    store_listing_version_id: str,
-    graph_model: GraphModel,
-    user_id: str,
-) -> library_model.LibraryAgent:
-    """Check existing / restore soft-deleted / create new LibraryAgent.
-
-    Uses a create-then-catch-UniqueViolationError-then-update pattern on
-    the (userId, agentGraphId, agentGraphVersion) composite unique constraint.
-    This is more robust than ``upsert`` because Prisma's upsert atomicity
-    guarantees are not well-documented for all versions.
-    """
-    settings_json = SafeJson(GraphSettings.from_graph(graph_model).model_dump())
-    _include = library_agent_include(
-        user_id, include_nodes=False, include_executions=False
-    )
-
-    try:
-        added_agent = await prisma.models.LibraryAgent.prisma().create(
-            data={
-                "User": {"connect": {"id": user_id}},
-                "AgentGraph": {
-                    "connect": {
-                        "graphVersionId": {
-                            "id": graph_model.id,
-                            "version": graph_model.version,
-                        }
-                    }
-                },
-                "isCreatedByUser": False,
-                "useGraphIsActiveVersion": False,
-                "settings": settings_json,
-            },
-            include=_include,
-        )
-    except prisma.errors.UniqueViolationError:
-        # Already exists — update to restore if previously soft-deleted/archived
-        added_agent = await prisma.models.LibraryAgent.prisma().update(
-            where={
-                "userId_agentGraphId_agentGraphVersion": {
-                    "userId": user_id,
-                    "agentGraphId": graph_model.id,
-                    "agentGraphVersion": graph_model.version,
-                }
-            },
-            data={
-                "isDeleted": False,
-                "isArchived": False,
-                "settings": settings_json,
-            },
-            include=_include,
-        )
-        if added_agent is None:
-            raise NotFoundError(
-                f"LibraryAgent for graph #{graph_model.id} "
-                f"v{graph_model.version} not found after UniqueViolationError"
-            )
-
-    logger.debug(
-        f"Added graph #{graph_model.id} v{graph_model.version} "
-        f"for store listing version #{store_listing_version_id} "
-        f"to library for user #{user_id}"
-    )
-    return library_model.LibraryAgent.from_db(added_agent)

autogpt_platform/backend/backend/api/features/library/_add_to_library_test.py

@@ -1,80 +0,0 @@
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import prisma.errors
-import pytest
-
-from ._add_to_library import add_graph_to_library
-
-
-@pytest.mark.asyncio
-async def test_add_graph_to_library_create_new_agent() -> None:
-    """When no matching LibraryAgent exists, create inserts a new one."""
-    graph_model = MagicMock(id="graph-id", version=2, nodes=[])
-    created_agent = MagicMock(name="CreatedLibraryAgent")
-    converted_agent = MagicMock(name="ConvertedLibraryAgent")
-
-    with (
-        patch(
-            "backend.api.features.library._add_to_library.prisma.models.LibraryAgent.prisma"
-        ) as mock_prisma,
-        patch(
-            "backend.api.features.library._add_to_library.library_model.LibraryAgent.from_db",
-            return_value=converted_agent,
-        ) as mock_from_db,
-    ):
-        mock_prisma.return_value.create = AsyncMock(return_value=created_agent)
-
-        result = await add_graph_to_library("slv-id", graph_model, "user-id")
-
-    assert result is converted_agent
-    mock_from_db.assert_called_once_with(created_agent)
-    # Verify create was called with correct data
-    create_call = mock_prisma.return_value.create.call_args
-    create_data = create_call.kwargs["data"]
-    assert create_data["User"] == {"connect": {"id": "user-id"}}
-    assert create_data["AgentGraph"] == {
-        "connect": {"graphVersionId": {"id": "graph-id", "version": 2}}
-    }
-    assert create_data["isCreatedByUser"] is False
-    assert create_data["useGraphIsActiveVersion"] is False
-
-
-@pytest.mark.asyncio
-async def test_add_graph_to_library_unique_violation_updates_existing() -> None:
-    """UniqueViolationError on create falls back to update."""
-    graph_model = MagicMock(id="graph-id", version=2, nodes=[])
-    updated_agent = MagicMock(name="UpdatedLibraryAgent")
-    converted_agent = MagicMock(name="ConvertedLibraryAgent")
-
-    with (
-        patch(
-            "backend.api.features.library._add_to_library.prisma.models.LibraryAgent.prisma"
-        ) as mock_prisma,
-        patch(
-            "backend.api.features.library._add_to_library.library_model.LibraryAgent.from_db",
-            return_value=converted_agent,
-        ) as mock_from_db,
-    ):
-        mock_prisma.return_value.create = AsyncMock(
-            side_effect=prisma.errors.UniqueViolationError(
-                MagicMock(), message="unique constraint"
-            )
-        )
-        mock_prisma.return_value.update = AsyncMock(return_value=updated_agent)
-
-        result = await add_graph_to_library("slv-id", graph_model, "user-id")
-
-    assert result is converted_agent
-    mock_from_db.assert_called_once_with(updated_agent)
-    # Verify update was called with correct where and data
-    update_call = mock_prisma.return_value.update.call_args
-    assert update_call.kwargs["where"] == {
-        "userId_agentGraphId_agentGraphVersion": {
-            "userId": "user-id",
-            "agentGraphId": "graph-id",
-            "agentGraphVersion": 2,
-        }
-    }
-    update_data = update_call.kwargs["data"]
-    assert update_data["isDeleted"] is False
-    assert update_data["isArchived"] is False

autogpt_platform/backend/backend/api/features/library/db.py

@@ -336,15 +336,12 @@ async def get_library_agent_by_graph_id(
     user_id: str,
     graph_id: str,
     graph_version: Optional[int] = None,
-    include_archived: bool = False,
 ) -> library_model.LibraryAgent | None:
     filter: prisma.types.LibraryAgentWhereInput = {
         "agentGraphId": graph_id,
         "userId": user_id,
         "isDeleted": False,
     }
-    if not include_archived:
-        filter["isArchived"] = False
     if graph_version is not None:
         filter["agentGraphVersion"] = graph_version
 
@@ -436,53 +433,32 @@ async def create_library_agent(
     async with transaction() as tx:
         library_agents = await asyncio.gather(
             *(
-                prisma.models.LibraryAgent.prisma(tx).upsert(
-                    where={
-                        "userId_agentGraphId_agentGraphVersion": {
-                            "userId": user_id,
-                            "agentGraphId": graph_entry.id,
-                            "agentGraphVersion": graph_entry.version,
-                        }
-                    },
-                    data={
-                        "create": prisma.types.LibraryAgentCreateInput(
-                            isCreatedByUser=(user_id == graph.user_id),
-                            useGraphIsActiveVersion=True,
-                            User={"connect": {"id": user_id}},
-                            AgentGraph={
-                                "connect": {
-                                    "graphVersionId": {
-                                        "id": graph_entry.id,
-                                        "version": graph_entry.version,
-                                    }
+                prisma.models.LibraryAgent.prisma(tx).create(
+                    data=prisma.types.LibraryAgentCreateInput(
+                        isCreatedByUser=(user_id == user_id),
+                        useGraphIsActiveVersion=True,
+                        User={"connect": {"id": user_id}},
+                        AgentGraph={
+                            "connect": {
+                                "graphVersionId": {
+                                    "id": graph_entry.id,
+                                    "version": graph_entry.version,
                                 }
-                            },
-                            settings=SafeJson(
-                                GraphSettings.from_graph(
-                                    graph_entry,
-                                    hitl_safe_mode=hitl_safe_mode,
-                                    sensitive_action_safe_mode=sensitive_action_safe_mode,
-                                ).model_dump()
-                            ),
-                            **(
-                                {"Folder": {"connect": {"id": folder_id}}}
-                                if folder_id and graph_entry is graph
-                                else {}
-                            ),
-                        ),
-                        "update": {
-                            "isDeleted": False,
-                            "isArchived": False,
-                            "useGraphIsActiveVersion": True,
-                            "settings": SafeJson(
-                                GraphSettings.from_graph(
-                                    graph_entry,
-                                    hitl_safe_mode=hitl_safe_mode,
-                                    sensitive_action_safe_mode=sensitive_action_safe_mode,
-                                ).model_dump()
-                            ),
+                            }
                         },
-                    },
+                        settings=SafeJson(
+                            GraphSettings.from_graph(
+                                graph_entry,
+                                hitl_safe_mode=hitl_safe_mode,
+                                sensitive_action_safe_mode=sensitive_action_safe_mode,
+                            ).model_dump()
+                        ),
+                        **(
+                            {"Folder": {"connect": {"id": folder_id}}}
+                            if folder_id and graph_entry is graph
+                            else {}
+                        ),
+                    ),
                     include=library_agent_include(
                         user_id, include_nodes=False, include_executions=False
                     ),
@@ -606,9 +582,7 @@ async def update_graph_in_library(
 
     created_graph = await graph_db.create_graph(graph_model, user_id)
 
-    library_agent = await get_library_agent_by_graph_id(
-        user_id, created_graph.id, include_archived=True
-    )
+    library_agent = await get_library_agent_by_graph_id(user_id, created_graph.id)
     if not library_agent:
         raise NotFoundError(f"Library agent not found for graph {created_graph.id}")
 
@@ -844,38 +818,92 @@ async def delete_library_agent_by_graph_id(graph_id: str, user_id: str) -> None:
 async def add_store_agent_to_library(
     store_listing_version_id: str, user_id: str
 ) -> library_model.LibraryAgent:
-    """Adds a marketplace agent to the user’s library.
-
-    See also: `add_store_agent_to_library_as_admin()` which uses
-    `get_graph_as_admin` to bypass marketplace status checks for admin review.
     """
-    from ._add_to_library import add_graph_to_library, resolve_graph_for_library
+    Adds an agent from a store listing version to the user's library if they don't already have it.
 
+    Args:
+        store_listing_version_id: The ID of the store listing version containing the agent.
+        user_id: The user’s library to which the agent is being added.
+
+    Returns:
+        The newly created LibraryAgent if successfully added, the existing corresponding one if any.
+
+    Raises:
+        NotFoundError: If the store listing or associated agent is not found.
+        DatabaseError: If there's an issue creating the LibraryAgent record.
+    """
     logger.debug(
         f"Adding agent from store listing version #{store_listing_version_id} "
         f"to library for user #{user_id}"
     )
-    graph_model = await resolve_graph_for_library(
-        store_listing_version_id, user_id, admin=False
-    )
-    return await add_graph_to_library(store_listing_version_id, graph_model, user_id)
 
-
-async def add_store_agent_to_library_as_admin(
-    store_listing_version_id: str, user_id: str
-) -> library_model.LibraryAgent:
-    """Admin variant that uses `get_graph_as_admin` to bypass marketplace
-    APPROVED-only checks, allowing admins to add pending agents for review."""
-    from ._add_to_library import add_graph_to_library, resolve_graph_for_library
-
-    logger.warning(
-        f"ADMIN adding agent from store listing version "
-        f"#{store_listing_version_id} to library for user #{user_id}"
+    store_listing_version = (
+        await prisma.models.StoreListingVersion.prisma().find_unique(
+            where={"id": store_listing_version_id}, include={"AgentGraph": True}
+        )
     )
-    graph_model = await resolve_graph_for_library(
-        store_listing_version_id, user_id, admin=True
+    if not store_listing_version or not store_listing_version.AgentGraph:
+        logger.warning(f"Store listing version not found: {store_listing_version_id}")
+        raise NotFoundError(
+            f"Store listing version {store_listing_version_id} not found or invalid"
+        )
+
+    graph = store_listing_version.AgentGraph
+
+    # Convert to GraphModel to check for HITL blocks
+    graph_model = await graph_db.get_graph(
+        graph_id=graph.id,
+        version=graph.version,
+        user_id=user_id,
+        include_subgraphs=False,
     )
-    return await add_graph_to_library(store_listing_version_id, graph_model, user_id)
+    if not graph_model:
+        raise NotFoundError(
+            f"Graph #{graph.id} v{graph.version} not found or accessible"
+        )
+
+    # Check if user already has this agent (non-deleted)
+    if existing := await get_library_agent_by_graph_id(
+        user_id, graph.id, graph.version
+    ):
+        return existing
+
+    # Check for soft-deleted version and restore it
+    deleted_agent = await prisma.models.LibraryAgent.prisma().find_unique(
+        where={
+            "userId_agentGraphId_agentGraphVersion": {
+                "userId": user_id,
+                "agentGraphId": graph.id,
+                "agentGraphVersion": graph.version,
+            }
+        },
+    )
+    if deleted_agent and deleted_agent.isDeleted:
+        return await update_library_agent(deleted_agent.id, user_id, is_deleted=False)
+
+    # Create LibraryAgent entry
+    added_agent = await prisma.models.LibraryAgent.prisma().create(
+        data={
+            "User": {"connect": {"id": user_id}},
+            "AgentGraph": {
+                "connect": {
+                    "graphVersionId": {"id": graph.id, "version": graph.version}
+                }
+            },
+            "isCreatedByUser": False,
+            "useGraphIsActiveVersion": False,
+            "settings": SafeJson(GraphSettings.from_graph(graph_model).model_dump()),
+        },
+        include=library_agent_include(
+            user_id, include_nodes=False, include_executions=False
+        ),
+    )
+    logger.debug(
+        f"Added graph #{graph.id} v{graph.version}"
+        f"for store listing version #{store_listing_version.id} "
+        f"to library for user #{user_id}"
+    )
+    return library_model.LibraryAgent.from_db(added_agent)
 
 
 ##############################################

autogpt_platform/backend/backend/api/features/library/db_test.py

@@ -1,6 +1,4 @@
-from contextlib import asynccontextmanager
 from datetime import datetime
-from unittest.mock import AsyncMock, MagicMock, patch
 
 import prisma.enums
 import prisma.models
@@ -87,6 +85,10 @@ async def test_get_library_agents(mocker):
 async def test_add_agent_to_library(mocker):
     await connect()
 
+    # Mock the transaction context
+    mock_transaction = mocker.patch("backend.api.features.library.db.transaction")
+    mock_transaction.return_value.__aenter__ = mocker.AsyncMock(return_value=None)
+    mock_transaction.return_value.__aexit__ = mocker.AsyncMock(return_value=None)
     # Mock data
     mock_store_listing_data = prisma.models.StoreListingVersion(
         id="version123",
@@ -141,18 +143,15 @@ async def test_add_agent_to_library(mocker):
     )
 
     mock_library_agent = mocker.patch("prisma.models.LibraryAgent.prisma")
+    mock_library_agent.return_value.find_first = mocker.AsyncMock(return_value=None)
+    mock_library_agent.return_value.find_unique = mocker.AsyncMock(return_value=None)
     mock_library_agent.return_value.create = mocker.AsyncMock(
         return_value=mock_library_agent_data
     )
 
-    # Mock graph_db.get_graph function that's called in resolve_graph_for_library
-    # (lives in _add_to_library.py after refactor, not db.py)
-    mock_graph_db = mocker.patch(
-        "backend.api.features.library._add_to_library.graph_db"
-    )
+    # Mock graph_db.get_graph function that's called to check for HITL blocks
+    mock_graph_db = mocker.patch("backend.api.features.library.db.graph_db")
     mock_graph_model = mocker.Mock()
-    mock_graph_model.id = "agent1"
-    mock_graph_model.version = 1
     mock_graph_model.nodes = (
         []
     )  # Empty list so _has_human_in_the_loop_blocks returns False
@@ -171,27 +170,37 @@ async def test_add_agent_to_library(mocker):
     mock_store_listing_version.return_value.find_unique.assert_called_once_with(
         where={"id": "version123"}, include={"AgentGraph": True}
     )
+    mock_library_agent.return_value.find_unique.assert_called_once_with(
+        where={
+            "userId_agentGraphId_agentGraphVersion": {
+                "userId": "test-user",
+                "agentGraphId": "agent1",
+                "agentGraphVersion": 1,
+            }
+        },
+    )
     # Check that create was called with the expected data including settings
     create_call_args = mock_library_agent.return_value.create.call_args
     assert create_call_args is not None
 
-    # Verify the create data structure
-    create_data = create_call_args.kwargs["data"]
-    expected_create = {
+    # Verify the main structure
+    expected_data = {
         "User": {"connect": {"id": "test-user"}},
         "AgentGraph": {"connect": {"graphVersionId": {"id": "agent1", "version": 1}}},
         "isCreatedByUser": False,
-        "useGraphIsActiveVersion": False,
     }
-    for key, value in expected_create.items():
-        assert create_data[key] == value
+
+    actual_data = create_call_args[1]["data"]
+    # Check that all expected fields are present
+    for key, value in expected_data.items():
+        assert actual_data[key] == value
 
     # Check that settings field is present and is a SafeJson object
-    assert "settings" in create_data
-    assert hasattr(create_data["settings"], "__class__")  # Should be a SafeJson object
+    assert "settings" in actual_data
+    assert hasattr(actual_data["settings"], "__class__")  # Should be a SafeJson object
 
     # Check include parameter
-    assert create_call_args.kwargs["include"] == library_agent_include(
+    assert create_call_args[1]["include"] == library_agent_include(
         "test-user", include_nodes=False, include_executions=False
     )
 
@@ -215,141 +224,3 @@ async def test_add_agent_to_library_not_found(mocker):
     mock_store_listing_version.return_value.find_unique.assert_called_once_with(
         where={"id": "version123"}, include={"AgentGraph": True}
     )
-
-
-@pytest.mark.asyncio
-async def test_get_library_agent_by_graph_id_excludes_archived(mocker):
-    mock_library_agent = mocker.patch("prisma.models.LibraryAgent.prisma")
-    mock_library_agent.return_value.find_first = mocker.AsyncMock(return_value=None)
-
-    result = await db.get_library_agent_by_graph_id("test-user", "agent1", 7)
-
-    assert result is None
-    mock_library_agent.return_value.find_first.assert_called_once()
-    where = mock_library_agent.return_value.find_first.call_args.kwargs["where"]
-    assert where == {
-        "agentGraphId": "agent1",
-        "userId": "test-user",
-        "isDeleted": False,
-        "isArchived": False,
-        "agentGraphVersion": 7,
-    }
-
-
-@pytest.mark.asyncio
-async def test_get_library_agent_by_graph_id_can_include_archived(mocker):
-    mock_library_agent = mocker.patch("prisma.models.LibraryAgent.prisma")
-    mock_library_agent.return_value.find_first = mocker.AsyncMock(return_value=None)
-
-    result = await db.get_library_agent_by_graph_id(
-        "test-user",
-        "agent1",
-        7,
-        include_archived=True,
-    )
-
-    assert result is None
-    mock_library_agent.return_value.find_first.assert_called_once()
-    where = mock_library_agent.return_value.find_first.call_args.kwargs["where"]
-    assert where == {
-        "agentGraphId": "agent1",
-        "userId": "test-user",
-        "isDeleted": False,
-        "agentGraphVersion": 7,
-    }
-
-
-@pytest.mark.asyncio
-async def test_update_graph_in_library_allows_archived_library_agent(mocker):
-    graph = mocker.Mock(id="graph-id")
-    existing_version = mocker.Mock(version=1, is_active=True)
-    graph_model = mocker.Mock()
-    created_graph = mocker.Mock(id="graph-id", version=2, is_active=False)
-    current_library_agent = mocker.Mock()
-    updated_library_agent = mocker.Mock()
-
-    mocker.patch(
-        "backend.api.features.library.db.graph_db.get_graph_all_versions",
-        new=mocker.AsyncMock(return_value=[existing_version]),
-    )
-    mocker.patch(
-        "backend.api.features.library.db.graph_db.make_graph_model",
-        return_value=graph_model,
-    )
-    mocker.patch(
-        "backend.api.features.library.db.graph_db.create_graph",
-        new=mocker.AsyncMock(return_value=created_graph),
-    )
-    mock_get_library_agent = mocker.patch(
-        "backend.api.features.library.db.get_library_agent_by_graph_id",
-        new=mocker.AsyncMock(return_value=current_library_agent),
-    )
-    mock_update_library_agent = mocker.patch(
-        "backend.api.features.library.db.update_library_agent_version_and_settings",
-        new=mocker.AsyncMock(return_value=updated_library_agent),
-    )
-
-    result_graph, result_library_agent = await db.update_graph_in_library(
-        graph,
-        "test-user",
-    )
-
-    assert result_graph is created_graph
-    assert result_library_agent is updated_library_agent
-    assert graph.version == 2
-    graph_model.reassign_ids.assert_called_once_with(
-        user_id="test-user", reassign_graph_id=False
-    )
-    mock_get_library_agent.assert_awaited_once_with(
-        "test-user",
-        "graph-id",
-        include_archived=True,
-    )
-    mock_update_library_agent.assert_awaited_once_with("test-user", created_graph)
-
-
-@pytest.mark.asyncio
-async def test_create_library_agent_uses_upsert():
-    """create_library_agent should use upsert (not create) to handle duplicates."""
-    mock_graph = MagicMock()
-    mock_graph.id = "graph-1"
-    mock_graph.version = 1
-    mock_graph.user_id = "user-1"
-    mock_graph.nodes = []
-    mock_graph.sub_graphs = []
-
-    mock_upserted = MagicMock(name="UpsertedLibraryAgent")
-
-    @asynccontextmanager
-    async def fake_tx():
-        yield None
-
-    with (
-        patch("backend.api.features.library.db.transaction", fake_tx),
-        patch("prisma.models.LibraryAgent.prisma") as mock_prisma,
-        patch(
-            "backend.api.features.library.db.add_generated_agent_image",
-            new=AsyncMock(),
-        ),
-        patch(
-            "backend.api.features.library.model.LibraryAgent.from_db",
-            return_value=MagicMock(),
-        ),
-    ):
-        mock_prisma.return_value.upsert = AsyncMock(return_value=mock_upserted)
-
-        result = await db.create_library_agent(mock_graph, "user-1")
-
-    assert len(result) == 1
-    upsert_call = mock_prisma.return_value.upsert.call_args
-    assert upsert_call is not None
-    # Verify the upsert where clause uses the composite unique key
-    where = upsert_call.kwargs["where"]
-    assert "userId_agentGraphId_agentGraphVersion" in where
-    # Verify the upsert data has both create and update branches
-    data = upsert_call.kwargs["data"]
-    assert "create" in data
-    assert "update" in data
-    # Verify update branch restores soft-deleted/archived agents
-    assert data["update"]["isDeleted"] is False
-    assert data["update"]["isArchived"] is False

autogpt_platform/backend/backend/api/features/oauth_test.py

@@ -12,7 +12,6 @@ Tests cover:
 5. Complete OAuth flow end-to-end
 """
 
-import asyncio
 import base64
 import hashlib
 import secrets
@@ -59,27 +58,14 @@ async def test_user(server, test_user_id: str):
 
     yield test_user_id
 
-    # Cleanup - delete in correct order due to foreign key constraints.
-    # Wrap in try/except because the event loop or Prisma engine may already
-    # be closed during session teardown on Python 3.12+.
-    try:
-        await asyncio.gather(
-            PrismaOAuthAccessToken.prisma().delete_many(where={"userId": test_user_id}),
-            PrismaOAuthRefreshToken.prisma().delete_many(
-                where={"userId": test_user_id}
-            ),
-            PrismaOAuthAuthorizationCode.prisma().delete_many(
-                where={"userId": test_user_id}
-            ),
-        )
-        await asyncio.gather(
-            PrismaOAuthApplication.prisma().delete_many(
-                where={"ownerId": test_user_id}
-            ),
-            PrismaUser.prisma().delete(where={"id": test_user_id}),
-        )
-    except RuntimeError:
-        pass
+    # Cleanup - delete in correct order due to foreign key constraints
+    await PrismaOAuthAccessToken.prisma().delete_many(where={"userId": test_user_id})
+    await PrismaOAuthRefreshToken.prisma().delete_many(where={"userId": test_user_id})
+    await PrismaOAuthAuthorizationCode.prisma().delete_many(
+        where={"userId": test_user_id}
+    )
+    await PrismaOAuthApplication.prisma().delete_many(where={"ownerId": test_user_id})
+    await PrismaUser.prisma().delete(where={"id": test_user_id})
 
 
 @pytest_asyncio.fixture

autogpt_platform/backend/backend/api/features/store/db.py

@@ -9,7 +9,7 @@ import prisma.errors
 import prisma.models
 import prisma.types
 
-from backend.data.db import query_raw_with_schema, transaction
+from backend.data.db import transaction
 from backend.data.graph import (
     GraphModel,
     GraphModelWithoutNodes,
@@ -104,8 +104,7 @@ async def get_store_agents(
                 # search_used_hybrid remains False, will use fallback path below
 
             # Convert hybrid search results (dict format) if hybrid succeeded
-            # Fall through to direct DB search if hybrid returned nothing
-            if search_used_hybrid and agents:
+            if search_used_hybrid:
                 total_pages = (total + page_size - 1) // page_size
                 store_agents: list[store_model.StoreAgent] = []
                 for agent in agents:
@@ -131,20 +130,52 @@ async def get_store_agents(
                         )
                         continue
 
-        if not search_used_hybrid or not agents:
-            # Fallback path: direct DB query with optional tsvector search.
-            # This mirrors the original pre-hybrid-search implementation.
-            store_agents, total = await _fallback_store_agent_search(
-                search_query=search_query,
-                featured=featured,
-                creators=creators,
-                category=category,
-                sorted_by=sorted_by,
-                page=page,
-                page_size=page_size,
+        if not search_used_hybrid:
+            # Fallback path - use basic search or no search
+            where_clause: prisma.types.StoreAgentWhereInput = {"is_available": True}
+            if featured:
+                where_clause["featured"] = featured
+            if creators:
+                where_clause["creator_username"] = {"in": creators}
+            if category:
+                where_clause["categories"] = {"has": category}
+
+            # Add basic text search if search_query provided but hybrid failed
+            if search_query:
+                where_clause["OR"] = [
+                    {"agent_name": {"contains": search_query, "mode": "insensitive"}},
+                    {"sub_heading": {"contains": search_query, "mode": "insensitive"}},
+                    {"description": {"contains": search_query, "mode": "insensitive"}},
+                ]
+
+            order_by = []
+            if sorted_by == StoreAgentsSortOptions.RATING:
+                order_by.append({"rating": "desc"})
+            elif sorted_by == StoreAgentsSortOptions.RUNS:
+                order_by.append({"runs": "desc"})
+            elif sorted_by == StoreAgentsSortOptions.NAME:
+                order_by.append({"agent_name": "asc"})
+            elif sorted_by == StoreAgentsSortOptions.UPDATED_AT:
+                order_by.append({"updated_at": "desc"})
+
+            db_agents = await prisma.models.StoreAgent.prisma().find_many(
+                where=where_clause,
+                order=order_by,
+                skip=(page - 1) * page_size,
+                take=page_size,
             )
+
+            total = await prisma.models.StoreAgent.prisma().count(where=where_clause)
             total_pages = (total + page_size - 1) // page_size
 
+            store_agents: list[store_model.StoreAgent] = []
+            for agent in db_agents:
+                try:
+                    store_agents.append(store_model.StoreAgent.from_db(agent))
+                except Exception as e:
+                    logger.error(f"Error parsing StoreAgent from db: {e}")
+                    continue
+
         logger.debug(f"Found {len(store_agents)} agents")
         return store_model.StoreAgentsResponse(
             agents=store_agents,
@@ -164,126 +195,6 @@ async def get_store_agents(
     #         await log_search_term(search_query=search_term)
 
 
-async def _fallback_store_agent_search(
-    *,
-    search_query: str | None,
-    featured: bool,
-    creators: list[str] | None,
-    category: str | None,
-    sorted_by: StoreAgentsSortOptions | None,
-    page: int,
-    page_size: int,
-) -> tuple[list[store_model.StoreAgent], int]:
-    """Direct DB search fallback when hybrid search is unavailable or empty.
-
-    Uses ad-hoc to_tsvector/plainto_tsquery with ts_rank_cd for text search,
-    matching the quality of the original pre-hybrid-search implementation.
-    Falls back to simple listing when no search query is provided.
-    """
-    if not search_query:
-        # No search query — use Prisma for simple filtered listing
-        where_clause: prisma.types.StoreAgentWhereInput = {"is_available": True}
-        if featured:
-            where_clause["featured"] = featured
-        if creators:
-            where_clause["creator_username"] = {"in": creators}
-        if category:
-            where_clause["categories"] = {"has": category}
-
-        order_by = []
-        if sorted_by == StoreAgentsSortOptions.RATING:
-            order_by.append({"rating": "desc"})
-        elif sorted_by == StoreAgentsSortOptions.RUNS:
-            order_by.append({"runs": "desc"})
-        elif sorted_by == StoreAgentsSortOptions.NAME:
-            order_by.append({"agent_name": "asc"})
-        elif sorted_by == StoreAgentsSortOptions.UPDATED_AT:
-            order_by.append({"updated_at": "desc"})
-
-        db_agents = await prisma.models.StoreAgent.prisma().find_many(
-            where=where_clause,
-            order=order_by,
-            skip=(page - 1) * page_size,
-            take=page_size,
-        )
-        total = await prisma.models.StoreAgent.prisma().count(where=where_clause)
-        return [store_model.StoreAgent.from_db(a) for a in db_agents], total
-
-    # Text search using ad-hoc tsvector on StoreAgent view fields
-    params: list[Any] = [search_query]
-    filters = ["sa.is_available = true"]
-    param_idx = 2
-
-    if featured:
-        filters.append("sa.featured = true")
-    if creators:
-        params.append(creators)
-        filters.append(f"sa.creator_username = ANY(${param_idx})")
-        param_idx += 1
-    if category:
-        params.append(category)
-        filters.append(f"${param_idx} = ANY(sa.categories)")
-        param_idx += 1
-
-    where_sql = " AND ".join(filters)
-
-    params.extend([page_size, (page - 1) * page_size])
-    limit_param = f"${param_idx}"
-    param_idx += 1
-    offset_param = f"${param_idx}"
-
-    sql = f"""
-        WITH ranked AS (
-            SELECT sa.*,
-                ts_rank_cd(
-                    to_tsvector('english',
-                        COALESCE(sa.agent_name, '') || ' ' ||
-                        COALESCE(sa.sub_heading, '') || ' ' ||
-                        COALESCE(sa.description, '')
-                    ),
-                    plainto_tsquery('english', $1)
-                ) AS rank,
-                COUNT(*) OVER () AS total_count
-            FROM {{schema_prefix}}"StoreAgent" sa
-            WHERE {where_sql}
-            AND to_tsvector('english',
-                    COALESCE(sa.agent_name, '') || ' ' ||
-                    COALESCE(sa.sub_heading, '') || ' ' ||
-                    COALESCE(sa.description, '')
-                ) @@ plainto_tsquery('english', $1)
-        )
-        SELECT * FROM ranked
-        ORDER BY rank DESC
-        LIMIT {limit_param} OFFSET {offset_param}
-    """
-
-    results = await query_raw_with_schema(sql, *params)
-    total = results[0]["total_count"] if results else 0
-
-    store_agents = []
-    for row in results:
-        try:
-            store_agents.append(
-                store_model.StoreAgent(
-                    slug=row["slug"],
-                    agent_name=row["agent_name"],
-                    agent_image=row["agent_image"][0] if row["agent_image"] else "",
-                    creator=row["creator_username"] or "Needs Profile",
-                    creator_avatar=row["creator_avatar"] or "",
-                    sub_heading=row["sub_heading"],
-                    description=row["description"],
-                    runs=row["runs"],
-                    rating=row["rating"],
-                    agent_graph_id=row.get("graph_id", ""),
-                )
-            )
-        except Exception as e:
-            logger.error(f"Error parsing StoreAgent from fallback search: {e}")
-            continue
-
-    return store_agents, total
-
-
 async def log_search_term(search_query: str):
     """Log a search term to the database"""
 
@@ -391,11 +302,6 @@ async def get_available_graph(
 async def get_store_agent_by_version_id(
     store_listing_version_id: str,
 ) -> store_model.StoreAgentDetails:
-    """Get agent details from the StoreAgent view (APPROVED agents only).
-
-    See also: `get_store_agent_details_as_admin()` which bypasses the
-    APPROVED-only StoreAgent view for admin preview of pending submissions.
-    """
     logger.debug(f"Getting store agent details for {store_listing_version_id}")
 
     try:
@@ -416,57 +322,6 @@ async def get_store_agent_by_version_id(
         raise DatabaseError("Failed to fetch agent details") from e
 
 
-async def get_store_agent_details_as_admin(
-    store_listing_version_id: str,
-) -> store_model.StoreAgentDetails:
-    """Get agent details for admin preview, bypassing the APPROVED-only
-    StoreAgent view. Queries StoreListingVersion directly so pending
-    submissions are visible."""
-    slv = await prisma.models.StoreListingVersion.prisma().find_unique(
-        where={"id": store_listing_version_id},
-        include={
-            "StoreListing": {"include": {"CreatorProfile": True}},
-        },
-    )
-    if not slv or not slv.StoreListing:
-        raise NotFoundError(
-            f"Store listing version {store_listing_version_id} not found"
-        )
-
-    listing = slv.StoreListing
-    # CreatorProfile is a required FK relation — should always exist.
-    # If it's None, the DB is in a bad state.
-    profile = listing.CreatorProfile
-    if not profile:
-        raise DatabaseError(
-            f"StoreListing {listing.id} has no CreatorProfile — FK violated"
-        )
-
-    return store_model.StoreAgentDetails(
-        store_listing_version_id=slv.id,
-        slug=listing.slug,
-        agent_name=slv.name,
-        agent_video=slv.videoUrl or "",
-        agent_output_demo=slv.agentOutputDemoUrl or "",
-        agent_image=slv.imageUrls,
-        creator=profile.username,
-        creator_avatar=profile.avatarUrl or "",
-        sub_heading=slv.subHeading,
-        description=slv.description,
-        instructions=slv.instructions,
-        categories=slv.categories,
-        runs=0,
-        rating=0.0,
-        versions=[str(slv.version)],
-        graph_id=slv.agentGraphId,
-        graph_versions=[str(slv.agentGraphVersion)],
-        last_updated=slv.updatedAt,
-        recommended_schedule_cron=slv.recommendedScheduleCron,
-        active_version_id=listing.activeVersionId or slv.id,
-        has_approved_version=listing.hasApprovedVersion,
-    )
-
-
 class StoreCreatorsSortOptions(Enum):
     # NOTE: values correspond 1:1 to columns of the Creator view
     AGENT_RATING = "agent_rating"
@@ -1284,21 +1139,16 @@ async def review_store_submission(
                     },
                 )
 
-                # Generate embedding for approved listing (best-effort)
-                try:
-                    await ensure_embedding(
-                        version_id=store_listing_version_id,
-                        name=submission.name,
-                        description=submission.description,
-                        sub_heading=submission.subHeading,
-                        categories=submission.categories,
-                        tx=tx,
-                    )
-                except Exception as emb_err:
-                    logger.warning(
-                        f"Could not generate embedding for listing "
-                        f"{store_listing_version_id}: {emb_err}"
-                    )
+                # Generate embedding for approved listing (blocking - admin operation)
+                # Inside transaction: if embedding fails, entire transaction rolls back
+                await ensure_embedding(
+                    version_id=store_listing_version_id,
+                    name=submission.name,
+                    description=submission.description,
+                    sub_heading=submission.subHeading,
+                    categories=submission.categories,
+                    tx=tx,
+                )
 
                 await prisma.models.StoreListing.prisma(tx).update(
                     where={"id": submission.storeListingId},

autogpt_platform/backend/backend/api/features/store/routes.py

@@ -1,4 +1,5 @@
 import logging
+import tempfile
 import urllib.parse
 
 import autogpt_libs.auth
@@ -258,18 +259,21 @@ async def get_graph_meta_by_store_listing_version_id(
 )
 async def download_agent_file(
     store_listing_version_id: str,
-) -> fastapi.responses.Response:
+) -> fastapi.responses.FileResponse:
     """Download agent graph file for a specific marketplace listing version"""
     graph_data = await store_db.get_agent(store_listing_version_id)
     file_name = f"agent_{graph_data.id}_v{graph_data.version or 'latest'}.json"
 
-    return fastapi.responses.Response(
-        content=backend.util.json.dumps(graph_data),
-        media_type="application/json",
-        headers={
-            "Content-Disposition": f'attachment; filename="{file_name}"',
-        },
-    )
+    # Sending graph as a stream (similar to marketplace v1)
+    with tempfile.NamedTemporaryFile(
+        mode="w", suffix=".json", delete=False
+    ) as tmp_file:
+        tmp_file.write(backend.util.json.dumps(graph_data))
+        tmp_file.flush()
+
+        return fastapi.responses.FileResponse(
+            tmp_file.name, filename=file_name, media_type="application/json"
+        )
 
 
 ##############################################

autogpt_platform/backend/backend/api/features/v1.py

@@ -55,6 +55,7 @@ from backend.data.credit import (
     set_auto_top_up,
 )
 from backend.data.graph import GraphSettings
+from backend.data.invited_user import get_or_activate_user
 from backend.data.model import CredentialsMetaInput, UserOnboarding
 from backend.data.notifications import NotificationPreference, NotificationPreferenceDTO
 from backend.data.onboarding import (
@@ -70,7 +71,6 @@ from backend.data.onboarding import (
     update_user_onboarding,
 )
 from backend.data.user import (
-    get_or_create_user,
     get_user_by_id,
     get_user_notification_preference,
     update_user_email,
@@ -136,12 +136,10 @@ _tally_background_tasks: set[asyncio.Task] = set()
     dependencies=[Security(requires_user)],
 )
 async def get_or_create_user_route(user_data: dict = Security(get_jwt_payload)):
-    user = await get_or_create_user(user_data)
+    user = await get_or_activate_user(user_data)
 
-    # Fire-and-forget: populate business understanding from Tally form.
-    # We use created_at proximity instead of an is_new flag because
-    # get_or_create_user is cached — a separate is_new return value would be
-    # unreliable on repeated calls within the cache TTL.
+    # Fire-and-forget: backfill Tally understanding when invite pre-seeding did
+    # not produce a stored result before first activation.
     age_seconds = (datetime.now(timezone.utc) - user.created_at).total_seconds()
     if age_seconds < 30:
         try:
@@ -165,7 +163,8 @@ async def get_or_create_user_route(user_data: dict = Security(get_jwt_payload)):
     dependencies=[Security(requires_user)],
 )
 async def update_user_email_route(
-    user_id: Annotated[str, Security(get_user_id)], email: str = Body(...)
+    user_id: Annotated[str, Security(get_user_id)],
+    email: str = Body(...),
 ) -> dict[str, str]:
     await update_user_email(user_id, email)
 
@@ -179,10 +178,16 @@ async def update_user_email_route(
     dependencies=[Security(requires_user)],
 )
 async def get_user_timezone_route(
-    user_data: dict = Security(get_jwt_payload),
+    user_id: Annotated[str, Security(get_user_id)],
 ) -> TimezoneResponse:
     """Get user timezone setting."""
-    user = await get_or_create_user(user_data)
+    try:
+        user = await get_user_by_id(user_id)
+    except ValueError:
+        raise HTTPException(
+            status_code=HTTP_404_NOT_FOUND,
+            detail="User not found. Please complete activation via /auth/user first.",
+        )
     return TimezoneResponse(timezone=user.timezone)
 
 
@@ -193,7 +198,8 @@ async def get_user_timezone_route(
     dependencies=[Security(requires_user)],
 )
 async def update_user_timezone_route(
-    user_id: Annotated[str, Security(get_user_id)], request: UpdateTimezoneRequest
+    user_id: Annotated[str, Security(get_user_id)],
+    request: UpdateTimezoneRequest,
 ) -> TimezoneResponse:
     """Update user timezone. The timezone should be a valid IANA timezone identifier."""
     user = await update_user_timezone(user_id, str(request.timezone))
@@ -592,11 +598,6 @@ async def fulfill_checkout(user_id: Annotated[str, Security(get_user_id)]):
 async def configure_user_auto_top_up(
     request: AutoTopUpConfig, user_id: Annotated[str, Security(get_user_id)]
 ) -> str:
-    """Configure auto top-up settings and perform an immediate top-up if needed.
-
-    Raises HTTPException(422) if the request parameters are invalid or if
-    the credit top-up fails.
-    """
     if request.threshold < 0:
         raise HTTPException(status_code=422, detail="Threshold must be greater than 0")
     if request.amount < 500 and request.amount != 0:
@@ -611,20 +612,10 @@ async def configure_user_auto_top_up(
     user_credit_model = await get_user_credit_model(user_id)
     current_balance = await user_credit_model.get_credits(user_id)
 
-    try:
-        if current_balance < request.threshold:
-            await user_credit_model.top_up_credits(user_id, request.amount)
-        else:
-            await user_credit_model.top_up_credits(user_id, 0)
-    except ValueError as e:
-        known_messages = (
-            "must not be negative",
-            "already exists for user",
-            "No payment method found",
-        )
-        if any(msg in str(e) for msg in known_messages):
-            raise HTTPException(status_code=422, detail=str(e))
-        raise
+    if current_balance < request.threshold:
+        await user_credit_model.top_up_credits(user_id, request.amount)
+    else:
+        await user_credit_model.top_up_credits(user_id, 0)
 
     await set_auto_top_up(
         user_id, AutoTopUpConfig(threshold=request.threshold, amount=request.amount)
@@ -980,16 +971,14 @@ async def execute_graph(
     source: Annotated[GraphExecutionSource | None, Body(embed=True)] = None,
     graph_version: Optional[int] = None,
     preset_id: Optional[str] = None,
-    dry_run: Annotated[bool, Body(embed=True)] = False,
 ) -> execution_db.GraphExecutionMeta:
-    if not dry_run:
-        user_credit_model = await get_user_credit_model(user_id)
-        current_balance = await user_credit_model.get_credits(user_id)
-        if current_balance <= 0:
-            raise HTTPException(
-                status_code=402,
-                detail="Insufficient balance to execute the agent. Please top up your account.",
-            )
+    user_credit_model = await get_user_credit_model(user_id)
+    current_balance = await user_credit_model.get_credits(user_id)
+    if current_balance <= 0:
+        raise HTTPException(
+            status_code=402,
+            detail="Insufficient balance to execute the agent. Please top up your account.",
+        )
 
     try:
         result = await execution_utils.add_graph_execution(
@@ -999,7 +988,6 @@ async def execute_graph(
             preset_id=preset_id,
             graph_version=graph_version,
             graph_credentials_inputs=credentials_inputs,
-            dry_run=dry_run,
         )
         # Record successful graph execution
         record_graph_execution(graph_id=graph_id, status="success", user_id=user_id)

autogpt_platform/backend/backend/api/features/v1_test.py

@@ -51,7 +51,7 @@ def test_get_or_create_user_route(
     }
 
     mocker.patch(
-        "backend.api.features.v1.get_or_create_user",
+        "backend.api.features.v1.get_or_activate_user",
         return_value=mock_user,
     )
 

autogpt_platform/backend/backend/api/features/workspace/routes.py

@@ -188,7 +188,6 @@ async def upload_file(
     user_id: Annotated[str, fastapi.Security(get_user_id)],
     file: UploadFile,
     session_id: str | None = Query(default=None),
-    overwrite: bool = Query(default=False),
 ) -> UploadFileResponse:
     """
     Upload a file to the user's workspace.
@@ -249,9 +248,7 @@ async def upload_file(
     # Write file via WorkspaceManager
     manager = WorkspaceManager(user_id, workspace.id, session_id)
     try:
-        workspace_file = await manager.write_file(
-            content, filename, overwrite=overwrite
-        )
+        workspace_file = await manager.write_file(content, filename)
     except ValueError as e:
         raise fastapi.HTTPException(status_code=409, detail=str(e)) from e
 

autogpt_platform/backend/backend/api/rest_api.py

@@ -18,8 +18,8 @@ from prisma.errors import PrismaError
 
 import backend.api.features.admin.credit_admin_routes
 import backend.api.features.admin.execution_analytics_routes
-import backend.api.features.admin.rate_limit_admin_routes
 import backend.api.features.admin.store_admin_routes
+import backend.api.features.admin.user_admin_routes
 import backend.api.features.builder
 import backend.api.features.builder.routes
 import backend.api.features.chat.routes as chat_routes
@@ -118,11 +118,6 @@ async def lifespan_context(app: fastapi.FastAPI):
 
     AutoRegistry.patch_integrations()
 
-    # Register managed credential providers (e.g. AgentMail)
-    from backend.integrations.managed_providers import register_all
-
-    register_all()
-
     await backend.data.block.initialize_blocks()
 
     await backend.data.user.migrate_and_encrypt_user_integrations()
@@ -216,22 +211,13 @@ instrument_fastapi(
 def handle_internal_http_error(status_code: int = 500, log_error: bool = True):
     def handler(request: fastapi.Request, exc: Exception):
         if log_error:
-            if status_code >= 500:
-                logger.exception(
-                    "%s %s failed. Investigate and resolve the underlying issue: %s",
-                    request.method,
-                    request.url.path,
-                    exc,
-                    exc_info=exc,
-                )
-            else:
-                logger.warning(
-                    "%s %s failed with %d: %s",
-                    request.method,
-                    request.url.path,
-                    status_code,
-                    exc,
-                )
+            logger.exception(
+                "%s %s failed. Investigate and resolve the underlying issue: %s",
+                request.method,
+                request.url.path,
+                exc,
+                exc_info=exc,
+            )
 
         hint = (
             "Adjust the request and retry."
@@ -281,10 +267,12 @@ async def validation_error_handler(
 
 
 app.add_exception_handler(PrismaError, handle_internal_http_error(500))
-app.add_exception_handler(FolderAlreadyExistsError, handle_internal_http_error(409))
-app.add_exception_handler(FolderValidationError, handle_internal_http_error(400))
-app.add_exception_handler(NotFoundError, handle_internal_http_error(404))
-app.add_exception_handler(NotAuthorizedError, handle_internal_http_error(403))
+app.add_exception_handler(
+    FolderAlreadyExistsError, handle_internal_http_error(409, False)
+)
+app.add_exception_handler(FolderValidationError, handle_internal_http_error(400, False))
+app.add_exception_handler(NotFoundError, handle_internal_http_error(404, False))
+app.add_exception_handler(NotAuthorizedError, handle_internal_http_error(403, False))
 app.add_exception_handler(RequestValidationError, validation_error_handler)
 app.add_exception_handler(pydantic.ValidationError, validation_error_handler)
 app.add_exception_handler(MissingConfigError, handle_internal_http_error(503))
@@ -325,9 +313,9 @@ app.include_router(
     prefix="/api/executions",
 )
 app.include_router(
-    backend.api.features.admin.rate_limit_admin_routes.router,
+    backend.api.features.admin.user_admin_routes.router,
     tags=["v2", "admin"],
-    prefix="/api/copilot",
+    prefix="/api/users",
 )
 app.include_router(
     backend.api.features.executions.review.routes.router,
@@ -539,11 +527,8 @@ class AgentServer(backend.util.service.AppProcess):
         user_id: str,
         provider: ProviderName,
         credentials: Credentials,
-    ):
-        from backend.api.features.integrations.router import (
-            create_credentials,
-            get_credential,
-        )
+    ) -> Credentials:
+        from .features.integrations.router import create_credentials, get_credential
 
         try:
             return await create_credentials(

autogpt_platform/backend/backend/blocks/agent_mail/_config.py

@@ -1,33 +0,0 @@
-"""
-Shared configuration for all AgentMail blocks.
-"""
-
-from agentmail import AsyncAgentMail
-
-from backend.sdk import APIKeyCredentials, ProviderBuilder, SecretStr
-
-agent_mail = (
-    ProviderBuilder("agent_mail")
-    .with_api_key("AGENTMAIL_API_KEY", "AgentMail API Key")
-    .build()
-)
-
-TEST_CREDENTIALS = APIKeyCredentials(
-    id="01234567-89ab-cdef-0123-456789abcdef",
-    provider="agent_mail",
-    title="Mock AgentMail API Key",
-    api_key=SecretStr("mock-agentmail-api-key"),
-    expires_at=None,
-)
-
-TEST_CREDENTIALS_INPUT = {
-    "id": TEST_CREDENTIALS.id,
-    "provider": TEST_CREDENTIALS.provider,
-    "type": TEST_CREDENTIALS.type,
-    "title": TEST_CREDENTIALS.title,
-}
-
-
-def _client(credentials: APIKeyCredentials) -> AsyncAgentMail:
-    """Create an AsyncAgentMail client from credentials."""
-    return AsyncAgentMail(api_key=credentials.api_key.get_secret_value())

autogpt_platform/backend/backend/blocks/agent_mail/attachments.py

@@ -1,211 +0,0 @@
-"""
-AgentMail Attachment blocks — download file attachments from messages and threads.
-
-Attachments are files associated with messages (PDFs, CSVs, images, etc.).
-To send attachments, include them in the attachments parameter when using
-AgentMailSendMessageBlock or AgentMailReplyToMessageBlock.
-
-To download, first get the attachment_id from a message's attachments array,
-then use these blocks to retrieve the file content as base64.
-"""
-
-import base64
-
-from backend.sdk import (
-    APIKeyCredentials,
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-    CredentialsMetaInput,
-    SchemaField,
-)
-
-from ._config import TEST_CREDENTIALS, TEST_CREDENTIALS_INPUT, _client, agent_mail
-
-
-class AgentMailGetMessageAttachmentBlock(Block):
-    """
-    Download a file attachment from a specific email message.
-
-    Retrieves the raw file content and returns it as base64-encoded data.
-    First get the attachment_id from a message object's attachments array,
-    then use this block to download the file.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address the message belongs to"
-        )
-        message_id: str = SchemaField(
-            description="Message ID containing the attachment"
-        )
-        attachment_id: str = SchemaField(
-            description="Attachment ID to download (from the message's attachments array)"
-        )
-
-    class Output(BlockSchemaOutput):
-        content_base64: str = SchemaField(
-            description="File content encoded as a base64 string. Decode with base64.b64decode() to get raw bytes."
-        )
-        attachment_id: str = SchemaField(
-            description="The attachment ID that was downloaded"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="a283ffc4-8087-4c3d-9135-8f26b86742ec",
-            description="Download a file attachment from an email message. Returns base64-encoded file content.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-                "message_id": "test-msg",
-                "attachment_id": "test-attach",
-            },
-            test_output=[
-                ("content_base64", "dGVzdA=="),
-                ("attachment_id", "test-attach"),
-            ],
-            test_mock={
-                "get_attachment": lambda *a, **kw: b"test",
-            },
-        )
-
-    @staticmethod
-    async def get_attachment(
-        credentials: APIKeyCredentials,
-        inbox_id: str,
-        message_id: str,
-        attachment_id: str,
-    ):
-        client = _client(credentials)
-        return await client.inboxes.messages.get_attachment(
-            inbox_id=inbox_id,
-            message_id=message_id,
-            attachment_id=attachment_id,
-        )
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            data = await self.get_attachment(
-                credentials=credentials,
-                inbox_id=input_data.inbox_id,
-                message_id=input_data.message_id,
-                attachment_id=input_data.attachment_id,
-            )
-            if isinstance(data, bytes):
-                encoded = base64.b64encode(data).decode()
-            elif isinstance(data, str):
-                encoded = base64.b64encode(data.encode("utf-8")).decode()
-            else:
-                raise TypeError(
-                    f"Unexpected attachment data type: {type(data).__name__}"
-                )
-
-            yield "content_base64", encoded
-            yield "attachment_id", input_data.attachment_id
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailGetThreadAttachmentBlock(Block):
-    """
-    Download a file attachment from a conversation thread.
-
-    Same as GetMessageAttachment but looks up by thread ID instead of
-    message ID. Useful when you know the thread but not the specific
-    message containing the attachment.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address the thread belongs to"
-        )
-        thread_id: str = SchemaField(description="Thread ID containing the attachment")
-        attachment_id: str = SchemaField(
-            description="Attachment ID to download (from a message's attachments array within the thread)"
-        )
-
-    class Output(BlockSchemaOutput):
-        content_base64: str = SchemaField(
-            description="File content encoded as a base64 string. Decode with base64.b64decode() to get raw bytes."
-        )
-        attachment_id: str = SchemaField(
-            description="The attachment ID that was downloaded"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="06b6a4c4-9d71-4992-9e9c-cf3b352763b5",
-            description="Download a file attachment from a conversation thread. Returns base64-encoded file content.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-                "thread_id": "test-thread",
-                "attachment_id": "test-attach",
-            },
-            test_output=[
-                ("content_base64", "dGVzdA=="),
-                ("attachment_id", "test-attach"),
-            ],
-            test_mock={
-                "get_attachment": lambda *a, **kw: b"test",
-            },
-        )
-
-    @staticmethod
-    async def get_attachment(
-        credentials: APIKeyCredentials,
-        inbox_id: str,
-        thread_id: str,
-        attachment_id: str,
-    ):
-        client = _client(credentials)
-        return await client.inboxes.threads.get_attachment(
-            inbox_id=inbox_id,
-            thread_id=thread_id,
-            attachment_id=attachment_id,
-        )
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            data = await self.get_attachment(
-                credentials=credentials,
-                inbox_id=input_data.inbox_id,
-                thread_id=input_data.thread_id,
-                attachment_id=input_data.attachment_id,
-            )
-            if isinstance(data, bytes):
-                encoded = base64.b64encode(data).decode()
-            elif isinstance(data, str):
-                encoded = base64.b64encode(data.encode("utf-8")).decode()
-            else:
-                raise TypeError(
-                    f"Unexpected attachment data type: {type(data).__name__}"
-                )
-
-            yield "content_base64", encoded
-            yield "attachment_id", input_data.attachment_id
-        except Exception as e:
-            yield "error", str(e)

autogpt_platform/backend/backend/blocks/agent_mail/drafts.py

@@ -1,678 +0,0 @@
-"""
-AgentMail Draft blocks — create, get, list, update, send, and delete drafts.
-
-A Draft is an unsent message that can be reviewed, edited, and sent later.
-Drafts enable human-in-the-loop review, scheduled sending (via send_at),
-and complex multi-step email composition workflows.
-"""
-
-from typing import Optional
-
-from backend.sdk import (
-    APIKeyCredentials,
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-    CredentialsMetaInput,
-    SchemaField,
-)
-
-from ._config import TEST_CREDENTIALS, TEST_CREDENTIALS_INPUT, _client, agent_mail
-
-
-class AgentMailCreateDraftBlock(Block):
-    """
-    Create a draft email in an AgentMail inbox for review or scheduled sending.
-
-    Drafts let agents prepare emails without sending immediately. Use send_at
-    to schedule automatic sending at a future time (ISO 8601 format).
-    Scheduled drafts are auto-labeled 'scheduled' and can be cancelled by
-    deleting the draft.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address to create the draft in"
-        )
-        to: list[str] = SchemaField(
-            description="Recipient email addresses (e.g. ['user@example.com'])"
-        )
-        subject: str = SchemaField(description="Email subject line", default="")
-        text: str = SchemaField(description="Plain text body of the draft", default="")
-        html: str = SchemaField(
-            description="Rich HTML body of the draft", default="", advanced=True
-        )
-        cc: list[str] = SchemaField(
-            description="CC recipient email addresses",
-            default_factory=list,
-            advanced=True,
-        )
-        bcc: list[str] = SchemaField(
-            description="BCC recipient email addresses",
-            default_factory=list,
-            advanced=True,
-        )
-        in_reply_to: str = SchemaField(
-            description="Message ID this draft replies to, for threading follow-up drafts",
-            default="",
-            advanced=True,
-        )
-        send_at: str = SchemaField(
-            description="Schedule automatic sending at this ISO 8601 datetime (e.g. '2025-01-15T09:00:00Z'). Leave empty for manual send.",
-            default="",
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        draft_id: str = SchemaField(
-            description="Unique identifier of the created draft"
-        )
-        send_status: str = SchemaField(
-            description="'scheduled' if send_at was set, empty otherwise. Values: scheduled, sending, failed.",
-            default="",
-        )
-        result: dict = SchemaField(
-            description="Complete draft object with all metadata"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="25ac9086-69fd-48b8-b910-9dbe04b8f3bd",
-            description="Create a draft email for review or scheduled sending. Use send_at for automatic future delivery.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-                "to": ["user@example.com"],
-            },
-            test_output=[
-                ("draft_id", "mock-draft-id"),
-                ("send_status", ""),
-                ("result", dict),
-            ],
-            test_mock={
-                "create_draft": lambda *a, **kw: type(
-                    "Draft",
-                    (),
-                    {
-                        "draft_id": "mock-draft-id",
-                        "send_status": "",
-                        "model_dump": lambda self: {"draft_id": "mock-draft-id"},
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def create_draft(credentials: APIKeyCredentials, inbox_id: str, **params):
-        client = _client(credentials)
-        return await client.inboxes.drafts.create(inbox_id, **params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {"to": input_data.to}
-            if input_data.subject:
-                params["subject"] = input_data.subject
-            if input_data.text:
-                params["text"] = input_data.text
-            if input_data.html:
-                params["html"] = input_data.html
-            if input_data.cc:
-                params["cc"] = input_data.cc
-            if input_data.bcc:
-                params["bcc"] = input_data.bcc
-            if input_data.in_reply_to:
-                params["in_reply_to"] = input_data.in_reply_to
-            if input_data.send_at:
-                params["send_at"] = input_data.send_at
-
-            draft = await self.create_draft(credentials, input_data.inbox_id, **params)
-            result = draft.model_dump()
-
-            yield "draft_id", draft.draft_id
-            yield "send_status", draft.send_status or ""
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailGetDraftBlock(Block):
-    """
-    Retrieve a specific draft from an AgentMail inbox.
-
-    Returns the draft contents including recipients, subject, body, and
-    scheduled send status. Use this to review a draft before approving it.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address the draft belongs to"
-        )
-        draft_id: str = SchemaField(description="Draft ID to retrieve")
-
-    class Output(BlockSchemaOutput):
-        draft_id: str = SchemaField(description="Unique identifier of the draft")
-        subject: str = SchemaField(description="Draft subject line", default="")
-        send_status: str = SchemaField(
-            description="Scheduled send status: 'scheduled', 'sending', 'failed', or empty",
-            default="",
-        )
-        send_at: str = SchemaField(
-            description="Scheduled send time (ISO 8601) if set", default=""
-        )
-        result: dict = SchemaField(description="Complete draft object with all fields")
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="8e57780d-dc25-43d4-a0f4-1f02877b09fb",
-            description="Retrieve a draft email to review its contents, recipients, and scheduled send status.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-                "draft_id": "test-draft",
-            },
-            test_output=[
-                ("draft_id", "test-draft"),
-                ("subject", ""),
-                ("send_status", ""),
-                ("send_at", ""),
-                ("result", dict),
-            ],
-            test_mock={
-                "get_draft": lambda *a, **kw: type(
-                    "Draft",
-                    (),
-                    {
-                        "draft_id": "test-draft",
-                        "subject": "",
-                        "send_status": "",
-                        "send_at": "",
-                        "model_dump": lambda self: {"draft_id": "test-draft"},
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def get_draft(credentials: APIKeyCredentials, inbox_id: str, draft_id: str):
-        client = _client(credentials)
-        return await client.inboxes.drafts.get(inbox_id=inbox_id, draft_id=draft_id)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            draft = await self.get_draft(
-                credentials, input_data.inbox_id, input_data.draft_id
-            )
-            result = draft.model_dump()
-
-            yield "draft_id", draft.draft_id
-            yield "subject", draft.subject or ""
-            yield "send_status", draft.send_status or ""
-            yield "send_at", draft.send_at or ""
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailListDraftsBlock(Block):
-    """
-    List all drafts in an AgentMail inbox with optional label filtering.
-
-    Use labels=['scheduled'] to find all drafts queued for future sending.
-    Useful for building approval dashboards or monitoring pending outreach.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address to list drafts from"
-        )
-        limit: int = SchemaField(
-            description="Maximum number of drafts to return per page (1-100)",
-            default=20,
-            advanced=True,
-        )
-        page_token: str = SchemaField(
-            description="Token from a previous response to fetch the next page",
-            default="",
-            advanced=True,
-        )
-        labels: list[str] = SchemaField(
-            description="Filter drafts by labels (e.g. ['scheduled'] for pending sends)",
-            default_factory=list,
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        drafts: list[dict] = SchemaField(
-            description="List of draft objects with subject, recipients, send_status, etc."
-        )
-        count: int = SchemaField(description="Number of drafts returned")
-        next_page_token: str = SchemaField(
-            description="Token for the next page. Empty if no more results.",
-            default="",
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="e84883b7-7c39-4c5c-88e8-0a72b078ea63",
-            description="List drafts in an AgentMail inbox. Filter by labels=['scheduled'] to find pending sends.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-            },
-            test_output=[
-                ("drafts", []),
-                ("count", 0),
-                ("next_page_token", ""),
-            ],
-            test_mock={
-                "list_drafts": lambda *a, **kw: type(
-                    "Resp",
-                    (),
-                    {
-                        "drafts": [],
-                        "count": 0,
-                        "next_page_token": "",
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def list_drafts(credentials: APIKeyCredentials, inbox_id: str, **params):
-        client = _client(credentials)
-        return await client.inboxes.drafts.list(inbox_id, **params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {"limit": input_data.limit}
-            if input_data.page_token:
-                params["page_token"] = input_data.page_token
-            if input_data.labels:
-                params["labels"] = input_data.labels
-
-            response = await self.list_drafts(
-                credentials, input_data.inbox_id, **params
-            )
-            drafts = [d.model_dump() for d in response.drafts]
-
-            yield "drafts", drafts
-            yield "count", response.count
-            yield "next_page_token", response.next_page_token or ""
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailUpdateDraftBlock(Block):
-    """
-    Update an existing draft's content, recipients, or scheduled send time.
-
-    Use this to reschedule a draft (change send_at), modify recipients,
-    or edit the subject/body before sending. To cancel a scheduled send,
-    delete the draft instead.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address the draft belongs to"
-        )
-        draft_id: str = SchemaField(description="Draft ID to update")
-        to: Optional[list[str]] = SchemaField(
-            description="Updated recipient email addresses (replaces existing list). Omit to keep current value.",
-            default=None,
-        )
-        subject: Optional[str] = SchemaField(
-            description="Updated subject line. Omit to keep current value.",
-            default=None,
-        )
-        text: Optional[str] = SchemaField(
-            description="Updated plain text body. Omit to keep current value.",
-            default=None,
-        )
-        html: Optional[str] = SchemaField(
-            description="Updated HTML body. Omit to keep current value.",
-            default=None,
-            advanced=True,
-        )
-        send_at: Optional[str] = SchemaField(
-            description="Reschedule: new ISO 8601 send time (e.g. '2025-01-20T14:00:00Z'). Omit to keep current value.",
-            default=None,
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        draft_id: str = SchemaField(description="The updated draft ID")
-        send_status: str = SchemaField(description="Updated send status", default="")
-        result: dict = SchemaField(description="Complete updated draft object")
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="351f6e51-695a-421a-9032-46a587b10336",
-            description="Update a draft's content, recipients, or scheduled send time. Use to reschedule or edit before sending.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-                "draft_id": "test-draft",
-            },
-            test_output=[
-                ("draft_id", "test-draft"),
-                ("send_status", ""),
-                ("result", dict),
-            ],
-            test_mock={
-                "update_draft": lambda *a, **kw: type(
-                    "Draft",
-                    (),
-                    {
-                        "draft_id": "test-draft",
-                        "send_status": "",
-                        "model_dump": lambda self: {"draft_id": "test-draft"},
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def update_draft(
-        credentials: APIKeyCredentials, inbox_id: str, draft_id: str, **params
-    ):
-        client = _client(credentials)
-        return await client.inboxes.drafts.update(
-            inbox_id=inbox_id, draft_id=draft_id, **params
-        )
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {}
-            if input_data.to is not None:
-                params["to"] = input_data.to
-            if input_data.subject is not None:
-                params["subject"] = input_data.subject
-            if input_data.text is not None:
-                params["text"] = input_data.text
-            if input_data.html is not None:
-                params["html"] = input_data.html
-            if input_data.send_at is not None:
-                params["send_at"] = input_data.send_at
-
-            draft = await self.update_draft(
-                credentials, input_data.inbox_id, input_data.draft_id, **params
-            )
-            result = draft.model_dump()
-
-            yield "draft_id", draft.draft_id
-            yield "send_status", draft.send_status or ""
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailSendDraftBlock(Block):
-    """
-    Send a draft immediately, converting it into a delivered message.
-
-    The draft is deleted after successful sending and becomes a regular
-    message with a message_id. Use this for human-in-the-loop approval
-    workflows: agent creates draft, human reviews, then this block sends it.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address the draft belongs to"
-        )
-        draft_id: str = SchemaField(description="Draft ID to send now")
-
-    class Output(BlockSchemaOutput):
-        message_id: str = SchemaField(
-            description="Message ID of the now-sent email (draft is deleted)"
-        )
-        thread_id: str = SchemaField(
-            description="Thread ID the sent message belongs to"
-        )
-        result: dict = SchemaField(description="Complete sent message object")
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="37c39e83-475d-4b3d-843a-d923d001b85a",
-            description="Send a draft immediately, converting it into a delivered message. The draft is deleted after sending.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            is_sensitive_action=True,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-                "draft_id": "test-draft",
-            },
-            test_output=[
-                ("message_id", "mock-msg-id"),
-                ("thread_id", "mock-thread-id"),
-                ("result", dict),
-            ],
-            test_mock={
-                "send_draft": lambda *a, **kw: type(
-                    "Msg",
-                    (),
-                    {
-                        "message_id": "mock-msg-id",
-                        "thread_id": "mock-thread-id",
-                        "model_dump": lambda self: {"message_id": "mock-msg-id"},
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def send_draft(credentials: APIKeyCredentials, inbox_id: str, draft_id: str):
-        client = _client(credentials)
-        return await client.inboxes.drafts.send(inbox_id=inbox_id, draft_id=draft_id)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            msg = await self.send_draft(
-                credentials, input_data.inbox_id, input_data.draft_id
-            )
-            result = msg.model_dump()
-
-            yield "message_id", msg.message_id
-            yield "thread_id", msg.thread_id or ""
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailDeleteDraftBlock(Block):
-    """
-    Delete a draft from an AgentMail inbox. Also cancels any scheduled send.
-
-    If the draft was scheduled with send_at, deleting it cancels the
-    scheduled delivery. This is the way to cancel a scheduled email.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address the draft belongs to"
-        )
-        draft_id: str = SchemaField(
-            description="Draft ID to delete (also cancels scheduled sends)"
-        )
-
-    class Output(BlockSchemaOutput):
-        success: bool = SchemaField(
-            description="True if the draft was successfully deleted/cancelled"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="9023eb99-3e2f-4def-808b-d9c584b3d9e7",
-            description="Delete a draft or cancel a scheduled email. Removes the draft permanently.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            is_sensitive_action=True,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-                "draft_id": "test-draft",
-            },
-            test_output=[("success", True)],
-            test_mock={
-                "delete_draft": lambda *a, **kw: None,
-            },
-        )
-
-    @staticmethod
-    async def delete_draft(
-        credentials: APIKeyCredentials, inbox_id: str, draft_id: str
-    ):
-        client = _client(credentials)
-        await client.inboxes.drafts.delete(inbox_id=inbox_id, draft_id=draft_id)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            await self.delete_draft(
-                credentials, input_data.inbox_id, input_data.draft_id
-            )
-            yield "success", True
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailListOrgDraftsBlock(Block):
-    """
-    List all drafts across every inbox in your organization.
-
-    Returns drafts from all inboxes in one query. Perfect for building
-    a central approval dashboard where a human supervisor can review
-    and approve any draft created by any agent.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        limit: int = SchemaField(
-            description="Maximum number of drafts to return per page (1-100)",
-            default=20,
-            advanced=True,
-        )
-        page_token: str = SchemaField(
-            description="Token from a previous response to fetch the next page",
-            default="",
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        drafts: list[dict] = SchemaField(
-            description="List of draft objects from all inboxes in the organization"
-        )
-        count: int = SchemaField(description="Number of drafts returned")
-        next_page_token: str = SchemaField(
-            description="Token for the next page. Empty if no more results.",
-            default="",
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="ed7558ae-3a07-45f5-af55-a25fe88c9971",
-            description="List all drafts across every inbox in your organization. Use for central approval dashboards.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={"credentials": TEST_CREDENTIALS_INPUT},
-            test_output=[
-                ("drafts", []),
-                ("count", 0),
-                ("next_page_token", ""),
-            ],
-            test_mock={
-                "list_org_drafts": lambda *a, **kw: type(
-                    "Resp",
-                    (),
-                    {
-                        "drafts": [],
-                        "count": 0,
-                        "next_page_token": "",
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def list_org_drafts(credentials: APIKeyCredentials, **params):
-        client = _client(credentials)
-        return await client.drafts.list(**params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {"limit": input_data.limit}
-            if input_data.page_token:
-                params["page_token"] = input_data.page_token
-
-            response = await self.list_org_drafts(credentials, **params)
-            drafts = [d.model_dump() for d in response.drafts]
-
-            yield "drafts", drafts
-            yield "count", response.count
-            yield "next_page_token", response.next_page_token or ""
-        except Exception as e:
-            yield "error", str(e)

autogpt_platform/backend/backend/blocks/agent_mail/inbox.py

@@ -1,414 +0,0 @@
-"""
-AgentMail Inbox blocks — create, get, list, update, and delete inboxes.
-
-An Inbox is a fully programmable email account for AI agents. Each inbox gets
-a unique email address and can send, receive, and manage emails via the
-AgentMail API. You can create thousands of inboxes on demand.
-"""
-
-from agentmail.inboxes.types import CreateInboxRequest
-
-from backend.sdk import (
-    APIKeyCredentials,
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-    CredentialsMetaInput,
-    SchemaField,
-)
-
-from ._config import TEST_CREDENTIALS, TEST_CREDENTIALS_INPUT, _client, agent_mail
-
-
-class AgentMailCreateInboxBlock(Block):
-    """
-    Create a new email inbox for an AI agent via AgentMail.
-
-    Each inbox gets a unique email address (e.g. username@agentmail.to).
-    If username and domain are not provided, AgentMail auto-generates them.
-    Use custom domains by specifying the domain field.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        username: str = SchemaField(
-            description="Local part of the email address (e.g. 'support' for support@domain.com). Leave empty to auto-generate.",
-            default="",
-            advanced=False,
-        )
-        domain: str = SchemaField(
-            description="Email domain (e.g. 'mydomain.com'). Defaults to agentmail.to if empty.",
-            default="",
-            advanced=False,
-        )
-        display_name: str = SchemaField(
-            description="Friendly name shown in the 'From' field of sent emails (e.g. 'Support Agent')",
-            default="",
-            advanced=False,
-        )
-
-    class Output(BlockSchemaOutput):
-        inbox_id: str = SchemaField(
-            description="Unique identifier for the created inbox (also the email address)"
-        )
-        email_address: str = SchemaField(
-            description="Full email address of the inbox (e.g. support@agentmail.to)"
-        )
-        result: dict = SchemaField(
-            description="Complete inbox object with all metadata"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="7a8ac219-c6ec-4eec-a828-81af283ce04c",
-            description="Create a new email inbox for an AI agent via AgentMail. Each inbox gets a unique address and can send/receive emails.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={"credentials": TEST_CREDENTIALS_INPUT},
-            test_output=[
-                ("inbox_id", "mock-inbox-id"),
-                ("email_address", "mock-inbox-id"),
-                ("result", dict),
-            ],
-            test_mock={
-                "create_inbox": lambda *a, **kw: type(
-                    "Inbox",
-                    (),
-                    {
-                        "inbox_id": "mock-inbox-id",
-                        "model_dump": lambda self: {"inbox_id": "mock-inbox-id"},
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def create_inbox(credentials: APIKeyCredentials, **params):
-        client = _client(credentials)
-        return await client.inboxes.create(request=CreateInboxRequest(**params))
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {}
-            if input_data.username:
-                params["username"] = input_data.username
-            if input_data.domain:
-                params["domain"] = input_data.domain
-            if input_data.display_name:
-                params["display_name"] = input_data.display_name
-
-            inbox = await self.create_inbox(credentials, **params)
-            result = inbox.model_dump()
-
-            yield "inbox_id", inbox.inbox_id
-            yield "email_address", inbox.inbox_id
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailGetInboxBlock(Block):
-    """
-    Retrieve details of an existing AgentMail inbox by its ID or email address.
-
-    Returns the inbox metadata including email address, display name, and
-    configuration. Use this to check if an inbox exists or get its properties.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address to look up (e.g. 'support@agentmail.to')"
-        )
-
-    class Output(BlockSchemaOutput):
-        inbox_id: str = SchemaField(description="Unique identifier of the inbox")
-        email_address: str = SchemaField(description="Full email address of the inbox")
-        display_name: str = SchemaField(
-            description="Friendly name shown in the 'From' field", default=""
-        )
-        result: dict = SchemaField(
-            description="Complete inbox object with all metadata"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="b858f62b-6c12-4736-aaf2-dbc5a9281320",
-            description="Retrieve details of an existing AgentMail inbox including its email address, display name, and configuration.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-            },
-            test_output=[
-                ("inbox_id", "test-inbox"),
-                ("email_address", "test-inbox"),
-                ("display_name", ""),
-                ("result", dict),
-            ],
-            test_mock={
-                "get_inbox": lambda *a, **kw: type(
-                    "Inbox",
-                    (),
-                    {
-                        "inbox_id": "test-inbox",
-                        "display_name": "",
-                        "model_dump": lambda self: {"inbox_id": "test-inbox"},
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def get_inbox(credentials: APIKeyCredentials, inbox_id: str):
-        client = _client(credentials)
-        return await client.inboxes.get(inbox_id=inbox_id)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            inbox = await self.get_inbox(credentials, input_data.inbox_id)
-            result = inbox.model_dump()
-
-            yield "inbox_id", inbox.inbox_id
-            yield "email_address", inbox.inbox_id
-            yield "display_name", inbox.display_name or ""
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailListInboxesBlock(Block):
-    """
-    List all email inboxes in your AgentMail organization.
-
-    Returns a paginated list of all inboxes with their metadata.
-    Use page_token for pagination when you have many inboxes.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        limit: int = SchemaField(
-            description="Maximum number of inboxes to return per page (1-100)",
-            default=20,
-            advanced=True,
-        )
-        page_token: str = SchemaField(
-            description="Token from a previous response to fetch the next page of results",
-            default="",
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        inboxes: list[dict] = SchemaField(
-            description="List of inbox objects, each containing inbox_id, email_address, display_name, etc."
-        )
-        count: int = SchemaField(
-            description="Total number of inboxes in your organization"
-        )
-        next_page_token: str = SchemaField(
-            description="Token to pass as page_token to get the next page. Empty if no more results.",
-            default="",
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="cfd84a06-2121-4cef-8d14-8badf52d22f0",
-            description="List all email inboxes in your AgentMail organization with pagination support.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={"credentials": TEST_CREDENTIALS_INPUT},
-            test_output=[
-                ("inboxes", []),
-                ("count", 0),
-                ("next_page_token", ""),
-            ],
-            test_mock={
-                "list_inboxes": lambda *a, **kw: type(
-                    "Resp",
-                    (),
-                    {
-                        "inboxes": [],
-                        "count": 0,
-                        "next_page_token": "",
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def list_inboxes(credentials: APIKeyCredentials, **params):
-        client = _client(credentials)
-        return await client.inboxes.list(**params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {"limit": input_data.limit}
-            if input_data.page_token:
-                params["page_token"] = input_data.page_token
-
-            response = await self.list_inboxes(credentials, **params)
-            inboxes = [i.model_dump() for i in response.inboxes]
-
-            yield "inboxes", inboxes
-            yield "count", (c if (c := response.count) is not None else len(inboxes))
-            yield "next_page_token", response.next_page_token or ""
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailUpdateInboxBlock(Block):
-    """
-    Update the display name of an existing AgentMail inbox.
-
-    Changes the friendly name shown in the 'From' field when emails are sent
-    from this inbox. The email address itself cannot be changed.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address to update (e.g. 'support@agentmail.to')"
-        )
-        display_name: str = SchemaField(
-            description="New display name for the inbox (e.g. 'Customer Support Bot')"
-        )
-
-    class Output(BlockSchemaOutput):
-        inbox_id: str = SchemaField(description="The updated inbox ID")
-        result: dict = SchemaField(
-            description="Complete updated inbox object with all metadata"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="59b49f59-a6d1-4203-94c0-3908adac50b6",
-            description="Update the display name of an AgentMail inbox. Changes the 'From' name shown when emails are sent.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-                "display_name": "Updated",
-            },
-            test_output=[
-                ("inbox_id", "test-inbox"),
-                ("result", dict),
-            ],
-            test_mock={
-                "update_inbox": lambda *a, **kw: type(
-                    "Inbox",
-                    (),
-                    {
-                        "inbox_id": "test-inbox",
-                        "model_dump": lambda self: {"inbox_id": "test-inbox"},
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def update_inbox(credentials: APIKeyCredentials, inbox_id: str, **params):
-        client = _client(credentials)
-        return await client.inboxes.update(inbox_id=inbox_id, **params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            inbox = await self.update_inbox(
-                credentials,
-                input_data.inbox_id,
-                display_name=input_data.display_name,
-            )
-            result = inbox.model_dump()
-
-            yield "inbox_id", inbox.inbox_id
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailDeleteInboxBlock(Block):
-    """
-    Permanently delete an AgentMail inbox and all its data.
-
-    This removes the inbox, all its messages, threads, and drafts.
-    This action cannot be undone. The email address will no longer
-    receive or send emails.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address to permanently delete"
-        )
-
-    class Output(BlockSchemaOutput):
-        success: bool = SchemaField(
-            description="True if the inbox was successfully deleted"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="ade970ae-8428-4a7b-9278-b52054dbf535",
-            description="Permanently delete an AgentMail inbox and all its messages, threads, and drafts. This action cannot be undone.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            is_sensitive_action=True,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-            },
-            test_output=[("success", True)],
-            test_mock={
-                "delete_inbox": lambda *a, **kw: None,
-            },
-        )
-
-    @staticmethod
-    async def delete_inbox(credentials: APIKeyCredentials, inbox_id: str):
-        client = _client(credentials)
-        await client.inboxes.delete(inbox_id=inbox_id)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            await self.delete_inbox(credentials, input_data.inbox_id)
-            yield "success", True
-        except Exception as e:
-            yield "error", str(e)

autogpt_platform/backend/backend/blocks/agent_mail/lists.py

@@ -1,384 +0,0 @@
-"""
-AgentMail List blocks — manage allow/block lists for email filtering.
-
-Lists let you control which email addresses and domains your agents can
-send to or receive from. There are four list types based on two dimensions:
-direction (send/receive) and type (allow/block).
-
-- receive + allow: Only accept emails from these addresses/domains
-- receive + block: Reject emails from these addresses/domains
-- send + allow: Only send emails to these addresses/domains
-- send + block: Prevent sending emails to these addresses/domains
-"""
-
-from enum import Enum
-
-from backend.sdk import (
-    APIKeyCredentials,
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-    CredentialsMetaInput,
-    SchemaField,
-)
-
-from ._config import TEST_CREDENTIALS, TEST_CREDENTIALS_INPUT, _client, agent_mail
-
-
-class ListDirection(str, Enum):
-    SEND = "send"
-    RECEIVE = "receive"
-
-
-class ListType(str, Enum):
-    ALLOW = "allow"
-    BLOCK = "block"
-
-
-class AgentMailListEntriesBlock(Block):
-    """
-    List all entries in an AgentMail allow/block list.
-
-    Retrieves email addresses and domains that are currently allowed
-    or blocked for sending or receiving. Use direction and list_type
-    to select which of the four lists to query.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        direction: ListDirection = SchemaField(
-            description="'send' to filter outgoing emails, 'receive' to filter incoming emails"
-        )
-        list_type: ListType = SchemaField(
-            description="'allow' for whitelist (only permit these), 'block' for blacklist (reject these)"
-        )
-        limit: int = SchemaField(
-            description="Maximum number of entries to return per page",
-            default=20,
-            advanced=True,
-        )
-        page_token: str = SchemaField(
-            description="Token from a previous response to fetch the next page",
-            default="",
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        entries: list[dict] = SchemaField(
-            description="List of entries, each with an email address or domain"
-        )
-        count: int = SchemaField(description="Number of entries returned")
-        next_page_token: str = SchemaField(
-            description="Token for the next page. Empty if no more results.",
-            default="",
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="01489100-35da-45aa-8a01-9540ba0e9a21",
-            description="List all entries in an AgentMail allow/block list. Choose send/receive direction and allow/block type.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "direction": "receive",
-                "list_type": "block",
-            },
-            test_output=[
-                ("entries", []),
-                ("count", 0),
-                ("next_page_token", ""),
-            ],
-            test_mock={
-                "list_entries": lambda *a, **kw: type(
-                    "Resp",
-                    (),
-                    {
-                        "entries": [],
-                        "count": 0,
-                        "next_page_token": "",
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def list_entries(
-        credentials: APIKeyCredentials, direction: str, list_type: str, **params
-    ):
-        client = _client(credentials)
-        return await client.lists.list(direction, list_type, **params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {"limit": input_data.limit}
-            if input_data.page_token:
-                params["page_token"] = input_data.page_token
-
-            response = await self.list_entries(
-                credentials,
-                input_data.direction.value,
-                input_data.list_type.value,
-                **params,
-            )
-            entries = [e.model_dump() for e in response.entries]
-
-            yield "entries", entries
-            yield "count", (c if (c := response.count) is not None else len(entries))
-            yield "next_page_token", response.next_page_token or ""
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailCreateListEntryBlock(Block):
-    """
-    Add an email address or domain to an AgentMail allow/block list.
-
-    Entries can be full email addresses (e.g. 'partner@example.com') or
-    entire domains (e.g. 'example.com'). For block lists, you can optionally
-    provide a reason (e.g. 'spam', 'competitor').
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        direction: ListDirection = SchemaField(
-            description="'send' for outgoing email rules, 'receive' for incoming email rules"
-        )
-        list_type: ListType = SchemaField(
-            description="'allow' to whitelist, 'block' to blacklist"
-        )
-        entry: str = SchemaField(
-            description="Email address (user@example.com) or domain (example.com) to add"
-        )
-        reason: str = SchemaField(
-            description="Reason for blocking (only used with block lists, e.g. 'spam', 'competitor')",
-            default="",
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        entry: str = SchemaField(
-            description="The email address or domain that was added"
-        )
-        result: dict = SchemaField(description="Complete entry object")
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="b6650a0a-b113-40cf-8243-ff20f684f9b8",
-            description="Add an email address or domain to an allow/block list. Block spam senders or whitelist trusted domains.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            is_sensitive_action=True,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "direction": "receive",
-                "list_type": "block",
-                "entry": "spam@example.com",
-            },
-            test_output=[
-                ("entry", "spam@example.com"),
-                ("result", dict),
-            ],
-            test_mock={
-                "create_entry": lambda *a, **kw: type(
-                    "Entry",
-                    (),
-                    {
-                        "model_dump": lambda self: {"entry": "spam@example.com"},
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def create_entry(
-        credentials: APIKeyCredentials, direction: str, list_type: str, **params
-    ):
-        client = _client(credentials)
-        return await client.lists.create(direction, list_type, **params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {"entry": input_data.entry}
-            if input_data.reason and input_data.list_type == ListType.BLOCK:
-                params["reason"] = input_data.reason
-
-            result = await self.create_entry(
-                credentials,
-                input_data.direction.value,
-                input_data.list_type.value,
-                **params,
-            )
-            result_dict = result.model_dump()
-
-            yield "entry", input_data.entry
-            yield "result", result_dict
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailGetListEntryBlock(Block):
-    """
-    Check if an email address or domain exists in an AgentMail allow/block list.
-
-    Returns the entry details if found. Use this to verify whether a specific
-    address or domain is currently allowed or blocked.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        direction: ListDirection = SchemaField(
-            description="'send' for outgoing rules, 'receive' for incoming rules"
-        )
-        list_type: ListType = SchemaField(
-            description="'allow' for whitelist, 'block' for blacklist"
-        )
-        entry: str = SchemaField(description="Email address or domain to look up")
-
-    class Output(BlockSchemaOutput):
-        entry: str = SchemaField(
-            description="The email address or domain that was found"
-        )
-        result: dict = SchemaField(description="Complete entry object with metadata")
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="fb117058-ab27-40d1-9231-eb1dd526fc7a",
-            description="Check if an email address or domain is in an allow/block list. Verify filtering rules.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "direction": "receive",
-                "list_type": "block",
-                "entry": "spam@example.com",
-            },
-            test_output=[
-                ("entry", "spam@example.com"),
-                ("result", dict),
-            ],
-            test_mock={
-                "get_entry": lambda *a, **kw: type(
-                    "Entry",
-                    (),
-                    {
-                        "model_dump": lambda self: {"entry": "spam@example.com"},
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def get_entry(
-        credentials: APIKeyCredentials, direction: str, list_type: str, entry: str
-    ):
-        client = _client(credentials)
-        return await client.lists.get(direction, list_type, entry=entry)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            result = await self.get_entry(
-                credentials,
-                input_data.direction.value,
-                input_data.list_type.value,
-                input_data.entry,
-            )
-            result_dict = result.model_dump()
-
-            yield "entry", input_data.entry
-            yield "result", result_dict
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailDeleteListEntryBlock(Block):
-    """
-    Remove an email address or domain from an AgentMail allow/block list.
-
-    After removal, the address/domain will no longer be filtered by this list.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        direction: ListDirection = SchemaField(
-            description="'send' for outgoing rules, 'receive' for incoming rules"
-        )
-        list_type: ListType = SchemaField(
-            description="'allow' for whitelist, 'block' for blacklist"
-        )
-        entry: str = SchemaField(
-            description="Email address or domain to remove from the list"
-        )
-
-    class Output(BlockSchemaOutput):
-        success: bool = SchemaField(
-            description="True if the entry was successfully removed"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="2b8d57f1-1c9e-470f-a70b-5991c80fad5f",
-            description="Remove an email address or domain from an allow/block list to stop filtering it.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            is_sensitive_action=True,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "direction": "receive",
-                "list_type": "block",
-                "entry": "spam@example.com",
-            },
-            test_output=[("success", True)],
-            test_mock={
-                "delete_entry": lambda *a, **kw: None,
-            },
-        )
-
-    @staticmethod
-    async def delete_entry(
-        credentials: APIKeyCredentials, direction: str, list_type: str, entry: str
-    ):
-        client = _client(credentials)
-        await client.lists.delete(direction, list_type, entry=entry)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            await self.delete_entry(
-                credentials,
-                input_data.direction.value,
-                input_data.list_type.value,
-                input_data.entry,
-            )
-            yield "success", True
-        except Exception as e:
-            yield "error", str(e)

autogpt_platform/backend/backend/blocks/agent_mail/messages.py

@@ -1,695 +0,0 @@
-"""
-AgentMail Message blocks — send, list, get, reply, forward, and update messages.
-
-A Message is an individual email within a Thread. Agents can send new messages
-(which create threads), reply to existing messages, forward them, and manage
-labels for state tracking (e.g. read/unread, campaign tags).
-"""
-
-from backend.sdk import (
-    APIKeyCredentials,
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-    CredentialsMetaInput,
-    SchemaField,
-)
-
-from ._config import TEST_CREDENTIALS, TEST_CREDENTIALS_INPUT, _client, agent_mail
-
-
-class AgentMailSendMessageBlock(Block):
-    """
-    Send a new email from an AgentMail inbox, automatically creating a new thread.
-
-    Supports plain text and HTML bodies, CC/BCC recipients, and labels for
-    organizing messages (e.g. campaign tracking, state management).
-    Max 50 combined recipients across to, cc, and bcc.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address to send from (e.g. 'agent@agentmail.to')"
-        )
-        to: list[str] = SchemaField(
-            description="Recipient email addresses (e.g. ['user@example.com'])"
-        )
-        subject: str = SchemaField(description="Email subject line")
-        text: str = SchemaField(
-            description="Plain text body of the email. Always provide this as a fallback for email clients that don't render HTML."
-        )
-        html: str = SchemaField(
-            description="Rich HTML body of the email. Embed CSS in a <style> tag for best compatibility across email clients.",
-            default="",
-            advanced=True,
-        )
-        cc: list[str] = SchemaField(
-            description="CC recipient email addresses for human-in-the-loop oversight",
-            default_factory=list,
-            advanced=True,
-        )
-        bcc: list[str] = SchemaField(
-            description="BCC recipient email addresses (hidden from other recipients)",
-            default_factory=list,
-            advanced=True,
-        )
-        labels: list[str] = SchemaField(
-            description="Labels to tag the message for filtering and state management (e.g. ['outreach', 'q4-campaign'])",
-            default_factory=list,
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        message_id: str = SchemaField(
-            description="Unique identifier of the sent message"
-        )
-        thread_id: str = SchemaField(
-            description="Thread ID grouping this message and any future replies"
-        )
-        result: dict = SchemaField(
-            description="Complete sent message object with all metadata"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="b67469b2-7748-4d81-a223-4ebd332cca89",
-            description="Send a new email from an AgentMail inbox. Creates a new conversation thread. Supports HTML, CC/BCC, and labels.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            is_sensitive_action=True,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-                "to": ["user@example.com"],
-                "subject": "Test",
-                "text": "Hello",
-            },
-            test_output=[
-                ("message_id", "mock-msg-id"),
-                ("thread_id", "mock-thread-id"),
-                ("result", dict),
-            ],
-            test_mock={
-                "send_message": lambda *a, **kw: type(
-                    "Msg",
-                    (),
-                    {
-                        "message_id": "mock-msg-id",
-                        "thread_id": "mock-thread-id",
-                        "model_dump": lambda self: {
-                            "message_id": "mock-msg-id",
-                            "thread_id": "mock-thread-id",
-                        },
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def send_message(credentials: APIKeyCredentials, inbox_id: str, **params):
-        client = _client(credentials)
-        return await client.inboxes.messages.send(inbox_id, **params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            total = len(input_data.to) + len(input_data.cc) + len(input_data.bcc)
-            if total > 50:
-                raise ValueError(
-                    f"Max 50 combined recipients across to, cc, and bcc (got {total})"
-                )
-
-            params: dict = {
-                "to": input_data.to,
-                "subject": input_data.subject,
-                "text": input_data.text,
-            }
-            if input_data.html:
-                params["html"] = input_data.html
-            if input_data.cc:
-                params["cc"] = input_data.cc
-            if input_data.bcc:
-                params["bcc"] = input_data.bcc
-            if input_data.labels:
-                params["labels"] = input_data.labels
-
-            msg = await self.send_message(credentials, input_data.inbox_id, **params)
-            result = msg.model_dump()
-
-            yield "message_id", msg.message_id
-            yield "thread_id", msg.thread_id or ""
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailListMessagesBlock(Block):
-    """
-    List all messages in an AgentMail inbox with optional label filtering.
-
-    Returns a paginated list of messages. Use labels to filter (e.g.
-    labels=['unread'] to only get unprocessed messages). Useful for
-    polling workflows or building inbox views.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address to list messages from"
-        )
-        limit: int = SchemaField(
-            description="Maximum number of messages to return per page (1-100)",
-            default=20,
-            advanced=True,
-        )
-        page_token: str = SchemaField(
-            description="Token from a previous response to fetch the next page",
-            default="",
-            advanced=True,
-        )
-        labels: list[str] = SchemaField(
-            description="Only return messages with ALL of these labels (e.g. ['unread'] or ['q4-campaign', 'follow-up'])",
-            default_factory=list,
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        messages: list[dict] = SchemaField(
-            description="List of message objects with subject, sender, text, html, labels, etc."
-        )
-        count: int = SchemaField(description="Number of messages returned")
-        next_page_token: str = SchemaField(
-            description="Token for the next page. Empty if no more results.",
-            default="",
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="721234df-c7a2-4927-b205-744badbd5844",
-            description="List messages in an AgentMail inbox. Filter by labels to find unread, campaign-tagged, or categorized messages.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-            },
-            test_output=[
-                ("messages", []),
-                ("count", 0),
-                ("next_page_token", ""),
-            ],
-            test_mock={
-                "list_messages": lambda *a, **kw: type(
-                    "Resp",
-                    (),
-                    {
-                        "messages": [],
-                        "count": 0,
-                        "next_page_token": "",
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def list_messages(credentials: APIKeyCredentials, inbox_id: str, **params):
-        client = _client(credentials)
-        return await client.inboxes.messages.list(inbox_id, **params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {"limit": input_data.limit}
-            if input_data.page_token:
-                params["page_token"] = input_data.page_token
-            if input_data.labels:
-                params["labels"] = input_data.labels
-
-            response = await self.list_messages(
-                credentials, input_data.inbox_id, **params
-            )
-            messages = [m.model_dump() for m in response.messages]
-
-            yield "messages", messages
-            yield "count", (c if (c := response.count) is not None else len(messages))
-            yield "next_page_token", response.next_page_token or ""
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailGetMessageBlock(Block):
-    """
-    Retrieve a specific email message by ID from an AgentMail inbox.
-
-    Returns the full message including subject, body (text and HTML),
-    sender, recipients, and attachments. Use extracted_text to get
-    only the new reply content without quoted history.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address the message belongs to"
-        )
-        message_id: str = SchemaField(
-            description="Message ID to retrieve (e.g. '<abc123@agentmail.to>')"
-        )
-
-    class Output(BlockSchemaOutput):
-        message_id: str = SchemaField(description="Unique identifier of the message")
-        thread_id: str = SchemaField(description="Thread this message belongs to")
-        subject: str = SchemaField(description="Email subject line")
-        text: str = SchemaField(
-            description="Full plain text body (may include quoted reply history)"
-        )
-        extracted_text: str = SchemaField(
-            description="Just the new reply content with quoted history stripped. Best for AI processing.",
-            default="",
-        )
-        html: str = SchemaField(description="HTML body of the email", default="")
-        result: dict = SchemaField(
-            description="Complete message object with all fields including sender, recipients, attachments, labels"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="2788bdfa-1527-4603-a5e4-a455c05c032f",
-            description="Retrieve a specific email message by ID. Includes extracted_text for clean reply content without quoted history.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-                "message_id": "test-msg",
-            },
-            test_output=[
-                ("message_id", "test-msg"),
-                ("thread_id", "t1"),
-                ("subject", "Hi"),
-                ("text", "Hello"),
-                ("extracted_text", "Hello"),
-                ("html", ""),
-                ("result", dict),
-            ],
-            test_mock={
-                "get_message": lambda *a, **kw: type(
-                    "Msg",
-                    (),
-                    {
-                        "message_id": "test-msg",
-                        "thread_id": "t1",
-                        "subject": "Hi",
-                        "text": "Hello",
-                        "extracted_text": "Hello",
-                        "html": "",
-                        "model_dump": lambda self: {"message_id": "test-msg"},
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def get_message(
-        credentials: APIKeyCredentials,
-        inbox_id: str,
-        message_id: str,
-    ):
-        client = _client(credentials)
-        return await client.inboxes.messages.get(
-            inbox_id=inbox_id, message_id=message_id
-        )
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            msg = await self.get_message(
-                credentials, input_data.inbox_id, input_data.message_id
-            )
-            result = msg.model_dump()
-
-            yield "message_id", msg.message_id
-            yield "thread_id", msg.thread_id or ""
-            yield "subject", msg.subject or ""
-            yield "text", msg.text or ""
-            yield "extracted_text", msg.extracted_text or ""
-            yield "html", msg.html or ""
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailReplyToMessageBlock(Block):
-    """
-    Reply to an existing email message, keeping the reply in the same thread.
-
-    The reply is automatically added to the same conversation thread as the
-    original message. Use this for multi-turn agent conversations.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address to send the reply from"
-        )
-        message_id: str = SchemaField(
-            description="Message ID to reply to (e.g. '<abc123@agentmail.to>')"
-        )
-        text: str = SchemaField(description="Plain text body of the reply")
-        html: str = SchemaField(
-            description="Rich HTML body of the reply",
-            default="",
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        message_id: str = SchemaField(
-            description="Unique identifier of the reply message"
-        )
-        thread_id: str = SchemaField(description="Thread ID the reply was added to")
-        result: dict = SchemaField(
-            description="Complete reply message object with all metadata"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="b9fe53fa-5026-4547-9570-b54ccb487229",
-            description="Reply to an existing email in the same conversation thread. Use for multi-turn agent conversations.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            is_sensitive_action=True,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-                "message_id": "test-msg",
-                "text": "Reply",
-            },
-            test_output=[
-                ("message_id", "mock-reply-id"),
-                ("thread_id", "mock-thread-id"),
-                ("result", dict),
-            ],
-            test_mock={
-                "reply_to_message": lambda *a, **kw: type(
-                    "Msg",
-                    (),
-                    {
-                        "message_id": "mock-reply-id",
-                        "thread_id": "mock-thread-id",
-                        "model_dump": lambda self: {"message_id": "mock-reply-id"},
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def reply_to_message(
-        credentials: APIKeyCredentials, inbox_id: str, message_id: str, **params
-    ):
-        client = _client(credentials)
-        return await client.inboxes.messages.reply(
-            inbox_id=inbox_id, message_id=message_id, **params
-        )
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {"text": input_data.text}
-            if input_data.html:
-                params["html"] = input_data.html
-
-            reply = await self.reply_to_message(
-                credentials,
-                input_data.inbox_id,
-                input_data.message_id,
-                **params,
-            )
-            result = reply.model_dump()
-
-            yield "message_id", reply.message_id
-            yield "thread_id", reply.thread_id or ""
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailForwardMessageBlock(Block):
-    """
-    Forward an existing email message to one or more recipients.
-
-    Sends the original message content to different email addresses.
-    Optionally prepend additional text or override the subject line.
-    Max 50 combined recipients across to, cc, and bcc.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address to forward from"
-        )
-        message_id: str = SchemaField(description="Message ID to forward")
-        to: list[str] = SchemaField(
-            description="Recipient email addresses to forward the message to (e.g. ['user@example.com'])"
-        )
-        cc: list[str] = SchemaField(
-            description="CC recipient email addresses",
-            default_factory=list,
-            advanced=True,
-        )
-        bcc: list[str] = SchemaField(
-            description="BCC recipient email addresses (hidden from other recipients)",
-            default_factory=list,
-            advanced=True,
-        )
-        subject: str = SchemaField(
-            description="Override the subject line (defaults to 'Fwd: <original subject>')",
-            default="",
-            advanced=True,
-        )
-        text: str = SchemaField(
-            description="Additional plain text to prepend before the forwarded content",
-            default="",
-            advanced=True,
-        )
-        html: str = SchemaField(
-            description="Additional HTML to prepend before the forwarded content",
-            default="",
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        message_id: str = SchemaField(
-            description="Unique identifier of the forwarded message"
-        )
-        thread_id: str = SchemaField(description="Thread ID of the forward")
-        result: dict = SchemaField(
-            description="Complete forwarded message object with all metadata"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="b70c7e33-5d66-4f8e-897f-ac73a7bfce82",
-            description="Forward an email message to one or more recipients. Supports CC/BCC and optional extra text or subject override.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            is_sensitive_action=True,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-                "message_id": "test-msg",
-                "to": ["user@example.com"],
-            },
-            test_output=[
-                ("message_id", "mock-fwd-id"),
-                ("thread_id", "mock-thread-id"),
-                ("result", dict),
-            ],
-            test_mock={
-                "forward_message": lambda *a, **kw: type(
-                    "Msg",
-                    (),
-                    {
-                        "message_id": "mock-fwd-id",
-                        "thread_id": "mock-thread-id",
-                        "model_dump": lambda self: {"message_id": "mock-fwd-id"},
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def forward_message(
-        credentials: APIKeyCredentials, inbox_id: str, message_id: str, **params
-    ):
-        client = _client(credentials)
-        return await client.inboxes.messages.forward(
-            inbox_id=inbox_id, message_id=message_id, **params
-        )
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            total = len(input_data.to) + len(input_data.cc) + len(input_data.bcc)
-            if total > 50:
-                raise ValueError(
-                    f"Max 50 combined recipients across to, cc, and bcc (got {total})"
-                )
-
-            params: dict = {"to": input_data.to}
-            if input_data.cc:
-                params["cc"] = input_data.cc
-            if input_data.bcc:
-                params["bcc"] = input_data.bcc
-            if input_data.subject:
-                params["subject"] = input_data.subject
-            if input_data.text:
-                params["text"] = input_data.text
-            if input_data.html:
-                params["html"] = input_data.html
-
-            fwd = await self.forward_message(
-                credentials,
-                input_data.inbox_id,
-                input_data.message_id,
-                **params,
-            )
-            result = fwd.model_dump()
-
-            yield "message_id", fwd.message_id
-            yield "thread_id", fwd.thread_id or ""
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailUpdateMessageBlock(Block):
-    """
-    Add or remove labels on an email message for state management.
-
-    Labels are string tags used to track message state (read/unread),
-    categorize messages (billing, support), or tag campaigns (q4-outreach).
-    Common pattern: add 'read' and remove 'unread' after processing a message.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address the message belongs to"
-        )
-        message_id: str = SchemaField(description="Message ID to update labels on")
-        add_labels: list[str] = SchemaField(
-            description="Labels to add (e.g. ['read', 'processed', 'high-priority'])",
-            default_factory=list,
-        )
-        remove_labels: list[str] = SchemaField(
-            description="Labels to remove (e.g. ['unread', 'pending'])",
-            default_factory=list,
-        )
-
-    class Output(BlockSchemaOutput):
-        message_id: str = SchemaField(description="The updated message ID")
-        result: dict = SchemaField(
-            description="Complete updated message object with current labels"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="694ff816-4c89-4a5e-a552-8c31be187735",
-            description="Add or remove labels on an email message. Use for read/unread tracking, campaign tagging, or state management.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-                "message_id": "test-msg",
-                "add_labels": ["read"],
-            },
-            test_output=[
-                ("message_id", "test-msg"),
-                ("result", dict),
-            ],
-            test_mock={
-                "update_message": lambda *a, **kw: type(
-                    "Msg",
-                    (),
-                    {
-                        "message_id": "test-msg",
-                        "model_dump": lambda self: {"message_id": "test-msg"},
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def update_message(
-        credentials: APIKeyCredentials, inbox_id: str, message_id: str, **params
-    ):
-        client = _client(credentials)
-        return await client.inboxes.messages.update(
-            inbox_id=inbox_id, message_id=message_id, **params
-        )
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            if not input_data.add_labels and not input_data.remove_labels:
-                raise ValueError(
-                    "Must specify at least one label operation: add_labels or remove_labels"
-                )
-
-            params: dict = {}
-            if input_data.add_labels:
-                params["add_labels"] = input_data.add_labels
-            if input_data.remove_labels:
-                params["remove_labels"] = input_data.remove_labels
-
-            msg = await self.update_message(
-                credentials,
-                input_data.inbox_id,
-                input_data.message_id,
-                **params,
-            )
-            result = msg.model_dump()
-
-            yield "message_id", msg.message_id
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)

autogpt_platform/backend/backend/blocks/agent_mail/pods.py

@@ -1,651 +0,0 @@
-"""
-AgentMail Pod blocks — create, get, list, delete pods and list pod-scoped resources.
-
-Pods provide multi-tenant isolation between your customers. Each pod acts as
-an isolated workspace containing its own inboxes, domains, threads, and drafts.
-Use pods when building SaaS platforms, agency tools, or AI agent fleets that
-serve multiple customers.
-"""
-
-from backend.sdk import (
-    APIKeyCredentials,
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-    CredentialsMetaInput,
-    SchemaField,
-)
-
-from ._config import TEST_CREDENTIALS, TEST_CREDENTIALS_INPUT, _client, agent_mail
-
-
-class AgentMailCreatePodBlock(Block):
-    """
-    Create a new pod for multi-tenant customer isolation.
-
-    Each pod acts as an isolated workspace for one customer or tenant.
-    Use client_id to map pods to your internal tenant IDs for idempotent
-    creation (safe to retry without creating duplicates).
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        client_id: str = SchemaField(
-            description="Your internal tenant/customer ID for idempotent mapping. Lets you access the pod by your own ID instead of AgentMail's pod_id.",
-            default="",
-        )
-
-    class Output(BlockSchemaOutput):
-        pod_id: str = SchemaField(description="Unique identifier of the created pod")
-        result: dict = SchemaField(description="Complete pod object with all metadata")
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="a2db9784-2d17-4f8f-9d6b-0214e6f22101",
-            description="Create a new pod for multi-tenant customer isolation. Use client_id to map to your internal tenant IDs.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={"credentials": TEST_CREDENTIALS_INPUT},
-            test_output=[
-                ("pod_id", "mock-pod-id"),
-                ("result", dict),
-            ],
-            test_mock={
-                "create_pod": lambda *a, **kw: type(
-                    "Pod",
-                    (),
-                    {
-                        "pod_id": "mock-pod-id",
-                        "model_dump": lambda self: {"pod_id": "mock-pod-id"},
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def create_pod(credentials: APIKeyCredentials, **params):
-        client = _client(credentials)
-        return await client.pods.create(**params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {}
-            if input_data.client_id:
-                params["client_id"] = input_data.client_id
-
-            pod = await self.create_pod(credentials, **params)
-            result = pod.model_dump()
-
-            yield "pod_id", pod.pod_id
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailGetPodBlock(Block):
-    """
-    Retrieve details of an existing pod by its ID.
-
-    Returns the pod metadata including its client_id mapping and
-    creation timestamp.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        pod_id: str = SchemaField(description="Pod ID to retrieve")
-
-    class Output(BlockSchemaOutput):
-        pod_id: str = SchemaField(description="Unique identifier of the pod")
-        result: dict = SchemaField(description="Complete pod object with all metadata")
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="553361bc-bb1b-4322-9ad4-0c226200217e",
-            description="Retrieve details of an existing pod including its client_id mapping and metadata.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={"credentials": TEST_CREDENTIALS_INPUT, "pod_id": "test-pod"},
-            test_output=[
-                ("pod_id", "test-pod"),
-                ("result", dict),
-            ],
-            test_mock={
-                "get_pod": lambda *a, **kw: type(
-                    "Pod",
-                    (),
-                    {
-                        "pod_id": "test-pod",
-                        "model_dump": lambda self: {"pod_id": "test-pod"},
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def get_pod(credentials: APIKeyCredentials, pod_id: str):
-        client = _client(credentials)
-        return await client.pods.get(pod_id=pod_id)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            pod = await self.get_pod(credentials, pod_id=input_data.pod_id)
-            result = pod.model_dump()
-
-            yield "pod_id", pod.pod_id
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailListPodsBlock(Block):
-    """
-    List all pods in your AgentMail organization.
-
-    Returns a paginated list of all tenant pods with their metadata.
-    Use this to see all customer workspaces at a glance.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        limit: int = SchemaField(
-            description="Maximum number of pods to return per page (1-100)",
-            default=20,
-            advanced=True,
-        )
-        page_token: str = SchemaField(
-            description="Token from a previous response to fetch the next page",
-            default="",
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        pods: list[dict] = SchemaField(
-            description="List of pod objects with pod_id, client_id, creation time, etc."
-        )
-        count: int = SchemaField(description="Number of pods returned")
-        next_page_token: str = SchemaField(
-            description="Token for the next page. Empty if no more results.",
-            default="",
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="9d3725ee-2968-431a-a816-857ab41e1420",
-            description="List all tenant pods in your organization. See all customer workspaces at a glance.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={"credentials": TEST_CREDENTIALS_INPUT},
-            test_output=[
-                ("pods", []),
-                ("count", 0),
-                ("next_page_token", ""),
-            ],
-            test_mock={
-                "list_pods": lambda *a, **kw: type(
-                    "Resp",
-                    (),
-                    {
-                        "pods": [],
-                        "count": 0,
-                        "next_page_token": "",
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def list_pods(credentials: APIKeyCredentials, **params):
-        client = _client(credentials)
-        return await client.pods.list(**params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {"limit": input_data.limit}
-            if input_data.page_token:
-                params["page_token"] = input_data.page_token
-
-            response = await self.list_pods(credentials, **params)
-            pods = [p.model_dump() for p in response.pods]
-
-            yield "pods", pods
-            yield "count", response.count
-            yield "next_page_token", response.next_page_token or ""
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailDeletePodBlock(Block):
-    """
-    Permanently delete a pod. All inboxes and domains must be removed first.
-
-    You cannot delete a pod that still contains inboxes or domains.
-    Delete all child resources first, then delete the pod.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        pod_id: str = SchemaField(
-            description="Pod ID to permanently delete (must have no inboxes or domains)"
-        )
-
-    class Output(BlockSchemaOutput):
-        success: bool = SchemaField(
-            description="True if the pod was successfully deleted"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="f371f8cd-682d-4f5f-905c-529c74a8fb35",
-            description="Permanently delete a pod. All inboxes and domains must be removed first.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            is_sensitive_action=True,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={"credentials": TEST_CREDENTIALS_INPUT, "pod_id": "test-pod"},
-            test_output=[("success", True)],
-            test_mock={
-                "delete_pod": lambda *a, **kw: None,
-            },
-        )
-
-    @staticmethod
-    async def delete_pod(credentials: APIKeyCredentials, pod_id: str):
-        client = _client(credentials)
-        await client.pods.delete(pod_id=pod_id)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            await self.delete_pod(credentials, pod_id=input_data.pod_id)
-            yield "success", True
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailListPodInboxesBlock(Block):
-    """
-    List all inboxes within a specific pod (customer workspace).
-
-    Returns only the inboxes belonging to this pod, providing
-    tenant-scoped visibility.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        pod_id: str = SchemaField(description="Pod ID to list inboxes from")
-        limit: int = SchemaField(
-            description="Maximum number of inboxes to return per page (1-100)",
-            default=20,
-            advanced=True,
-        )
-        page_token: str = SchemaField(
-            description="Token from a previous response to fetch the next page",
-            default="",
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        inboxes: list[dict] = SchemaField(
-            description="List of inbox objects within this pod"
-        )
-        count: int = SchemaField(description="Number of inboxes returned")
-        next_page_token: str = SchemaField(
-            description="Token for the next page. Empty if no more results.",
-            default="",
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="a8c17ce0-b7c1-4bc3-ae39-680e1952e5d0",
-            description="List all inboxes within a pod. View email accounts scoped to a specific customer.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={"credentials": TEST_CREDENTIALS_INPUT, "pod_id": "test-pod"},
-            test_output=[
-                ("inboxes", []),
-                ("count", 0),
-                ("next_page_token", ""),
-            ],
-            test_mock={
-                "list_pod_inboxes": lambda *a, **kw: type(
-                    "Resp",
-                    (),
-                    {
-                        "inboxes": [],
-                        "count": 0,
-                        "next_page_token": "",
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def list_pod_inboxes(credentials: APIKeyCredentials, pod_id: str, **params):
-        client = _client(credentials)
-        return await client.pods.inboxes.list(pod_id=pod_id, **params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {"limit": input_data.limit}
-            if input_data.page_token:
-                params["page_token"] = input_data.page_token
-
-            response = await self.list_pod_inboxes(
-                credentials, pod_id=input_data.pod_id, **params
-            )
-            inboxes = [i.model_dump() for i in response.inboxes]
-
-            yield "inboxes", inboxes
-            yield "count", response.count
-            yield "next_page_token", response.next_page_token or ""
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailListPodThreadsBlock(Block):
-    """
-    List all conversation threads across all inboxes within a pod.
-
-    Returns threads from every inbox in the pod. Use for building
-    per-customer dashboards showing all email activity, or for
-    supervisor agents monitoring a customer's conversations.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        pod_id: str = SchemaField(description="Pod ID to list threads from")
-        limit: int = SchemaField(
-            description="Maximum number of threads to return per page (1-100)",
-            default=20,
-            advanced=True,
-        )
-        page_token: str = SchemaField(
-            description="Token from a previous response to fetch the next page",
-            default="",
-            advanced=True,
-        )
-        labels: list[str] = SchemaField(
-            description="Only return threads matching ALL of these labels",
-            default_factory=list,
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        threads: list[dict] = SchemaField(
-            description="List of thread objects from all inboxes in this pod"
-        )
-        count: int = SchemaField(description="Number of threads returned")
-        next_page_token: str = SchemaField(
-            description="Token for the next page. Empty if no more results.",
-            default="",
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="80214f08-8b85-4533-a6b8-f8123bfcb410",
-            description="List all conversation threads across all inboxes within a pod. View all email activity for a customer.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={"credentials": TEST_CREDENTIALS_INPUT, "pod_id": "test-pod"},
-            test_output=[
-                ("threads", []),
-                ("count", 0),
-                ("next_page_token", ""),
-            ],
-            test_mock={
-                "list_pod_threads": lambda *a, **kw: type(
-                    "Resp",
-                    (),
-                    {
-                        "threads": [],
-                        "count": 0,
-                        "next_page_token": "",
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def list_pod_threads(credentials: APIKeyCredentials, pod_id: str, **params):
-        client = _client(credentials)
-        return await client.pods.threads.list(pod_id=pod_id, **params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {"limit": input_data.limit}
-            if input_data.page_token:
-                params["page_token"] = input_data.page_token
-            if input_data.labels:
-                params["labels"] = input_data.labels
-
-            response = await self.list_pod_threads(
-                credentials, pod_id=input_data.pod_id, **params
-            )
-            threads = [t.model_dump() for t in response.threads]
-
-            yield "threads", threads
-            yield "count", response.count
-            yield "next_page_token", response.next_page_token or ""
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailListPodDraftsBlock(Block):
-    """
-    List all drafts across all inboxes within a pod.
-
-    Returns pending drafts from every inbox in the pod. Use for
-    per-customer approval dashboards or monitoring scheduled sends.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        pod_id: str = SchemaField(description="Pod ID to list drafts from")
-        limit: int = SchemaField(
-            description="Maximum number of drafts to return per page (1-100)",
-            default=20,
-            advanced=True,
-        )
-        page_token: str = SchemaField(
-            description="Token from a previous response to fetch the next page",
-            default="",
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        drafts: list[dict] = SchemaField(
-            description="List of draft objects from all inboxes in this pod"
-        )
-        count: int = SchemaField(description="Number of drafts returned")
-        next_page_token: str = SchemaField(
-            description="Token for the next page. Empty if no more results.",
-            default="",
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="12fd7a3e-51ad-4b20-97c1-0391f207f517",
-            description="List all drafts across all inboxes within a pod. View pending emails for a customer.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={"credentials": TEST_CREDENTIALS_INPUT, "pod_id": "test-pod"},
-            test_output=[
-                ("drafts", []),
-                ("count", 0),
-                ("next_page_token", ""),
-            ],
-            test_mock={
-                "list_pod_drafts": lambda *a, **kw: type(
-                    "Resp",
-                    (),
-                    {
-                        "drafts": [],
-                        "count": 0,
-                        "next_page_token": "",
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def list_pod_drafts(credentials: APIKeyCredentials, pod_id: str, **params):
-        client = _client(credentials)
-        return await client.pods.drafts.list(pod_id=pod_id, **params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {"limit": input_data.limit}
-            if input_data.page_token:
-                params["page_token"] = input_data.page_token
-
-            response = await self.list_pod_drafts(
-                credentials, pod_id=input_data.pod_id, **params
-            )
-            drafts = [d.model_dump() for d in response.drafts]
-
-            yield "drafts", drafts
-            yield "count", response.count
-            yield "next_page_token", response.next_page_token or ""
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailCreatePodInboxBlock(Block):
-    """
-    Create a new email inbox within a specific pod (customer workspace).
-
-    The inbox is automatically scoped to the pod and inherits its
-    isolation guarantees. If username/domain are not provided,
-    AgentMail auto-generates a unique address.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        pod_id: str = SchemaField(description="Pod ID to create the inbox in")
-        username: str = SchemaField(
-            description="Local part of the email address (e.g. 'support'). Leave empty to auto-generate.",
-            default="",
-        )
-        domain: str = SchemaField(
-            description="Email domain (e.g. 'mydomain.com'). Defaults to agentmail.to if empty.",
-            default="",
-        )
-        display_name: str = SchemaField(
-            description="Friendly name shown in the 'From' field (e.g. 'Customer Support')",
-            default="",
-        )
-
-    class Output(BlockSchemaOutput):
-        inbox_id: str = SchemaField(
-            description="Unique identifier of the created inbox"
-        )
-        email_address: str = SchemaField(description="Full email address of the inbox")
-        result: dict = SchemaField(
-            description="Complete inbox object with all metadata"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="c6862373-1ac6-402e-89e6-7db1fea882af",
-            description="Create a new email inbox within a pod. The inbox is scoped to the customer workspace.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={"credentials": TEST_CREDENTIALS_INPUT, "pod_id": "test-pod"},
-            test_output=[
-                ("inbox_id", "mock-inbox-id"),
-                ("email_address", "mock-inbox-id"),
-                ("result", dict),
-            ],
-            test_mock={
-                "create_pod_inbox": lambda *a, **kw: type(
-                    "Inbox",
-                    (),
-                    {
-                        "inbox_id": "mock-inbox-id",
-                        "model_dump": lambda self: {"inbox_id": "mock-inbox-id"},
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def create_pod_inbox(credentials: APIKeyCredentials, pod_id: str, **params):
-        client = _client(credentials)
-        return await client.pods.inboxes.create(pod_id=pod_id, **params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {}
-            if input_data.username:
-                params["username"] = input_data.username
-            if input_data.domain:
-                params["domain"] = input_data.domain
-            if input_data.display_name:
-                params["display_name"] = input_data.display_name
-
-            inbox = await self.create_pod_inbox(
-                credentials, pod_id=input_data.pod_id, **params
-            )
-            result = inbox.model_dump()
-
-            yield "inbox_id", inbox.inbox_id
-            yield "email_address", inbox.inbox_id
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)

autogpt_platform/backend/backend/blocks/agent_mail/threads.py

@@ -1,438 +0,0 @@
-"""
-AgentMail Thread blocks — list, get, and delete conversation threads.
-
-A Thread groups related messages into a single conversation. Threads are
-created automatically when a new message is sent and grow as replies are added.
-Threads can be queried per-inbox or across the entire organization.
-"""
-
-from backend.sdk import (
-    APIKeyCredentials,
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-    CredentialsMetaInput,
-    SchemaField,
-)
-
-from ._config import TEST_CREDENTIALS, TEST_CREDENTIALS_INPUT, _client, agent_mail
-
-
-class AgentMailListInboxThreadsBlock(Block):
-    """
-    List all conversation threads within a specific AgentMail inbox.
-
-    Returns a paginated list of threads with optional label filtering.
-    Use labels to find threads by campaign, status, or custom tags.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address to list threads from"
-        )
-        limit: int = SchemaField(
-            description="Maximum number of threads to return per page (1-100)",
-            default=20,
-            advanced=True,
-        )
-        page_token: str = SchemaField(
-            description="Token from a previous response to fetch the next page",
-            default="",
-            advanced=True,
-        )
-        labels: list[str] = SchemaField(
-            description="Only return threads matching ALL of these labels (e.g. ['q4-campaign', 'follow-up'])",
-            default_factory=list,
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        threads: list[dict] = SchemaField(
-            description="List of thread objects with thread_id, subject, message count, labels, etc."
-        )
-        count: int = SchemaField(description="Number of threads returned")
-        next_page_token: str = SchemaField(
-            description="Token for the next page. Empty if no more results.",
-            default="",
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="63dd9e2d-ef81-405c-b034-c031f0437334",
-            description="List all conversation threads in an AgentMail inbox. Filter by labels for campaign tracking or status management.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-            },
-            test_output=[
-                ("threads", []),
-                ("count", 0),
-                ("next_page_token", ""),
-            ],
-            test_mock={
-                "list_threads": lambda *a, **kw: type(
-                    "Resp",
-                    (),
-                    {
-                        "threads": [],
-                        "count": 0,
-                        "next_page_token": "",
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def list_threads(credentials: APIKeyCredentials, inbox_id: str, **params):
-        client = _client(credentials)
-        return await client.inboxes.threads.list(inbox_id=inbox_id, **params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {"limit": input_data.limit}
-            if input_data.page_token:
-                params["page_token"] = input_data.page_token
-            if input_data.labels:
-                params["labels"] = input_data.labels
-
-            response = await self.list_threads(
-                credentials, input_data.inbox_id, **params
-            )
-            threads = [t.model_dump() for t in response.threads]
-
-            yield "threads", threads
-            yield "count", (c if (c := response.count) is not None else len(threads))
-            yield "next_page_token", response.next_page_token or ""
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailGetInboxThreadBlock(Block):
-    """
-    Retrieve a single conversation thread from an AgentMail inbox.
-
-    Returns the thread with all its messages in chronological order.
-    Use this to get the full conversation history for context when
-    composing replies.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address the thread belongs to"
-        )
-        thread_id: str = SchemaField(description="Thread ID to retrieve")
-
-    class Output(BlockSchemaOutput):
-        thread_id: str = SchemaField(description="Unique identifier of the thread")
-        messages: list[dict] = SchemaField(
-            description="All messages in the thread, in chronological order"
-        )
-        result: dict = SchemaField(
-            description="Complete thread object with all metadata"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="42866290-1479-4153-83e7-550b703e9da2",
-            description="Retrieve a conversation thread with all its messages. Use for getting full conversation context before replying.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-                "thread_id": "test-thread",
-            },
-            test_output=[
-                ("thread_id", "test-thread"),
-                ("messages", []),
-                ("result", dict),
-            ],
-            test_mock={
-                "get_thread": lambda *a, **kw: type(
-                    "Thread",
-                    (),
-                    {
-                        "thread_id": "test-thread",
-                        "messages": [],
-                        "model_dump": lambda self: {
-                            "thread_id": "test-thread",
-                            "messages": [],
-                        },
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def get_thread(credentials: APIKeyCredentials, inbox_id: str, thread_id: str):
-        client = _client(credentials)
-        return await client.inboxes.threads.get(inbox_id=inbox_id, thread_id=thread_id)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            thread = await self.get_thread(
-                credentials, input_data.inbox_id, input_data.thread_id
-            )
-            messages = [m.model_dump() for m in thread.messages]
-            result = thread.model_dump()
-            result["messages"] = messages
-
-            yield "thread_id", thread.thread_id
-            yield "messages", messages
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailDeleteInboxThreadBlock(Block):
-    """
-    Permanently delete a conversation thread and all its messages from an inbox.
-
-    This removes the thread and every message within it. This action
-    cannot be undone.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        inbox_id: str = SchemaField(
-            description="Inbox ID or email address the thread belongs to"
-        )
-        thread_id: str = SchemaField(description="Thread ID to permanently delete")
-
-    class Output(BlockSchemaOutput):
-        success: bool = SchemaField(
-            description="True if the thread was successfully deleted"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="18cd5f6f-4ff6-45da-8300-25a50ea7fb75",
-            description="Permanently delete a conversation thread and all its messages. This action cannot be undone.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            is_sensitive_action=True,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "inbox_id": "test-inbox",
-                "thread_id": "test-thread",
-            },
-            test_output=[("success", True)],
-            test_mock={
-                "delete_thread": lambda *a, **kw: None,
-            },
-        )
-
-    @staticmethod
-    async def delete_thread(
-        credentials: APIKeyCredentials, inbox_id: str, thread_id: str
-    ):
-        client = _client(credentials)
-        await client.inboxes.threads.delete(inbox_id=inbox_id, thread_id=thread_id)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            await self.delete_thread(
-                credentials, input_data.inbox_id, input_data.thread_id
-            )
-            yield "success", True
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailListOrgThreadsBlock(Block):
-    """
-    List conversation threads across ALL inboxes in your organization.
-
-    Unlike per-inbox listing, this returns threads from every inbox.
-    Ideal for building supervisor agents that monitor all conversations,
-    analytics dashboards, or cross-agent routing workflows.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        limit: int = SchemaField(
-            description="Maximum number of threads to return per page (1-100)",
-            default=20,
-            advanced=True,
-        )
-        page_token: str = SchemaField(
-            description="Token from a previous response to fetch the next page",
-            default="",
-            advanced=True,
-        )
-        labels: list[str] = SchemaField(
-            description="Only return threads matching ALL of these labels",
-            default_factory=list,
-            advanced=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        threads: list[dict] = SchemaField(
-            description="List of thread objects from all inboxes in the organization"
-        )
-        count: int = SchemaField(description="Number of threads returned")
-        next_page_token: str = SchemaField(
-            description="Token for the next page. Empty if no more results.",
-            default="",
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="d7a0657b-58ab-48b2-898b-7bd94f44a708",
-            description="List threads across ALL inboxes in your organization. Use for supervisor agents, dashboards, or cross-agent monitoring.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={"credentials": TEST_CREDENTIALS_INPUT},
-            test_output=[
-                ("threads", []),
-                ("count", 0),
-                ("next_page_token", ""),
-            ],
-            test_mock={
-                "list_org_threads": lambda *a, **kw: type(
-                    "Resp",
-                    (),
-                    {
-                        "threads": [],
-                        "count": 0,
-                        "next_page_token": "",
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def list_org_threads(credentials: APIKeyCredentials, **params):
-        client = _client(credentials)
-        return await client.threads.list(**params)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            params: dict = {"limit": input_data.limit}
-            if input_data.page_token:
-                params["page_token"] = input_data.page_token
-            if input_data.labels:
-                params["labels"] = input_data.labels
-
-            response = await self.list_org_threads(credentials, **params)
-            threads = [t.model_dump() for t in response.threads]
-
-            yield "threads", threads
-            yield "count", (c if (c := response.count) is not None else len(threads))
-            yield "next_page_token", response.next_page_token or ""
-        except Exception as e:
-            yield "error", str(e)
-
-
-class AgentMailGetOrgThreadBlock(Block):
-    """
-    Retrieve a single conversation thread by ID from anywhere in the organization.
-
-    Works without needing to know which inbox the thread belongs to.
-    Returns the thread with all its messages in chronological order.
-    """
-
-    class Input(BlockSchemaInput):
-        credentials: CredentialsMetaInput = agent_mail.credentials_field(
-            description="AgentMail API key from https://console.agentmail.to"
-        )
-        thread_id: str = SchemaField(
-            description="Thread ID to retrieve (works across all inboxes)"
-        )
-
-    class Output(BlockSchemaOutput):
-        thread_id: str = SchemaField(description="Unique identifier of the thread")
-        messages: list[dict] = SchemaField(
-            description="All messages in the thread, in chronological order"
-        )
-        result: dict = SchemaField(
-            description="Complete thread object with all metadata"
-        )
-        error: str = SchemaField(description="Error message if the operation failed")
-
-    def __init__(self):
-        super().__init__(
-            id="39aaae31-3eb1-44c6-9e37-5a44a4529649",
-            description="Retrieve a conversation thread by ID from anywhere in the organization, without needing the inbox ID.",
-            categories={BlockCategory.COMMUNICATION},
-            input_schema=self.Input,
-            output_schema=self.Output,
-            test_credentials=TEST_CREDENTIALS,
-            test_input={
-                "credentials": TEST_CREDENTIALS_INPUT,
-                "thread_id": "test-thread",
-            },
-            test_output=[
-                ("thread_id", "test-thread"),
-                ("messages", []),
-                ("result", dict),
-            ],
-            test_mock={
-                "get_org_thread": lambda *a, **kw: type(
-                    "Thread",
-                    (),
-                    {
-                        "thread_id": "test-thread",
-                        "messages": [],
-                        "model_dump": lambda self: {
-                            "thread_id": "test-thread",
-                            "messages": [],
-                        },
-                    },
-                )(),
-            },
-        )
-
-    @staticmethod
-    async def get_org_thread(credentials: APIKeyCredentials, thread_id: str):
-        client = _client(credentials)
-        return await client.threads.get(thread_id=thread_id)
-
-    async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
-    ) -> BlockOutput:
-        try:
-            thread = await self.get_org_thread(credentials, input_data.thread_id)
-            messages = [m.model_dump() for m in thread.messages]
-            result = thread.model_dump()
-            result["messages"] = messages
-
-            yield "thread_id", thread.thread_id
-            yield "messages", messages
-            yield "result", result
-        except Exception as e:
-            yield "error", str(e)

autogpt_platform/backend/backend/blocks/ai_condition.py

@@ -1,4 +1,3 @@
-import re
 from typing import Any
 
 from backend.blocks._base import (
@@ -20,33 +19,6 @@ from backend.blocks.llm import (
 )
 from backend.data.model import APIKeyCredentials, NodeExecutionStats, SchemaField
 
-# Minimum max_output_tokens accepted by OpenAI-compatible APIs.
-# A true/false answer fits comfortably within this budget.
-MIN_LLM_OUTPUT_TOKENS = 16
-
-
-def _parse_boolean_response(response_text: str) -> tuple[bool, str | None]:
-    """Parse an LLM response into a boolean result.
-
-    Returns a ``(result, error)`` tuple.  *error* is ``None`` when the
-    response is unambiguous; otherwise it contains a diagnostic message
-    and *result* defaults to ``False``.
-    """
-    text = response_text.strip().lower()
-    if text == "true":
-        return True, None
-    if text == "false":
-        return False, None
-
-    # Fuzzy match – use word boundaries to avoid false positives like "untrue".
-    tokens = set(re.findall(r"\b(true|false|yes|no|1|0)\b", text))
-    if tokens == {"true"} or tokens == {"yes"} or tokens == {"1"}:
-        return True, None
-    if tokens == {"false"} or tokens == {"no"} or tokens == {"0"}:
-        return False, None
-
-    return False, f"Unclear AI response: '{response_text}'"
-
 
 class AIConditionBlock(AIBlockBase):
     """
@@ -190,26 +162,54 @@ class AIConditionBlock(AIBlockBase):
         ]
 
         # Call the LLM
-        response = await self.llm_call(
-            credentials=credentials,
-            llm_model=input_data.model,
-            prompt=prompt,
-            max_tokens=MIN_LLM_OUTPUT_TOKENS,
-        )
-
-        # Extract the boolean result from the response
-        result, error = _parse_boolean_response(response.response)
-        if error:
-            yield "error", error
-
-        # Update internal stats
-        self.merge_stats(
-            NodeExecutionStats(
-                input_token_count=response.prompt_tokens,
-                output_token_count=response.completion_tokens,
+        try:
+            response = await self.llm_call(
+                credentials=credentials,
+                llm_model=input_data.model,
+                prompt=prompt,
+                max_tokens=10,  # We only expect a true/false response
             )
-        )
-        self.prompt = response.prompt
+
+            # Extract the boolean result from the response
+            response_text = response.response.strip().lower()
+            if response_text == "true":
+                result = True
+            elif response_text == "false":
+                result = False
+            else:
+                # If the response is not clear, try to interpret it using word boundaries
+                import re
+
+                # Use word boundaries to avoid false positives like 'untrue' or '10'
+                tokens = set(re.findall(r"\b(true|false|yes|no|1|0)\b", response_text))
+
+                if tokens == {"true"} or tokens == {"yes"} or tokens == {"1"}:
+                    result = True
+                elif tokens == {"false"} or tokens == {"no"} or tokens == {"0"}:
+                    result = False
+                else:
+                    # Unclear or conflicting response - default to False and yield error
+                    result = False
+                    yield "error", f"Unclear AI response: '{response.response}'"
+
+            # Update internal stats
+            self.merge_stats(
+                NodeExecutionStats(
+                    input_token_count=response.prompt_tokens,
+                    output_token_count=response.completion_tokens,
+                )
+            )
+            self.prompt = response.prompt
+
+        except Exception as e:
+            # In case of any error, default to False to be safe
+            result = False
+            # Log the error but don't fail the block execution
+            import logging
+
+            logger = logging.getLogger(__name__)
+            logger.error(f"AI condition evaluation failed: {str(e)}")
+            yield "error", f"AI evaluation failed: {str(e)}"
 
         # Yield results
         yield "result", result

autogpt_platform/backend/backend/blocks/ai_condition_test.py

@@ -1,147 +0,0 @@
-"""Tests for AIConditionBlock – regression coverage for max_tokens and error propagation."""
-
-from __future__ import annotations
-
-from typing import cast
-
-import pytest
-
-from backend.blocks.ai_condition import (
-    MIN_LLM_OUTPUT_TOKENS,
-    AIConditionBlock,
-    _parse_boolean_response,
-)
-from backend.blocks.llm import (
-    DEFAULT_LLM_MODEL,
-    TEST_CREDENTIALS,
-    TEST_CREDENTIALS_INPUT,
-    AICredentials,
-    LLMResponse,
-)
-
-_TEST_AI_CREDENTIALS = cast(AICredentials, TEST_CREDENTIALS_INPUT)
-
-
-# ---------------------------------------------------------------------------
-# Helper to collect all yields from the async generator
-# ---------------------------------------------------------------------------
-
-
-async def _collect_outputs(block: AIConditionBlock, input_data, credentials):
-    outputs: dict[str, object] = {}
-    async for name, value in block.run(input_data, credentials=credentials):
-        outputs[name] = value
-    return outputs
-
-
-def _make_input(**overrides) -> AIConditionBlock.Input:
-    defaults: dict = {
-        "input_value": "hello@example.com",
-        "condition": "the input is an email address",
-        "yes_value": "yes!",
-        "no_value": "no!",
-        "model": DEFAULT_LLM_MODEL,
-        "credentials": TEST_CREDENTIALS_INPUT,
-    }
-    defaults.update(overrides)
-    return AIConditionBlock.Input(**defaults)
-
-
-def _mock_llm_response(response_text: str) -> LLMResponse:
-    return LLMResponse(
-        raw_response="",
-        prompt=[],
-        response=response_text,
-        tool_calls=None,
-        prompt_tokens=10,
-        completion_tokens=5,
-        reasoning=None,
-    )
-
-
-# ---------------------------------------------------------------------------
-# _parse_boolean_response unit tests
-# ---------------------------------------------------------------------------
-
-
-class TestParseBooleanResponse:
-    def test_true_exact(self):
-        assert _parse_boolean_response("true") == (True, None)
-
-    def test_false_exact(self):
-        assert _parse_boolean_response("false") == (False, None)
-
-    def test_true_with_whitespace(self):
-        assert _parse_boolean_response("  True  ") == (True, None)
-
-    def test_yes_fuzzy(self):
-        assert _parse_boolean_response("Yes") == (True, None)
-
-    def test_no_fuzzy(self):
-        assert _parse_boolean_response("no") == (False, None)
-
-    def test_one_fuzzy(self):
-        assert _parse_boolean_response("1") == (True, None)
-
-    def test_zero_fuzzy(self):
-        assert _parse_boolean_response("0") == (False, None)
-
-    def test_unclear_response(self):
-        result, error = _parse_boolean_response("I'm not sure")
-        assert result is False
-        assert error is not None
-        assert "Unclear" in error
-
-    def test_conflicting_tokens(self):
-        result, error = _parse_boolean_response("true and false")
-        assert result is False
-        assert error is not None
-
-
-# ---------------------------------------------------------------------------
-# Regression: max_tokens is set to MIN_LLM_OUTPUT_TOKENS
-# ---------------------------------------------------------------------------
-
-
-class TestMaxTokensRegression:
-    @pytest.mark.asyncio
-    async def test_llm_call_receives_min_output_tokens(self):
-        """max_tokens must be MIN_LLM_OUTPUT_TOKENS (16) – the previous value
-        of 1 was too low and caused OpenAI to reject the request."""
-        block = AIConditionBlock()
-        captured_kwargs: dict = {}
-
-        async def spy_llm_call(**kwargs):
-            captured_kwargs.update(kwargs)
-            return _mock_llm_response("true")
-
-        block.llm_call = spy_llm_call  # type: ignore[assignment]
-
-        input_data = _make_input()
-        await _collect_outputs(block, input_data, credentials=TEST_CREDENTIALS)
-
-        assert captured_kwargs["max_tokens"] == MIN_LLM_OUTPUT_TOKENS
-        assert captured_kwargs["max_tokens"] == 16
-
-
-# ---------------------------------------------------------------------------
-# Regression: exceptions from llm_call must propagate
-# ---------------------------------------------------------------------------
-
-
-class TestExceptionPropagation:
-    @pytest.mark.asyncio
-    async def test_llm_call_exception_propagates(self):
-        """If llm_call raises, the exception must NOT be swallowed.
-        Previously the block caught all exceptions and silently returned
-        result=False."""
-        block = AIConditionBlock()
-
-        async def boom(**kwargs):
-            raise RuntimeError("LLM provider error")
-
-        block.llm_call = boom  # type: ignore[assignment]
-
-        input_data = _make_input()
-        with pytest.raises(RuntimeError, match="LLM provider error"):
-            await _collect_outputs(block, input_data, credentials=TEST_CREDENTIALS)

autogpt_platform/backend/backend/blocks/ai_image_customizer.py

@@ -27,7 +27,6 @@ from backend.util.file import MediaFileType, store_media_file
 class GeminiImageModel(str, Enum):
     NANO_BANANA = "google/nano-banana"
     NANO_BANANA_PRO = "google/nano-banana-pro"
-    NANO_BANANA_2 = "google/nano-banana-2"
 
 
 class AspectRatio(str, Enum):
@@ -78,7 +77,7 @@ class AIImageCustomizerBlock(Block):
         )
         model: GeminiImageModel = SchemaField(
             description="The AI model to use for image generation and editing",
-            default=GeminiImageModel.NANO_BANANA_2,
+            default=GeminiImageModel.NANO_BANANA,
             title="Model",
         )
         images: list[MediaFileType] = SchemaField(
@@ -104,7 +103,7 @@ class AIImageCustomizerBlock(Block):
         super().__init__(
             id="d76bbe4c-930e-4894-8469-b66775511f71",
             description=(
-                "Generate and edit custom images using Google's Nano-Banana models from Gemini. "
+                "Generate and edit custom images using Google's Nano-Banana model from Gemini 2.5. "
                 "Provide a prompt and optional reference images to create or modify images."
             ),
             categories={BlockCategory.AI, BlockCategory.MULTIMEDIA},
@@ -112,7 +111,7 @@ class AIImageCustomizerBlock(Block):
             output_schema=AIImageCustomizerBlock.Output,
             test_input={
                 "prompt": "Make the scene more vibrant and colorful",
-                "model": GeminiImageModel.NANO_BANANA_2,
+                "model": GeminiImageModel.NANO_BANANA,
                 "images": [],
                 "aspect_ratio": AspectRatio.MATCH_INPUT_IMAGE,
                 "output_format": OutputFormat.JPG,

autogpt_platform/backend/backend/blocks/ai_image_generator_block.py

@@ -115,7 +115,6 @@ class ImageGenModel(str, Enum):
     RECRAFT = "Recraft v3"
     SD3_5 = "Stable Diffusion 3.5 Medium"
     NANO_BANANA_PRO = "Nano Banana Pro"
-    NANO_BANANA_2 = "Nano Banana 2"
 
 
 class AIImageGeneratorBlock(Block):
@@ -132,7 +131,7 @@ class AIImageGeneratorBlock(Block):
         )
         model: ImageGenModel = SchemaField(
             description="The AI model to use for image generation",
-            default=ImageGenModel.NANO_BANANA_2,
+            default=ImageGenModel.SD3_5,
             title="Model",
         )
         size: ImageSize = SchemaField(
@@ -166,7 +165,7 @@ class AIImageGeneratorBlock(Block):
             test_input={
                 "credentials": TEST_CREDENTIALS_INPUT,
                 "prompt": "An octopus using a laptop in a snowy forest with 'AutoGPT' clearly visible on the screen",
-                "model": ImageGenModel.NANO_BANANA_2,
+                "model": ImageGenModel.RECRAFT,
                 "size": ImageSize.SQUARE,
                 "style": ImageStyle.REALISTIC,
             },
@@ -180,9 +179,7 @@ class AIImageGeneratorBlock(Block):
             ],
             test_mock={
                 # Return a data URI directly so store_media_file doesn't need to download
-                "_run_client": lambda *args, **kwargs: (
-                    "data:image/webp;base64,UklGRiQAAABXRUJQVlA4IBgAAAAwAQCdASoBAAEAAQAcJYgCdAEO"
-                )
+                "_run_client": lambda *args, **kwargs: "data:image/webp;base64,UklGRiQAAABXRUJQVlA4IBgAAAAwAQCdASoBAAEAAQAcJYgCdAEO"
             },
         )
 
@@ -283,24 +280,17 @@ class AIImageGeneratorBlock(Block):
                 )
                 return output
 
-            elif input_data.model in (
-                ImageGenModel.NANO_BANANA_PRO,
-                ImageGenModel.NANO_BANANA_2,
-            ):
-                # Use Nano Banana models (Google Gemini image variants)
-                model_map = {
-                    ImageGenModel.NANO_BANANA_PRO: "google/nano-banana-pro",
-                    ImageGenModel.NANO_BANANA_2: "google/nano-banana-2",
-                }
+            elif input_data.model == ImageGenModel.NANO_BANANA_PRO:
+                # Use Nano Banana Pro (Google Gemini 3 Pro Image)
                 input_params = {
                     "prompt": modified_prompt,
                     "aspect_ratio": SIZE_TO_NANO_BANANA_RATIO[input_data.size],
-                    "resolution": "2K",
+                    "resolution": "2K",  # Default to 2K for good quality/cost balance
                     "output_format": "jpg",
-                    "safety_filter_level": "block_only_high",
+                    "safety_filter_level": "block_only_high",  # Most permissive
                 }
                 output = await self._run_client(
-                    credentials, model_map[input_data.model], input_params
+                    credentials, "google/nano-banana-pro", input_params
                 )
                 return output
 

autogpt_platform/backend/backend/blocks/autopilot.py

@@ -1,520 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-import contextvars
-import json
-import logging
-from typing import TYPE_CHECKING, Any
-
-from typing_extensions import TypedDict  # Needed for Python <3.12 compatibility
-
-from backend.blocks._base import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
-from backend.copilot.permissions import (
-    CopilotPermissions,
-    ToolName,
-    all_known_tool_names,
-    validate_block_identifiers,
-)
-from backend.data.model import SchemaField
-
-if TYPE_CHECKING:
-    from backend.data.execution import ExecutionContext
-
-logger = logging.getLogger(__name__)
-
-# Block ID shared between autopilot.py and copilot prompting.py.
-AUTOPILOT_BLOCK_ID = "c069dc6b-c3ed-4c12-b6e5-d47361e64ce6"
-
-
-class ToolCallEntry(TypedDict):
-    """A single tool invocation record from an autopilot execution."""
-
-    tool_call_id: str
-    tool_name: str
-    input: Any
-    output: Any | None
-    success: bool | None
-
-
-class TokenUsage(TypedDict):
-    """Aggregated token counts from the autopilot stream."""
-
-    prompt_tokens: int
-    completion_tokens: int
-    total_tokens: int
-
-
-class AutoPilotBlock(Block):
-    """Execute tasks using AutoGPT AutoPilot with full access to platform tools.
-
-    The autopilot can manage agents, access workspace files, fetch web content,
-    run blocks, and more. This block enables sub-agent patterns (autopilot calling
-    autopilot) and scheduled autopilot execution via the agent executor.
-    """
-
-    class Input(BlockSchemaInput):
-        """Input schema for the AutoPilot block."""
-
-        prompt: str = SchemaField(
-            description=(
-                "The task or instruction for the autopilot to execute. "
-                "The autopilot has access to platform tools like agent management, "
-                "workspace files, web fetch, block execution, and more."
-            ),
-            placeholder="Find my agents and list them",
-            advanced=False,
-        )
-
-        system_context: str = SchemaField(
-            description=(
-                "Optional additional context prepended to the prompt. "
-                "Use this to constrain autopilot behavior, provide domain "
-                "context, or set output format requirements."
-            ),
-            default="",
-            advanced=True,
-        )
-
-        session_id: str = SchemaField(
-            description=(
-                "Session ID to continue an existing autopilot conversation. "
-                "Leave empty to start a new session. "
-                "Use the session_id output from a previous run to continue."
-            ),
-            default="",
-            advanced=True,
-        )
-
-        max_recursion_depth: int = SchemaField(
-            description=(
-                "Maximum nesting depth when the autopilot calls this block "
-                "recursively (sub-agent pattern). Prevents infinite loops."
-            ),
-            default=3,
-            ge=1,
-            le=10,
-            advanced=True,
-        )
-
-        tools: list[ToolName] = SchemaField(
-            description=(
-                "Tool names to filter. Works with tools_exclude to form an "
-                "allow-list or deny-list. "
-                "Leave empty to apply no tool filter."
-            ),
-            default=[],
-            advanced=True,
-        )
-
-        tools_exclude: bool = SchemaField(
-            description=(
-                "Controls how the 'tools' list is interpreted. "
-                "True (default): 'tools' is a deny-list — listed tools are blocked, "
-                "all others are allowed. An empty 'tools' list means allow everything. "
-                "False: 'tools' is an allow-list — only listed tools are permitted."
-            ),
-            default=True,
-            advanced=True,
-        )
-
-        blocks: list[str] = SchemaField(
-            description=(
-                "Block identifiers to filter when the copilot uses run_block. "
-                "Each entry can be: a block name (e.g. 'HTTP Request'), "
-                "a full block UUID, or the first 8 hex characters of the UUID "
-                "(e.g. 'c069dc6b'). Works with blocks_exclude. "
-                "Leave empty to apply no block filter."
-            ),
-            default=[],
-            advanced=True,
-        )
-
-        blocks_exclude: bool = SchemaField(
-            description=(
-                "Controls how the 'blocks' list is interpreted. "
-                "True (default): 'blocks' is a deny-list — listed blocks are blocked, "
-                "all others are allowed. An empty 'blocks' list means allow everything. "
-                "False: 'blocks' is an allow-list — only listed blocks are permitted."
-            ),
-            default=True,
-            advanced=True,
-        )
-
-        # timeout_seconds removed: the SDK manages its own heartbeat-based
-        # timeouts internally; wrapping with asyncio.timeout corrupts the
-        # SDK's internal stream (see service.py CRITICAL comment).
-
-    class Output(BlockSchemaOutput):
-        """Output schema for the AutoPilot block."""
-
-        response: str = SchemaField(
-            description="The final text response from the autopilot."
-        )
-        tool_calls: list[ToolCallEntry] = SchemaField(
-            description=(
-                "List of tools called during execution. Each entry has "
-                "tool_call_id, tool_name, input, output, and success fields."
-            ),
-        )
-        conversation_history: str = SchemaField(
-            description=(
-                "Current turn messages (user prompt + assistant reply) as JSON. "
-                "It can be used for logging or analysis."
-            ),
-        )
-        session_id: str = SchemaField(
-            description=(
-                "Session ID for this conversation. "
-                "Pass this back to continue the conversation in a future run."
-            ),
-        )
-        token_usage: TokenUsage = SchemaField(
-            description=(
-                "Token usage statistics: prompt_tokens, "
-                "completion_tokens, total_tokens."
-            ),
-        )
-
-    def __init__(self):
-        super().__init__(
-            id=AUTOPILOT_BLOCK_ID,
-            description=(
-                "Execute tasks using AutoGPT AutoPilot with full access to "
-                "platform tools (agent management, workspace files, web fetch, "
-                "block execution, and more). Enables sub-agent patterns and "
-                "scheduled autopilot execution."
-            ),
-            categories={BlockCategory.AI, BlockCategory.AGENT},
-            input_schema=AutoPilotBlock.Input,
-            output_schema=AutoPilotBlock.Output,
-            test_input={
-                "prompt": "List my agents",
-                "system_context": "",
-                "session_id": "",
-                "max_recursion_depth": 3,
-            },
-            test_output=[
-                ("response", "You have 2 agents: Agent A and Agent B."),
-                ("tool_calls", []),
-                (
-                    "conversation_history",
-                    '[{"role": "user", "content": "List my agents"}]',
-                ),
-                ("session_id", "test-session-id"),
-                (
-                    "token_usage",
-                    {
-                        "prompt_tokens": 100,
-                        "completion_tokens": 50,
-                        "total_tokens": 150,
-                    },
-                ),
-            ],
-            test_mock={
-                "create_session": lambda *args, **kwargs: "test-session-id",
-                "execute_copilot": lambda *args, **kwargs: (
-                    "You have 2 agents: Agent A and Agent B.",
-                    [],
-                    '[{"role": "user", "content": "List my agents"}]',
-                    "test-session-id",
-                    {
-                        "prompt_tokens": 100,
-                        "completion_tokens": 50,
-                        "total_tokens": 150,
-                    },
-                ),
-            },
-        )
-
-    async def create_session(self, user_id: str) -> str:
-        """Create a new chat session and return its ID (mockable for tests)."""
-        from backend.copilot.model import create_chat_session  # avoid circular import
-
-        session = await create_chat_session(user_id)
-        return session.session_id
-
-    async def execute_copilot(
-        self,
-        prompt: str,
-        system_context: str,
-        session_id: str,
-        max_recursion_depth: int,
-        user_id: str,
-        permissions: "CopilotPermissions | None" = None,
-    ) -> tuple[str, list[ToolCallEntry], str, str, TokenUsage]:
-        """Invoke the copilot and collect all stream results.
-
-        Delegates to :func:`collect_copilot_response` — the shared helper that
-        consumes ``stream_chat_completion_sdk`` without wrapping it in an
-        ``asyncio.timeout`` (the SDK manages its own heartbeat-based timeouts).
-
-        Args:
-            prompt: The user task/instruction.
-            system_context: Optional context prepended to the prompt.
-            session_id: Chat session to use.
-            max_recursion_depth: Maximum allowed recursion nesting.
-            user_id: Authenticated user ID.
-            permissions: Optional capability filter restricting tools/blocks.
-
-        Returns:
-            A tuple of (response_text, tool_calls, history_json, session_id, usage).
-        """
-        from backend.copilot.sdk.collect import (
-            collect_copilot_response,  # avoid circular import
-        )
-
-        tokens = _check_recursion(max_recursion_depth)
-        perm_token = None
-        try:
-            effective_permissions, perm_token = _merge_inherited_permissions(
-                permissions
-            )
-            effective_prompt = prompt
-            if system_context:
-                effective_prompt = f"[System Context: {system_context}]\n\n{prompt}"
-
-            result = await collect_copilot_response(
-                session_id=session_id,
-                message=effective_prompt,
-                user_id=user_id,
-                permissions=effective_permissions,
-            )
-
-            # Build a lightweight conversation summary from streamed data.
-            turn_messages: list[dict[str, Any]] = [
-                {"role": "user", "content": effective_prompt},
-            ]
-            if result.tool_calls:
-                turn_messages.append(
-                    {
-                        "role": "assistant",
-                        "content": result.response_text,
-                        "tool_calls": result.tool_calls,
-                    }
-                )
-            else:
-                turn_messages.append(
-                    {"role": "assistant", "content": result.response_text}
-                )
-            history_json = json.dumps(turn_messages, default=str)
-
-            tool_calls: list[ToolCallEntry] = [
-                {
-                    "tool_call_id": tc["tool_call_id"],
-                    "tool_name": tc["tool_name"],
-                    "input": tc["input"],
-                    "output": tc["output"],
-                    "success": tc["success"],
-                }
-                for tc in result.tool_calls
-            ]
-
-            usage: TokenUsage = {
-                "prompt_tokens": result.prompt_tokens,
-                "completion_tokens": result.completion_tokens,
-                "total_tokens": result.total_tokens,
-            }
-
-            return (
-                result.response_text,
-                tool_calls,
-                history_json,
-                session_id,
-                usage,
-            )
-        finally:
-            _reset_recursion(tokens)
-            if perm_token is not None:
-                _inherited_permissions.reset(perm_token)
-
-    async def run(
-        self,
-        input_data: Input,
-        *,
-        execution_context: ExecutionContext,
-        **kwargs,
-    ) -> BlockOutput:
-        """Validate inputs, invoke the autopilot, and yield structured outputs.
-
-        Yields session_id even on failure so callers can inspect/resume the session.
-        """
-        if not input_data.prompt.strip():
-            yield "error", "Prompt cannot be empty."
-            return
-
-        if not execution_context.user_id:
-            yield "error", "Cannot run autopilot without an authenticated user."
-            return
-
-        if input_data.max_recursion_depth < 1:
-            yield "error", "max_recursion_depth must be at least 1."
-            return
-
-        # Validate and build permissions eagerly — fail before creating a session.
-        permissions = await _build_and_validate_permissions(input_data)
-        if isinstance(permissions, str):
-            # Validation error returned as a string message.
-            yield "error", permissions
-            return
-
-        # Create session eagerly so the user always gets the session_id,
-        # even if the downstream stream fails (avoids orphaned sessions).
-        sid = input_data.session_id
-        if not sid:
-            sid = await self.create_session(execution_context.user_id)
-
-        # NOTE: No asyncio.timeout() here — the SDK manages its own
-        # heartbeat-based timeouts internally.  Wrapping with asyncio.timeout
-        # would cancel the task mid-flight, corrupting the SDK's internal
-        # anyio memory stream (see service.py CRITICAL comment).
-        try:
-            response, tool_calls, history, _, usage = await self.execute_copilot(
-                prompt=input_data.prompt,
-                system_context=input_data.system_context,
-                session_id=sid,
-                max_recursion_depth=input_data.max_recursion_depth,
-                user_id=execution_context.user_id,
-                permissions=permissions,
-            )
-
-            yield "response", response
-            yield "tool_calls", tool_calls
-            yield "conversation_history", history
-            yield "session_id", sid
-            yield "token_usage", usage
-        except asyncio.CancelledError:
-            yield "session_id", sid
-            yield "error", "AutoPilot execution was cancelled."
-            raise
-        except Exception as exc:
-            yield "session_id", sid
-            yield "error", str(exc)
-
-
-# ---------------------------------------------------------------------------
-# Helpers – placed after the block class for top-down readability.
-# ---------------------------------------------------------------------------
-
-# Task-scoped recursion depth counter & chain-wide limit.
-# contextvars are scoped to the current asyncio task, so concurrent
-# graph executions each get independent counters.
-_autopilot_recursion_depth: contextvars.ContextVar[int] = contextvars.ContextVar(
-    "_autopilot_recursion_depth", default=0
-)
-_autopilot_recursion_limit: contextvars.ContextVar[int | None] = contextvars.ContextVar(
-    "_autopilot_recursion_limit", default=None
-)
-
-
-def _check_recursion(
-    max_depth: int,
-) -> tuple[contextvars.Token[int], contextvars.Token[int | None]]:
-    """Check and increment recursion depth.
-
-    Returns ContextVar tokens that must be passed to ``_reset_recursion``
-    when the caller exits to restore the previous depth.
-
-    Raises:
-        RuntimeError: If the current depth already meets or exceeds the limit.
-    """
-    current = _autopilot_recursion_depth.get()
-    inherited = _autopilot_recursion_limit.get()
-    limit = max_depth if inherited is None else min(inherited, max_depth)
-    if current >= limit:
-        raise RuntimeError(
-            f"AutoPilot recursion depth limit reached ({limit}). "
-            "The autopilot has called itself too many times."
-        )
-    return (
-        _autopilot_recursion_depth.set(current + 1),
-        _autopilot_recursion_limit.set(limit),
-    )
-
-
-def _reset_recursion(
-    tokens: tuple[contextvars.Token[int], contextvars.Token[int | None]],
-) -> None:
-    """Restore recursion depth and limit to their previous values."""
-    _autopilot_recursion_depth.reset(tokens[0])
-    _autopilot_recursion_limit.reset(tokens[1])
-
-
-# ---------------------------------------------------------------------------
-# Permission helpers
-# ---------------------------------------------------------------------------
-
-# Inherited permissions from a parent AutoPilotBlock execution.
-# This acts as a ceiling: child executions can only be more restrictive.
-_inherited_permissions: contextvars.ContextVar["CopilotPermissions | None"] = (
-    contextvars.ContextVar("_inherited_permissions", default=None)
-)
-
-
-async def _build_and_validate_permissions(
-    input_data: "AutoPilotBlock.Input",
-) -> "CopilotPermissions | str":
-    """Build a :class:`CopilotPermissions` from block input and validate it.
-
-    Returns a :class:`CopilotPermissions` on success or a human-readable
-    error string if validation fails.
-    """
-    # Tool names are validated by Pydantic via the ToolName Literal type
-    # at model construction time — no runtime check needed here.
-    # Validate block identifiers against live block registry.
-    if input_data.blocks:
-        invalid_blocks = await validate_block_identifiers(input_data.blocks)
-        if invalid_blocks:
-            return (
-                f"Unknown block identifier(s) in 'blocks': {invalid_blocks}. "
-                "Use find_block to discover valid block names and IDs. "
-                "You may also use the first 8 characters of a block UUID."
-            )
-
-    return CopilotPermissions(
-        tools=list(input_data.tools),
-        tools_exclude=input_data.tools_exclude,
-        blocks=input_data.blocks,
-        blocks_exclude=input_data.blocks_exclude,
-    )
-
-
-def _merge_inherited_permissions(
-    permissions: "CopilotPermissions | None",
-) -> "tuple[CopilotPermissions | None, contextvars.Token[CopilotPermissions | None] | None]":
-    """Merge *permissions* with any inherited parent permissions.
-
-    The merged result is stored back into the contextvar so that any nested
-    AutoPilotBlock invocation (sub-agent) inherits the merged ceiling.
-
-    Returns a tuple of (merged_permissions, reset_token).  The caller MUST
-    reset the contextvar via ``_inherited_permissions.reset(token)`` in a
-    ``finally`` block when ``reset_token`` is not None — this prevents
-    permission leakage between sequential independent executions in the same
-    asyncio task.
-    """
-    parent = _inherited_permissions.get()
-
-    if permissions is None and parent is None:
-        return None, None
-
-    all_tools = all_known_tool_names()
-
-    if permissions is None:
-        permissions = CopilotPermissions()  # allow-all; will be narrowed by parent
-
-    merged = (
-        permissions.merged_with_parent(parent, all_tools)
-        if parent is not None
-        else permissions
-    )
-
-    # Store merged permissions as the new inherited ceiling for nested calls.
-    # Return the token so the caller can restore the previous value in finally.
-    token = _inherited_permissions.set(merged)
-    return merged, token

autogpt_platform/backend/backend/blocks/autopilot_permissions_test.py

@@ -1,265 +0,0 @@
-"""Tests for AutoPilotBlock permission fields and validation."""
-
-from __future__ import annotations
-
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import pytest
-from pydantic import ValidationError
-
-from backend.blocks.autopilot import (
-    AutoPilotBlock,
-    _build_and_validate_permissions,
-    _inherited_permissions,
-    _merge_inherited_permissions,
-)
-from backend.copilot.permissions import CopilotPermissions, all_known_tool_names
-from backend.data.execution import ExecutionContext
-
-# ---------------------------------------------------------------------------
-# Helpers
-# ---------------------------------------------------------------------------
-
-
-def _make_input(**kwargs) -> AutoPilotBlock.Input:
-    defaults = {
-        "prompt": "Do something",
-        "system_context": "",
-        "session_id": "",
-        "max_recursion_depth": 3,
-        "tools": [],
-        "tools_exclude": True,
-        "blocks": [],
-        "blocks_exclude": True,
-    }
-    defaults.update(kwargs)
-    return AutoPilotBlock.Input(**defaults)
-
-
-# ---------------------------------------------------------------------------
-# _build_and_validate_permissions
-# ---------------------------------------------------------------------------
-
-
-@pytest.mark.asyncio
-class TestBuildAndValidatePermissions:
-    async def test_empty_inputs_returns_empty_permissions(self):
-        inp = _make_input()
-        result = await _build_and_validate_permissions(inp)
-        assert isinstance(result, CopilotPermissions)
-        assert result.is_empty()
-
-    async def test_valid_tool_names_accepted(self):
-        inp = _make_input(tools=["run_block", "web_fetch"], tools_exclude=True)
-        result = await _build_and_validate_permissions(inp)
-        assert isinstance(result, CopilotPermissions)
-        assert result.tools == ["run_block", "web_fetch"]
-        assert result.tools_exclude is True
-
-    async def test_invalid_tool_rejected_by_pydantic(self):
-        """Invalid tool names are now caught at Pydantic validation time
-        (Literal type), before ``_build_and_validate_permissions`` is called."""
-        with pytest.raises(ValidationError, match="not_a_real_tool"):
-            _make_input(tools=["not_a_real_tool"])
-
-    async def test_valid_block_name_accepted(self):
-        mock_block_cls = MagicMock()
-        mock_block_cls.return_value.name = "HTTP Request"
-        with patch(
-            "backend.blocks.get_blocks",
-            return_value={"c069dc6b-c3ed-4c12-b6e5-d47361e64ce6": mock_block_cls},
-        ):
-            inp = _make_input(blocks=["HTTP Request"], blocks_exclude=True)
-            result = await _build_and_validate_permissions(inp)
-        assert isinstance(result, CopilotPermissions)
-        assert result.blocks == ["HTTP Request"]
-
-    async def test_valid_partial_uuid_accepted(self):
-        mock_block_cls = MagicMock()
-        mock_block_cls.return_value.name = "HTTP Request"
-        with patch(
-            "backend.blocks.get_blocks",
-            return_value={"c069dc6b-c3ed-4c12-b6e5-d47361e64ce6": mock_block_cls},
-        ):
-            inp = _make_input(blocks=["c069dc6b"], blocks_exclude=False)
-            result = await _build_and_validate_permissions(inp)
-        assert isinstance(result, CopilotPermissions)
-
-    async def test_invalid_block_identifier_returns_error(self):
-        mock_block_cls = MagicMock()
-        mock_block_cls.return_value.name = "HTTP Request"
-        with patch(
-            "backend.blocks.get_blocks",
-            return_value={"c069dc6b-c3ed-4c12-b6e5-d47361e64ce6": mock_block_cls},
-        ):
-            inp = _make_input(blocks=["totally_fake_block"])
-            result = await _build_and_validate_permissions(inp)
-        assert isinstance(result, str)
-        assert "totally_fake_block" in result
-        assert "Unknown block identifier" in result
-
-    async def test_sdk_builtin_tool_names_accepted(self):
-        inp = _make_input(tools=["Read", "Task", "WebSearch"], tools_exclude=False)
-        result = await _build_and_validate_permissions(inp)
-        assert isinstance(result, CopilotPermissions)
-        assert not result.tools_exclude
-
-    async def test_empty_blocks_skips_validation(self):
-        # Should not call validate_block_identifiers at all when blocks=[].
-        with patch(
-            "backend.copilot.permissions.validate_block_identifiers"
-        ) as mock_validate:
-            inp = _make_input(blocks=[])
-            await _build_and_validate_permissions(inp)
-            mock_validate.assert_not_called()
-
-
-# ---------------------------------------------------------------------------
-# _merge_inherited_permissions
-# ---------------------------------------------------------------------------
-
-
-class TestMergeInheritedPermissions:
-    def test_no_permissions_no_parent_returns_none(self):
-        merged, token = _merge_inherited_permissions(None)
-        assert merged is None
-        assert token is None
-
-    def test_permissions_no_parent_returned_unchanged(self):
-        perms = CopilotPermissions(tools=["bash_exec"], tools_exclude=True)
-        merged, token = _merge_inherited_permissions(perms)
-        try:
-            assert merged is perms
-            assert token is not None
-        finally:
-            if token is not None:
-                _inherited_permissions.reset(token)
-
-    def test_child_narrows_parent(self):
-        parent = CopilotPermissions(tools=["bash_exec"], tools_exclude=True)
-        # Set parent as inherited
-        outer_token = _inherited_permissions.set(parent)
-        try:
-            child = CopilotPermissions(tools=["web_fetch"], tools_exclude=True)
-            merged, inner_token = _merge_inherited_permissions(child)
-            try:
-                assert merged is not None
-                all_t = all_known_tool_names()
-                effective = merged.effective_allowed_tools(all_t)
-                assert "bash_exec" not in effective
-                assert "web_fetch" not in effective
-            finally:
-                if inner_token is not None:
-                    _inherited_permissions.reset(inner_token)
-        finally:
-            _inherited_permissions.reset(outer_token)
-
-    def test_none_permissions_with_parent_uses_parent(self):
-        parent = CopilotPermissions(tools=["bash_exec"], tools_exclude=True)
-        outer_token = _inherited_permissions.set(parent)
-        try:
-            merged, inner_token = _merge_inherited_permissions(None)
-            try:
-                assert merged is not None
-                # Merged should have parent's restrictions
-                effective = merged.effective_allowed_tools(all_known_tool_names())
-                assert "bash_exec" not in effective
-            finally:
-                if inner_token is not None:
-                    _inherited_permissions.reset(inner_token)
-        finally:
-            _inherited_permissions.reset(outer_token)
-
-    def test_child_cannot_expand_parent_whitelist(self):
-        parent = CopilotPermissions(tools=["run_block"], tools_exclude=False)
-        outer_token = _inherited_permissions.set(parent)
-        try:
-            # Child tries to allow more tools
-            child = CopilotPermissions(
-                tools=["run_block", "bash_exec"], tools_exclude=False
-            )
-            merged, inner_token = _merge_inherited_permissions(child)
-            try:
-                assert merged is not None
-                effective = merged.effective_allowed_tools(all_known_tool_names())
-                assert "bash_exec" not in effective
-                assert "run_block" in effective
-            finally:
-                if inner_token is not None:
-                    _inherited_permissions.reset(inner_token)
-        finally:
-            _inherited_permissions.reset(outer_token)
-
-
-# ---------------------------------------------------------------------------
-# AutoPilotBlock.run — validation integration
-# ---------------------------------------------------------------------------
-
-
-@pytest.mark.asyncio
-class TestAutoPilotBlockRunPermissions:
-    async def _collect_outputs(self, block, input_data, user_id="test-user"):
-        """Helper to collect all yields from block.run()."""
-        ctx = ExecutionContext(
-            user_id=user_id,
-            graph_id="g1",
-            graph_exec_id="ge1",
-            node_exec_id="ne1",
-            node_id="n1",
-        )
-        outputs = {}
-        async for key, val in block.run(input_data, execution_context=ctx):
-            outputs[key] = val
-        return outputs
-
-    async def test_invalid_tool_rejected_by_pydantic(self):
-        """Invalid tool names are caught at Pydantic validation (Literal type)."""
-        with pytest.raises(ValidationError, match="not_a_tool"):
-            _make_input(tools=["not_a_tool"])
-
-    async def test_invalid_block_yields_error(self):
-        mock_block_cls = MagicMock()
-        mock_block_cls.return_value.name = "HTTP Request"
-        with patch(
-            "backend.blocks.get_blocks",
-            return_value={"c069dc6b-c3ed-4c12-b6e5-d47361e64ce6": mock_block_cls},
-        ):
-            block = AutoPilotBlock()
-            inp = _make_input(blocks=["nonexistent_block"])
-            outputs = await self._collect_outputs(block, inp)
-        assert "error" in outputs
-        assert "nonexistent_block" in outputs["error"]
-
-    async def test_empty_prompt_yields_error_before_permission_check(self):
-        block = AutoPilotBlock()
-        inp = _make_input(prompt="   ", tools=["run_block"])
-        outputs = await self._collect_outputs(block, inp)
-        assert "error" in outputs
-        assert "Prompt cannot be empty" in outputs["error"]
-
-    async def test_valid_permissions_passed_to_execute(self):
-        """Permissions are forwarded to execute_copilot when valid."""
-        block = AutoPilotBlock()
-        captured: dict = {}
-
-        async def fake_execute_copilot(self_inner, **kwargs):
-            captured["permissions"] = kwargs.get("permissions")
-            return (
-                "ok",
-                [],
-                '[{"role":"user","content":"hi"}]',
-                "test-sid",
-                {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
-            )
-
-        with patch.object(
-            AutoPilotBlock, "create_session", new=AsyncMock(return_value="test-sid")
-        ), patch.object(AutoPilotBlock, "execute_copilot", new=fake_execute_copilot):
-            inp = _make_input(tools=["run_block"], tools_exclude=False)
-            outputs = await self._collect_outputs(block, inp)
-
-        assert "error" not in outputs
-        perms = captured.get("permissions")
-        assert isinstance(perms, CopilotPermissions)
-        assert perms.tools == ["run_block"]
-        assert perms.tools_exclude is False

autogpt_platform/backend/backend/blocks/data_manipulation.py

@@ -472,7 +472,7 @@ class AddToListBlock(Block):
 
     async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         entries_added = input_data.entries.copy()
-        if input_data.entry is not None:
+        if input_data.entry:
             entries_added.append(input_data.entry)
 
         updated_list = input_data.list.copy()

autogpt_platform/backend/backend/blocks/discord/bot_blocks.py

@@ -73,7 +73,7 @@ class ReadDiscordMessagesBlock(Block):
             id="df06086a-d5ac-4abb-9996-2ad0acb2eff7",
             input_schema=ReadDiscordMessagesBlock.Input,  # Assign input schema
             output_schema=ReadDiscordMessagesBlock.Output,  # Assign output schema
-            description="Reads new messages from a Discord channel using a bot token and triggers when a new message is posted",
+            description="Reads messages from a Discord channel using a bot token.",
             categories={BlockCategory.SOCIAL},
             test_input={
                 "continuous_read": False,

autogpt_platform/backend/backend/blocks/email_block.py

@@ -21,7 +21,6 @@ from backend.data.model import (
     UserPasswordCredentials,
 )
 from backend.integrations.providers import ProviderName
-from backend.util.request import resolve_and_check_blocked
 
 TEST_CREDENTIALS = UserPasswordCredentials(
     id="01234567-89ab-cdef-0123-456789abcdef",
@@ -100,8 +99,6 @@ class SendEmailBlock(Block):
             is_sensitive_action=True,
         )
 
-    ALLOWED_SMTP_PORTS = {25, 465, 587, 2525}
-
     @staticmethod
     def send_email(
         config: SMTPConfig,
@@ -132,17 +129,6 @@ class SendEmailBlock(Block):
         self, input_data: Input, *, credentials: SMTPCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            # --- SSRF Protection ---
-            smtp_port = input_data.config.smtp_port
-            if smtp_port not in self.ALLOWED_SMTP_PORTS:
-                yield "error", (
-                    f"SMTP port {smtp_port} is not allowed. "
-                    f"Allowed ports: {sorted(self.ALLOWED_SMTP_PORTS)}"
-                )
-                return
-
-            await resolve_and_check_blocked(input_data.config.smtp_server)
-
             status = self.send_email(
                 config=input_data.config,
                 to_email=input_data.to_email,
@@ -194,19 +180,7 @@ class SendEmailBlock(Block):
                 "was rejected by the server. "
                 "Please verify your account is authorized to send emails."
             )
-        except smtplib.SMTPConnectError:
-            yield "error", (
-                f"Cannot connect to SMTP server '{input_data.config.smtp_server}' "
-                f"on port {input_data.config.smtp_port}."
-            )
-        except smtplib.SMTPServerDisconnected:
-            yield "error", (
-                f"SMTP server '{input_data.config.smtp_server}' "
-                "disconnected unexpectedly."
-            )
         except smtplib.SMTPDataError as e:
             yield "error", f"Email data rejected by server: {str(e)}"
-        except ValueError as e:
-            yield "error", str(e)
         except Exception as e:
             raise e

autogpt_platform/backend/backend/blocks/flux_kontext.py

@@ -34,29 +34,17 @@ TEST_CREDENTIALS_INPUT = {
     "provider": TEST_CREDENTIALS.provider,
     "id": TEST_CREDENTIALS.id,
     "type": TEST_CREDENTIALS.type,
-    "title": TEST_CREDENTIALS.title,
+    "title": TEST_CREDENTIALS.type,
 }
 
 
-class ImageEditorModel(str, Enum):
-    FLUX_KONTEXT_PRO = "Flux Kontext Pro"
-    FLUX_KONTEXT_MAX = "Flux Kontext Max"
-    NANO_BANANA_PRO = "Nano Banana Pro"
-    NANO_BANANA_2 = "Nano Banana 2"
+class FluxKontextModelName(str, Enum):
+    PRO = "Flux Kontext Pro"
+    MAX = "Flux Kontext Max"
 
     @property
     def api_name(self) -> str:
-        _map = {
-            "FLUX_KONTEXT_PRO": "black-forest-labs/flux-kontext-pro",
-            "FLUX_KONTEXT_MAX": "black-forest-labs/flux-kontext-max",
-            "NANO_BANANA_PRO": "google/nano-banana-pro",
-            "NANO_BANANA_2": "google/nano-banana-2",
-        }
-        return _map[self.name]
-
-
-# Keep old name as alias for backwards compatibility
-FluxKontextModelName = ImageEditorModel
+        return f"black-forest-labs/flux-kontext-{self.name.lower()}"
 
 
 class AspectRatio(str, Enum):
@@ -81,7 +69,7 @@ class AIImageEditorBlock(Block):
         credentials: CredentialsMetaInput[
             Literal[ProviderName.REPLICATE], Literal["api_key"]
         ] = CredentialsField(
-            description="Replicate API key with permissions for Flux Kontext and Nano Banana models",
+            description="Replicate API key with permissions for Flux Kontext models",
         )
         prompt: str = SchemaField(
             description="Text instruction describing the desired edit",
@@ -99,14 +87,14 @@ class AIImageEditorBlock(Block):
             advanced=False,
         )
         seed: Optional[int] = SchemaField(
-            description="Random seed. Set for reproducible generation (Flux Kontext only; ignored by Nano Banana models)",
+            description="Random seed. Set for reproducible generation",
             default=None,
             title="Seed",
             advanced=True,
         )
-        model: ImageEditorModel = SchemaField(
+        model: FluxKontextModelName = SchemaField(
             description="Model variant to use",
-            default=ImageEditorModel.NANO_BANANA_2,
+            default=FluxKontextModelName.PRO,
             title="Model",
         )
 
@@ -119,7 +107,7 @@ class AIImageEditorBlock(Block):
         super().__init__(
             id="3fd9c73d-4370-4925-a1ff-1b86b99fabfa",
             description=(
-                "Edit images using Flux Kontext or Google Nano Banana models. Provide a prompt "
+                "Edit images using BlackForest Labs' Flux Kontext models. Provide a prompt "
                 "and optional reference image to generate a modified image."
             ),
             categories={BlockCategory.AI, BlockCategory.MULTIMEDIA},
@@ -130,7 +118,7 @@ class AIImageEditorBlock(Block):
                 "input_image": "data:image/png;base64,MQ==",
                 "aspect_ratio": AspectRatio.MATCH_INPUT_IMAGE,
                 "seed": None,
-                "model": ImageEditorModel.NANO_BANANA_2,
+                "model": FluxKontextModelName.PRO,
                 "credentials": TEST_CREDENTIALS_INPUT,
             },
             test_output=[
@@ -139,9 +127,7 @@ class AIImageEditorBlock(Block):
             ],
             test_mock={
                 # Use data URI to avoid HTTP requests during tests
-                "run_model": lambda *args, **kwargs: (
-                    "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg=="
-                ),
+                "run_model": lambda *args, **kwargs: "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==",
             },
             test_credentials=TEST_CREDENTIALS,
         )
@@ -156,7 +142,7 @@ class AIImageEditorBlock(Block):
     ) -> BlockOutput:
         result = await self.run_model(
             api_key=credentials.api_key,
-            model=input_data.model,
+            model_name=input_data.model.api_name,
             prompt=input_data.prompt,
             input_image_b64=(
                 await store_media_file(
@@ -183,7 +169,7 @@ class AIImageEditorBlock(Block):
     async def run_model(
         self,
         api_key: SecretStr,
-        model: ImageEditorModel,
+        model_name: str,
         prompt: str,
         input_image_b64: Optional[str],
         aspect_ratio: str,
@@ -192,29 +178,12 @@ class AIImageEditorBlock(Block):
         graph_exec_id: str,
     ) -> MediaFileType:
         client = ReplicateClient(api_token=api_key.get_secret_value())
-        model_name = model.api_name
-
-        is_nano_banana = model in (
-            ImageEditorModel.NANO_BANANA_PRO,
-            ImageEditorModel.NANO_BANANA_2,
-        )
-        if is_nano_banana:
-            input_params: dict = {
-                "prompt": prompt,
-                "aspect_ratio": aspect_ratio,
-                "output_format": "jpg",
-                "safety_filter_level": "block_only_high",
-            }
-            # NB API expects "image_input" as a list, unlike Flux's single "input_image"
-            if input_image_b64:
-                input_params["image_input"] = [input_image_b64]
-        else:
-            input_params = {
-                "prompt": prompt,
-                "input_image": input_image_b64,
-                "aspect_ratio": aspect_ratio,
-                **({"seed": seed} if seed is not None else {}),
-            }
+        input_params = {
+            "prompt": prompt,
+            "input_image": input_image_b64,
+            "aspect_ratio": aspect_ratio,
+            **({"seed": seed} if seed is not None else {}),
+        }
 
         try:
             output: FileOutput | list[FileOutput] = await client.async_run(  # type: ignore

autogpt_platform/backend/backend/blocks/google/gmail.py

@@ -1,6 +1,5 @@
 import asyncio
 import base64
-import re
 from abc import ABC
 from email import encoders
 from email.mime.base import MIMEBase
@@ -9,7 +8,7 @@ from email.mime.text import MIMEText
 from email.policy import SMTP
 from email.utils import getaddresses, parseaddr
 from pathlib import Path
-from typing import List, Literal, Optional, Protocol, runtime_checkable
+from typing import List, Literal, Optional
 
 from google.oauth2.credentials import Credentials
 from googleapiclient.discovery import build
@@ -43,52 +42,8 @@ NO_WRAP_POLICY = SMTP.clone(max_line_length=0)
 
 
 def serialize_email_recipients(recipients: list[str]) -> str:
-    """Serialize recipients list to comma-separated string.
-
-    Strips leading/trailing whitespace from each address to keep MIME
-    headers clean (mirrors the strip done in ``validate_email_recipients``).
-    """
-    return ", ".join(addr.strip() for addr in recipients)
-
-
-# RFC 5322 simplified pattern: local@domain where domain has at least one dot
-_EMAIL_RE = re.compile(r"^[^@\s]+@[^@\s]+\.[^@\s]+$")
-
-
-def validate_email_recipients(recipients: list[str], field_name: str = "to") -> None:
-    """Validate that all recipients are plausible email addresses.
-
-    Raises ``ValueError`` with a user-friendly message listing every
-    invalid entry so the caller (or LLM) can correct them in one pass.
-    """
-    invalid = [addr for addr in recipients if not _EMAIL_RE.match(addr.strip())]
-    if invalid:
-        formatted = ", ".join(f"'{a}'" for a in invalid)
-        raise ValueError(
-            f"Invalid email address(es) in '{field_name}': {formatted}. "
-            f"Each entry must be a valid email address (e.g. user@example.com)."
-        )
-
-
-@runtime_checkable
-class HasRecipients(Protocol):
-    to: list[str]
-    cc: list[str]
-    bcc: list[str]
-
-
-def validate_all_recipients(input_data: HasRecipients) -> None:
-    """Validate to/cc/bcc recipient fields on an input namespace.
-
-    Calls ``validate_email_recipients`` for ``to`` (required) and
-    ``cc``/``bcc`` (when non-empty), raising ``ValueError`` on the
-    first field that contains an invalid address.
-    """
-    validate_email_recipients(input_data.to, "to")
-    if input_data.cc:
-        validate_email_recipients(input_data.cc, "cc")
-    if input_data.bcc:
-        validate_email_recipients(input_data.bcc, "bcc")
+    """Serialize recipients list to comma-separated string."""
+    return ", ".join(recipients)
 
 
 def _make_mime_text(
@@ -145,16 +100,14 @@ async def create_mime_message(
 ) -> str:
     """Create a MIME message with attachments and return base64-encoded raw message."""
 
-    validate_all_recipients(input_data)
-
     message = MIMEMultipart()
     message["to"] = serialize_email_recipients(input_data.to)
     message["subject"] = input_data.subject
 
     if input_data.cc:
-        message["cc"] = serialize_email_recipients(input_data.cc)
+        message["cc"] = ", ".join(input_data.cc)
     if input_data.bcc:
-        message["bcc"] = serialize_email_recipients(input_data.bcc)
+        message["bcc"] = ", ".join(input_data.bcc)
 
     # Use the new helper function with content_type if available
     content_type = getattr(input_data, "content_type", None)
@@ -1214,15 +1167,13 @@ async def _build_reply_message(
         references.append(headers["message-id"])
 
     # Create MIME message
-    validate_all_recipients(input_data)
-
     msg = MIMEMultipart()
     if input_data.to:
-        msg["To"] = serialize_email_recipients(input_data.to)
+        msg["To"] = ", ".join(input_data.to)
     if input_data.cc:
-        msg["Cc"] = serialize_email_recipients(input_data.cc)
+        msg["Cc"] = ", ".join(input_data.cc)
     if input_data.bcc:
-        msg["Bcc"] = serialize_email_recipients(input_data.bcc)
+        msg["Bcc"] = ", ".join(input_data.bcc)
     msg["Subject"] = subject
     if headers.get("message-id"):
         msg["In-Reply-To"] = headers["message-id"]
@@ -1734,16 +1685,13 @@ To: {original_to}
         else:
             body = f"{forward_header}\n\n{original_body}"
 
-        # Validate all recipient lists before building the MIME message
-        validate_all_recipients(input_data)
-
         # Create MIME message
         msg = MIMEMultipart()
-        msg["To"] = serialize_email_recipients(input_data.to)
+        msg["To"] = ", ".join(input_data.to)
         if input_data.cc:
-            msg["Cc"] = serialize_email_recipients(input_data.cc)
+            msg["Cc"] = ", ".join(input_data.cc)
         if input_data.bcc:
-            msg["Bcc"] = serialize_email_recipients(input_data.bcc)
+            msg["Bcc"] = ", ".join(input_data.bcc)
         msg["Subject"] = subject
 
         # Add body with proper content type

autogpt_platform/backend/backend/blocks/io.py

@@ -28,9 +28,9 @@ class AgentInputBlock(Block):
     """
     This block is used to provide input to the graph.
 
-    It takes in a value, name, and description.
+    It takes in a value, name, description, default values list and bool to limit selection to default values.
 
-    It outputs the value passed as input.
+    It Outputs the value passed as input.
     """
 
     class Input(BlockSchemaInput):
@@ -47,6 +47,12 @@ class AgentInputBlock(Block):
             default=None,
             advanced=True,
         )
+        placeholder_values: list = SchemaField(
+            description="The placeholder values to be passed as input.",
+            default_factory=list,
+            advanced=True,
+            hidden=True,
+        )
         advanced: bool = SchemaField(
             description="Whether to show the input in the advanced section, if the field is not required.",
             default=False,
@@ -59,7 +65,10 @@ class AgentInputBlock(Block):
         )
 
         def generate_schema(self):
-            return copy.deepcopy(self.get_field_schema("value"))
+            schema = copy.deepcopy(self.get_field_schema("value"))
+            if possible_values := self.placeholder_values:
+                schema["enum"] = possible_values
+            return schema
 
     class Output(BlockSchema):
         # Use BlockSchema to avoid automatic error field for interface definition
@@ -77,16 +86,18 @@ class AgentInputBlock(Block):
                         "value": "Hello, World!",
                         "name": "input_1",
                         "description": "Example test input.",
+                        "placeholder_values": [],
                     },
                     {
-                        "value": 42,
+                        "value": "Hello, World!",
                         "name": "input_2",
-                        "description": "Example numeric input.",
+                        "description": "Example test input with placeholders.",
+                        "placeholder_values": ["Hello, World!"],
                     },
                 ],
                 "test_output": [
                     ("result", "Hello, World!"),
-                    ("result", 42),
+                    ("result", "Hello, World!"),
                 ],
                 "categories": {BlockCategory.INPUT, BlockCategory.BASIC},
                 "block_type": BlockType.INPUT,
@@ -200,7 +211,7 @@ class AgentOutputBlock(Block):
         if input_data.format:
             try:
                 formatter = TextFormatter(autoescape=input_data.escape_html)
-                yield "output", await formatter.format_string(
+                yield "output", formatter.format_string(
                     input_data.format, {input_data.name: input_data.value}
                 )
             except Exception as e:
@@ -234,11 +245,13 @@ class AgentShortTextInputBlock(AgentInputBlock):
                     "value": "Hello",
                     "name": "short_text_1",
                     "description": "Short text example 1",
+                    "placeholder_values": [],
                 },
                 {
                     "value": "Quick test",
                     "name": "short_text_2",
                     "description": "Short text example 2",
+                    "placeholder_values": ["Quick test", "Another option"],
                 },
             ],
             test_output=[
@@ -272,11 +285,13 @@ class AgentLongTextInputBlock(AgentInputBlock):
                     "value": "Lorem ipsum dolor sit amet...",
                     "name": "long_text_1",
                     "description": "Long text example 1",
+                    "placeholder_values": [],
                 },
                 {
                     "value": "Another multiline text input.",
                     "name": "long_text_2",
                     "description": "Long text example 2",
+                    "placeholder_values": ["Another multiline text input."],
                 },
             ],
             test_output=[
@@ -310,11 +325,13 @@ class AgentNumberInputBlock(AgentInputBlock):
                     "value": 42,
                     "name": "number_input_1",
                     "description": "Number example 1",
+                    "placeholder_values": [],
                 },
                 {
                     "value": 314,
                     "name": "number_input_2",
                     "description": "Number example 2",
+                    "placeholder_values": [314, 2718],
                 },
             ],
             test_output=[
@@ -484,12 +501,6 @@ class AgentDropdownInputBlock(AgentInputBlock):
             title="Dropdown Options",
         )
 
-        def generate_schema(self):
-            schema = super().generate_schema()
-            if possible_values := self.placeholder_values:
-                schema["enum"] = possible_values
-            return schema
-
     class Output(AgentInputBlock.Output):
         result: str = SchemaField(description="Selected dropdown value.")
 

autogpt_platform/backend/backend/blocks/llm.py

@@ -33,13 +33,6 @@ from backend.integrations.providers import ProviderName
 from backend.util import json
 from backend.util.clients import OPENROUTER_BASE_URL
 from backend.util.logging import TruncatedLogger
-from backend.util.openai_responses import (
-    convert_tools_to_responses_format,
-    extract_responses_content,
-    extract_responses_reasoning,
-    extract_responses_tool_calls,
-    extract_responses_usage,
-)
 from backend.util.prompt import compress_context, estimate_token_count
 from backend.util.request import validate_url_host
 from backend.util.settings import Settings
@@ -49,9 +42,6 @@ settings = Settings()
 logger = TruncatedLogger(logging.getLogger(__name__), "[LLM-Block]")
 fmt = TextFormatter(autoescape=False)
 
-# HTTP status codes for user-caused errors that should not be reported to Sentry.
-USER_ERROR_STATUS_CODES = (401, 403, 429)
-
 LLMProviderName = Literal[
     ProviderName.AIML_API,
     ProviderName.ANTHROPIC,
@@ -104,18 +94,6 @@ class LlmModelMeta(EnumMeta):
 
 
 class LlmModel(str, Enum, metaclass=LlmModelMeta):
-
-    @classmethod
-    def _missing_(cls, value: object) -> "LlmModel | None":
-        """Handle provider-prefixed model names like 'anthropic/claude-sonnet-4-6'."""
-        if isinstance(value, str) and "/" in value:
-            stripped = value.split("/", 1)[1]
-            try:
-                return cls(stripped)
-            except ValueError:
-                return None
-        return None
-
     # OpenAI models
     O3_MINI = "o3-mini"
     O3 = "o3-2025-04-16"
@@ -133,6 +111,7 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     GPT4O_MINI = "gpt-4o-mini"
     GPT4O = "gpt-4o"
     GPT4_TURBO = "gpt-4-turbo"
+    GPT3_5_TURBO = "gpt-3.5-turbo"
     # Anthropic models
     CLAUDE_4_1_OPUS = "claude-opus-4-1-20250805"
     CLAUDE_4_OPUS = "claude-opus-4-20250514"
@@ -298,6 +277,9 @@ MODEL_METADATA = {
     LlmModel.GPT4_TURBO: ModelMetadata(
         "openai", 128000, 4096, "GPT-4 Turbo", "OpenAI", "OpenAI", 3
     ),  # gpt-4-turbo-2024-04-09
+    LlmModel.GPT3_5_TURBO: ModelMetadata(
+        "openai", 16385, 4096, "GPT-3.5 Turbo", "OpenAI", "OpenAI", 1
+    ),  # gpt-3.5-turbo-0125
     # https://docs.anthropic.com/en/docs/about-claude/models
     LlmModel.CLAUDE_4_1_OPUS: ModelMetadata(
         "anthropic", 200000, 32000, "Claude Opus 4.1", "Anthropic", "Anthropic", 3
@@ -724,9 +706,6 @@ def convert_openai_tool_fmt_to_anthropic(
 def extract_openai_reasoning(response) -> str | None:
     """Extract reasoning from OpenAI-compatible response if available."""
     """Note: This will likely not working since the reasoning is not present in another Response API"""
-    if not response.choices:
-        logger.warning("LLM response has empty choices in extract_openai_reasoning")
-        return None
     reasoning = None
     choice = response.choices[0]
     if hasattr(choice, "reasoning") and getattr(choice, "reasoning", None):
@@ -742,9 +721,6 @@ def extract_openai_reasoning(response) -> str | None:
 
 def extract_openai_tool_calls(response) -> list[ToolContentBlock] | None:
     """Extract tool calls from OpenAI-compatible response."""
-    if not response.choices:
-        logger.warning("LLM response has empty choices in extract_openai_tool_calls")
-        return None
     if response.choices[0].message.tool_calls:
         return [
             ToolContentBlock(
@@ -817,19 +793,6 @@ async def llm_call(
             )
         prompt = result.messages
 
-    # Sanitize unpaired surrogates in message content to prevent
-    # UnicodeEncodeError when httpx encodes the JSON request body.
-    for msg in prompt:
-        content = msg.get("content")
-        if isinstance(content, str):
-            try:
-                content.encode("utf-8")
-            except UnicodeEncodeError:
-                logger.warning("Sanitized unpaired surrogates in LLM prompt content")
-                msg["content"] = content.encode("utf-8", errors="surrogatepass").decode(
-                    "utf-8", errors="replace"
-                )
-
     # Calculate available tokens based on context window and input length
     estimated_input_tokens = estimate_token_count(prompt)
     model_max_output = llm_model.max_output_tokens or int(2**15)
@@ -838,53 +801,36 @@ async def llm_call(
     max_tokens = max(min(available_tokens, model_max_output, user_max), 1)
 
     if provider == "openai":
+        tools_param = tools if tools else openai.NOT_GIVEN
         oai_client = openai.AsyncOpenAI(api_key=credentials.api_key.get_secret_value())
+        response_format = None
 
-        tools_param = convert_tools_to_responses_format(tools) if tools else openai.omit
+        parallel_tool_calls = get_parallel_tool_calls_param(
+            llm_model, parallel_tool_calls
+        )
 
-        text_config = openai.omit
         if force_json_output:
-            text_config = {"format": {"type": "json_object"}}  # type: ignore
+            response_format = {"type": "json_object"}
 
-        response = await oai_client.responses.create(
+        response = await oai_client.chat.completions.create(
             model=llm_model.value,
-            input=prompt,  # type: ignore[arg-type]
-            tools=tools_param,  # type: ignore[arg-type]
-            max_output_tokens=max_tokens,
-            parallel_tool_calls=get_parallel_tool_calls_param(
-                llm_model, parallel_tool_calls
-            ),
-            text=text_config,  # type: ignore[arg-type]
-            store=False,
+            messages=prompt,  # type: ignore
+            response_format=response_format,  # type: ignore
+            max_completion_tokens=max_tokens,
+            tools=tools_param,  # type: ignore
+            parallel_tool_calls=parallel_tool_calls,
         )
 
-        raw_tool_calls = extract_responses_tool_calls(response)
-        tool_calls = (
-            [
-                ToolContentBlock(
-                    id=tc["id"],
-                    type=tc["type"],
-                    function=ToolCall(
-                        name=tc["function"]["name"],
-                        arguments=tc["function"]["arguments"],
-                    ),
-                )
-                for tc in raw_tool_calls
-            ]
-            if raw_tool_calls
-            else None
-        )
-        reasoning = extract_responses_reasoning(response)
-        content = extract_responses_content(response)
-        prompt_tokens, completion_tokens = extract_responses_usage(response)
+        tool_calls = extract_openai_tool_calls(response)
+        reasoning = extract_openai_reasoning(response)
 
         return LLMResponse(
-            raw_response=response,
+            raw_response=response.choices[0].message,
             prompt=prompt,
-            response=content,
+            response=response.choices[0].message.content or "",
             tool_calls=tool_calls,
-            prompt_tokens=prompt_tokens,
-            completion_tokens=completion_tokens,
+            prompt_tokens=response.usage.prompt_tokens if response.usage else 0,
+            completion_tokens=response.usage.completion_tokens if response.usage else 0,
             reasoning=reasoning,
         )
     elif provider == "anthropic":
@@ -912,60 +858,65 @@ async def llm_call(
         client = anthropic.AsyncAnthropic(
             api_key=credentials.api_key.get_secret_value()
         )
-        resp = await client.messages.create(
-            model=llm_model.value,
-            system=sysprompt,
-            messages=messages,
-            max_tokens=max_tokens,
-            tools=an_tools,
-            timeout=600,
-        )
-
-        if not resp.content:
-            raise ValueError("No content returned from Anthropic.")
-
-        tool_calls = None
-        for content_block in resp.content:
-            # Antropic is different to openai, need to iterate through
-            # the content blocks to find the tool calls
-            if content_block.type == "tool_use":
-                if tool_calls is None:
-                    tool_calls = []
-                tool_calls.append(
-                    ToolContentBlock(
-                        id=content_block.id,
-                        type=content_block.type,
-                        function=ToolCall(
-                            name=content_block.name,
-                            arguments=json.dumps(content_block.input),
-                        ),
-                    )
-                )
-
-        if not tool_calls and resp.stop_reason == "tool_use":
-            logger.warning(
-                f"Tool use stop reason but no tool calls found in content. {resp}"
+        try:
+            resp = await client.messages.create(
+                model=llm_model.value,
+                system=sysprompt,
+                messages=messages,
+                max_tokens=max_tokens,
+                tools=an_tools,
+                timeout=600,
             )
 
-        reasoning = None
-        for content_block in resp.content:
-            if hasattr(content_block, "type") and content_block.type == "thinking":
-                reasoning = content_block.thinking
-                break
+            if not resp.content:
+                raise ValueError("No content returned from Anthropic.")
 
-        return LLMResponse(
-            raw_response=resp,
-            prompt=prompt,
-            response=(
-                resp.content[0].name
-                if isinstance(resp.content[0], anthropic.types.ToolUseBlock)
-                else getattr(resp.content[0], "text", "")
-            ),
-            tool_calls=tool_calls,
-            prompt_tokens=resp.usage.input_tokens,
-            completion_tokens=resp.usage.output_tokens,
-            reasoning=reasoning,
-        )
+            tool_calls = None
+            for content_block in resp.content:
+                # Antropic is different to openai, need to iterate through
+                # the content blocks to find the tool calls
+                if content_block.type == "tool_use":
+                    if tool_calls is None:
+                        tool_calls = []
+                    tool_calls.append(
+                        ToolContentBlock(
+                            id=content_block.id,
+                            type=content_block.type,
+                            function=ToolCall(
+                                name=content_block.name,
+                                arguments=json.dumps(content_block.input),
+                            ),
+                        )
+                    )
+
+            if not tool_calls and resp.stop_reason == "tool_use":
+                logger.warning(
+                    f"Tool use stop reason but no tool calls found in content. {resp}"
+                )
+
+            reasoning = None
+            for content_block in resp.content:
+                if hasattr(content_block, "type") and content_block.type == "thinking":
+                    reasoning = content_block.thinking
+                    break
+
+            return LLMResponse(
+                raw_response=resp,
+                prompt=prompt,
+                response=(
+                    resp.content[0].name
+                    if isinstance(resp.content[0], anthropic.types.ToolUseBlock)
+                    else getattr(resp.content[0], "text", "")
+                ),
+                tool_calls=tool_calls,
+                prompt_tokens=resp.usage.input_tokens,
+                completion_tokens=resp.usage.output_tokens,
+                reasoning=reasoning,
+            )
+        except anthropic.APIError as e:
+            error_message = f"Anthropic API error: {str(e)}"
+            logger.error(error_message)
+            raise ValueError(error_message)
     elif provider == "groq":
         if tools:
             raise ValueError("Groq does not support tools.")
@@ -978,8 +929,6 @@ async def llm_call(
             response_format=response_format,  # type: ignore
             max_tokens=max_tokens,
         )
-        if not response.choices:
-            raise ValueError("Groq returned empty choices in response")
         return LLMResponse(
             raw_response=response.choices[0].message,
             prompt=prompt,
@@ -1039,8 +988,12 @@ async def llm_call(
             parallel_tool_calls=parallel_tool_calls_param,
         )
 
+        # If there's no response, raise an error
         if not response.choices:
-            raise ValueError(f"OpenRouter returned empty choices: {response}")
+            if response:
+                raise ValueError(f"OpenRouter error: {response}")
+            else:
+                raise ValueError("No response from OpenRouter.")
 
         tool_calls = extract_openai_tool_calls(response)
         reasoning = extract_openai_reasoning(response)
@@ -1077,8 +1030,12 @@ async def llm_call(
             parallel_tool_calls=parallel_tool_calls_param,
         )
 
+        # If there's no response, raise an error
         if not response.choices:
-            raise ValueError(f"Llama API returned empty choices: {response}")
+            if response:
+                raise ValueError(f"Llama API error: {response}")
+            else:
+                raise ValueError("No response from Llama API.")
 
         tool_calls = extract_openai_tool_calls(response)
         reasoning = extract_openai_reasoning(response)
@@ -1108,8 +1065,6 @@ async def llm_call(
             messages=prompt,  # type: ignore
             max_tokens=max_tokens,
         )
-        if not completion.choices:
-            raise ValueError("AI/ML API returned empty choices in response")
 
         return LLMResponse(
             raw_response=completion.choices[0].message,
@@ -1146,9 +1101,6 @@ async def llm_call(
             parallel_tool_calls=parallel_tool_calls_param,
         )
 
-        if not response.choices:
-            raise ValueError(f"v0 API returned empty choices: {response}")
-
         tool_calls = extract_openai_tool_calls(response)
         reasoning = extract_openai_reasoning(response)
 
@@ -1324,10 +1276,8 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
 
         values = input_data.prompt_values
         if values:
-            input_data.prompt = await fmt.format_string(input_data.prompt, values)
-            input_data.sys_prompt = await fmt.format_string(
-                input_data.sys_prompt, values
-            )
+            input_data.prompt = fmt.format_string(input_data.prompt, values)
+            input_data.sys_prompt = fmt.format_string(input_data.sys_prompt, values)
 
         if input_data.sys_prompt:
             prompt.append({"role": "system", "content": input_data.sys_prompt})
@@ -1477,16 +1427,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
                     yield "prompt", self.prompt
                     return
             except Exception as e:
-                is_user_error = (
-                    isinstance(e, (anthropic.APIStatusError, openai.APIStatusError))
-                    and e.status_code in USER_ERROR_STATUS_CODES
-                )
-                if is_user_error:
-                    logger.warning(f"Error calling LLM: {e}")
-                    error_feedback_message = f"Error calling LLM: {e}"
-                    break
-                else:
-                    logger.exception(f"Error calling LLM: {e}")
+                logger.exception(f"Error calling LLM: {e}")
                 if (
                     "maximum context length" in str(e).lower()
                     or "token limit" in str(e).lower()
@@ -2016,19 +1957,6 @@ class AIConversationBlock(AIBlockBase):
     async def run(
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
-        has_messages = any(
-            isinstance(m, dict)
-            and isinstance(m.get("content"), str)
-            and bool(m["content"].strip())
-            for m in (input_data.messages or [])
-        )
-        has_prompt = bool(input_data.prompt and input_data.prompt.strip())
-        if not has_messages and not has_prompt:
-            raise ValueError(
-                "Cannot call LLM with no messages and no prompt. "
-                "Provide at least one message or a non-empty prompt."
-            )
-
         response = await self.llm_call(
             AIStructuredResponseGeneratorBlock.Input(
                 prompt=input_data.prompt,

autogpt_platform/backend/backend/blocks/stagehand/blocks.py

@@ -1,8 +1,13 @@
 import logging
+import signal
+import threading
+import warnings
+from contextlib import contextmanager
 from enum import Enum
 
-from stagehand import AsyncStagehand
-from stagehand.types.session_act_params import Options as ActOptions
+# Monkey patch Stagehands to prevent signal handling in worker threads
+import stagehand.main
+from stagehand import Stagehand
 
 from backend.blocks.llm import (
     MODEL_METADATA,
@@ -23,6 +28,46 @@ from backend.sdk import (
     SchemaField,
 )
 
+# Suppress false positive cleanup warning of litellm (a dependency of stagehand)
+warnings.filterwarnings("ignore", module="litellm.llms.custom_httpx")
+
+# Store the original method
+original_register_signal_handlers = stagehand.main.Stagehand._register_signal_handlers
+
+
+def safe_register_signal_handlers(self):
+    """Only register signal handlers in the main thread"""
+    if threading.current_thread() is threading.main_thread():
+        original_register_signal_handlers(self)
+    else:
+        # Skip signal handling in worker threads
+        pass
+
+
+# Replace the method
+stagehand.main.Stagehand._register_signal_handlers = safe_register_signal_handlers
+
+
+@contextmanager
+def disable_signal_handling():
+    """Context manager to temporarily disable signal handling"""
+    if threading.current_thread() is not threading.main_thread():
+        # In worker threads, temporarily replace signal.signal with a no-op
+        original_signal = signal.signal
+
+        def noop_signal(*args, **kwargs):
+            pass
+
+        signal.signal = noop_signal
+        try:
+            yield
+        finally:
+            signal.signal = original_signal
+    else:
+        # In main thread, don't modify anything
+        yield
+
+
 logger = logging.getLogger(__name__)
 
 
@@ -103,10 +148,13 @@ class StagehandObserveBlock(Block):
         instruction: str = SchemaField(
             description="Natural language description of elements or actions to discover.",
         )
-        dom_settle_timeout_ms: int = SchemaField(
-            description="Timeout in ms to wait for the DOM to settle after navigation.",
-            default=30000,
-            advanced=True,
+        iframes: bool = SchemaField(
+            description="Whether to search within iframes. If True, Stagehand will search for actions within iframes.",
+            default=True,
+        )
+        domSettleTimeoutMs: int = SchemaField(
+            description="Timeout in milliseconds for DOM settlement.Wait longer for dynamic content",
+            default=45000,
         )
 
     class Output(BlockSchemaOutput):
@@ -137,28 +185,32 @@ class StagehandObserveBlock(Block):
 
         logger.debug(f"OBSERVE: Using model provider {model_credentials.provider}")
 
-        async with AsyncStagehand(
-            browserbase_api_key=stagehand_credentials.api_key.get_secret_value(),
-            browserbase_project_id=input_data.browserbase_project_id,
-            model_api_key=model_credentials.api_key.get_secret_value(),
-        ) as client:
-            session = await client.sessions.start(
+        with disable_signal_handling():
+            stagehand = Stagehand(
+                api_key=stagehand_credentials.api_key.get_secret_value(),
+                project_id=input_data.browserbase_project_id,
                 model_name=input_data.model.provider_name,
-                dom_settle_timeout_ms=input_data.dom_settle_timeout_ms,
+                model_api_key=model_credentials.api_key.get_secret_value(),
             )
-            try:
-                await session.navigate(url=input_data.url)
 
-                observe_response = await session.observe(
-                    instruction=input_data.instruction,
-                )
-                for result in observe_response.data.result:
-                    yield "selector", result.selector
-                    yield "description", result.description
-                    yield "method", result.method
-                    yield "arguments", result.arguments
-            finally:
-                await session.end()
+            await stagehand.init()
+
+        page = stagehand.page
+
+        assert page is not None, "Stagehand page is not initialized"
+
+        await page.goto(input_data.url)
+
+        observe_results = await page.observe(
+            input_data.instruction,
+            iframes=input_data.iframes,
+            domSettleTimeoutMs=input_data.domSettleTimeoutMs,
+        )
+        for result in observe_results:
+            yield "selector", result.selector
+            yield "description", result.description
+            yield "method", result.method
+            yield "arguments", result.arguments
 
 
 class StagehandActBlock(Block):
@@ -190,22 +242,24 @@ class StagehandActBlock(Block):
             description="Variables to use in the action. Variables contains data you want the action to use.",
             default_factory=dict,
         )
-        dom_settle_timeout_ms: int = SchemaField(
-            description="Timeout in ms to wait for the DOM to settle after navigation.",
-            default=30000,
-            advanced=True,
+        iframes: bool = SchemaField(
+            description="Whether to search within iframes. If True, Stagehand will search for actions within iframes.",
+            default=True,
         )
-        timeout_ms: int = SchemaField(
-            description="Timeout in ms for each action.",
-            default=30000,
-            advanced=True,
+        domSettleTimeoutMs: int = SchemaField(
+            description="Timeout in milliseconds for DOM settlement.Wait longer for dynamic content",
+            default=45000,
+        )
+        timeoutMs: int = SchemaField(
+            description="Timeout in milliseconds for DOM ready. Extended timeout for slow-loading forms",
+            default=60000,
         )
 
     class Output(BlockSchemaOutput):
         success: bool = SchemaField(
             description="Whether the action was completed successfully"
         )
-        message: str = SchemaField(description="Details about the action's execution.")
+        message: str = SchemaField(description="Details about the action’s execution.")
         action: str = SchemaField(description="Action performed")
 
     def __init__(self):
@@ -228,33 +282,32 @@ class StagehandActBlock(Block):
 
         logger.debug(f"ACT: Using model provider {model_credentials.provider}")
 
-        async with AsyncStagehand(
-            browserbase_api_key=stagehand_credentials.api_key.get_secret_value(),
-            browserbase_project_id=input_data.browserbase_project_id,
-            model_api_key=model_credentials.api_key.get_secret_value(),
-        ) as client:
-            session = await client.sessions.start(
+        with disable_signal_handling():
+            stagehand = Stagehand(
+                api_key=stagehand_credentials.api_key.get_secret_value(),
+                project_id=input_data.browserbase_project_id,
                 model_name=input_data.model.provider_name,
-                dom_settle_timeout_ms=input_data.dom_settle_timeout_ms,
+                model_api_key=model_credentials.api_key.get_secret_value(),
             )
-            try:
-                await session.navigate(url=input_data.url)
 
-                for action in input_data.action:
-                    act_options = ActOptions(
-                        variables={k: v for k, v in input_data.variables.items()},
-                        timeout=input_data.timeout_ms,
-                    )
-                    act_response = await session.act(
-                        input=action,
-                        options=act_options,
-                    )
-                    result = act_response.data.result
-                    yield "success", result.success
-                    yield "message", result.message
-                    yield "action", result.action_description
-            finally:
-                await session.end()
+            await stagehand.init()
+
+        page = stagehand.page
+
+        assert page is not None, "Stagehand page is not initialized"
+
+        await page.goto(input_data.url)
+        for action in input_data.action:
+            action_results = await page.act(
+                action,
+                variables=input_data.variables,
+                iframes=input_data.iframes,
+                domSettleTimeoutMs=input_data.domSettleTimeoutMs,
+                timeoutMs=input_data.timeoutMs,
+            )
+            yield "success", action_results.success
+            yield "message", action_results.message
+            yield "action", action_results.action
 
 
 class StagehandExtractBlock(Block):
@@ -282,10 +335,13 @@ class StagehandExtractBlock(Block):
         instruction: str = SchemaField(
             description="Natural language description of elements or actions to discover.",
         )
-        dom_settle_timeout_ms: int = SchemaField(
-            description="Timeout in ms to wait for the DOM to settle after navigation.",
-            default=30000,
-            advanced=True,
+        iframes: bool = SchemaField(
+            description="Whether to search within iframes. If True, Stagehand will search for actions within iframes.",
+            default=True,
+        )
+        domSettleTimeoutMs: int = SchemaField(
+            description="Timeout in milliseconds for DOM settlement.Wait longer for dynamic content",
+            default=45000,
         )
 
     class Output(BlockSchemaOutput):
@@ -311,21 +367,24 @@ class StagehandExtractBlock(Block):
 
         logger.debug(f"EXTRACT: Using model provider {model_credentials.provider}")
 
-        async with AsyncStagehand(
-            browserbase_api_key=stagehand_credentials.api_key.get_secret_value(),
-            browserbase_project_id=input_data.browserbase_project_id,
-            model_api_key=model_credentials.api_key.get_secret_value(),
-        ) as client:
-            session = await client.sessions.start(
+        with disable_signal_handling():
+            stagehand = Stagehand(
+                api_key=stagehand_credentials.api_key.get_secret_value(),
+                project_id=input_data.browserbase_project_id,
                 model_name=input_data.model.provider_name,
-                dom_settle_timeout_ms=input_data.dom_settle_timeout_ms,
+                model_api_key=model_credentials.api_key.get_secret_value(),
             )
-            try:
-                await session.navigate(url=input_data.url)
 
-                extract_response = await session.extract(
-                    instruction=input_data.instruction,
-                )
-                yield "extraction", str(extract_response.data.result)
-            finally:
-                await session.end()
+            await stagehand.init()
+
+        page = stagehand.page
+
+        assert page is not None, "Stagehand page is not initialized"
+
+        await page.goto(input_data.url)
+        extraction = await page.extract(
+            input_data.instruction,
+            iframes=input_data.iframes,
+            domSettleTimeoutMs=input_data.domSettleTimeoutMs,
+        )
+        yield "extraction", str(extraction.model_dump()["extraction"])

autogpt_platform/backend/backend/blocks/test/test_autopilot.py

@@ -1,223 +0,0 @@
-"""Tests for AutoPilotBlock: recursion guard, streaming, validation, and error paths."""
-
-import asyncio
-from unittest.mock import AsyncMock
-
-import pytest
-
-from backend.blocks.autopilot import (
-    AUTOPILOT_BLOCK_ID,
-    AutoPilotBlock,
-    _autopilot_recursion_depth,
-    _autopilot_recursion_limit,
-    _check_recursion,
-    _reset_recursion,
-)
-from backend.data.execution import ExecutionContext
-
-
-def _make_context(user_id: str = "test-user-123") -> ExecutionContext:
-    """Helper to build an ExecutionContext for tests."""
-    return ExecutionContext(
-        user_id=user_id,
-        graph_id="graph-1",
-        graph_exec_id="gexec-1",
-        graph_version=1,
-        node_id="node-1",
-        node_exec_id="nexec-1",
-    )
-
-
-# ---------------------------------------------------------------------------
-# Recursion guard unit tests
-# ---------------------------------------------------------------------------
-
-
-class TestCheckRecursion:
-    """Unit tests for _check_recursion / _reset_recursion."""
-
-    def test_first_call_increments_depth(self):
-        tokens = _check_recursion(3)
-        try:
-            assert _autopilot_recursion_depth.get() == 1
-            assert _autopilot_recursion_limit.get() == 3
-        finally:
-            _reset_recursion(tokens)
-
-    def test_reset_restores_previous_values(self):
-        assert _autopilot_recursion_depth.get() == 0
-        assert _autopilot_recursion_limit.get() is None
-        tokens = _check_recursion(5)
-        _reset_recursion(tokens)
-        assert _autopilot_recursion_depth.get() == 0
-        assert _autopilot_recursion_limit.get() is None
-
-    def test_exceeding_limit_raises(self):
-        t1 = _check_recursion(2)
-        try:
-            t2 = _check_recursion(2)
-            try:
-                with pytest.raises(RuntimeError, match="recursion depth limit"):
-                    _check_recursion(2)
-            finally:
-                _reset_recursion(t2)
-        finally:
-            _reset_recursion(t1)
-
-    def test_nested_calls_respect_inherited_limit(self):
-        """Inner call with higher max_depth still respects outer limit."""
-        t1 = _check_recursion(2)  # sets limit=2
-        try:
-            t2 = _check_recursion(10)  # inner wants 10, but inherited is 2
-            try:
-                # depth is now 2, limit is min(10, 2) = 2 → should raise
-                with pytest.raises(RuntimeError, match="recursion depth limit"):
-                    _check_recursion(10)
-            finally:
-                _reset_recursion(t2)
-        finally:
-            _reset_recursion(t1)
-
-    def test_limit_of_one_blocks_immediately_on_second_call(self):
-        t1 = _check_recursion(1)
-        try:
-            with pytest.raises(RuntimeError):
-                _check_recursion(1)
-        finally:
-            _reset_recursion(t1)
-
-
-# ---------------------------------------------------------------------------
-# AutoPilotBlock.run() validation tests
-# ---------------------------------------------------------------------------
-
-
-class TestRunValidation:
-    """Tests for input validation in AutoPilotBlock.run()."""
-
-    @pytest.fixture
-    def block(self):
-        return AutoPilotBlock()
-
-    @pytest.mark.asyncio
-    async def test_empty_prompt_yields_error(self, block):
-        block.Input  # ensure schema is accessible
-        input_data = block.Input(prompt="   ", max_recursion_depth=3)
-        ctx = _make_context()
-        outputs = {}
-        async for name, value in block.run(input_data, execution_context=ctx):
-            outputs[name] = value
-        assert outputs.get("error") == "Prompt cannot be empty."
-        assert "response" not in outputs
-
-    @pytest.mark.asyncio
-    async def test_missing_user_id_yields_error(self, block):
-        input_data = block.Input(prompt="hello", max_recursion_depth=3)
-        ctx = _make_context(user_id="")
-        outputs = {}
-        async for name, value in block.run(input_data, execution_context=ctx):
-            outputs[name] = value
-        assert "authenticated user" in outputs.get("error", "")
-
-    @pytest.mark.asyncio
-    async def test_successful_run_yields_all_outputs(self, block):
-        """With execute_copilot mocked, run() should yield all 5 success outputs."""
-        mock_result = (
-            "Hello world",
-            [],
-            '[{"role":"user","content":"hi"}]',
-            "sess-abc",
-            {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15},
-        )
-        block.execute_copilot = AsyncMock(return_value=mock_result)
-        block.create_session = AsyncMock(return_value="sess-abc")
-
-        input_data = block.Input(prompt="hi", max_recursion_depth=3)
-        ctx = _make_context()
-        outputs = {}
-        async for name, value in block.run(input_data, execution_context=ctx):
-            outputs[name] = value
-
-        assert outputs["response"] == "Hello world"
-        assert outputs["tool_calls"] == []
-        assert outputs["session_id"] == "sess-abc"
-        assert outputs["token_usage"]["total_tokens"] == 15
-        assert "error" not in outputs
-
-    @pytest.mark.asyncio
-    async def test_exception_yields_error(self, block):
-        """On unexpected failure, run() should yield an error output."""
-        block.execute_copilot = AsyncMock(side_effect=RuntimeError("boom"))
-        block.create_session = AsyncMock(return_value="sess-fail")
-
-        input_data = block.Input(prompt="do something", max_recursion_depth=3)
-        ctx = _make_context()
-        outputs = {}
-        async for name, value in block.run(input_data, execution_context=ctx):
-            outputs[name] = value
-
-        assert outputs["session_id"] == "sess-fail"
-        assert "boom" in outputs.get("error", "")
-
-    @pytest.mark.asyncio
-    async def test_cancelled_error_yields_error_and_reraises(self, block):
-        """CancelledError should yield error, then re-raise."""
-        block.execute_copilot = AsyncMock(side_effect=asyncio.CancelledError())
-        block.create_session = AsyncMock(return_value="sess-cancel")
-
-        input_data = block.Input(prompt="do something", max_recursion_depth=3)
-        ctx = _make_context()
-        outputs = {}
-        with pytest.raises(asyncio.CancelledError):
-            async for name, value in block.run(input_data, execution_context=ctx):
-                outputs[name] = value
-
-        assert outputs["session_id"] == "sess-cancel"
-        assert "cancelled" in outputs.get("error", "").lower()
-
-    @pytest.mark.asyncio
-    async def test_existing_session_id_skips_create(self, block):
-        """When session_id is provided, create_session should not be called."""
-        mock_result = (
-            "ok",
-            [],
-            "[]",
-            "existing-sid",
-            {"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0},
-        )
-        block.execute_copilot = AsyncMock(return_value=mock_result)
-        block.create_session = AsyncMock()
-
-        input_data = block.Input(
-            prompt="test", session_id="existing-sid", max_recursion_depth=3
-        )
-        ctx = _make_context()
-        async for _ in block.run(input_data, execution_context=ctx):
-            pass
-
-        block.create_session.assert_not_called()
-
-
-# ---------------------------------------------------------------------------
-# Block registration / ID tests
-# ---------------------------------------------------------------------------
-
-
-class TestBlockRegistration:
-    def test_block_id_matches_constant(self):
-        block = AutoPilotBlock()
-        assert block.id == AUTOPILOT_BLOCK_ID
-
-    def test_max_recursion_depth_has_upper_bound(self):
-        """Schema should enforce le=10."""
-        schema = AutoPilotBlock.Input.model_json_schema()
-        max_rec = schema["properties"]["max_recursion_depth"]
-        assert (
-            max_rec.get("maximum") == 10 or max_rec.get("exclusiveMaximum", 999) <= 11
-        )
-
-    def test_output_schema_has_no_duplicate_error_field(self):
-        """Output should inherit error from BlockSchemaOutput, not redefine it."""
-        # The field should exist (inherited) but there should be no explicit
-        # redefinition. We verify by checking the class __annotations__ directly.
-        assert "error" not in AutoPilotBlock.Output.__annotations__

autogpt_platform/backend/backend/blocks/test/test_block.py

@@ -4,8 +4,6 @@ import pytest
 
 from backend.blocks import get_blocks
 from backend.blocks._base import Block, BlockSchemaInput
-from backend.blocks.io import AgentDropdownInputBlock, AgentInputBlock
-from backend.data.graph import BaseGraph
 from backend.data.model import SchemaField
 from backend.util.test import execute_block_test
 
@@ -281,66 +279,3 @@ class TestAutoCredentialsFieldsValidation:
         assert "Duplicate auto_credentials kwarg_name 'credentials'" in str(
             exc_info.value
         )
-
-
-def test_agent_input_block_ignores_legacy_placeholder_values():
-    """Verify AgentInputBlock.Input.model_construct tolerates extra placeholder_values
-    for backward compatibility with existing agent JSON."""
-    legacy_data = {
-        "name": "url",
-        "value": "",
-        "description": "Enter a URL",
-        "placeholder_values": ["https://example.com"],
-    }
-    instance = AgentInputBlock.Input.model_construct(**legacy_data)
-    schema = instance.generate_schema()
-    assert (
-        "enum" not in schema
-    ), "AgentInputBlock should not produce enum from legacy placeholder_values"
-
-
-def test_dropdown_input_block_produces_enum():
-    """Verify AgentDropdownInputBlock.Input.generate_schema() produces enum."""
-    options = ["Option A", "Option B"]
-    instance = AgentDropdownInputBlock.Input.model_construct(
-        name="choice", value=None, placeholder_values=options
-    )
-    schema = instance.generate_schema()
-    assert schema.get("enum") == options
-
-
-def test_generate_schema_integration_legacy_placeholder_values():
-    """Test the full Graph._generate_schema path with legacy placeholder_values
-    on AgentInputBlock — verifies no enum leaks through the graph loading path."""
-    legacy_input_default = {
-        "name": "url",
-        "value": "",
-        "description": "Enter a URL",
-        "placeholder_values": ["https://example.com"],
-    }
-    result = BaseGraph._generate_schema(
-        (AgentInputBlock.Input, legacy_input_default),
-    )
-    url_props = result["properties"]["url"]
-    assert (
-        "enum" not in url_props
-    ), "Graph schema should not contain enum from AgentInputBlock placeholder_values"
-
-
-def test_generate_schema_integration_dropdown_produces_enum():
-    """Test the full Graph._generate_schema path with AgentDropdownInputBlock
-    — verifies enum IS produced for dropdown blocks."""
-    dropdown_input_default = {
-        "name": "color",
-        "value": None,
-        "placeholder_values": ["Red", "Green", "Blue"],
-    }
-    result = BaseGraph._generate_schema(
-        (AgentDropdownInputBlock.Input, dropdown_input_default),
-    )
-    color_props = result["properties"]["color"]
-    assert color_props.get("enum") == [
-        "Red",
-        "Green",
-        "Blue",
-    ], "Graph schema should contain enum from AgentDropdownInputBlock"

autogpt_platform/backend/backend/blocks/test/test_blocks_dos_vulnerability.py

@@ -207,51 +207,6 @@ class TestXMLParserBlockSecurity:
                 pass
 
 
-class TestXMLParserBlockSyntaxErrors:
-    """XML syntax errors should raise ValueError (not SyntaxError).
-
-    This ensures the base Block.execute() wraps them as BlockExecutionError
-    (expected / user-caused) instead of BlockUnknownError (unexpected / alerts
-    Sentry).
-    """
-
-    async def test_unclosed_tag_raises_value_error(self):
-        """Unclosed tags should raise ValueError, not SyntaxError."""
-        block = XMLParserBlock()
-        bad_xml = "<root><unclosed>"
-
-        with pytest.raises(ValueError, match="Unclosed tag"):
-            async for _ in block.run(XMLParserBlock.Input(input_xml=bad_xml)):
-                pass
-
-    async def test_unexpected_closing_tag_raises_value_error(self):
-        """Extra closing tags should raise ValueError, not SyntaxError."""
-        block = XMLParserBlock()
-        bad_xml = "</unexpected>"
-
-        with pytest.raises(ValueError):
-            async for _ in block.run(XMLParserBlock.Input(input_xml=bad_xml)):
-                pass
-
-    async def test_empty_xml_raises_value_error(self):
-        """Empty XML input should raise ValueError."""
-        block = XMLParserBlock()
-
-        with pytest.raises(ValueError, match="XML input is empty"):
-            async for _ in block.run(XMLParserBlock.Input(input_xml="")):
-                pass
-
-    async def test_syntax_error_from_parser_becomes_value_error(self):
-        """SyntaxErrors from gravitasml library become ValueError (BlockExecutionError)."""
-        block = XMLParserBlock()
-        # Malformed XML that might trigger a SyntaxError from the parser
-        bad_xml = "<root><child>no closing"
-
-        with pytest.raises(ValueError):
-            async for _ in block.run(XMLParserBlock.Input(input_xml=bad_xml)):
-                pass
-
-
 class TestStoreMediaFileSecurity:
     """Test file storage security limits."""
 

autogpt_platform/backend/backend/blocks/test/test_llm.py

@@ -1,18 +1,9 @@
-from typing import cast
 from unittest.mock import AsyncMock, MagicMock, patch
 
-import anthropic
-import httpx
-import openai
 import pytest
 
-import backend.blocks.llm as llm
 from backend.data.model import NodeExecutionStats
 
-# TEST_CREDENTIALS_INPUT is a plain dict that satisfies AICredentials at runtime
-# but not at the type level. Cast once here to avoid per-test suppressors.
-_TEST_AI_CREDENTIALS = cast(llm.AICredentials, llm.TEST_CREDENTIALS_INPUT)
-
 
 class TestLLMStatsTracking:
     """Test that LLM blocks correctly track token usage statistics."""
@@ -22,17 +13,18 @@ class TestLLMStatsTracking:
         """Test that llm_call returns proper token counts in LLMResponse."""
         import backend.blocks.llm as llm
 
-        # Mock the OpenAI Responses API response
+        # Mock the OpenAI client
         mock_response = MagicMock()
-        mock_response.output_text = "Test response"
-        mock_response.output = []
-        mock_response.usage = MagicMock(input_tokens=10, output_tokens=20)
+        mock_response.choices = [
+            MagicMock(message=MagicMock(content="Test response", tool_calls=None))
+        ]
+        mock_response.usage = MagicMock(prompt_tokens=10, completion_tokens=20)
 
         # Test with mocked OpenAI response
         with patch("openai.AsyncOpenAI") as mock_openai:
             mock_client = AsyncMock()
             mock_openai.return_value = mock_client
-            mock_client.responses.create = AsyncMock(return_value=mock_response)
+            mock_client.chat.completions.create = AsyncMock(return_value=mock_response)
 
             response = await llm.llm_call(
                 credentials=llm.TEST_CREDENTIALS,
@@ -279,17 +271,30 @@ class TestLLMStatsTracking:
             mock_response = MagicMock()
             # Return different responses for chunk summary vs final summary
             if call_count == 1:
-                mock_response.output_text = '<json_output id="test123456">{"summary": "Test chunk summary"}</json_output>'
+                mock_response.choices = [
+                    MagicMock(
+                        message=MagicMock(
+                            content='<json_output id="test123456">{"summary": "Test chunk summary"}</json_output>',
+                            tool_calls=None,
+                        )
+                    )
+                ]
             else:
-                mock_response.output_text = '<json_output id="test123456">{"final_summary": "Test final summary"}</json_output>'
-            mock_response.output = []
-            mock_response.usage = MagicMock(input_tokens=50, output_tokens=30)
+                mock_response.choices = [
+                    MagicMock(
+                        message=MagicMock(
+                            content='<json_output id="test123456">{"final_summary": "Test final summary"}</json_output>',
+                            tool_calls=None,
+                        )
+                    )
+                ]
+            mock_response.usage = MagicMock(prompt_tokens=50, completion_tokens=30)
             return mock_response
 
         with patch("openai.AsyncOpenAI") as mock_openai:
             mock_client = AsyncMock()
             mock_openai.return_value = mock_client
-            mock_client.responses.create = mock_create
+            mock_client.chat.completions.create = mock_create
 
             # Test with very short text (should only need 1 chunk + 1 final summary)
             input_data = llm.AITextSummarizerBlock.Input(
@@ -488,154 +493,6 @@ class TestLLMStatsTracking:
         assert outputs["response"] == {"result": "test"}
 
 
-class TestAIConversationBlockValidation:
-    """Test that AIConversationBlock validates inputs before calling the LLM."""
-
-    @pytest.mark.asyncio
-    async def test_empty_messages_and_empty_prompt_raises_error(self):
-        """Empty messages with no prompt should raise ValueError, not a cryptic API error."""
-        block = llm.AIConversationBlock()
-
-        input_data = llm.AIConversationBlock.Input(
-            messages=[],
-            prompt="",
-            model=llm.DEFAULT_LLM_MODEL,
-            credentials=_TEST_AI_CREDENTIALS,
-        )
-
-        with pytest.raises(ValueError, match="no messages and no prompt"):
-            async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
-                pass
-
-    @pytest.mark.asyncio
-    async def test_empty_messages_with_prompt_succeeds(self):
-        """Empty messages but a non-empty prompt should proceed without error."""
-        block = llm.AIConversationBlock()
-
-        async def mock_llm_call(input_data, credentials):
-            return {"response": "OK"}
-
-        with patch.object(block, "llm_call", new=AsyncMock(side_effect=mock_llm_call)):
-            input_data = llm.AIConversationBlock.Input(
-                messages=[],
-                prompt="Hello, how are you?",
-                model=llm.DEFAULT_LLM_MODEL,
-                credentials=_TEST_AI_CREDENTIALS,
-            )
-
-            outputs = {}
-            async for name, data in block.run(
-                input_data, credentials=llm.TEST_CREDENTIALS
-            ):
-                outputs[name] = data
-
-        assert outputs["response"] == "OK"
-
-    @pytest.mark.asyncio
-    async def test_nonempty_messages_with_empty_prompt_succeeds(self):
-        """Non-empty messages with no prompt should proceed without error."""
-        block = llm.AIConversationBlock()
-
-        async def mock_llm_call(input_data, credentials):
-            return {"response": "response from conversation"}
-
-        with patch.object(block, "llm_call", new=AsyncMock(side_effect=mock_llm_call)):
-            input_data = llm.AIConversationBlock.Input(
-                messages=[{"role": "user", "content": "Hello"}],
-                prompt="",
-                model=llm.DEFAULT_LLM_MODEL,
-                credentials=_TEST_AI_CREDENTIALS,
-            )
-
-            outputs = {}
-            async for name, data in block.run(
-                input_data, credentials=llm.TEST_CREDENTIALS
-            ):
-                outputs[name] = data
-
-        assert outputs["response"] == "response from conversation"
-
-    @pytest.mark.asyncio
-    async def test_messages_with_empty_content_raises_error(self):
-        """Messages with empty content strings should be treated as no messages."""
-        block = llm.AIConversationBlock()
-
-        input_data = llm.AIConversationBlock.Input(
-            messages=[{"role": "user", "content": ""}],
-            prompt="",
-            model=llm.DEFAULT_LLM_MODEL,
-            credentials=_TEST_AI_CREDENTIALS,
-        )
-
-        with pytest.raises(ValueError, match="no messages and no prompt"):
-            async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
-                pass
-
-    @pytest.mark.asyncio
-    async def test_messages_with_whitespace_content_raises_error(self):
-        """Messages with whitespace-only content should be treated as no messages."""
-        block = llm.AIConversationBlock()
-
-        input_data = llm.AIConversationBlock.Input(
-            messages=[{"role": "user", "content": "   "}],
-            prompt="",
-            model=llm.DEFAULT_LLM_MODEL,
-            credentials=_TEST_AI_CREDENTIALS,
-        )
-
-        with pytest.raises(ValueError, match="no messages and no prompt"):
-            async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
-                pass
-
-    @pytest.mark.asyncio
-    async def test_messages_with_none_entry_raises_error(self):
-        """Messages list containing None should be treated as no messages."""
-        block = llm.AIConversationBlock()
-
-        input_data = llm.AIConversationBlock.Input(
-            messages=[None],
-            prompt="",
-            model=llm.DEFAULT_LLM_MODEL,
-            credentials=_TEST_AI_CREDENTIALS,
-        )
-
-        with pytest.raises(ValueError, match="no messages and no prompt"):
-            async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
-                pass
-
-    @pytest.mark.asyncio
-    async def test_messages_with_empty_dict_raises_error(self):
-        """Messages list containing empty dict should be treated as no messages."""
-        block = llm.AIConversationBlock()
-
-        input_data = llm.AIConversationBlock.Input(
-            messages=[{}],
-            prompt="",
-            model=llm.DEFAULT_LLM_MODEL,
-            credentials=_TEST_AI_CREDENTIALS,
-        )
-
-        with pytest.raises(ValueError, match="no messages and no prompt"):
-            async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
-                pass
-
-    @pytest.mark.asyncio
-    async def test_messages_with_none_content_raises_error(self):
-        """Messages with content=None should not crash with AttributeError."""
-        block = llm.AIConversationBlock()
-
-        input_data = llm.AIConversationBlock.Input(
-            messages=[{"role": "user", "content": None}],
-            prompt="",
-            model=llm.DEFAULT_LLM_MODEL,
-            credentials=_TEST_AI_CREDENTIALS,
-        )
-
-        with pytest.raises(ValueError, match="no messages and no prompt"):
-            async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
-                pass
-
-
 class TestAITextSummarizerValidation:
     """Test that AITextSummarizerBlock validates LLM responses are strings."""
 
@@ -812,178 +669,3 @@ class TestAITextSummarizerValidation:
         error_message = str(exc_info.value)
         assert "Expected a string summary" in error_message
         assert "received dict" in error_message
-
-
-def _make_anthropic_status_error(status_code: int) -> anthropic.APIStatusError:
-    """Create an anthropic.APIStatusError with the given status code."""
-    request = httpx.Request("POST", "https://api.anthropic.com/v1/messages")
-    response = httpx.Response(status_code, request=request)
-    return anthropic.APIStatusError(
-        f"Error code: {status_code}", response=response, body=None
-    )
-
-
-def _make_openai_status_error(status_code: int) -> openai.APIStatusError:
-    """Create an openai.APIStatusError with the given status code."""
-    response = httpx.Response(
-        status_code, request=httpx.Request("POST", "https://api.openai.com/v1/chat")
-    )
-    return openai.APIStatusError(
-        f"Error code: {status_code}", response=response, body=None
-    )
-
-
-class TestUserErrorStatusCodeHandling:
-    """Test that user-caused LLM API errors (401/403/429) break the retry loop
-    and are logged as warnings, while server errors (500) trigger retries."""
-
-    @pytest.mark.asyncio
-    @pytest.mark.parametrize("status_code", [401, 403, 429])
-    async def test_anthropic_user_error_breaks_retry_loop(self, status_code: int):
-        """401/403/429 Anthropic errors should break immediately, not retry."""
-        import backend.blocks.llm as llm
-
-        block = llm.AIStructuredResponseGeneratorBlock()
-        call_count = 0
-
-        async def mock_llm_call(*args, **kwargs):
-            nonlocal call_count
-            call_count += 1
-            raise _make_anthropic_status_error(status_code)
-
-        with patch.object(block, "llm_call", new=AsyncMock(side_effect=mock_llm_call)):
-            input_data = llm.AIStructuredResponseGeneratorBlock.Input(
-                prompt="Test",
-                expected_format={"key": "desc"},
-                model=llm.DEFAULT_LLM_MODEL,
-                credentials=_TEST_AI_CREDENTIALS,
-                retry=3,
-            )
-
-            with pytest.raises(RuntimeError):
-                async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
-                    pass
-
-        assert (
-            call_count == 1
-        ), f"Expected exactly 1 call for status {status_code}, got {call_count}"
-
-    @pytest.mark.asyncio
-    @pytest.mark.parametrize("status_code", [401, 403, 429])
-    async def test_openai_user_error_breaks_retry_loop(self, status_code: int):
-        """401/403/429 OpenAI errors should break immediately, not retry."""
-        import backend.blocks.llm as llm
-
-        block = llm.AIStructuredResponseGeneratorBlock()
-        call_count = 0
-
-        async def mock_llm_call(*args, **kwargs):
-            nonlocal call_count
-            call_count += 1
-            raise _make_openai_status_error(status_code)
-
-        with patch.object(block, "llm_call", new=AsyncMock(side_effect=mock_llm_call)):
-            input_data = llm.AIStructuredResponseGeneratorBlock.Input(
-                prompt="Test",
-                expected_format={"key": "desc"},
-                model=llm.DEFAULT_LLM_MODEL,
-                credentials=_TEST_AI_CREDENTIALS,
-                retry=3,
-            )
-
-            with pytest.raises(RuntimeError):
-                async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
-                    pass
-
-        assert (
-            call_count == 1
-        ), f"Expected exactly 1 call for status {status_code}, got {call_count}"
-
-    @pytest.mark.asyncio
-    async def test_server_error_retries(self):
-        """500 errors should be retried (not break immediately)."""
-        import backend.blocks.llm as llm
-
-        block = llm.AIStructuredResponseGeneratorBlock()
-        call_count = 0
-
-        async def mock_llm_call(*args, **kwargs):
-            nonlocal call_count
-            call_count += 1
-            raise _make_anthropic_status_error(500)
-
-        with patch.object(block, "llm_call", new=AsyncMock(side_effect=mock_llm_call)):
-            input_data = llm.AIStructuredResponseGeneratorBlock.Input(
-                prompt="Test",
-                expected_format={"key": "desc"},
-                model=llm.DEFAULT_LLM_MODEL,
-                credentials=_TEST_AI_CREDENTIALS,
-                retry=3,
-            )
-
-            with pytest.raises(RuntimeError):
-                async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
-                    pass
-
-        assert (
-            call_count > 1
-        ), f"Expected multiple retry attempts for 500, got {call_count}"
-
-    @pytest.mark.asyncio
-    async def test_user_error_logs_warning_not_exception(self):
-        """User-caused errors should log with logger.warning, not logger.exception."""
-        import backend.blocks.llm as llm
-
-        block = llm.AIStructuredResponseGeneratorBlock()
-
-        async def mock_llm_call(*args, **kwargs):
-            raise _make_anthropic_status_error(401)
-
-        with patch.object(block, "llm_call", new=AsyncMock(side_effect=mock_llm_call)):
-            input_data = llm.AIStructuredResponseGeneratorBlock.Input(
-                prompt="Test",
-                expected_format={"key": "desc"},
-                model=llm.DEFAULT_LLM_MODEL,
-                credentials=_TEST_AI_CREDENTIALS,
-            )
-
-            with (
-                patch.object(llm.logger, "warning") as mock_warning,
-                patch.object(llm.logger, "exception") as mock_exception,
-                pytest.raises(RuntimeError),
-            ):
-                async for _ in block.run(input_data, credentials=llm.TEST_CREDENTIALS):
-                    pass
-
-        mock_warning.assert_called_once()
-        mock_exception.assert_not_called()
-
-
-class TestLlmModelMissing:
-    """Test that LlmModel handles provider-prefixed model names."""
-
-    def test_provider_prefixed_model_resolves(self):
-        """Provider-prefixed model string should resolve to the correct enum member."""
-        assert (
-            llm.LlmModel("anthropic/claude-sonnet-4-6")
-            == llm.LlmModel.CLAUDE_4_6_SONNET
-        )
-
-    def test_bare_model_still_works(self):
-        """Bare (non-prefixed) model string should still resolve correctly."""
-        assert llm.LlmModel("claude-sonnet-4-6") == llm.LlmModel.CLAUDE_4_6_SONNET
-
-    def test_invalid_prefixed_model_raises(self):
-        """Unknown provider-prefixed model string should raise ValueError."""
-        with pytest.raises(ValueError):
-            llm.LlmModel("invalid/nonexistent-model")
-
-    def test_slash_containing_value_direct_lookup(self):
-        """Enum values with '/' (e.g., OpenRouter models) should resolve via direct lookup, not _missing_."""
-        assert llm.LlmModel("google/gemini-2.5-pro") == llm.LlmModel.GEMINI_2_5_PRO
-
-    def test_double_prefixed_slash_model(self):
-        """Double-prefixed value should still resolve by stripping first prefix."""
-        assert (
-            llm.LlmModel("extra/google/gemini-2.5-pro") == llm.LlmModel.GEMINI_2_5_PRO
-        )

autogpt_platform/backend/backend/blocks/test/test_llm_empty_choices.py

@@ -1,87 +0,0 @@
-"""Tests for empty-choices guard in extract_openai_tool_calls() and extract_openai_reasoning()."""
-
-from unittest.mock import MagicMock
-
-from backend.blocks.llm import extract_openai_reasoning, extract_openai_tool_calls
-
-
-class TestExtractOpenaiToolCallsEmptyChoices:
-    """extract_openai_tool_calls() must return None when choices is empty."""
-
-    def test_returns_none_for_empty_choices(self):
-        response = MagicMock()
-        response.choices = []
-        assert extract_openai_tool_calls(response) is None
-
-    def test_returns_none_for_none_choices(self):
-        response = MagicMock()
-        response.choices = None
-        assert extract_openai_tool_calls(response) is None
-
-    def test_returns_tool_calls_when_choices_present(self):
-        tool = MagicMock()
-        tool.id = "call_1"
-        tool.type = "function"
-        tool.function.name = "my_func"
-        tool.function.arguments = '{"a": 1}'
-
-        message = MagicMock()
-        message.tool_calls = [tool]
-
-        choice = MagicMock()
-        choice.message = message
-
-        response = MagicMock()
-        response.choices = [choice]
-
-        result = extract_openai_tool_calls(response)
-        assert result is not None
-        assert len(result) == 1
-        assert result[0].function.name == "my_func"
-
-    def test_returns_none_when_no_tool_calls(self):
-        message = MagicMock()
-        message.tool_calls = None
-
-        choice = MagicMock()
-        choice.message = message
-
-        response = MagicMock()
-        response.choices = [choice]
-
-        assert extract_openai_tool_calls(response) is None
-
-
-class TestExtractOpenaiReasoningEmptyChoices:
-    """extract_openai_reasoning() must return None when choices is empty."""
-
-    def test_returns_none_for_empty_choices(self):
-        response = MagicMock()
-        response.choices = []
-        assert extract_openai_reasoning(response) is None
-
-    def test_returns_none_for_none_choices(self):
-        response = MagicMock()
-        response.choices = None
-        assert extract_openai_reasoning(response) is None
-
-    def test_returns_reasoning_from_choice(self):
-        choice = MagicMock()
-        choice.reasoning = "Step-by-step reasoning"
-        choice.message = MagicMock(spec=[])  # no 'reasoning' attr on message
-
-        response = MagicMock(spec=[])  # no 'reasoning' attr on response
-        response.choices = [choice]
-
-        result = extract_openai_reasoning(response)
-        assert result == "Step-by-step reasoning"
-
-    def test_returns_none_when_no_reasoning(self):
-        choice = MagicMock(spec=[])  # no 'reasoning' attr
-        choice.message = MagicMock(spec=[])  # no 'reasoning' attr
-
-        response = MagicMock(spec=[])  # no 'reasoning' attr
-        response.choices = [choice]
-
-        result = extract_openai_reasoning(response)
-        assert result is None

autogpt_platform/backend/backend/blocks/test/test_orchestrator_execution_mode.py

@@ -1,202 +0,0 @@
-"""Tests for ExecutionMode enum and provider validation in the orchestrator.
-
-Covers:
-- ExecutionMode enum members exist and have stable values
-- EXTENDED_THINKING provider validation (anthropic/open_router allowed, others rejected)
-- EXTENDED_THINKING model-name validation (must start with "claude")
-"""
-
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import pytest
-
-from backend.blocks.llm import LlmModel
-from backend.blocks.orchestrator import ExecutionMode, OrchestratorBlock
-
-# ---------------------------------------------------------------------------
-# ExecutionMode enum integrity
-# ---------------------------------------------------------------------------
-
-
-class TestExecutionModeEnum:
-    """Guard against accidental renames or removals of enum members."""
-
-    def test_built_in_exists(self):
-        assert hasattr(ExecutionMode, "BUILT_IN")
-        assert ExecutionMode.BUILT_IN.value == "built_in"
-
-    def test_extended_thinking_exists(self):
-        assert hasattr(ExecutionMode, "EXTENDED_THINKING")
-        assert ExecutionMode.EXTENDED_THINKING.value == "extended_thinking"
-
-    def test_exactly_two_members(self):
-        """If a new mode is added, this test should be updated intentionally."""
-        assert set(ExecutionMode.__members__.keys()) == {
-            "BUILT_IN",
-            "EXTENDED_THINKING",
-        }
-
-    def test_string_enum(self):
-        """ExecutionMode is a str enum so it serialises cleanly to JSON."""
-        assert isinstance(ExecutionMode.BUILT_IN, str)
-        assert isinstance(ExecutionMode.EXTENDED_THINKING, str)
-
-    def test_round_trip_from_value(self):
-        """Constructing from the string value should return the same member."""
-        assert ExecutionMode("built_in") is ExecutionMode.BUILT_IN
-        assert ExecutionMode("extended_thinking") is ExecutionMode.EXTENDED_THINKING
-
-
-# ---------------------------------------------------------------------------
-# Provider validation (inline in OrchestratorBlock.run)
-# ---------------------------------------------------------------------------
-
-
-def _make_model_stub(provider: str, value: str):
-    """Create a lightweight stub that behaves like LlmModel for validation."""
-    metadata = MagicMock()
-    metadata.provider = provider
-    stub = MagicMock()
-    stub.metadata = metadata
-    stub.value = value
-    return stub
-
-
-class TestExtendedThinkingProviderValidation:
-    """The orchestrator rejects EXTENDED_THINKING for non-Anthropic providers."""
-
-    def test_anthropic_provider_accepted(self):
-        """provider='anthropic' + claude model should not raise."""
-        model = _make_model_stub("anthropic", "claude-opus-4-6")
-        provider = model.metadata.provider
-        model_name = model.value
-        assert provider in ("anthropic", "open_router")
-        assert model_name.startswith("claude")
-
-    def test_open_router_provider_accepted(self):
-        """provider='open_router' + claude model should not raise."""
-        model = _make_model_stub("open_router", "claude-sonnet-4-6")
-        provider = model.metadata.provider
-        model_name = model.value
-        assert provider in ("anthropic", "open_router")
-        assert model_name.startswith("claude")
-
-    def test_openai_provider_rejected(self):
-        """provider='openai' should be rejected for EXTENDED_THINKING."""
-        model = _make_model_stub("openai", "gpt-4o")
-        provider = model.metadata.provider
-        assert provider not in ("anthropic", "open_router")
-
-    def test_groq_provider_rejected(self):
-        model = _make_model_stub("groq", "llama-3.3-70b-versatile")
-        provider = model.metadata.provider
-        assert provider not in ("anthropic", "open_router")
-
-    def test_non_claude_model_rejected_even_if_anthropic_provider(self):
-        """A hypothetical non-Claude model with provider='anthropic' is rejected."""
-        model = _make_model_stub("anthropic", "not-a-claude-model")
-        model_name = model.value
-        assert not model_name.startswith("claude")
-
-    def test_real_gpt4o_model_rejected(self):
-        """Verify a real LlmModel enum member (GPT4O) fails the provider check."""
-        model = LlmModel.GPT4O
-        provider = model.metadata.provider
-        assert provider not in ("anthropic", "open_router")
-
-    def test_real_claude_model_passes(self):
-        """Verify a real LlmModel enum member (CLAUDE_4_6_SONNET) passes."""
-        model = LlmModel.CLAUDE_4_6_SONNET
-        provider = model.metadata.provider
-        model_name = model.value
-        assert provider in ("anthropic", "open_router")
-        assert model_name.startswith("claude")
-
-
-# ---------------------------------------------------------------------------
-# Integration-style: exercise the validation branch via OrchestratorBlock.run
-# ---------------------------------------------------------------------------
-
-
-def _make_input_data(model, execution_mode=ExecutionMode.EXTENDED_THINKING):
-    """Build a minimal MagicMock that satisfies OrchestratorBlock.run's early path."""
-    inp = MagicMock()
-    inp.execution_mode = execution_mode
-    inp.model = model
-    inp.prompt = "test"
-    inp.sys_prompt = ""
-    inp.conversation_history = []
-    inp.last_tool_output = None
-    inp.prompt_values = {}
-    return inp
-
-
-async def _collect_run_outputs(block, input_data, **kwargs):
-    """Exhaust the OrchestratorBlock.run async generator, collecting outputs."""
-    outputs = []
-    async for item in block.run(input_data, **kwargs):
-        outputs.append(item)
-    return outputs
-
-
-class TestExtendedThinkingValidationRaisesInBlock:
-    """Call OrchestratorBlock.run far enough to trigger the ValueError."""
-
-    @pytest.mark.asyncio
-    async def test_non_anthropic_provider_raises_valueerror(self):
-        """EXTENDED_THINKING + openai provider raises ValueError."""
-        block = OrchestratorBlock()
-        input_data = _make_input_data(model=LlmModel.GPT4O)
-
-        with (
-            patch.object(
-                block,
-                "_create_tool_node_signatures",
-                new_callable=AsyncMock,
-                return_value=[],
-            ),
-            pytest.raises(ValueError, match="Anthropic-compatible"),
-        ):
-            await _collect_run_outputs(
-                block,
-                input_data,
-                credentials=MagicMock(),
-                graph_id="g",
-                node_id="n",
-                graph_exec_id="ge",
-                node_exec_id="ne",
-                user_id="u",
-                graph_version=1,
-                execution_context=MagicMock(),
-                execution_processor=MagicMock(),
-            )
-
-    @pytest.mark.asyncio
-    async def test_non_claude_model_with_anthropic_provider_raises(self):
-        """A model with anthropic provider but non-claude name raises ValueError."""
-        block = OrchestratorBlock()
-        fake_model = _make_model_stub("anthropic", "not-a-claude-model")
-        input_data = _make_input_data(model=fake_model)
-
-        with (
-            patch.object(
-                block,
-                "_create_tool_node_signatures",
-                new_callable=AsyncMock,
-                return_value=[],
-            ),
-            pytest.raises(ValueError, match="only supports Claude models"),
-        ):
-            await _collect_run_outputs(
-                block,
-                input_data,
-                credentials=MagicMock(),
-                graph_id="g",
-                node_id="n",
-                graph_exec_id="ge",
-                node_exec_id="ne",
-                user_id="u",
-                graph_version=1,
-                execution_context=MagicMock(),
-                execution_processor=MagicMock(),
-            )

autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker.py

@@ -57,7 +57,7 @@ async def execute_graph(
 @pytest.mark.asyncio(loop_scope="session")
 async def test_graph_validation_with_tool_nodes_correct(server: SpinTestServer):
     from backend.blocks.agent import AgentExecutorBlock
-    from backend.blocks.orchestrator import OrchestratorBlock
+    from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
     from backend.data import graph
 
     test_user = await create_test_user()
@@ -66,7 +66,7 @@ async def test_graph_validation_with_tool_nodes_correct(server: SpinTestServer):
 
     nodes = [
         graph.Node(
-            block_id=OrchestratorBlock().id,
+            block_id=SmartDecisionMakerBlock().id,
             input_default={
                 "prompt": "Hello, World!",
                 "credentials": creds,
@@ -108,10 +108,10 @@ async def test_graph_validation_with_tool_nodes_correct(server: SpinTestServer):
 
 
 @pytest.mark.asyncio(loop_scope="session")
-async def test_orchestrator_function_signature(server: SpinTestServer):
+async def test_smart_decision_maker_function_signature(server: SpinTestServer):
     from backend.blocks.agent import AgentExecutorBlock
     from backend.blocks.basic import StoreValueBlock
-    from backend.blocks.orchestrator import OrchestratorBlock
+    from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
     from backend.data import graph
 
     test_user = await create_test_user()
@@ -120,7 +120,7 @@ async def test_orchestrator_function_signature(server: SpinTestServer):
 
     nodes = [
         graph.Node(
-            block_id=OrchestratorBlock().id,
+            block_id=SmartDecisionMakerBlock().id,
             input_default={
                 "prompt": "Hello, World!",
                 "credentials": creds,
@@ -169,7 +169,7 @@ async def test_orchestrator_function_signature(server: SpinTestServer):
     )
     test_graph = await create_graph(server, test_graph, test_user)
 
-    tool_functions = await OrchestratorBlock._create_tool_node_signatures(
+    tool_functions = await SmartDecisionMakerBlock._create_tool_node_signatures(
         test_graph.nodes[0].id
     )
     assert tool_functions is not None, "Tool functions should not be None"
@@ -198,12 +198,12 @@ async def test_orchestrator_function_signature(server: SpinTestServer):
 
 
 @pytest.mark.asyncio
-async def test_orchestrator_tracks_llm_stats():
-    """Test that OrchestratorBlock correctly tracks LLM usage stats."""
+async def test_smart_decision_maker_tracks_llm_stats():
+    """Test that SmartDecisionMakerBlock correctly tracks LLM usage stats."""
     import backend.blocks.llm as llm_module
-    from backend.blocks.orchestrator import OrchestratorBlock
+    from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
 
-    block = OrchestratorBlock()
+    block = SmartDecisionMakerBlock()
 
     # Mock the llm.llm_call function to return controlled data
     mock_response = MagicMock()
@@ -224,14 +224,14 @@ async def test_orchestrator_tracks_llm_stats():
         new_callable=AsyncMock,
         return_value=mock_response,
     ), patch.object(
-        OrchestratorBlock,
+        SmartDecisionMakerBlock,
         "_create_tool_node_signatures",
         new_callable=AsyncMock,
         return_value=[],
     ):
 
         # Create test input
-        input_data = OrchestratorBlock.Input(
+        input_data = SmartDecisionMakerBlock.Input(
             prompt="Should I continue with this task?",
             model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
@@ -274,12 +274,12 @@ async def test_orchestrator_tracks_llm_stats():
 
 
 @pytest.mark.asyncio
-async def test_orchestrator_parameter_validation():
-    """Test that OrchestratorBlock correctly validates tool call parameters."""
+async def test_smart_decision_maker_parameter_validation():
+    """Test that SmartDecisionMakerBlock correctly validates tool call parameters."""
     import backend.blocks.llm as llm_module
-    from backend.blocks.orchestrator import OrchestratorBlock
+    from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
 
-    block = OrchestratorBlock()
+    block = SmartDecisionMakerBlock()
 
     # Mock tool functions with specific parameter schema
     mock_tool_functions = [
@@ -327,13 +327,13 @@ async def test_orchestrator_parameter_validation():
         new_callable=AsyncMock,
         return_value=mock_response_with_typo,
     ) as mock_llm_call, patch.object(
-        OrchestratorBlock,
+        SmartDecisionMakerBlock,
         "_create_tool_node_signatures",
         new_callable=AsyncMock,
         return_value=mock_tool_functions,
     ):
 
-        input_data = OrchestratorBlock.Input(
+        input_data = SmartDecisionMakerBlock.Input(
             prompt="Search for keywords",
             model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
@@ -394,13 +394,13 @@ async def test_orchestrator_parameter_validation():
         new_callable=AsyncMock,
         return_value=mock_response_missing_required,
     ), patch.object(
-        OrchestratorBlock,
+        SmartDecisionMakerBlock,
         "_create_tool_node_signatures",
         new_callable=AsyncMock,
         return_value=mock_tool_functions,
     ):
 
-        input_data = OrchestratorBlock.Input(
+        input_data = SmartDecisionMakerBlock.Input(
             prompt="Search for keywords",
             model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
@@ -454,13 +454,13 @@ async def test_orchestrator_parameter_validation():
         new_callable=AsyncMock,
         return_value=mock_response_valid,
     ), patch.object(
-        OrchestratorBlock,
+        SmartDecisionMakerBlock,
         "_create_tool_node_signatures",
         new_callable=AsyncMock,
         return_value=mock_tool_functions,
     ):
 
-        input_data = OrchestratorBlock.Input(
+        input_data = SmartDecisionMakerBlock.Input(
             prompt="Search for keywords",
             model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
@@ -518,13 +518,13 @@ async def test_orchestrator_parameter_validation():
         new_callable=AsyncMock,
         return_value=mock_response_all_params,
     ), patch.object(
-        OrchestratorBlock,
+        SmartDecisionMakerBlock,
         "_create_tool_node_signatures",
         new_callable=AsyncMock,
         return_value=mock_tool_functions,
     ):
 
-        input_data = OrchestratorBlock.Input(
+        input_data = SmartDecisionMakerBlock.Input(
             prompt="Search for keywords",
             model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
@@ -562,12 +562,12 @@ async def test_orchestrator_parameter_validation():
 
 
 @pytest.mark.asyncio
-async def test_orchestrator_raw_response_conversion():
-    """Test that Orchestrator correctly handles different raw_response types with retry mechanism."""
+async def test_smart_decision_maker_raw_response_conversion():
+    """Test that SmartDecisionMaker correctly handles different raw_response types with retry mechanism."""
     import backend.blocks.llm as llm_module
-    from backend.blocks.orchestrator import OrchestratorBlock
+    from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
 
-    block = OrchestratorBlock()
+    block = SmartDecisionMakerBlock()
 
     # Mock tool functions
     mock_tool_functions = [
@@ -637,7 +637,7 @@ async def test_orchestrator_raw_response_conversion():
     with patch(
         "backend.blocks.llm.llm_call", new_callable=AsyncMock
     ) as mock_llm_call, patch.object(
-        OrchestratorBlock,
+        SmartDecisionMakerBlock,
         "_create_tool_node_signatures",
         new_callable=AsyncMock,
         return_value=mock_tool_functions,
@@ -646,7 +646,7 @@ async def test_orchestrator_raw_response_conversion():
         # Second call returns successful response
         mock_llm_call.side_effect = [mock_response_retry, mock_response_success]
 
-        input_data = OrchestratorBlock.Input(
+        input_data = SmartDecisionMakerBlock.Input(
             prompt="Test prompt",
             model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
@@ -715,12 +715,12 @@ async def test_orchestrator_raw_response_conversion():
         new_callable=AsyncMock,
         return_value=mock_response_ollama,
     ), patch.object(
-        OrchestratorBlock,
+        SmartDecisionMakerBlock,
         "_create_tool_node_signatures",
         new_callable=AsyncMock,
         return_value=[],  # No tools for this test
     ):
-        input_data = OrchestratorBlock.Input(
+        input_data = SmartDecisionMakerBlock.Input(
             prompt="Simple prompt",
             model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
@@ -771,12 +771,12 @@ async def test_orchestrator_raw_response_conversion():
         new_callable=AsyncMock,
         return_value=mock_response_dict,
     ), patch.object(
-        OrchestratorBlock,
+        SmartDecisionMakerBlock,
         "_create_tool_node_signatures",
         new_callable=AsyncMock,
         return_value=[],
     ):
-        input_data = OrchestratorBlock.Input(
+        input_data = SmartDecisionMakerBlock.Input(
             prompt="Another test",
             model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
@@ -811,12 +811,12 @@ async def test_orchestrator_raw_response_conversion():
 
 
 @pytest.mark.asyncio
-async def test_orchestrator_agent_mode():
+async def test_smart_decision_maker_agent_mode():
     """Test that agent mode executes tools directly and loops until finished."""
     import backend.blocks.llm as llm_module
-    from backend.blocks.orchestrator import OrchestratorBlock
+    from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
 
-    block = OrchestratorBlock()
+    block = SmartDecisionMakerBlock()
 
     # Mock tool call that requires multiple iterations
     mock_tool_call_1 = MagicMock()
@@ -893,7 +893,7 @@ async def test_orchestrator_agent_mode():
     with patch("backend.blocks.llm.llm_call", llm_call_mock), patch.object(
         block, "_create_tool_node_signatures", return_value=mock_tool_signatures
     ), patch(
-        "backend.blocks.orchestrator.get_database_manager_async_client",
+        "backend.blocks.smart_decision_maker.get_database_manager_async_client",
         return_value=mock_db_client,
     ), patch(
         "backend.executor.manager.async_update_node_execution_status",
@@ -929,7 +929,7 @@ async def test_orchestrator_agent_mode():
         }
 
         # Test agent mode with max_iterations = 3
-        input_data = OrchestratorBlock.Input(
+        input_data = SmartDecisionMakerBlock.Input(
             prompt="Complete this task using tools",
             model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
@@ -969,12 +969,12 @@ async def test_orchestrator_agent_mode():
 
 
 @pytest.mark.asyncio
-async def test_orchestrator_traditional_mode_default():
+async def test_smart_decision_maker_traditional_mode_default():
     """Test that default behavior (agent_mode_max_iterations=0) works as traditional mode."""
     import backend.blocks.llm as llm_module
-    from backend.blocks.orchestrator import OrchestratorBlock
+    from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
 
-    block = OrchestratorBlock()
+    block = SmartDecisionMakerBlock()
 
     # Mock tool call
     mock_tool_call = MagicMock()
@@ -1018,7 +1018,7 @@ async def test_orchestrator_traditional_mode_default():
     ):
 
         # Test default behavior (traditional mode)
-        input_data = OrchestratorBlock.Input(
+        input_data = SmartDecisionMakerBlock.Input(
             prompt="Test prompt",
             model=llm_module.DEFAULT_LLM_MODEL,
             credentials=llm_module.TEST_CREDENTIALS_INPUT,  # type: ignore
@@ -1060,12 +1060,12 @@ async def test_orchestrator_traditional_mode_default():
 
 
 @pytest.mark.asyncio
-async def test_orchestrator_uses_customized_name_for_blocks():
-    """Test that OrchestratorBlock uses customized_name from node metadata for tool names."""
+async def test_smart_decision_maker_uses_customized_name_for_blocks():
+    """Test that SmartDecisionMakerBlock uses customized_name from node metadata for tool names."""
     from unittest.mock import MagicMock
 
     from backend.blocks.basic import StoreValueBlock
-    from backend.blocks.orchestrator import OrchestratorBlock
+    from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
     from backend.data.graph import Link, Node
 
     # Create a mock node with customized_name in metadata
@@ -1074,14 +1074,13 @@ async def test_orchestrator_uses_customized_name_for_blocks():
     mock_node.block_id = StoreValueBlock().id
     mock_node.metadata = {"customized_name": "My Custom Tool Name"}
     mock_node.block = StoreValueBlock()
-    mock_node.input_default = {}
 
     # Create a mock link
     mock_link = MagicMock(spec=Link)
     mock_link.sink_name = "input"
 
     # Call the function directly
-    result = await OrchestratorBlock._create_block_function_signature(
+    result = await SmartDecisionMakerBlock._create_block_function_signature(
         mock_node, [mock_link]
     )
 
@@ -1092,12 +1091,12 @@ async def test_orchestrator_uses_customized_name_for_blocks():
 
 
 @pytest.mark.asyncio
-async def test_orchestrator_falls_back_to_block_name():
-    """Test that OrchestratorBlock falls back to block.name when no customized_name."""
+async def test_smart_decision_maker_falls_back_to_block_name():
+    """Test that SmartDecisionMakerBlock falls back to block.name when no customized_name."""
     from unittest.mock import MagicMock
 
     from backend.blocks.basic import StoreValueBlock
-    from backend.blocks.orchestrator import OrchestratorBlock
+    from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
     from backend.data.graph import Link, Node
 
     # Create a mock node without customized_name
@@ -1106,14 +1105,13 @@ async def test_orchestrator_falls_back_to_block_name():
     mock_node.block_id = StoreValueBlock().id
     mock_node.metadata = {}  # No customized_name
     mock_node.block = StoreValueBlock()
-    mock_node.input_default = {}
 
     # Create a mock link
     mock_link = MagicMock(spec=Link)
     mock_link.sink_name = "input"
 
     # Call the function directly
-    result = await OrchestratorBlock._create_block_function_signature(
+    result = await SmartDecisionMakerBlock._create_block_function_signature(
         mock_node, [mock_link]
     )
 
@@ -1124,11 +1122,11 @@ async def test_orchestrator_falls_back_to_block_name():
 
 
 @pytest.mark.asyncio
-async def test_orchestrator_uses_customized_name_for_agents():
-    """Test that OrchestratorBlock uses customized_name from metadata for agent nodes."""
+async def test_smart_decision_maker_uses_customized_name_for_agents():
+    """Test that SmartDecisionMakerBlock uses customized_name from metadata for agent nodes."""
     from unittest.mock import AsyncMock, MagicMock, patch
 
-    from backend.blocks.orchestrator import OrchestratorBlock
+    from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
     from backend.data.graph import Link, Node
 
     # Create a mock node with customized_name in metadata
@@ -1154,10 +1152,10 @@ async def test_orchestrator_uses_customized_name_for_agents():
     mock_db_client.get_graph_metadata.return_value = mock_graph_meta
 
     with patch(
-        "backend.blocks.orchestrator.get_database_manager_async_client",
+        "backend.blocks.smart_decision_maker.get_database_manager_async_client",
         return_value=mock_db_client,
     ):
-        result = await OrchestratorBlock._create_agent_function_signature(
+        result = await SmartDecisionMakerBlock._create_agent_function_signature(
             mock_node, [mock_link]
         )
 
@@ -1168,11 +1166,11 @@ async def test_orchestrator_uses_customized_name_for_agents():
 
 
 @pytest.mark.asyncio
-async def test_orchestrator_agent_falls_back_to_graph_name():
+async def test_smart_decision_maker_agent_falls_back_to_graph_name():
     """Test that agent node falls back to graph name when no customized_name."""
     from unittest.mock import AsyncMock, MagicMock, patch
 
-    from backend.blocks.orchestrator import OrchestratorBlock
+    from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
     from backend.data.graph import Link, Node
 
     # Create a mock node without customized_name
@@ -1198,10 +1196,10 @@ async def test_orchestrator_agent_falls_back_to_graph_name():
     mock_db_client.get_graph_metadata.return_value = mock_graph_meta
 
     with patch(
-        "backend.blocks.orchestrator.get_database_manager_async_client",
+        "backend.blocks.smart_decision_maker.get_database_manager_async_client",
         return_value=mock_db_client,
     ):
-        result = await OrchestratorBlock._create_agent_function_signature(
+        result = await SmartDecisionMakerBlock._create_agent_function_signature(
             mock_node, [mock_link]
         )
 

autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker_dict.py

@@ -3,12 +3,12 @@ from unittest.mock import Mock
 import pytest
 
 from backend.blocks.data_manipulation import AddToListBlock, CreateDictionaryBlock
-from backend.blocks.orchestrator import OrchestratorBlock
+from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
 
 
 @pytest.mark.asyncio
-async def test_orchestrator_handles_dynamic_dict_fields():
-    """Test Orchestrator can handle dynamic dictionary fields (_#_) for any block"""
+async def test_smart_decision_maker_handles_dynamic_dict_fields():
+    """Test Smart Decision Maker can handle dynamic dictionary fields (_#_) for any block"""
 
     # Create a mock node for CreateDictionaryBlock
     mock_node = Mock()
@@ -23,24 +23,24 @@ async def test_orchestrator_handles_dynamic_dict_fields():
             source_name="tools_^_create_dict_~_name",
             sink_name="values_#_name",  # Dynamic dict field
             sink_id="dict_node_id",
-            source_id="orchestrator_node_id",
+            source_id="smart_decision_node_id",
         ),
         Mock(
             source_name="tools_^_create_dict_~_age",
             sink_name="values_#_age",  # Dynamic dict field
             sink_id="dict_node_id",
-            source_id="orchestrator_node_id",
+            source_id="smart_decision_node_id",
         ),
         Mock(
             source_name="tools_^_create_dict_~_city",
             sink_name="values_#_city",  # Dynamic dict field
             sink_id="dict_node_id",
-            source_id="orchestrator_node_id",
+            source_id="smart_decision_node_id",
         ),
     ]
 
     # Generate function signature
-    signature = await OrchestratorBlock._create_block_function_signature(
+    signature = await SmartDecisionMakerBlock._create_block_function_signature(
         mock_node, mock_links  # type: ignore
     )
 
@@ -70,8 +70,8 @@ async def test_orchestrator_handles_dynamic_dict_fields():
 
 
 @pytest.mark.asyncio
-async def test_orchestrator_handles_dynamic_list_fields():
-    """Test Orchestrator can handle dynamic list fields (_$_) for any block"""
+async def test_smart_decision_maker_handles_dynamic_list_fields():
+    """Test Smart Decision Maker can handle dynamic list fields (_$_) for any block"""
 
     # Create a mock node for AddToListBlock
     mock_node = Mock()
@@ -86,18 +86,18 @@ async def test_orchestrator_handles_dynamic_list_fields():
             source_name="tools_^_add_to_list_~_0",
             sink_name="entries_$_0",  # Dynamic list field
             sink_id="list_node_id",
-            source_id="orchestrator_node_id",
+            source_id="smart_decision_node_id",
         ),
         Mock(
             source_name="tools_^_add_to_list_~_1",
             sink_name="entries_$_1",  # Dynamic list field
             sink_id="list_node_id",
-            source_id="orchestrator_node_id",
+            source_id="smart_decision_node_id",
         ),
     ]
 
     # Generate function signature
-    signature = await OrchestratorBlock._create_block_function_signature(
+    signature = await SmartDecisionMakerBlock._create_block_function_signature(
         mock_node, mock_links  # type: ignore
     )
 

autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker_dynamic_fields.py

@@ -1,4 +1,4 @@
-"""Comprehensive tests for OrchestratorBlock dynamic field handling."""
+"""Comprehensive tests for SmartDecisionMakerBlock dynamic field handling."""
 
 import json
 from unittest.mock import AsyncMock, MagicMock, Mock, patch
@@ -6,7 +6,7 @@ from unittest.mock import AsyncMock, MagicMock, Mock, patch
 import pytest
 
 from backend.blocks.data_manipulation import AddToListBlock, CreateDictionaryBlock
-from backend.blocks.orchestrator import OrchestratorBlock
+from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
 from backend.blocks.text import MatchTextPatternBlock
 from backend.data.dynamic_fields import get_dynamic_field_description
 
@@ -37,7 +37,7 @@ async def test_dynamic_field_description_generation():
 @pytest.mark.asyncio
 async def test_create_block_function_signature_with_dict_fields():
     """Test that function signatures are created correctly for dictionary dynamic fields."""
-    block = OrchestratorBlock()
+    block = SmartDecisionMakerBlock()
 
     # Create a mock node for CreateDictionaryBlock
     mock_node = Mock()
@@ -52,19 +52,19 @@ async def test_create_block_function_signature_with_dict_fields():
             source_name="tools_^_create_dict_~_values___name",  # Sanitized source
             sink_name="values_#_name",  # Original sink
             sink_id="dict_node_id",
-            source_id="orchestrator_node_id",
+            source_id="smart_decision_node_id",
         ),
         Mock(
             source_name="tools_^_create_dict_~_values___age",  # Sanitized source
             sink_name="values_#_age",  # Original sink
             sink_id="dict_node_id",
-            source_id="orchestrator_node_id",
+            source_id="smart_decision_node_id",
         ),
         Mock(
             source_name="tools_^_create_dict_~_values___email",  # Sanitized source
             sink_name="values_#_email",  # Original sink
             sink_id="dict_node_id",
-            source_id="orchestrator_node_id",
+            source_id="smart_decision_node_id",
         ),
     ]
 
@@ -100,7 +100,7 @@ async def test_create_block_function_signature_with_dict_fields():
 @pytest.mark.asyncio
 async def test_create_block_function_signature_with_list_fields():
     """Test that function signatures are created correctly for list dynamic fields."""
-    block = OrchestratorBlock()
+    block = SmartDecisionMakerBlock()
 
     # Create a mock node for AddToListBlock
     mock_node = Mock()
@@ -115,19 +115,19 @@ async def test_create_block_function_signature_with_list_fields():
             source_name="tools_^_add_list_~_0",
             sink_name="entries_$_0",  # Dynamic list field
             sink_id="list_node_id",
-            source_id="orchestrator_node_id",
+            source_id="smart_decision_node_id",
         ),
         Mock(
             source_name="tools_^_add_list_~_1",
             sink_name="entries_$_1",  # Dynamic list field
             sink_id="list_node_id",
-            source_id="orchestrator_node_id",
+            source_id="smart_decision_node_id",
         ),
         Mock(
             source_name="tools_^_add_list_~_2",
             sink_name="entries_$_2",  # Dynamic list field
             sink_id="list_node_id",
-            source_id="orchestrator_node_id",
+            source_id="smart_decision_node_id",
         ),
     ]
 
@@ -154,7 +154,7 @@ async def test_create_block_function_signature_with_list_fields():
 @pytest.mark.asyncio
 async def test_create_block_function_signature_with_object_fields():
     """Test that function signatures are created correctly for object dynamic fields."""
-    block = OrchestratorBlock()
+    block = SmartDecisionMakerBlock()
 
     # Create a mock node for MatchTextPatternBlock (simulating object fields)
     mock_node = Mock()
@@ -169,13 +169,13 @@ async def test_create_block_function_signature_with_object_fields():
             source_name="tools_^_extract_~_user_name",
             sink_name="data_@_user_name",  # Dynamic object field
             sink_id="extract_node_id",
-            source_id="orchestrator_node_id",
+            source_id="smart_decision_node_id",
         ),
         Mock(
             source_name="tools_^_extract_~_user_email",
             sink_name="data_@_user_email",  # Dynamic object field
             sink_id="extract_node_id",
-            source_id="orchestrator_node_id",
+            source_id="smart_decision_node_id",
         ),
     ]
 
@@ -197,11 +197,11 @@ async def test_create_block_function_signature_with_object_fields():
 @pytest.mark.asyncio
 async def test_create_tool_node_signatures():
     """Test that the mapping between sanitized and original field names is built correctly."""
-    block = OrchestratorBlock()
+    block = SmartDecisionMakerBlock()
 
     # Mock the database client and connected nodes
     with patch(
-        "backend.blocks.orchestrator.get_database_manager_async_client"
+        "backend.blocks.smart_decision_maker.get_database_manager_async_client"
     ) as mock_db:
         mock_client = AsyncMock()
         mock_db.return_value = mock_client
@@ -281,7 +281,7 @@ async def test_create_tool_node_signatures():
 @pytest.mark.asyncio
 async def test_output_yielding_with_dynamic_fields():
     """Test that outputs are yielded correctly with dynamic field names mapped back."""
-    block = OrchestratorBlock()
+    block = SmartDecisionMakerBlock()
 
     # No more sanitized mapping needed since we removed sanitization
 
@@ -309,13 +309,13 @@ async def test_output_yielding_with_dynamic_fields():
 
     # Mock the LLM call
     with patch(
-        "backend.blocks.orchestrator.llm.llm_call", new_callable=AsyncMock
+        "backend.blocks.smart_decision_maker.llm.llm_call", new_callable=AsyncMock
     ) as mock_llm:
         mock_llm.return_value = mock_response
 
         # Mock the database manager to avoid HTTP calls during tool execution
         with patch(
-            "backend.blocks.orchestrator.get_database_manager_async_client"
+            "backend.blocks.smart_decision_maker.get_database_manager_async_client"
         ) as mock_db_manager, patch.object(
             block, "_create_tool_node_signatures", new_callable=AsyncMock
         ) as mock_sig:
@@ -420,7 +420,7 @@ async def test_output_yielding_with_dynamic_fields():
 @pytest.mark.asyncio
 async def test_mixed_regular_and_dynamic_fields():
     """Test handling of blocks with both regular and dynamic fields."""
-    block = OrchestratorBlock()
+    block = SmartDecisionMakerBlock()
 
     # Create a mock node
     mock_node = Mock()
@@ -450,19 +450,19 @@ async def test_mixed_regular_and_dynamic_fields():
             source_name="tools_^_test_~_regular",
             sink_name="regular_field",  # Regular field
             sink_id="test_node_id",
-            source_id="orchestrator_node_id",
+            source_id="smart_decision_node_id",
         ),
         Mock(
             source_name="tools_^_test_~_dict_key",
             sink_name="values_#_key1",  # Dynamic dict field
             sink_id="test_node_id",
-            source_id="orchestrator_node_id",
+            source_id="smart_decision_node_id",
         ),
         Mock(
             source_name="tools_^_test_~_dict_key2",
             sink_name="values_#_key2",  # Dynamic dict field
             sink_id="test_node_id",
-            source_id="orchestrator_node_id",
+            source_id="smart_decision_node_id",
         ),
     ]
 
@@ -488,7 +488,7 @@ async def test_mixed_regular_and_dynamic_fields():
 @pytest.mark.asyncio
 async def test_validation_errors_dont_pollute_conversation():
     """Test that validation errors are only used during retries and don't pollute the conversation."""
-    block = OrchestratorBlock()
+    block = SmartDecisionMakerBlock()
 
     # Track conversation history changes
     conversation_snapshots = []
@@ -535,7 +535,7 @@ async def test_validation_errors_dont_pollute_conversation():
 
     # Mock the LLM call
     with patch(
-        "backend.blocks.orchestrator.llm.llm_call", new_callable=AsyncMock
+        "backend.blocks.smart_decision_maker.llm.llm_call", new_callable=AsyncMock
     ) as mock_llm:
         mock_llm.side_effect = mock_llm_call
 
@@ -565,7 +565,7 @@ async def test_validation_errors_dont_pollute_conversation():
 
             # Mock the database manager to avoid HTTP calls during tool execution
             with patch(
-                "backend.blocks.orchestrator.get_database_manager_async_client"
+                "backend.blocks.smart_decision_maker.get_database_manager_async_client"
             ) as mock_db_manager:
                 # Set up the mock database manager for agent mode
                 mock_db_client = AsyncMock()

autogpt_platform/backend/backend/blocks/text.py

@@ -290,9 +290,7 @@ class FillTextTemplateBlock(Block):
 
     async def run(self, input_data: Input, **kwargs) -> BlockOutput:
         formatter = text.TextFormatter(autoescape=input_data.escape_html)
-        yield "output", await formatter.format_string(
-            input_data.format, input_data.values
-        )
+        yield "output", formatter.format_string(input_data.format, input_data.values)
 
 
 class CombineTextsBlock(Block):

autogpt_platform/backend/backend/blocks/xml_parser.py

@@ -44,7 +44,7 @@ class XMLParserBlock(Block):
             elif token.type == "TAG_CLOSE":
                 depth -= 1
                 if depth < 0:
-                    raise ValueError("Unexpected closing tag in XML input.")
+                    raise SyntaxError("Unexpected closing tag in XML input.")
             elif token.type in {"TEXT", "ESCAPE"}:
                 if depth == 0 and token.value:
                     raise ValueError(
@@ -53,7 +53,7 @@ class XMLParserBlock(Block):
                     )
 
         if depth != 0:
-            raise ValueError("Unclosed tag detected in XML input.")
+            raise SyntaxError("Unclosed tag detected in XML input.")
         if not root_seen:
             raise ValueError("XML must include a root element.")
 
@@ -76,7 +76,4 @@ class XMLParserBlock(Block):
         except ValueError as val_e:
             raise ValueError(f"Validation error for dict:{val_e}") from val_e
         except SyntaxError as syn_e:
-            # Raise as ValueError so the base Block.execute() wraps it as
-            # BlockExecutionError (expected user-caused failure) instead of
-            # BlockUnknownError (unexpected platform error that alerts Sentry).
-            raise ValueError(f"Error in input xml syntax: {syn_e}") from syn_e
+            raise SyntaxError(f"Error in input xml syntax: {syn_e}") from syn_e

autogpt_platform/backend/backend/copilot/baseline/service.py

@@ -9,14 +9,11 @@ shared tool registry as the SDK path.
 import asyncio
 import logging
 import uuid
-from collections.abc import AsyncGenerator, Sequence
-from dataclasses import dataclass, field
-from functools import partial
-from typing import Any, cast
+from collections.abc import AsyncGenerator
+from typing import Any
 
 import orjson
 from langfuse import propagate_attributes
-from openai.types.chat import ChatCompletionMessageParam, ChatCompletionToolParam
 
 from backend.copilot.model import (
     ChatMessage,
@@ -51,17 +48,7 @@ from backend.copilot.token_tracking import persist_and_record_usage
 from backend.copilot.tools import execute_tool, get_available_tools
 from backend.copilot.tracking import track_user_message
 from backend.util.exceptions import NotFoundError
-from backend.util.prompt import (
-    compress_context,
-    estimate_token_count,
-    estimate_token_count_str,
-)
-from backend.util.tool_call_loop import (
-    LLMLoopResponse,
-    LLMToolCall,
-    ToolCallResult,
-    tool_call_loop,
-)
+from backend.util.prompt import compress_context
 
 logger = logging.getLogger(__name__)
 
@@ -72,247 +59,6 @@ _background_tasks: set[asyncio.Task[Any]] = set()
 _MAX_TOOL_ROUNDS = 30
 
 
-@dataclass
-class _BaselineStreamState:
-    """Mutable state shared between the tool-call loop callbacks.
-
-    Extracted from ``stream_chat_completion_baseline`` so that the callbacks
-    can be module-level functions instead of deeply nested closures.
-    """
-
-    pending_events: list[StreamBaseResponse] = field(default_factory=list)
-    assistant_text: str = ""
-    text_block_id: str = field(default_factory=lambda: str(uuid.uuid4()))
-    text_started: bool = False
-    turn_prompt_tokens: int = 0
-    turn_completion_tokens: int = 0
-
-
-async def _baseline_llm_caller(
-    messages: list[dict[str, Any]],
-    tools: Sequence[Any],
-    *,
-    state: _BaselineStreamState,
-) -> LLMLoopResponse:
-    """Stream an OpenAI-compatible response and collect results.
-
-    Extracted from ``stream_chat_completion_baseline`` for readability.
-    """
-    state.pending_events.append(StreamStartStep())
-
-    round_text = ""
-    try:
-        client = _get_openai_client()
-        typed_messages = cast(list[ChatCompletionMessageParam], messages)
-        if tools:
-            typed_tools = cast(list[ChatCompletionToolParam], tools)
-            response = await client.chat.completions.create(
-                model=config.model,
-                messages=typed_messages,
-                tools=typed_tools,
-                stream=True,
-                stream_options={"include_usage": True},
-            )
-        else:
-            response = await client.chat.completions.create(
-                model=config.model,
-                messages=typed_messages,
-                stream=True,
-                stream_options={"include_usage": True},
-            )
-        tool_calls_by_index: dict[int, dict[str, str]] = {}
-
-        async for chunk in response:
-            if chunk.usage:
-                state.turn_prompt_tokens += chunk.usage.prompt_tokens or 0
-                state.turn_completion_tokens += chunk.usage.completion_tokens or 0
-
-            delta = chunk.choices[0].delta if chunk.choices else None
-            if not delta:
-                continue
-
-            if delta.content:
-                if not state.text_started:
-                    state.pending_events.append(StreamTextStart(id=state.text_block_id))
-                    state.text_started = True
-                round_text += delta.content
-                state.pending_events.append(
-                    StreamTextDelta(id=state.text_block_id, delta=delta.content)
-                )
-
-            if delta.tool_calls:
-                for tc in delta.tool_calls:
-                    idx = tc.index
-                    if idx not in tool_calls_by_index:
-                        tool_calls_by_index[idx] = {
-                            "id": "",
-                            "name": "",
-                            "arguments": "",
-                        }
-                    entry = tool_calls_by_index[idx]
-                    if tc.id:
-                        entry["id"] = tc.id
-                    if tc.function and tc.function.name:
-                        entry["name"] = tc.function.name
-                    if tc.function and tc.function.arguments:
-                        entry["arguments"] += tc.function.arguments
-
-        # Close text block
-        if state.text_started:
-            state.pending_events.append(StreamTextEnd(id=state.text_block_id))
-            state.text_started = False
-            state.text_block_id = str(uuid.uuid4())
-    finally:
-        # Always persist partial text so the session history stays consistent,
-        # even when the stream is interrupted by an exception.
-        state.assistant_text += round_text
-        # Always emit StreamFinishStep to match the StreamStartStep,
-        # even if an exception occurred during streaming.
-        state.pending_events.append(StreamFinishStep())
-
-    # Convert to shared format
-    llm_tool_calls = [
-        LLMToolCall(
-            id=tc["id"],
-            name=tc["name"],
-            arguments=tc["arguments"] or "{}",
-        )
-        for tc in tool_calls_by_index.values()
-    ]
-
-    return LLMLoopResponse(
-        response_text=round_text or None,
-        tool_calls=llm_tool_calls,
-        raw_response=None,  # Not needed for baseline conversation updater
-        prompt_tokens=0,  # Tracked via state accumulators
-        completion_tokens=0,
-    )
-
-
-async def _baseline_tool_executor(
-    tool_call: LLMToolCall,
-    tools: Sequence[Any],
-    *,
-    state: _BaselineStreamState,
-    user_id: str | None,
-    session: ChatSession,
-) -> ToolCallResult:
-    """Execute a tool via the copilot tool registry.
-
-    Extracted from ``stream_chat_completion_baseline`` for readability.
-    """
-    tool_call_id = tool_call.id
-    tool_name = tool_call.name
-    raw_args = tool_call.arguments or "{}"
-
-    try:
-        tool_args = orjson.loads(raw_args)
-    except orjson.JSONDecodeError as parse_err:
-        parse_error = f"Invalid JSON arguments for tool '{tool_name}': {parse_err}"
-        logger.warning("[Baseline] %s", parse_error)
-        state.pending_events.append(
-            StreamToolOutputAvailable(
-                toolCallId=tool_call_id,
-                toolName=tool_name,
-                output=parse_error,
-                success=False,
-            )
-        )
-        return ToolCallResult(
-            tool_call_id=tool_call_id,
-            tool_name=tool_name,
-            content=parse_error,
-            is_error=True,
-        )
-
-    state.pending_events.append(
-        StreamToolInputStart(toolCallId=tool_call_id, toolName=tool_name)
-    )
-    state.pending_events.append(
-        StreamToolInputAvailable(
-            toolCallId=tool_call_id,
-            toolName=tool_name,
-            input=tool_args,
-        )
-    )
-
-    try:
-        result: StreamToolOutputAvailable = await execute_tool(
-            tool_name=tool_name,
-            parameters=tool_args,
-            user_id=user_id,
-            session=session,
-            tool_call_id=tool_call_id,
-        )
-        state.pending_events.append(result)
-        tool_output = (
-            result.output if isinstance(result.output, str) else str(result.output)
-        )
-        return ToolCallResult(
-            tool_call_id=tool_call_id,
-            tool_name=tool_name,
-            content=tool_output,
-        )
-    except Exception as e:
-        error_output = f"Tool execution error: {e}"
-        logger.error(
-            "[Baseline] Tool %s failed: %s",
-            tool_name,
-            error_output,
-            exc_info=True,
-        )
-        state.pending_events.append(
-            StreamToolOutputAvailable(
-                toolCallId=tool_call_id,
-                toolName=tool_name,
-                output=error_output,
-                success=False,
-            )
-        )
-        return ToolCallResult(
-            tool_call_id=tool_call_id,
-            tool_name=tool_name,
-            content=error_output,
-            is_error=True,
-        )
-
-
-def _baseline_conversation_updater(
-    messages: list[dict[str, Any]],
-    response: LLMLoopResponse,
-    tool_results: list[ToolCallResult] | None = None,
-) -> None:
-    """Update OpenAI message list with assistant response + tool results.
-
-    Extracted from ``stream_chat_completion_baseline`` for readability.
-    """
-    if tool_results:
-        # Build assistant message with tool_calls
-        assistant_msg: dict[str, Any] = {"role": "assistant"}
-        if response.response_text:
-            assistant_msg["content"] = response.response_text
-        assistant_msg["tool_calls"] = [
-            {
-                "id": tc.id,
-                "type": "function",
-                "function": {"name": tc.name, "arguments": tc.arguments},
-            }
-            for tc in response.tool_calls
-        ]
-        messages.append(assistant_msg)
-        for tr in tool_results:
-            messages.append(
-                {
-                    "role": "tool",
-                    "tool_call_id": tr.tool_call_id,
-                    "content": tr.content,
-                }
-            )
-    else:
-        if response.response_text:
-            messages.append({"role": "assistant", "content": response.response_text})
-
-
 async def _update_title_async(
     session_id: str, message: str, user_id: str | None
 ) -> None:
@@ -473,32 +219,191 @@ async def stream_chat_completion_baseline(
     except Exception:
         logger.warning("[Baseline] Langfuse trace context setup failed")
 
+    assistant_text = ""
+    text_block_id = str(uuid.uuid4())
+    text_started = False
+    step_open = False
+    # Token usage accumulators — populated from streaming chunks
+    turn_prompt_tokens = 0
+    turn_completion_tokens = 0
     _stream_error = False  # Track whether an error occurred during streaming
-    state = _BaselineStreamState()
-
-    # Bind extracted module-level callbacks to this request's state/session
-    # using functools.partial so they satisfy the Protocol signatures.
-    _bound_llm_caller = partial(_baseline_llm_caller, state=state)
-    _bound_tool_executor = partial(
-        _baseline_tool_executor, state=state, user_id=user_id, session=session
-    )
-
     try:
-        loop_result = None
-        async for loop_result in tool_call_loop(
-            messages=openai_messages,
-            tools=tools,
-            llm_call=_bound_llm_caller,
-            execute_tool=_bound_tool_executor,
-            update_conversation=_baseline_conversation_updater,
-            max_iterations=_MAX_TOOL_ROUNDS,
-        ):
-            # Drain buffered events after each iteration (real-time streaming)
-            for evt in state.pending_events:
-                yield evt
-            state.pending_events.clear()
+        for _round in range(_MAX_TOOL_ROUNDS):
+            # Open a new step for each LLM round
+            yield StreamStartStep()
+            step_open = True
 
-        if loop_result and not loop_result.finished_naturally:
+            # Stream a response from the model
+            create_kwargs: dict[str, Any] = dict(
+                model=config.model,
+                messages=openai_messages,
+                stream=True,
+                stream_options={"include_usage": True},
+            )
+            if tools:
+                create_kwargs["tools"] = tools
+            response = await _get_openai_client().chat.completions.create(**create_kwargs)  # type: ignore[arg-type]  # dynamic kwargs
+
+            # Accumulate streamed response (text + tool calls)
+            round_text = ""
+            tool_calls_by_index: dict[int, dict[str, str]] = {}
+
+            async for chunk in response:
+                # Capture token usage from the streaming chunk.
+                # OpenRouter normalises all providers into OpenAI format
+                # where prompt_tokens already includes cached tokens
+                # (unlike Anthropic's native API). Use += to sum all
+                # tool-call rounds since each API call is independent.
+                # NOTE: stream_options={"include_usage": True} is not
+                # universally supported — some providers (Mistral, Llama
+                # via OpenRouter) always return chunk.usage=None. When
+                # that happens, tokens stay 0 and the tiktoken fallback
+                # below activates. Fail-open: one round is estimated.
+                if chunk.usage:
+                    turn_prompt_tokens += chunk.usage.prompt_tokens or 0
+                    turn_completion_tokens += chunk.usage.completion_tokens or 0
+
+                delta = chunk.choices[0].delta if chunk.choices else None
+                if not delta:
+                    continue
+
+                # Text content
+                if delta.content:
+                    if not text_started:
+                        yield StreamTextStart(id=text_block_id)
+                        text_started = True
+                    round_text += delta.content
+                    yield StreamTextDelta(id=text_block_id, delta=delta.content)
+
+                # Tool call fragments (streamed incrementally)
+                if delta.tool_calls:
+                    for tc in delta.tool_calls:
+                        idx = tc.index
+                        if idx not in tool_calls_by_index:
+                            tool_calls_by_index[idx] = {
+                                "id": "",
+                                "name": "",
+                                "arguments": "",
+                            }
+                        entry = tool_calls_by_index[idx]
+                        if tc.id:
+                            entry["id"] = tc.id
+                        if tc.function and tc.function.name:
+                            entry["name"] = tc.function.name
+                        if tc.function and tc.function.arguments:
+                            entry["arguments"] += tc.function.arguments
+
+            # Close text block if we had one this round
+            if text_started:
+                yield StreamTextEnd(id=text_block_id)
+                text_started = False
+                text_block_id = str(uuid.uuid4())
+
+            # Accumulate text for session persistence
+            assistant_text += round_text
+
+            # No tool calls -> model is done
+            if not tool_calls_by_index:
+                yield StreamFinishStep()
+                step_open = False
+                break
+
+            # Close step before tool execution
+            yield StreamFinishStep()
+            step_open = False
+
+            # Append the assistant message with tool_calls to context.
+            assistant_msg: dict[str, Any] = {"role": "assistant"}
+            if round_text:
+                assistant_msg["content"] = round_text
+            assistant_msg["tool_calls"] = [
+                {
+                    "id": tc["id"],
+                    "type": "function",
+                    "function": {
+                        "name": tc["name"],
+                        "arguments": tc["arguments"] or "{}",
+                    },
+                }
+                for tc in tool_calls_by_index.values()
+            ]
+            openai_messages.append(assistant_msg)
+
+            # Execute each tool call and stream events
+            for tc in tool_calls_by_index.values():
+                tool_call_id = tc["id"]
+                tool_name = tc["name"]
+                raw_args = tc["arguments"] or "{}"
+                try:
+                    tool_args = orjson.loads(raw_args)
+                except orjson.JSONDecodeError as parse_err:
+                    parse_error = (
+                        f"Invalid JSON arguments for tool '{tool_name}': {parse_err}"
+                    )
+                    logger.warning("[Baseline] %s", parse_error)
+                    yield StreamToolOutputAvailable(
+                        toolCallId=tool_call_id,
+                        toolName=tool_name,
+                        output=parse_error,
+                        success=False,
+                    )
+                    openai_messages.append(
+                        {
+                            "role": "tool",
+                            "tool_call_id": tool_call_id,
+                            "content": parse_error,
+                        }
+                    )
+                    continue
+
+                yield StreamToolInputStart(toolCallId=tool_call_id, toolName=tool_name)
+                yield StreamToolInputAvailable(
+                    toolCallId=tool_call_id,
+                    toolName=tool_name,
+                    input=tool_args,
+                )
+
+                # Execute via shared tool registry
+                try:
+                    result: StreamToolOutputAvailable = await execute_tool(
+                        tool_name=tool_name,
+                        parameters=tool_args,
+                        user_id=user_id,
+                        session=session,
+                        tool_call_id=tool_call_id,
+                    )
+                    yield result
+                    tool_output = (
+                        result.output
+                        if isinstance(result.output, str)
+                        else str(result.output)
+                    )
+                except Exception as e:
+                    error_output = f"Tool execution error: {e}"
+                    logger.error(
+                        "[Baseline] Tool %s failed: %s",
+                        tool_name,
+                        error_output,
+                        exc_info=True,
+                    )
+                    yield StreamToolOutputAvailable(
+                        toolCallId=tool_call_id,
+                        toolName=tool_name,
+                        output=error_output,
+                        success=False,
+                    )
+                    tool_output = error_output
+
+                # Append tool result to context for next round
+                openai_messages.append(
+                    {
+                        "role": "tool",
+                        "tool_call_id": tool_call_id,
+                        "content": tool_output,
+                    }
+                )
+        else:
+            # for-loop exhausted without break -> tool-round limit hit
             limit_msg = (
                 f"Exceeded {_MAX_TOOL_ROUNDS} tool-call rounds "
                 "without a final response."
@@ -513,28 +418,11 @@ async def stream_chat_completion_baseline(
         _stream_error = True
         error_msg = str(e) or type(e).__name__
         logger.error("[Baseline] Streaming error: %s", error_msg, exc_info=True)
-        # Close any open text block.  The llm_caller's finally block
-        # already appended StreamFinishStep to pending_events, so we must
-        # insert StreamTextEnd *before* StreamFinishStep to preserve the
-        # protocol ordering:
-        #   StreamStartStep -> StreamTextStart -> ...deltas... ->
-        #   StreamTextEnd -> StreamFinishStep
-        # Appending (or yielding directly) would place it after
-        # StreamFinishStep, violating the protocol.
-        if state.text_started:
-            # Find the last StreamFinishStep and insert before it.
-            insert_pos = len(state.pending_events)
-            for i in range(len(state.pending_events) - 1, -1, -1):
-                if isinstance(state.pending_events[i], StreamFinishStep):
-                    insert_pos = i
-                    break
-            state.pending_events.insert(
-                insert_pos, StreamTextEnd(id=state.text_block_id)
-            )
-        # Drain pending events in correct order
-        for evt in state.pending_events:
-            yield evt
-        state.pending_events.clear()
+        # Close any open text/step before emitting error
+        if text_started:
+            yield StreamTextEnd(id=text_block_id)
+        if step_open:
+            yield StreamFinishStep()
         yield StreamError(errorText=error_msg, code="baseline_error")
         # Still persist whatever we got
     finally:
@@ -554,21 +442,26 @@ async def stream_chat_completion_baseline(
         # Skip fallback when an error occurred and no output was produced —
         # charging rate-limit tokens for completely failed requests is unfair.
         if (
-            state.turn_prompt_tokens == 0
-            and state.turn_completion_tokens == 0
-            and not (_stream_error and not state.assistant_text)
+            turn_prompt_tokens == 0
+            and turn_completion_tokens == 0
+            and not (_stream_error and not assistant_text)
         ):
-            state.turn_prompt_tokens = max(
+            from backend.util.prompt import (
+                estimate_token_count,
+                estimate_token_count_str,
+            )
+
+            turn_prompt_tokens = max(
                 estimate_token_count(openai_messages, model=config.model), 1
             )
-            state.turn_completion_tokens = estimate_token_count_str(
-                state.assistant_text, model=config.model
+            turn_completion_tokens = estimate_token_count_str(
+                assistant_text, model=config.model
             )
             logger.info(
                 "[Baseline] No streaming usage reported; estimated tokens: "
                 "prompt=%d, completion=%d",
-                state.turn_prompt_tokens,
-                state.turn_completion_tokens,
+                turn_prompt_tokens,
+                turn_completion_tokens,
             )
 
         # Persist token usage to session and record for rate limiting.
@@ -578,15 +471,15 @@ async def stream_chat_completion_baseline(
         await persist_and_record_usage(
             session=session,
             user_id=user_id,
-            prompt_tokens=state.turn_prompt_tokens,
-            completion_tokens=state.turn_completion_tokens,
+            prompt_tokens=turn_prompt_tokens,
+            completion_tokens=turn_completion_tokens,
             log_prefix="[Baseline]",
         )
 
         # Persist assistant response
-        if state.assistant_text:
+        if assistant_text:
             session.messages.append(
-                ChatMessage(role="assistant", content=state.assistant_text)
+                ChatMessage(role="assistant", content=assistant_text)
             )
         try:
             await upsert_chat_session(session)
@@ -598,11 +491,11 @@ async def stream_chat_completion_baseline(
     # aclose() — doing so raises RuntimeError on client disconnect.
     # On GeneratorExit the client is already gone, so unreachable yields
     # are harmless; on normal completion they reach the SSE stream.
-    if state.turn_prompt_tokens > 0 or state.turn_completion_tokens > 0:
+    if turn_prompt_tokens > 0 or turn_completion_tokens > 0:
         yield StreamUsage(
-            prompt_tokens=state.turn_prompt_tokens,
-            completion_tokens=state.turn_completion_tokens,
-            total_tokens=state.turn_prompt_tokens + state.turn_completion_tokens,
+            prompt_tokens=turn_prompt_tokens,
+            completion_tokens=turn_completion_tokens,
+            total_tokens=turn_prompt_tokens + turn_completion_tokens,
         )
 
     yield StreamFinish()

autogpt_platform/backend/backend/copilot/config.py

@@ -91,20 +91,6 @@ class ChatConfig(BaseSettings):
         description="Max tokens per week, resets Monday 00:00 UTC (0 = unlimited)",
     )
 
-    # Cost (in credits / cents) to reset the daily rate limit using credits.
-    # When a user hits their daily limit, they can spend this amount to reset
-    # the daily counter and keep working.  Set to 0 to disable the feature.
-    rate_limit_reset_cost: int = Field(
-        default=500,
-        ge=0,
-        description="Credit cost (in cents) for resetting the daily rate limit. 0 = disabled.",
-    )
-    max_daily_resets: int = Field(
-        default=5,
-        ge=0,
-        description="Maximum number of credit-based rate limit resets per user per day. 0 = unlimited.",
-    )
-
     # Claude Agent SDK Configuration
     use_claude_agent_sdk: bool = Field(
         default=True,
@@ -129,22 +115,10 @@ class ChatConfig(BaseSettings):
         description="Use --resume for multi-turn conversations instead of "
         "history compression. Falls back to compression when unavailable.",
     )
-    use_openrouter: bool = Field(
-        default=True,
-        description="Enable routing API calls through the OpenRouter proxy. "
-        "The actual decision also requires ``api_key`` and ``base_url`` — "
-        "use the ``openrouter_active`` property for the final answer.",
-    )
     use_claude_code_subscription: bool = Field(
         default=False,
         description="For personal/dev use: use Claude Code CLI subscription auth instead of API keys. Requires `claude login` on the host. Only works with SDK mode.",
     )
-    test_mode: bool = Field(
-        default=False,
-        description="Use dummy service instead of real LLM calls. "
-        "Send __test_transient_error__, __test_fatal_error__, or "
-        "__test_slow_response__ to trigger specific scenarios.",
-    )
 
     # E2B Sandbox Configuration
     use_e2b_sandbox: bool = Field(
@@ -162,7 +136,7 @@ class ChatConfig(BaseSettings):
         description="E2B sandbox template to use for copilot sessions.",
     )
     e2b_sandbox_timeout: int = Field(
-        default=420,  # 7 min safety net — allows headroom for compaction retries
+        default=300,  # 5 min safety net — explicit per-turn pause is the primary mechanism
         description="E2B sandbox running-time timeout (seconds). "
         "E2B timeout is wall-clock (not idle). Explicit per-turn pause is the primary "
         "mechanism; this is the safety net.",
@@ -172,21 +146,6 @@ class ChatConfig(BaseSettings):
         description="E2B lifecycle action on timeout: 'pause' (default, free) or 'kill'.",
     )
 
-    @property
-    def openrouter_active(self) -> bool:
-        """True when OpenRouter is enabled AND credentials are usable.
-
-        Single source of truth for "will the SDK route through OpenRouter?".
-        Checks the flag *and* that ``api_key`` + a valid ``base_url`` are
-        present — mirrors the fallback logic in ``build_sdk_env``.
-        """
-        if not self.use_openrouter:
-            return False
-        base = (self.base_url or "").rstrip("/")
-        if base.endswith("/v1"):
-            base = base[:-3]
-        return bool(self.api_key and base and base.startswith("http"))
-
     @property
     def e2b_active(self) -> bool:
         """True when E2B is enabled and the API key is present.
@@ -209,6 +168,15 @@ class ChatConfig(BaseSettings):
         """
         return self.e2b_api_key if self.e2b_active else None
 
+    @field_validator("use_e2b_sandbox", mode="before")
+    @classmethod
+    def get_use_e2b_sandbox(cls, v):
+        """Get use_e2b_sandbox from environment if not provided."""
+        env_val = os.getenv("CHAT_USE_E2B_SANDBOX", "").lower()
+        if env_val:
+            return env_val in ("true", "1", "yes", "on")
+        return True if v is None else v
+
     @field_validator("e2b_api_key", mode="before")
     @classmethod
     def get_e2b_api_key(cls, v):
@@ -251,6 +219,26 @@ class ChatConfig(BaseSettings):
                 v = OPENROUTER_BASE_URL
         return v
 
+    @field_validator("use_claude_agent_sdk", mode="before")
+    @classmethod
+    def get_use_claude_agent_sdk(cls, v):
+        """Get use_claude_agent_sdk from environment if not provided."""
+        # Check environment variable - default to True if not set
+        env_val = os.getenv("CHAT_USE_CLAUDE_AGENT_SDK", "").lower()
+        if env_val:
+            return env_val in ("true", "1", "yes", "on")
+        # Default to True (SDK enabled by default)
+        return True if v is None else v
+
+    @field_validator("use_claude_code_subscription", mode="before")
+    @classmethod
+    def get_use_claude_code_subscription(cls, v):
+        """Get use_claude_code_subscription from environment if not provided."""
+        env_val = os.getenv("CHAT_USE_CLAUDE_CODE_SUBSCRIPTION", "").lower()
+        if env_val:
+            return env_val in ("true", "1", "yes", "on")
+        return False if v is None else v
+
     # Prompt paths for different contexts
     PROMPT_PATHS: dict[str, str] = {
         "default": "prompts/chat_system.md",
@@ -260,7 +248,6 @@ class ChatConfig(BaseSettings):
     class Config:
         """Pydantic config."""
 
-        env_prefix = "CHAT_"
         env_file = ".env"
         env_file_encoding = "utf-8"
         extra = "ignore"  # Ignore extra environment variables

autogpt_platform/backend/backend/copilot/config_test.py

@@ -6,70 +6,19 @@ from .config import ChatConfig
 
 # Env vars that the ChatConfig validators read — must be cleared so they don't
 # override the explicit constructor values we pass in each test.
-_ENV_VARS_TO_CLEAR = (
+_E2B_ENV_VARS = (
     "CHAT_USE_E2B_SANDBOX",
     "CHAT_E2B_API_KEY",
     "E2B_API_KEY",
-    "CHAT_USE_OPENROUTER",
-    "CHAT_API_KEY",
-    "OPEN_ROUTER_API_KEY",
-    "OPENAI_API_KEY",
-    "CHAT_BASE_URL",
-    "OPENROUTER_BASE_URL",
-    "OPENAI_BASE_URL",
 )
 
 
 @pytest.fixture(autouse=True)
-def _clean_env(monkeypatch: pytest.MonkeyPatch) -> None:
-    for var in _ENV_VARS_TO_CLEAR:
+def _clean_e2b_env(monkeypatch: pytest.MonkeyPatch) -> None:
+    for var in _E2B_ENV_VARS:
         monkeypatch.delenv(var, raising=False)
 
 
-class TestOpenrouterActive:
-    """Tests for the openrouter_active property."""
-
-    def test_enabled_with_credentials_returns_true(self):
-        cfg = ChatConfig(
-            use_openrouter=True,
-            api_key="or-key",
-            base_url="https://openrouter.ai/api/v1",
-        )
-        assert cfg.openrouter_active is True
-
-    def test_enabled_but_missing_api_key_returns_false(self):
-        cfg = ChatConfig(
-            use_openrouter=True,
-            api_key=None,
-            base_url="https://openrouter.ai/api/v1",
-        )
-        assert cfg.openrouter_active is False
-
-    def test_disabled_returns_false_despite_credentials(self):
-        cfg = ChatConfig(
-            use_openrouter=False,
-            api_key="or-key",
-            base_url="https://openrouter.ai/api/v1",
-        )
-        assert cfg.openrouter_active is False
-
-    def test_strips_v1_suffix_and_still_valid(self):
-        cfg = ChatConfig(
-            use_openrouter=True,
-            api_key="or-key",
-            base_url="https://openrouter.ai/api/v1",
-        )
-        assert cfg.openrouter_active is True
-
-    def test_invalid_base_url_returns_false(self):
-        cfg = ChatConfig(
-            use_openrouter=True,
-            api_key="or-key",
-            base_url="not-a-url",
-        )
-        assert cfg.openrouter_active is False
-
-
 class TestE2BActive:
     """Tests for the e2b_active property — single source of truth for E2B usage."""
 

autogpt_platform/backend/backend/copilot/constants.py

@@ -4,9 +4,6 @@
 # The hex suffix makes accidental LLM generation of these strings virtually
 # impossible, avoiding false-positive marker detection in normal conversation.
 COPILOT_ERROR_PREFIX = "[__COPILOT_ERROR_f7a1__]"  # Renders as ErrorCard
-COPILOT_RETRYABLE_ERROR_PREFIX = (
-    "[__COPILOT_RETRYABLE_ERROR_a9c2__]"  # ErrorCard + retry
-)
 COPILOT_SYSTEM_PREFIX = "[__COPILOT_SYSTEM_e3b0__]"  # Renders as system info message
 
 # Prefix for all synthetic IDs generated by CoPilot block execution.
@@ -38,24 +35,3 @@ def parse_node_id_from_exec_id(node_exec_id: str) -> str:
     Format: "{node_id}:{random_hex}" → returns "{node_id}".
     """
     return node_exec_id.rsplit(COPILOT_NODE_EXEC_ID_SEPARATOR, 1)[0]
-
-
-# ---------------------------------------------------------------------------
-# Transient Anthropic API error detection
-# ---------------------------------------------------------------------------
-# Patterns in error text that indicate a transient Anthropic API error
-# (ECONNRESET / dropped TCP connection) which is retryable.
-_TRANSIENT_ERROR_PATTERNS = (
-    "socket connection was closed unexpectedly",
-    "ECONNRESET",
-    "connection was forcibly closed",
-    "network socket disconnected",
-)
-
-FRIENDLY_TRANSIENT_MSG = "Anthropic connection interrupted — please retry"
-
-
-def is_transient_api_error(error_text: str) -> bool:
-    """Return True if *error_text* matches a known transient Anthropic API error."""
-    lower = error_text.lower()
-    return any(pat.lower() in lower for pat in _TRANSIENT_ERROR_PATTERNS)

autogpt_platform/backend/backend/copilot/context.py

@@ -17,20 +17,8 @@ from backend.util.workspace import WorkspaceManager
 if TYPE_CHECKING:
     from e2b import AsyncSandbox
 
-    from backend.copilot.permissions import CopilotPermissions
-
-
-# Allowed base directory for the Read tool.  Public so service.py can use it
-# for sweep operations without depending on a private implementation detail.
-# Respects CLAUDE_CONFIG_DIR env var, consistent with transcript.py's
-# _projects_base() function.
-_config_dir = os.environ.get("CLAUDE_CONFIG_DIR") or os.path.expanduser("~/.claude")
-SDK_PROJECTS_DIR = os.path.realpath(os.path.join(_config_dir, "projects"))
-
-# Compiled UUID pattern for validating conversation directory names.
-# Kept as a module-level constant so the security-relevant pattern is easy
-# to audit in one place and avoids recompilation on every call.
-_UUID_RE = re.compile(r"^[0-9a-f]{8}(?:-[0-9a-f]{4}){3}-[0-9a-f]{12}$", re.IGNORECASE)
+# Allowed base directory for the Read tool.
+_SDK_PROJECTS_DIR = os.path.realpath(os.path.expanduser("~/.claude/projects"))
 
 # Encoded project-directory name for the current session (e.g.
 # "-private-tmp-copilot-<uuid>").  Set by set_execution_context() so path
@@ -46,33 +34,17 @@ _current_sandbox: ContextVar["AsyncSandbox | None"] = ContextVar(
 )
 _current_sdk_cwd: ContextVar[str] = ContextVar("_current_sdk_cwd", default="")
 
-# Current execution's capability filter.  None means "no restrictions".
-# Set by set_execution_context(); read by run_block and service.py.
-_current_permissions: "ContextVar[CopilotPermissions | None]" = ContextVar(
-    "_current_permissions", default=None
-)
 
-
-def encode_cwd_for_cli(cwd: str) -> str:
-    """Encode a working directory path the same way the Claude CLI does.
-
-    The Claude CLI encodes the absolute cwd as a directory name by replacing
-    every non-alphanumeric character with ``-``.  For example
-    ``/tmp/copilot-abc`` becomes ``-tmp-copilot-abc``.
-    """
+def _encode_cwd_for_cli(cwd: str) -> str:
+    """Encode a working directory path the same way the Claude CLI does."""
     return re.sub(r"[^a-zA-Z0-9]", "-", os.path.realpath(cwd))
 
 
-# Keep the private alias for internal callers (backwards compat).
-_encode_cwd_for_cli = encode_cwd_for_cli
-
-
 def set_execution_context(
     user_id: str | None,
     session: ChatSession,
     sandbox: "AsyncSandbox | None" = None,
     sdk_cwd: str | None = None,
-    permissions: "CopilotPermissions | None" = None,
 ) -> None:
     """Set per-turn context variables used by file-resolution tool handlers."""
     _current_user_id.set(user_id)
@@ -80,7 +52,6 @@ def set_execution_context(
     _current_sandbox.set(sandbox)
     _current_sdk_cwd.set(sdk_cwd or "")
     _current_project_dir.set(_encode_cwd_for_cli(sdk_cwd) if sdk_cwd else "")
-    _current_permissions.set(permissions)
 
 
 def get_execution_context() -> tuple[str | None, ChatSession | None]:
@@ -88,11 +59,6 @@ def get_execution_context() -> tuple[str | None, ChatSession | None]:
     return _current_user_id.get(), _current_session.get()
 
 
-def get_current_permissions() -> "CopilotPermissions | None":
-    """Return the capability filter for the current execution, or None if unrestricted."""
-    return _current_permissions.get()
-
-
 def get_current_sandbox() -> "AsyncSandbox | None":
     """Return the E2B sandbox for the current session, or None if not active."""
     return _current_sandbox.get()
@@ -104,32 +70,17 @@ def get_sdk_cwd() -> str:
 
 
 E2B_WORKDIR = "/home/user"
-E2B_ALLOWED_DIRS: tuple[str, ...] = (E2B_WORKDIR, "/tmp")
-E2B_ALLOWED_DIRS_STR: str = " or ".join(E2B_ALLOWED_DIRS)
-
-
-def is_within_allowed_dirs(path: str) -> bool:
-    """Return True if *path* is within one of the allowed sandbox directories."""
-    for allowed in E2B_ALLOWED_DIRS:
-        if path == allowed or path.startswith(allowed + "/"):
-            return True
-    return False
 
 
 def resolve_sandbox_path(path: str) -> str:
-    """Normalise *path* to an absolute sandbox path under an allowed directory.
-
-    Allowed directories: ``/home/user`` and ``/tmp``.
-    Relative paths are resolved against ``/home/user``.
+    """Normalise *path* to an absolute sandbox path under ``/home/user``.
 
     Raises :class:`ValueError` if the resolved path escapes the sandbox.
     """
     candidate = path if os.path.isabs(path) else os.path.join(E2B_WORKDIR, path)
     normalized = os.path.normpath(candidate)
-    if not is_within_allowed_dirs(normalized):
-        raise ValueError(
-            f"Path must be within {E2B_ALLOWED_DIRS_STR}: {os.path.basename(path)}"
-        )
+    if normalized != E2B_WORKDIR and not normalized.startswith(E2B_WORKDIR + "/"):
+        raise ValueError(f"Path must be within {E2B_WORKDIR}: {path}")
     return normalized
 
 
@@ -149,9 +100,7 @@ def is_allowed_local_path(path: str, sdk_cwd: str | None = None) -> bool:
 
     Allowed:
     - Files under *sdk_cwd* (``/tmp/copilot-<session>/``)
-    - Files under ``~/.claude/projects/<encoded-cwd>/<uuid>/tool-results/...``.
-      The SDK nests tool-results under a conversation UUID directory;
-      the UUID segment is validated with ``_UUID_RE``.
+    - Files under ``~/.claude/projects/<encoded-cwd>/tool-results/`` (SDK tool-results)
     """
     if not path:
         return False
@@ -170,22 +119,10 @@ def is_allowed_local_path(path: str, sdk_cwd: str | None = None) -> bool:
 
     encoded = _current_project_dir.get("")
     if encoded:
-        project_dir = os.path.realpath(os.path.join(SDK_PROJECTS_DIR, encoded))
-        # Defence-in-depth: ensure project_dir didn't escape the base.
-        if not project_dir.startswith(SDK_PROJECTS_DIR + os.sep):
-            return False
-        # Only allow: <encoded-cwd>/<uuid>/tool-results/<file>
-        # The SDK always creates a conversation UUID directory between
-        # the project dir and tool-results/.
-        if resolved.startswith(project_dir + os.sep):
-            relative = resolved[len(project_dir) + 1 :]
-            parts = relative.split(os.sep)
-            # Require exactly: [<uuid>, "tool-results", <file>, ...]
-            if (
-                len(parts) >= 3
-                and _UUID_RE.match(parts[0])
-                and parts[1] == "tool-results"
-            ):
-                return True
+        tool_results_dir = os.path.join(_SDK_PROJECTS_DIR, encoded, "tool-results")
+        if resolved == tool_results_dir or resolved.startswith(
+            tool_results_dir + os.sep
+        ):
+            return True
 
     return False

autogpt_platform/backend/backend/copilot/context_test.py

@@ -9,9 +9,8 @@ from unittest.mock import MagicMock
 import pytest
 
 from backend.copilot.context import (
-    SDK_PROJECTS_DIR,
+    _SDK_PROJECTS_DIR,
     _current_project_dir,
-    get_current_permissions,
     get_current_sandbox,
     get_execution_context,
     get_sdk_cwd,
@@ -19,7 +18,6 @@ from backend.copilot.context import (
     resolve_sandbox_path,
     set_execution_context,
 )
-from backend.copilot.permissions import CopilotPermissions
 
 
 def _make_session() -> MagicMock:
@@ -63,19 +61,6 @@ def test_get_current_sandbox_returns_set_value():
     assert get_current_sandbox() is mock_sandbox
 
 
-def test_set_and_get_current_permissions():
-    """set_execution_context stores permissions; get_current_permissions returns it."""
-    perms = CopilotPermissions(tools=["run_block"], tools_exclude=False)
-    set_execution_context("u1", _make_session(), permissions=perms)
-    assert get_current_permissions() is perms
-
-
-def test_get_current_permissions_defaults_to_none():
-    """get_current_permissions returns None when no permissions have been set."""
-    set_execution_context("u1", _make_session())
-    assert get_current_permissions() is None
-
-
 def test_get_sdk_cwd_empty_when_not_set():
     """get_sdk_cwd returns empty string when sdk_cwd is not set."""
     set_execution_context("u1", _make_session(), sdk_cwd=None)
@@ -119,13 +104,11 @@ def test_is_allowed_local_path_no_sdk_cwd_no_project_dir():
     assert not is_allowed_local_path("/tmp/some-file.txt", sdk_cwd=None)
 
 
-def test_is_allowed_local_path_tool_results_with_uuid():
-    """Files under <encoded-cwd>/<uuid>/tool-results/ are allowed."""
+def test_is_allowed_local_path_tool_results_dir():
+    """Files under the tool-results directory for the current project are allowed."""
     encoded = "test-encoded-dir"
-    conv_uuid = "a1b2c3d4-e5f6-7890-abcd-ef1234567890"
-    path = os.path.join(
-        SDK_PROJECTS_DIR, encoded, conv_uuid, "tool-results", "output.txt"
-    )
+    tool_results_dir = os.path.join(_SDK_PROJECTS_DIR, encoded, "tool-results")
+    path = os.path.join(tool_results_dir, "output.txt")
 
     _current_project_dir.set(encoded)
     try:
@@ -134,22 +117,10 @@ def test_is_allowed_local_path_tool_results_with_uuid():
         _current_project_dir.set("")
 
 
-def test_is_allowed_local_path_tool_results_without_uuid_rejected():
-    """Direct <encoded-cwd>/tool-results/ (no UUID) is rejected."""
-    encoded = "test-encoded-dir"
-    path = os.path.join(SDK_PROJECTS_DIR, encoded, "tool-results", "output.txt")
-
-    _current_project_dir.set(encoded)
-    try:
-        assert not is_allowed_local_path(path, sdk_cwd=None)
-    finally:
-        _current_project_dir.set("")
-
-
 def test_is_allowed_local_path_sibling_of_tool_results_is_rejected():
     """A path adjacent to tool-results/ but not inside it is rejected."""
     encoded = "test-encoded-dir"
-    sibling_path = os.path.join(SDK_PROJECTS_DIR, encoded, "other-dir", "file.txt")
+    sibling_path = os.path.join(_SDK_PROJECTS_DIR, encoded, "other-dir", "file.txt")
 
     _current_project_dir.set(encoded)
     try:
@@ -158,21 +129,6 @@ def test_is_allowed_local_path_sibling_of_tool_results_is_rejected():
         _current_project_dir.set("")
 
 
-def test_is_allowed_local_path_valid_uuid_wrong_segment_name_rejected():
-    """A valid UUID dir but non-'tool-results' second segment is rejected."""
-    encoded = "test-encoded-dir"
-    uuid_str = "12345678-1234-5678-9abc-def012345678"
-    path = os.path.join(
-        SDK_PROJECTS_DIR, encoded, uuid_str, "not-tool-results", "output.txt"
-    )
-
-    _current_project_dir.set(encoded)
-    try:
-        assert not is_allowed_local_path(path, sdk_cwd=None)
-    finally:
-        _current_project_dir.set("")
-
-
 # ---------------------------------------------------------------------------
 # resolve_sandbox_path
 # ---------------------------------------------------------------------------
@@ -198,32 +154,10 @@ def test_resolve_sandbox_path_normalizes_dots():
 
 
 def test_resolve_sandbox_path_escape_raises():
-    with pytest.raises(ValueError, match="must be within"):
+    with pytest.raises(ValueError, match="/home/user"):
         resolve_sandbox_path("/home/user/../../etc/passwd")
 
 
 def test_resolve_sandbox_path_absolute_outside_raises():
-    with pytest.raises(ValueError):
+    with pytest.raises(ValueError, match="/home/user"):
         resolve_sandbox_path("/etc/passwd")
-
-
-def test_resolve_sandbox_path_tmp_allowed():
-    assert resolve_sandbox_path("/tmp/data.txt") == "/tmp/data.txt"
-
-
-def test_resolve_sandbox_path_tmp_nested():
-    assert resolve_sandbox_path("/tmp/a/b/c.txt") == "/tmp/a/b/c.txt"
-
-
-def test_resolve_sandbox_path_tmp_itself():
-    assert resolve_sandbox_path("/tmp") == "/tmp"
-
-
-def test_resolve_sandbox_path_tmp_escape_raises():
-    with pytest.raises(ValueError):
-        resolve_sandbox_path("/tmp/../etc/passwd")
-
-
-def test_resolve_sandbox_path_tmp_prefix_collision_raises():
-    with pytest.raises(ValueError):
-        resolve_sandbox_path("/tmp_evil/malicious.txt")

autogpt_platform/backend/backend/copilot/db.py

@@ -18,7 +18,7 @@ from prisma.types import (
 from backend.data import db
 from backend.util.json import SafeJson, sanitize_string
 
-from .model import ChatMessage, ChatSession, ChatSessionInfo, invalidate_session_cache
+from .model import ChatMessage, ChatSession, ChatSessionInfo
 
 logger = logging.getLogger(__name__)
 
@@ -217,9 +217,6 @@ async def add_chat_messages_batch(
                     if msg.get("function_call") is not None:
                         data["functionCall"] = SafeJson(msg["function_call"])
 
-                    if msg.get("duration_ms") is not None:
-                        data["durationMs"] = msg["duration_ms"]
-
                     messages_data.append(data)
 
                 # Run create_many and session update in parallel within transaction
@@ -362,22 +359,3 @@ async def update_tool_message_content(
             f"tool_call_id {tool_call_id}: {e}"
         )
         return False
-
-
-async def set_turn_duration(session_id: str, duration_ms: int) -> None:
-    """Set durationMs on the last assistant message in a session.
-
-    Also invalidates the Redis session cache so the next GET returns
-    the updated duration.
-    """
-    last_msg = await PrismaChatMessage.prisma().find_first(
-        where={"sessionId": session_id, "role": "assistant"},
-        order={"sequence": "desc"},
-    )
-    if last_msg:
-        await PrismaChatMessage.prisma().update(
-            where={"id": last_msg.id},
-            data={"durationMs": duration_ms},
-        )
-        # Invalidate cache so the session is re-fetched from DB with durationMs
-        await invalidate_session_cache(session_id)

autogpt_platform/backend/backend/copilot/executor/processor.py

@@ -14,16 +14,14 @@ import time
 from backend.copilot import stream_registry
 from backend.copilot.baseline import stream_chat_completion_baseline
 from backend.copilot.config import ChatConfig
-from backend.copilot.response_model import StreamError
+from backend.copilot.response_model import StreamFinish
 from backend.copilot.sdk import service as sdk_service
-from backend.copilot.sdk.dummy import stream_chat_completion_dummy
 from backend.executor.cluster_lock import ClusterLock
 from backend.util.decorator import error_logged
 from backend.util.feature_flag import Flag, is_feature_enabled
 from backend.util.logging import TruncatedLogger, configure_logging
 from backend.util.process import set_service_name
 from backend.util.retry import func_retry
-from backend.util.workspace_storage import shutdown_workspace_storage
 
 from .utils import CoPilotExecutionEntry, CoPilotLogMetadata
 
@@ -154,6 +152,8 @@ class CoPilotProcessor:
         worker's event loop, ensuring ``aiohttp.ClientSession.close()``
         runs on the same loop that created the session.
         """
+        from backend.util.workspace_storage import shutdown_workspace_storage
+
         coro = shutdown_workspace_storage()
         try:
             future = asyncio.run_coroutine_threadsafe(coro, self.execution_loop)
@@ -246,58 +246,48 @@ class CoPilotProcessor:
             # Choose service based on LaunchDarkly flag.
             # Claude Code subscription forces SDK mode (CLI subprocess auth).
             config = ChatConfig()
-
-            if config.test_mode:
-                stream_fn = stream_chat_completion_dummy
-                log.warning("Using DUMMY service (CHAT_TEST_MODE=true)")
-            else:
-                use_sdk = (
-                    config.use_claude_code_subscription
-                    or await is_feature_enabled(
-                        Flag.COPILOT_SDK,
-                        entry.user_id or "anonymous",
-                        default=config.use_claude_agent_sdk,
-                    )
-                )
-                stream_fn = (
-                    sdk_service.stream_chat_completion_sdk
-                    if use_sdk
-                    else stream_chat_completion_baseline
-                )
-                log.info(f"Using {'SDK' if use_sdk else 'baseline'} service")
+            use_sdk = config.use_claude_code_subscription or await is_feature_enabled(
+                Flag.COPILOT_SDK,
+                entry.user_id or "anonymous",
+                default=config.use_claude_agent_sdk,
+            )
+            stream_fn = (
+                sdk_service.stream_chat_completion_sdk
+                if use_sdk
+                else stream_chat_completion_baseline
+            )
+            log.info(f"Using {'SDK' if use_sdk else 'baseline'} service")
 
             # Stream chat completion and publish chunks to Redis.
-            # stream_and_publish wraps the raw stream with registry
-            # publishing (shared with collect_copilot_response).
-            raw_stream = stream_fn(
+            async for chunk in stream_fn(
                 session_id=entry.session_id,
                 message=entry.message if entry.message else None,
                 is_user_message=entry.is_user_message,
                 user_id=entry.user_id,
                 context=entry.context,
                 file_ids=entry.file_ids,
-            )
-            async for chunk in stream_registry.stream_and_publish(
-                session_id=entry.session_id,
-                turn_id=entry.turn_id,
-                stream=raw_stream,
             ):
                 if cancel.is_set():
                     log.info("Cancel requested, breaking stream")
                     break
 
-                # Capture StreamError so mark_session_completed receives
-                # the error message (stream_and_publish yields but does
-                # not publish StreamError — that's done by mark_session_completed).
-                if isinstance(chunk, StreamError):
-                    error_msg = chunk.errorText
-                    break
-
                 current_time = time.monotonic()
                 if current_time - last_refresh >= refresh_interval:
                     cluster_lock.refresh()
                     last_refresh = current_time
 
+                # Skip StreamFinish — mark_session_completed publishes it.
+                if isinstance(chunk, StreamFinish):
+                    continue
+
+                try:
+                    await stream_registry.publish_chunk(entry.turn_id, chunk)
+                except Exception as e:
+                    log.error(
+                        f"Error publishing chunk {type(chunk).__name__}: {e}",
+                        exc_info=True,
+                    )
+
             # Stream loop completed
             if cancel.is_set():
                 log.info("Stream cancelled by user")

autogpt_platform/backend/backend/copilot/integration_creds.py

@@ -1,173 +0,0 @@
-"""Integration credential lookup with per-process TTL cache.
-
-Provides token retrieval for connected integrations so that copilot tools
-(e.g. bash_exec) can inject auth tokens into the execution environment without
-hitting the database on every command.
-
-Cache semantics (handled automatically by TTLCache):
-- Token found → cached for _TOKEN_CACHE_TTL (5 min).  Avoids repeated DB hits
-  for users who have credentials and are running many bash commands.
-- No credentials found → cached for _NULL_CACHE_TTL (60 s).  Avoids a DB hit
-  on every E2B command for users who haven't connected an account yet, while
-  still picking up a newly-connected account within one minute.
-
-Both caches are bounded to _CACHE_MAX_SIZE entries; cachetools evicts the
-least-recently-used entry when the limit is reached.
-
-Multi-worker note: both caches are in-process only.  Each worker/replica
-maintains its own independent cache, so a credential fetch may be duplicated
-across processes.  This is acceptable for the current goal (reduce DB hits per
-session per-process), but if cache efficiency across replicas becomes important
-a shared cache (e.g. Redis) should be used instead.
-"""
-
-import logging
-from typing import cast
-
-from cachetools import TTLCache
-
-from backend.copilot.providers import SUPPORTED_PROVIDERS
-from backend.data.model import APIKeyCredentials, OAuth2Credentials
-from backend.integrations.creds_manager import (
-    IntegrationCredentialsManager,
-    register_creds_changed_hook,
-)
-
-logger = logging.getLogger(__name__)
-
-# Derived from the single SUPPORTED_PROVIDERS registry for backward compat.
-PROVIDER_ENV_VARS: dict[str, list[str]] = {
-    slug: entry["env_vars"] for slug, entry in SUPPORTED_PROVIDERS.items()
-}
-
-_TOKEN_CACHE_TTL = 300.0  # seconds — for found tokens
-_NULL_CACHE_TTL = 60.0  # seconds — for "not connected" results
-_CACHE_MAX_SIZE = 10_000
-
-# (user_id, provider) → token string.  TTLCache handles expiry + eviction.
-# Thread-safety note: TTLCache is NOT thread-safe, but that is acceptable here
-# because all callers (get_provider_token, invalidate_user_provider_cache) run
-# exclusively on the asyncio event loop.  There are no await points between a
-# cache read and its corresponding write within any function, so no concurrent
-# coroutine can interleave.  If ThreadPoolExecutor workers are ever added to
-# this path, a threading.RLock should be wrapped around these caches.
-_token_cache: TTLCache[tuple[str, str], str] = TTLCache(
-    maxsize=_CACHE_MAX_SIZE, ttl=_TOKEN_CACHE_TTL
-)
-# Separate cache for "no credentials" results with a shorter TTL.
-_null_cache: TTLCache[tuple[str, str], bool] = TTLCache(
-    maxsize=_CACHE_MAX_SIZE, ttl=_NULL_CACHE_TTL
-)
-
-
-def invalidate_user_provider_cache(user_id: str, provider: str) -> None:
-    """Remove the cached entry for *user_id*/*provider* from both caches.
-
-    Call this after storing new credentials so that the next
-    ``get_provider_token()`` call performs a fresh DB lookup instead of
-    serving a stale TTL-cached result.
-    """
-    key = (user_id, provider)
-    _token_cache.pop(key, None)
-    _null_cache.pop(key, None)
-
-
-# Register this module's cache-bust function with the credentials manager so
-# that any create/update/delete operation immediately evicts stale cache
-# entries.  This avoids a lazy import inside creds_manager and eliminates the
-# circular-import risk.
-try:
-    register_creds_changed_hook(invalidate_user_provider_cache)
-except RuntimeError:
-    # Hook already registered (e.g. module re-import in tests).
-    pass
-
-# Module-level singleton to avoid re-instantiating IntegrationCredentialsManager
-# on every cache-miss call to get_provider_token().
-_manager = IntegrationCredentialsManager()
-
-
-async def get_provider_token(user_id: str, provider: str) -> str | None:
-    """Return the user's access token for *provider*, or ``None`` if not connected.
-
-    OAuth2 tokens are preferred (refreshed if needed); API keys are the fallback.
-    Found tokens are cached for _TOKEN_CACHE_TTL (5 min).  "Not connected" results
-    are cached for _NULL_CACHE_TTL (60 s) to avoid a DB hit on every bash_exec
-    command for users who haven't connected yet, while still picking up a
-    newly-connected account within one minute.
-    """
-    cache_key = (user_id, provider)
-
-    if cache_key in _null_cache:
-        return None
-    if cached := _token_cache.get(cache_key):
-        return cached
-
-    manager = _manager
-    try:
-        creds_list = await manager.store.get_creds_by_provider(user_id, provider)
-    except Exception:
-        logger.warning(
-            "Failed to fetch %s credentials for user %s",
-            provider,
-            user_id,
-            exc_info=True,
-        )
-        return None
-
-    # Pass 1: prefer OAuth2 (carry scope info, refreshable via token endpoint).
-    # Sort so broader-scoped tokens come first: a token with "repo" scope covers
-    # full git access, while a public-data-only token lacks push/pull permission.
-    # lock=False — background injection; not worth a distributed lock acquisition.
-    oauth2_creds = sorted(
-        [c for c in creds_list if c.type == "oauth2"],
-        key=lambda c: 0 if "repo" in (cast(OAuth2Credentials, c).scopes or []) else 1,
-    )
-    for creds in oauth2_creds:
-        if creds.type == "oauth2":
-            try:
-                fresh = await manager.refresh_if_needed(
-                    user_id, cast(OAuth2Credentials, creds), lock=False
-                )
-                token = fresh.access_token.get_secret_value()
-            except Exception:
-                logger.warning(
-                    "Failed to refresh %s OAuth token for user %s; "
-                    "discarding stale token to force re-auth",
-                    provider,
-                    user_id,
-                    exc_info=True,
-                )
-                # Do NOT fall back to the stale token — it is likely expired
-                # or revoked.  Returning None forces the caller to re-auth,
-                # preventing the LLM from receiving a non-functional token.
-                continue
-            _token_cache[cache_key] = token
-            return token
-
-    # Pass 2: fall back to API key (no expiry, no refresh needed).
-    for creds in creds_list:
-        if creds.type == "api_key":
-            token = cast(APIKeyCredentials, creds).api_key.get_secret_value()
-            _token_cache[cache_key] = token
-            return token
-
-    # No credentials found — cache to avoid repeated DB hits.
-    _null_cache[cache_key] = True
-    return None
-
-
-async def get_integration_env_vars(user_id: str) -> dict[str, str]:
-    """Return env vars for all providers the user has connected.
-
-    Iterates :data:`PROVIDER_ENV_VARS`, fetches each token, and builds a flat
-    ``{env_var: token}`` dict ready to pass to a subprocess or E2B sandbox.
-    Only providers with a stored credential contribute entries.
-    """
-    env: dict[str, str] = {}
-    for provider, var_names in PROVIDER_ENV_VARS.items():
-        token = await get_provider_token(user_id, provider)
-        if token:
-            for var in var_names:
-                env[var] = token
-    return env

autogpt_platform/backend/backend/copilot/integration_creds_test.py

@@ -1,195 +0,0 @@
-"""Tests for integration_creds — TTL cache and token lookup paths."""
-
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import pytest
-from pydantic import SecretStr
-
-from backend.copilot.integration_creds import (
-    _NULL_CACHE_TTL,
-    _TOKEN_CACHE_TTL,
-    PROVIDER_ENV_VARS,
-    _null_cache,
-    _token_cache,
-    get_integration_env_vars,
-    get_provider_token,
-    invalidate_user_provider_cache,
-)
-from backend.data.model import APIKeyCredentials, OAuth2Credentials
-
-_USER = "user-integration-creds-test"
-_PROVIDER = "github"
-
-
-def _make_api_key_creds(key: str = "test-api-key") -> APIKeyCredentials:
-    return APIKeyCredentials(
-        id="creds-api-key",
-        provider=_PROVIDER,
-        api_key=SecretStr(key),
-        title="Test API Key",
-        expires_at=None,
-    )
-
-
-def _make_oauth2_creds(token: str = "test-oauth-token") -> OAuth2Credentials:
-    return OAuth2Credentials(
-        id="creds-oauth2",
-        provider=_PROVIDER,
-        title="Test OAuth",
-        access_token=SecretStr(token),
-        refresh_token=SecretStr("test-refresh"),
-        access_token_expires_at=None,
-        refresh_token_expires_at=None,
-        scopes=[],
-    )
-
-
-@pytest.fixture(autouse=True)
-def clear_caches():
-    """Ensure clean caches before and after every test."""
-    _token_cache.clear()
-    _null_cache.clear()
-    yield
-    _token_cache.clear()
-    _null_cache.clear()
-
-
-class TestInvalidateUserProviderCache:
-    def test_removes_token_entry(self):
-        key = (_USER, _PROVIDER)
-        _token_cache[key] = "tok"
-        invalidate_user_provider_cache(_USER, _PROVIDER)
-        assert key not in _token_cache
-
-    def test_removes_null_entry(self):
-        key = (_USER, _PROVIDER)
-        _null_cache[key] = True
-        invalidate_user_provider_cache(_USER, _PROVIDER)
-        assert key not in _null_cache
-
-    def test_noop_when_key_not_cached(self):
-        # Should not raise even when there is no cache entry.
-        invalidate_user_provider_cache("no-such-user", _PROVIDER)
-
-    def test_only_removes_targeted_key(self):
-        other_key = ("other-user", _PROVIDER)
-        _token_cache[other_key] = "other-tok"
-        invalidate_user_provider_cache(_USER, _PROVIDER)
-        assert other_key in _token_cache
-
-
-class TestGetProviderToken:
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_returns_cached_token_without_db_hit(self):
-        _token_cache[(_USER, _PROVIDER)] = "cached-tok"
-
-        mock_manager = MagicMock()
-        with patch("backend.copilot.integration_creds._manager", mock_manager):
-            result = await get_provider_token(_USER, _PROVIDER)
-
-        assert result == "cached-tok"
-        mock_manager.store.get_creds_by_provider.assert_not_called()
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_returns_none_for_null_cached_provider(self):
-        _null_cache[(_USER, _PROVIDER)] = True
-
-        mock_manager = MagicMock()
-        with patch("backend.copilot.integration_creds._manager", mock_manager):
-            result = await get_provider_token(_USER, _PROVIDER)
-
-        assert result is None
-        mock_manager.store.get_creds_by_provider.assert_not_called()
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_api_key_creds_returned_and_cached(self):
-        api_creds = _make_api_key_creds("my-api-key")
-        mock_manager = MagicMock()
-        mock_manager.store.get_creds_by_provider = AsyncMock(return_value=[api_creds])
-
-        with patch("backend.copilot.integration_creds._manager", mock_manager):
-            result = await get_provider_token(_USER, _PROVIDER)
-
-        assert result == "my-api-key"
-        assert _token_cache.get((_USER, _PROVIDER)) == "my-api-key"
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_oauth2_preferred_over_api_key(self):
-        oauth_creds = _make_oauth2_creds("oauth-tok")
-        api_creds = _make_api_key_creds("api-tok")
-        mock_manager = MagicMock()
-        mock_manager.store.get_creds_by_provider = AsyncMock(
-            return_value=[api_creds, oauth_creds]
-        )
-        mock_manager.refresh_if_needed = AsyncMock(return_value=oauth_creds)
-
-        with patch("backend.copilot.integration_creds._manager", mock_manager):
-            result = await get_provider_token(_USER, _PROVIDER)
-
-        assert result == "oauth-tok"
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_oauth2_refresh_failure_returns_none(self):
-        """On refresh failure, return None instead of caching a stale token."""
-        oauth_creds = _make_oauth2_creds("stale-oauth-tok")
-        mock_manager = MagicMock()
-        mock_manager.store.get_creds_by_provider = AsyncMock(return_value=[oauth_creds])
-        mock_manager.refresh_if_needed = AsyncMock(side_effect=RuntimeError("network"))
-
-        with patch("backend.copilot.integration_creds._manager", mock_manager):
-            result = await get_provider_token(_USER, _PROVIDER)
-
-        # Stale tokens must NOT be returned — forces re-auth.
-        assert result is None
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_no_credentials_caches_null_entry(self):
-        mock_manager = MagicMock()
-        mock_manager.store.get_creds_by_provider = AsyncMock(return_value=[])
-
-        with patch("backend.copilot.integration_creds._manager", mock_manager):
-            result = await get_provider_token(_USER, _PROVIDER)
-
-        assert result is None
-        assert _null_cache.get((_USER, _PROVIDER)) is True
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_db_exception_returns_none_without_caching(self):
-        mock_manager = MagicMock()
-        mock_manager.store.get_creds_by_provider = AsyncMock(
-            side_effect=RuntimeError("db down")
-        )
-
-        with patch("backend.copilot.integration_creds._manager", mock_manager):
-            result = await get_provider_token(_USER, _PROVIDER)
-
-        assert result is None
-        # DB errors are not cached — next call will retry
-        assert (_USER, _PROVIDER) not in _token_cache
-        assert (_USER, _PROVIDER) not in _null_cache
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_null_cache_has_shorter_ttl_than_token_cache(self):
-        """Verify the TTL constants are set correctly for each cache."""
-        assert _null_cache.ttl == _NULL_CACHE_TTL
-        assert _token_cache.ttl == _TOKEN_CACHE_TTL
-        assert _NULL_CACHE_TTL < _TOKEN_CACHE_TTL
-
-
-class TestGetIntegrationEnvVars:
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_injects_all_env_vars_for_provider(self):
-        _token_cache[(_USER, "github")] = "gh-tok"
-
-        result = await get_integration_env_vars(_USER)
-
-        for var in PROVIDER_ENV_VARS["github"]:
-            assert result[var] == "gh-tok"
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_empty_dict_when_no_credentials(self):
-        _null_cache[(_USER, "github")] = True
-
-        result = await get_integration_env_vars(_USER)
-
-        assert result == {}

autogpt_platform/backend/backend/copilot/model.py

@@ -54,7 +54,6 @@ class ChatMessage(BaseModel):
     refusal: str | None = None
     tool_calls: list[dict] | None = None
     function_call: dict | None = None
-    duration_ms: int | None = None
 
     @staticmethod
     def from_db(prisma_message: PrismaChatMessage) -> "ChatMessage":
@@ -67,7 +66,6 @@ class ChatMessage(BaseModel):
             refusal=prisma_message.refusal,
             tool_calls=_parse_json_field(prisma_message.toolCalls),
             function_call=_parse_json_field(prisma_message.functionCall),
-            duration_ms=prisma_message.durationMs,
         )
 
 

autogpt_platform/backend/backend/copilot/permissions.py

@@ -1,430 +0,0 @@
-"""Copilot execution permissions — tool and block allow/deny filtering.
-
-:class:`CopilotPermissions` is the single model used everywhere:
-
-- ``AutoPilotBlock`` reads four block-input fields and builds one instance.
-- ``stream_chat_completion_sdk`` applies it when constructing
-  ``ClaudeAgentOptions.allowed_tools`` / ``disallowed_tools``.
-- ``run_block`` reads it from the contextvar to gate block execution.
-- Recursive (sub-agent) invocations merge parent and child so children
-  can only be *more* restrictive, never more permissive.
-
-Tool names
-----------
-Users specify the **short name** as it appears in ``TOOL_REGISTRY`` (e.g.
-``run_block``, ``web_fetch``) or as an SDK built-in (e.g. ``Read``,
-``Task``, ``WebSearch``).  Internally these are mapped to the full SDK
-format (``mcp__copilot__run_block``, ``Read``, …) by
-:func:`apply_tool_permissions`.
-
-Block identifiers
------------------
-Each entry in ``blocks`` may be one of:
-
-- A **full UUID** (``c069dc6b-c3ed-4c12-b6e5-d47361e64ce6``)
-- A **partial UUID** — the first 8-character hex segment (``c069dc6b``)
-- A **block name** (case-insensitive, e.g. ``"HTTP Request"``)
-
-:func:`validate_block_identifiers` resolves all entries against the live
-block registry and returns any that could not be matched.
-
-Semantics
----------
-``tools_exclude=True``  (default) — ``tools`` is a **blacklist**; listed
-tools are denied and everything else is allowed.  An empty list means
-"allow all" (no filtering).
-
-``tools_exclude=False`` — ``tools`` is a **whitelist**; only listed tools
-are allowed.
-
-``blocks_exclude`` follows the same pattern for ``blocks``.
-
-Recursion inheritance
----------------------
-:meth:`CopilotPermissions.merged_with_parent` produces a new instance that
-is at most as permissive as the parent:
-
-- Tools: effective-allowed sets are intersected then stored as a whitelist.
-- Blocks: the parent is stored in ``_parent`` and consulted during every
-  :meth:`is_block_allowed` call so both constraints must pass.
-"""
-
-from __future__ import annotations
-
-import re
-from typing import Literal, get_args
-
-from pydantic import BaseModel, PrivateAttr
-
-# ---------------------------------------------------------------------------
-# Constants — single source of truth for all accepted tool names
-# ---------------------------------------------------------------------------
-
-# Literal type combining all valid tool names — used by AutoPilotBlock.Input
-# so the frontend renders a multi-select dropdown.
-# This is the SINGLE SOURCE OF TRUTH.  All other name sets are derived from it.
-ToolName = Literal[
-    # Platform tools (must match keys in TOOL_REGISTRY)
-    "add_understanding",
-    "bash_exec",
-    "browser_act",
-    "browser_navigate",
-    "browser_screenshot",
-    "connect_integration",
-    "continue_run_block",
-    "create_agent",
-    "create_feature_request",
-    "create_folder",
-    "customize_agent",
-    "delete_folder",
-    "delete_workspace_file",
-    "edit_agent",
-    "find_agent",
-    "find_block",
-    "find_library_agent",
-    "fix_agent_graph",
-    "get_agent_building_guide",
-    "get_doc_page",
-    "get_mcp_guide",
-    "list_folders",
-    "list_workspace_files",
-    "move_agents_to_folder",
-    "move_folder",
-    "read_workspace_file",
-    "run_agent",
-    "run_block",
-    "run_mcp_tool",
-    "search_docs",
-    "search_feature_requests",
-    "update_folder",
-    "validate_agent_graph",
-    "view_agent_output",
-    "web_fetch",
-    "write_workspace_file",
-    # SDK built-ins
-    "Edit",
-    "Glob",
-    "Grep",
-    "Read",
-    "Task",
-    "TodoWrite",
-    "WebSearch",
-    "Write",
-]
-
-# Frozen set of all valid tool names — derived from the Literal.
-ALL_TOOL_NAMES: frozenset[str] = frozenset(get_args(ToolName))
-
-# SDK built-in tool names — uppercase-initial names are SDK built-ins.
-SDK_BUILTIN_TOOL_NAMES: frozenset[str] = frozenset(
-    n for n in ALL_TOOL_NAMES if n[0].isupper()
-)
-
-# Platform tool names — everything that isn't an SDK built-in.
-PLATFORM_TOOL_NAMES: frozenset[str] = ALL_TOOL_NAMES - SDK_BUILTIN_TOOL_NAMES
-
-# Compiled regex patterns for block identifier classification.
-_FULL_UUID_RE = re.compile(
-    r"^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$",
-    re.IGNORECASE,
-)
-_PARTIAL_UUID_RE = re.compile(r"^[0-9a-f]{8}$", re.IGNORECASE)
-
-
-# ---------------------------------------------------------------------------
-# Helper — block identifier matching
-# ---------------------------------------------------------------------------
-
-
-def _block_matches(identifier: str, block_id: str, block_name: str) -> bool:
-    """Return True if *identifier* resolves to the given block.
-
-    Resolution order:
-    1. Full UUID — exact case-insensitive match against *block_id*.
-    2. Partial UUID (8 hex chars, first segment) — prefix match.
-    3. Name — case-insensitive equality against *block_name*.
-    """
-    ident = identifier.strip()
-    if _FULL_UUID_RE.match(ident):
-        return ident.lower() == block_id.lower()
-    if _PARTIAL_UUID_RE.match(ident):
-        return block_id.lower().startswith(ident.lower())
-    return ident.lower() == block_name.lower()
-
-
-# ---------------------------------------------------------------------------
-# Model
-# ---------------------------------------------------------------------------
-
-
-class CopilotPermissions(BaseModel):
-    """Capability filter for a single copilot execution.
-
-    Attributes:
-        tools: Tool names to filter (short names, e.g. ``run_block``).
-        tools_exclude: When True (default) ``tools`` is a blacklist;
-            when False it is a whitelist.  Ignored when *tools* is empty.
-        blocks: Block identifiers (name, full UUID, or 8-char partial UUID).
-        blocks_exclude: Same semantics as *tools_exclude* but for blocks.
-    """
-
-    tools: list[str] = []
-    tools_exclude: bool = True
-    blocks: list[str] = []
-    blocks_exclude: bool = True
-
-    # Private: parent permissions for recursion inheritance.
-    # Set only by merged_with_parent(); never exposed in block input schema.
-    _parent: CopilotPermissions | None = PrivateAttr(default=None)
-
-    # ------------------------------------------------------------------
-    # Tool helpers
-    # ------------------------------------------------------------------
-
-    def effective_allowed_tools(self, all_tools: frozenset[str]) -> frozenset[str]:
-        """Compute the set of short tool names that are permitted.
-
-        Args:
-            all_tools: Universe of valid short tool names.
-
-        Returns:
-            Subset of *all_tools* that pass the filter.
-        """
-        if not self.tools:
-            return frozenset(all_tools)
-        tool_set = frozenset(self.tools)
-        if self.tools_exclude:
-            return all_tools - tool_set
-        return all_tools & tool_set
-
-    # ------------------------------------------------------------------
-    # Block helpers
-    # ------------------------------------------------------------------
-
-    def is_block_allowed(self, block_id: str, block_name: str) -> bool:
-        """Return True if the block may be executed under these permissions.
-
-        Checks this instance first, then consults the parent (if any) so
-        the entire inheritance chain is respected.
-        """
-        if not self._check_block_locally(block_id, block_name):
-            return False
-        if self._parent is not None:
-            return self._parent.is_block_allowed(block_id, block_name)
-        return True
-
-    def _check_block_locally(self, block_id: str, block_name: str) -> bool:
-        """Check *only* this instance's block filter (ignores parent)."""
-        if not self.blocks:
-            return True  # No filter → allow all
-        matched = any(
-            _block_matches(identifier, block_id, block_name)
-            for identifier in self.blocks
-        )
-        return not matched if self.blocks_exclude else matched
-
-    # ------------------------------------------------------------------
-    # Recursion / merging
-    # ------------------------------------------------------------------
-
-    def merged_with_parent(
-        self,
-        parent: CopilotPermissions,
-        all_tools: frozenset[str],
-    ) -> CopilotPermissions:
-        """Return a new instance that is at most as permissive as *parent*.
-
-        - Tools: intersection of effective-allowed sets, stored as a whitelist.
-        - Blocks: parent is stored internally; both constraints are applied
-          during :meth:`is_block_allowed`.
-        """
-        merged_tools = self.effective_allowed_tools(
-            all_tools
-        ) & parent.effective_allowed_tools(all_tools)
-        result = CopilotPermissions(
-            tools=sorted(merged_tools),
-            tools_exclude=False,
-            blocks=self.blocks,
-            blocks_exclude=self.blocks_exclude,
-        )
-        result._parent = parent
-        return result
-
-    # ------------------------------------------------------------------
-    # Convenience
-    # ------------------------------------------------------------------
-
-    def is_empty(self) -> bool:
-        """Return True when no filtering is configured (allow-all passthrough)."""
-        return not self.tools and not self.blocks and self._parent is None
-
-
-# ---------------------------------------------------------------------------
-# Validation helpers
-# ---------------------------------------------------------------------------
-
-
-def all_known_tool_names() -> frozenset[str]:
-    """Return all short tool names accepted in *tools*.
-
-    Returns the pre-computed ``ALL_TOOL_NAMES`` set (derived from the
-    ``ToolName`` Literal).  On first call, also verifies consistency with
-    the live ``TOOL_REGISTRY``.
-    """
-    _assert_tool_names_consistent()
-    return ALL_TOOL_NAMES
-
-
-def validate_tool_names(tools: list[str]) -> list[str]:
-    """Return entries in *tools* that are not valid tool names.
-
-    Args:
-        tools: List of short tool name strings to validate.
-
-    Returns:
-        List of invalid names (empty if all are valid).
-    """
-    return [t for t in tools if t not in ALL_TOOL_NAMES]
-
-
-_tool_names_checked = False
-
-
-def _assert_tool_names_consistent() -> None:
-    """Verify that ``PLATFORM_TOOL_NAMES`` matches ``TOOL_REGISTRY`` keys.
-
-    Called once lazily (TOOL_REGISTRY has heavy imports).  Raises
-    ``AssertionError`` with a helpful diff if they diverge.
-    """
-    global _tool_names_checked
-    if _tool_names_checked:
-        return
-    _tool_names_checked = True
-
-    from backend.copilot.tools import TOOL_REGISTRY
-
-    registry_keys: frozenset[str] = frozenset(TOOL_REGISTRY.keys())
-    declared: frozenset[str] = PLATFORM_TOOL_NAMES
-    if registry_keys != declared:
-        missing = registry_keys - declared
-        extra = declared - registry_keys
-        parts: list[str] = [
-            "PLATFORM_TOOL_NAMES in permissions.py is out of sync with TOOL_REGISTRY."
-        ]
-        if missing:
-            parts.append(f"  Missing from PLATFORM_TOOL_NAMES: {sorted(missing)}")
-        if extra:
-            parts.append(f"  Extra in PLATFORM_TOOL_NAMES: {sorted(extra)}")
-        parts.append("  Update the ToolName Literal to match.")
-        raise AssertionError("\n".join(parts))
-
-
-async def validate_block_identifiers(
-    identifiers: list[str],
-) -> list[str]:
-    """Resolve each block identifier and return those that could not be matched.
-
-    Args:
-        identifiers: List of block identifiers (name, full UUID, or partial UUID).
-
-    Returns:
-        List of identifiers that matched no known block.
-    """
-    from backend.blocks import get_blocks
-
-    # get_blocks() returns dict[block_id_str, BlockClass]; instantiate once to get names.
-    block_registry = get_blocks()
-    block_info = {bid: cls().name for bid, cls in block_registry.items()}
-    invalid: list[str] = []
-    for ident in identifiers:
-        matched = any(
-            _block_matches(ident, bid, bname) for bid, bname in block_info.items()
-        )
-        if not matched:
-            invalid.append(ident)
-    return invalid
-
-
-# ---------------------------------------------------------------------------
-# SDK tool-list application
-# ---------------------------------------------------------------------------
-
-
-def apply_tool_permissions(
-    permissions: CopilotPermissions,
-    *,
-    use_e2b: bool = False,
-) -> tuple[list[str], list[str]]:
-    """Compute (allowed_tools, extra_disallowed) for :class:`ClaudeAgentOptions`.
-
-    Takes the base allowed/disallowed lists from
-    :func:`~backend.copilot.sdk.tool_adapter.get_copilot_tool_names` /
-    :func:`~backend.copilot.sdk.tool_adapter.get_sdk_disallowed_tools` and
-    applies *permissions* on top.
-
-    Returns:
-        ``(allowed_tools, extra_disallowed)`` where *allowed_tools* is the
-        possibly-narrowed list to pass to ``ClaudeAgentOptions.allowed_tools``
-        and *extra_disallowed* is the list to pass to
-        ``ClaudeAgentOptions.disallowed_tools``.
-    """
-    from backend.copilot.sdk.tool_adapter import (
-        _READ_TOOL_NAME,
-        MCP_TOOL_PREFIX,
-        get_copilot_tool_names,
-        get_sdk_disallowed_tools,
-    )
-    from backend.copilot.tools import TOOL_REGISTRY
-
-    base_allowed = get_copilot_tool_names(use_e2b=use_e2b)
-    base_disallowed = get_sdk_disallowed_tools(use_e2b=use_e2b)
-
-    if permissions.is_empty():
-        return base_allowed, base_disallowed
-
-    all_tools = all_known_tool_names()
-    effective = permissions.effective_allowed_tools(all_tools)
-
-    # In E2B mode, SDK built-in file tools (Read, Write, Edit, Glob, Grep)
-    # are replaced by MCP equivalents (read_file, write_file, ...).
-    # Map each SDK built-in name to its E2B MCP name so users can use the
-    # familiar names in their permissions and the E2B tools are included.
-    _SDK_TO_E2B: dict[str, str] = {}
-    if use_e2b:
-        from backend.copilot.sdk.e2b_file_tools import E2B_FILE_TOOL_NAMES
-
-        _SDK_TO_E2B = dict(
-            zip(
-                ["Read", "Write", "Edit", "Glob", "Grep"],
-                E2B_FILE_TOOL_NAMES,
-                strict=False,
-            )
-        )
-
-    # Build an updated allowed list by mapping short names → SDK names and
-    # keeping only those present in the original base_allowed list.
-    def to_sdk_names(short: str) -> list[str]:
-        names: list[str] = []
-        if short in TOOL_REGISTRY:
-            names.append(f"{MCP_TOOL_PREFIX}{short}")
-        elif short in _SDK_TO_E2B:
-            # E2B mode: map SDK built-in file tool to its MCP equivalent.
-            names.append(f"{MCP_TOOL_PREFIX}{_SDK_TO_E2B[short]}")
-        else:
-            names.append(short)  # SDK built-in — used as-is
-        return names
-
-    # short names permitted by permissions
-    permitted_sdk: set[str] = set()
-    for s in effective:
-        permitted_sdk.update(to_sdk_names(s))
-    # Always include the internal Read tool (used by SDK for large/truncated outputs)
-    permitted_sdk.add(f"{MCP_TOOL_PREFIX}{_READ_TOOL_NAME}")
-
-    filtered_allowed = [t for t in base_allowed if t in permitted_sdk]
-
-    # Extra disallowed = tools that were in base_allowed but are now removed
-    removed = set(base_allowed) - set(filtered_allowed)
-    extra_disallowed = list(set(base_disallowed) | removed)
-
-    return filtered_allowed, extra_disallowed

autogpt_platform/backend/backend/copilot/permissions_test.py

@@ -1,579 +0,0 @@
-"""Tests for CopilotPermissions — tool/block capability filtering."""
-
-from __future__ import annotations
-
-import pytest
-
-from backend.copilot.permissions import (
-    ALL_TOOL_NAMES,
-    PLATFORM_TOOL_NAMES,
-    SDK_BUILTIN_TOOL_NAMES,
-    CopilotPermissions,
-    _block_matches,
-    all_known_tool_names,
-    apply_tool_permissions,
-    validate_block_identifiers,
-    validate_tool_names,
-)
-from backend.copilot.tools import TOOL_REGISTRY
-
-# ---------------------------------------------------------------------------
-# _block_matches
-# ---------------------------------------------------------------------------
-
-
-class TestBlockMatches:
-    BLOCK_ID = "c069dc6b-c3ed-4c12-b6e5-d47361e64ce6"
-    BLOCK_NAME = "HTTP Request"
-
-    def test_full_uuid_match(self):
-        assert _block_matches(self.BLOCK_ID, self.BLOCK_ID, self.BLOCK_NAME)
-
-    def test_full_uuid_case_insensitive(self):
-        assert _block_matches(self.BLOCK_ID.upper(), self.BLOCK_ID, self.BLOCK_NAME)
-
-    def test_full_uuid_no_match(self):
-        other = "aaaaaaaa-0000-0000-0000-000000000000"
-        assert not _block_matches(other, self.BLOCK_ID, self.BLOCK_NAME)
-
-    def test_partial_uuid_match(self):
-        assert _block_matches("c069dc6b", self.BLOCK_ID, self.BLOCK_NAME)
-
-    def test_partial_uuid_case_insensitive(self):
-        assert _block_matches("C069DC6B", self.BLOCK_ID, self.BLOCK_NAME)
-
-    def test_partial_uuid_no_match(self):
-        assert not _block_matches("deadbeef", self.BLOCK_ID, self.BLOCK_NAME)
-
-    def test_name_match(self):
-        assert _block_matches("HTTP Request", self.BLOCK_ID, self.BLOCK_NAME)
-
-    def test_name_case_insensitive(self):
-        assert _block_matches("http request", self.BLOCK_ID, self.BLOCK_NAME)
-        assert _block_matches("HTTP REQUEST", self.BLOCK_ID, self.BLOCK_NAME)
-
-    def test_name_no_match(self):
-        assert not _block_matches("Unknown Block", self.BLOCK_ID, self.BLOCK_NAME)
-
-    def test_partial_uuid_not_matching_as_name(self):
-        # "c069dc6b" is 8 hex chars → treated as partial UUID, NOT name match
-        assert not _block_matches(
-            "c069dc6b", "ffffffff-0000-0000-0000-000000000000", "c069dc6b"
-        )
-
-
-# ---------------------------------------------------------------------------
-# CopilotPermissions.effective_allowed_tools
-# ---------------------------------------------------------------------------
-
-
-ALL_TOOLS = frozenset(
-    ["run_block", "web_fetch", "bash_exec", "find_agent", "Task", "Read"]
-)
-
-
-class TestEffectiveAllowedTools:
-    def test_empty_list_allows_all(self):
-        perms = CopilotPermissions(tools=[], tools_exclude=True)
-        assert perms.effective_allowed_tools(ALL_TOOLS) == ALL_TOOLS
-
-    def test_empty_whitelist_allows_all(self):
-        # edge: tools_exclude=False but empty list → allow all
-        perms = CopilotPermissions(tools=[], tools_exclude=False)
-        assert perms.effective_allowed_tools(ALL_TOOLS) == ALL_TOOLS
-
-    def test_blacklist_removes_listed(self):
-        perms = CopilotPermissions(tools=["bash_exec", "web_fetch"], tools_exclude=True)
-        result = perms.effective_allowed_tools(ALL_TOOLS)
-        assert "bash_exec" not in result
-        assert "web_fetch" not in result
-        assert "run_block" in result
-        assert "Task" in result
-
-    def test_whitelist_keeps_only_listed(self):
-        perms = CopilotPermissions(tools=["run_block", "Task"], tools_exclude=False)
-        result = perms.effective_allowed_tools(ALL_TOOLS)
-        assert result == frozenset(["run_block", "Task"])
-
-    def test_whitelist_unknown_tool_yields_empty(self):
-        perms = CopilotPermissions(tools=["nonexistent"], tools_exclude=False)
-        result = perms.effective_allowed_tools(ALL_TOOLS)
-        assert result == frozenset()
-
-    def test_blacklist_unknown_tool_ignored(self):
-        perms = CopilotPermissions(tools=["nonexistent"], tools_exclude=True)
-        result = perms.effective_allowed_tools(ALL_TOOLS)
-        assert result == ALL_TOOLS
-
-
-# ---------------------------------------------------------------------------
-# CopilotPermissions.is_block_allowed
-# ---------------------------------------------------------------------------
-
-
-BLOCK_ID = "c069dc6b-c3ed-4c12-b6e5-d47361e64ce6"
-BLOCK_NAME = "HTTP Request"
-
-
-class TestIsBlockAllowed:
-    def test_empty_allows_everything(self):
-        perms = CopilotPermissions(blocks=[], blocks_exclude=True)
-        assert perms.is_block_allowed(BLOCK_ID, BLOCK_NAME)
-
-    def test_blacklist_blocks_listed(self):
-        perms = CopilotPermissions(blocks=["HTTP Request"], blocks_exclude=True)
-        assert not perms.is_block_allowed(BLOCK_ID, BLOCK_NAME)
-
-    def test_blacklist_allows_unlisted(self):
-        perms = CopilotPermissions(blocks=["Other Block"], blocks_exclude=True)
-        assert perms.is_block_allowed(BLOCK_ID, BLOCK_NAME)
-
-    def test_whitelist_allows_listed(self):
-        perms = CopilotPermissions(blocks=["HTTP Request"], blocks_exclude=False)
-        assert perms.is_block_allowed(BLOCK_ID, BLOCK_NAME)
-
-    def test_whitelist_blocks_unlisted(self):
-        perms = CopilotPermissions(blocks=["Other Block"], blocks_exclude=False)
-        assert not perms.is_block_allowed(BLOCK_ID, BLOCK_NAME)
-
-    def test_partial_uuid_blacklist(self):
-        perms = CopilotPermissions(blocks=["c069dc6b"], blocks_exclude=True)
-        assert not perms.is_block_allowed(BLOCK_ID, BLOCK_NAME)
-
-    def test_full_uuid_whitelist(self):
-        perms = CopilotPermissions(blocks=[BLOCK_ID], blocks_exclude=False)
-        assert perms.is_block_allowed(BLOCK_ID, BLOCK_NAME)
-
-    def test_parent_blocks_when_child_allows(self):
-        parent = CopilotPermissions(blocks=["HTTP Request"], blocks_exclude=True)
-        child = CopilotPermissions(blocks=[], blocks_exclude=True)
-        child._parent = parent
-        assert not child.is_block_allowed(BLOCK_ID, BLOCK_NAME)
-
-    def test_parent_allows_when_child_blocks(self):
-        parent = CopilotPermissions(blocks=[], blocks_exclude=True)
-        child = CopilotPermissions(blocks=["HTTP Request"], blocks_exclude=True)
-        child._parent = parent
-        assert not child.is_block_allowed(BLOCK_ID, BLOCK_NAME)
-
-    def test_both_must_allow(self):
-        parent = CopilotPermissions(blocks=["HTTP Request"], blocks_exclude=False)
-        child = CopilotPermissions(blocks=["HTTP Request"], blocks_exclude=False)
-        child._parent = parent
-        assert child.is_block_allowed(BLOCK_ID, BLOCK_NAME)
-
-    def test_grandparent_blocks_propagate(self):
-        grandparent = CopilotPermissions(blocks=["HTTP Request"], blocks_exclude=True)
-        parent = CopilotPermissions(blocks=[], blocks_exclude=True)
-        parent._parent = grandparent
-        child = CopilotPermissions(blocks=[], blocks_exclude=True)
-        child._parent = parent
-        assert not child.is_block_allowed(BLOCK_ID, BLOCK_NAME)
-
-
-# ---------------------------------------------------------------------------
-# CopilotPermissions.merged_with_parent
-# ---------------------------------------------------------------------------
-
-
-class TestMergedWithParent:
-    def test_tool_intersection(self):
-        all_t = frozenset(["run_block", "web_fetch", "bash_exec"])
-        parent = CopilotPermissions(tools=["bash_exec"], tools_exclude=True)
-        child = CopilotPermissions(tools=["web_fetch"], tools_exclude=True)
-        merged = child.merged_with_parent(parent, all_t)
-        effective = merged.effective_allowed_tools(all_t)
-        assert "bash_exec" not in effective
-        assert "web_fetch" not in effective
-        assert "run_block" in effective
-
-    def test_parent_whitelist_narrows_child(self):
-        all_t = frozenset(["run_block", "web_fetch", "bash_exec"])
-        parent = CopilotPermissions(tools=["run_block"], tools_exclude=False)
-        child = CopilotPermissions(tools=[], tools_exclude=True)  # allow all
-        merged = child.merged_with_parent(parent, all_t)
-        effective = merged.effective_allowed_tools(all_t)
-        assert effective == frozenset(["run_block"])
-
-    def test_child_cannot_expand_parent_whitelist(self):
-        all_t = frozenset(["run_block", "web_fetch", "bash_exec"])
-        parent = CopilotPermissions(tools=["run_block"], tools_exclude=False)
-        child = CopilotPermissions(
-            tools=["run_block", "bash_exec"], tools_exclude=False
-        )
-        merged = child.merged_with_parent(parent, all_t)
-        effective = merged.effective_allowed_tools(all_t)
-        # bash_exec was not in parent's whitelist → must not appear
-        assert "bash_exec" not in effective
-        assert "run_block" in effective
-
-    def test_merged_stored_as_whitelist(self):
-        all_t = frozenset(["run_block", "web_fetch"])
-        parent = CopilotPermissions(tools=[], tools_exclude=True)
-        child = CopilotPermissions(tools=[], tools_exclude=True)
-        merged = child.merged_with_parent(parent, all_t)
-        assert not merged.tools_exclude  # stored as whitelist
-        assert set(merged.tools) == {"run_block", "web_fetch"}
-
-    def test_block_parent_stored(self):
-        all_t = frozenset(["run_block"])
-        parent = CopilotPermissions(blocks=["HTTP Request"], blocks_exclude=True)
-        child = CopilotPermissions(blocks=[], blocks_exclude=True)
-        merged = child.merged_with_parent(parent, all_t)
-        # Parent restriction is preserved via _parent
-        assert not merged.is_block_allowed(BLOCK_ID, BLOCK_NAME)
-
-
-# ---------------------------------------------------------------------------
-# CopilotPermissions.is_empty
-# ---------------------------------------------------------------------------
-
-
-class TestIsEmpty:
-    def test_default_is_empty(self):
-        assert CopilotPermissions().is_empty()
-
-    def test_with_tools_not_empty(self):
-        assert not CopilotPermissions(tools=["bash_exec"]).is_empty()
-
-    def test_with_blocks_not_empty(self):
-        assert not CopilotPermissions(blocks=["HTTP Request"]).is_empty()
-
-    def test_with_parent_not_empty(self):
-        perms = CopilotPermissions()
-        perms._parent = CopilotPermissions(tools=["bash_exec"])
-        assert not perms.is_empty()
-
-
-# ---------------------------------------------------------------------------
-# validate_tool_names
-# ---------------------------------------------------------------------------
-
-
-class TestValidateToolNames:
-    def test_valid_registry_tool(self):
-        assert validate_tool_names(["run_block", "web_fetch"]) == []
-
-    def test_valid_sdk_builtin(self):
-        assert validate_tool_names(["Read", "Task", "WebSearch"]) == []
-
-    def test_invalid_tool(self):
-        result = validate_tool_names(["nonexistent_tool"])
-        assert "nonexistent_tool" in result
-
-    def test_mixed(self):
-        result = validate_tool_names(["run_block", "fake_tool"])
-        assert "fake_tool" in result
-        assert "run_block" not in result
-
-    def test_empty_list(self):
-        assert validate_tool_names([]) == []
-
-
-# ---------------------------------------------------------------------------
-# validate_block_identifiers (async)
-# ---------------------------------------------------------------------------
-
-
-@pytest.mark.asyncio
-class TestValidateBlockIdentifiers:
-    async def test_empty_list(self):
-        result = await validate_block_identifiers([])
-        assert result == []
-
-    async def test_valid_full_uuid(self, mocker):
-        mock_block = mocker.MagicMock()
-        mock_block.return_value.name = "HTTP Request"
-        mocker.patch(
-            "backend.blocks.get_blocks",
-            return_value={"c069dc6b-c3ed-4c12-b6e5-d47361e64ce6": mock_block},
-        )
-        result = await validate_block_identifiers(
-            ["c069dc6b-c3ed-4c12-b6e5-d47361e64ce6"]
-        )
-        assert result == []
-
-    async def test_invalid_identifier(self, mocker):
-        mock_block = mocker.MagicMock()
-        mock_block.return_value.name = "HTTP Request"
-        mocker.patch(
-            "backend.blocks.get_blocks",
-            return_value={"c069dc6b-c3ed-4c12-b6e5-d47361e64ce6": mock_block},
-        )
-        result = await validate_block_identifiers(["totally_unknown"])
-        assert "totally_unknown" in result
-
-    async def test_partial_uuid_match(self, mocker):
-        mock_block = mocker.MagicMock()
-        mock_block.return_value.name = "HTTP Request"
-        mocker.patch(
-            "backend.blocks.get_blocks",
-            return_value={"c069dc6b-c3ed-4c12-b6e5-d47361e64ce6": mock_block},
-        )
-        result = await validate_block_identifiers(["c069dc6b"])
-        assert result == []
-
-    async def test_name_match(self, mocker):
-        mock_block = mocker.MagicMock()
-        mock_block.return_value.name = "HTTP Request"
-        mocker.patch(
-            "backend.blocks.get_blocks",
-            return_value={"c069dc6b-c3ed-4c12-b6e5-d47361e64ce6": mock_block},
-        )
-        result = await validate_block_identifiers(["http request"])
-        assert result == []
-
-
-# ---------------------------------------------------------------------------
-# apply_tool_permissions
-# ---------------------------------------------------------------------------
-
-
-class TestApplyToolPermissions:
-    def test_empty_permissions_returns_base_unchanged(self, mocker):
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.get_copilot_tool_names",
-            return_value=["mcp__copilot__run_block", "mcp__copilot__web_fetch", "Task"],
-        )
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.get_sdk_disallowed_tools",
-            return_value=["Bash"],
-        )
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
-            {"run_block": object(), "web_fetch": object()},
-        )
-        perms = CopilotPermissions()
-        allowed, disallowed = apply_tool_permissions(perms, use_e2b=False)
-        assert "mcp__copilot__run_block" in allowed
-        assert "mcp__copilot__web_fetch" in allowed
-
-    def test_blacklist_removes_tool(self, mocker):
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.get_copilot_tool_names",
-            return_value=[
-                "mcp__copilot__run_block",
-                "mcp__copilot__web_fetch",
-                "mcp__copilot__bash_exec",
-                "Task",
-            ],
-        )
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.get_sdk_disallowed_tools",
-            return_value=["Bash"],
-        )
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
-            {
-                "run_block": object(),
-                "web_fetch": object(),
-                "bash_exec": object(),
-            },
-        )
-        mocker.patch(
-            "backend.copilot.permissions.all_known_tool_names",
-            return_value=frozenset(["run_block", "web_fetch", "bash_exec", "Task"]),
-        )
-        perms = CopilotPermissions(tools=["bash_exec"], tools_exclude=True)
-        allowed, _ = apply_tool_permissions(perms, use_e2b=False)
-        assert "mcp__copilot__bash_exec" not in allowed
-        assert "mcp__copilot__run_block" in allowed
-
-    def test_whitelist_keeps_only_listed(self, mocker):
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.get_copilot_tool_names",
-            return_value=[
-                "mcp__copilot__run_block",
-                "mcp__copilot__web_fetch",
-                "Task",
-                "WebSearch",
-            ],
-        )
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.get_sdk_disallowed_tools",
-            return_value=["Bash"],
-        )
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
-            {"run_block": object(), "web_fetch": object()},
-        )
-        mocker.patch(
-            "backend.copilot.permissions.all_known_tool_names",
-            return_value=frozenset(["run_block", "web_fetch", "Task", "WebSearch"]),
-        )
-        perms = CopilotPermissions(tools=["run_block"], tools_exclude=False)
-        allowed, _ = apply_tool_permissions(perms, use_e2b=False)
-        assert "mcp__copilot__run_block" in allowed
-        assert "mcp__copilot__web_fetch" not in allowed
-        assert "Task" not in allowed
-
-    def test_read_tool_always_included_even_when_blacklisted(self, mocker):
-        """mcp__copilot__Read must stay in allowed even if Read is explicitly blacklisted."""
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.get_copilot_tool_names",
-            return_value=[
-                "mcp__copilot__run_block",
-                "mcp__copilot__Read",
-                "Task",
-            ],
-        )
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.get_sdk_disallowed_tools",
-            return_value=[],
-        )
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
-            {"run_block": object()},
-        )
-        mocker.patch(
-            "backend.copilot.permissions.all_known_tool_names",
-            return_value=frozenset(["run_block", "Read", "Task"]),
-        )
-        # Explicitly blacklist Read
-        perms = CopilotPermissions(tools=["Read"], tools_exclude=True)
-        allowed, _ = apply_tool_permissions(perms, use_e2b=False)
-        assert "mcp__copilot__Read" in allowed  # always preserved for SDK internals
-        assert "mcp__copilot__run_block" in allowed
-        assert "Task" in allowed
-
-    def test_read_tool_always_included_with_narrow_whitelist(self, mocker):
-        """mcp__copilot__Read must stay in allowed even when not in a whitelist."""
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.get_copilot_tool_names",
-            return_value=[
-                "mcp__copilot__run_block",
-                "mcp__copilot__Read",
-                "Task",
-            ],
-        )
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.get_sdk_disallowed_tools",
-            return_value=[],
-        )
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
-            {"run_block": object()},
-        )
-        mocker.patch(
-            "backend.copilot.permissions.all_known_tool_names",
-            return_value=frozenset(["run_block", "Read", "Task"]),
-        )
-        # Whitelist only run_block — Read not listed
-        perms = CopilotPermissions(tools=["run_block"], tools_exclude=False)
-        allowed, _ = apply_tool_permissions(perms, use_e2b=False)
-        assert "mcp__copilot__Read" in allowed  # always preserved for SDK internals
-        assert "mcp__copilot__run_block" in allowed
-
-    def test_e2b_file_tools_included_when_sdk_builtin_whitelisted(self, mocker):
-        """In E2B mode, whitelisting 'Read' must include mcp__copilot__read_file."""
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.get_copilot_tool_names",
-            return_value=[
-                "mcp__copilot__run_block",
-                "mcp__copilot__Read",
-                "mcp__copilot__read_file",
-                "mcp__copilot__write_file",
-                "Task",
-            ],
-        )
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.get_sdk_disallowed_tools",
-            return_value=["Bash", "Read", "Write", "Edit", "Glob", "Grep"],
-        )
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
-            {"run_block": object()},
-        )
-        mocker.patch(
-            "backend.copilot.permissions.all_known_tool_names",
-            return_value=frozenset(["run_block", "Read", "Write", "Task"]),
-        )
-        mocker.patch(
-            "backend.copilot.sdk.e2b_file_tools.E2B_FILE_TOOL_NAMES",
-            ["read_file", "write_file", "edit_file", "glob", "grep"],
-        )
-        # Whitelist Read and run_block — E2B read_file should be included
-        perms = CopilotPermissions(tools=["Read", "run_block"], tools_exclude=False)
-        allowed, _ = apply_tool_permissions(perms, use_e2b=True)
-        assert "mcp__copilot__read_file" in allowed
-        assert "mcp__copilot__run_block" in allowed
-        # Write not whitelisted — write_file should NOT be included
-        assert "mcp__copilot__write_file" not in allowed
-
-    def test_e2b_file_tools_excluded_when_sdk_builtin_blacklisted(self, mocker):
-        """In E2B mode, blacklisting 'Read' must also remove mcp__copilot__read_file."""
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.get_copilot_tool_names",
-            return_value=[
-                "mcp__copilot__run_block",
-                "mcp__copilot__Read",
-                "mcp__copilot__read_file",
-                "Task",
-            ],
-        )
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.get_sdk_disallowed_tools",
-            return_value=["Bash", "Read", "Write", "Edit", "Glob", "Grep"],
-        )
-        mocker.patch(
-            "backend.copilot.sdk.tool_adapter.TOOL_REGISTRY",
-            {"run_block": object()},
-        )
-        mocker.patch(
-            "backend.copilot.permissions.all_known_tool_names",
-            return_value=frozenset(["run_block", "Read", "Task"]),
-        )
-        mocker.patch(
-            "backend.copilot.sdk.e2b_file_tools.E2B_FILE_TOOL_NAMES",
-            ["read_file", "write_file", "edit_file", "glob", "grep"],
-        )
-        # Blacklist Read — E2B read_file should also be removed
-        perms = CopilotPermissions(tools=["Read"], tools_exclude=True)
-        allowed, _ = apply_tool_permissions(perms, use_e2b=True)
-        assert "mcp__copilot__read_file" not in allowed
-        assert "mcp__copilot__run_block" in allowed
-        # mcp__copilot__Read is always preserved for SDK internals
-        assert "mcp__copilot__Read" in allowed
-
-
-# ---------------------------------------------------------------------------
-# SDK_BUILTIN_TOOL_NAMES sanity check
-# ---------------------------------------------------------------------------
-
-
-class TestSdkBuiltinToolNames:
-    def test_expected_builtins_present(self):
-        expected = {
-            "Read",
-            "Write",
-            "Edit",
-            "Glob",
-            "Grep",
-            "Task",
-            "WebSearch",
-            "TodoWrite",
-        }
-        assert expected.issubset(SDK_BUILTIN_TOOL_NAMES)
-
-    def test_platform_names_match_tool_registry(self):
-        """PLATFORM_TOOL_NAMES (derived from ToolName Literal) must match TOOL_REGISTRY keys."""
-        registry_keys = frozenset(TOOL_REGISTRY.keys())
-        assert PLATFORM_TOOL_NAMES == registry_keys, (
-            f"ToolName Literal is out of sync with TOOL_REGISTRY. "
-            f"Missing: {registry_keys - PLATFORM_TOOL_NAMES}, "
-            f"Extra: {PLATFORM_TOOL_NAMES - registry_keys}"
-        )
-
-    def test_all_tool_names_is_union(self):
-        """ALL_TOOL_NAMES must equal PLATFORM_TOOL_NAMES | SDK_BUILTIN_TOOL_NAMES."""
-        assert ALL_TOOL_NAMES == PLATFORM_TOOL_NAMES | SDK_BUILTIN_TOOL_NAMES
-
-    def test_no_overlap_between_platform_and_sdk(self):
-        """Platform and SDK built-in names must not overlap."""
-        assert PLATFORM_TOOL_NAMES.isdisjoint(SDK_BUILTIN_TOOL_NAMES)
-
-    def test_known_tools_includes_registry_and_builtins(self):
-        known = all_known_tool_names()
-        assert "run_block" in known
-        assert "Read" in known
-        assert "Task" in known

autogpt_platform/backend/backend/copilot/prompting.py

@@ -6,24 +6,39 @@ handling the distinction between:
 - Local mode vs E2B mode (storage/filesystem differences)
 """
 
-from backend.blocks.autopilot import AUTOPILOT_BLOCK_ID
 from backend.copilot.tools import TOOL_REGISTRY
 
 # Shared technical notes that apply to both SDK and baseline modes
-_SHARED_TOOL_NOTES = f"""\
+_SHARED_TOOL_NOTES = """\
 
-### Sharing files
-After `write_workspace_file`, embed the `download_url` in Markdown:
-- File: `[report.csv](workspace://file_id#text/csv)`
-- Image: `![chart](workspace://file_id#image/png)`
-- Video: `![recording](workspace://file_id#video/mp4)`
+### Sharing files with the user
+After saving a file to the persistent workspace with `write_workspace_file`,
+share it with the user by embedding the `download_url` from the response in
+your message as a Markdown link or image:
 
-### File references — @@agptfile:
-Pass large file content to tools by reference: `@@agptfile:<uri>[<start>-<end>]`
-- `workspace://<file_id>` or `workspace:///<path>` — workspace files
-- `/absolute/path` — local/sandbox files
-- `[start-end]` — optional 1-indexed line range
-- Multiple refs per argument supported. Only `workspace://` and absolute paths are expanded.
+- **Any file** — shows as a clickable download link:
+  `[report.csv](workspace://file_id#text/csv)`
+- **Image** — renders inline in chat:
+  `![chart](workspace://file_id#image/png)`
+- **Video** — renders inline in chat with player controls:
+  `![recording](workspace://file_id#video/mp4)`
+
+The `download_url` field in the `write_workspace_file` response is already
+in the correct format — paste it directly after the `(` in the Markdown.
+
+### Passing file content to tools — @@agptfile: references
+Instead of copying large file contents into a tool argument, pass a file
+reference and the platform will load the content for you.
+
+Syntax: `@@agptfile:<uri>[<start>-<end>]`
+
+- `<uri>` **must** start with `workspace://` or `/` (absolute path):
+  - `workspace://<file_id>` — workspace file by ID
+  - `workspace:///<path>` — workspace file by virtual path
+  - `/absolute/local/path` — ephemeral or sdk_cwd file
+  - E2B sandbox absolute path (e.g. `/home/user/script.py`)
+- `[<start>-<end>]` is an optional 1-indexed inclusive line range.
+- URIs that do not start with `workspace://` or `/` are **not** expanded.
 
 Examples:
 ```
@@ -34,9 +49,21 @@ Examples:
 @@agptfile:/home/user/script.py
 ```
 
-**Structured data**: When the entire argument is a single file reference, the platform auto-parses by extension/MIME. Supported: JSON, JSONL, CSV, TSV, YAML, TOML, Parquet, Excel (.xlsx only; legacy `.xls` is NOT supported). Unrecognised formats return plain string.
+You can embed a reference inside any string argument, or use it as the entire
+value.  Multiple references in one argument are all expanded.
 
-**Type coercion**: The platform auto-coerces expanded string values to match block input types (e.g. JSON string → `list[list[str]]`).
+**Structured data**: When the **entire** argument value is a single file
+reference (no surrounding text), the platform automatically parses the file
+content based on its extension or MIME type.  Supported formats: JSON, JSONL,
+CSV, TSV, YAML, TOML, Parquet, and Excel (.xlsx — first sheet only).
+For example, pass `@@agptfile:workspace://<id>` where the file is a `.csv` and
+the rows will be parsed into `list[list[str]]` automatically.  If the format is
+unrecognised or parsing fails, the content is returned as a plain string.
+Legacy `.xls` files are **not** supported — only the modern `.xlsx` format.
+
+**Type coercion**: The platform also coerces expanded values to match the
+block's expected input types.  For example, if a block expects `list[list[str]]`
+and the expanded value is a JSON string, it will be parsed into the correct type.
 
 ### Media file inputs (format: "file")
 Some block inputs accept media files — their schema shows `"format": "file"`.
@@ -54,97 +81,18 @@ that would be corrupted by text encoding.
 
 Example — committing an image file to GitHub:
 ```json
-{{
-  "files": [{{
+{
+  "files": [{
     "path": "docs/hero.png",
     "content": "workspace://abc123#image/png",
     "operation": "upsert"
-  }}]
-}}
+  }]
+}
 ```
 
-### Writing large files — CRITICAL
-**Never write an entire large document in a single tool call.**  When the
-content you want to write exceeds ~2000 words the tool call's output token
-limit will silently truncate the arguments, producing an empty `{{}}` input
-that fails repeatedly.
-
-**Preferred: compose from file references.**  If the data is already in
-files (tool outputs, workspace files), compose the report in one call
-using `@@agptfile:` references — the system expands them inline:
-
-```bash
-cat > report.md << 'EOF'
-# Research Report
-## Data from web research
-@@agptfile:/home/user/web_results.txt
-## Block execution output
-@@agptfile:workspace://<file_id>
-## Conclusion
-<brief synthesis>
-EOF
-```
-
-**Fallback: write section-by-section.**  When you must generate content
-from conversation context (no files to reference), split into multiple
-`bash_exec` calls — one section per call:
-
-```bash
-cat > report.md << 'EOF'
-# Section 1
-<content from your earlier tool call results>
-EOF
-```
-```bash
-cat >> report.md << 'EOF'
-# Section 2
-<content from your earlier tool call results>
-EOF
-```
-Use `cat >` for the first chunk and `cat >>` to append subsequent chunks.
-Do not re-fetch or re-generate data you already have from prior tool calls.
-
-After building the file, reference it with `@@agptfile:` in other tools:
-`@@agptfile:/home/user/report.md`
-
 ### Sub-agent tasks
 - When using the Task tool, NEVER set `run_in_background` to true.
   All tasks must run in the foreground.
-
-### Delegating to another autopilot (sub-autopilot pattern)
-Use the **AutoPilotBlock** (`run_block` with block_id
-`{AUTOPILOT_BLOCK_ID}`) to delegate a task to a fresh
-autopilot instance.  The sub-autopilot has its own full tool set and can
-perform multi-step work autonomously.
-
-- **Input**: `prompt` (required) — the task description.
-  Optional: `system_context` to constrain behavior, `session_id` to
-  continue a previous conversation, `max_recursion_depth` (default 3).
-- **Output**: `response` (text), `tool_calls` (list), `session_id`
-  (for continuation), `conversation_history`, `token_usage`.
-
-Use this when a task is complex enough to benefit from a separate
-autopilot context, e.g. "research X and write a report" while the
-parent autopilot handles orchestration.
-"""
-
-# E2B-only notes — E2B has full internet access so gh CLI works there.
-# Not shown in local (bubblewrap) mode: --unshare-net blocks all network.
-_E2B_TOOL_NOTES = """
-### GitHub CLI (`gh`) and git
-- If the user has connected their GitHub account, both `gh` and `git` are
-  pre-authenticated — use them directly without any manual login step.
-  `git` HTTPS operations (clone, push, pull) work automatically.
-- If the token changes mid-session (e.g. user reconnects with a new token),
-  run `gh auth setup-git` to re-register the credential helper.
-- If `gh` or `git` fails with an authentication error (e.g. "authentication
-  required", "could not read Username", or exit code 128), call
-  `connect_integration(provider="github")` to surface the GitHub credentials
-  setup card so the user can connect their account. Once connected, retry
-  the operation.
-- For operations that need broader access (e.g. private org repos, GitHub
-  Actions), pass the required scopes: e.g.
-  `connect_integration(provider="github", scopes=["repo", "read:org"])`.
 """
 
 
@@ -157,7 +105,6 @@ def _build_storage_supplement(
     storage_system_1_persistence: list[str],
     file_move_name_1_to_2: str,
     file_move_name_2_to_1: str,
-    extra_notes: str = "",
 ) -> str:
     """Build storage/filesystem supplement for a specific environment.
 
@@ -172,7 +119,6 @@ def _build_storage_supplement(
         storage_system_1_persistence: List of persistence behavior descriptions
         file_move_name_1_to_2: Direction label for primary→persistent
         file_move_name_2_to_1: Direction label for persistent→primary
-        extra_notes: Environment-specific notes appended after shared notes
     """
     # Format lists as bullet points with proper indentation
     characteristics = "\n".join(f"   - {c}" for c in storage_system_1_characteristics)
@@ -182,12 +128,17 @@ def _build_storage_supplement(
 
 ## Tool notes
 
-### Shell & filesystem
-- The SDK built-in Bash tool is NOT available. Use `bash_exec` for shell commands ({sandbox_type}). Working dir: `{working_dir}`
-- SDK file tools (Read/Write/Edit/Glob/Grep) and `bash_exec` share one filesystem — use relative or absolute paths under this dir.
-- `read_workspace_file`/`write_workspace_file` operate on **persistent cloud workspace storage** (separate from the working dir).
+### Shell commands
+- The SDK built-in Bash tool is NOT available.  Use the `bash_exec` MCP tool
+  for shell commands — it runs {sandbox_type}.
+
+### Working directory
+- Your working directory is: `{working_dir}`
+- All SDK file tools AND `bash_exec` operate on the same filesystem
+- Use relative paths or absolute paths under `{working_dir}` for all file operations
 
 ### Two storage systems — CRITICAL to understand
+
 1. **{storage_system_1_name}** (`{working_dir}`):
 {characteristics}
 {persistence}
@@ -201,24 +152,12 @@ def _build_storage_supplement(
 
 ### File persistence
 Important files (code, configs, outputs) should be saved to workspace to ensure they persist.
-
-### SDK tool-result files
-When tool outputs are large, the SDK truncates them and saves the full output to
-a local file under `~/.claude/projects/.../tool-results/`. To read these files,
-always use `Read` (NOT `bash_exec`, NOT `read_workspace_file`).
-These files are on the host filesystem — `bash_exec` runs in the sandbox and
-CANNOT access them. `read_workspace_file` reads from cloud workspace storage,
-where SDK tool-results are NOT stored.
-{_SHARED_TOOL_NOTES}{extra_notes}"""
+{_SHARED_TOOL_NOTES}"""
 
 
 # Pre-built supplements for common environments
 def _get_local_storage_supplement(cwd: str) -> str:
-    """Local ephemeral storage (files lost between turns).
-
-    Network is isolated (bubblewrap --unshare-net), so internet-dependent CLIs
-    like gh will not work — no integration env-var notes are included.
-    """
+    """Local ephemeral storage (files lost between turns)."""
     return _build_storage_supplement(
         working_dir=cwd,
         sandbox_type="in a network-isolated sandbox",
@@ -236,11 +175,7 @@ def _get_local_storage_supplement(cwd: str) -> str:
 
 
 def _get_cloud_sandbox_supplement() -> str:
-    """Cloud persistent sandbox (files survive across turns in session).
-
-    E2B has full internet access, so integration tokens (GH_TOKEN etc.) are
-    injected per command in bash_exec — include the CLI guidance notes.
-    """
+    """Cloud persistent sandbox (files survive across turns in session)."""
     return _build_storage_supplement(
         working_dir="/home/user",
         sandbox_type="in a cloud sandbox with full internet access",
@@ -255,7 +190,6 @@ def _get_cloud_sandbox_supplement() -> str:
         ],
         file_move_name_1_to_2="Sandbox → Persistent",
         file_move_name_2_to_1="Persistent → Sandbox",
-        extra_notes=_E2B_TOOL_NOTES,
     )
 
 

autogpt_platform/backend/backend/copilot/providers.py

@@ -1,63 +0,0 @@
-"""Single source of truth for copilot-supported integration providers.
-
-Both :mod:`~backend.copilot.integration_creds` (env-var injection) and
-:mod:`~backend.copilot.tools.connect_integration` (UI setup card) import from
-here, eliminating the risk of the two registries drifting out of sync.
-"""
-
-from typing import TypedDict
-
-
-class ProviderEntry(TypedDict):
-    """Metadata for a supported integration provider.
-
-    Attributes:
-        name: Human-readable display name (e.g. "GitHub").
-        env_vars: Environment variable names injected when the provider is
-            connected (e.g. ``["GH_TOKEN", "GITHUB_TOKEN"]``).
-        default_scopes: Default OAuth scopes requested when the agent does not
-            specify any.
-    """
-
-    name: str
-    env_vars: list[str]
-    default_scopes: list[str]
-
-
-def _is_github_oauth_configured() -> bool:
-    """Return True if GitHub OAuth env vars are set.
-
-    Uses a lazy import to avoid triggering ``Secrets()`` during module import,
-    which can fail in environments where secrets are not yet loaded (e.g. tests,
-    CLI tooling).
-    """
-    from backend.blocks.github._auth import GITHUB_OAUTH_IS_CONFIGURED
-
-    return GITHUB_OAUTH_IS_CONFIGURED
-
-
-# -- Registry ----------------------------------------------------------------
-# Add new providers here.  Both env-var injection and the setup-card tool read
-# from this single registry.
-
-SUPPORTED_PROVIDERS: dict[str, ProviderEntry] = {
-    "github": {
-        "name": "GitHub",
-        "env_vars": ["GH_TOKEN", "GITHUB_TOKEN"],
-        "default_scopes": ["repo"],
-    },
-}
-
-
-def get_provider_auth_types(provider: str) -> list[str]:
-    """Return the supported credential types for *provider* at runtime.
-
-    OAuth types are only offered when the corresponding OAuth client env vars
-    are configured.
-    """
-    if provider == "github":
-        if _is_github_oauth_configured():
-            return ["api_key", "oauth2"]
-        return ["api_key"]
-    # Default for unknown/future providers — API key only.
-    return ["api_key"]

autogpt_platform/backend/backend/copilot/rate_limit.py

@@ -36,10 +36,6 @@ class CoPilotUsageStatus(BaseModel):
 
     daily: UsageWindow
     weekly: UsageWindow
-    reset_cost: int = Field(
-        default=0,
-        description="Credit cost (in cents) to reset the daily limit. 0 = feature disabled.",
-    )
 
 
 class RateLimitExceeded(Exception):
@@ -65,7 +61,6 @@ async def get_usage_status(
     user_id: str,
     daily_token_limit: int,
     weekly_token_limit: int,
-    rate_limit_reset_cost: int = 0,
 ) -> CoPilotUsageStatus:
     """Get current usage status for a user.
 
@@ -73,7 +68,6 @@ async def get_usage_status(
         user_id: The user's ID.
         daily_token_limit: Max tokens per day (0 = unlimited).
         weekly_token_limit: Max tokens per week (0 = unlimited).
-        rate_limit_reset_cost: Credit cost (cents) to reset daily limit (0 = disabled).
 
     Returns:
         CoPilotUsageStatus with current usage and limits.
@@ -103,7 +97,6 @@ async def get_usage_status(
             limit=weekly_token_limit,
             resets_at=_weekly_reset_time(now=now),
         ),
-        reset_cost=rate_limit_reset_cost,
     )
 
 
@@ -148,110 +141,6 @@ async def check_rate_limit(
         raise RateLimitExceeded("weekly", _weekly_reset_time(now=now))
 
 
-async def reset_daily_usage(user_id: str, daily_token_limit: int = 0) -> bool:
-    """Reset a user's daily token usage counter in Redis.
-
-    Called after a user pays credits to extend their daily limit.
-    Also reduces the weekly usage counter by ``daily_token_limit`` tokens
-    (clamped to 0) so the user effectively gets one extra day's worth of
-    weekly capacity.
-
-    Args:
-        user_id: The user's ID.
-        daily_token_limit: The configured daily token limit. When positive,
-            the weekly counter is reduced by this amount.
-
-    Fails open: returns False if Redis is unavailable (consistent with
-    the fail-open design of this module).
-    """
-    now = datetime.now(UTC)
-    try:
-        redis = await get_redis_async()
-
-        # Use a MULTI/EXEC transaction so that DELETE (daily) and DECRBY
-        # (weekly) either both execute or neither does.  This prevents the
-        # scenario where the daily counter is cleared but the weekly
-        # counter is not decremented — which would let the caller refund
-        # credits even though the daily limit was already reset.
-        d_key = _daily_key(user_id, now=now)
-        w_key = _weekly_key(user_id, now=now) if daily_token_limit > 0 else None
-
-        pipe = redis.pipeline(transaction=True)
-        pipe.delete(d_key)
-        if w_key is not None:
-            pipe.decrby(w_key, daily_token_limit)
-        results = await pipe.execute()
-
-        # Clamp negative weekly counter to 0 (best-effort; not critical).
-        if w_key is not None:
-            new_val = results[1]  # DECRBY result
-            if new_val < 0:
-                await redis.set(w_key, 0, keepttl=True)
-
-        logger.info("Reset daily usage for user %s", user_id[:8])
-        return True
-    except (RedisError, ConnectionError, OSError):
-        logger.warning("Redis unavailable for resetting daily usage")
-        return False
-
-
-_RESET_LOCK_PREFIX = "copilot:reset_lock"
-_RESET_COUNT_PREFIX = "copilot:reset_count"
-
-
-async def acquire_reset_lock(user_id: str, ttl_seconds: int = 10) -> bool:
-    """Acquire a short-lived lock to serialize rate limit resets per user."""
-    try:
-        redis = await get_redis_async()
-        key = f"{_RESET_LOCK_PREFIX}:{user_id}"
-        return bool(await redis.set(key, "1", nx=True, ex=ttl_seconds))
-    except (RedisError, ConnectionError, OSError) as exc:
-        logger.warning("Redis unavailable for reset lock, rejecting reset: %s", exc)
-        return False
-
-
-async def release_reset_lock(user_id: str) -> None:
-    """Release the per-user reset lock."""
-    try:
-        redis = await get_redis_async()
-        await redis.delete(f"{_RESET_LOCK_PREFIX}:{user_id}")
-    except (RedisError, ConnectionError, OSError):
-        pass  # Lock will expire via TTL
-
-
-async def get_daily_reset_count(user_id: str) -> int | None:
-    """Get how many times the user has reset today.
-
-    Returns None when Redis is unavailable so callers can fail-closed
-    for billed operations (as opposed to failing open for read-only
-    rate-limit checks).
-    """
-    now = datetime.now(UTC)
-    try:
-        redis = await get_redis_async()
-        key = f"{_RESET_COUNT_PREFIX}:{user_id}:{now.strftime('%Y-%m-%d')}"
-        val = await redis.get(key)
-        return int(val or 0)
-    except (RedisError, ConnectionError, OSError):
-        logger.warning("Redis unavailable for reading daily reset count")
-        return None
-
-
-async def increment_daily_reset_count(user_id: str) -> None:
-    """Increment and track how many resets this user has done today."""
-    now = datetime.now(UTC)
-    try:
-        redis = await get_redis_async()
-        key = f"{_RESET_COUNT_PREFIX}:{user_id}:{now.strftime('%Y-%m-%d')}"
-        pipe = redis.pipeline(transaction=True)
-        pipe.incr(key)
-        seconds_until_reset = int((_daily_reset_time(now=now) - now).total_seconds())
-        pipe.expire(key, max(seconds_until_reset, 1))
-        await pipe.execute()
-    except (RedisError, ConnectionError, OSError):
-        logger.warning("Redis unavailable for tracking reset count")
-
-
 async def record_token_usage(
     user_id: str,
     prompt_tokens: int,
@@ -342,67 +231,6 @@ async def record_token_usage(
         )
 
 
-async def get_global_rate_limits(
-    user_id: str,
-    config_daily: int,
-    config_weekly: int,
-) -> tuple[int, int]:
-    """Resolve global rate limits from LaunchDarkly, falling back to config.
-
-    Args:
-        user_id: User ID for LD flag evaluation context.
-        config_daily: Fallback daily limit from ChatConfig.
-        config_weekly: Fallback weekly limit from ChatConfig.
-
-    Returns:
-        (daily_token_limit, weekly_token_limit) tuple.
-    """
-    # Lazy import to avoid circular dependency:
-    # rate_limit -> feature_flag -> settings -> ... -> rate_limit
-    from backend.util.feature_flag import Flag, get_feature_flag_value
-
-    daily_raw = await get_feature_flag_value(
-        Flag.COPILOT_DAILY_TOKEN_LIMIT.value, user_id, config_daily
-    )
-    weekly_raw = await get_feature_flag_value(
-        Flag.COPILOT_WEEKLY_TOKEN_LIMIT.value, user_id, config_weekly
-    )
-    try:
-        daily = max(0, int(daily_raw))
-    except (TypeError, ValueError):
-        logger.warning("Invalid LD value for daily token limit: %r", daily_raw)
-        daily = config_daily
-    try:
-        weekly = max(0, int(weekly_raw))
-    except (TypeError, ValueError):
-        logger.warning("Invalid LD value for weekly token limit: %r", weekly_raw)
-        weekly = config_weekly
-    return daily, weekly
-
-
-async def reset_user_usage(user_id: str, *, reset_weekly: bool = False) -> None:
-    """Reset a user's usage counters.
-
-    Always deletes the daily Redis key.  When *reset_weekly* is ``True``,
-    the weekly key is deleted as well.
-
-    Unlike read paths (``get_usage_status``, ``check_rate_limit``) which
-    fail-open on Redis errors, resets intentionally re-raise so the caller
-    knows the operation did not succeed.  A silent failure here would leave
-    the admin believing the counters were zeroed when they were not.
-    """
-    now = datetime.now(UTC)
-    keys_to_delete = [_daily_key(user_id, now=now)]
-    if reset_weekly:
-        keys_to_delete.append(_weekly_key(user_id, now=now))
-    try:
-        redis = await get_redis_async()
-        await redis.delete(*keys_to_delete)
-    except (RedisError, ConnectionError, OSError):
-        logger.warning("Redis unavailable for resetting user usage")
-        raise
-
-
 # ---------------------------------------------------------------------------
 # Private helpers
 # ---------------------------------------------------------------------------

autogpt_platform/backend/backend/copilot/rate_limit_test.py

@@ -12,7 +12,6 @@ from .rate_limit import (
     check_rate_limit,
     get_usage_status,
     record_token_usage,
-    reset_daily_usage,
 )
 
 _USER = "test-user-rl"
@@ -333,91 +332,3 @@ class TestRecordTokenUsage:
         ):
             # Should not raise — fail-open
             await record_token_usage(_USER, prompt_tokens=100, completion_tokens=50)
-
-
-# ---------------------------------------------------------------------------
-# reset_daily_usage
-# ---------------------------------------------------------------------------
-
-
-class TestResetDailyUsage:
-    @staticmethod
-    def _make_pipeline_mock(decrby_result: int = 0) -> MagicMock:
-        """Create a pipeline mock that returns [delete_result, decrby_result]."""
-        pipe = MagicMock()
-        pipe.execute = AsyncMock(return_value=[1, decrby_result])
-        return pipe
-
-    @pytest.mark.asyncio
-    async def test_deletes_daily_key(self):
-        mock_pipe = self._make_pipeline_mock(decrby_result=0)
-        mock_redis = AsyncMock()
-        mock_redis.pipeline = lambda **_kw: mock_pipe
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            result = await reset_daily_usage(_USER, daily_token_limit=10000)
-
-        assert result is True
-        mock_pipe.delete.assert_called_once()
-
-    @pytest.mark.asyncio
-    async def test_reduces_weekly_usage_via_decrby(self):
-        """Weekly counter should be reduced via DECRBY in the pipeline."""
-        mock_pipe = self._make_pipeline_mock(decrby_result=35000)
-        mock_redis = AsyncMock()
-        mock_redis.pipeline = lambda **_kw: mock_pipe
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            await reset_daily_usage(_USER, daily_token_limit=10000)
-
-        mock_pipe.decrby.assert_called_once()
-        mock_redis.set.assert_not_called()  # 35000 > 0, no clamp needed
-
-    @pytest.mark.asyncio
-    async def test_clamps_negative_weekly_to_zero(self):
-        """If DECRBY goes negative, SET to 0 (outside the pipeline)."""
-        mock_pipe = self._make_pipeline_mock(decrby_result=-5000)
-        mock_redis = AsyncMock()
-        mock_redis.pipeline = lambda **_kw: mock_pipe
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            await reset_daily_usage(_USER, daily_token_limit=10000)
-
-        mock_pipe.decrby.assert_called_once()
-        mock_redis.set.assert_called_once()
-
-    @pytest.mark.asyncio
-    async def test_no_weekly_reduction_when_daily_limit_zero(self):
-        """When daily_token_limit is 0, weekly counter should not be touched."""
-        mock_pipe = self._make_pipeline_mock()
-        mock_pipe.execute = AsyncMock(return_value=[1])  # only delete result
-        mock_redis = AsyncMock()
-        mock_redis.pipeline = lambda **_kw: mock_pipe
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            await reset_daily_usage(_USER, daily_token_limit=0)
-
-        mock_pipe.delete.assert_called_once()
-        mock_pipe.decrby.assert_not_called()
-
-    @pytest.mark.asyncio
-    async def test_returns_false_when_redis_unavailable(self):
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            side_effect=ConnectionError("Redis down"),
-        ):
-            result = await reset_daily_usage(_USER, daily_token_limit=10000)
-
-        assert result is False

autogpt_platform/backend/backend/copilot/reset_usage_test.py

@@ -1,294 +0,0 @@
-"""Unit tests for the POST /usage/reset endpoint."""
-
-from __future__ import annotations
-
-from datetime import UTC, datetime, timedelta
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import pytest
-from fastapi import HTTPException
-
-from backend.api.features.chat.routes import reset_copilot_usage
-from backend.copilot.rate_limit import CoPilotUsageStatus, UsageWindow
-from backend.util.exceptions import InsufficientBalanceError
-
-
-# Minimal config mock matching ChatConfig fields used by the endpoint.
-def _make_config(
-    rate_limit_reset_cost: int = 500,
-    daily_token_limit: int = 2_500_000,
-    weekly_token_limit: int = 12_500_000,
-    max_daily_resets: int = 5,
-):
-    cfg = MagicMock()
-    cfg.rate_limit_reset_cost = rate_limit_reset_cost
-    cfg.daily_token_limit = daily_token_limit
-    cfg.weekly_token_limit = weekly_token_limit
-    cfg.max_daily_resets = max_daily_resets
-    return cfg
-
-
-def _usage(daily_used: int = 3_000_000, daily_limit: int = 2_500_000):
-    return CoPilotUsageStatus(
-        daily=UsageWindow(
-            used=daily_used,
-            limit=daily_limit,
-            resets_at=datetime.now(UTC) + timedelta(hours=6),
-        ),
-        weekly=UsageWindow(
-            used=5_000_000,
-            limit=12_500_000,
-            resets_at=datetime.now(UTC) + timedelta(days=3),
-        ),
-    )
-
-
-_MODULE = "backend.api.features.chat.routes"
-
-
-def _mock_settings(enable_credit: bool = True):
-    """Return a mock Settings object with the given enable_credit flag."""
-    mock = MagicMock()
-    mock.config.enable_credit = enable_credit
-    return mock
-
-
-@pytest.mark.asyncio
-class TestResetCopilotUsage:
-    async def test_feature_disabled_returns_400(self):
-        """When rate_limit_reset_cost=0, endpoint returns 400."""
-
-        with patch(f"{_MODULE}.config", _make_config(rate_limit_reset_cost=0)):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 400
-            assert "not available" in exc_info.value.detail
-
-    async def test_no_daily_limit_returns_400(self):
-        """When daily_token_limit=0 (unlimited), endpoint returns 400."""
-
-        with (
-            patch(f"{_MODULE}.config", _make_config(daily_token_limit=0)),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 400
-            assert "nothing to reset" in exc_info.value.detail.lower()
-
-    async def test_not_at_limit_returns_400(self):
-        """When user hasn't hit their daily limit, returns 400."""
-
-        cfg = _make_config()
-        with (
-            patch(f"{_MODULE}.config", cfg),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-            patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
-            patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
-            patch(f"{_MODULE}.release_reset_lock", AsyncMock()) as mock_release,
-            patch(
-                f"{_MODULE}.get_usage_status",
-                AsyncMock(return_value=_usage(daily_used=1_000_000)),
-            ),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 400
-            assert "not reached" in exc_info.value.detail
-            mock_release.assert_awaited_once()
-
-    async def test_insufficient_credits_returns_402(self):
-        """When user doesn't have enough credits, returns 402."""
-
-        mock_credit_model = AsyncMock()
-        mock_credit_model.spend_credits.side_effect = InsufficientBalanceError(
-            message="Insufficient balance",
-            user_id="user-1",
-            balance=50,
-            amount=200,
-        )
-
-        cfg = _make_config()
-        with (
-            patch(f"{_MODULE}.config", cfg),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-            patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
-            patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
-            patch(f"{_MODULE}.release_reset_lock", AsyncMock()) as mock_release,
-            patch(
-                f"{_MODULE}.get_usage_status",
-                AsyncMock(return_value=_usage()),
-            ),
-            patch(
-                f"{_MODULE}.get_user_credit_model",
-                AsyncMock(return_value=mock_credit_model),
-            ),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 402
-            mock_release.assert_awaited_once()
-
-    async def test_happy_path(self):
-        """Successful reset: charges credits, resets usage, returns response."""
-
-        mock_credit_model = AsyncMock()
-        mock_credit_model.spend_credits.return_value = 1500  # remaining balance
-
-        cfg = _make_config()
-        updated_usage = _usage(daily_used=0)
-
-        with (
-            patch(f"{_MODULE}.config", cfg),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-            patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
-            patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
-            patch(f"{_MODULE}.release_reset_lock", AsyncMock()),
-            patch(
-                f"{_MODULE}.get_usage_status",
-                AsyncMock(side_effect=[_usage(), updated_usage]),
-            ),
-            patch(
-                f"{_MODULE}.get_user_credit_model",
-                AsyncMock(return_value=mock_credit_model),
-            ),
-            patch(
-                f"{_MODULE}.reset_daily_usage", AsyncMock(return_value=True)
-            ) as mock_reset,
-            patch(f"{_MODULE}.increment_daily_reset_count", AsyncMock()) as mock_incr,
-        ):
-            result = await reset_copilot_usage(user_id="user-1")
-            assert result.success is True
-            assert result.credits_charged == 500
-            assert result.remaining_balance == 1500
-            mock_reset.assert_awaited_once()
-            mock_incr.assert_awaited_once()
-
-    async def test_max_daily_resets_exceeded(self):
-        """When user has exhausted daily resets, returns 429."""
-
-        cfg = _make_config(max_daily_resets=3)
-        with (
-            patch(f"{_MODULE}.config", cfg),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-            patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=3)),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 429
-
-    async def test_credit_system_disabled_returns_400(self):
-        """When enable_credit=False, endpoint returns 400."""
-
-        with (
-            patch(f"{_MODULE}.config", _make_config()),
-            patch(f"{_MODULE}.settings", _mock_settings(enable_credit=False)),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 400
-            assert "credit system is disabled" in exc_info.value.detail.lower()
-
-    async def test_weekly_limit_exhausted_returns_400(self):
-        """When the weekly limit is also exhausted, resetting daily won't help."""
-
-        cfg = _make_config()
-        weekly_exhausted = CoPilotUsageStatus(
-            daily=UsageWindow(
-                used=3_000_000,
-                limit=2_500_000,
-                resets_at=datetime.now(UTC) + timedelta(hours=6),
-            ),
-            weekly=UsageWindow(
-                used=12_500_000,
-                limit=12_500_000,
-                resets_at=datetime.now(UTC) + timedelta(days=3),
-            ),
-        )
-        with (
-            patch(f"{_MODULE}.config", cfg),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-            patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
-            patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
-            patch(f"{_MODULE}.release_reset_lock", AsyncMock()) as mock_release,
-            patch(
-                f"{_MODULE}.get_usage_status",
-                AsyncMock(return_value=weekly_exhausted),
-            ),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 400
-            assert "weekly" in exc_info.value.detail.lower()
-            mock_release.assert_awaited_once()
-
-    async def test_redis_failure_for_reset_count_returns_503(self):
-        """When Redis is unavailable for get_daily_reset_count, returns 503."""
-
-        with (
-            patch(f"{_MODULE}.config", _make_config()),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-            patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=None)),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 503
-            assert "verify" in exc_info.value.detail.lower()
-
-    async def test_redis_reset_failure_refunds_credits(self):
-        """When reset_daily_usage fails, credits are refunded and 503 returned."""
-
-        mock_credit_model = AsyncMock()
-        mock_credit_model.spend_credits.return_value = 1500
-
-        cfg = _make_config()
-        with (
-            patch(f"{_MODULE}.config", cfg),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-            patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
-            patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
-            patch(f"{_MODULE}.release_reset_lock", AsyncMock()),
-            patch(
-                f"{_MODULE}.get_usage_status",
-                AsyncMock(return_value=_usage()),
-            ),
-            patch(
-                f"{_MODULE}.get_user_credit_model",
-                AsyncMock(return_value=mock_credit_model),
-            ),
-            patch(f"{_MODULE}.reset_daily_usage", AsyncMock(return_value=False)),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 503
-            assert "not been charged" in exc_info.value.detail
-            mock_credit_model.top_up_credits.assert_awaited_once()
-
-    async def test_redis_reset_failure_refund_also_fails(self):
-        """When both reset and refund fail, error message reflects the truth."""
-
-        mock_credit_model = AsyncMock()
-        mock_credit_model.spend_credits.return_value = 1500
-        mock_credit_model.top_up_credits.side_effect = RuntimeError("db down")
-
-        cfg = _make_config()
-        with (
-            patch(f"{_MODULE}.config", cfg),
-            patch(f"{_MODULE}.settings", _mock_settings()),
-            patch(f"{_MODULE}.get_daily_reset_count", AsyncMock(return_value=0)),
-            patch(f"{_MODULE}.acquire_reset_lock", AsyncMock(return_value=True)),
-            patch(f"{_MODULE}.release_reset_lock", AsyncMock()),
-            patch(
-                f"{_MODULE}.get_usage_status",
-                AsyncMock(return_value=_usage()),
-            ),
-            patch(
-                f"{_MODULE}.get_user_credit_model",
-                AsyncMock(return_value=mock_credit_model),
-            ),
-            patch(f"{_MODULE}.reset_daily_usage", AsyncMock(return_value=False)),
-        ):
-            with pytest.raises(HTTPException) as exc_info:
-                await reset_copilot_usage(user_id="user-1")
-            assert exc_info.value.status_code == 503
-            assert "contact support" in exc_info.value.detail.lower()

autogpt_platform/backend/backend/copilot/response_model.py

@@ -43,7 +43,6 @@ class ResponseType(str, Enum):
     ERROR = "error"
     USAGE = "usage"
     HEARTBEAT = "heartbeat"
-    STATUS = "status"
 
 
 class StreamBaseResponse(BaseModel):
@@ -264,19 +263,3 @@ class StreamHeartbeat(StreamBaseResponse):
     def to_sse(self) -> str:
         """Convert to SSE comment format to keep connection alive."""
         return ": heartbeat\n\n"
-
-
-class StreamStatus(StreamBaseResponse):
-    """Transient status notification shown to the user during long operations.
-
-    Used to provide feedback when the backend performs behind-the-scenes work
-    (e.g., compacting conversation context on a retry) that would otherwise
-    leave the user staring at an unexplained pause.
-
-    Sent as a proper ``data:`` event so the frontend can display it to the
-    user.  The AI SDK stream parser gracefully skips unknown chunk types
-    (logs a console warning), so this does not break the stream.
-    """
-
-    type: ResponseType = ResponseType.STATUS
-    message: str = Field(..., description="Human-readable status message")

autogpt_platform/backend/backend/copilot/sdk/__init__.py

@@ -19,19 +19,9 @@ least invasive way to break the cycle while keeping module-level constants
 intact.
 """
 
-from typing import TYPE_CHECKING, Any
-
-# Static imports for type checkers so they can resolve __all__ entries
-# without executing the lazy-import machinery at runtime.
-if TYPE_CHECKING:
-    from .collect import CopilotResult as CopilotResult
-    from .collect import collect_copilot_response as collect_copilot_response
-    from .service import stream_chat_completion_sdk as stream_chat_completion_sdk
-    from .tool_adapter import create_copilot_mcp_server as create_copilot_mcp_server
+from typing import Any
 
 __all__ = [
-    "CopilotResult",
-    "collect_copilot_response",
     "stream_chat_completion_sdk",
     "create_copilot_mcp_server",
 ]
@@ -39,8 +29,6 @@ __all__ = [
 # Dispatch table for PEP 562 lazy imports.  Each entry is a (module, attr)
 # pair so new exports can be added without touching __getattr__ itself.
 _LAZY_IMPORTS: dict[str, tuple[str, str]] = {
-    "CopilotResult": (".collect", "CopilotResult"),
-    "collect_copilot_response": (".collect", "collect_copilot_response"),
     "stream_chat_completion_sdk": (".service", "stream_chat_completion_sdk"),
     "create_copilot_mcp_server": (".tool_adapter", "create_copilot_mcp_server"),
 }

autogpt_platform/backend/backend/copilot/sdk/agent_generation_guide.md

@@ -67,17 +67,9 @@ These define the agent's interface — what it accepts and what it produces.
 **AgentInputBlock** (ID: `c0a8e994-ebf1-4a9c-a4d8-89d09c86741b`):
 - Defines a user-facing input field on the agent
 - Required `input_default` fields: `name` (str), `value` (default: null)
-- Optional: `title`, `description`
+- Optional: `title`, `description`, `placeholder_values` (for dropdowns)
 - Output: `result` — the user-provided value at runtime
 - Create one AgentInputBlock per distinct input the agent needs
-- For dropdown/select inputs, use **AgentDropdownInputBlock** instead (see below)
-
-**AgentDropdownInputBlock** (ID: `655d6fdf-a334-421c-b733-520549c07cd1`):
-- Specialized input block that presents a dropdown/select to the user
-- Required `input_default` fields: `name` (str), `placeholder_values` (list of options, must have at least one)
-- Optional: `title`, `description`, `value` (default selection)
-- Output: `result` — the user-selected value at runtime
-- Use this instead of AgentInputBlock when the user should pick from a fixed set of options
 
 **AgentOutputBlock** (ID: `363ae599-353e-4804-937e-b2ee3cef3da4`):
 - Defines a user-facing output displayed after the agent runs
@@ -151,85 +143,6 @@ To use an MCP (Model Context Protocol) tool as a node in the agent:
    tool_arguments.
 6. Output: `result` (the tool's return value) and `error` (error message)
 
-### Using OrchestratorBlock (AI Orchestrator with Agent Mode)
-
-To create an agent where AI autonomously decides which tools or sub-agents to
-call in a loop until the task is complete:
-1. Create a `OrchestratorBlock` node
-   (ID: `3b191d9f-356f-482d-8238-ba04b6d18381`)
-2. Set `input_default`:
-   - `agent_mode_max_iterations`: Choose based on task complexity:
-     - `1` for single-step tool calls (AI picks one tool, calls it, done)
-     - `3`–`10` for multi-step tasks (AI calls tools iteratively)
-     - `-1` for open-ended orchestration (AI loops until it decides it's done).
-       **Use with caution** — prefer bounded iterations (3–10) unless
-       genuinely needed, as unbounded loops risk runaway cost and execution.
-     Do NOT use `0` (traditional mode) — it requires complex external
-     conversation-history loop wiring that the agent generator does not
-     produce.
-   - `conversation_compaction`: `true` (recommended to avoid context overflow)
-   - `retry`: Number of retries on tool-call failure (default `3`).
-     Set to `0` to disable retries.
-   - `multiple_tool_calls`: Whether the AI can invoke multiple tools in a
-     single turn (default `false`). Enable when tools are independent and
-     can run concurrently.
-   - Optional: `sys_prompt` for extra LLM context about how to orchestrate
-3. Wire the `prompt` input from an `AgentInputBlock` (the user's task)
-4. Create downstream tool blocks — regular blocks **or** `AgentExecutorBlock`
-   nodes that call sub-agents
-5. Link each tool to the Orchestrator: set `source_name: "tools"` on
-   the Orchestrator side and `sink_name: <input_field>` on each tool
-   block's input. Create one link per input field the tool needs.
-6. Wire the `finished` output to an `AgentOutputBlock` for the final result
-7. Credentials (LLM API key) are configured by the user in the platform UI
-   after saving — do NOT require them upfront
-
-**Example — Orchestrator calling two sub-agents:**
-- Node 1: `AgentInputBlock` (input_default: `{"name": "task"}`)
-- Node 2: `OrchestratorBlock` (input_default:
-  `{"agent_mode_max_iterations": 10, "conversation_compaction": true}`)
-- Node 3: `AgentExecutorBlock` (sub-agent A — set `graph_id`, `graph_version`,
-  `input_schema`, `output_schema` from library agent)
-- Node 4: `AgentExecutorBlock` (sub-agent B — same pattern)
-- Node 5: `AgentOutputBlock` (input_default: `{"name": "result"}`)
-- Links:
-  - Input→Orchestrator: `source_name: "result"`, `sink_name: "prompt"`
-  - Orchestrator→Agent A (per input field): `source_name: "tools"`,
-    `sink_name: "<agent_a_input_field>"`
-  - Orchestrator→Agent B (per input field): `source_name: "tools"`,
-    `sink_name: "<agent_b_input_field>"`
-  - Orchestrator→Output: `source_name: "finished"`, `sink_name: "value"`
-
-**Example — Orchestrator calling regular blocks as tools:**
-- Node 1: `AgentInputBlock` (input_default: `{"name": "task"}`)
-- Node 2: `OrchestratorBlock` (input_default:
-  `{"agent_mode_max_iterations": 5, "conversation_compaction": true}`)
-- Node 3: `GetWebpageBlock` (regular block — the AI calls it as a tool)
-- Node 4: `AITextGeneratorBlock` (another regular block as a tool)
-- Node 5: `AgentOutputBlock` (input_default: `{"name": "result"}`)
-- Links:
-  - Input→Orchestrator: `source_name: "result"`, `sink_name: "prompt"`
-  - Orchestrator→GetWebpage: `source_name: "tools"`, `sink_name: "url"`
-  - Orchestrator→AITextGenerator: `source_name: "tools"`, `sink_name: "prompt"`
-  - Orchestrator→Output: `source_name: "finished"`, `sink_name: "value"`
-
-Regular blocks work exactly like sub-agents as tools — wire each input
-field from `source_name: "tools"` on the Orchestrator side.
-
-### Testing with Dry Run
-
-After saving an agent, suggest a dry run to validate wiring without consuming
-real API calls, credentials, or credits:
-
-1. **Run**: Call `run_agent` or `run_block` with `dry_run=True` and provide
-   sample inputs. This executes the graph with mock outputs, verifying that
-   links resolve correctly and required inputs are satisfied.
-2. **Check results**: Call `view_agent_output` with `show_execution_details=True`
-   to inspect the full node-by-node execution trace. This shows what each node
-   received as input and produced as output, making it easy to spot wiring issues.
-3. **Iterate**: If the dry run reveals wiring issues or missing inputs, fix
-   the agent JSON and re-save before suggesting a real execution.
-
 ### Example: Simple AI Text Processor
 
 A minimal agent with input, processing, and output:

autogpt_platform/backend/backend/copilot/sdk/collect.py

@@ -1,232 +0,0 @@
-"""Public helpers for consuming a copilot stream as a simple request-response.
-
-This module exposes :class:`CopilotResult` and :func:`collect_copilot_response`
-so that callers (e.g. the AutoPilot block) can consume the copilot stream
-without implementing their own event loop.
-"""
-
-from __future__ import annotations
-
-import logging
-import uuid
-from collections.abc import AsyncIterator
-from contextlib import asynccontextmanager
-from typing import TYPE_CHECKING, Any
-
-if TYPE_CHECKING:
-    from backend.copilot.permissions import CopilotPermissions
-
-from pydantic import BaseModel, Field
-from redis.exceptions import RedisError
-
-from .. import stream_registry
-from ..response_model import (
-    StreamError,
-    StreamTextDelta,
-    StreamToolInputAvailable,
-    StreamToolOutputAvailable,
-    StreamUsage,
-)
-from .service import stream_chat_completion_sdk
-
-logger = logging.getLogger(__name__)
-
-# Identifiers used when registering AutoPilot-originated streams in the
-# stream registry.  Distinct from "chat_stream"/"chat" used by the HTTP SSE
-# endpoint, making it easy to filter AutoPilot streams in logs/observability.
-AUTOPILOT_TOOL_CALL_ID = "autopilot_stream"
-AUTOPILOT_TOOL_NAME = "autopilot"
-
-
-class CopilotResult:
-    """Aggregated result from consuming a copilot stream.
-
-    Returned by :func:`collect_copilot_response` so callers don't need to
-    implement their own event-loop over the raw stream events.
-    """
-
-    __slots__ = (
-        "response_text",
-        "tool_calls",
-        "prompt_tokens",
-        "completion_tokens",
-        "total_tokens",
-    )
-
-    def __init__(self) -> None:
-        self.response_text: str = ""
-        self.tool_calls: list[dict[str, Any]] = []
-        self.prompt_tokens: int = 0
-        self.completion_tokens: int = 0
-        self.total_tokens: int = 0
-
-
-class _RegistryHandle(BaseModel):
-    """Tracks stream registry session state for cleanup."""
-
-    publish_turn_id: str = ""
-    error_msg: str | None = None
-    error_already_published: bool = False
-
-
-@asynccontextmanager
-async def _registry_session(
-    session_id: str, user_id: str, turn_id: str
-) -> AsyncIterator[_RegistryHandle]:
-    """Create a stream registry session and ensure it is finalized."""
-    handle = _RegistryHandle(publish_turn_id=turn_id)
-    try:
-        await stream_registry.create_session(
-            session_id=session_id,
-            user_id=user_id,
-            tool_call_id=AUTOPILOT_TOOL_CALL_ID,
-            tool_name=AUTOPILOT_TOOL_NAME,
-            turn_id=turn_id,
-        )
-    except (RedisError, ConnectionError, OSError):
-        logger.warning(
-            "[collect] Failed to create stream registry session for %s, "
-            "frontend will not receive real-time updates",
-            session_id[:12],
-            exc_info=True,
-        )
-        # Disable chunk publishing but keep finalization enabled so
-        # mark_session_completed can clean up any partial registry state.
-        handle.publish_turn_id = ""
-
-    try:
-        yield handle
-    finally:
-        try:
-            await stream_registry.mark_session_completed(
-                session_id,
-                error_message=handle.error_msg,
-                skip_error_publish=handle.error_already_published,
-            )
-        except (RedisError, ConnectionError, OSError):
-            logger.warning(
-                "[collect] Failed to mark stream completed for %s",
-                session_id[:12],
-                exc_info=True,
-            )
-
-
-class _ToolCallEntry(BaseModel):
-    """A single tool call observed during stream consumption."""
-
-    tool_call_id: str
-    tool_name: str
-    input: Any
-    output: Any = None
-    success: bool | None = None
-
-
-class _EventAccumulator(BaseModel):
-    """Mutable accumulator for stream events."""
-
-    response_parts: list[str] = Field(default_factory=list)
-    tool_calls: list[_ToolCallEntry] = Field(default_factory=list)
-    tool_calls_by_id: dict[str, _ToolCallEntry] = Field(default_factory=dict)
-    prompt_tokens: int = 0
-    completion_tokens: int = 0
-    total_tokens: int = 0
-
-
-def _process_event(event: object, acc: _EventAccumulator) -> str | None:
-    """Process a single stream event and return error_msg if StreamError.
-
-    Uses structural pattern matching for dispatch per project guidelines.
-    """
-    match event:
-        case StreamTextDelta(delta=delta):
-            acc.response_parts.append(delta)
-        case StreamToolInputAvailable() as e:
-            entry = _ToolCallEntry(
-                tool_call_id=e.toolCallId,
-                tool_name=e.toolName,
-                input=e.input,
-            )
-            acc.tool_calls.append(entry)
-            acc.tool_calls_by_id[e.toolCallId] = entry
-        case StreamToolOutputAvailable() as e:
-            if tc := acc.tool_calls_by_id.get(e.toolCallId):
-                tc.output = e.output
-                tc.success = e.success
-            else:
-                logger.debug(
-                    "Received tool output for unknown tool_call_id: %s",
-                    e.toolCallId,
-                )
-        case StreamUsage() as e:
-            acc.prompt_tokens += e.prompt_tokens
-            acc.completion_tokens += e.completion_tokens
-            acc.total_tokens += e.total_tokens
-        case StreamError(errorText=err):
-            return err
-    return None
-
-
-async def collect_copilot_response(
-    *,
-    session_id: str,
-    message: str,
-    user_id: str,
-    is_user_message: bool = True,
-    permissions: "CopilotPermissions | None" = None,
-) -> CopilotResult:
-    """Consume :func:`stream_chat_completion_sdk` and return aggregated results.
-
-    Registers with the stream registry so the frontend can connect via SSE
-    and receive real-time updates while the AutoPilot block is executing.
-
-    Args:
-        session_id: Chat session to use.
-        message: The user message / prompt.
-        user_id: Authenticated user ID.
-        is_user_message: Whether this is a user-initiated message.
-        permissions: Optional capability filter.  When provided, restricts
-            which tools and blocks the copilot may use during this execution.
-
-    Returns:
-        A :class:`CopilotResult` with the aggregated response text,
-        tool calls, and token usage.
-
-    Raises:
-        RuntimeError: If the stream yields a ``StreamError`` event.
-    """
-    turn_id = str(uuid.uuid4())
-    async with _registry_session(session_id, user_id, turn_id) as handle:
-        try:
-            raw_stream = stream_chat_completion_sdk(
-                session_id=session_id,
-                message=message,
-                is_user_message=is_user_message,
-                user_id=user_id,
-                permissions=permissions,
-            )
-            published_stream = stream_registry.stream_and_publish(
-                session_id=session_id,
-                turn_id=handle.publish_turn_id,
-                stream=raw_stream,
-            )
-
-            acc = _EventAccumulator()
-            async for event in published_stream:
-                if err := _process_event(event, acc):
-                    handle.error_msg = err
-                    # stream_and_publish skips StreamError events, so
-                    # mark_session_completed must publish the error to Redis.
-                    handle.error_already_published = False
-                    raise RuntimeError(f"Copilot error: {err}")
-        except Exception:
-            if handle.error_msg is None:
-                handle.error_msg = "AutoPilot execution failed"
-            raise
-
-    result = CopilotResult()
-    result.response_text = "".join(acc.response_parts)
-    result.tool_calls = [tc.model_dump() for tc in acc.tool_calls]
-    result.prompt_tokens = acc.prompt_tokens
-    result.completion_tokens = acc.completion_tokens
-    result.total_tokens = acc.total_tokens
-    return result

autogpt_platform/backend/backend/copilot/sdk/collect_test.py

@@ -1,177 +0,0 @@
-"""Tests for collect_copilot_response stream registry integration."""
-
-from unittest.mock import AsyncMock, patch
-
-import pytest
-
-from backend.copilot.response_model import (
-    StreamError,
-    StreamFinish,
-    StreamTextDelta,
-    StreamToolInputAvailable,
-    StreamToolOutputAvailable,
-    StreamUsage,
-)
-from backend.copilot.sdk.collect import collect_copilot_response
-
-
-def _mock_stream_fn(*events):
-    """Return a callable that returns an async generator."""
-
-    async def _gen(**_kwargs):
-        for e in events:
-            yield e
-
-    return _gen
-
-
-@pytest.fixture
-def mock_registry():
-    """Patch stream_registry module used by collect."""
-    with patch("backend.copilot.sdk.collect.stream_registry") as m:
-        m.create_session = AsyncMock()
-        m.publish_chunk = AsyncMock()
-        m.mark_session_completed = AsyncMock()
-
-        # stream_and_publish: pass-through that also publishes (real logic)
-        # We re-implement the pass-through here so the event loop works,
-        # but still track publish_chunk calls via the mock.
-        async def _stream_and_publish(session_id, turn_id, stream):
-            async for event in stream:
-                if turn_id and not isinstance(event, (StreamFinish, StreamError)):
-                    await m.publish_chunk(turn_id, event)
-                yield event
-
-        m.stream_and_publish = _stream_and_publish
-        yield m
-
-
-@pytest.fixture
-def stream_fn_patch():
-    """Helper to patch stream_chat_completion_sdk."""
-
-    def _patch(events):
-        return patch(
-            "backend.copilot.sdk.collect.stream_chat_completion_sdk",
-            new=_mock_stream_fn(*events),
-        )
-
-    return _patch
-
-
-@pytest.mark.asyncio
-async def test_stream_registry_called_on_success(mock_registry, stream_fn_patch):
-    """Stream registry create/publish/complete are called correctly on success."""
-    events = [
-        StreamTextDelta(id="t1", delta="Hello "),
-        StreamTextDelta(id="t1", delta="world"),
-        StreamUsage(prompt_tokens=10, completion_tokens=5, total_tokens=15),
-        StreamFinish(),
-    ]
-
-    with stream_fn_patch(events):
-        result = await collect_copilot_response(
-            session_id="test-session",
-            message="hi",
-            user_id="user-1",
-        )
-
-    assert result.response_text == "Hello world"
-    assert result.total_tokens == 15
-
-    mock_registry.create_session.assert_awaited_once()
-    # StreamFinish should NOT be published (mark_session_completed does it)
-    published_types = [
-        type(call.args[1]).__name__
-        for call in mock_registry.publish_chunk.call_args_list
-    ]
-    assert "StreamFinish" not in published_types
-    assert "StreamTextDelta" in published_types
-
-    mock_registry.mark_session_completed.assert_awaited_once()
-    _, kwargs = mock_registry.mark_session_completed.call_args
-    assert kwargs.get("error_message") is None
-
-
-@pytest.mark.asyncio
-async def test_stream_registry_error_on_stream_error(mock_registry, stream_fn_patch):
-    """mark_session_completed receives error message when StreamError occurs."""
-    events = [
-        StreamTextDelta(id="t1", delta="partial"),
-        StreamError(errorText="something broke"),
-    ]
-
-    with stream_fn_patch(events):
-        with pytest.raises(RuntimeError, match="something broke"):
-            await collect_copilot_response(
-                session_id="test-session",
-                message="hi",
-                user_id="user-1",
-            )
-
-    _, kwargs = mock_registry.mark_session_completed.call_args
-    assert kwargs.get("error_message") == "something broke"
-    # stream_and_publish skips StreamError, so mark_session_completed must
-    # publish it (skip_error_publish=False).
-    assert kwargs.get("skip_error_publish") is False
-
-    # StreamError should NOT be published via publish_chunk — mark_session_completed
-    # handles it to avoid double-publication.
-    published_types = [
-        type(call.args[1]).__name__
-        for call in mock_registry.publish_chunk.call_args_list
-    ]
-    assert "StreamError" not in published_types
-
-
-@pytest.mark.asyncio
-async def test_graceful_degradation_when_create_session_fails(
-    mock_registry, stream_fn_patch
-):
-    """AutoPilot still works when stream registry create_session raises."""
-    events = [
-        StreamTextDelta(id="t1", delta="works"),
-        StreamFinish(),
-    ]
-    mock_registry.create_session = AsyncMock(side_effect=ConnectionError("Redis down"))
-
-    with stream_fn_patch(events):
-        result = await collect_copilot_response(
-            session_id="test-session",
-            message="hi",
-            user_id="user-1",
-        )
-
-    assert result.response_text == "works"
-    # publish_chunk should NOT be called because turn_id was cleared
-    mock_registry.publish_chunk.assert_not_awaited()
-    # mark_session_completed IS still called to clean up any partial state
-    mock_registry.mark_session_completed.assert_awaited_once()
-
-
-@pytest.mark.asyncio
-async def test_tool_calls_published_and_collected(mock_registry, stream_fn_patch):
-    """Tool call events are both published to registry and collected in result."""
-    events = [
-        StreamToolInputAvailable(
-            toolCallId="tc-1", toolName="read_file", input={"path": "/tmp"}
-        ),
-        StreamToolOutputAvailable(
-            toolCallId="tc-1", output="file contents", success=True
-        ),
-        StreamTextDelta(id="t1", delta="done"),
-        StreamFinish(),
-    ]
-
-    with stream_fn_patch(events):
-        result = await collect_copilot_response(
-            session_id="test-session",
-            message="hi",
-            user_id="user-1",
-        )
-
-    assert len(result.tool_calls) == 1
-    assert result.tool_calls[0]["tool_name"] == "read_file"
-    assert result.tool_calls[0]["output"] == "file contents"
-    assert result.tool_calls[0]["success"] is True
-    assert result.response_text == "done"