chore(deps): bump actions/checkout from 4 to 6

Bumps [actions/checkout](https://github.com/actions/checkout) from 4 to 6.
- [Release notes](https://github.com/actions/checkout/releases)
- [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md)
- [Commits](https://github.com/actions/checkout/compare/v4...v6)

---
updated-dependencies:
- dependency-name: actions/checkout
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>

.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
 
@@ -140,69 +88,21 @@ 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:
+2. Check for new comments (all three sources):
 ```bash
-gh pr view {N} --repo Significant-Gravitas/AutoGPT --json mergeable --jq '.mergeable'
+gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments      # inline review comments
+gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments     # PR conversation comments
+gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews       # top-level reviews
 ```
-   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.
+   Compare against previously seen comments to detect new ones.
 
-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):**
+3. **React to whichever changed first:**
 
 | 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.

.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

@@ -1,558 +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: "1.0.0"
----
-
-# 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.
-
-## 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]
-
-## UI Tests (if applicable)
-1. [Page/component] — [interaction to test]
-
-## Negative Tests
-1. [What should NOT happen]
-```
-
-**Be critical** — include edge cases, error paths, and security checks.
-
-## 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:
-
-```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 .
-```
-
-### 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. Name them sequentially with descriptive names:
-
-```bash
-agent-browser --session-name pr-test screenshot $RESULTS_DIR/{NN}-{description}.png
-# Examples:
-# $RESULTS_DIR/01-login-page.png
-# $RESULTS_DIR/02-builder-with-block.png
-# $RESULTS_DIR/03-copilot-response.png
-# $RESULTS_DIR/04-agent-execution-result.png
-# $RESULTS_DIR/05-error-state.png
-```
-
-**Aim for at least one screenshot per test scenario.** More is better — screenshots are the primary evidence that tests were actually run.
-
-## 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 summary table:
-
-| # | Scenario | Result |
-|---|----------|--------|
-| 1 | {name} | PASS/FAIL |
-| 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
-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 |
-| 2 | Builder block addition | PASS |
-| 3 | Copilot chat | FAIL |"
-# ... 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.
-
-```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
-TREE_JSON='['
-FIRST=true
-for img in $RESULTS_DIR/*.png; do
-  BASENAME=$(basename "$img")
-  B64=$(base64 < "$img")
-  BLOB_SHA=$(gh api "repos/${REPO}/git/blobs" -f content="$B64" -f encoding="base64" --jq '.sha')
-  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 SCREENSHOT_EXPLANATIONS and TEST_RESULTS_TABLE from Step 6
-
-IMAGE_MARKDOWN=""
-for img in $RESULTS_DIR/*.png; do
-  BASENAME=$(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($i,2))}1')
-  EXPLANATION="${SCREENSHOT_EXPLANATIONS[$BASENAME]}"
-  IMAGE_MARKDOWN="${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=$(mktemp)
-cat > "$COMMENT_FILE" <<INNEREOF
-## 🧪 E2E Test Report
-
-| # | Scenario | Result |
-|---|----------|--------|
-${TEST_RESULTS_TABLE}
-
-${IMAGE_MARKDOWN}
-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
-2. Every screenshot rendered inline (not just linked)
-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, after finding a bug:
-
-1. Identify the root cause in the code
-2. Fix it in the worktree
-3. Rebuild the affected service: `cd $PLATFORM_DIR && docker compose up --build -d {service_name}`
-4. Re-test the scenario
-5. If fix works, commit and push:
-   ```bash
-   cd $WORKTREE_PATH
-   git add -A
-   git commit -m "fix: {description of fix}"
-   git push
-   ```
-6. Continue testing remaining scenarios
-7. After all fixes, run the full test suite again to ensure no regressions
-
-### Fix loop (like pr-address)
-
-```text
-test scenario → find bug → fix code → rebuild service → re-test
-→ repeat until all scenarios pass
-→ commit + push all fixes
-→ run full re-test to verify
-```
-
-## 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.

.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/classic-autogpt-ci.yml

@@ -61,7 +61,7 @@ jobs:
       #   See: https://github.com/actions/runner/issues/598#issuecomment-2011890429
 
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
           submodules: true

.github/workflows/classic-autogpt-docker-cache-clean.yml

@@ -16,7 +16,7 @@ jobs:
         build-type: [release, dev]
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v3

.github/workflows/classic-autogpt-docker-ci.yml

@@ -35,7 +35,7 @@ jobs:
         build-type: [release, dev]
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
@@ -101,7 +101,7 @@ jobs:
 
     steps:
       - name: Check out repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           submodules: true
 

.github/workflows/classic-autogpt-docker-release.yml

@@ -20,7 +20,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Log in to Docker hub
         uses: docker/login-action@v3

.github/workflows/classic-autogpts-ci.yml

@@ -44,7 +44,7 @@ jobs:
       min-python-version: '3.10'
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
           submodules: true

.github/workflows/classic-benchmark-ci.yml

@@ -42,7 +42,7 @@ jobs:
         working-directory: classic/benchmark
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
           submodules: true
@@ -114,7 +114,7 @@ jobs:
     timeout-minutes: 20
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
           submodules: true

.github/workflows/classic-benchmark_publish_package.yml

@@ -10,7 +10,7 @@ jobs:
       contents: write
     steps:
     - name: Checkout repository
-      uses: actions/checkout@v4
+      uses: actions/checkout@v6
       with:
         submodules: true
         fetch-depth: 0

.github/workflows/classic-forge-ci.yml

@@ -63,7 +63,7 @@ jobs:
       #   See: https://github.com/actions/runner/issues/598#issuecomment-2011890429
 
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
           submodules: true

.github/workflows/classic-frontend-ci.yml

@@ -25,7 +25,7 @@ jobs:
 
     steps:
       - name: Checkout Repo
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Setup Flutter
         uses: subosito/flutter-action@v2

.github/workflows/classic-python-checks.yml

@@ -33,7 +33,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - id: changes-in
         name: Determine affected subprojects
@@ -68,7 +68,7 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
@@ -120,7 +120,7 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 

.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
 

.github/workflows/pr-overlap-check.yml

@@ -16,7 +16,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0  # Need full history for merge testing
 

autogpt_platform/CLAUDE.md

@@ -55,37 +55,16 @@ AutoGPT Platform is a monorepo containing:
 - Create the PR against the `dev` branch of the repository.
 - 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"},
-    {file = "ruff-0.15.7-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dce0896488562f09a27b9c91b1f58a097457143931f3c4d519690dea54e624c5"},
-    {file = "ruff-0.15.7-py3-none-manylinux_2_31_riscv64.whl", hash = "sha256:1852ce241d2bc89e5dc823e03cff4ce73d816b5c6cdadd27dbfe7b03217d2a12"},
-    {file = "ruff-0.15.7-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:5f3e4b221fb4bd293f79912fc5e93a9063ebd6d0dcbd528f91b89172a9b8436c"},
-    {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"},
-    {file = "ruff-0.15.7-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:112c1fa316a558bb34319282c1200a8bf0495f1b735aeb78bfcb2991e6087580"},
-    {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

autogpt_platform/backend/CLAUDE.md

@@ -85,30 +85,6 @@ 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

@@ -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/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/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

@@ -60,6 +60,7 @@ from backend.copilot.tools.models import (
 )
 from backend.copilot.tracking import track_user_message
 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 NotFoundError
 
@@ -894,6 +895,36 @@ async def session_assign_user(
     return {"status": "ok"}
 
 
+# ========== Suggested Prompts ==========
+
+
+class SuggestedPromptsResponse(BaseModel):
+    """Response model for user-specific suggested prompts."""
+
+    prompts: list[str]
+
+
+@router.get(
+    "/suggested-prompts",
+    dependencies=[Security(auth.requires_user)],
+)
+async def get_suggested_prompts(
+    user_id: Annotated[str, Security(auth.get_user_id)],
+) -> SuggestedPromptsResponse:
+    """
+    Get LLM-generated suggested prompts for the authenticated user.
+
+    Returns personalized quick-action prompts based on the user's
+    business understanding. Returns an empty list if no custom prompts
+    are available.
+    """
+    understanding = await get_business_understanding(user_id)
+    if understanding is None:
+        return SuggestedPromptsResponse(prompts=[])
+
+    return SuggestedPromptsResponse(prompts=understanding.suggested_prompts)
+
+
 # ========== Configuration ==========
 
 

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

@@ -1,7 +1,7 @@
-"""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
+from unittest.mock import AsyncMock, MagicMock
 
 import fastapi
 import fastapi.testclient
@@ -400,3 +400,62 @@ def test_usage_rejects_unauthenticated_request() -> None:
     response = unauthenticated_client.get("/usage")
 
     assert response.status_code == 401
+
+
+# ─── Suggested prompts endpoint ──────────────────────────────────────
+
+
+def _mock_get_business_understanding(
+    mocker: pytest_mock.MockerFixture,
+    *,
+    return_value=None,
+):
+    """Mock get_business_understanding."""
+    return mocker.patch(
+        "backend.api.features.chat.routes.get_business_understanding",
+        new_callable=AsyncMock,
+        return_value=return_value,
+    )
+
+
+def test_suggested_prompts_returns_prompts(
+    mocker: pytest_mock.MockerFixture,
+    test_user_id: str,
+) -> None:
+    """User with understanding and prompts gets them back."""
+    mock_understanding = MagicMock()
+    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
+    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 list."""
+    _mock_get_business_understanding(mocker, return_value=None)
+
+    response = client.get("/suggested-prompts")
+
+    assert response.status_code == 200
+    assert response.json() == {"prompts": []}
+
+
+def test_suggested_prompts_empty_prompts(
+    mocker: pytest_mock.MockerFixture,
+    test_user_id: str,
+) -> None:
+    """User with understanding but no prompts gets empty list."""
+    mock_understanding = MagicMock()
+    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() == {"prompts": []}

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"""
 
@@ -1228,21 +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/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)

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

@@ -19,6 +19,7 @@ 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.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
@@ -210,22 +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."
@@ -275,10 +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))
@@ -318,6 +312,11 @@ app.include_router(
     tags=["v2", "admin"],
     prefix="/api/executions",
 )
+app.include_router(
+    backend.api.features.admin.user_admin_routes.router,
+    tags=["v2", "admin"],
+    prefix="/api/users",
+)
 app.include_router(
     backend.api.features.executions.review.routes.router,
     tags=["v2", "executions", "review"],

autogpt_platform/backend/backend/blocks/autopilot.py

@@ -1,376 +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.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,
-        )
-
-        # 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
-
-        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,
-    ) -> 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.
-
-        Returns:
-            A tuple of (response_text, tool_calls, history_json, session_id, usage).
-        """
-        from backend.copilot.sdk.collect import collect_copilot_response
-
-        tokens = _check_recursion(max_recursion_depth)
-        try:
-            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,
-            )
-
-            # 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)
-
-    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
-
-        # 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,
-            )
-
-            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])

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
@@ -118,6 +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"
@@ -283,6 +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
@@ -796,19 +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)
@@ -817,53 +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":

autogpt_platform/backend/backend/blocks/smart_decision_maker.py

@@ -61,27 +61,20 @@ class ExecutionParams(BaseModel):
 def _get_tool_requests(entry: dict[str, Any]) -> list[str]:
     """
     Return a list of tool_call_ids if the entry is a tool request.
-    Supports OpenAI Chat Completions, Responses API, and Anthropic formats.
+    Supports both OpenAI and Anthropics formats.
     """
     tool_call_ids = []
-
-    # OpenAI Responses API: function_call items have type="function_call"
-    if entry.get("type") == "function_call":
-        if call_id := entry.get("call_id"):
-            tool_call_ids.append(call_id)
-        return tool_call_ids
-
     if entry.get("role") != "assistant":
         return tool_call_ids
 
-    # OpenAI Chat Completions: check for tool_calls in the entry.
+    # OpenAI: check for tool_calls in the entry.
     calls = entry.get("tool_calls")
     if isinstance(calls, list):
         for call in calls:
             if tool_id := call.get("id"):
                 tool_call_ids.append(tool_id)
 
-    # Anthropic: check content items for tool_use type.
+    # Anthropics: check content items for tool_use type.
     content = entry.get("content")
     if isinstance(content, list):
         for item in content:
@@ -96,22 +89,16 @@ def _get_tool_requests(entry: dict[str, Any]) -> list[str]:
 def _get_tool_responses(entry: dict[str, Any]) -> list[str]:
     """
     Return a list of tool_call_ids if the entry is a tool response.
-    Supports OpenAI Chat Completions, Responses API, and Anthropic formats.
+    Supports both OpenAI and Anthropics formats.
     """
     tool_call_ids: list[str] = []
 
-    # OpenAI Responses API: function_call_output items
-    if entry.get("type") == "function_call_output":
-        if call_id := entry.get("call_id"):
-            tool_call_ids.append(str(call_id))
-        return tool_call_ids
-
-    # OpenAI Chat Completions: a tool response message with role "tool".
+    # OpenAI: a tool response message with role "tool" and key "tool_call_id".
     if entry.get("role") == "tool":
         if tool_call_id := entry.get("tool_call_id"):
             tool_call_ids.append(str(tool_call_id))
 
-    # Anthropic: check content items for tool_result type.
+    # Anthropics: check content items for tool_result type.
     if entry.get("role") == "user":
         content = entry.get("content")
         if isinstance(content, list):
@@ -124,16 +111,14 @@ def _get_tool_responses(entry: dict[str, Any]) -> list[str]:
     return tool_call_ids
 
 
-def _create_tool_response(
-    call_id: str, output: Any, *, responses_api: bool = False
-) -> dict[str, Any]:
+def _create_tool_response(call_id: str, output: Any) -> dict[str, Any]:
     """
-    Create a tool response message for OpenAI, Anthropic, or OpenAI Responses API,
-    based on the tool_id format and the responses_api flag.
+    Create a tool response message for either OpenAI or Anthropics,
+    based on the tool_id format.
     """
     content = output if isinstance(output, str) else json.dumps(output)
 
-    # Anthropic format: tool IDs typically start with "toolu_"
+    # Anthropics format: tool IDs typically start with "toolu_"
     if call_id.startswith("toolu_"):
         return {
             "role": "user",
@@ -143,11 +128,8 @@ def _create_tool_response(
             ],
         }
 
-    # OpenAI Responses API format
-    if responses_api:
-        return {"type": "function_call_output", "call_id": call_id, "output": content}
-
-    # OpenAI Chat Completions format (default fallback)
+    # OpenAI format: tool IDs typically start with "call_".
+    # Or default fallback (if the tool_id doesn't match any known prefix)
     return {"role": "tool", "tool_call_id": call_id, "content": content}
 
 
@@ -195,19 +177,10 @@ def _combine_tool_responses(tool_outputs: list[dict[str, Any]]) -> list[dict[str
     return tool_outputs
 
 
-def _convert_raw_response_to_dict(
-    raw_response: Any,
-) -> dict[str, Any] | list[dict[str, Any]]:
+def _convert_raw_response_to_dict(raw_response: Any) -> dict[str, Any]:
     """
     Safely convert raw_response to dictionary format for conversation history.
     Handles different response types from different LLM providers.
-
-    For the OpenAI Responses API, the raw_response is the entire Response
-    object.  Its ``output`` items (messages, function_calls) are extracted
-    individually so they can be used as valid input items on the next call.
-    Returns a **list** of dicts in that case.
-
-    For Chat Completions / Anthropic / Ollama, returns a single dict.
     """
     if isinstance(raw_response, str):
         # Ollama returns a string, convert to dict format
@@ -215,28 +188,11 @@ def _convert_raw_response_to_dict(
     elif isinstance(raw_response, dict):
         # Already a dict (from tests or some providers)
         return raw_response
-    elif _is_responses_api_object(raw_response):
-        # OpenAI Responses API: extract individual output items
-        items = [json.to_dict(item) for item in raw_response.output]
-        return items if items else [{"role": "assistant", "content": ""}]
     else:
-        # Chat Completions / Anthropic return message objects
+        # OpenAI/Anthropic return objects, convert with json.to_dict
         return json.to_dict(raw_response)
 
 
-def _is_responses_api_object(obj: Any) -> bool:
-    """Detect an OpenAI Responses API Response object.
-
-    These have ``object == "response"`` and an ``output`` list, but no
-    ``role`` attribute (unlike ChatCompletionMessage).
-    """
-    return (
-        getattr(obj, "object", None) == "response"
-        and hasattr(obj, "output")
-        and not hasattr(obj, "role")
-    )
-
-
 def get_pending_tool_calls(conversation_history: list[Any] | None) -> dict[str, int]:
     """
     All the tool calls entry in the conversation history requires a response.
@@ -798,34 +754,19 @@ class SmartDecisionMakerBlock(Block):
         self, prompt: list[dict], response, tool_outputs: list | None = None
     ):
         """Update conversation history with response and tool outputs."""
-        converted = _convert_raw_response_to_dict(response.raw_response)
+        # Don't add separate reasoning message with tool calls (breaks Anthropic's tool_use->tool_result pairing)
+        assistant_message = _convert_raw_response_to_dict(response.raw_response)
+        has_tool_calls = isinstance(assistant_message.get("content"), list) and any(
+            item.get("type") == "tool_use"
+            for item in assistant_message.get("content", [])
+        )
 
-        if isinstance(converted, list):
-            # Responses API: output items are already individual dicts
-            has_tool_calls = any(
-                item.get("type") == "function_call" for item in converted
+        if response.reasoning and not has_tool_calls:
+            prompt.append(
+                {"role": "assistant", "content": f"[Reasoning]: {response.reasoning}"}
             )
-            if response.reasoning and not has_tool_calls:
-                prompt.append(
-                    {
-                        "role": "assistant",
-                        "content": f"[Reasoning]: {response.reasoning}",
-                    }
-                )
-            prompt.extend(converted)
-        else:
-            # Chat Completions / Anthropic: single assistant message dict
-            has_tool_calls = isinstance(converted.get("content"), list) and any(
-                item.get("type") == "tool_use" for item in converted.get("content", [])
-            )
-            if response.reasoning and not has_tool_calls:
-                prompt.append(
-                    {
-                        "role": "assistant",
-                        "content": f"[Reasoning]: {response.reasoning}",
-                    }
-                )
-            prompt.append(converted)
+
+        prompt.append(assistant_message)
 
         if tool_outputs:
             prompt.extend(tool_outputs)
@@ -835,8 +776,6 @@ class SmartDecisionMakerBlock(Block):
         tool_info: ToolInfo,
         execution_params: ExecutionParams,
         execution_processor: "ExecutionProcessor",
-        *,
-        responses_api: bool = False,
     ) -> dict:
         """Execute a single tool using the execution manager for proper integration."""
         # Lazy imports to avoid circular dependencies
@@ -929,17 +868,13 @@ class SmartDecisionMakerBlock(Block):
                 if node_outputs
                 else "Tool executed successfully"
             )
-            return _create_tool_response(
-                tool_call.id, tool_response_content, responses_api=responses_api
-            )
+            return _create_tool_response(tool_call.id, tool_response_content)
 
         except Exception as e:
-            logger.warning(f"Tool execution with manager failed: {e}")
+            logger.error(f"Tool execution with manager failed: {e}")
             # Return error response
             return _create_tool_response(
-                tool_call.id,
-                f"Tool execution failed: {str(e)}",
-                responses_api=responses_api,
+                tool_call.id, f"Tool execution failed: {str(e)}"
             )
 
     async def _execute_tools_agent_mode(
@@ -960,7 +895,6 @@ class SmartDecisionMakerBlock(Block):
         """Execute tools in agent mode with a loop until finished."""
         max_iterations = input_data.agent_mode_max_iterations
         iteration = 0
-        use_responses_api = input_data.model.metadata.provider == "openai"
 
         # Execution parameters for tool execution
         execution_params = ExecutionParams(
@@ -1017,19 +951,14 @@ class SmartDecisionMakerBlock(Block):
             for tool_info in processed_tools:
                 try:
                     tool_response = await self._execute_single_tool_with_manager(
-                        tool_info,
-                        execution_params,
-                        execution_processor,
-                        responses_api=use_responses_api,
+                        tool_info, execution_params, execution_processor
                     )
                     tool_outputs.append(tool_response)
                 except Exception as e:
                     logger.error(f"Tool execution failed: {e}")
                     # Create error response for the tool
                     error_response = _create_tool_response(
-                        tool_info.tool_call.id,
-                        f"Error: {str(e)}",
-                        responses_api=use_responses_api,
+                        tool_info.tool_call.id, f"Error: {str(e)}"
                     )
                     tool_outputs.append(error_response)
 
@@ -1091,17 +1020,11 @@ class SmartDecisionMakerBlock(Block):
         if pending_tool_calls and input_data.last_tool_output is None:
             raise ValueError(f"Tool call requires an output for {pending_tool_calls}")
 
-        use_responses_api = input_data.model.metadata.provider == "openai"
-
         tool_output = []
         if pending_tool_calls and input_data.last_tool_output is not None:
             first_call_id = next(iter(pending_tool_calls.keys()))
             tool_output.append(
-                _create_tool_response(
-                    first_call_id,
-                    input_data.last_tool_output,
-                    responses_api=use_responses_api,
-                )
+                _create_tool_response(first_call_id, input_data.last_tool_output)
             )
 
             prompt.extend(tool_output)
@@ -1133,9 +1056,7 @@ class SmartDecisionMakerBlock(Block):
             )
 
         if input_data.sys_prompt and not any(
-            p.get("role") == "system"
-            and isinstance(p.get("content"), str)
-            and p["content"].startswith(MAIN_OBJECTIVE_PREFIX)
+            p["role"] == "system" and p["content"].startswith(MAIN_OBJECTIVE_PREFIX)
             for p in prompt
         ):
             prompt.append(
@@ -1146,9 +1067,7 @@ class SmartDecisionMakerBlock(Block):
             )
 
         if input_data.prompt and not any(
-            p.get("role") == "user"
-            and isinstance(p.get("content"), str)
-            and p["content"].startswith(MAIN_OBJECTIVE_PREFIX)
+            p["role"] == "user" and p["content"].startswith(MAIN_OBJECTIVE_PREFIX)
             for p in prompt
         ):
             prompt.append(
@@ -1256,26 +1175,11 @@ class SmartDecisionMakerBlock(Block):
                 )
                 yield emit_key, arg_value
 
-        converted = _convert_raw_response_to_dict(response.raw_response)
-
-        # Check for tool calls to avoid inserting reasoning between tool pairs
-        if isinstance(converted, list):
-            has_tool_calls = any(
-                item.get("type") == "function_call" for item in converted
-            )
-        else:
-            has_tool_calls = isinstance(converted.get("content"), list) and any(
-                item.get("type") == "tool_use" for item in converted.get("content", [])
-            )
-
-        if response.reasoning and not has_tool_calls:
+        if response.reasoning:
             prompt.append(
                 {"role": "assistant", "content": f"[Reasoning]: {response.reasoning}"}
             )
 
-        if isinstance(converted, list):
-            prompt.extend(converted)
-        else:
-            prompt.append(converted)
+        prompt.append(_convert_raw_response_to_dict(response.raw_response))
 
         yield "conversations", prompt

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_llm.py

@@ -13,17 +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,
@@ -270,17 +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(

autogpt_platform/backend/backend/copilot/config.py

@@ -148,7 +148,7 @@ 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.",

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/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"`.
@@ -54,53 +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"
-  }}]
-}}
+  }]
+}
 ```
 
 ### 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"])`.
 """
 
 
@@ -113,7 +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.
 
@@ -128,7 +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)
@@ -138,12 +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}
@@ -164,16 +159,12 @@ a local file under `~/.claude/projects/.../tool-results/`. To read these files,
 always use `read_file` or `Read` (NOT `read_workspace_file`).
 `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",
@@ -191,11 +182,7 @@ 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",
@@ -210,7 +197,6 @@ 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/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

@@ -24,14 +24,10 @@ 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
 
 __all__ = [
-    "CopilotResult",
-    "collect_copilot_response",
     "stream_chat_completion_sdk",
     "create_copilot_mcp_server",
 ]
@@ -39,8 +35,6 @@ __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/collect.py

@@ -1,108 +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
-
-from typing import Any
-
-
-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
-
-
-async def collect_copilot_response(
-    *,
-    session_id: str,
-    message: str,
-    user_id: str,
-    is_user_message: bool = True,
-) -> CopilotResult:
-    """Consume :func:`stream_chat_completion_sdk` and return aggregated results.
-
-    This is the recommended entry-point for callers that need a simple
-    request-response interface (e.g. the AutoPilot block) rather than
-    streaming individual events.  It avoids duplicating the event-collection
-    logic and does NOT wrap the stream in ``asyncio.timeout`` — the SDK
-    manages its own heartbeat-based timeouts internally.
-
-    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.
-
-    Returns:
-        A :class:`CopilotResult` with the aggregated response text,
-        tool calls, and token usage.
-
-    Raises:
-        RuntimeError: If the stream yields a ``StreamError`` event.
-    """
-    from backend.copilot.response_model import (
-        StreamError,
-        StreamTextDelta,
-        StreamToolInputAvailable,
-        StreamToolOutputAvailable,
-        StreamUsage,
-    )
-
-    from .service import stream_chat_completion_sdk
-
-    result = CopilotResult()
-    response_parts: list[str] = []
-    tool_calls_by_id: dict[str, dict[str, Any]] = {}
-
-    async for event in stream_chat_completion_sdk(
-        session_id=session_id,
-        message=message,
-        is_user_message=is_user_message,
-        user_id=user_id,
-    ):
-        if isinstance(event, StreamTextDelta):
-            response_parts.append(event.delta)
-        elif isinstance(event, StreamToolInputAvailable):
-            entry: dict[str, Any] = {
-                "tool_call_id": event.toolCallId,
-                "tool_name": event.toolName,
-                "input": event.input,
-                "output": None,
-                "success": None,
-            }
-            result.tool_calls.append(entry)
-            tool_calls_by_id[event.toolCallId] = entry
-        elif isinstance(event, StreamToolOutputAvailable):
-            if tc := tool_calls_by_id.get(event.toolCallId):
-                tc["output"] = event.output
-                tc["success"] = event.success
-        elif isinstance(event, StreamUsage):
-            result.prompt_tokens += event.prompt_tokens
-            result.completion_tokens += event.completion_tokens
-            result.total_tokens += event.total_tokens
-        elif isinstance(event, StreamError):
-            raise RuntimeError(f"Copilot error: {event.errorText}")
-
-    result.response_text = "".join(response_parts)
-    return result

autogpt_platform/backend/backend/copilot/sdk/compaction.py

@@ -12,7 +12,6 @@ import asyncio
 import logging
 import uuid
 from dataclasses import dataclass, field
-from typing import Any
 
 from ..constants import COMPACTION_DONE_MSG, COMPACTION_TOOL_NAME
 from ..model import ChatMessage, ChatSession
@@ -120,12 +119,14 @@ def filter_compaction_messages(
     filtered: list[ChatMessage] = []
     for msg in messages:
         if msg.role == "assistant" and msg.tool_calls:
-            real_calls: list[dict[str, Any]] = []
             for tc in msg.tool_calls:
                 if tc.get("function", {}).get("name") == COMPACTION_TOOL_NAME:
                     compaction_ids.add(tc.get("id", ""))
-                else:
-                    real_calls.append(tc)
+            real_calls = [
+                tc
+                for tc in msg.tool_calls
+                if tc.get("function", {}).get("name") != COMPACTION_TOOL_NAME
+            ]
             if not real_calls and not msg.content:
                 continue
         if msg.role == "tool" and msg.tool_call_id in compaction_ids:
@@ -221,7 +222,6 @@ class CompactionTracker:
 
     def reset_for_query(self) -> None:
         """Reset per-query state before a new SDK query."""
-        self._compact_start.clear()
         self._done = False
         self._start_emitted = False
         self._tool_call_id = ""

autogpt_platform/backend/backend/copilot/sdk/conftest.py

@@ -1,54 +0,0 @@
-"""Shared test fixtures for copilot SDK tests."""
-
-from __future__ import annotations
-
-from unittest.mock import patch
-from uuid import uuid4
-
-import pytest
-
-from backend.util import json
-
-
-@pytest.fixture()
-def mock_chat_config():
-    """Mock ChatConfig so compact_transcript tests skip real config lookup."""
-    with patch(
-        "backend.copilot.config.ChatConfig",
-        return_value=type("Cfg", (), {"model": "m", "api_key": "k", "base_url": "u"})(),
-    ):
-        yield
-
-
-def build_test_transcript(pairs: list[tuple[str, str]]) -> str:
-    """Build a minimal valid JSONL transcript from (role, content) pairs.
-
-    Use this helper in any copilot SDK test that needs a well-formed
-    transcript without hitting the real storage layer.
-    """
-    lines: list[str] = []
-    last_uuid: str | None = None
-    for role, content in pairs:
-        uid = str(uuid4())
-        entry_type = "assistant" if role == "assistant" else "user"
-        msg: dict = {"role": role, "content": content}
-        if role == "assistant":
-            msg.update(
-                {
-                    "model": "",
-                    "id": f"msg_{uid[:8]}",
-                    "type": "message",
-                    "content": [{"type": "text", "text": content}],
-                    "stop_reason": "end_turn",
-                    "stop_sequence": None,
-                }
-            )
-        entry = {
-            "type": entry_type,
-            "uuid": uid,
-            "parentUuid": last_uuid,
-            "message": msg,
-        }
-        lines.append(json.dumps(entry, separators=(",", ":")))
-        last_uuid = uid
-    return "\n".join(lines) + "\n"

autogpt_platform/backend/backend/copilot/sdk/prompt_too_long_test.py

@@ -1,651 +0,0 @@
-"""Tests for retry logic and transcript compaction helpers."""
-
-from __future__ import annotations
-
-import asyncio
-from unittest.mock import AsyncMock, patch
-from uuid import uuid4
-
-import pytest
-
-from backend.util import json
-from backend.util.prompt import CompressResult
-
-from .conftest import build_test_transcript as _build_transcript
-from .service import _friendly_error_text, _is_prompt_too_long
-from .transcript import (
-    _flatten_assistant_content,
-    _flatten_tool_result_content,
-    _messages_to_transcript,
-    _run_compression,
-    _transcript_to_messages,
-    compact_transcript,
-    validate_transcript,
-)
-
-# ---------------------------------------------------------------------------
-# _flatten_assistant_content
-# ---------------------------------------------------------------------------
-
-
-class TestFlattenAssistantContent:
-    def test_text_blocks(self):
-        blocks = [
-            {"type": "text", "text": "Hello"},
-            {"type": "text", "text": "World"},
-        ]
-        assert _flatten_assistant_content(blocks) == "Hello\nWorld"
-
-    def test_tool_use_blocks(self):
-        blocks = [{"type": "tool_use", "name": "read_file", "input": {}}]
-        assert _flatten_assistant_content(blocks) == "[tool_use: read_file]"
-
-    def test_mixed_blocks(self):
-        blocks = [
-            {"type": "text", "text": "Let me read that."},
-            {"type": "tool_use", "name": "Read", "input": {"path": "/foo"}},
-        ]
-        result = _flatten_assistant_content(blocks)
-        assert "Let me read that." in result
-        assert "[tool_use: Read]" in result
-
-    def test_raw_strings(self):
-        assert _flatten_assistant_content(["hello", "world"]) == "hello\nworld"
-
-    def test_unknown_block_type_preserved_as_placeholder(self):
-        blocks = [
-            {"type": "text", "text": "See this image:"},
-            {"type": "image", "source": {"type": "base64", "data": "..."}},
-        ]
-        result = _flatten_assistant_content(blocks)
-        assert "See this image:" in result
-        assert "[__image__]" in result
-
-    def test_empty(self):
-        assert _flatten_assistant_content([]) == ""
-
-
-# ---------------------------------------------------------------------------
-# _flatten_tool_result_content
-# ---------------------------------------------------------------------------
-
-
-class TestFlattenToolResultContent:
-    def test_tool_result_with_text(self):
-        blocks = [
-            {
-                "type": "tool_result",
-                "tool_use_id": "123",
-                "content": [{"type": "text", "text": "file contents here"}],
-            }
-        ]
-        assert _flatten_tool_result_content(blocks) == "file contents here"
-
-    def test_tool_result_with_string_content(self):
-        blocks = [{"type": "tool_result", "tool_use_id": "123", "content": "ok"}]
-        assert _flatten_tool_result_content(blocks) == "ok"
-
-    def test_text_block(self):
-        blocks = [{"type": "text", "text": "plain text"}]
-        assert _flatten_tool_result_content(blocks) == "plain text"
-
-    def test_raw_string(self):
-        assert _flatten_tool_result_content(["raw"]) == "raw"
-
-    def test_tool_result_with_none_content(self):
-        """tool_result with content=None should produce empty string."""
-        blocks = [{"type": "tool_result", "tool_use_id": "x", "content": None}]
-        assert _flatten_tool_result_content(blocks) == ""
-
-    def test_tool_result_with_empty_list_content(self):
-        """tool_result with content=[] should produce empty string."""
-        blocks = [{"type": "tool_result", "tool_use_id": "x", "content": []}]
-        assert _flatten_tool_result_content(blocks) == ""
-
-    def test_empty(self):
-        assert _flatten_tool_result_content([]) == ""
-
-    def test_nested_dict_without_text(self):
-        """Dict blocks without text key use json.dumps fallback."""
-        blocks = [
-            {
-                "type": "tool_result",
-                "tool_use_id": "x",
-                "content": [{"type": "image", "source": "data:..."}],
-            }
-        ]
-        result = _flatten_tool_result_content(blocks)
-        assert "image" in result  # json.dumps fallback
-
-    def test_unknown_block_type_preserved_as_placeholder(self):
-        blocks = [{"type": "image", "source": {"type": "base64", "data": "..."}}]
-        result = _flatten_tool_result_content(blocks)
-        assert "[__image__]" in result
-
-
-# ---------------------------------------------------------------------------
-# _transcript_to_messages
-# ---------------------------------------------------------------------------
-
-
-def _make_entry(entry_type: str, role: str, content: str | list, **kwargs) -> str:
-    """Build a JSONL line for testing."""
-    uid = str(uuid4())
-    msg: dict = {"role": role, "content": content}
-    msg.update(kwargs)
-    entry = {
-        "type": entry_type,
-        "uuid": uid,
-        "parentUuid": None,
-        "message": msg,
-    }
-    return json.dumps(entry, separators=(",", ":"))
-
-
-class TestTranscriptToMessages:
-    def test_basic_roundtrip(self):
-        lines = [
-            _make_entry("user", "user", "Hello"),
-            _make_entry("assistant", "assistant", [{"type": "text", "text": "Hi"}]),
-        ]
-        content = "\n".join(lines) + "\n"
-        messages = _transcript_to_messages(content)
-        assert len(messages) == 2
-        assert messages[0] == {"role": "user", "content": "Hello"}
-        assert messages[1] == {"role": "assistant", "content": "Hi"}
-
-    def test_skips_strippable_types(self):
-        """Progress and metadata entries are excluded."""
-        lines = [
-            _make_entry("user", "user", "Hello"),
-            json.dumps(
-                {
-                    "type": "progress",
-                    "uuid": str(uuid4()),
-                    "parentUuid": None,
-                    "message": {"role": "assistant", "content": "..."},
-                }
-            ),
-            _make_entry("assistant", "assistant", [{"type": "text", "text": "Hi"}]),
-        ]
-        content = "\n".join(lines) + "\n"
-        messages = _transcript_to_messages(content)
-        assert len(messages) == 2
-
-    def test_empty_content(self):
-        assert _transcript_to_messages("") == []
-
-    def test_tool_result_content(self):
-        """User entries with tool_result content blocks are flattened."""
-        lines = [
-            _make_entry(
-                "user",
-                "user",
-                [
-                    {
-                        "type": "tool_result",
-                        "tool_use_id": "123",
-                        "content": "tool output",
-                    }
-                ],
-            ),
-        ]
-        content = "\n".join(lines) + "\n"
-        messages = _transcript_to_messages(content)
-        assert len(messages) == 1
-        assert messages[0]["content"] == "tool output"
-
-    def test_malformed_json_lines_skipped(self):
-        """Malformed JSON lines in transcript are silently skipped."""
-        lines = [
-            _make_entry("user", "user", "Hello"),
-            "this is not valid json",
-            _make_entry("assistant", "assistant", [{"type": "text", "text": "Hi"}]),
-        ]
-        content = "\n".join(lines) + "\n"
-        messages = _transcript_to_messages(content)
-        assert len(messages) == 2
-
-    def test_empty_lines_skipped(self):
-        """Empty lines and whitespace-only lines are skipped."""
-        lines = [
-            _make_entry("user", "user", "Hello"),
-            "",
-            "   ",
-            _make_entry("assistant", "assistant", [{"type": "text", "text": "Hi"}]),
-        ]
-        content = "\n".join(lines) + "\n"
-        messages = _transcript_to_messages(content)
-        assert len(messages) == 2
-
-    def test_unicode_content_preserved(self):
-        """Unicode characters survive transcript roundtrip."""
-        lines = [
-            _make_entry("user", "user", "Hello 你好 🌍"),
-            _make_entry(
-                "assistant",
-                "assistant",
-                [{"type": "text", "text": "Bonjour 日本語 émojis 🎉"}],
-            ),
-        ]
-        content = "\n".join(lines) + "\n"
-        messages = _transcript_to_messages(content)
-        assert messages[0]["content"] == "Hello 你好 🌍"
-        assert messages[1]["content"] == "Bonjour 日本語 émojis 🎉"
-
-    def test_entry_without_role_skipped(self):
-        """Entries with missing role in message are skipped."""
-        entry_no_role = json.dumps(
-            {
-                "type": "user",
-                "uuid": str(uuid4()),
-                "parentUuid": None,
-                "message": {"content": "no role here"},
-            }
-        )
-        lines = [
-            entry_no_role,
-            _make_entry("user", "user", "Hello"),
-        ]
-        content = "\n".join(lines) + "\n"
-        messages = _transcript_to_messages(content)
-        assert len(messages) == 1
-        assert messages[0]["content"] == "Hello"
-
-    def test_tool_use_and_result_pairs(self):
-        """Tool use + tool result pairs are properly flattened."""
-        lines = [
-            _make_entry(
-                "assistant",
-                "assistant",
-                [
-                    {"type": "text", "text": "Let me check."},
-                    {"type": "tool_use", "name": "read_file", "input": {"path": "/x"}},
-                ],
-            ),
-            _make_entry(
-                "user",
-                "user",
-                [
-                    {
-                        "type": "tool_result",
-                        "tool_use_id": "abc",
-                        "content": [{"type": "text", "text": "file contents"}],
-                    }
-                ],
-            ),
-        ]
-        content = "\n".join(lines) + "\n"
-        messages = _transcript_to_messages(content)
-        assert len(messages) == 2
-        assert "Let me check." in messages[0]["content"]
-        assert "[tool_use: read_file]" in messages[0]["content"]
-        assert messages[1]["content"] == "file contents"
-
-
-# ---------------------------------------------------------------------------
-# _messages_to_transcript
-# ---------------------------------------------------------------------------
-
-
-class TestMessagesToTranscript:
-    def test_produces_valid_jsonl(self):
-        messages = [
-            {"role": "user", "content": "Hello"},
-            {"role": "assistant", "content": "Hi there"},
-        ]
-        result = _messages_to_transcript(messages)
-        lines = result.strip().split("\n")
-        assert len(lines) == 2
-        for line in lines:
-            parsed = json.loads(line)
-            assert "type" in parsed
-            assert "uuid" in parsed
-            assert "message" in parsed
-
-    def test_assistant_has_proper_structure(self):
-        messages = [{"role": "assistant", "content": "Hello"}]
-        result = _messages_to_transcript(messages)
-        entry = json.loads(result.strip())
-        assert entry["type"] == "assistant"
-        msg = entry["message"]
-        assert msg["role"] == "assistant"
-        assert msg["type"] == "message"
-        assert msg["stop_reason"] == "end_turn"
-        assert isinstance(msg["content"], list)
-        assert msg["content"][0]["type"] == "text"
-
-    def test_user_has_plain_content(self):
-        messages = [{"role": "user", "content": "Hi"}]
-        result = _messages_to_transcript(messages)
-        entry = json.loads(result.strip())
-        assert entry["type"] == "user"
-        assert entry["message"]["content"] == "Hi"
-
-    def test_parent_uuid_chain(self):
-        messages = [
-            {"role": "user", "content": "A"},
-            {"role": "assistant", "content": "B"},
-            {"role": "user", "content": "C"},
-        ]
-        result = _messages_to_transcript(messages)
-        lines = result.strip().split("\n")
-        entries = [json.loads(line) for line in lines]
-        assert entries[0]["parentUuid"] == ""
-        assert entries[1]["parentUuid"] == entries[0]["uuid"]
-        assert entries[2]["parentUuid"] == entries[1]["uuid"]
-
-    def test_empty_messages(self):
-        assert _messages_to_transcript([]) == ""
-
-    def test_output_is_valid_transcript(self):
-        """Output should pass validate_transcript if it has assistant entries."""
-        messages = [
-            {"role": "user", "content": "Hello"},
-            {"role": "assistant", "content": "Hi"},
-        ]
-        result = _messages_to_transcript(messages)
-        assert validate_transcript(result)
-
-    def test_roundtrip_to_messages(self):
-        """Messages → transcript → messages preserves structure."""
-        original = [
-            {"role": "user", "content": "Hello"},
-            {"role": "assistant", "content": "Hi there"},
-            {"role": "user", "content": "How are you?"},
-        ]
-        transcript = _messages_to_transcript(original)
-        restored = _transcript_to_messages(transcript)
-        assert len(restored) == len(original)
-        for orig, rest in zip(original, restored):
-            assert orig["role"] == rest["role"]
-            assert orig["content"] == rest["content"]
-
-
-# ---------------------------------------------------------------------------
-# compact_transcript
-# ---------------------------------------------------------------------------
-
-
-class TestCompactTranscript:
-    @pytest.mark.asyncio
-    async def test_too_few_messages_returns_none(self, mock_chat_config):
-        """compact_transcript returns None when transcript has < 2 messages."""
-        transcript = _build_transcript([("user", "Hello")])
-        result = await compact_transcript(transcript, model="test-model")
-        assert result is None
-
-    @pytest.mark.asyncio
-    async def test_returns_none_when_not_compacted(self, mock_chat_config):
-        """When compress_context says no compaction needed, returns None.
-        The compressor couldn't reduce it, so retrying with the same
-        content would fail identically."""
-        transcript = _build_transcript(
-            [
-                ("user", "Hello"),
-                ("assistant", "Hi there"),
-            ]
-        )
-        mock_result = type(
-            "CompressResult",
-            (),
-            {
-                "was_compacted": False,
-                "messages": [],
-                "original_token_count": 100,
-                "token_count": 100,
-                "messages_summarized": 0,
-                "messages_dropped": 0,
-            },
-        )()
-        with patch(
-            "backend.copilot.sdk.transcript._run_compression",
-            new_callable=AsyncMock,
-            return_value=mock_result,
-        ):
-            result = await compact_transcript(transcript, model="test-model")
-        assert result is None
-
-    @pytest.mark.asyncio
-    async def test_returns_compacted_transcript(self, mock_chat_config):
-        """When compaction succeeds, returns a valid compacted transcript."""
-        transcript = _build_transcript(
-            [
-                ("user", "Hello"),
-                ("assistant", "Hi"),
-                ("user", "More"),
-                ("assistant", "Details"),
-            ]
-        )
-        compacted_msgs = [
-            {"role": "user", "content": "[summary]"},
-            {"role": "assistant", "content": "Summarized response"},
-        ]
-        mock_result = type(
-            "CompressResult",
-            (),
-            {
-                "was_compacted": True,
-                "messages": compacted_msgs,
-                "original_token_count": 500,
-                "token_count": 100,
-                "messages_summarized": 2,
-                "messages_dropped": 0,
-            },
-        )()
-        with patch(
-            "backend.copilot.sdk.transcript._run_compression",
-            new_callable=AsyncMock,
-            return_value=mock_result,
-        ):
-            result = await compact_transcript(transcript, model="test-model")
-        assert result is not None
-        assert validate_transcript(result)
-        msgs = _transcript_to_messages(result)
-        assert len(msgs) == 2
-        assert msgs[1]["content"] == "Summarized response"
-
-    @pytest.mark.asyncio
-    async def test_returns_none_on_compression_failure(self, mock_chat_config):
-        """When _run_compression raises, returns None."""
-        transcript = _build_transcript(
-            [
-                ("user", "Hello"),
-                ("assistant", "Hi"),
-            ]
-        )
-        with patch(
-            "backend.copilot.sdk.transcript._run_compression",
-            new_callable=AsyncMock,
-            side_effect=RuntimeError("LLM unavailable"),
-        ):
-            result = await compact_transcript(transcript, model="test-model")
-        assert result is None
-
-
-# ---------------------------------------------------------------------------
-# _is_prompt_too_long
-# ---------------------------------------------------------------------------
-
-
-class TestIsPromptTooLong:
-    """Unit tests for _is_prompt_too_long pattern matching."""
-
-    def test_prompt_is_too_long(self):
-        err = RuntimeError("prompt is too long for model context")
-        assert _is_prompt_too_long(err) is True
-
-    def test_request_too_large(self):
-        err = Exception("request too large: 250000 tokens")
-        assert _is_prompt_too_long(err) is True
-
-    def test_maximum_context_length(self):
-        err = ValueError("maximum context length exceeded")
-        assert _is_prompt_too_long(err) is True
-
-    def test_context_length_exceeded(self):
-        err = Exception("context_length_exceeded")
-        assert _is_prompt_too_long(err) is True
-
-    def test_input_tokens_exceed(self):
-        err = Exception("input tokens exceed the max_tokens limit")
-        assert _is_prompt_too_long(err) is True
-
-    def test_input_is_too_long(self):
-        err = Exception("input is too long for the model")
-        assert _is_prompt_too_long(err) is True
-
-    def test_content_length_exceeds(self):
-        err = Exception("content length exceeds maximum")
-        assert _is_prompt_too_long(err) is True
-
-    def test_unrelated_error_returns_false(self):
-        err = RuntimeError("network timeout")
-        assert _is_prompt_too_long(err) is False
-
-    def test_auth_error_returns_false(self):
-        err = Exception("authentication failed: invalid API key")
-        assert _is_prompt_too_long(err) is False
-
-    def test_chained_exception_detected(self):
-        """Prompt-too-long error wrapped in another exception is detected."""
-        inner = RuntimeError("prompt is too long")
-        outer = Exception("SDK error")
-        outer.__cause__ = inner
-        assert _is_prompt_too_long(outer) is True
-
-    def test_case_insensitive(self):
-        err = Exception("PROMPT IS TOO LONG")
-        assert _is_prompt_too_long(err) is True
-
-    def test_old_max_tokens_exceeded_not_matched(self):
-        """The old broad 'max_tokens_exceeded' pattern was removed.
-        Only 'input tokens exceed' should match now."""
-        err = Exception("max_tokens_exceeded")
-        assert _is_prompt_too_long(err) is False
-
-
-# ---------------------------------------------------------------------------
-# _run_compression timeout fallback
-# ---------------------------------------------------------------------------
-
-
-class TestRunCompressionTimeout:
-    """Verify _run_compression falls back to truncation when LLM times out."""
-
-    @pytest.mark.asyncio
-    async def test_timeout_falls_back_to_truncation(self):
-        """When compress_context with LLM client times out,
-        _run_compression falls back to truncation (client=None)."""
-        messages = [
-            {"role": "user", "content": "Hello"},
-            {"role": "assistant", "content": "Hi there"},
-        ]
-        truncation_result = CompressResult(
-            messages=messages,
-            was_compacted=False,
-            original_token_count=50,
-            token_count=50,
-            messages_summarized=0,
-            messages_dropped=0,
-        )
-
-        call_args: list[dict] = []
-
-        async def _mock_compress(**kwargs):
-            call_args.append(kwargs)
-            if kwargs.get("client") is not None:
-                # Simulate timeout by raising asyncio.TimeoutError
-                raise asyncio.TimeoutError("LLM compaction timed out")
-            return truncation_result
-
-        with (
-            patch(
-                "backend.copilot.sdk.transcript.get_openai_client",
-                return_value="fake-client",
-            ),
-            patch(
-                "backend.copilot.sdk.transcript.compress_context",
-                side_effect=_mock_compress,
-            ),
-        ):
-            result = await _run_compression(messages, "test-model", "[test]")
-
-        assert result == truncation_result
-        # Should have been called twice: once with client, once without
-        assert len(call_args) == 2
-        assert call_args[0]["client"] is not None  # LLM attempt
-        assert call_args[1]["client"] is None  # truncation fallback
-
-    @pytest.mark.asyncio
-    async def test_no_client_uses_truncation_directly(self):
-        """When no OpenAI client is configured, goes straight to truncation."""
-        messages = [
-            {"role": "user", "content": "Hello"},
-            {"role": "assistant", "content": "Hi there"},
-        ]
-        truncation_result = CompressResult(
-            messages=messages,
-            was_compacted=False,
-            original_token_count=50,
-            token_count=50,
-            messages_summarized=0,
-            messages_dropped=0,
-        )
-
-        with (
-            patch(
-                "backend.copilot.sdk.transcript.get_openai_client",
-                return_value=None,
-            ),
-            patch(
-                "backend.copilot.sdk.transcript.compress_context",
-                new_callable=AsyncMock,
-                return_value=truncation_result,
-            ) as mock_compress,
-        ):
-            result = await _run_compression(messages, "test-model", "[test]")
-
-        assert result == truncation_result
-        mock_compress.assert_called_once()
-        # When no client, compress_context is called with client=None
-        assert mock_compress.call_args.kwargs.get("client") is None
-
-
-# ---------------------------------------------------------------------------
-# _friendly_error_text
-# ---------------------------------------------------------------------------
-
-
-class TestFriendlyErrorText:
-    """Verify user-friendly error message mapping."""
-
-    def test_authentication_error(self):
-        result = _friendly_error_text("authentication failed: invalid API key")
-        assert "Authentication" in result
-        assert "API key" in result
-
-    def test_rate_limit_error(self):
-        result = _friendly_error_text("rate limit exceeded")
-        assert "Rate limit" in result
-
-    def test_overloaded_error(self):
-        result = _friendly_error_text("API is overloaded")
-        assert "overloaded" in result
-
-    def test_timeout_error(self):
-        result = _friendly_error_text("Request timeout after 30s")
-        assert "timed out" in result
-
-    def test_connection_error(self):
-        result = _friendly_error_text("Connection refused")
-        assert "Connection" in result or "connection" in result
-
-    def test_unknown_error_passthrough(self):
-        result = _friendly_error_text("some unknown error XYZ")
-        assert "SDK stream error:" in result
-        assert "XYZ" in result
-
-    def test_unauthorized_error(self):
-        result = _friendly_error_text("401 Unauthorized")
-        assert "Authentication" in result

autogpt_platform/backend/backend/copilot/sdk/service_helpers_test.py

@@ -1,283 +0,0 @@
-"""Unit tests for extracted service helpers.
-
-Covers ``_is_prompt_too_long``, ``_reduce_context``, ``_iter_sdk_messages``,
-and the ``ReducedContext`` named tuple.
-"""
-
-from __future__ import annotations
-
-import asyncio
-from collections.abc import AsyncGenerator
-from unittest.mock import AsyncMock, patch
-
-import pytest
-
-from .conftest import build_test_transcript as _build_transcript
-from .service import (
-    ReducedContext,
-    _is_prompt_too_long,
-    _iter_sdk_messages,
-    _reduce_context,
-)
-
-# ---------------------------------------------------------------------------
-# _is_prompt_too_long
-# ---------------------------------------------------------------------------
-
-
-class TestIsPromptTooLong:
-    def test_direct_match(self) -> None:
-        assert _is_prompt_too_long(Exception("prompt is too long")) is True
-
-    def test_case_insensitive(self) -> None:
-        assert _is_prompt_too_long(Exception("PROMPT IS TOO LONG")) is True
-
-    def test_no_match(self) -> None:
-        assert _is_prompt_too_long(Exception("network timeout")) is False
-
-    def test_request_too_large(self) -> None:
-        assert _is_prompt_too_long(Exception("request too large for model")) is True
-
-    def test_context_length_exceeded(self) -> None:
-        assert _is_prompt_too_long(Exception("context_length_exceeded")) is True
-
-    def test_max_tokens_exceeded_not_matched(self) -> None:
-        """'max_tokens_exceeded' is intentionally excluded (too broad)."""
-        assert _is_prompt_too_long(Exception("max_tokens_exceeded")) is False
-
-    def test_max_tokens_config_error_no_match(self) -> None:
-        """'max_tokens must be at least 1' should NOT match."""
-        assert _is_prompt_too_long(Exception("max_tokens must be at least 1")) is False
-
-    def test_chained_cause(self) -> None:
-        inner = Exception("prompt is too long")
-        outer = RuntimeError("SDK error")
-        outer.__cause__ = inner
-        assert _is_prompt_too_long(outer) is True
-
-    def test_chained_context(self) -> None:
-        inner = Exception("request too large")
-        outer = RuntimeError("wrapped")
-        outer.__context__ = inner
-        assert _is_prompt_too_long(outer) is True
-
-    def test_deep_chain(self) -> None:
-        bottom = Exception("maximum context length")
-        middle = RuntimeError("middle")
-        middle.__cause__ = bottom
-        top = ValueError("top")
-        top.__cause__ = middle
-        assert _is_prompt_too_long(top) is True
-
-    def test_chain_no_match(self) -> None:
-        inner = Exception("rate limit exceeded")
-        outer = RuntimeError("wrapped")
-        outer.__cause__ = inner
-        assert _is_prompt_too_long(outer) is False
-
-    def test_cycle_detection(self) -> None:
-        """Exception chain with a cycle should not infinite-loop."""
-        a = Exception("error a")
-        b = Exception("error b")
-        a.__cause__ = b
-        b.__cause__ = a  # cycle
-        assert _is_prompt_too_long(a) is False
-
-    def test_all_patterns(self) -> None:
-        patterns = [
-            "prompt is too long",
-            "request too large",
-            "maximum context length",
-            "context_length_exceeded",
-            "input tokens exceed",
-            "input is too long",
-            "content length exceeds",
-        ]
-        for pattern in patterns:
-            assert _is_prompt_too_long(Exception(pattern)) is True, pattern
-
-
-# ---------------------------------------------------------------------------
-# _reduce_context
-# ---------------------------------------------------------------------------
-
-
-class TestReduceContext:
-    @pytest.mark.asyncio
-    async def test_first_retry_compaction_success(self) -> None:
-        transcript = _build_transcript([("user", "hi"), ("assistant", "hello")])
-        compacted = _build_transcript([("user", "hi"), ("assistant", "[summary]")])
-
-        with (
-            patch(
-                "backend.copilot.sdk.service.compact_transcript",
-                new_callable=AsyncMock,
-                return_value=compacted,
-            ),
-            patch(
-                "backend.copilot.sdk.service.validate_transcript",
-                return_value=True,
-            ),
-            patch(
-                "backend.copilot.sdk.service.write_transcript_to_tempfile",
-                return_value="/tmp/resume.jsonl",
-            ),
-        ):
-            ctx = await _reduce_context(
-                transcript, False, "sess-123", "/tmp/cwd", "[test]"
-            )
-
-        assert isinstance(ctx, ReducedContext)
-        assert ctx.use_resume is True
-        assert ctx.resume_file == "/tmp/resume.jsonl"
-        assert ctx.transcript_lost is False
-        assert ctx.tried_compaction is True
-
-    @pytest.mark.asyncio
-    async def test_compaction_fails_drops_transcript(self) -> None:
-        transcript = _build_transcript([("user", "hi"), ("assistant", "hello")])
-
-        with patch(
-            "backend.copilot.sdk.service.compact_transcript",
-            new_callable=AsyncMock,
-            return_value=None,
-        ):
-            ctx = await _reduce_context(
-                transcript, False, "sess-123", "/tmp/cwd", "[test]"
-            )
-
-        assert ctx.use_resume is False
-        assert ctx.resume_file is None
-        assert ctx.transcript_lost is True
-        assert ctx.tried_compaction is True
-
-    @pytest.mark.asyncio
-    async def test_already_tried_compaction_skips(self) -> None:
-        transcript = _build_transcript([("user", "hi"), ("assistant", "hello")])
-
-        ctx = await _reduce_context(transcript, True, "sess-123", "/tmp/cwd", "[test]")
-
-        assert ctx.use_resume is False
-        assert ctx.transcript_lost is True
-        assert ctx.tried_compaction is True
-
-    @pytest.mark.asyncio
-    async def test_empty_transcript_drops(self) -> None:
-        ctx = await _reduce_context("", False, "sess-123", "/tmp/cwd", "[test]")
-
-        assert ctx.use_resume is False
-        assert ctx.transcript_lost is True
-
-    @pytest.mark.asyncio
-    async def test_compaction_returns_same_content_drops(self) -> None:
-        transcript = _build_transcript([("user", "hi"), ("assistant", "hello")])
-
-        with patch(
-            "backend.copilot.sdk.service.compact_transcript",
-            new_callable=AsyncMock,
-            return_value=transcript,  # same content
-        ):
-            ctx = await _reduce_context(
-                transcript, False, "sess-123", "/tmp/cwd", "[test]"
-            )
-
-        assert ctx.transcript_lost is True
-
-    @pytest.mark.asyncio
-    async def test_write_tempfile_fails_drops(self) -> None:
-        transcript = _build_transcript([("user", "hi"), ("assistant", "hello")])
-        compacted = _build_transcript([("user", "hi"), ("assistant", "[summary]")])
-
-        with (
-            patch(
-                "backend.copilot.sdk.service.compact_transcript",
-                new_callable=AsyncMock,
-                return_value=compacted,
-            ),
-            patch(
-                "backend.copilot.sdk.service.validate_transcript",
-                return_value=True,
-            ),
-            patch(
-                "backend.copilot.sdk.service.write_transcript_to_tempfile",
-                return_value=None,
-            ),
-        ):
-            ctx = await _reduce_context(
-                transcript, False, "sess-123", "/tmp/cwd", "[test]"
-            )
-
-        assert ctx.transcript_lost is True
-
-
-# ---------------------------------------------------------------------------
-# _iter_sdk_messages
-# ---------------------------------------------------------------------------
-
-
-class TestIterSdkMessages:
-    @pytest.mark.asyncio
-    async def test_yields_messages(self) -> None:
-        messages = ["msg1", "msg2", "msg3"]
-        client = AsyncMock()
-
-        async def _fake_receive() -> AsyncGenerator[str]:
-            for m in messages:
-                yield m
-
-        client.receive_response = _fake_receive
-        result = [msg async for msg in _iter_sdk_messages(client)]
-        assert result == messages
-
-    @pytest.mark.asyncio
-    async def test_heartbeat_on_timeout(self) -> None:
-        """Yields None when asyncio.wait times out."""
-        client = AsyncMock()
-        received: list = []
-
-        async def _slow_receive() -> AsyncGenerator[str]:
-            await asyncio.sleep(100)  # never completes
-            yield "never"  # pragma: no cover — unreachable, yield makes this an async generator
-
-        client.receive_response = _slow_receive
-
-        with patch("backend.copilot.sdk.service._HEARTBEAT_INTERVAL", 0.01):
-            count = 0
-            async for msg in _iter_sdk_messages(client):
-                received.append(msg)
-                count += 1
-                if count >= 3:
-                    break
-
-        assert all(m is None for m in received)
-
-    @pytest.mark.asyncio
-    async def test_exception_propagates(self) -> None:
-        client = AsyncMock()
-
-        async def _error_receive() -> AsyncGenerator[str]:
-            raise RuntimeError("SDK crash")
-            yield  # pragma: no cover — unreachable, yield makes this an async generator
-
-        client.receive_response = _error_receive
-
-        with pytest.raises(RuntimeError, match="SDK crash"):
-            async for _ in _iter_sdk_messages(client):
-                pass
-
-    @pytest.mark.asyncio
-    async def test_task_cleanup_on_break(self) -> None:
-        """Pending task is cancelled when generator is closed."""
-        client = AsyncMock()
-
-        async def _slow_receive() -> AsyncGenerator[str]:
-            yield "first"
-            await asyncio.sleep(100)
-            yield "second"
-
-        client.receive_response = _slow_receive
-
-        gen = _iter_sdk_messages(client)
-        first = await gen.__anext__()
-        assert first == "first"
-        await gen.aclose()  # should cancel pending task cleanly

autogpt_platform/backend/backend/copilot/sdk/subscription.py

@@ -1,144 +0,0 @@
-"""Claude Code subscription auth helpers.
-
-Handles locating the SDK-bundled CLI binary, provisioning credentials from
-environment variables, and validating that subscription auth is functional.
-"""
-
-import functools
-import json
-import logging
-import os
-import shutil
-import subprocess
-
-logger = logging.getLogger(__name__)
-
-
-def find_bundled_cli() -> str:
-    """Locate the Claude CLI binary bundled inside ``claude_agent_sdk``.
-
-    Falls back to ``shutil.which("claude")`` if the SDK bundle is absent.
-    """
-    try:
-        from claude_agent_sdk._internal.transport.subprocess_cli import (
-            SubprocessCLITransport,
-        )
-
-        path = SubprocessCLITransport._find_bundled_cli(None)  # type: ignore[arg-type]
-        if path:
-            return str(path)
-    except Exception:
-        pass
-    system_path = shutil.which("claude")
-    if system_path:
-        return system_path
-    raise RuntimeError(
-        "Claude CLI not found — neither the SDK-bundled binary nor a "
-        "system-installed `claude` could be located."
-    )
-
-
-def provision_credentials_file() -> None:
-    """Write ``~/.claude/.credentials.json`` from env when running headless.
-
-    If ``CLAUDE_CODE_OAUTH_TOKEN`` is set (an OAuth *access* token obtained
-    from ``claude auth status`` or extracted from the macOS keychain), this
-    helper writes a minimal credentials file so the bundled CLI can
-    authenticate without an interactive ``claude login``.
-
-    A ``CLAUDE_CODE_REFRESH_TOKEN`` env var is optional but recommended —
-    it lets the CLI silently refresh an expired access token.
-    """
-    access_token = os.environ.get("CLAUDE_CODE_OAUTH_TOKEN", "").strip()
-    if not access_token:
-        return
-
-    creds_dir = os.path.expanduser("~/.claude")
-    creds_path = os.path.join(creds_dir, ".credentials.json")
-
-    # Don't overwrite an existing credentials file (e.g. from a volume mount).
-    if os.path.exists(creds_path):
-        logger.debug("Credentials file already exists at %s — skipping", creds_path)
-        return
-
-    os.makedirs(creds_dir, exist_ok=True)
-
-    creds = {
-        "claudeAiOauth": {
-            "accessToken": access_token,
-            "refreshToken": os.environ.get("CLAUDE_CODE_REFRESH_TOKEN", "").strip(),
-            "expiresAt": 0,
-            "scopes": [
-                "user:inference",
-                "user:profile",
-                "user:sessions:claude_code",
-            ],
-        }
-    }
-    with open(creds_path, "w") as f:
-        json.dump(creds, f)
-    logger.info("Provisioned Claude credentials file at %s", creds_path)
-
-
-@functools.cache
-def validate_subscription() -> None:
-    """Validate the bundled Claude CLI is reachable and authenticated.
-
-    Cached so the blocking subprocess check runs at most once per process
-    lifetime.  On first call, also provisions ``~/.claude/.credentials.json``
-    from the ``CLAUDE_CODE_OAUTH_TOKEN`` env var when available.
-    """
-    provision_credentials_file()
-
-    cli = find_bundled_cli()
-    result = subprocess.run(
-        [cli, "--version"],
-        capture_output=True,
-        text=True,
-        timeout=10,
-    )
-    if result.returncode != 0:
-        raise RuntimeError(
-            f"Claude CLI check failed (exit {result.returncode}): "
-            f"{result.stderr.strip()}"
-        )
-    logger.info(
-        "Claude Code subscription mode: CLI version %s",
-        result.stdout.strip(),
-    )
-
-    # Verify the CLI is actually authenticated.
-    auth_result = subprocess.run(
-        [cli, "auth", "status"],
-        capture_output=True,
-        text=True,
-        timeout=10,
-        env={
-            **os.environ,
-            "ANTHROPIC_API_KEY": "",
-            "ANTHROPIC_AUTH_TOKEN": "",
-            "ANTHROPIC_BASE_URL": "",
-        },
-    )
-    if auth_result.returncode != 0:
-        raise RuntimeError(
-            "Claude CLI is not authenticated. Either:\n"
-            "  • Set CLAUDE_CODE_OAUTH_TOKEN env var (from `claude auth status` "
-            "or macOS keychain), or\n"
-            "  • Mount ~/.claude/.credentials.json into the container, or\n"
-            "  • Run `claude login` inside the container."
-        )
-    try:
-        status = json.loads(auth_result.stdout)
-        if not status.get("loggedIn"):
-            raise RuntimeError(
-                "Claude CLI reports loggedIn=false. Set CLAUDE_CODE_OAUTH_TOKEN "
-                "or run `claude login`."
-            )
-        logger.info(
-            "Claude subscription auth: method=%s, email=%s",
-            status.get("authMethod"),
-            status.get("email"),
-        )
-    except json.JSONDecodeError:
-        logger.warning("Could not parse `claude auth status` output")

autogpt_platform/backend/backend/copilot/sdk/transcript.py

@@ -10,9 +10,6 @@ Storage is handled via ``WorkspaceStorageBackend`` (GCS in prod, local
 filesystem for self-hosted) — no DB column needed.
 """
 
-from __future__ import annotations
-
-import asyncio
 import logging
 import os
 import re
@@ -20,12 +17,8 @@ import shutil
 import time
 from dataclasses import dataclass
 from pathlib import Path
-from uuid import uuid4
 
 from backend.util import json
-from backend.util.clients import get_openai_client
-from backend.util.prompt import CompressResult, compress_context
-from backend.util.workspace_storage import GCSWorkspaceStorage, get_workspace_storage
 
 logger = logging.getLogger(__name__)
 
@@ -106,14 +99,7 @@ def strip_progress_entries(content: str) -> str:
             continue
         parent = entry.get("parentUuid", "")
         original_parent = parent
-        # seen_parents is local per-entry (not shared across iterations) so
-        # it can only detect cycles within a single ancestry walk, not across
-        # entries.  This is intentional: each entry's parent chain is
-        # independent, and reusing a global set would incorrectly short-circuit
-        # valid re-use of the same UUID as a parent in different subtrees.
-        seen_parents: set[str] = set()
-        while parent in stripped_uuids and parent not in seen_parents:
-            seen_parents.add(parent)
+        while parent in stripped_uuids:
             parent = uuid_to_parent.get(parent, "")
         if parent != original_parent:
             entry["parentUuid"] = parent
@@ -350,7 +336,7 @@ def write_transcript_to_tempfile(
     # Validate cwd is under the expected sandbox prefix (CodeQL sanitizer).
     real_cwd = os.path.realpath(cwd)
     if not real_cwd.startswith(_SAFE_CWD_PREFIX):
-        logger.warning("[Transcript] cwd outside sandbox: %s", cwd)
+        logger.warning(f"[Transcript] cwd outside sandbox: {cwd}")
         return None
 
     try:
@@ -360,17 +346,17 @@ def write_transcript_to_tempfile(
             os.path.join(real_cwd, f"transcript-{safe_id}.jsonl")
         )
         if not jsonl_path.startswith(real_cwd):
-            logger.warning("[Transcript] Path escaped cwd: %s", jsonl_path)
+            logger.warning(f"[Transcript] Path escaped cwd: {jsonl_path}")
             return None
 
         with open(jsonl_path, "w") as f:
             f.write(transcript_content)
 
-        logger.info("[Transcript] Wrote resume file: %s", jsonl_path)
+        logger.info(f"[Transcript] Wrote resume file: {jsonl_path}")
         return jsonl_path
 
     except OSError as e:
-        logger.warning("[Transcript] Failed to write resume file: %s", e)
+        logger.warning(f"[Transcript] Failed to write resume file: {e}")
         return None
 
 
@@ -431,6 +417,8 @@ def _meta_storage_path_parts(user_id: str, session_id: str) -> tuple[str, str, s
 
 def _build_path_from_parts(parts: tuple[str, str, str], backend: object) -> str:
     """Build a full storage path from (workspace_id, file_id, filename) parts."""
+    from backend.util.workspace_storage import GCSWorkspaceStorage
+
     wid, fid, fname = parts
     if isinstance(backend, GCSWorkspaceStorage):
         blob = f"workspaces/{wid}/{fid}/{fname}"
@@ -469,15 +457,17 @@ async def upload_transcript(
         content: Complete JSONL transcript (from TranscriptBuilder).
         message_count: ``len(session.messages)`` at upload time.
     """
+    from backend.util.workspace_storage import get_workspace_storage
+
     # Strip metadata entries (progress, file-history-snapshot, etc.)
     # Note: SDK-built transcripts shouldn't have these, but strip for safety
     stripped = strip_progress_entries(content)
     if not validate_transcript(stripped):
         # Log entry types for debugging — helps identify why validation failed
-        entry_types = [
-            json.loads(line, fallback={"type": "INVALID_JSON"}).get("type", "?")
-            for line in stripped.strip().split("\n")
-        ]
+        entry_types: list[str] = []
+        for line in stripped.strip().split("\n"):
+            entry = json.loads(line, fallback={"type": "INVALID_JSON"})
+            entry_types.append(entry.get("type", "?"))
         logger.warning(
             "%s Skipping upload — stripped content not valid "
             "(types=%s, stripped_len=%d, raw_len=%d)",
@@ -513,14 +503,11 @@ async def upload_transcript(
             content=json.dumps(meta).encode("utf-8"),
         )
     except Exception as e:
-        logger.warning("%s Failed to write metadata: %s", log_prefix, e)
+        logger.warning(f"{log_prefix} Failed to write metadata: {e}")
 
     logger.info(
-        "%s Uploaded %dB (stripped from %dB, msg_count=%d)",
-        log_prefix,
-        len(encoded),
-        len(content),
-        message_count,
+        f"{log_prefix} Uploaded {len(encoded)}B "
+        f"(stripped from {len(content)}B, msg_count={message_count})"
     )
 
 
@@ -534,6 +521,8 @@ async def download_transcript(
     Returns a ``TranscriptDownload`` with the JSONL content and the
     ``message_count`` watermark from the upload, or ``None`` if not found.
     """
+    from backend.util.workspace_storage import get_workspace_storage
+
     storage = await get_workspace_storage()
     path = _build_storage_path(user_id, session_id, storage)
 
@@ -541,10 +530,10 @@ async def download_transcript(
         data = await storage.retrieve(path)
         content = data.decode("utf-8")
     except FileNotFoundError:
-        logger.debug("%s No transcript in storage", log_prefix)
+        logger.debug(f"{log_prefix} No transcript in storage")
         return None
     except Exception as e:
-        logger.warning("%s Failed to download transcript: %s", log_prefix, e)
+        logger.warning(f"{log_prefix} Failed to download transcript: {e}")
         return None
 
     # Try to load metadata (best-effort — old transcripts won't have it)
@@ -556,14 +545,10 @@ async def download_transcript(
         meta = json.loads(meta_data.decode("utf-8"), fallback={})
         message_count = meta.get("message_count", 0)
         uploaded_at = meta.get("uploaded_at", 0.0)
-    except FileNotFoundError:
+    except (FileNotFoundError, Exception):
         pass  # No metadata — treat as unknown (msg_count=0 → always fill gap)
-    except Exception as e:
-        logger.debug("%s Failed to load transcript metadata: %s", log_prefix, e)
 
-    logger.info(
-        "%s Downloaded %dB (msg_count=%d)", log_prefix, len(content), message_count
-    )
+    logger.info(f"{log_prefix} Downloaded {len(content)}B (msg_count={message_count})")
     return TranscriptDownload(
         content=content,
         message_count=message_count,
@@ -577,6 +562,8 @@ async def delete_transcript(user_id: str, session_id: str) -> None:
     Removes both the ``.jsonl`` transcript and the companion ``.meta.json``
     so stale ``message_count`` watermarks cannot corrupt gap-fill logic.
     """
+    from backend.util.workspace_storage import get_workspace_storage
+
     storage = await get_workspace_storage()
     path = _build_storage_path(user_id, session_id, storage)
 
@@ -593,280 +580,3 @@ async def delete_transcript(user_id: str, session_id: str) -> None:
         logger.info("[Transcript] Deleted metadata for session %s", session_id)
     except Exception as e:
         logger.warning("[Transcript] Failed to delete metadata: %s", e)
-
-
-# ---------------------------------------------------------------------------
-# Transcript compaction — LLM summarization for prompt-too-long recovery
-# ---------------------------------------------------------------------------
-
-# JSONL protocol values used in transcript serialization.
-STOP_REASON_END_TURN = "end_turn"
-COMPACT_MSG_ID_PREFIX = "msg_compact_"
-ENTRY_TYPE_MESSAGE = "message"
-
-
-def _flatten_assistant_content(blocks: list) -> str:
-    """Flatten assistant content blocks into a single plain-text string.
-
-    Structured ``tool_use`` blocks are converted to ``[tool_use: name]``
-    placeholders.  This is intentional: ``compress_context`` requires plain
-    text for token counting and LLM summarization.  The structural loss is
-    acceptable because compaction only runs when the original transcript was
-    already too large for the model — a summarized plain-text version is
-    better than no context at all.
-    """
-    parts: list[str] = []
-    for block in blocks:
-        if isinstance(block, dict):
-            btype = block.get("type", "")
-            if btype == "text":
-                parts.append(block.get("text", ""))
-            elif btype == "tool_use":
-                parts.append(f"[tool_use: {block.get('name', '?')}]")
-            else:
-                # Preserve non-text blocks (e.g. image) as placeholders.
-                # Use __prefix__ to distinguish from literal user text.
-                parts.append(f"[__{btype}__]")
-        elif isinstance(block, str):
-            parts.append(block)
-    return "\n".join(parts) if parts else ""
-
-
-def _flatten_tool_result_content(blocks: list) -> str:
-    """Flatten tool_result and other content blocks into plain text.
-
-    Handles nested tool_result structures, text blocks, and raw strings.
-    Uses ``json.dumps`` as fallback for dict blocks without a ``text`` key
-    or where ``text`` is ``None``.
-
-    Like ``_flatten_assistant_content``, structured blocks (images, nested
-    tool results) are reduced to text representations for compression.
-    """
-    str_parts: list[str] = []
-    for block in blocks:
-        if isinstance(block, dict) and block.get("type") == "tool_result":
-            inner = block.get("content") or ""
-            if isinstance(inner, list):
-                for sub in inner:
-                    if isinstance(sub, dict):
-                        sub_type = sub.get("type")
-                        if sub_type in ("image", "document"):
-                            # Avoid serializing base64 binary data into
-                            # the compaction input — use a placeholder.
-                            str_parts.append(f"[__{sub_type}__]")
-                        elif sub_type == "text" or sub.get("text") is not None:
-                            str_parts.append(str(sub.get("text", "")))
-                        else:
-                            str_parts.append(json.dumps(sub))
-                    else:
-                        str_parts.append(str(sub))
-            else:
-                str_parts.append(str(inner))
-        elif isinstance(block, dict) and block.get("type") == "text":
-            str_parts.append(str(block.get("text", "")))
-        elif isinstance(block, dict):
-            # Preserve non-text/non-tool_result blocks (e.g. image) as placeholders.
-            # Use __prefix__ to distinguish from literal user text.
-            btype = block.get("type", "unknown")
-            str_parts.append(f"[__{btype}__]")
-        elif isinstance(block, str):
-            str_parts.append(block)
-    return "\n".join(str_parts) if str_parts else ""
-
-
-def _transcript_to_messages(content: str) -> list[dict]:
-    """Convert JSONL transcript entries to plain message dicts for compression.
-
-    Parses each line of the JSONL *content*, skips strippable metadata entries
-    (progress, file-history-snapshot, etc.), and extracts the ``role`` and
-    flattened ``content`` from the ``message`` field of each remaining entry.
-
-    Structured content blocks (``tool_use``, ``tool_result``, images) are
-    flattened to plain text via ``_flatten_assistant_content`` and
-    ``_flatten_tool_result_content`` so that ``compress_context`` can
-    perform token counting and LLM summarization on uniform strings.
-
-    Returns:
-        A list of ``{"role": str, "content": str}`` dicts suitable for
-        ``compress_context``.
-    """
-    messages: list[dict] = []
-    for line in content.strip().split("\n"):
-        if not line.strip():
-            continue
-        entry = json.loads(line, fallback=None)
-        if not isinstance(entry, dict):
-            continue
-        if entry.get("type", "") in STRIPPABLE_TYPES and not entry.get(
-            "isCompactSummary"
-        ):
-            continue
-        msg = entry.get("message", {})
-        role = msg.get("role", "")
-        if not role:
-            continue
-        msg_dict: dict = {"role": role}
-        raw_content = msg.get("content")
-        if role == "assistant" and isinstance(raw_content, list):
-            msg_dict["content"] = _flatten_assistant_content(raw_content)
-        elif isinstance(raw_content, list):
-            msg_dict["content"] = _flatten_tool_result_content(raw_content)
-        else:
-            msg_dict["content"] = raw_content or ""
-        messages.append(msg_dict)
-    return messages
-
-
-def _messages_to_transcript(messages: list[dict]) -> str:
-    """Convert compressed message dicts back to JSONL transcript format.
-
-    Rebuilds a minimal JSONL transcript from the ``{"role", "content"}``
-    dicts returned by ``compress_context``.  Each message becomes one JSONL
-    line with a fresh ``uuid`` / ``parentUuid`` chain so the CLI's
-    ``--resume`` flag can reconstruct a valid conversation tree.
-
-    Assistant messages are wrapped in the full ``message`` envelope
-    (``id``, ``model``, ``stop_reason``, structured ``content`` blocks)
-    that the CLI expects.  User messages use the simpler ``{role, content}``
-    form.
-
-    Returns:
-        A newline-terminated JSONL string, or an empty string if *messages*
-        is empty.
-    """
-    lines: list[str] = []
-    last_uuid: str = ""  # root entry uses empty string, not null
-    for msg in messages:
-        role = msg.get("role", "user")
-        entry_type = "assistant" if role == "assistant" else "user"
-        uid = str(uuid4())
-        content = msg.get("content", "")
-        if role == "assistant":
-            message: dict = {
-                "role": "assistant",
-                "model": "",
-                "id": f"{COMPACT_MSG_ID_PREFIX}{uuid4().hex[:24]}",
-                "type": ENTRY_TYPE_MESSAGE,
-                "content": [{"type": "text", "text": content}] if content else [],
-                "stop_reason": STOP_REASON_END_TURN,
-                "stop_sequence": None,
-            }
-        else:
-            message = {"role": role, "content": content}
-        entry = {
-            "type": entry_type,
-            "uuid": uid,
-            "parentUuid": last_uuid,
-            "message": message,
-        }
-        lines.append(json.dumps(entry, separators=(",", ":")))
-        last_uuid = uid
-    return "\n".join(lines) + "\n" if lines else ""
-
-
-_COMPACTION_TIMEOUT_SECONDS = 60
-_TRUNCATION_TIMEOUT_SECONDS = 30
-
-
-async def _run_compression(
-    messages: list[dict],
-    model: str,
-    log_prefix: str,
-) -> CompressResult:
-    """Run LLM-based compression with truncation fallback.
-
-    Uses the shared OpenAI client from ``get_openai_client()``.
-    If no client is configured or the LLM call fails, falls back to
-    truncation-based compression which drops older messages without
-    summarization.
-
-    A 60-second timeout prevents a hung LLM call from blocking the
-    retry path indefinitely.  The truncation fallback also has a
-    30-second timeout to guard against slow tokenization on very large
-    transcripts.
-    """
-    client = get_openai_client()
-    if client is None:
-        logger.warning("%s No OpenAI client configured, using truncation", log_prefix)
-        return await asyncio.wait_for(
-            compress_context(messages=messages, model=model, client=None),
-            timeout=_TRUNCATION_TIMEOUT_SECONDS,
-        )
-    try:
-        return await asyncio.wait_for(
-            compress_context(messages=messages, model=model, client=client),
-            timeout=_COMPACTION_TIMEOUT_SECONDS,
-        )
-    except Exception as e:
-        logger.warning("%s LLM compaction failed, using truncation: %s", log_prefix, e)
-        return await asyncio.wait_for(
-            compress_context(messages=messages, model=model, client=None),
-            timeout=_TRUNCATION_TIMEOUT_SECONDS,
-        )
-
-
-async def compact_transcript(
-    content: str,
-    *,
-    model: str,
-    log_prefix: str = "[Transcript]",
-) -> str | None:
-    """Compact an oversized JSONL transcript using LLM summarization.
-
-    Converts transcript entries to plain messages, runs ``compress_context``
-    (the same compressor used for pre-query history), and rebuilds JSONL.
-
-    Structured content (``tool_use`` blocks, ``tool_result`` nesting, images)
-    is flattened to plain text for compression.  This matches the fidelity of
-    the Plan C (DB compression) fallback path, where
-    ``_format_conversation_context`` similarly renders tool calls as
-    ``You called tool: name(args)`` and results as ``Tool result: ...``.
-    Neither path preserves structured API content blocks — the compacted
-    context serves as text history for the LLM, which creates proper
-    structured tool calls going forward.
-
-    Images are per-turn attachments loaded from workspace storage by file ID
-    (via ``_prepare_file_attachments``), not part of the conversation history.
-    They are re-attached each turn and are unaffected by compaction.
-
-    Returns the compacted JSONL string, or ``None`` on failure.
-
-    See also:
-        ``_compress_messages`` in ``service.py`` — compresses ``ChatMessage``
-        lists for pre-query DB history.  Both share ``compress_context()``
-        but operate on different input formats (JSONL transcript entries
-        here vs. ChatMessage dicts there).
-    """
-    messages = _transcript_to_messages(content)
-    if len(messages) < 2:
-        logger.warning("%s Too few messages to compact (%d)", log_prefix, len(messages))
-        return None
-    try:
-        result = await _run_compression(messages, model, log_prefix)
-        if not result.was_compacted:
-            # Compressor says it's within budget, but the SDK rejected it.
-            # Return None so the caller falls through to DB fallback.
-            logger.warning(
-                "%s Compressor reports within budget but SDK rejected — "
-                "signalling failure",
-                log_prefix,
-            )
-            return None
-        logger.info(
-            "%s Compacted transcript: %d->%d tokens (%d summarized, %d dropped)",
-            log_prefix,
-            result.original_token_count,
-            result.token_count,
-            result.messages_summarized,
-            result.messages_dropped,
-        )
-        compacted = _messages_to_transcript(result.messages)
-        if not validate_transcript(compacted):
-            logger.warning("%s Compacted transcript failed validation", log_prefix)
-            return None
-        return compacted
-    except Exception as e:
-        logger.error(
-            "%s Transcript compaction failed: %s", log_prefix, e, exc_info=True
-        )
-        return None

autogpt_platform/backend/backend/copilot/sdk/transcript_builder.py

@@ -68,7 +68,7 @@ class TranscriptBuilder:
             type=entry_type,
             uuid=data.get("uuid") or str(uuid4()),
             parentUuid=data.get("parentUuid"),
-            isCompactSummary=data.get("isCompactSummary"),
+            isCompactSummary=data.get("isCompactSummary") or None,
             message=data.get("message", {}),
         )
 

autogpt_platform/backend/backend/copilot/sdk/transcript_test.py

@@ -1,8 +1,7 @@
 """Unit tests for JSONL transcript management utilities."""
 
-import asyncio
 import os
-from unittest.mock import AsyncMock, MagicMock, patch
+from unittest.mock import AsyncMock, patch
 
 import pytest
 
@@ -302,7 +301,7 @@ class TestDeleteTranscript:
         mock_storage.delete = AsyncMock()
 
         with patch(
-            "backend.copilot.sdk.transcript.get_workspace_storage",
+            "backend.util.workspace_storage.get_workspace_storage",
             new_callable=AsyncMock,
             return_value=mock_storage,
         ):
@@ -322,7 +321,7 @@ class TestDeleteTranscript:
         )
 
         with patch(
-            "backend.copilot.sdk.transcript.get_workspace_storage",
+            "backend.util.workspace_storage.get_workspace_storage",
             new_callable=AsyncMock,
             return_value=mock_storage,
         ):
@@ -340,7 +339,7 @@ class TestDeleteTranscript:
         )
 
         with patch(
-            "backend.copilot.sdk.transcript.get_workspace_storage",
+            "backend.util.workspace_storage.get_workspace_storage",
             new_callable=AsyncMock,
             return_value=mock_storage,
         ):
@@ -819,183 +818,6 @@ class TestCompactionFlowIntegration:
         assert lines2[-1]["parentUuid"] == "a2"
 
 
-# ---------------------------------------------------------------------------
-# _run_compression (direct tests for the 3 code paths)
-# ---------------------------------------------------------------------------
-
-
-class TestRunCompression:
-    """Direct tests for ``_run_compression`` covering all 3 code paths.
-
-    Paths:
-    (a) No OpenAI client configured → truncation fallback immediately.
-    (b) LLM success → returns LLM-compressed result.
-    (c) LLM call raises → truncation fallback.
-    """
-
-    def _make_compress_result(self, was_compacted: bool, msgs=None):
-        """Build a minimal CompressResult-like object."""
-        from types import SimpleNamespace
-
-        return SimpleNamespace(
-            was_compacted=was_compacted,
-            messages=msgs or [{"role": "user", "content": "summary"}],
-            original_token_count=500,
-            token_count=100 if was_compacted else 500,
-            messages_summarized=2 if was_compacted else 0,
-            messages_dropped=0,
-        )
-
-    @pytest.mark.asyncio
-    async def test_no_client_uses_truncation(self):
-        """Path (a): ``get_openai_client()`` returns None → truncation only."""
-        from .transcript import _run_compression
-
-        truncation_result = self._make_compress_result(
-            True, [{"role": "user", "content": "truncated"}]
-        )
-
-        with (
-            patch(
-                "backend.copilot.sdk.transcript.get_openai_client",
-                return_value=None,
-            ),
-            patch(
-                "backend.copilot.sdk.transcript.compress_context",
-                new_callable=AsyncMock,
-                return_value=truncation_result,
-            ) as mock_compress,
-        ):
-            result = await _run_compression(
-                [{"role": "user", "content": "hello"}],
-                model="test-model",
-                log_prefix="[test]",
-            )
-
-        # compress_context called with client=None (truncation mode)
-        call_kwargs = mock_compress.call_args
-        assert (
-            call_kwargs.kwargs.get("client") is None
-            or (call_kwargs.args and call_kwargs.args[2] is None)
-            or mock_compress.call_args[1].get("client") is None
-        )
-        assert result is truncation_result
-
-    @pytest.mark.asyncio
-    async def test_llm_success_returns_llm_result(self):
-        """Path (b): ``get_openai_client()`` returns a client → LLM compresses."""
-        from .transcript import _run_compression
-
-        llm_result = self._make_compress_result(
-            True, [{"role": "user", "content": "LLM summary"}]
-        )
-        mock_client = MagicMock()
-
-        with (
-            patch(
-                "backend.copilot.sdk.transcript.get_openai_client",
-                return_value=mock_client,
-            ),
-            patch(
-                "backend.copilot.sdk.transcript.compress_context",
-                new_callable=AsyncMock,
-                return_value=llm_result,
-            ) as mock_compress,
-        ):
-            result = await _run_compression(
-                [{"role": "user", "content": "long conversation"}],
-                model="test-model",
-                log_prefix="[test]",
-            )
-
-        # compress_context called with the real client
-        assert mock_compress.called
-        assert result is llm_result
-
-    @pytest.mark.asyncio
-    async def test_llm_failure_falls_back_to_truncation(self):
-        """Path (c): LLM call raises → truncation fallback used instead."""
-        from .transcript import _run_compression
-
-        truncation_result = self._make_compress_result(
-            True, [{"role": "user", "content": "truncated fallback"}]
-        )
-        mock_client = MagicMock()
-        call_count = [0]
-
-        async def _compress_side_effect(**kwargs):
-            call_count[0] += 1
-            if kwargs.get("client") is not None:
-                raise RuntimeError("LLM timeout")
-            return truncation_result
-
-        with (
-            patch(
-                "backend.copilot.sdk.transcript.get_openai_client",
-                return_value=mock_client,
-            ),
-            patch(
-                "backend.copilot.sdk.transcript.compress_context",
-                side_effect=_compress_side_effect,
-            ),
-        ):
-            result = await _run_compression(
-                [{"role": "user", "content": "long conversation"}],
-                model="test-model",
-                log_prefix="[test]",
-            )
-
-        # compress_context called twice: once for LLM (raises), once for truncation
-        assert call_count[0] == 2
-        assert result is truncation_result
-
-    @pytest.mark.asyncio
-    async def test_llm_timeout_falls_back_to_truncation(self):
-        """Path (d): LLM call exceeds timeout → truncation fallback used."""
-        from .transcript import _run_compression
-
-        truncation_result = self._make_compress_result(
-            True, [{"role": "user", "content": "truncated after timeout"}]
-        )
-        call_count = [0]
-
-        async def _compress_side_effect(*, messages, model, client):
-            call_count[0] += 1
-            if client is not None:
-                # Simulate a hang that exceeds the timeout
-                await asyncio.sleep(9999)
-            return truncation_result
-
-        fake_client = MagicMock()
-        with (
-            patch(
-                "backend.copilot.sdk.transcript.get_openai_client",
-                return_value=fake_client,
-            ),
-            patch(
-                "backend.copilot.sdk.transcript.compress_context",
-                side_effect=_compress_side_effect,
-            ),
-            patch(
-                "backend.copilot.sdk.transcript._COMPACTION_TIMEOUT_SECONDS",
-                0.05,
-            ),
-            patch(
-                "backend.copilot.sdk.transcript._TRUNCATION_TIMEOUT_SECONDS",
-                5,
-            ),
-        ):
-            result = await _run_compression(
-                [{"role": "user", "content": "long conversation"}],
-                model="test-model",
-                log_prefix="[test]",
-            )
-
-        # compress_context called twice: once for LLM (times out), once truncation
-        assert call_count[0] == 2
-        assert result is truncation_result
-
-
 # ---------------------------------------------------------------------------
 # cleanup_stale_project_dirs
 # ---------------------------------------------------------------------------

autogpt_platform/backend/backend/copilot/tools/__init__.py

@@ -12,7 +12,6 @@ from .agent_browser import BrowserActTool, BrowserNavigateTool, BrowserScreensho
 from .agent_output import AgentOutputTool
 from .base import BaseTool
 from .bash_exec import BashExecTool
-from .connect_integration import ConnectIntegrationTool
 from .continue_run_block import ContinueRunBlockTool
 from .create_agent import CreateAgentTool
 from .customize_agent import CustomizeAgentTool
@@ -85,7 +84,6 @@ TOOL_REGISTRY: dict[str, BaseTool] = {
     "browser_screenshot": BrowserScreenshotTool(),
     # Sandboxed code execution (bubblewrap)
     "bash_exec": BashExecTool(),
-    "connect_integration": ConnectIntegrationTool(),
     # Persistent workspace tools (cloud storage, survives across sessions)
     # Feature request tools
     "search_feature_requests": SearchFeatureRequestsTool(),

autogpt_platform/backend/backend/copilot/tools/add_understanding.py

@@ -22,12 +22,13 @@ class AddUnderstandingTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return (
-            "Store user's business context, workflows, pain points, and automation goals. "
-            "Call whenever the user shares business info. Each call incrementally merges "
-            "with existing data — provide only the fields you have. "
-            "Builds a profile that helps recommend better agents for the user's needs."
-        )
+        return """Capture and store information about the user's business context,
+workflows, pain points, and automation goals. Call this tool whenever the user
+shares information about their business. Each call incrementally adds to the
+existing understanding - you don't need to provide all fields at once.
+
+Use this to build a comprehensive profile that helps recommend better agents
+and automations for the user's specific needs."""
 
     @property
     def parameters(self) -> dict[str, Any]:

autogpt_platform/backend/backend/copilot/tools/agent_browser.py

@@ -20,9 +20,7 @@ SSRF protection:
 
 Requires:
   npm install -g agent-browser
-  In Docker: system chromium package with AGENT_BROWSER_EXECUTABLE_PATH=/usr/bin/chromium
-             (set automatically — no `agent-browser install` needed).
-  Locally: run `agent-browser install` to download Chromium.
+  agent-browser install   (downloads Chromium, one-time per machine)
 """
 
 import asyncio
@@ -410,11 +408,18 @@ class BrowserNavigateTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Navigate to a URL in a real browser. Returns accessibility tree with @ref IDs "
-            "for browser_act. Session persists (cookies/auth carry over). "
-            "For static pages, prefer web_fetch. "
-            "For SPAs, elements may load late — use browser_act with wait + browser_screenshot to verify. "
-            "For auth: navigate to login, fill creds and submit with browser_act, then navigate to target."
+            "Navigate to a URL using a real browser. Returns an accessibility "
+            "tree snapshot listing the page's interactive elements with @ref IDs "
+            "(e.g. @e3) that can be used with browser_act. "
+            "Session persists — cookies and login state carry over between calls. "
+            "Use this (with browser_act) for multi-step interaction: login flows, "
+            "form filling, button clicks, or anything requiring page interaction. "
+            "For plain static pages, prefer web_fetch — no browser overhead. "
+            "For authenticated pages: navigate to the login page first, use browser_act "
+            "to fill credentials and submit, then navigate to the target page. "
+            "Note: for slow SPAs, the returned snapshot may reflect a partially-loaded "
+            "state. If elements seem missing, use browser_act with action='wait' and a "
+            "CSS selector or millisecond delay, then take a browser_screenshot to verify."
         )
 
     @property
@@ -424,13 +429,13 @@ class BrowserNavigateTool(BaseTool):
             "properties": {
                 "url": {
                     "type": "string",
-                    "description": "HTTP/HTTPS URL to navigate to.",
+                    "description": "The HTTP/HTTPS URL to navigate to.",
                 },
                 "wait_for": {
                     "type": "string",
                     "enum": ["networkidle", "load", "domcontentloaded"],
                     "default": "networkidle",
-                    "description": "Navigation completion strategy (default: networkidle).",
+                    "description": "When to consider navigation complete. Use 'networkidle' for SPAs (default).",
                 },
             },
             "required": ["url"],
@@ -549,12 +554,14 @@ class BrowserActTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Interact with the current browser page using @ref IDs from the snapshot. "
-            "Actions: click, dblclick, fill, type, scroll, hover, press, "
+            "Interact with the current browser page. Use @ref IDs from the "
+            "snapshot (e.g. '@e3') to target elements. Returns an updated snapshot. "
+            "Supported actions: click, dblclick, fill, type, scroll, hover, press, "
             "check, uncheck, select, wait, back, forward, reload. "
-            "fill clears field first; type appends. "
-            "wait accepts CSS selector or milliseconds (e.g. '1000'). "
-            "Returns updated snapshot."
+            "fill clears the field before typing; type appends without clearing. "
+            "wait accepts a CSS selector (waits for element) or milliseconds string (e.g. '1000'). "
+            "Example login flow: fill @e1 with email → fill @e2 with password → "
+            "click @e3 (submit) → browser_navigate to the target page."
         )
 
     @property
@@ -580,21 +587,30 @@ class BrowserActTool(BaseTool):
                         "forward",
                         "reload",
                     ],
-                    "description": "Action to perform.",
+                    "description": "The action to perform.",
                 },
                 "target": {
                     "type": "string",
-                    "description": "@ref ID (e.g. '@e3'), CSS selector, or text. Required for: click, dblclick, fill, type, hover, check, uncheck, select. For wait: CSS selector or milliseconds string (e.g. '1000').",
+                    "description": (
+                        "Element to target. Use @ref from snapshot (e.g. '@e3'), "
+                        "a CSS selector, or a text description. "
+                        "Required for: click, dblclick, fill, type, hover, check, uncheck, select. "
+                        "For wait: a CSS selector to wait for, or milliseconds as a string (e.g. '1000')."
+                    ),
                 },
                 "value": {
                     "type": "string",
-                    "description": "Text for fill/type, key for press (e.g. 'Enter'), option for select.",
+                    "description": (
+                        "For fill/type: the text to enter. "
+                        "For press: key name (e.g. 'Enter', 'Tab', 'Control+a'). "
+                        "For select: the option value to select."
+                    ),
                 },
                 "direction": {
                     "type": "string",
                     "enum": ["up", "down", "left", "right"],
                     "default": "down",
-                    "description": "Scroll direction (default: down).",
+                    "description": "For scroll: direction to scroll.",
                 },
             },
             "required": ["action"],
@@ -741,10 +757,12 @@ class BrowserScreenshotTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Screenshot the current browser page and save to workspace. "
-            "annotate=true overlays @ref labels on elements. "
-            "IMPORTANT: After calling, you MUST immediately call read_workspace_file with the "
-            "returned file_id to display the image inline."
+            "Take a screenshot of the current browser page and save it to the workspace. "
+            "IMPORTANT: After calling this tool, immediately call read_workspace_file "
+            "with the returned file_id to display the image inline to the user — "
+            "the screenshot is not visible until you do this. "
+            "With annotate=true (default), @ref labels are overlaid on interactive "
+            "elements, making it easy to see which @ref ID maps to which element on screen."
         )
 
     @property
@@ -755,12 +773,12 @@ class BrowserScreenshotTool(BaseTool):
                 "annotate": {
                     "type": "boolean",
                     "default": True,
-                    "description": "Overlay @ref labels (default: true).",
+                    "description": "Overlay @ref labels on interactive elements (default: true).",
                 },
                 "filename": {
                     "type": "string",
                     "default": "screenshot.png",
-                    "description": "Workspace filename (default: screenshot.png).",
+                    "description": "Filename to save in the workspace.",
                 },
             },
         }

autogpt_platform/backend/backend/copilot/tools/agent_browser_integration_test.py

@@ -1,351 +0,0 @@
-"""Integration tests for agent-browser + system chromium.
-
-These tests actually invoke the agent-browser binary via subprocess and require:
-  - agent-browser installed (npm install -g agent-browser)
-  - AGENT_BROWSER_EXECUTABLE_PATH=/usr/bin/chromium (set in Docker)
-
-Run with:
-    poetry run test
-
-Or to run only this file:
-    poetry run pytest backend/copilot/tools/agent_browser_integration_test.py -v -p no:autogpt_platform
-
-Skipped automatically when agent-browser binary is not found.
-Tests that hit external sites are marked ``integration`` and skipped by default
-in CI (use ``-m integration`` to include them).
-
-Two test tiers:
-  - CLI tests: call agent-browser subprocess directly (no backend imports needed)
-  - Tool class tests: call BrowserNavigateTool/BrowserActTool._execute() directly
-    with user_id=None (skips workspace/DB interactions — no Postgres/RabbitMQ needed)
-"""
-
-import concurrent.futures
-import os
-import shutil
-import subprocess
-import tempfile
-from datetime import datetime, timezone
-from urllib.parse import urlparse
-
-import pytest
-
-from backend.copilot.model import ChatSession
-from backend.copilot.tools.agent_browser import BrowserActTool, BrowserNavigateTool
-from backend.copilot.tools.models import (
-    BrowserActResponse,
-    BrowserNavigateResponse,
-    ErrorResponse,
-)
-
-pytestmark = pytest.mark.skipif(
-    shutil.which("agent-browser") is None,
-    reason="agent-browser binary not found",
-)
-
-_SESSION = "integration-test-session"
-
-
-def _agent_browser(
-    *args: str, session: str = _SESSION, timeout: int = 30
-) -> tuple[int, str, str]:
-    """Run agent-browser for the given session, return (rc, stdout, stderr)."""
-    result = subprocess.run(
-        ["agent-browser", "--session", session, "--session-name", session, *args],
-        capture_output=True,
-        text=True,
-        timeout=timeout,
-    )
-    return result.returncode, result.stdout, result.stderr
-
-
-def _close_session(session: str, timeout: int = 5) -> None:
-    """Best-effort close for a browser session; never raises on failure."""
-    try:
-        subprocess.run(
-            ["agent-browser", "--session", session, "--session-name", session, "close"],
-            capture_output=True,
-            timeout=timeout,
-        )
-    except (subprocess.TimeoutExpired, OSError):
-        pass
-
-
-@pytest.fixture(autouse=True)
-def _teardown():
-    """Close the shared test session after each test (best-effort)."""
-    yield
-    _close_session(_SESSION)
-
-
-# ---------------------------------------------------------------------------
-# Tests
-# ---------------------------------------------------------------------------
-
-
-def test_chromium_executable_env_is_set():
-    """AGENT_BROWSER_EXECUTABLE_PATH must be set and point to an executable binary."""
-    exe = os.environ.get("AGENT_BROWSER_EXECUTABLE_PATH", "")
-    assert exe, "AGENT_BROWSER_EXECUTABLE_PATH is not set"
-    assert os.path.isfile(exe), f"Chromium binary not found at {exe}"
-    assert os.access(exe, os.X_OK), f"Chromium binary at {exe} is not executable"
-
-
-@pytest.mark.integration
-def test_navigate_returns_success():
-    """agent-browser can open a public URL using system chromium."""
-    rc, _, stderr = _agent_browser("open", "https://example.com")
-    assert rc == 0, f"open failed (rc={rc}): {stderr}"
-
-
-@pytest.mark.integration
-def test_get_title_after_navigate():
-    """get title returns the page title after navigation."""
-    rc, _, _ = _agent_browser("open", "https://example.com")
-    assert rc == 0
-
-    rc, stdout, stderr = _agent_browser("get", "title", timeout=10)
-    assert rc == 0, f"get title failed: {stderr}"
-    assert "example" in stdout.lower()
-
-
-@pytest.mark.integration
-def test_get_url_after_navigate():
-    """get url returns the navigated URL."""
-    rc, _, _ = _agent_browser("open", "https://example.com")
-    assert rc == 0
-
-    rc, stdout, stderr = _agent_browser("get", "url", timeout=10)
-    assert rc == 0, f"get url failed: {stderr}"
-    assert urlparse(stdout.strip()).netloc == "example.com"
-
-
-@pytest.mark.integration
-def test_snapshot_returns_interactive_elements():
-    """snapshot -i -c lists interactive elements on the page."""
-    rc, _, _ = _agent_browser("open", "https://example.com")
-    assert rc == 0
-
-    rc, stdout, stderr = _agent_browser("snapshot", "-i", "-c", timeout=15)
-    assert rc == 0, f"snapshot failed: {stderr}"
-    assert len(stdout.strip()) > 0, "snapshot returned empty output"
-
-
-@pytest.mark.integration
-def test_screenshot_produces_valid_png():
-    """screenshot saves a non-empty, valid PNG file."""
-    rc, _, _ = _agent_browser("open", "https://example.com")
-    assert rc == 0
-
-    with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as f:
-        tmp = f.name
-    try:
-        rc, _, stderr = _agent_browser("screenshot", tmp, timeout=15)
-        assert rc == 0, f"screenshot failed: {stderr}"
-        size = os.path.getsize(tmp)
-        assert size > 1000, f"PNG too small ({size} bytes) — likely blank or corrupt"
-        with open(tmp, "rb") as f:
-            assert f.read(4) == b"\x89PNG", "Output is not a valid PNG"
-    finally:
-        os.unlink(tmp)
-
-
-@pytest.mark.integration
-def test_scroll_down():
-    """scroll down succeeds without error."""
-    rc, _, _ = _agent_browser("open", "https://example.com")
-    assert rc == 0
-
-    rc, _, stderr = _agent_browser("scroll", "down", timeout=10)
-    assert rc == 0, f"scroll failed: {stderr}"
-
-
-@pytest.mark.integration
-def test_fill_form_field():
-    """fill writes text into an input field."""
-    rc, _, _ = _agent_browser("open", "https://httpbin.org/forms/post")
-    assert rc == 0
-
-    rc, _, stderr = _agent_browser(
-        "fill", "input[name=custname]", "IntegrationTestUser", timeout=10
-    )
-    assert rc == 0, f"fill failed: {stderr}"
-
-
-@pytest.mark.integration
-def test_concurrent_independent_sessions():
-    """Two independent sessions can navigate in parallel without interference."""
-    session_a = "integration-concurrent-a"
-    session_b = "integration-concurrent-b"
-
-    try:
-        with concurrent.futures.ThreadPoolExecutor(max_workers=2) as pool:
-            fut_a = pool.submit(
-                _agent_browser, "open", "https://example.com", session=session_a
-            )
-            fut_b = pool.submit(
-                _agent_browser, "open", "https://httpbin.org/html", session=session_b
-            )
-            rc_a, _, err_a = fut_a.result(timeout=40)
-            rc_b, _, err_b = fut_b.result(timeout=40)
-        assert rc_a == 0, f"session_a open failed: {err_a}"
-        assert rc_b == 0, f"session_b open failed: {err_b}"
-
-        rc_ua, url_a, err_ua = _agent_browser(
-            "get", "url", session=session_a, timeout=10
-        )
-        rc_ub, url_b, err_ub = _agent_browser(
-            "get", "url", session=session_b, timeout=10
-        )
-        assert rc_ua == 0, f"session_a get url failed: {err_ua}"
-        assert rc_ub == 0, f"session_b get url failed: {err_ub}"
-        assert urlparse(url_a.strip()).netloc == "example.com"
-        assert urlparse(url_b.strip()).netloc == "httpbin.org"
-    finally:
-        _close_session(session_a)
-        _close_session(session_b)
-
-
-@pytest.mark.integration
-def test_close_session():
-    """close shuts down the browser daemon cleanly."""
-    rc, _, _ = _agent_browser("open", "https://example.com")
-    assert rc == 0
-
-    rc, _, stderr = _agent_browser("close", timeout=10)
-    assert rc == 0, f"close failed: {stderr}"
-
-
-# ---------------------------------------------------------------------------
-# Python tool class integration tests
-#
-# These tests exercise the actual BrowserNavigateTool / BrowserActTool Python
-# classes (not just the CLI binary) to verify the full call path — URL
-# validation, subprocess dispatch, response parsing — works with system
-# chromium.  user_id=None skips workspace/DB interactions so no Postgres or
-# RabbitMQ is needed.
-# ---------------------------------------------------------------------------
-
-_TOOL_SESSION_ID = "integration-tool-test-session"
-_TEST_SESSION = ChatSession(
-    session_id=_TOOL_SESSION_ID,
-    user_id="test-user",
-    messages=[],
-    usage=[],
-    started_at=datetime.now(timezone.utc),
-    updated_at=datetime.now(timezone.utc),
-)
-
-
-@pytest.fixture(autouse=False)
-def _close_tool_session():
-    """Tear down the tool-test browser session after each tool test."""
-    yield
-    _close_session(_TOOL_SESSION_ID)
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_tool_navigate_returns_response(_close_tool_session):
-    """BrowserNavigateTool._execute returns a BrowserNavigateResponse with real content."""
-    tool = BrowserNavigateTool()
-    resp = await tool._execute(
-        user_id=None, session=_TEST_SESSION, url="https://example.com"
-    )
-    assert isinstance(
-        resp, BrowserNavigateResponse
-    ), f"Expected BrowserNavigateResponse, got: {resp}"
-    assert urlparse(resp.url).netloc == "example.com"
-    assert resp.title, "Expected non-empty page title"
-    assert resp.snapshot, "Expected non-empty accessibility snapshot"
-
-
-@pytest.mark.asyncio
-@pytest.mark.parametrize(
-    "ssrf_url",
-    [
-        "http://169.254.169.254/",  # AWS/GCP/Azure metadata endpoint
-        "http://127.0.0.1/",  # IPv4 loopback
-        "http://10.0.0.1/",  # RFC-1918 private range
-        "http://[::1]/",  # IPv6 loopback
-        "http://0.0.0.0/",  # Wildcard / INADDR_ANY
-    ],
-)
-async def test_tool_navigate_blocked_url(ssrf_url: str, _close_tool_session):
-    """BrowserNavigateTool._execute rejects internal/private URLs (SSRF guard)."""
-    tool = BrowserNavigateTool()
-    resp = await tool._execute(user_id=None, session=_TEST_SESSION, url=ssrf_url)
-    assert isinstance(
-        resp, ErrorResponse
-    ), f"Expected ErrorResponse for SSRF URL {ssrf_url!r}, got: {resp}"
-    assert resp.error == "blocked_url"
-
-
-@pytest.mark.asyncio
-async def test_tool_navigate_missing_url(_close_tool_session):
-    """BrowserNavigateTool._execute returns an error when url is empty."""
-    tool = BrowserNavigateTool()
-    resp = await tool._execute(user_id=None, session=_TEST_SESSION, url="")
-    assert isinstance(resp, ErrorResponse)
-    assert resp.error == "missing_url"
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_tool_act_scroll(_close_tool_session):
-    """BrowserActTool._execute can scroll after a navigate."""
-    nav = BrowserNavigateTool()
-    nav_resp = await nav._execute(
-        user_id=None, session=_TEST_SESSION, url="https://example.com"
-    )
-    assert isinstance(nav_resp, BrowserNavigateResponse)
-
-    act = BrowserActTool()
-    resp = await act._execute(
-        user_id=None, session=_TEST_SESSION, action="scroll", direction="down"
-    )
-    assert isinstance(
-        resp, BrowserActResponse
-    ), f"Expected BrowserActResponse, got: {resp}"
-    assert resp.action == "scroll"
-
-
-@pytest.mark.integration
-@pytest.mark.asyncio
-async def test_tool_act_fill_and_click(_close_tool_session):
-    """BrowserActTool._execute can fill a form field."""
-    nav = BrowserNavigateTool()
-    nav_resp = await nav._execute(
-        user_id=None, session=_TEST_SESSION, url="https://httpbin.org/forms/post"
-    )
-    assert isinstance(nav_resp, BrowserNavigateResponse)
-
-    act = BrowserActTool()
-    resp = await act._execute(
-        user_id=None,
-        session=_TEST_SESSION,
-        action="fill",
-        target="input[name=custname]",
-        value="ToolIntegrationTest",
-    )
-    assert isinstance(resp, BrowserActResponse), f"fill failed: {resp}"
-
-
-@pytest.mark.asyncio
-async def test_tool_act_missing_action(_close_tool_session):
-    """BrowserActTool._execute returns an error when action is missing."""
-    act = BrowserActTool()
-    resp = await act._execute(user_id=None, session=_TEST_SESSION, action="")
-    assert isinstance(resp, ErrorResponse)
-    assert resp.error == "missing_action"
-
-
-@pytest.mark.asyncio
-async def test_tool_act_missing_target(_close_tool_session):
-    """BrowserActTool._execute returns an error when click target is missing."""
-    act = BrowserActTool()
-    resp = await act._execute(
-        user_id=None, session=_TEST_SESSION, action="click", target=""
-    )
-    assert isinstance(resp, ErrorResponse)
-    assert resp.error == "missing_target"

autogpt_platform/backend/backend/copilot/tools/agent_output.py

@@ -108,12 +108,22 @@ class AgentOutputTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return (
-            "Retrieve execution outputs from a library agent. "
-            "Identify by agent_name, library_agent_id, or store_slug. "
-            "Filter by execution_id or run_time. "
-            "Optionally wait for running executions."
-        )
+        return """Retrieve execution outputs from agents in the user's library.
+
+        Identify the agent using one of:
+        - agent_name: Fuzzy search in user's library
+        - library_agent_id: Exact library agent ID
+        - store_slug: Marketplace format 'username/agent-name'
+
+        Select which run to retrieve using:
+        - execution_id: Specific execution ID
+        - run_time: 'latest' (default), 'yesterday', 'last week', or ISO date 'YYYY-MM-DD'
+
+        Wait for completion (optional):
+        - wait_if_running: Max seconds to wait if execution is still running (0-300).
+          If the execution is running/queued, waits up to this many seconds for completion.
+          Returns current status on timeout. If already finished, returns immediately.
+        """
 
     @property
     def parameters(self) -> dict[str, Any]:
@@ -122,29 +132,32 @@ class AgentOutputTool(BaseTool):
             "properties": {
                 "agent_name": {
                     "type": "string",
-                    "description": "Agent name (fuzzy match).",
+                    "description": "Agent name to search for in user's library (fuzzy match)",
                 },
                 "library_agent_id": {
                     "type": "string",
-                    "description": "Library agent ID.",
+                    "description": "Exact library agent ID",
                 },
                 "store_slug": {
                     "type": "string",
-                    "description": "Marketplace 'username/agent-name'.",
+                    "description": "Marketplace identifier: 'username/agent-slug'",
                 },
                 "execution_id": {
                     "type": "string",
-                    "description": "Specific execution ID.",
+                    "description": "Specific execution ID to retrieve",
                 },
                 "run_time": {
                     "type": "string",
-                    "description": "Time filter: 'latest', 'today', 'yesterday', 'last week', 'last 7 days', 'last month', 'last 30 days', 'YYYY-MM-DD', or ISO datetime.",
+                    "description": (
+                        "Time filter: 'latest', 'yesterday', 'last week', or 'YYYY-MM-DD'"
+                    ),
                 },
                 "wait_if_running": {
                     "type": "integer",
-                    "description": "Max seconds to wait if still running (0-300). Returns current state on timeout.",
-                    "minimum": 0,
-                    "maximum": 300,
+                    "description": (
+                        "Max seconds to wait if execution is still running (0-300). "
+                        "If running, waits for completion. Returns current state on timeout."
+                    ),
                 },
             },
             "required": [],

autogpt_platform/backend/backend/copilot/tools/base.py

@@ -164,9 +164,8 @@ class BaseTool:
 
         """
         if self.requires_auth and not user_id:
-            logger.warning(
-                "Attempted tool call for %s but user not authenticated",
-                self.name,
+            logger.error(
+                f"Attempted tool call for {self.name} but user not authenticated"
             )
             return StreamToolOutputAvailable(
                 toolCallId=tool_call_id,
@@ -197,7 +196,7 @@ class BaseTool:
                 output=raw_output,
             )
         except Exception as e:
-            logger.warning("Error in %s", self.name, exc_info=True)
+            logger.error(f"Error in {self.name}: {e}", exc_info=True)
             return StreamToolOutputAvailable(
                 toolCallId=tool_call_id,
                 toolName=self.name,

autogpt_platform/backend/backend/copilot/tools/bash_exec.py

@@ -22,7 +22,6 @@ from e2b import AsyncSandbox
 from e2b.exceptions import TimeoutException
 
 from backend.copilot.context import E2B_WORKDIR, get_current_sandbox
-from backend.copilot.integration_creds import get_integration_env_vars
 from backend.copilot.model import ChatSession
 
 from .base import BaseTool
@@ -42,9 +41,15 @@ class BashExecTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Execute a Bash command or script. Shares filesystem with SDK file tools. "
-            "Useful for scripts, data processing, and package installation. "
-            "Killed after timeout (default 30s, max 120s)."
+            "Execute a Bash command or script. "
+            "Full Bash scripting is supported (loops, conditionals, pipes, "
+            "functions, etc.). "
+            "The working directory is shared with the SDK Read/Write/Edit/Glob/Grep "
+            "tools — files created by either are immediately visible to both. "
+            "Execution is killed after the timeout (default 30s, max 120s). "
+            "Returns stdout and stderr. "
+            "Useful for file manipulation, data processing, running scripts, "
+            "and installing packages."
         )
 
     @property
@@ -54,11 +59,13 @@ class BashExecTool(BaseTool):
             "properties": {
                 "command": {
                     "type": "string",
-                    "description": "Bash command or script.",
+                    "description": "Bash command or script to execute.",
                 },
                 "timeout": {
                     "type": "integer",
-                    "description": "Max seconds (default 30, max 120).",
+                    "description": (
+                        "Max execution time in seconds (default 30, max 120)."
+                    ),
                     "default": 30,
                 },
             },
@@ -67,10 +74,7 @@ class BashExecTool(BaseTool):
 
     @property
     def requires_auth(self) -> bool:
-        # True because _execute_on_e2b injects user tokens (GH_TOKEN etc.)
-        # when user_id is present.  Defense-in-depth: ensures only authenticated
-        # users reach the token injection path.
-        return True
+        return False
 
     async def _execute(
         self,
@@ -78,14 +82,6 @@ class BashExecTool(BaseTool):
         session: ChatSession,
         **kwargs: Any,
     ) -> ToolResponseBase:
-        """Run a bash command on E2B (if available) or in a bubblewrap sandbox.
-
-        Dispatches to :meth:`_execute_on_e2b` when a sandbox is present in the
-        current execution context, otherwise falls back to the local bubblewrap
-        sandbox.  Returns a :class:`BashExecResponse` on success or an
-        :class:`ErrorResponse` when the sandbox is unavailable or the command
-        is empty.
-        """
         session_id = session.session_id if session else None
 
         command: str = (kwargs.get("command") or "").strip()
@@ -100,9 +96,7 @@ class BashExecTool(BaseTool):
 
         sandbox = get_current_sandbox()
         if sandbox is not None:
-            return await self._execute_on_e2b(
-                sandbox, command, timeout, session_id, user_id
-            )
+            return await self._execute_on_e2b(sandbox, command, timeout, session_id)
 
         # Bubblewrap fallback: local isolated execution.
         if not has_full_sandbox():
@@ -139,42 +133,19 @@ class BashExecTool(BaseTool):
         command: str,
         timeout: int,
         session_id: str | None,
-        user_id: str | None = None,
     ) -> ToolResponseBase:
-        """Execute *command* on the E2B sandbox via commands.run().
-
-        Integration tokens (e.g. GH_TOKEN) are injected into the sandbox env
-        for any user with connected accounts. E2B has full internet access, so
-        CLI tools like ``gh`` work without manual authentication.
-        """
-        envs: dict[str, str] = {
-            "PATH": "/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin",
-        }
-        # Collect injected secret values so we can scrub them from output.
-        secret_values: list[str] = []
-        if user_id is not None:
-            integration_env = await get_integration_env_vars(user_id)
-            secret_values = [v for v in integration_env.values() if v]
-            envs.update(integration_env)
-
+        """Execute *command* on the E2B sandbox via commands.run()."""
         try:
             result = await sandbox.commands.run(
                 f"bash -c {shlex.quote(command)}",
                 cwd=E2B_WORKDIR,
                 timeout=timeout,
-                envs=envs,
+                envs={"PATH": "/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin"},
             )
-            stdout = result.stdout or ""
-            stderr = result.stderr or ""
-            # Scrub injected tokens from command output to prevent exfiltration
-            # via `echo $GH_TOKEN`, `env`, `printenv`, etc.
-            for secret in secret_values:
-                stdout = stdout.replace(secret, "[REDACTED]")
-                stderr = stderr.replace(secret, "[REDACTED]")
             return BashExecResponse(
                 message=f"Command executed on E2B (exit {result.exit_code})",
-                stdout=stdout,
-                stderr=stderr,
+                stdout=result.stdout or "",
+                stderr=result.stderr or "",
                 exit_code=result.exit_code,
                 timed_out=False,
                 session_id=session_id,

autogpt_platform/backend/backend/copilot/tools/bash_exec_test.py

@@ -1,78 +0,0 @@
-"""Tests for BashExecTool — E2B path with token injection."""
-
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import pytest
-
-from ._test_data import make_session
-from .bash_exec import BashExecTool
-from .models import BashExecResponse
-
-_USER = "user-bash-exec-test"
-
-
-def _make_tool() -> BashExecTool:
-    return BashExecTool()
-
-
-def _make_sandbox(exit_code: int = 0, stdout: str = "", stderr: str = "") -> MagicMock:
-    result = MagicMock()
-    result.exit_code = exit_code
-    result.stdout = stdout
-    result.stderr = stderr
-
-    sandbox = MagicMock()
-    sandbox.commands.run = AsyncMock(return_value=result)
-    return sandbox
-
-
-class TestBashExecE2BTokenInjection:
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_token_injected_when_user_id_set(self):
-        """When user_id is provided, integration env vars are merged into sandbox envs."""
-        tool = _make_tool()
-        session = make_session(user_id=_USER)
-        sandbox = _make_sandbox(stdout="ok")
-        env_vars = {"GH_TOKEN": "gh-secret", "GITHUB_TOKEN": "gh-secret"}
-
-        with patch(
-            "backend.copilot.tools.bash_exec.get_integration_env_vars",
-            new=AsyncMock(return_value=env_vars),
-        ) as mock_get_env:
-            result = await tool._execute_on_e2b(
-                sandbox=sandbox,
-                command="echo hi",
-                timeout=10,
-                session_id=session.session_id,
-                user_id=_USER,
-            )
-
-        mock_get_env.assert_awaited_once_with(_USER)
-        call_kwargs = sandbox.commands.run.call_args[1]
-        assert call_kwargs["envs"]["GH_TOKEN"] == "gh-secret"
-        assert call_kwargs["envs"]["GITHUB_TOKEN"] == "gh-secret"
-        assert isinstance(result, BashExecResponse)
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_no_token_injection_when_user_id_is_none(self):
-        """When user_id is None, get_integration_env_vars must NOT be called."""
-        tool = _make_tool()
-        session = make_session(user_id=_USER)
-        sandbox = _make_sandbox(stdout="ok")
-
-        with patch(
-            "backend.copilot.tools.bash_exec.get_integration_env_vars",
-            new=AsyncMock(return_value={"GH_TOKEN": "should-not-appear"}),
-        ) as mock_get_env:
-            result = await tool._execute_on_e2b(
-                sandbox=sandbox,
-                command="echo hi",
-                timeout=10,
-                session_id=session.session_id,
-                user_id=None,
-            )
-
-        mock_get_env.assert_not_called()
-        call_kwargs = sandbox.commands.run.call_args[1]
-        assert "GH_TOKEN" not in call_kwargs["envs"]
-        assert isinstance(result, BashExecResponse)

autogpt_platform/backend/backend/copilot/tools/conftest.py

@@ -1,20 +0,0 @@
-"""Local conftest for copilot/tools tests.
-
-Overrides the session-scoped `server` and `graph_cleanup` autouse fixtures from
-backend/conftest.py so that integration tests in this directory do not trigger
-the full SpinTestServer startup (which requires Postgres + RabbitMQ).
-"""
-
-import pytest_asyncio
-
-
-@pytest_asyncio.fixture(scope="session", loop_scope="session")
-async def server():  # type: ignore[override]
-    """No-op server stub — tools tests don't need the full backend."""
-    return None
-
-
-@pytest_asyncio.fixture(scope="session", loop_scope="session", autouse=True)
-async def graph_cleanup():  # type: ignore[override]
-    """No-op graph cleanup stub."""
-    yield

autogpt_platform/backend/backend/copilot/tools/connect_integration.py

@@ -1,196 +0,0 @@
-"""Tool for prompting the user to connect a required integration.
-
-When the copilot encounters an authentication failure (e.g. `gh` CLI returns
-"authentication required"), it calls this tool to surface the credentials
-setup card in the chat — the same UI that appears when a GitHub block runs
-without configured credentials.
-"""
-
-from typing import Any, TypedDict
-
-from backend.copilot.model import ChatSession
-from backend.copilot.providers import SUPPORTED_PROVIDERS, get_provider_auth_types
-from backend.copilot.tools.models import (
-    ErrorResponse,
-    ResponseType,
-    SetupInfo,
-    SetupRequirementsResponse,
-    ToolResponseBase,
-    UserReadiness,
-)
-
-from .base import BaseTool
-
-
-class _CredentialEntry(TypedDict):
-    """Shape of each entry inside SetupRequirementsResponse.user_readiness.missing_credentials.
-
-    Partially overlaps with :class:`~backend.data.model.CredentialsMetaInput`
-    (``id``, ``title``, ``provider``) but carries extra UI-facing fields
-    (``types``, ``scopes``) that the frontend ``SetupRequirementsCard`` needs
-    to render the inline credential setup card.
-
-    Display name is derived from :data:`SUPPORTED_PROVIDERS` at build time
-    rather than stored here — eliminates the old ``provider_name`` field.
-    ``types`` replaces the old singular ``type`` field; the frontend already
-    prefers ``types`` and only fell back to ``type`` for compatibility.
-    """
-
-    id: str
-    title: str
-    # Slug used as the credential key (e.g. "github").
-    provider: str
-    # All supported credential types the user can choose from (e.g. ["api_key", "oauth2"]).
-    # The first element is the default/primary type.
-    types: list[str]
-    scopes: list[str]
-
-
-class ConnectIntegrationTool(BaseTool):
-    """Surface the credentials setup UI when an integration is not connected."""
-
-    @property
-    def name(self) -> str:
-        return "connect_integration"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Prompt the user to connect a required integration (e.g. GitHub). "
-            "Call this when an external CLI or API call fails because the user "
-            "has not connected the relevant account. "
-            "The tool surfaces a credentials setup card in the chat so the user "
-            "can authenticate without leaving the page. "
-            "After the user connects the account, retry the operation. "
-            "In E2B/cloud sandbox mode the token (GH_TOKEN/GITHUB_TOKEN) is "
-            "automatically injected per-command in bash_exec — no manual export needed. "
-            "In local bubblewrap mode network is isolated so GitHub CLI commands "
-            "will still fail after connecting; inform the user of this limitation."
-        )
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "provider": {
-                    "type": "string",
-                    "description": (
-                        "Integration provider slug, e.g. 'github'. "
-                        "Must be one of the supported providers."
-                    ),
-                    "enum": list(SUPPORTED_PROVIDERS.keys()),
-                },
-                "reason": {
-                    "type": "string",
-                    "description": (
-                        "Brief explanation of why the integration is needed, "
-                        "shown to the user in the setup card."
-                    ),
-                    "maxLength": 500,
-                },
-                "scopes": {
-                    "type": "array",
-                    "items": {"type": "string"},
-                    "description": (
-                        "OAuth scopes to request. Omit to use the provider default. "
-                        "Add extra scopes when you need more access — e.g. for GitHub: "
-                        "'repo' (clone/push/pull), 'read:org' (org membership), "
-                        "'workflow' (GitHub Actions). "
-                        "Requesting only the scopes you actually need is best practice."
-                    ),
-                },
-            },
-            "required": ["provider"],
-        }
-
-    @property
-    def requires_auth(self) -> bool:
-        # Require auth so only authenticated users can trigger the setup card.
-        # The card itself is user-agnostic (no per-user data needed), so
-        # user_id is intentionally unused in _execute.
-        return True
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs: Any,
-    ) -> ToolResponseBase:
-        """Build and return a :class:`SetupRequirementsResponse` for the requested provider.
-
-        Validates the *provider* slug against the known registry, merges any
-        agent-requested OAuth *scopes* with the provider defaults, and constructs
-        the credential setup card payload that the frontend renders as an inline
-        authentication prompt.
-
-        Returns an :class:`ErrorResponse` if *provider* is unknown.
-        """
-        _ = user_id  # setup card is user-agnostic; auth is enforced via requires_auth
-        session_id = session.session_id if session else None
-        provider: str = (kwargs.get("provider") or "").strip().lower()
-        reason: str = (kwargs.get("reason") or "").strip()[
-            :500
-        ]  # cap LLM-controlled text
-        extra_scopes: list[str] = [
-            str(s).strip() for s in (kwargs.get("scopes") or []) if str(s).strip()
-        ]
-
-        entry = SUPPORTED_PROVIDERS.get(provider)
-        if not entry:
-            supported = ", ".join(f"'{p}'" for p in SUPPORTED_PROVIDERS)
-            return ErrorResponse(
-                message=(
-                    f"Unknown provider '{provider}'. "
-                    f"Supported providers: {supported}."
-                ),
-                error="unknown_provider",
-                session_id=session_id,
-            )
-
-        display_name: str = entry["name"]
-        supported_types: list[str] = get_provider_auth_types(provider)
-        # Merge agent-requested scopes with provider defaults (deduplicated, order preserved).
-        default_scopes: list[str] = entry["default_scopes"]
-        seen: set[str] = set()
-        scopes: list[str] = []
-        for s in default_scopes + extra_scopes:
-            if s not in seen:
-                seen.add(s)
-                scopes.append(s)
-        field_key = f"{provider}_credentials"
-
-        message_parts = [
-            f"To continue, please connect your {display_name} account.",
-        ]
-        if reason:
-            message_parts.append(reason)
-
-        credential_entry: _CredentialEntry = {
-            "id": field_key,
-            "title": f"{display_name} Credentials",
-            "provider": provider,
-            "types": supported_types,
-            "scopes": scopes,
-        }
-        missing_credentials: dict[str, _CredentialEntry] = {field_key: credential_entry}
-
-        return SetupRequirementsResponse(
-            type=ResponseType.SETUP_REQUIREMENTS,
-            message=" ".join(message_parts),
-            session_id=session_id,
-            setup_info=SetupInfo(
-                agent_id=f"connect_{provider}",
-                agent_name=display_name,
-                user_readiness=UserReadiness(
-                    has_all_credentials=False,
-                    missing_credentials=missing_credentials,
-                    ready_to_run=False,
-                ),
-                requirements={
-                    "credentials": [missing_credentials[field_key]],
-                    "inputs": [],
-                    "execution_modes": [],
-                },
-            ),
-        )

autogpt_platform/backend/backend/copilot/tools/connect_integration_test.py

@@ -1,135 +0,0 @@
-"""Tests for ConnectIntegrationTool."""
-
-import pytest
-
-from ._test_data import make_session
-from .connect_integration import ConnectIntegrationTool
-from .models import ErrorResponse, SetupRequirementsResponse
-
-_TEST_USER_ID = "test-user-connect-integration"
-
-
-class TestConnectIntegrationTool:
-    def _make_tool(self) -> ConnectIntegrationTool:
-        return ConnectIntegrationTool()
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_unknown_provider_returns_error(self):
-        tool = self._make_tool()
-        session = make_session(user_id=_TEST_USER_ID)
-        result = await tool._execute(
-            user_id=_TEST_USER_ID, session=session, provider="nonexistent"
-        )
-        assert isinstance(result, ErrorResponse)
-        assert result.error == "unknown_provider"
-        assert "nonexistent" in result.message
-        assert "github" in result.message
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_empty_provider_returns_error(self):
-        tool = self._make_tool()
-        session = make_session(user_id=_TEST_USER_ID)
-        result = await tool._execute(
-            user_id=_TEST_USER_ID, session=session, provider=""
-        )
-        assert isinstance(result, ErrorResponse)
-        assert result.error == "unknown_provider"
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_github_provider_returns_setup_response(self):
-        tool = self._make_tool()
-        session = make_session(user_id=_TEST_USER_ID)
-        result = await tool._execute(
-            user_id=_TEST_USER_ID, session=session, provider="github"
-        )
-        assert isinstance(result, SetupRequirementsResponse)
-        assert result.setup_info.agent_name == "GitHub"
-        assert result.setup_info.agent_id == "connect_github"
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_github_has_missing_credentials_in_readiness(self):
-        tool = self._make_tool()
-        session = make_session(user_id=_TEST_USER_ID)
-        result = await tool._execute(
-            user_id=_TEST_USER_ID, session=session, provider="github"
-        )
-        assert isinstance(result, SetupRequirementsResponse)
-        readiness = result.setup_info.user_readiness
-        assert readiness.has_all_credentials is False
-        assert readiness.ready_to_run is False
-        assert "github_credentials" in readiness.missing_credentials
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_github_requirements_include_credential_entry(self):
-        tool = self._make_tool()
-        session = make_session(user_id=_TEST_USER_ID)
-        result = await tool._execute(
-            user_id=_TEST_USER_ID, session=session, provider="github"
-        )
-        assert isinstance(result, SetupRequirementsResponse)
-        creds = result.setup_info.requirements["credentials"]
-        assert len(creds) == 1
-        assert creds[0]["provider"] == "github"
-        assert creds[0]["id"] == "github_credentials"
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_reason_appears_in_message(self):
-        tool = self._make_tool()
-        session = make_session(user_id=_TEST_USER_ID)
-        reason = "Needed to create a pull request."
-        result = await tool._execute(
-            user_id=_TEST_USER_ID, session=session, provider="github", reason=reason
-        )
-        assert isinstance(result, SetupRequirementsResponse)
-        assert reason in result.message
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_session_id_propagated(self):
-        tool = self._make_tool()
-        session = make_session(user_id=_TEST_USER_ID)
-        result = await tool._execute(
-            user_id=_TEST_USER_ID, session=session, provider="github"
-        )
-        assert isinstance(result, SetupRequirementsResponse)
-        assert result.session_id == session.session_id
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_provider_case_insensitive(self):
-        """Provider slug is normalised to lowercase before lookup."""
-        tool = self._make_tool()
-        session = make_session(user_id=_TEST_USER_ID)
-        result = await tool._execute(
-            user_id=_TEST_USER_ID, session=session, provider="GitHub"
-        )
-        assert isinstance(result, SetupRequirementsResponse)
-
-    def test_tool_name(self):
-        assert ConnectIntegrationTool().name == "connect_integration"
-
-    def test_requires_auth(self):
-        assert ConnectIntegrationTool().requires_auth is True
-
-    @pytest.mark.asyncio(loop_scope="session")
-    async def test_unauthenticated_user_gets_need_login_response(self):
-        """execute() with user_id=None must return NeedLoginResponse, not the setup card.
-
-        This verifies that the requires_auth guard in BaseTool.execute() fires
-        before _execute() is called, so unauthenticated callers cannot probe
-        which integrations are configured.
-        """
-        import json
-
-        tool = self._make_tool()
-        # Session still needs a user_id string; the None is passed to execute()
-        # to simulate an unauthenticated call.
-        session = make_session(user_id=_TEST_USER_ID)
-        result = await tool.execute(
-            user_id=None,
-            session=session,
-            tool_call_id="test-call-id",
-            provider="github",
-        )
-        raw = result.output
-        output = json.loads(raw) if isinstance(raw, str) else raw
-        assert output.get("type") == "need_login"
-        assert result.success is False

autogpt_platform/backend/backend/copilot/tools/continue_run_block.py

@@ -30,7 +30,12 @@ class ContinueRunBlockTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return "Resume block execution after a run_block call returned review_required. Pass the review_id."
+        return (
+            "Continue executing a block after human review approval. "
+            "Use this after a run_block call returned review_required. "
+            "Pass the review_id from the review_required response. "
+            "The block will execute with the original pre-approved input data."
+        )
 
     @property
     def parameters(self) -> dict[str, Any]:
@@ -39,7 +44,10 @@ class ContinueRunBlockTool(BaseTool):
             "properties": {
                 "review_id": {
                     "type": "string",
-                    "description": "review_id from the review_required response.",
+                    "description": (
+                        "The review_id from a previous review_required response. "
+                        "This resumes execution with the pre-approved input data."
+                    ),
                 },
             },
             "required": ["review_id"],

autogpt_platform/backend/backend/copilot/tools/create_agent.py

@@ -23,8 +23,12 @@ class CreateAgentTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Create a new agent from JSON (nodes + links). Validates, auto-fixes, and saves. "
-            "Before calling, search for existing agents with find_library_agent."
+            "Create a new agent workflow. Pass `agent_json` with the complete "
+            "agent graph JSON you generated using block schemas from find_block. "
+            "The tool validates, auto-fixes, and saves.\n\n"
+            "IMPORTANT: Before calling this tool, search for relevant existing agents "
+            "using find_library_agent that could be used as building blocks. "
+            "Pass their IDs in the library_agent_ids parameter."
         )
 
     @property
@@ -38,21 +42,34 @@ class CreateAgentTool(BaseTool):
             "properties": {
                 "agent_json": {
                     "type": "object",
-                    "description": "Agent graph with 'nodes' and 'links' arrays.",
+                    "description": (
+                        "The agent JSON to validate and save. "
+                        "Must contain 'nodes' and 'links' arrays, and optionally "
+                        "'name' and 'description'."
+                    ),
                 },
                 "library_agent_ids": {
                     "type": "array",
                     "items": {"type": "string"},
-                    "description": "Library agent IDs as building blocks.",
+                    "description": (
+                        "List of library agent IDs to use as building blocks."
+                    ),
                 },
                 "save": {
                     "type": "boolean",
-                    "description": "Save the agent (default: true). False for preview.",
+                    "description": (
+                        "Whether to save the agent. Default is true. "
+                        "Set to false for preview only."
+                    ),
                     "default": True,
                 },
                 "folder_id": {
                     "type": "string",
-                    "description": "Folder ID to save into (default: root).",
+                    "description": (
+                        "Optional folder ID to save the agent into. "
+                        "If not provided, the agent is saved at root level. "
+                        "Use list_folders to find available folders."
+                    ),
                 },
             },
             "required": ["agent_json"],

autogpt_platform/backend/backend/copilot/tools/customize_agent.py

@@ -23,7 +23,9 @@ class CustomizeAgentTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Customize a marketplace/template agent. Validates, auto-fixes, and saves."
+            "Customize a marketplace or template agent. Pass `agent_json` "
+            "with the complete customized agent JSON. The tool validates, "
+            "auto-fixes, and saves."
         )
 
     @property
@@ -37,21 +39,32 @@ class CustomizeAgentTool(BaseTool):
             "properties": {
                 "agent_json": {
                     "type": "object",
-                    "description": "Customized agent JSON with nodes and links.",
+                    "description": (
+                        "Complete customized agent JSON to validate and save. "
+                        "Optionally include 'name' and 'description'."
+                    ),
                 },
                 "library_agent_ids": {
                     "type": "array",
                     "items": {"type": "string"},
-                    "description": "Library agent IDs as building blocks.",
+                    "description": (
+                        "List of library agent IDs to use as building blocks."
+                    ),
                 },
                 "save": {
                     "type": "boolean",
-                    "description": "Save the agent (default: true). False for preview.",
+                    "description": (
+                        "Whether to save the customized agent. Default is true."
+                    ),
                     "default": True,
                 },
                 "folder_id": {
                     "type": "string",
-                    "description": "Folder ID to save into (default: root).",
+                    "description": (
+                        "Optional folder ID to save the agent into. "
+                        "If not provided, the agent is saved at root level. "
+                        "Use list_folders to find available folders."
+                    ),
                 },
             },
             "required": ["agent_json"],

autogpt_platform/backend/backend/copilot/tools/e2b_sandbox.py

@@ -41,7 +41,8 @@ import contextlib
 import logging
 from typing import Any, Awaitable, Callable, Literal
 
-from e2b import AsyncSandbox, SandboxLifecycle
+from e2b import AsyncSandbox
+from e2b.sandbox.sandbox_api import SandboxLifecycle
 
 from backend.data.redis_client import get_redis_async
 

autogpt_platform/backend/backend/copilot/tools/edit_agent.py

@@ -23,8 +23,12 @@ class EditAgentTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Edit an existing agent. Validates, auto-fixes, and saves. "
-            "Before calling, search for existing agents with find_library_agent."
+            "Edit an existing agent. Pass `agent_json` with the complete "
+            "updated agent JSON you generated. The tool validates, auto-fixes, "
+            "and saves.\n\n"
+            "IMPORTANT: Before calling this tool, if the changes involve adding new "
+            "functionality, search for relevant existing agents using find_library_agent "
+            "that could be used as building blocks."
         )
 
     @property
@@ -38,20 +42,33 @@ class EditAgentTool(BaseTool):
             "properties": {
                 "agent_id": {
                     "type": "string",
-                    "description": "Graph ID or library agent ID to edit.",
+                    "description": (
+                        "The ID of the agent to edit. "
+                        "Can be a graph ID or library agent ID."
+                    ),
                 },
                 "agent_json": {
                     "type": "object",
-                    "description": "Updated agent JSON with nodes and links.",
+                    "description": (
+                        "Complete updated agent JSON to validate and save. "
+                        "Must contain 'nodes' and 'links'. "
+                        "Include 'name' and/or 'description' if they need "
+                        "to be updated."
+                    ),
                 },
                 "library_agent_ids": {
                     "type": "array",
                     "items": {"type": "string"},
-                    "description": "Library agent IDs as building blocks.",
+                    "description": (
+                        "List of library agent IDs to use as building blocks for the changes."
+                    ),
                 },
                 "save": {
                     "type": "boolean",
-                    "description": "Save changes (default: true). False for preview.",
+                    "description": (
+                        "Whether to save the changes. "
+                        "Default is true. Set to false for preview only."
+                    ),
                     "default": True,
                 },
             },

autogpt_platform/backend/backend/copilot/tools/feature_requests.py

@@ -134,7 +134,11 @@ class SearchFeatureRequestsTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return "Search existing feature requests. Check before creating a new one."
+        return (
+            "Search existing feature requests to check if a similar request "
+            "already exists before creating a new one. Returns matching feature "
+            "requests with their ID, title, and description."
+        )
 
     @property
     def parameters(self) -> dict[str, Any]:
@@ -230,9 +234,14 @@ class CreateFeatureRequestTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Create a feature request or add need to existing one. "
-            "Search first to avoid duplicates. Pass existing_issue_id to add to existing. "
-            "Never include PII (names, emails, phone numbers, company names) in title/description."
+            "Create a new feature request or add a customer need to an existing one. "
+            "Always search first with search_feature_requests to avoid duplicates. "
+            "If a matching request exists, pass its ID as existing_issue_id to add "
+            "the user's need to it instead of creating a duplicate. "
+            "IMPORTANT: Never include personally identifiable information (PII) in "
+            "the title or description — no names, emails, phone numbers, company "
+            "names, or other identifying details. Write titles and descriptions in "
+            "generic, feature-focused language."
         )
 
     @property
@@ -242,15 +251,28 @@ class CreateFeatureRequestTool(BaseTool):
             "properties": {
                 "title": {
                     "type": "string",
-                    "description": "Feature request title. No names, emails, or company info.",
+                    "description": (
+                        "Title for the feature request. Must be generic and "
+                        "feature-focused — do not include any user names, emails, "
+                        "company names, or other PII."
+                    ),
                 },
                 "description": {
                     "type": "string",
-                    "description": "What the user wants and why. No names, emails, or company info.",
+                    "description": (
+                        "Detailed description of what the user wants and why. "
+                        "Must not contain any personally identifiable information "
+                        "(PII) — describe the feature need generically without "
+                        "referencing specific users, companies, or contact details."
+                    ),
                 },
                 "existing_issue_id": {
                     "type": "string",
-                    "description": "Linear issue ID to add need to (from search results).",
+                    "description": (
+                        "If adding a need to an existing feature request, "
+                        "provide its Linear issue ID (from search results). "
+                        "Omit to create a new feature request."
+                    ),
                 },
             },
             "required": ["title", "description"],

autogpt_platform/backend/backend/copilot/tools/find_agent.py

@@ -18,7 +18,10 @@ class FindAgentTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return "Search marketplace agents by capability, or look up by slug ('username/agent-name')."
+        return (
+            "Discover agents from the marketplace based on capabilities and "
+            "user needs, or look up a specific agent by its creator/slug ID."
+        )
 
     @property
     def parameters(self) -> dict[str, Any]:
@@ -27,7 +30,7 @@ class FindAgentTool(BaseTool):
             "properties": {
                 "query": {
                     "type": "string",
-                    "description": "Search keywords, or 'username/agent-name' for direct slug lookup.",
+                    "description": "Search query describing what the user wants to accomplish, or a creator/slug ID (e.g. 'username/agent-name') for direct lookup. Use single keywords for best results.",
                 },
             },
             "required": ["query"],

autogpt_platform/backend/backend/copilot/tools/find_block.py

@@ -54,9 +54,13 @@ class FindBlockTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Search blocks by name or description. Returns block IDs for run_block. "
-            "Always call this FIRST to get block IDs before using run_block. "
-            "Then call run_block with the block's id and empty input_data to see its detailed schema."
+            "Search for available blocks by name or description, or look up a "
+            "specific block by its ID. "
+            "Blocks are reusable components that perform specific tasks like "
+            "sending emails, making API calls, processing text, etc. "
+            "IMPORTANT: Use this tool FIRST to get the block's 'id' before calling run_block. "
+            "The response includes each block's id, name, and description. "
+            "Call run_block with the block's id **with no inputs** to see detailed inputs/outputs and execute it."
         )
 
     @property
@@ -66,11 +70,19 @@ class FindBlockTool(BaseTool):
             "properties": {
                 "query": {
                     "type": "string",
-                    "description": "Search keywords (e.g. 'email', 'http', 'ai').",
+                    "description": (
+                        "Search query to find blocks by name or description, "
+                        "or a block ID (UUID) for direct lookup. "
+                        "Use keywords like 'email', 'http', 'text', 'ai', etc."
+                    ),
                 },
                 "include_schemas": {
                     "type": "boolean",
-                    "description": "Include full input/output schemas (for agent JSON generation).",
+                    "description": (
+                        "If true, include full input_schema and output_schema "
+                        "for each block. Use when generating agent JSON that "
+                        "needs block schemas. Default is false."
+                    ),
                     "default": False,
                 },
             },

autogpt_platform/backend/backend/copilot/tools/find_library_agent.py

@@ -19,8 +19,13 @@ class FindLibraryAgentTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Search user's library agents. Returns graph_id, schemas for sub-agent composition. "
-            "Omit query to list all."
+            "Search for or list agents in the user's library. Use this to find "
+            "agents the user has already added to their library, including agents "
+            "they created or added from the marketplace. "
+            "When creating agents with sub-agent composition, use this to get "
+            "the agent's graph_id, graph_version, input_schema, and output_schema "
+            "needed for AgentExecutorBlock nodes. "
+            "Omit the query to list all agents."
         )
 
     @property
@@ -30,7 +35,10 @@ class FindLibraryAgentTool(BaseTool):
             "properties": {
                 "query": {
                     "type": "string",
-                    "description": "Search by name/description. Omit to list all.",
+                    "description": (
+                        "Search query to find agents by name or description. "
+                        "Omit to list all agents in the library."
+                    ),
                 },
             },
             "required": [],

autogpt_platform/backend/backend/copilot/tools/fix_agent.py

@@ -22,10 +22,20 @@ class FixAgentGraphTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Auto-fix common agent JSON issues: missing/invalid UUIDs, StoreValueBlock prerequisites, "
-            "double curly brace escaping, AddToList/AddToDictionary prerequisites, credentials, "
-            "node spacing, AI model defaults, link static properties, and type mismatches. "
-            "Returns fixed JSON and list of fixes applied."
+            "Auto-fix common issues in an agent JSON graph. Applies fixes for:\n"
+            "- Missing or invalid UUIDs on nodes and links\n"
+            "- StoreValueBlock prerequisites for ConditionBlock\n"
+            "- Double curly brace escaping in prompt templates\n"
+            "- AddToList/AddToDictionary prerequisite blocks\n"
+            "- CodeExecutionBlock output field naming\n"
+            "- Missing credentials configuration\n"
+            "- Node X coordinate spacing (800+ units apart)\n"
+            "- AI model default parameters\n"
+            "- Link static properties based on input schema\n"
+            "- Type mismatches (inserts conversion blocks)\n\n"
+            "Returns the fixed agent JSON plus a list of fixes applied. "
+            "After fixing, the agent is re-validated. If still invalid, "
+            "the remaining errors are included in the response."
         )
 
     @property

autogpt_platform/backend/backend/copilot/tools/get_agent_building_guide.py

@@ -42,7 +42,12 @@ class GetAgentBuildingGuideTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return "Get the agent JSON building guide (nodes, links, AgentExecutorBlock, MCPToolBlock usage). Call before generating agent JSON."
+        return (
+            "Returns the complete guide for building agent JSON graphs, including "
+            "block IDs, link structure, AgentInputBlock, AgentOutputBlock, "
+            "AgentExecutorBlock (for sub-agent composition), and MCPToolBlock usage. "
+            "Call this before generating agent JSON to ensure correct structure."
+        )
 
     @property
     def parameters(self) -> dict[str, Any]:

autogpt_platform/backend/backend/copilot/tools/get_doc_page.py

@@ -25,7 +25,8 @@ class GetDocPageTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Read full documentation page content by path (from search_docs results)."
+            "Get the full content of a documentation page by its path. "
+            "Use this after search_docs to read the complete content of a relevant page."
         )
 
     @property
@@ -35,7 +36,10 @@ class GetDocPageTool(BaseTool):
             "properties": {
                 "path": {
                     "type": "string",
-                    "description": "Doc file path (e.g. 'platform/block-sdk-guide.md').",
+                    "description": (
+                        "The path to the documentation file, as returned by search_docs. "
+                        "Example: 'platform/block-sdk-guide.md'"
+                    ),
                 },
             },
             "required": ["path"],

autogpt_platform/backend/backend/copilot/tools/get_mcp_guide.py

@@ -38,7 +38,11 @@ class GetMCPGuideTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return "Get MCP server URLs and auth guide. Call before run_mcp_tool if you need a server URL or auth info."
+        return (
+            "Returns the MCP tool guide: known hosted server URLs (Notion, Linear, "
+            "Stripe, Intercom, Cloudflare, Atlassian) and authentication workflow. "
+            "Call before using run_mcp_tool if you need a server URL or auth info."
+        )
 
     @property
     def parameters(self) -> dict[str, Any]:

autogpt_platform/backend/backend/copilot/tools/manage_folders.py

@@ -88,7 +88,10 @@ class CreateFolderTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return "Create a library folder. Use parent_id to nest inside another folder."
+        return (
+            "Create a new folder in the user's library to organize agents. "
+            "Optionally nest it inside an existing folder using parent_id."
+        )
 
     @property
     def requires_auth(self) -> bool:
@@ -101,19 +104,22 @@ class CreateFolderTool(BaseTool):
             "properties": {
                 "name": {
                     "type": "string",
-                    "description": "Folder name (max 100 chars).",
+                    "description": "Name for the new folder (max 100 chars).",
                 },
                 "parent_id": {
                     "type": "string",
-                    "description": "Parent folder ID (omit for root).",
+                    "description": (
+                        "ID of the parent folder to nest inside. "
+                        "Omit to create at root level."
+                    ),
                 },
                 "icon": {
                     "type": "string",
-                    "description": "Icon identifier.",
+                    "description": "Optional icon identifier for the folder.",
                 },
                 "color": {
                     "type": "string",
-                    "description": "Hex color (#RRGGBB).",
+                    "description": "Optional hex color code (#RRGGBB).",
                 },
             },
             "required": ["name"],
@@ -169,9 +175,13 @@ class ListFoldersTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "List library folders. Omit parent_id for full tree. "
-            "Set include_agents=true when user asks about agents, wants to see "
-            "what's in their folders, or mentions agents alongside folders."
+            "List the user's library folders. "
+            "Omit parent_id to get the full folder tree. "
+            "Provide parent_id to list only direct children of that folder. "
+            "Set include_agents=true to also return the agents inside each folder "
+            "and root-level agents not in any folder. Always set include_agents=true "
+            "when the user asks about agents, wants to see what's in their folders, "
+            "or mentions agents alongside folders."
         )
 
     @property
@@ -185,11 +195,17 @@ class ListFoldersTool(BaseTool):
             "properties": {
                 "parent_id": {
                     "type": "string",
-                    "description": "List children of this folder (omit for full tree).",
+                    "description": (
+                        "List children of this folder. "
+                        "Omit to get the full folder tree."
+                    ),
                 },
                 "include_agents": {
                     "type": "boolean",
-                    "description": "Include agents in each folder (default: false).",
+                    "description": (
+                        "Whether to include the list of agents inside each folder. "
+                        "Defaults to false."
+                    ),
                 },
             },
             "required": [],
@@ -341,7 +357,10 @@ class MoveFolderTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return "Move a folder. Set target_parent_id to null for root."
+        return (
+            "Move a folder to a different parent folder. "
+            "Set target_parent_id to null to move to root level."
+        )
 
     @property
     def requires_auth(self) -> bool:
@@ -354,11 +373,14 @@ class MoveFolderTool(BaseTool):
             "properties": {
                 "folder_id": {
                     "type": "string",
-                    "description": "Folder ID.",
+                    "description": "ID of the folder to move.",
                 },
                 "target_parent_id": {
                     "type": ["string", "null"],
-                    "description": "New parent folder ID (null for root).",
+                    "description": (
+                        "ID of the new parent folder. "
+                        "Use null to move to root level."
+                    ),
                 },
             },
             "required": ["folder_id"],
@@ -411,7 +433,10 @@ class DeleteFolderTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return "Delete a folder. Agents inside move to root (not deleted)."
+        return (
+            "Delete a folder from the user's library. "
+            "Agents inside the folder are moved to root level (not deleted)."
+        )
 
     @property
     def requires_auth(self) -> bool:
@@ -474,7 +499,10 @@ class MoveAgentsToFolderTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return "Move agents to a folder. Set folder_id to null for root."
+        return (
+            "Move one or more agents to a folder. "
+            "Set folder_id to null to move agents to root level."
+        )
 
     @property
     def requires_auth(self) -> bool:
@@ -488,11 +516,13 @@ class MoveAgentsToFolderTool(BaseTool):
                 "agent_ids": {
                     "type": "array",
                     "items": {"type": "string"},
-                    "description": "Library agent IDs to move.",
+                    "description": "List of library agent IDs to move.",
                 },
                 "folder_id": {
                     "type": ["string", "null"],
-                    "description": "Target folder ID (null for root).",
+                    "description": (
+                        "Target folder ID. Use null to move to root level."
+                    ),
                 },
             },
             "required": ["agent_ids"],

autogpt_platform/backend/backend/copilot/tools/run_agent.py

@@ -104,11 +104,19 @@ class RunAgentTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return (
-            "Run or schedule an agent. Automatically checks inputs and credentials. "
-            "Identify by username_agent_slug ('user/agent') or library_agent_id. "
-            "For scheduling, provide schedule_name + cron."
-        )
+        return """Run or schedule an agent from the marketplace or user's library.
+
+        The tool automatically handles the setup flow:
+        - Returns missing inputs if required fields are not provided
+        - Returns missing credentials if user needs to configure them
+        - Executes immediately if all requirements are met
+        - Schedules execution if cron expression is provided
+
+        Identify the agent using either:
+        - username_agent_slug: Marketplace format 'username/agent-name'
+        - library_agent_id: ID of an agent in the user's library
+
+        For scheduled execution, provide: schedule_name, cron, and optionally timezone."""
 
     @property
     def parameters(self) -> dict[str, Any]:
@@ -117,38 +125,40 @@ class RunAgentTool(BaseTool):
             "properties": {
                 "username_agent_slug": {
                     "type": "string",
-                    "description": "Marketplace format 'username/agent-name'.",
+                    "description": "Agent identifier in format 'username/agent-name'",
                 },
                 "library_agent_id": {
                     "type": "string",
-                    "description": "Library agent ID.",
+                    "description": "Library agent ID from user's library",
                 },
                 "inputs": {
                     "type": "object",
-                    "description": "Input values for the agent.",
+                    "description": "Input values for the agent",
                     "additionalProperties": True,
                 },
                 "use_defaults": {
                     "type": "boolean",
-                    "description": "Run with default values (confirm with user first).",
+                    "description": "Set to true to run with default values (user must confirm)",
                 },
                 "schedule_name": {
                     "type": "string",
-                    "description": "Name for scheduled execution. Providing this triggers scheduling mode (also requires cron).",
+                    "description": "Name for scheduled execution (triggers scheduling mode)",
                 },
                 "cron": {
                     "type": "string",
-                    "description": "Cron expression (min hour day month weekday).",
+                    "description": "Cron expression (5 fields: min hour day month weekday)",
                 },
                 "timezone": {
                     "type": "string",
-                    "description": "IANA timezone (default: UTC).",
+                    "description": "IANA timezone for schedule (default: UTC)",
                 },
                 "wait_for_result": {
                     "type": "integer",
-                    "description": "Max seconds to wait for completion (0-300).",
-                    "minimum": 0,
-                    "maximum": 300,
+                    "description": (
+                        "Max seconds to wait for execution to complete (0-300). "
+                        "If >0, blocks until the execution finishes or times out. "
+                        "Returns execution outputs when complete."
+                    ),
                 },
             },
             "required": [],

autogpt_platform/backend/backend/copilot/tools/run_block.py

@@ -45,10 +45,13 @@ class RunBlockTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Execute a block. IMPORTANT: Always get block_id from find_block first "
-            "— do NOT guess or fabricate IDs. "
-            "Call with empty input_data to see schema, then with data to execute. "
-            "If review_required, use continue_run_block."
+            "Execute a specific block with the provided input data. "
+            "IMPORTANT: You MUST call find_block first to get the block's 'id' - "
+            "do NOT guess or make up block IDs. "
+            "On first attempt (without input_data), returns detailed schema showing "
+            "required inputs and outputs. Then call again with proper input_data to execute. "
+            "If a block requires human review, use continue_run_block with the "
+            "review_id after the user approves."
         )
 
     @property
@@ -58,14 +61,28 @@ class RunBlockTool(BaseTool):
             "properties": {
                 "block_id": {
                     "type": "string",
-                    "description": "Block ID from find_block results.",
+                    "description": (
+                        "The block's 'id' field from find_block results. "
+                        "NEVER guess this - always get it from find_block first."
+                    ),
+                },
+                "block_name": {
+                    "type": "string",
+                    "description": (
+                        "The block's human-readable name from find_block results. "
+                        "Used for display purposes in the UI."
+                    ),
                 },
                 "input_data": {
                     "type": "object",
-                    "description": "Input values. Use {} first to see schema.",
+                    "description": (
+                        "Input values for the block. "
+                        "First call with empty {} to see the block's schema, "
+                        "then call again with proper values to execute."
+                    ),
                 },
             },
-            "required": ["block_id", "input_data"],
+            "required": ["block_id", "block_name", "input_data"],
         }
 
     @property

autogpt_platform/backend/backend/copilot/tools/run_mcp_tool.py

@@ -57,9 +57,10 @@ class RunMCPToolTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Discover and execute MCP server tools. "
-            "Call with server_url only to list tools, then with tool_name + tool_arguments to execute. "
-            "Call get_mcp_guide first for server URLs and auth."
+            "Connect to an MCP (Model Context Protocol) server to discover and execute its tools. "
+            "Two-step: (1) call with server_url to list available tools, "
+            "(2) call again with server_url + tool_name + tool_arguments to execute. "
+            "Call get_mcp_guide for known server URLs and auth details."
         )
 
     @property
@@ -69,15 +70,24 @@ class RunMCPToolTool(BaseTool):
             "properties": {
                 "server_url": {
                     "type": "string",
-                    "description": "MCP server URL (Streamable HTTP endpoint).",
+                    "description": (
+                        "URL of the MCP server (Streamable HTTP endpoint), "
+                        "e.g. https://mcp.example.com/mcp"
+                    ),
                 },
                 "tool_name": {
                     "type": "string",
-                    "description": "Tool to execute. Omit to discover available tools.",
+                    "description": (
+                        "Name of the MCP tool to execute. "
+                        "Omit on first call to discover available tools."
+                    ),
                 },
                 "tool_arguments": {
                     "type": "object",
-                    "description": "Arguments matching the tool's input schema.",
+                    "description": (
+                        "Arguments to pass to the selected tool. "
+                        "Must match the tool's input schema returned during discovery."
+                    ),
                 },
             },
             "required": ["server_url"],

autogpt_platform/backend/backend/copilot/tools/search_docs.py

@@ -38,7 +38,11 @@ class SearchDocsTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return "Search platform documentation by keyword. Use get_doc_page to read full results."
+        return (
+            "Search the AutoGPT platform documentation for information about "
+            "how to use the platform, build agents, configure blocks, and more. "
+            "Returns relevant documentation sections. Use get_doc_page to read full content."
+        )
 
     @property
     def parameters(self) -> dict[str, Any]:
@@ -47,7 +51,10 @@ class SearchDocsTool(BaseTool):
             "properties": {
                 "query": {
                     "type": "string",
-                    "description": "Documentation search query.",
+                    "description": (
+                        "Search query to find relevant documentation. "
+                        "Use natural language to describe what you're looking for."
+                    ),
                 },
             },
             "required": ["query"],

autogpt_platform/backend/backend/copilot/tools/tool_schema_test.py

@@ -1,119 +0,0 @@
-"""Schema regression tests for all registered CoPilot tools.
-
-Validates that every tool in TOOL_REGISTRY produces a well-formed schema:
-- description is non-empty
-- all `required` fields exist in `properties`
-- every property has a `type` and `description`
-- total schema character budget does not regress past threshold
-"""
-
-import json
-from typing import Any, cast
-
-import pytest
-
-from backend.copilot.tools import TOOL_REGISTRY
-
-# Character budget (~4 chars/token heuristic, targeting ~8000 tokens)
-_CHAR_BUDGET = 32_000
-
-
-@pytest.fixture(scope="module")
-def all_tool_schemas() -> list[tuple[str, Any]]:
-    """Return (tool_name, openai_schema) pairs for every registered tool."""
-    return [(name, tool.as_openai_tool()) for name, tool in TOOL_REGISTRY.items()]
-
-
-def _get_parametrize_data() -> list[tuple[str, object]]:
-    """Build parametrize data at collection time."""
-    return [(name, tool.as_openai_tool()) for name, tool in TOOL_REGISTRY.items()]
-
-
-@pytest.mark.parametrize(
-    "tool_name,schema",
-    _get_parametrize_data(),
-    ids=[name for name, _ in _get_parametrize_data()],
-)
-class TestToolSchema:
-    """Validate schema invariants for every registered tool."""
-
-    def test_description_non_empty(self, tool_name: str, schema: dict) -> None:
-        desc = schema["function"].get("description", "")
-        assert desc, f"Tool '{tool_name}' has an empty description"
-
-    def test_required_fields_exist_in_properties(
-        self, tool_name: str, schema: dict
-    ) -> None:
-        params = schema["function"].get("parameters", {})
-        properties = params.get("properties", {})
-        required = params.get("required", [])
-        for field in required:
-            assert field in properties, (
-                f"Tool '{tool_name}': required field '{field}' "
-                f"not found in properties {list(properties.keys())}"
-            )
-
-    def test_every_property_has_type_and_description(
-        self, tool_name: str, schema: dict
-    ) -> None:
-        params = schema["function"].get("parameters", {})
-        properties = params.get("properties", {})
-        for prop_name, prop_def in properties.items():
-            assert (
-                "type" in prop_def
-            ), f"Tool '{tool_name}', property '{prop_name}' is missing 'type'"
-            assert (
-                "description" in prop_def
-            ), f"Tool '{tool_name}', property '{prop_name}' is missing 'description'"
-
-
-def test_browser_act_action_enum_complete() -> None:
-    """Assert browser_act action enum still contains all 14 supported actions.
-
-    This prevents future PRs from accidentally dropping actions during description
-    trimming. The enum is the authoritative list — this locks it at 14 values.
-    """
-    tool = TOOL_REGISTRY["browser_act"]
-    schema = tool.as_openai_tool()
-    fn_def = schema["function"]
-    params = cast(dict[str, Any], fn_def.get("parameters", {}))
-    actions = params["properties"]["action"]["enum"]
-    expected = {
-        "click",
-        "dblclick",
-        "fill",
-        "type",
-        "scroll",
-        "hover",
-        "press",
-        "check",
-        "uncheck",
-        "select",
-        "wait",
-        "back",
-        "forward",
-        "reload",
-    }
-    assert set(actions) == expected, (
-        f"browser_act action enum changed. Got {set(actions)}, expected {expected}. "
-        "If you added/removed an action, update this test intentionally."
-    )
-
-
-def test_total_schema_char_budget() -> None:
-    """Assert total tool schema size stays under the character budget.
-
-    This locks in the 34% token reduction from #12398 and prevents future
-    description bloat from eroding the gains. Uses character count with a
-    ~4 chars/token heuristic (budget of 32000 chars ≈ 8000 tokens).
-    Character count is tokenizer-agnostic — no dependency on GPT or Claude
-    tokenizers — while still providing a stable regression gate.
-    """
-    schemas = [tool.as_openai_tool() for tool in TOOL_REGISTRY.values()]
-    serialized = json.dumps(schemas)
-    total_chars = len(serialized)
-    assert total_chars < _CHAR_BUDGET, (
-        f"Tool schemas use {total_chars} chars (~{total_chars // 4} tokens), "
-        f"exceeding budget of {_CHAR_BUDGET} chars (~{_CHAR_BUDGET // 4} tokens). "
-        f"Description bloat detected — trim descriptions or raise the budget intentionally."
-    )

autogpt_platform/backend/backend/copilot/tools/validate_agent.py

@@ -22,9 +22,17 @@ class ValidateAgentGraphTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Validate agent JSON for correctness: block_ids, links, required fields, "
-            "type compatibility, nested sink notation, prompt brace escaping, "
-            "and AgentExecutorBlock configs. On failure, use fix_agent_graph to auto-fix."
+            "Validate an agent JSON graph for correctness. Checks:\n"
+            "- All block_ids reference real blocks\n"
+            "- All links reference valid source/sink nodes and fields\n"
+            "- Required input fields are wired or have defaults\n"
+            "- Data types are compatible across links\n"
+            "- Nested sink links use correct notation\n"
+            "- Prompt templates use proper curly brace escaping\n"
+            "- AgentExecutorBlock configurations are valid\n\n"
+            "Call this after generating agent JSON to verify correctness. "
+            "If validation fails, either fix issues manually based on the error "
+            "descriptions, or call fix_agent_graph to auto-fix common problems."
         )
 
     @property
@@ -38,7 +46,11 @@ class ValidateAgentGraphTool(BaseTool):
             "properties": {
                 "agent_json": {
                     "type": "object",
-                    "description": "Agent JSON with 'nodes' and 'links' arrays.",
+                    "description": (
+                        "The agent JSON to validate. Must contain 'nodes' and 'links' arrays. "
+                        "Each node needs: id (UUID), block_id, input_default, metadata. "
+                        "Each link needs: id (UUID), source_id, source_name, sink_id, sink_name."
+                    ),
                 },
             },
             "required": ["agent_json"],

autogpt_platform/backend/backend/copilot/tools/web_fetch.py

@@ -59,7 +59,13 @@ class WebFetchTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return "Fetch a public web page. Public URLs only — internal addresses blocked. Returns readable text from HTML by default."
+        return (
+            "Fetch the content of a public web page by URL. "
+            "Returns readable text extracted from HTML by default. "
+            "Useful for reading documentation, articles, and API responses. "
+            "Only supports HTTP/HTTPS GET requests to public URLs "
+            "(private/internal network addresses are blocked)."
+        )
 
     @property
     def parameters(self) -> dict[str, Any]:
@@ -68,11 +74,14 @@ class WebFetchTool(BaseTool):
             "properties": {
                 "url": {
                     "type": "string",
-                    "description": "Public HTTP/HTTPS URL.",
+                    "description": "The public HTTP/HTTPS URL to fetch.",
                 },
                 "extract_text": {
                     "type": "boolean",
-                    "description": "Extract text from HTML (default: true).",
+                    "description": (
+                        "If true (default), extract readable text from HTML. "
+                        "If false, return raw content."
+                    ),
                     "default": True,
                 },
             },

autogpt_platform/backend/backend/copilot/tools/workspace_files.py

@@ -27,8 +27,6 @@ from .models import ErrorResponse, ResponseType, ToolResponseBase
 
 logger = logging.getLogger(__name__)
 
-_MAX_FILE_SIZE_MB = Config().max_file_size_mb
-
 # Sentinel file_id used when a tool-result file is read directly from the local
 # host filesystem (rather than from workspace storage).
 _LOCAL_TOOL_RESULT_FILE_ID = "local"
@@ -417,7 +415,13 @@ class ListWorkspaceFilesTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return "List persistent workspace files. For ephemeral session files, use SDK Glob/Read instead. Optionally filter by path prefix."
+        return (
+            "List files in the user's persistent workspace (cloud storage). "
+            "These files survive across sessions. "
+            "For ephemeral session files, use the SDK Read/Glob tools instead. "
+            "Returns file names, paths, sizes, and metadata. "
+            "Optionally filter by path prefix."
+        )
 
     @property
     def parameters(self) -> dict[str, Any]:
@@ -426,17 +430,24 @@ class ListWorkspaceFilesTool(BaseTool):
             "properties": {
                 "path_prefix": {
                     "type": "string",
-                    "description": "Filter by path prefix (e.g. '/documents/').",
+                    "description": (
+                        "Optional path prefix to filter files "
+                        "(e.g., '/documents/' to list only files in documents folder). "
+                        "By default, only files from the current session are listed."
+                    ),
                 },
                 "limit": {
                     "type": "integer",
-                    "description": "Max files to return (default 50, max 100).",
+                    "description": "Maximum number of files to return (default 50, max 100)",
                     "minimum": 1,
                     "maximum": 100,
                 },
                 "include_all_sessions": {
                     "type": "boolean",
-                    "description": "Include files from all sessions (default: false).",
+                    "description": (
+                        "If true, list files from all sessions. "
+                        "Default is false (only current session's files)."
+                    ),
                 },
             },
             "required": [],
@@ -519,11 +530,18 @@ class ReadWorkspaceFileTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Read a file from persistent workspace. Specify file_id or path. "
-            "Small text/image files return inline; large/binary return metadata+URL. "
-            "Use save_to_path to copy to working dir for processing. "
-            "Use offset/length for paginated reads. "
-            "Paths scoped to current session; use /sessions/<id>/... for cross-session access."
+            "Read a file from the user's persistent workspace (cloud storage). "
+            "These files survive across sessions. "
+            "For ephemeral session files, use the SDK Read tool instead. "
+            "Specify either file_id or path to identify the file. "
+            "For small text files, returns content directly. "
+            "For large or binary files, returns metadata and a download URL. "
+            "Use 'save_to_path' to copy the file to the working directory "
+            "(sandbox or ephemeral) for processing with bash_exec or file tools. "
+            "Use 'offset' and 'length' for paginated reads of large files "
+            "(e.g., persisted tool outputs). "
+            "Paths are scoped to the current session by default. "
+            "Use /sessions/<session_id>/... for cross-session access."
         )
 
     @property
@@ -533,30 +551,48 @@ class ReadWorkspaceFileTool(BaseTool):
             "properties": {
                 "file_id": {
                     "type": "string",
-                    "description": "File ID from list_workspace_files.",
+                    "description": "The file's unique ID (from list_workspace_files)",
                 },
                 "path": {
                     "type": "string",
-                    "description": "Virtual file path (e.g. '/documents/report.pdf').",
+                    "description": (
+                        "The virtual file path (e.g., '/documents/report.pdf'). "
+                        "Scoped to current session by default."
+                    ),
                 },
                 "save_to_path": {
                     "type": "string",
-                    "description": "Copy file to this working directory path for processing.",
+                    "description": (
+                        "If provided, save the file to this path in the working "
+                        "directory (cloud sandbox when E2B is active, or "
+                        "ephemeral dir otherwise) so it can be processed with "
+                        "bash_exec or file tools. "
+                        "The file content is still returned in the response."
+                    ),
                 },
                 "force_download_url": {
                     "type": "boolean",
-                    "description": "Always return metadata+URL instead of inline content.",
+                    "description": (
+                        "If true, always return metadata+URL instead of inline content. "
+                        "Default is false (auto-selects based on file size/type)."
+                    ),
                 },
                 "offset": {
                     "type": "integer",
-                    "description": "Character offset for paginated reads (0-based).",
+                    "description": (
+                        "Character offset to start reading from (0-based). "
+                        "Use with 'length' for paginated reads of large files."
+                    ),
                 },
                 "length": {
                     "type": "integer",
-                    "description": "Max characters to return for paginated reads.",
+                    "description": (
+                        "Maximum number of characters to return. "
+                        "Defaults to full file. Use with 'offset' for paginated reads."
+                    ),
                 },
             },
-            "required": [],  # At least one of file_id or path must be provided
+            "required": [],  # At least one must be provided
         }
 
     @property
@@ -719,10 +755,15 @@ class WriteWorkspaceFileTool(BaseTool):
     @property
     def description(self) -> str:
         return (
-            "Write a file to persistent workspace (survives across sessions). "
-            "Provide exactly one of: content (text), content_base64 (binary), "
-            f"or source_path (copy from working dir). Max {_MAX_FILE_SIZE_MB}MB. "
-            "Paths scoped to current session; use /sessions/<id>/... for cross-session access."
+            "Write or create a file in the user's persistent workspace (cloud storage). "
+            "These files survive across sessions. "
+            "For ephemeral session files, use the SDK Write tool instead. "
+            "Provide content as plain text via 'content', OR base64-encoded via "
+            "'content_base64', OR copy a file from the ephemeral working directory "
+            "via 'source_path'. Exactly one of these three is required. "
+            f"Maximum file size is {Config().max_file_size_mb}MB. "
+            "Files are saved to the current session's folder by default. "
+            "Use /sessions/<session_id>/... for cross-session access."
         )
 
     @property
@@ -732,31 +773,51 @@ class WriteWorkspaceFileTool(BaseTool):
             "properties": {
                 "filename": {
                     "type": "string",
-                    "description": "Filename (e.g. 'report.pdf').",
+                    "description": "Name for the file (e.g., 'report.pdf')",
                 },
                 "content": {
                     "type": "string",
-                    "description": "Plain text content. Mutually exclusive with content_base64/source_path.",
+                    "description": (
+                        "Plain text content to write. Use this for text files "
+                        "(code, configs, documents, etc.). "
+                        "Mutually exclusive with content_base64 and source_path."
+                    ),
                 },
                 "content_base64": {
                     "type": "string",
-                    "description": "Base64-encoded binary content. Mutually exclusive with content/source_path.",
+                    "description": (
+                        "Base64-encoded file content. Use this for binary files "
+                        "(images, PDFs, etc.). "
+                        "Mutually exclusive with content and source_path."
+                    ),
                 },
                 "source_path": {
                     "type": "string",
-                    "description": "Working directory path to copy to workspace. Mutually exclusive with content/content_base64.",
+                    "description": (
+                        "Path to a file in the ephemeral working directory to "
+                        "copy to workspace (e.g., '/tmp/copilot-.../output.csv'). "
+                        "Use this to persist files created by bash_exec or SDK Write. "
+                        "Mutually exclusive with content and content_base64."
+                    ),
                 },
                 "path": {
                     "type": "string",
-                    "description": "Virtual path (e.g. '/documents/report.pdf'). Defaults to '/{filename}'.",
+                    "description": (
+                        "Optional virtual path where to save the file "
+                        "(e.g., '/documents/report.pdf'). "
+                        "Defaults to '/{filename}'. Scoped to current session."
+                    ),
                 },
                 "mime_type": {
                     "type": "string",
-                    "description": "MIME type. Auto-detected from filename if omitted.",
+                    "description": (
+                        "Optional MIME type of the file. "
+                        "Auto-detected from filename if not provided."
+                    ),
                 },
                 "overwrite": {
                     "type": "boolean",
-                    "description": "Overwrite if file exists (default: false).",
+                    "description": "Whether to overwrite if file exists at path (default: false)",
                 },
             },
             "required": ["filename"],
@@ -798,10 +859,10 @@ class WriteWorkspaceFileTool(BaseTool):
             return resolved
         content: bytes = resolved
 
-        max_size = _MAX_FILE_SIZE_MB * 1024 * 1024
+        max_size = Config().max_file_size_mb * 1024 * 1024
         if len(content) > max_size:
             return ErrorResponse(
-                message=f"File too large. Maximum size is {_MAX_FILE_SIZE_MB}MB",
+                message=f"File too large. Maximum size is {Config().max_file_size_mb}MB",
                 session_id=session_id,
             )
 
@@ -883,7 +944,12 @@ class DeleteWorkspaceFileTool(BaseTool):
 
     @property
     def description(self) -> str:
-        return "Delete a file from persistent workspace. Specify file_id or path. Paths scoped to current session; use /sessions/<id>/... for cross-session access."
+        return (
+            "Delete a file from the user's persistent workspace (cloud storage). "
+            "Specify either file_id or path to identify the file. "
+            "Paths are scoped to the current session by default. "
+            "Use /sessions/<session_id>/... for cross-session access."
+        )
 
     @property
     def parameters(self) -> dict[str, Any]:
@@ -892,14 +958,17 @@ class DeleteWorkspaceFileTool(BaseTool):
             "properties": {
                 "file_id": {
                     "type": "string",
-                    "description": "File ID from list_workspace_files.",
+                    "description": "The file's unique ID (from list_workspace_files)",
                 },
                 "path": {
                     "type": "string",
-                    "description": "Virtual file path.",
+                    "description": (
+                        "The virtual file path (e.g., '/documents/report.pdf'). "
+                        "Scoped to current session by default."
+                    ),
                 },
             },
-            "required": [],  # At least one of file_id or path must be provided
+            "required": [],  # At least one must be provided
         }
 
     @property

autogpt_platform/backend/backend/data/block_cost_config.py

@@ -76,6 +76,7 @@ MODEL_COST: dict[LlmModel, int] = {
     LlmModel.GPT4O_MINI: 1,
     LlmModel.GPT4O: 3,
     LlmModel.GPT4_TURBO: 10,
+    LlmModel.GPT3_5_TURBO: 1,
     LlmModel.CLAUDE_4_1_OPUS: 21,
     LlmModel.CLAUDE_4_OPUS: 21,
     LlmModel.CLAUDE_4_SONNET: 5,

autogpt_platform/backend/backend/data/db.py

@@ -38,10 +38,6 @@ POOL_TIMEOUT = os.getenv("DB_POOL_TIMEOUT")
 if POOL_TIMEOUT:
     DATABASE_URL = add_param(DATABASE_URL, "pool_timeout", POOL_TIMEOUT)
 
-STMT_CACHE_SIZE = os.getenv("DB_STATEMENT_CACHE_SIZE")
-if STMT_CACHE_SIZE:
-    DATABASE_URL = add_param(DATABASE_URL, "statement_cache_size", STMT_CACHE_SIZE)
-
 HTTP_TIMEOUT = int(POOL_TIMEOUT) if POOL_TIMEOUT else None
 
 prisma = Prisma(

autogpt_platform/backend/backend/data/execution.py

@@ -877,12 +877,12 @@ async def get_execution_outputs_by_node_exec_id(
         where={"referencedByOutputExecId": node_exec_id}
     )
 
-    result: CompletedBlockOutput = defaultdict(list)
+    result = {}
     for output in outputs:
         if output.data is not None:
-            result[output.name].append(type_utils.convert(output.data, JsonValue))
+            result[output.name] = type_utils.convert(output.data, JsonValue)
 
-    return dict(result)
+    return result
 
 
 async def update_graph_execution_start_time(

autogpt_platform/backend/backend/data/execution_outputs_test.py

@@ -1,102 +0,0 @@
-"""Test that get_execution_outputs_by_node_exec_id returns CompletedBlockOutput.
-
-CompletedBlockOutput is dict[str, list[Any]] — values must be lists.
-The RPC service layer validates return types via TypeAdapter, so if
-the function returns plain values instead of lists, it causes:
-
-    1 validation error for dict[str,list[any]] response
-    Input should be a valid list [type=list_type, input_value='', input_type=str]
-
-This breaks SmartDecisionMakerBlock agent mode tool execution.
-"""
-
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import pytest
-from pydantic import TypeAdapter
-
-from backend.data.block import CompletedBlockOutput
-
-
-@pytest.mark.asyncio
-async def test_outputs_are_lists():
-    """Each value in the returned dict must be a list, matching CompletedBlockOutput."""
-    from backend.data.execution import get_execution_outputs_by_node_exec_id
-
-    mock_output = MagicMock()
-    mock_output.name = "response"
-    mock_output.data = "some text output"
-
-    with patch(
-        "backend.data.execution.AgentNodeExecutionInputOutput.prisma"
-    ) as mock_prisma:
-        mock_prisma.return_value.find_many = AsyncMock(return_value=[mock_output])
-        result = await get_execution_outputs_by_node_exec_id("test-exec-id")
-
-    # The result must conform to CompletedBlockOutput = dict[str, list[Any]]
-    assert "response" in result
-    assert isinstance(
-        result["response"], list
-    ), f"Expected list, got {type(result['response']).__name__}: {result['response']!r}"
-
-    # Must also pass TypeAdapter validation (this is what the RPC layer does)
-    adapter = TypeAdapter(CompletedBlockOutput)
-    validated = adapter.validate_python(result)  # This is the line that fails in prod
-    assert validated == {"response": ["some text output"]}
-
-
-@pytest.mark.asyncio
-async def test_multiple_outputs_same_name_are_collected():
-    """Multiple outputs with the same name should all appear in the list."""
-    from backend.data.execution import get_execution_outputs_by_node_exec_id
-
-    mock_out1 = MagicMock()
-    mock_out1.name = "result"
-    mock_out1.data = "first"
-
-    mock_out2 = MagicMock()
-    mock_out2.name = "result"
-    mock_out2.data = "second"
-
-    with patch(
-        "backend.data.execution.AgentNodeExecutionInputOutput.prisma"
-    ) as mock_prisma:
-        mock_prisma.return_value.find_many = AsyncMock(
-            return_value=[mock_out1, mock_out2]
-        )
-        result = await get_execution_outputs_by_node_exec_id("test-exec-id")
-
-    assert isinstance(result["result"], list)
-    assert len(result["result"]) == 2
-
-
-@pytest.mark.asyncio
-async def test_empty_outputs_returns_empty_dict():
-    """No outputs → empty dict."""
-    from backend.data.execution import get_execution_outputs_by_node_exec_id
-
-    with patch(
-        "backend.data.execution.AgentNodeExecutionInputOutput.prisma"
-    ) as mock_prisma:
-        mock_prisma.return_value.find_many = AsyncMock(return_value=[])
-        result = await get_execution_outputs_by_node_exec_id("test-exec-id")
-
-    assert result == {}
-
-
-@pytest.mark.asyncio
-async def test_none_data_skipped():
-    """Outputs with data=None should be skipped."""
-    from backend.data.execution import get_execution_outputs_by_node_exec_id
-
-    mock_output = MagicMock()
-    mock_output.name = "response"
-    mock_output.data = None
-
-    with patch(
-        "backend.data.execution.AgentNodeExecutionInputOutput.prisma"
-    ) as mock_prisma:
-        mock_prisma.return_value.find_many = AsyncMock(return_value=[mock_output])
-        result = await get_execution_outputs_by_node_exec_id("test-exec-id")
-
-    assert result == {}

autogpt_platform/backend/backend/data/invited_user.py

@@ -0,0 +1,750 @@
+import asyncio
+import csv
+import io
+import logging
+import os
+import re
+import socket
+from dataclasses import dataclass
+from datetime import datetime, timezone
+from typing import Any, Literal, Optional
+from uuid import uuid4
+
+import prisma.enums
+import prisma.models
+import prisma.types
+from prisma.errors import UniqueViolationError
+from pydantic import BaseModel, EmailStr, TypeAdapter, ValidationError
+
+from backend.data.db import transaction
+from backend.data.model import User
+from backend.data.redis_client import get_redis_async
+from backend.data.tally import get_business_understanding_input_from_tally, mask_email
+from backend.data.understanding import (
+    BusinessUnderstandingInput,
+    merge_business_understanding_data,
+)
+from backend.data.user import get_user_by_email, get_user_by_id
+from backend.executor.cluster_lock import AsyncClusterLock
+from backend.util.exceptions import (
+    NotAuthorizedError,
+    NotFoundError,
+    PreconditionFailed,
+)
+from backend.util.json import SafeJson
+from backend.util.settings import Settings
+
+logger = logging.getLogger(__name__)
+_settings = Settings()
+
+_WORKER_ID = f"{socket.gethostname()}:{os.getpid()}"
+
+_tally_seed_tasks: dict[str, asyncio.Task] = {}
+_TALLY_STALE_SECONDS = 300
+_MAX_TALLY_ERROR_LENGTH = 200
+_email_adapter = TypeAdapter(EmailStr)
+
+MAX_BULK_INVITE_FILE_BYTES = 1024 * 1024
+MAX_BULK_INVITE_ROWS = 500
+
+
+class InvitedUserRecord(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_db(cls, invited_user: "prisma.models.InvitedUser") -> "InvitedUserRecord":
+        payload = (
+            invited_user.tallyUnderstanding
+            if isinstance(invited_user.tallyUnderstanding, dict)
+            else None
+        )
+        return cls(
+            id=invited_user.id,
+            email=invited_user.email,
+            status=invited_user.status,
+            auth_user_id=invited_user.authUserId,
+            name=invited_user.name,
+            tally_understanding=payload,
+            tally_status=invited_user.tallyStatus,
+            tally_computed_at=invited_user.tallyComputedAt,
+            tally_error=invited_user.tallyError,
+            created_at=invited_user.createdAt,
+            updated_at=invited_user.updatedAt,
+        )
+
+
+class BulkInvitedUserRowResult(BaseModel):
+    row_number: int
+    email: Optional[str] = None
+    name: Optional[str] = None
+    status: Literal["CREATED", "SKIPPED", "ERROR"]
+    message: str
+    invited_user: Optional[InvitedUserRecord] = None
+
+
+class BulkInvitedUsersResult(BaseModel):
+    created_count: int
+    skipped_count: int
+    error_count: int
+    results: list[BulkInvitedUserRowResult]
+
+
+@dataclass(frozen=True)
+class _ParsedInviteRow:
+    row_number: int
+    email: str
+    name: Optional[str]
+
+
+def normalize_email(email: str) -> str:
+    return email.strip().lower()
+
+
+def _normalize_name(name: Optional[str]) -> Optional[str]:
+    if name is None:
+        return None
+    normalized = name.strip()
+    return normalized or None
+
+
+def _default_profile_name(email: str, preferred_name: Optional[str]) -> str:
+    if preferred_name:
+        return preferred_name
+    local_part = email.split("@", 1)[0].strip()
+    return local_part or "user"
+
+
+def _sanitize_username_base(email: str) -> str:
+    local_part = email.split("@", 1)[0].lower()
+    sanitized = re.sub(r"[^a-z0-9-]", "", local_part)
+    sanitized = sanitized.strip("-")
+    return sanitized[:40] or "user"
+
+
+async def _generate_unique_profile_username(email: str, tx) -> str:
+    base = _sanitize_username_base(email)
+
+    for _ in range(2):
+        candidate = f"{base}-{uuid4().hex[:6]}"
+        existing = await prisma.models.Profile.prisma(tx).find_unique(
+            where={"username": candidate}
+        )
+        if existing is None:
+            return candidate
+
+    raise RuntimeError(f"Unable to generate unique username for {email}")
+
+
+async def _ensure_default_profile(
+    user_id: str,
+    email: str,
+    preferred_name: Optional[str],
+    tx,
+) -> None:
+    existing_profile = await prisma.models.Profile.prisma(tx).find_unique(
+        where={"userId": user_id}
+    )
+    if existing_profile is not None:
+        return
+
+    username = await _generate_unique_profile_username(email, tx)
+    await prisma.models.Profile.prisma(tx).create(
+        data=prisma.types.ProfileCreateInput(
+            userId=user_id,
+            name=_default_profile_name(email, preferred_name),
+            username=username,
+            description="I'm new here",
+            links=[],
+            avatarUrl="",
+        )
+    )
+
+
+async def _ensure_default_onboarding(user_id: str, tx) -> None:
+    await prisma.models.UserOnboarding.prisma(tx).upsert(
+        where={"userId": user_id},
+        data={
+            "create": prisma.types.UserOnboardingCreateInput(userId=user_id),
+            "update": {},
+        },
+    )
+
+
+async def _apply_tally_understanding(
+    user_id: str,
+    invited_user: "prisma.models.InvitedUser",
+    tx,
+) -> None:
+    if not isinstance(invited_user.tallyUnderstanding, dict):
+        return
+
+    try:
+        input_data = BusinessUnderstandingInput.model_validate(
+            invited_user.tallyUnderstanding
+        )
+    except Exception:
+        logger.warning(
+            "Malformed tallyUnderstanding for invited user %s; skipping",
+            invited_user.id,
+            exc_info=True,
+        )
+        return
+
+    payload = merge_business_understanding_data({}, input_data)
+    await prisma.models.CoPilotUnderstanding.prisma(tx).upsert(
+        where={"userId": user_id},
+        data={
+            "create": {"userId": user_id, "data": SafeJson(payload)},
+            "update": {"data": SafeJson(payload)},
+        },
+    )
+
+
+async def list_invited_users(
+    page: int = 1,
+    page_size: int = 50,
+) -> tuple[list[InvitedUserRecord], int]:
+    total = await prisma.models.InvitedUser.prisma().count()
+    invited_users = await prisma.models.InvitedUser.prisma().find_many(
+        order={"createdAt": "desc"},
+        skip=(page - 1) * page_size,
+        take=page_size,
+    )
+    return [InvitedUserRecord.from_db(iu) for iu in invited_users], total
+
+
+async def create_invited_user(
+    email: str, name: Optional[str] = None
+) -> InvitedUserRecord:
+    normalized_email = normalize_email(email)
+    normalized_name = _normalize_name(name)
+
+    existing_user = await prisma.models.User.prisma().find_unique(
+        where={"email": normalized_email}
+    )
+    if existing_user is not None:
+        raise PreconditionFailed("An active user with this email already exists")
+
+    existing_invited_user = await prisma.models.InvitedUser.prisma().find_unique(
+        where={"email": normalized_email}
+    )
+    if existing_invited_user is not None:
+        raise PreconditionFailed("An invited user with this email already exists")
+
+    try:
+        invited_user = await prisma.models.InvitedUser.prisma().create(
+            data={
+                "email": normalized_email,
+                "name": normalized_name,
+                "status": prisma.enums.InvitedUserStatus.INVITED,
+                "tallyStatus": prisma.enums.TallyComputationStatus.PENDING,
+            }
+        )
+    except UniqueViolationError:
+        raise PreconditionFailed("An invited user with this email already exists")
+    schedule_invited_user_tally_precompute(invited_user.id)
+    return InvitedUserRecord.from_db(invited_user)
+
+
+async def revoke_invited_user(invited_user_id: str) -> InvitedUserRecord:
+    invited_user = await prisma.models.InvitedUser.prisma().find_unique(
+        where={"id": invited_user_id}
+    )
+    if invited_user is None:
+        raise NotFoundError(f"Invited user {invited_user_id} not found")
+
+    if invited_user.status == prisma.enums.InvitedUserStatus.CLAIMED:
+        raise PreconditionFailed("Claimed invited users cannot be revoked")
+
+    if invited_user.status == prisma.enums.InvitedUserStatus.REVOKED:
+        return InvitedUserRecord.from_db(invited_user)
+
+    revoked_user = await prisma.models.InvitedUser.prisma().update(
+        where={"id": invited_user_id},
+        data={"status": prisma.enums.InvitedUserStatus.REVOKED},
+    )
+    if revoked_user is None:
+        raise NotFoundError(f"Invited user {invited_user_id} not found")
+    return InvitedUserRecord.from_db(revoked_user)
+
+
+async def retry_invited_user_tally(invited_user_id: str) -> InvitedUserRecord:
+    invited_user = await prisma.models.InvitedUser.prisma().find_unique(
+        where={"id": invited_user_id}
+    )
+    if invited_user is None:
+        raise NotFoundError(f"Invited user {invited_user_id} not found")
+
+    if invited_user.status == prisma.enums.InvitedUserStatus.REVOKED:
+        raise PreconditionFailed("Revoked invited users cannot retry Tally seeding")
+
+    refreshed_user = await prisma.models.InvitedUser.prisma().update(
+        where={"id": invited_user_id},
+        data={
+            "tallyUnderstanding": None,
+            "tallyStatus": prisma.enums.TallyComputationStatus.PENDING,
+            "tallyComputedAt": None,
+            "tallyError": None,
+        },
+    )
+    if refreshed_user is None:
+        raise NotFoundError(f"Invited user {invited_user_id} not found")
+    schedule_invited_user_tally_precompute(invited_user_id)
+    return InvitedUserRecord.from_db(refreshed_user)
+
+
+def _decode_bulk_invite_file(content: bytes) -> str:
+    if len(content) > MAX_BULK_INVITE_FILE_BYTES:
+        raise ValueError("Invite file exceeds the maximum size of 1 MB")
+
+    try:
+        return content.decode("utf-8-sig")
+    except UnicodeDecodeError as exc:
+        raise ValueError("Invite file must be UTF-8 encoded") from exc
+
+
+def _parse_bulk_invite_csv(text: str) -> list[_ParsedInviteRow]:
+    indexed_rows: list[tuple[int, list[str]]] = []
+
+    for row_number, row in enumerate(csv.reader(io.StringIO(text)), start=1):
+        normalized_row = [cell.strip() for cell in row]
+        if any(normalized_row):
+            indexed_rows.append((row_number, normalized_row))
+
+    if not indexed_rows:
+        return []
+
+    header = [cell.lower() for cell in indexed_rows[0][1]]
+    has_header = "email" in header
+    email_index = header.index("email") if has_header else 0
+    name_index: Optional[int] = (
+        header.index("name")
+        if has_header and "name" in header
+        else (1 if not has_header else None)
+    )
+    data_rows = indexed_rows[1:] if has_header else indexed_rows
+
+    parsed_rows: list[_ParsedInviteRow] = []
+    for row_number, row in data_rows:
+        if len(parsed_rows) >= MAX_BULK_INVITE_ROWS:
+            break
+        email = row[email_index].strip() if len(row) > email_index else ""
+        name = (
+            row[name_index].strip()
+            if name_index is not None and len(row) > name_index
+            else ""
+        )
+        parsed_rows.append(
+            _ParsedInviteRow(
+                row_number=row_number,
+                email=email,
+                name=name or None,
+            )
+        )
+
+    return parsed_rows
+
+
+def _parse_bulk_invite_text(text: str) -> list[_ParsedInviteRow]:
+    parsed_rows: list[_ParsedInviteRow] = []
+
+    for row_number, raw_line in enumerate(text.splitlines(), start=1):
+        if len(parsed_rows) >= MAX_BULK_INVITE_ROWS:
+            break
+        line = raw_line.strip()
+        if not line or line.startswith("#"):
+            continue
+
+        parsed_rows.append(
+            _ParsedInviteRow(
+                row_number=row_number,
+                email=line,
+                name=None,
+            )
+        )
+
+    return parsed_rows
+
+
+def _parse_bulk_invite_file(
+    filename: Optional[str],
+    content: bytes,
+) -> list[_ParsedInviteRow]:
+    text = _decode_bulk_invite_file(content)
+    file_name = filename.lower() if filename else ""
+    parsed_rows = (
+        _parse_bulk_invite_csv(text)
+        if file_name.endswith(".csv")
+        else _parse_bulk_invite_text(text)
+    )
+
+    if not parsed_rows:
+        raise ValueError("Invite file did not contain any emails")
+
+    return parsed_rows
+
+
+async def bulk_create_invited_users_from_file(
+    filename: Optional[str],
+    content: bytes,
+) -> BulkInvitedUsersResult:
+    parsed_rows = _parse_bulk_invite_file(filename, content)
+
+    created_count = 0
+    skipped_count = 0
+    error_count = 0
+    results: list[BulkInvitedUserRowResult] = []
+    seen_emails: set[str] = set()
+
+    for row in parsed_rows:
+        row_name = _normalize_name(row.name)
+
+        try:
+            validated_email = _email_adapter.validate_python(row.email)
+        except ValidationError:
+            error_count += 1
+            results.append(
+                BulkInvitedUserRowResult(
+                    row_number=row.row_number,
+                    email=row.email or None,
+                    name=row_name,
+                    status="ERROR",
+                    message="Invalid email address",
+                )
+            )
+            continue
+
+        normalized_email = normalize_email(str(validated_email))
+        if normalized_email in seen_emails:
+            skipped_count += 1
+            results.append(
+                BulkInvitedUserRowResult(
+                    row_number=row.row_number,
+                    email=normalized_email,
+                    name=row_name,
+                    status="SKIPPED",
+                    message="Duplicate email in upload file",
+                )
+            )
+            continue
+
+        seen_emails.add(normalized_email)
+
+        try:
+            invited_user = await create_invited_user(normalized_email, row_name)
+        except PreconditionFailed as exc:
+            skipped_count += 1
+            results.append(
+                BulkInvitedUserRowResult(
+                    row_number=row.row_number,
+                    email=normalized_email,
+                    name=row_name,
+                    status="SKIPPED",
+                    message=str(exc),
+                )
+            )
+        except Exception:
+            masked = mask_email(normalized_email)
+            logger.exception(
+                "Failed to create bulk invite for row %s (%s)",
+                row.row_number,
+                masked,
+            )
+            error_count += 1
+            results.append(
+                BulkInvitedUserRowResult(
+                    row_number=row.row_number,
+                    email=normalized_email,
+                    name=row_name,
+                    status="ERROR",
+                    message="Unexpected error creating invite",
+                )
+            )
+        else:
+            created_count += 1
+            results.append(
+                BulkInvitedUserRowResult(
+                    row_number=row.row_number,
+                    email=normalized_email,
+                    name=row_name,
+                    status="CREATED",
+                    message="Invite created",
+                    invited_user=invited_user,
+                )
+            )
+
+    return BulkInvitedUsersResult(
+        created_count=created_count,
+        skipped_count=skipped_count,
+        error_count=error_count,
+        results=results,
+    )
+
+
+async def _compute_invited_user_tally_seed(invited_user_id: str) -> None:
+    invited_user = await prisma.models.InvitedUser.prisma().find_unique(
+        where={"id": invited_user_id}
+    )
+    if invited_user is None:
+        return
+
+    if invited_user.status == prisma.enums.InvitedUserStatus.REVOKED:
+        return
+
+    try:
+        r = await get_redis_async()
+    except Exception:
+        r = None
+
+    lock: AsyncClusterLock | None = None
+
+    if r is not None:
+        lock = AsyncClusterLock(
+            redis=r,
+            key=f"tally_seed:{invited_user_id}",
+            owner_id=_WORKER_ID,
+            timeout=_TALLY_STALE_SECONDS,
+        )
+        current_owner = await lock.try_acquire()
+
+        if current_owner is None:
+            logger.warn("Redis unvailable for tally lock - skipping tally enrichement")
+            return
+        elif current_owner != _WORKER_ID:
+            logger.debug(
+                "Tally seed for %s already locked by %s, skipping",
+                invited_user_id,
+                current_owner,
+            )
+            return
+    if (
+        invited_user.tallyStatus == prisma.enums.TallyComputationStatus.RUNNING
+        and invited_user.updatedAt is not None
+    ):
+        age = (datetime.now(timezone.utc) - invited_user.updatedAt).total_seconds()
+        if age < _TALLY_STALE_SECONDS:
+            logger.debug(
+                "Tally task for %s still RUNNING (age=%ds), skipping",
+                invited_user_id,
+                int(age),
+            )
+            return
+        logger.info(
+            "Tally task for %s is stale (age=%ds), re-running",
+            invited_user_id,
+            int(age),
+        )
+
+    await prisma.models.InvitedUser.prisma().update(
+        where={"id": invited_user_id},
+        data={
+            "tallyStatus": prisma.enums.TallyComputationStatus.RUNNING,
+            "tallyError": None,
+        },
+    )
+
+    try:
+        input_data = await get_business_understanding_input_from_tally(
+            invited_user.email,
+            require_api_key=True,
+        )
+        payload = (
+            SafeJson(input_data.model_dump(exclude_none=True))
+            if input_data is not None
+            else None
+        )
+        await prisma.models.InvitedUser.prisma().update(
+            where={"id": invited_user_id},
+            data={
+                "tallyUnderstanding": payload,
+                "tallyStatus": prisma.enums.TallyComputationStatus.READY,
+                "tallyComputedAt": datetime.now(timezone.utc),
+                "tallyError": None,
+            },
+        )
+    except Exception as exc:
+        logger.exception(
+            "Failed to compute Tally understanding for invited user %s",
+            invited_user_id,
+        )
+        sanitized_error = re.sub(
+            r"https?://\S+", "<url>", f"{type(exc).__name__}: {exc}"
+        )[:_MAX_TALLY_ERROR_LENGTH]
+        await prisma.models.InvitedUser.prisma().update(
+            where={"id": invited_user_id},
+            data={
+                "tallyStatus": prisma.enums.TallyComputationStatus.FAILED,
+                "tallyError": sanitized_error,
+            },
+        )
+
+
+def schedule_invited_user_tally_precompute(invited_user_id: str) -> None:
+    existing = _tally_seed_tasks.get(invited_user_id)
+    if existing is not None and not existing.done():
+        logger.debug("Tally task already running for %s, skipping", invited_user_id)
+        return
+
+    task = asyncio.create_task(_compute_invited_user_tally_seed(invited_user_id))
+    _tally_seed_tasks[invited_user_id] = task
+
+    def _on_done(t: asyncio.Task, _id: str = invited_user_id) -> None:
+        if _tally_seed_tasks.get(_id) is t:
+            del _tally_seed_tasks[_id]
+
+    task.add_done_callback(_on_done)
+
+
+async def _open_signup_create_user(
+    auth_user_id: str,
+    normalized_email: str,
+    metadata_name: Optional[str],
+) -> User:
+    """Create a user without requiring an invite (open signup mode)."""
+    preferred_name = _normalize_name(metadata_name)
+    try:
+        async with transaction() as tx:
+            user = await prisma.models.User.prisma(tx).create(
+                data=prisma.types.UserCreateInput(
+                    id=auth_user_id,
+                    email=normalized_email,
+                    name=preferred_name,
+                )
+            )
+            await _ensure_default_profile(
+                auth_user_id, normalized_email, preferred_name, tx
+            )
+            await _ensure_default_onboarding(auth_user_id, tx)
+    except UniqueViolationError:
+        existing = await prisma.models.User.prisma().find_unique(
+            where={"id": auth_user_id}
+        )
+        if existing is not None:
+            return User.from_db(existing)
+        raise
+
+    return User.from_db(user)
+
+
+# TODO: We need to change this functions logic before going live
+async def get_or_activate_user(user_data: dict) -> User:
+    auth_user_id = user_data.get("sub")
+    if not auth_user_id:
+        raise NotAuthorizedError("User ID not found in token")
+
+    auth_email = user_data.get("email")
+    if not auth_email:
+        raise NotAuthorizedError("Email not found in token")
+
+    normalized_email = normalize_email(auth_email)
+    user_metadata = user_data.get("user_metadata")
+    metadata_name = (
+        user_metadata.get("name") if isinstance(user_metadata, dict) else None
+    )
+
+    existing_user = None
+    try:
+        existing_user = await get_user_by_id(auth_user_id)
+    except ValueError:
+        existing_user = None
+    except Exception:
+        logger.exception("Error on get user by id during tally enrichment process")
+        raise
+
+    if existing_user is not None:
+        return existing_user
+
+    if not _settings.config.enable_invite_gate or normalized_email.endswith("@agpt.co"):
+        return await _open_signup_create_user(
+            auth_user_id, normalized_email, metadata_name
+        )
+
+    invited_user = await prisma.models.InvitedUser.prisma().find_unique(
+        where={"email": normalized_email}
+    )
+    if invited_user is None:
+        raise NotAuthorizedError("Your email is not allowed to access the platform")
+
+    if invited_user.status != prisma.enums.InvitedUserStatus.INVITED:
+        raise NotAuthorizedError("Your invitation is no longer active")
+
+    try:
+        async with transaction() as tx:
+            current_user = await prisma.models.User.prisma(tx).find_unique(
+                where={"id": auth_user_id}
+            )
+            if current_user is not None:
+                return User.from_db(current_user)
+
+            current_invited_user = await prisma.models.InvitedUser.prisma(
+                tx
+            ).find_unique(where={"email": normalized_email})
+            if current_invited_user is None:
+                raise NotAuthorizedError(
+                    "Your email is not allowed to access the platform"
+                )
+
+            if current_invited_user.status != prisma.enums.InvitedUserStatus.INVITED:
+                raise NotAuthorizedError("Your invitation is no longer active")
+
+            if current_invited_user.authUserId not in (None, auth_user_id):
+                raise NotAuthorizedError("Your invitation has already been claimed")
+
+            preferred_name = current_invited_user.name or _normalize_name(metadata_name)
+            await prisma.models.User.prisma(tx).create(
+                data=prisma.types.UserCreateInput(
+                    id=auth_user_id,
+                    email=normalized_email,
+                    name=preferred_name,
+                )
+            )
+
+            await prisma.models.InvitedUser.prisma(tx).update(
+                where={"id": current_invited_user.id},
+                data={
+                    "status": prisma.enums.InvitedUserStatus.CLAIMED,
+                    "authUserId": auth_user_id,
+                },
+            )
+
+            await _ensure_default_profile(
+                auth_user_id,
+                normalized_email,
+                preferred_name,
+                tx,
+            )
+            await _ensure_default_onboarding(auth_user_id, tx)
+            await _apply_tally_understanding(auth_user_id, current_invited_user, tx)
+    except UniqueViolationError:
+        logger.info("Concurrent activation for user %s; re-fetching", auth_user_id)
+        already_created = await prisma.models.User.prisma().find_unique(
+            where={"id": auth_user_id}
+        )
+        if already_created is not None:
+            return User.from_db(already_created)
+        raise RuntimeError(
+            f"UniqueViolationError during activation but user {auth_user_id} not found"
+        )
+
+    get_user_by_id.cache_delete(auth_user_id)
+    get_user_by_email.cache_delete(normalized_email)
+
+    activated_user = await prisma.models.User.prisma().find_unique(
+        where={"id": auth_user_id}
+    )
+    if activated_user is None:
+        raise RuntimeError(
+            f"Activated user {auth_user_id} was not found after creation"
+        )
+
+    return User.from_db(activated_user)

autogpt_platform/backend/backend/data/invited_user_test.py

@@ -0,0 +1,335 @@
+from contextlib import asynccontextmanager
+from datetime import datetime, timezone
+from types import SimpleNamespace
+from typing import cast
+from unittest.mock import AsyncMock, Mock
+
+import prisma.enums
+import prisma.models
+import pytest
+import pytest_mock
+
+from backend.util.exceptions import NotAuthorizedError, PreconditionFailed
+
+from .invited_user import (
+    InvitedUserRecord,
+    bulk_create_invited_users_from_file,
+    create_invited_user,
+    get_or_activate_user,
+    retry_invited_user_tally,
+)
+
+
+def _invited_user_db_record(
+    *,
+    status: prisma.enums.InvitedUserStatus = prisma.enums.InvitedUserStatus.INVITED,
+    tally_understanding: dict | None = None,
+):
+    now = datetime.now(timezone.utc)
+    return SimpleNamespace(
+        id="invite-1",
+        email="invited@example.com",
+        status=status,
+        authUserId=None,
+        name="Invited User",
+        tallyUnderstanding=tally_understanding,
+        tallyStatus=prisma.enums.TallyComputationStatus.PENDING,
+        tallyComputedAt=None,
+        tallyError=None,
+        createdAt=now,
+        updatedAt=now,
+    )
+
+
+def _invited_user_record(
+    *,
+    status: prisma.enums.InvitedUserStatus = prisma.enums.InvitedUserStatus.INVITED,
+    tally_understanding: dict | None = None,
+):
+    return InvitedUserRecord.from_db(
+        cast(
+            prisma.models.InvitedUser,
+            _invited_user_db_record(
+                status=status,
+                tally_understanding=tally_understanding,
+            ),
+        )
+    )
+
+
+def _user_db_record():
+    now = datetime.now(timezone.utc)
+    return SimpleNamespace(
+        id="auth-user-1",
+        email="invited@example.com",
+        emailVerified=True,
+        name="Invited User",
+        createdAt=now,
+        updatedAt=now,
+        metadata={},
+        integrations="",
+        stripeCustomerId=None,
+        topUpConfig=None,
+        maxEmailsPerDay=3,
+        notifyOnAgentRun=True,
+        notifyOnZeroBalance=True,
+        notifyOnLowBalance=True,
+        notifyOnBlockExecutionFailed=True,
+        notifyOnContinuousAgentError=True,
+        notifyOnDailySummary=True,
+        notifyOnWeeklySummary=True,
+        notifyOnMonthlySummary=True,
+        notifyOnAgentApproved=True,
+        notifyOnAgentRejected=True,
+        timezone="not-set",
+    )
+
+
+@pytest.mark.asyncio
+async def test_create_invited_user_rejects_existing_active_user(
+    mocker: pytest_mock.MockerFixture,
+) -> None:
+    user_repo = Mock()
+    user_repo.find_unique = AsyncMock(return_value=_user_db_record())
+    invited_user_repo = Mock()
+    invited_user_repo.find_unique = AsyncMock()
+
+    mocker.patch(
+        "backend.data.invited_user.prisma.models.User.prisma", return_value=user_repo
+    )
+    mocker.patch(
+        "backend.data.invited_user.prisma.models.InvitedUser.prisma",
+        return_value=invited_user_repo,
+    )
+
+    with pytest.raises(PreconditionFailed):
+        await create_invited_user("Invited@example.com")
+
+
+@pytest.mark.asyncio
+async def test_create_invited_user_schedules_tally_seed(
+    mocker: pytest_mock.MockerFixture,
+) -> None:
+    user_repo = Mock()
+    user_repo.find_unique = AsyncMock(return_value=None)
+    invited_user_repo = Mock()
+    invited_user_repo.find_unique = AsyncMock(return_value=None)
+    invited_user_repo.create = AsyncMock(return_value=_invited_user_db_record())
+    schedule = mocker.patch(
+        "backend.data.invited_user.schedule_invited_user_tally_precompute"
+    )
+
+    mocker.patch(
+        "backend.data.invited_user.prisma.models.User.prisma", return_value=user_repo
+    )
+    mocker.patch(
+        "backend.data.invited_user.prisma.models.InvitedUser.prisma",
+        return_value=invited_user_repo,
+    )
+
+    invited_user = await create_invited_user("Invited@example.com", "Invited User")
+
+    assert invited_user.email == "invited@example.com"
+    invited_user_repo.create.assert_awaited_once()
+    schedule.assert_called_once_with("invite-1")
+
+
+@pytest.mark.asyncio
+async def test_retry_invited_user_tally_resets_state_and_schedules(
+    mocker: pytest_mock.MockerFixture,
+) -> None:
+    invited_user_repo = Mock()
+    invited_user_repo.find_unique = AsyncMock(return_value=_invited_user_db_record())
+    invited_user_repo.update = AsyncMock(return_value=_invited_user_db_record())
+    schedule = mocker.patch(
+        "backend.data.invited_user.schedule_invited_user_tally_precompute"
+    )
+
+    mocker.patch(
+        "backend.data.invited_user.prisma.models.InvitedUser.prisma",
+        return_value=invited_user_repo,
+    )
+
+    invited_user = await retry_invited_user_tally("invite-1")
+
+    assert invited_user.id == "invite-1"
+    invited_user_repo.update.assert_awaited_once()
+    schedule.assert_called_once_with("invite-1")
+
+
+@pytest.mark.asyncio
+async def test_get_or_activate_user_requires_invite(
+    mocker: pytest_mock.MockerFixture,
+) -> None:
+    invited_user_repo = Mock()
+    invited_user_repo.find_unique = AsyncMock(return_value=None)
+
+    mock_get_user_by_id = AsyncMock(side_effect=ValueError("User not found"))
+    mock_get_user_by_id.cache_delete = Mock()
+    mocker.patch(
+        "backend.data.invited_user.get_user_by_id",
+        mock_get_user_by_id,
+    )
+    mocker.patch(
+        "backend.data.invited_user._settings.config.enable_invite_gate",
+        True,
+    )
+    mocker.patch(
+        "backend.data.invited_user.prisma.models.InvitedUser.prisma",
+        return_value=invited_user_repo,
+    )
+
+    with pytest.raises(NotAuthorizedError):
+        await get_or_activate_user(
+            {"sub": "auth-user-1", "email": "invited@example.com"}
+        )
+
+
+@pytest.mark.asyncio
+async def test_get_or_activate_user_creates_user_from_invite(
+    mocker: pytest_mock.MockerFixture,
+) -> None:
+    tx = object()
+    invited_user = _invited_user_db_record(
+        tally_understanding={"user_name": "Invited User", "industry": "Automation"}
+    )
+    created_user = _user_db_record()
+
+    outside_user_repo = Mock()
+    # Only called once at post-transaction verification (line 741);
+    # get_user_by_id (line 657) uses prisma.user.find_unique, not this mock.
+    outside_user_repo.find_unique = AsyncMock(return_value=created_user)
+
+    inside_user_repo = Mock()
+    inside_user_repo.find_unique = AsyncMock(return_value=None)
+    inside_user_repo.create = AsyncMock(return_value=created_user)
+
+    outside_invited_repo = Mock()
+    outside_invited_repo.find_unique = AsyncMock(return_value=invited_user)
+
+    inside_invited_repo = Mock()
+    inside_invited_repo.find_unique = AsyncMock(return_value=invited_user)
+    inside_invited_repo.update = AsyncMock(return_value=invited_user)
+
+    def user_prisma(client=None):
+        return inside_user_repo if client is tx else outside_user_repo
+
+    def invited_user_prisma(client=None):
+        return inside_invited_repo if client is tx else outside_invited_repo
+
+    @asynccontextmanager
+    async def fake_transaction():
+        yield tx
+
+    # Mock get_user_by_id since it uses prisma.user.find_unique (global client),
+    # not prisma.models.User.prisma().find_unique which we mock above.
+    mock_get_user_by_id = AsyncMock(side_effect=ValueError("User not found"))
+    mock_get_user_by_id.cache_delete = Mock()
+    mocker.patch(
+        "backend.data.invited_user.get_user_by_id",
+        mock_get_user_by_id,
+    )
+    mock_get_user_by_email = AsyncMock()
+    mock_get_user_by_email.cache_delete = Mock()
+    mocker.patch(
+        "backend.data.invited_user.get_user_by_email",
+        mock_get_user_by_email,
+    )
+    ensure_profile = mocker.patch(
+        "backend.data.invited_user._ensure_default_profile",
+        AsyncMock(),
+    )
+    ensure_onboarding = mocker.patch(
+        "backend.data.invited_user._ensure_default_onboarding",
+        AsyncMock(),
+    )
+    apply_tally = mocker.patch(
+        "backend.data.invited_user._apply_tally_understanding",
+        AsyncMock(),
+    )
+    mocker.patch("backend.data.invited_user.transaction", fake_transaction)
+    mocker.patch(
+        "backend.data.invited_user.prisma.models.User.prisma", side_effect=user_prisma
+    )
+    mocker.patch(
+        "backend.data.invited_user.prisma.models.InvitedUser.prisma",
+        side_effect=invited_user_prisma,
+    )
+
+    user = await get_or_activate_user(
+        {
+            "sub": "auth-user-1",
+            "email": "Invited@example.com",
+            "user_metadata": {"name": "Invited User"},
+        }
+    )
+
+    assert user.id == "auth-user-1"
+    inside_user_repo.create.assert_awaited_once()
+    inside_invited_repo.update.assert_awaited_once()
+    ensure_profile.assert_awaited_once()
+    ensure_onboarding.assert_awaited_once_with("auth-user-1", tx)
+    apply_tally.assert_awaited_once_with("auth-user-1", invited_user, tx)
+
+
+@pytest.mark.asyncio
+async def test_bulk_create_invited_users_from_text_file(
+    mocker: pytest_mock.MockerFixture,
+) -> None:
+    create_invited = mocker.patch(
+        "backend.data.invited_user.create_invited_user",
+        AsyncMock(
+            side_effect=[
+                _invited_user_record(),
+                _invited_user_record(),
+            ]
+        ),
+    )
+
+    result = await bulk_create_invited_users_from_file(
+        "invites.txt",
+        b"Invited@example.com\nsecond@example.com\n",
+    )
+
+    assert result.created_count == 2
+    assert result.skipped_count == 0
+    assert result.error_count == 0
+    assert [row.status for row in result.results] == ["CREATED", "CREATED"]
+    assert create_invited.await_count == 2
+
+
+@pytest.mark.asyncio
+async def test_bulk_create_invited_users_handles_csv_duplicates_and_invalid_rows(
+    mocker: pytest_mock.MockerFixture,
+) -> None:
+    create_invited = mocker.patch(
+        "backend.data.invited_user.create_invited_user",
+        AsyncMock(
+            side_effect=[
+                _invited_user_record(),
+                PreconditionFailed("An invited user with this email already exists"),
+            ]
+        ),
+    )
+
+    result = await bulk_create_invited_users_from_file(
+        "invites.csv",
+        (
+            "email,name\n"
+            "valid@example.com,Valid User\n"
+            "not-an-email,Bad Row\n"
+            "valid@example.com,Duplicate In File\n"
+            "existing@example.com,Existing User\n"
+        ).encode("utf-8"),
+    )
+
+    assert result.created_count == 1
+    assert result.skipped_count == 2
+    assert result.error_count == 1
+    assert [row.status for row in result.results] == [
+        "CREATED",
+        "ERROR",
+        "SKIPPED",
+        "SKIPPED",
+    ]
+    assert create_invited.await_count == 2

autogpt_platform/backend/backend/data/tally.py

@@ -41,7 +41,7 @@ _MAX_PAGES = 100
 _LLM_TIMEOUT = 30
 
 
-def _mask_email(email: str) -> str:
+def mask_email(email: str) -> str:
     """Mask an email for safe logging: 'alice@example.com' -> 'a***e@example.com'."""
     try:
         local, domain = email.rsplit("@", 1)
@@ -196,8 +196,7 @@ async def _refresh_cache(form_id: str) -> tuple[dict, list]:
 
     Returns (email_index, questions).
     """
-    settings = Settings()
-    client = _make_tally_client(settings.secrets.tally_api_key)
+    client = _make_tally_client(_settings.secrets.tally_api_key)
 
     redis = await get_redis_async()
     last_fetch_key = _LAST_FETCH_KEY.format(form_id=form_id)
@@ -332,6 +331,9 @@ Fields:
 - current_software (list of strings): software/tools currently used
 - existing_automation (list of strings): existing automations
 - additional_notes (string): any additional context
+- suggested_prompts (list of 5 strings): short action prompts (each under 20 words) that would help \
+this person get started with automating their work. Should be specific to their industry, role, and \
+pain points; actionable and conversational in tone; focused on automation opportunities.
 
 Form data:
 """
@@ -339,21 +341,21 @@ Form data:
 _EXTRACTION_SUFFIX = "\n\nReturn ONLY valid JSON."
 
 
-async def extract_business_understanding(
+async def extract_business_understanding_from_tally(
     formatted_text: str,
 ) -> BusinessUnderstandingInput:
-    """Use an LLM to extract structured business understanding from form text.
+    """
+    Use an LLM to extract structured business understanding from form text.
 
     Raises on timeout or unparseable response so the caller can handle it.
     """
-    settings = Settings()
-    api_key = settings.secrets.open_router_api_key
+    api_key = _settings.secrets.open_router_api_key
     client = AsyncOpenAI(api_key=api_key, base_url=OPENROUTER_BASE_URL)
 
     try:
         response = await asyncio.wait_for(
             client.chat.completions.create(
-                model="openai/gpt-4o-mini",
+                model=_settings.config.tally_extraction_llm_model,
                 messages=[
                     {
                         "role": "user",
@@ -378,9 +380,57 @@ async def extract_business_understanding(
 
     # Filter out null values before constructing
     cleaned = {k: v for k, v in data.items() if v is not None}
+
+    # Validate suggested_prompts: filter >20 words, keep top 3
+    raw_prompts = cleaned.get("suggested_prompts", [])
+    if isinstance(raw_prompts, list):
+        valid = [
+            p.strip()
+            for p in raw_prompts
+            if isinstance(p, str) and len(p.strip().split()) <= 20
+        ]
+        # This will keep up to 3 suggestions
+        short_prompts = valid[:3] if valid else None
+        if short_prompts:
+            cleaned["suggested_prompts"] = short_prompts
+        else:
+            # We dont want to add a None value suggested_prompts field
+            cleaned.pop("suggested_prompts", None)
+    else:
+        # suggested_prompts must be a list - removing it as its not here
+        cleaned.pop("suggested_prompts", None)
+
     return BusinessUnderstandingInput(**cleaned)
 
 
+async def get_business_understanding_input_from_tally(
+    email: str,
+    *,
+    require_api_key: bool = False,
+) -> Optional[BusinessUnderstandingInput]:
+    if not _settings.secrets.tally_api_key:
+        if require_api_key:
+            raise RuntimeError("Tally API key is not configured")
+        logger.debug("Tally: no API key configured, skipping")
+        return None
+
+    masked = mask_email(email)
+    result = await find_submission_by_email(TALLY_FORM_ID, email)
+    if result is None:
+        logger.debug(f"Tally: no submission found for {masked}")
+        return None
+
+    submission, questions = result
+    logger.info(f"Tally: found submission for {masked}, extracting understanding")
+
+    formatted = format_submission_for_llm(submission, questions)
+    if not formatted.strip():
+        logger.warning("Tally: formatted submission was empty, skipping")
+        return None
+
+    return await extract_business_understanding_from_tally(formatted)
+
+
 async def populate_understanding_from_tally(user_id: str, email: str) -> None:
     """Main orchestrator: check Tally for a matching submission and populate understanding.
 
@@ -395,32 +445,9 @@ async def populate_understanding_from_tally(user_id: str, email: str) -> None:
             )
             return
 
-        # Check required config is present
-        settings = Settings()
-        if not settings.secrets.tally_api_key or not settings.secrets.tally_form_id:
-            logger.debug("Tally: Tally config incomplete, skipping")
+        understanding_input = await get_business_understanding_input_from_tally(email)
+        if understanding_input is None:
             return
-        if not settings.secrets.open_router_api_key:
-            logger.debug("Tally: no OpenRouter API key configured, skipping")
-            return
-
-        # Look up submission by email
-        masked = _mask_email(email)
-        result = await find_submission_by_email(settings.secrets.tally_form_id, email)
-        if result is None:
-            logger.debug(f"Tally: no submission found for {masked}")
-            return
-
-        submission, questions = result
-        logger.info(f"Tally: found submission for {masked}, extracting understanding")
-
-        # Format and extract
-        formatted = format_submission_for_llm(submission, questions)
-        if not formatted.strip():
-            logger.warning("Tally: formatted submission was empty, skipping")
-            return
-
-        understanding_input = await extract_business_understanding(formatted)
 
         # Upsert into database
         await upsert_business_understanding(user_id, understanding_input)

autogpt_platform/backend/backend/data/tally_test.py

@@ -12,11 +12,11 @@ from backend.data.tally import (
     _build_email_index,
     _format_answer,
     _make_tally_client,
-    _mask_email,
     _refresh_cache,
-    extract_business_understanding,
+    extract_business_understanding_from_tally,
     find_submission_by_email,
     format_submission_for_llm,
+    mask_email,
     populate_understanding_from_tally,
 )
 
@@ -248,7 +248,7 @@ async def test_populate_understanding_skips_no_api_key():
             new_callable=AsyncMock,
             return_value=None,
         ),
-        patch("backend.data.tally.Settings", return_value=mock_settings),
+        patch("backend.data.tally._settings", mock_settings),
         patch(
             "backend.data.tally.find_submission_by_email",
             new_callable=AsyncMock,
@@ -284,6 +284,7 @@ async def test_populate_understanding_full_flow():
         ],
     }
     mock_input = MagicMock()
+    mock_input.suggested_prompts = ["Prompt 1", "Prompt 2", "Prompt 3"]
 
     with (
         patch(
@@ -291,14 +292,14 @@ async def test_populate_understanding_full_flow():
             new_callable=AsyncMock,
             return_value=None,
         ),
-        patch("backend.data.tally.Settings", return_value=mock_settings),
+        patch("backend.data.tally._settings", mock_settings),
         patch(
             "backend.data.tally.find_submission_by_email",
             new_callable=AsyncMock,
             return_value=(submission, SAMPLE_QUESTIONS),
         ),
         patch(
-            "backend.data.tally.extract_business_understanding",
+            "backend.data.tally.extract_business_understanding_from_tally",
             new_callable=AsyncMock,
             return_value=mock_input,
         ) as mock_extract,
@@ -331,14 +332,14 @@ async def test_populate_understanding_handles_llm_timeout():
             new_callable=AsyncMock,
             return_value=None,
         ),
-        patch("backend.data.tally.Settings", return_value=mock_settings),
+        patch("backend.data.tally._settings", mock_settings),
         patch(
             "backend.data.tally.find_submission_by_email",
             new_callable=AsyncMock,
             return_value=(submission, SAMPLE_QUESTIONS),
         ),
         patch(
-            "backend.data.tally.extract_business_understanding",
+            "backend.data.tally.extract_business_understanding_from_tally",
             new_callable=AsyncMock,
             side_effect=asyncio.TimeoutError(),
         ),
@@ -356,13 +357,13 @@ async def test_populate_understanding_handles_llm_timeout():
 
 
 def test_mask_email():
-    assert _mask_email("alice@example.com") == "a***e@example.com"
-    assert _mask_email("ab@example.com") == "a***@example.com"
-    assert _mask_email("a@example.com") == "a***@example.com"
+    assert mask_email("alice@example.com") == "a***e@example.com"
+    assert mask_email("ab@example.com") == "a***@example.com"
+    assert mask_email("a@example.com") == "a***@example.com"
 
 
 def test_mask_email_invalid():
-    assert _mask_email("no-at-sign") == "***"
+    assert mask_email("no-at-sign") == "***"
 
 
 # ── Prompt construction (curly-brace safety) ─────────────────────────────────
@@ -393,11 +394,11 @@ def test_extraction_prompt_no_format_placeholders():
     assert single_braces == [], f"Found format placeholders: {single_braces}"
 
 
-# ── extract_business_understanding ────────────────────────────────────────────
+# ── extract_business_understanding_from_tally ────────────────────────────────────────────
 
 
 @pytest.mark.asyncio
-async def test_extract_business_understanding_success():
+async def test_extract_business_understanding_from_tally_success():
     """Happy path: LLM returns valid JSON that maps to BusinessUnderstandingInput."""
     mock_choice = MagicMock()
     mock_choice.message.content = json.dumps(
@@ -406,6 +407,13 @@ async def test_extract_business_understanding_success():
             "business_name": "Acme Corp",
             "industry": "Technology",
             "pain_points": ["manual reporting"],
+            "suggested_prompts": [
+                "Automate weekly reports",
+                "Set up invoice processing",
+                "Create a customer onboarding flow",
+                "Track project deadlines automatically",
+                "Send follow-up emails after meetings",
+            ],
         }
     )
     mock_response = MagicMock()
@@ -415,16 +423,56 @@ async def test_extract_business_understanding_success():
     mock_client.chat.completions.create.return_value = mock_response
 
     with patch("backend.data.tally.AsyncOpenAI", return_value=mock_client):
-        result = await extract_business_understanding("Q: Name?\nA: Alice")
+        result = await extract_business_understanding_from_tally("Q: Name?\nA: Alice")
 
     assert result.user_name == "Alice"
     assert result.business_name == "Acme Corp"
     assert result.industry == "Technology"
     assert result.pain_points == ["manual reporting"]
+    # suggested_prompts validated and sliced to top 3
+    assert result.suggested_prompts == [
+        "Automate weekly reports",
+        "Set up invoice processing",
+        "Create a customer onboarding flow",
+    ]
 
 
 @pytest.mark.asyncio
-async def test_extract_business_understanding_filters_nulls():
+async def test_extract_business_understanding_from_tally_filters_long_prompts():
+    """Prompts exceeding 20 words are excluded and only top 3 are kept."""
+    long_prompt = " ".join(["word"] * 21)
+    mock_choice = MagicMock()
+    mock_choice.message.content = json.dumps(
+        {
+            "user_name": "Alice",
+            "suggested_prompts": [
+                long_prompt,
+                "Short prompt one",
+                long_prompt,
+                "Short prompt two",
+                "Short prompt three",
+                "Short prompt four",
+            ],
+        }
+    )
+    mock_response = MagicMock()
+    mock_response.choices = [mock_choice]
+
+    mock_client = AsyncMock()
+    mock_client.chat.completions.create.return_value = mock_response
+
+    with patch("backend.data.tally.AsyncOpenAI", return_value=mock_client):
+        result = await extract_business_understanding_from_tally("Q: Name?\nA: Alice")
+
+    assert result.suggested_prompts == [
+        "Short prompt one",
+        "Short prompt two",
+        "Short prompt three",
+    ]
+
+
+@pytest.mark.asyncio
+async def test_extract_business_understanding_from_tally_filters_nulls():
     """Null values from LLM should be excluded from the result."""
     mock_choice = MagicMock()
     mock_choice.message.content = json.dumps(
@@ -437,7 +485,7 @@ async def test_extract_business_understanding_filters_nulls():
     mock_client.chat.completions.create.return_value = mock_response
 
     with patch("backend.data.tally.AsyncOpenAI", return_value=mock_client):
-        result = await extract_business_understanding("Q: Name?\nA: Alice")
+        result = await extract_business_understanding_from_tally("Q: Name?\nA: Alice")
 
     assert result.user_name == "Alice"
     assert result.business_name is None
@@ -445,7 +493,7 @@ async def test_extract_business_understanding_filters_nulls():
 
 
 @pytest.mark.asyncio
-async def test_extract_business_understanding_invalid_json():
+async def test_extract_business_understanding_from_tally_invalid_json():
     """Invalid JSON from LLM should raise JSONDecodeError."""
     mock_choice = MagicMock()
     mock_choice.message.content = "not valid json {"
@@ -459,11 +507,11 @@ async def test_extract_business_understanding_invalid_json():
         patch("backend.data.tally.AsyncOpenAI", return_value=mock_client),
         pytest.raises(json.JSONDecodeError),
     ):
-        await extract_business_understanding("Q: Name?\nA: Alice")
+        await extract_business_understanding_from_tally("Q: Name?\nA: Alice")
 
 
 @pytest.mark.asyncio
-async def test_extract_business_understanding_timeout():
+async def test_extract_business_understanding_from_tally_timeout():
     """LLM timeout should propagate as asyncio.TimeoutError."""
     mock_client = AsyncMock()
     mock_client.chat.completions.create.side_effect = asyncio.TimeoutError()
@@ -473,7 +521,7 @@ async def test_extract_business_understanding_timeout():
         patch("backend.data.tally._LLM_TIMEOUT", 0.001),
         pytest.raises(asyncio.TimeoutError),
     ):
-        await extract_business_understanding("Q: Name?\nA: Alice")
+        await extract_business_understanding_from_tally("Q: Name?\nA: Alice")
 
 
 # ── _refresh_cache ───────────────────────────────────────────────────────────
@@ -492,7 +540,7 @@ async def test_refresh_cache_full_fetch():
     submissions = SAMPLE_SUBMISSIONS
 
     with (
-        patch("backend.data.tally.Settings", return_value=mock_settings),
+        patch("backend.data.tally._settings", mock_settings),
         patch(
             "backend.data.tally.get_redis_async",
             new_callable=AsyncMock,
@@ -540,7 +588,7 @@ async def test_refresh_cache_incremental_fetch():
     new_submissions = [SAMPLE_SUBMISSIONS[0]]  # Just Alice
 
     with (
-        patch("backend.data.tally.Settings", return_value=mock_settings),
+        patch("backend.data.tally._settings", mock_settings),
         patch(
             "backend.data.tally.get_redis_async",
             new_callable=AsyncMock,

autogpt_platform/backend/backend/data/understanding.py

@@ -86,6 +86,11 @@ class BusinessUnderstandingInput(pydantic.BaseModel):
         None, description="Any additional context"
     )
 
+    # Suggested prompts (UI-only, not included in system prompt)
+    suggested_prompts: Optional[list[str]] = pydantic.Field(
+        None, description="LLM-generated suggested prompts based on business context"
+    )
+
 
 class BusinessUnderstanding(pydantic.BaseModel):
     """Full business understanding model returned from database."""
@@ -122,6 +127,9 @@ class BusinessUnderstanding(pydantic.BaseModel):
     # Additional context
     additional_notes: Optional[str] = None
 
+    # Suggested prompts (UI-only, not included in system prompt)
+    suggested_prompts: list[str] = pydantic.Field(default_factory=list)
+
     @classmethod
     def from_db(cls, db_record: CoPilotUnderstanding) -> "BusinessUnderstanding":
         """Convert database record to Pydantic model."""
@@ -149,6 +157,7 @@ class BusinessUnderstanding(pydantic.BaseModel):
             current_software=_json_to_list(business.get("current_software")),
             existing_automation=_json_to_list(business.get("existing_automation")),
             additional_notes=business.get("additional_notes"),
+            suggested_prompts=_json_to_list(data.get("suggested_prompts")),
         )
 
 
@@ -166,6 +175,62 @@ def _merge_lists(existing: list | None, new: list | None) -> list | None:
     return merged
 
 
+def merge_business_understanding_data(
+    existing_data: dict[str, Any],
+    input_data: BusinessUnderstandingInput,
+) -> dict[str, Any]:
+    merged_data = dict(existing_data)
+
+    merged_business: dict[str, Any] = {}
+    if isinstance(merged_data.get("business"), dict):
+        merged_business = dict(merged_data["business"])
+
+    business_string_fields = [
+        "job_title",
+        "business_name",
+        "industry",
+        "business_size",
+        "user_role",
+        "additional_notes",
+    ]
+    business_list_fields = [
+        "key_workflows",
+        "daily_activities",
+        "pain_points",
+        "bottlenecks",
+        "manual_tasks",
+        "automation_goals",
+        "current_software",
+        "existing_automation",
+    ]
+
+    if input_data.user_name is not None:
+        merged_data["name"] = input_data.user_name
+
+    for field in business_string_fields:
+        value = getattr(input_data, field)
+        if value is not None:
+            merged_business[field] = value
+
+    for field in business_list_fields:
+        value = getattr(input_data, field)
+        if value is not None:
+            existing_list = _json_to_list(merged_business.get(field))
+            merged_list = _merge_lists(existing_list, value)
+            merged_business[field] = merged_list
+
+    merged_business["version"] = 1
+    merged_data["business"] = merged_business
+
+    # suggested_prompts lives at the top level (not under `business`) because
+    # it's a UI-only artifact consumed by the frontend, not business understanding
+    # data. The `business` sub-dict feeds the system prompt.
+    if input_data.suggested_prompts is not None:
+        merged_data["suggested_prompts"] = input_data.suggested_prompts
+
+    return merged_data
+
+
 async def _get_from_cache(user_id: str) -> Optional[BusinessUnderstanding]:
     """Get business understanding from Redis cache."""
     try:
@@ -245,63 +310,18 @@ async def upsert_business_understanding(
         where={"userId": user_id}
     )
 
-    # Get existing data structure or start fresh
     existing_data: dict[str, Any] = {}
     if existing and isinstance(existing.data, dict):
         existing_data = dict(existing.data)
 
-    existing_business: dict[str, Any] = {}
-    if isinstance(existing_data.get("business"), dict):
-        existing_business = dict(existing_data["business"])
-
-    # Business fields (stored inside business object)
-    business_string_fields = [
-        "job_title",
-        "business_name",
-        "industry",
-        "business_size",
-        "user_role",
-        "additional_notes",
-    ]
-    business_list_fields = [
-        "key_workflows",
-        "daily_activities",
-        "pain_points",
-        "bottlenecks",
-        "manual_tasks",
-        "automation_goals",
-        "current_software",
-        "existing_automation",
-    ]
-
-    # Handle top-level name field
-    if input_data.user_name is not None:
-        existing_data["name"] = input_data.user_name
-
-    # Business string fields - overwrite if provided
-    for field in business_string_fields:
-        value = getattr(input_data, field)
-        if value is not None:
-            existing_business[field] = value
-
-    # Business list fields - merge with existing
-    for field in business_list_fields:
-        value = getattr(input_data, field)
-        if value is not None:
-            existing_list = _json_to_list(existing_business.get(field))
-            merged = _merge_lists(existing_list, value)
-            existing_business[field] = merged
-
-    # Set version and nest business data
-    existing_business["version"] = 1
-    existing_data["business"] = existing_business
+    merged_data = merge_business_understanding_data(existing_data, input_data)
 
     # Upsert with the merged data
     record = await CoPilotUnderstanding.prisma().upsert(
         where={"userId": user_id},
         data={
-            "create": {"userId": user_id, "data": SafeJson(existing_data)},
-            "update": {"data": SafeJson(existing_data)},
+            "create": {"userId": user_id, "data": SafeJson(merged_data)},
+            "update": {"data": SafeJson(merged_data)},
         },
     )
 

autogpt_platform/backend/backend/data/understanding_test.py

@@ -0,0 +1,102 @@
+"""Tests for business understanding merge and format logic."""
+
+from datetime import datetime, timezone
+from typing import Any
+
+from backend.data.understanding import (
+    BusinessUnderstanding,
+    BusinessUnderstandingInput,
+    format_understanding_for_prompt,
+    merge_business_understanding_data,
+)
+
+
+def _make_input(**kwargs: Any) -> BusinessUnderstandingInput:
+    """Create a BusinessUnderstandingInput with only the specified fields."""
+    return BusinessUnderstandingInput.model_validate(kwargs)
+
+
+# ─── merge_business_understanding_data: suggested_prompts ─────────────
+
+
+def test_merge_suggested_prompts_overwrites_existing():
+    """New suggested_prompts should fully replace existing ones (not append)."""
+    existing = {
+        "name": "Alice",
+        "business": {"industry": "Tech", "version": 1},
+        "suggested_prompts": ["Old prompt 1", "Old prompt 2"],
+    }
+    input_data = _make_input(
+        suggested_prompts=["New prompt A", "New prompt B", "New prompt C"],
+    )
+
+    result = merge_business_understanding_data(existing, input_data)
+
+    assert result["suggested_prompts"] == [
+        "New prompt A",
+        "New prompt B",
+        "New prompt C",
+    ]
+
+
+def test_merge_suggested_prompts_none_preserves_existing():
+    """When input has suggested_prompts=None, existing prompts are preserved."""
+    existing = {
+        "name": "Alice",
+        "business": {"industry": "Tech", "version": 1},
+        "suggested_prompts": ["Keep me"],
+    }
+    input_data = _make_input(industry="Finance")
+
+    result = merge_business_understanding_data(existing, input_data)
+
+    assert result["suggested_prompts"] == ["Keep me"]
+    assert result["business"]["industry"] == "Finance"
+
+
+def test_merge_suggested_prompts_added_to_empty_data():
+    """Suggested prompts are set at top level even when starting from empty data."""
+    existing: dict[str, Any] = {}
+    input_data = _make_input(suggested_prompts=["Prompt 1"])
+
+    result = merge_business_understanding_data(existing, input_data)
+
+    assert result["suggested_prompts"] == ["Prompt 1"]
+
+
+def test_merge_suggested_prompts_empty_list_overwrites():
+    """An explicit empty list should overwrite existing prompts."""
+    existing: dict[str, Any] = {
+        "suggested_prompts": ["Old prompt"],
+        "business": {"version": 1},
+    }
+    input_data = _make_input(suggested_prompts=[])
+
+    result = merge_business_understanding_data(existing, input_data)
+
+    assert result["suggested_prompts"] == []
+
+
+# ─── format_understanding_for_prompt: excludes suggested_prompts ──────
+
+
+def test_format_understanding_excludes_suggested_prompts():
+    """suggested_prompts is UI-only and must NOT appear in the system prompt."""
+    understanding = BusinessUnderstanding(
+        id="test-id",
+        user_id="user-1",
+        created_at=datetime.now(tz=timezone.utc),
+        updated_at=datetime.now(tz=timezone.utc),
+        user_name="Alice",
+        industry="Technology",
+        suggested_prompts=["Automate reports", "Set up alerts", "Track KPIs"],
+    )
+
+    formatted = format_understanding_for_prompt(understanding)
+
+    assert "Alice" in formatted
+    assert "Technology" in formatted
+    assert "suggested_prompts" not in formatted
+    assert "Automate reports" not in formatted
+    assert "Set up alerts" not in formatted
+    assert "Track KPIs" not in formatted