feat(frontend/builder): add confirmation dialog for workspace file removal

When users remove a file from a file input in the builder, show a
confirmation dialog since workspace file deletion is non-reversible.
Only triggers for workspace uploads (onDeleteFile provided); base64
mode clears immediately as before.

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

@@ -0,0 +1,200 @@
+---
+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."
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# PR Address
+
+## Find the PR
+
+```bash
+gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT
+gh pr view {N}
+```
+
+## 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 }
+          }
+        }
+      }
+    }
+  }
+}'
+```
+
+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.
+
+## For each unaddressed comment
+
+Address comments **one at a time**: fix → commit → push → inline reply → next.
+
+1. Read the referenced code, make the fix (or reply explaining why it's not needed)
+2. Commit and push the fix
+3. Reply **inline** (not as a new top-level comment) referencing the fixing commit — this is what resolves the conversation for bot reviewers (coderabbitai, sentry):
+
+| Comment type | How to reply |
+|---|---|
+| Inline review (`pulls/{N}/comments`) | `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments/{ID}/replies -f body="🤖 Fixed in <commit-sha>: <description>"` |
+| Conversation (`issues/{N}/comments`) | `gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments -f body="🤖 Fixed in <commit-sha>: <description>"` |
+
+## Format and commit
+
+After fixing, format the changed code:
+
+- **Backend** (from `autogpt_platform/backend/`): `poetry run format`
+- **Frontend** (from `autogpt_platform/frontend/`): `pnpm format && pnpm lint && pnpm types`
+
+If API routes changed, regenerate the frontend client:
+```bash
+cd autogpt_platform/backend && poetry run rest &
+REST_PID=$!
+trap "kill $REST_PID 2>/dev/null" EXIT
+WAIT=0; until curl -sf http://localhost:8006/health > /dev/null 2>&1; do sleep 1; WAIT=$((WAIT+1)); [ $WAIT -ge 60 ] && echo "Timed out" && exit 1; done
+cd ../frontend && pnpm generate:api:force
+kill $REST_PID 2>/dev/null; trap - EXIT
+```
+Never manually edit files in `src/app/api/__generated__/`.
+
+Then commit and **push immediately** — never batch commits without pushing.
+
+For backend commits in worktrees: `poetry run git commit` (pre-commit hooks).
+
+## The loop
+
+```text
+address comments → format → commit → push
+→ wait for CI (while addressing new comments) → fix failures → push
+→ re-check comments after CI settles
+→ repeat until: all comments addressed AND CI green AND no new comments arriving
+```
+
+### Polling for CI + new comments
+
+After pushing, poll for **both** CI status and new comments in a single loop. Do not use `gh pr checks --watch` — it blocks the tool and prevents reacting to new comments while CI is running.
+
+> **Note:** `gh pr checks --watch --fail-fast` is tempting but it blocks the entire Bash tool call, meaning the agent cannot check for or address new comments until CI fully completes. Always poll manually instead.
+
+**Polling loop — repeat every 30 seconds:**
+
+1. Check CI status:
+```bash
+gh pr checks {N} --repo Significant-Gravitas/AutoGPT --json bucket,name,link
+```
+   Parse the results: if every check has `bucket` of `"pass"` or `"skipping"`, CI is green. If any has `"fail"`, CI has failed. Otherwise CI is still pending.
+
+2. Check for merge conflicts:
+```bash
+gh pr view {N} --repo Significant-Gravitas/AutoGPT --json mergeable --jq '.mergeable'
+```
+   If the result is `"CONFLICTING"`, the PR has a merge conflict — see "Resolving merge conflicts" below. If `"UNKNOWN"`, GitHub is still computing mergeability — wait and re-check next poll.
+
+3. Check for new/changed comments (all three sources):
+
+   **Inline threads** — re-run the GraphQL query from "Fetch comments". For each unresolved thread, record `{thread_id, last_comment_databaseId}` as your baseline. On each poll, action is needed if:
+   - A new thread `id` appears that wasn't in the baseline (new thread), OR
+   - An existing thread's `last_comment_databaseId` has changed (new reply on existing thread)
+
+   **Conversation comments:**
+   ```bash
+   gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments --paginate
+   ```
+   Compare total count and newest `id` against baseline. Filter to non-empty, non-bot, non-author-update messages.
+
+   **Top-level reviews:**
+   ```bash
+   gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews --paginate
+   ```
+   Watch for new non-empty reviews (`CHANGES_REQUESTED` or `COMMENTED` with body). Compare total count and newest `id` against baseline.
+
+4. **React in this precedence order (first match wins):**
+
+| What happened | Action |
+|---|---|
+| Merge conflict detected | See "Resolving merge conflicts" below. |
+| Mergeability is `UNKNOWN` | GitHub is still computing mergeability. Sleep 30 seconds, then restart polling from the top. |
+| New comments detected | Address them (fix → commit → push → reply). After pushing, re-fetch all comments to update your baseline, then restart this polling loop from the top (new commits invalidate CI status). |
+| CI failed (bucket == "fail") | Get failed check links: `gh pr checks {N} --repo Significant-Gravitas/AutoGPT --json bucket,link --jq '.[] \| select(.bucket == "fail") \| .link'`. Extract run ID from link (format: `.../actions/runs/<run-id>/job/...`), read logs with `gh run view <run-id> --repo Significant-Gravitas/AutoGPT --log-failed`. Fix → commit → push → restart polling. |
+| CI green + no new comments | **Do not exit immediately.** Bots (coderabbitai, sentry) often post reviews shortly after CI settles. Continue polling for **2 more cycles (60s)** after CI goes green. Only exit after 2 consecutive green+quiet polls. |
+| CI pending + no new comments | Sleep 30 seconds, then poll again. |
+
+**The loop ends when:** CI fully green + all comments addressed + **2 consecutive polls with no new comments after CI settled.**
+
+### Resolving merge conflicts
+
+1. Identify the PR's target branch and remote:
+```bash
+gh pr view {N} --repo Significant-Gravitas/AutoGPT --json baseRefName --jq '.baseRefName'
+git remote -v   # find the remote pointing to Significant-Gravitas/AutoGPT (typically 'upstream' in forks, 'origin' for direct contributors)
+```
+
+2. Pull the latest base branch with a 3-way merge:
+```bash
+git pull {base-remote} {base-branch} --no-rebase
+```
+
+3. Resolve conflicting files, then verify no conflict markers remain:
+```bash
+if grep -R -n -E '^(<<<<<<<|=======|>>>>>>>)' <conflicted-files>; then
+  echo "Unresolved conflict markers found — resolve before proceeding."
+  exit 1
+fi
+```
+
+4. Stage and push:
+```bash
+git add <conflicted-files>
+git commit -m "Resolve merge conflicts with {base-branch}"
+git push
+```
+
+5. Restart the polling loop from the top — new commits reset CI status.

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

@@ -0,0 +1,74 @@
+---
+name: pr-review
+description: Review a PR for correctness, security, code quality, and testing issues. TRIGGER when user asks to review a PR, check PR quality, or give feedback on a PR.
+user-invocable: true
+args: "[PR number or URL] — if omitted, finds PR for current branch."
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# PR Review
+
+## Find the PR
+
+```bash
+gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT
+gh pr view {N}
+```
+
+## Read the diff
+
+```bash
+gh pr diff {N}
+```
+
+## Fetch existing review comments
+
+Before posting anything, fetch existing inline comments to avoid duplicates:
+
+```bash
+gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments --paginate
+gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews
+```
+
+## What to check
+
+**Correctness:** logic errors, off-by-one, missing edge cases, race conditions (TOCTOU in file access, credit charging), error handling gaps, async correctness (missing `await`, unclosed resources).
+
+**Security:** input validation at boundaries, no injection (command, XSS, SQL), secrets not logged, file paths sanitized (`os.path.basename()` in error messages).
+
+**Code quality:** apply rules from backend/frontend CLAUDE.md files.
+
+**Architecture:** DRY, single responsibility, modular functions. `Security()` vs `Depends()` for FastAPI auth. `data:` for SSE events, `: comment` for heartbeats. `transaction=True` for Redis pipelines.
+
+**Testing:** edge cases covered, colocated `*_test.py` (backend) / `__tests__/` (frontend), mocks target where symbol is **used** not defined, `AsyncMock` for async.
+
+## Output format
+
+Every comment **must** be prefixed with `🤖` and a criticality badge:
+
+| Tier | Badge | Meaning |
+|---|---|---|
+| Blocker | `🔴 **Blocker**` | Must fix before merge |
+| Should Fix | `🟠 **Should Fix**` | Important improvement |
+| Nice to Have | `🟡 **Nice to Have**` | Minor suggestion |
+| Nit | `🔵 **Nit**` | Style / wording |
+
+Example: `🤖 🔴 **Blocker**: Missing error handling for X — suggest wrapping in try/except.`
+
+## Post inline comments
+
+For each finding, post an inline comment on the PR (do not just write a local report):
+
+```bash
+# Get the latest commit SHA for the PR
+COMMIT_SHA=$(gh api repos/Significant-Gravitas/AutoGPT/pulls/{N} --jq '.head.sha')
+
+# Post an inline comment on a specific file/line
+gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments \
+  -f body="🤖 🔴 **Blocker**: <description>" \
+  -f commit_id="$COMMIT_SHA" \
+  -f path="<file path>" \
+  -F line=<line number>
+```

.claude/skills/worktree/SKILL.md

@@ -0,0 +1,85 @@
+---
+name: worktree
+description: Set up a new git worktree for parallel development. Creates the worktree, copies .env files, installs dependencies, and generates Prisma client. TRIGGER when user asks to set up a worktree, work on a branch in isolation, or needs a separate environment for a branch or PR.
+user-invocable: true
+args: "[name] — optional worktree name (e.g., 'AutoGPT7'). If omitted, uses next available AutoGPT<N>."
+metadata:
+  author: autogpt-team
+  version: "3.0.0"
+---
+
+# Worktree Setup
+
+## Create the worktree
+
+Derive paths from the git toplevel. If a name is provided as argument, use it. Otherwise, check `git worktree list` and pick the next `AutoGPT<N>`.
+
+```bash
+ROOT=$(git rev-parse --show-toplevel)
+PARENT=$(dirname "$ROOT")
+
+# From an existing branch
+git worktree add "$PARENT/<NAME>" <branch-name>
+
+# From a new branch off dev
+git worktree add -b <new-branch> "$PARENT/<NAME>" dev
+```
+
+## Copy environment files
+
+Copy `.env` from the root worktree. Falls back to `.env.default` if `.env` doesn't exist.
+
+```bash
+ROOT=$(git rev-parse --show-toplevel)
+TARGET="$(dirname "$ROOT")/<NAME>"
+
+for envpath in autogpt_platform/backend autogpt_platform/frontend autogpt_platform; do
+  if [ -f "$ROOT/$envpath/.env" ]; then
+    cp "$ROOT/$envpath/.env" "$TARGET/$envpath/.env"
+  elif [ -f "$ROOT/$envpath/.env.default" ]; then
+    cp "$ROOT/$envpath/.env.default" "$TARGET/$envpath/.env"
+  fi
+done
+```
+
+## Install dependencies
+
+```bash
+TARGET="$(dirname "$(git rev-parse --show-toplevel)")/<NAME>"
+cd "$TARGET/autogpt_platform/autogpt_libs" && poetry install
+cd "$TARGET/autogpt_platform/backend" && poetry install && poetry run prisma generate
+cd "$TARGET/autogpt_platform/frontend" && pnpm install
+```
+
+Replace `<NAME>` with the actual worktree name (e.g., `AutoGPT7`).
+
+## Running the app (optional)
+
+Backend uses ports: 8001, 8002, 8003, 8005, 8006, 8007, 8008. Free them first if needed:
+
+```bash
+TARGET="$(dirname "$(git rev-parse --show-toplevel)")/<NAME>"
+for port in 8001 8002 8003 8005 8006 8007 8008; do
+  lsof -ti :$port | xargs kill -9 2>/dev/null || true
+done
+cd "$TARGET/autogpt_platform/backend" && poetry run app
+```
+
+## CoPilot testing
+
+SDK mode spawns a Claude subprocess — won't work inside Claude Code. Set `CHAT_USE_CLAUDE_AGENT_SDK=false` in `backend/.env` to use baseline mode.
+
+## Cleanup
+
+```bash
+# Replace <NAME> with the actual worktree name (e.g., AutoGPT7)
+git worktree remove "$(dirname "$(git rev-parse --show-toplevel)")/<NAME>"
+```
+
+## Alternative: Branchlet (optional)
+
+If [branchlet](https://www.npmjs.com/package/branchlet) is installed:
+
+```bash
+branchlet create -n <name> -s <source-branch> -b <new-branch>
+```

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

@@ -5,12 +5,14 @@ on:
     branches: [master, dev, ci-test*]
     paths:
       - ".github/workflows/platform-backend-ci.yml"
+      - ".github/workflows/scripts/get_package_version_from_lockfile.py"
       - "autogpt_platform/backend/**"
       - "autogpt_platform/autogpt_libs/**"
   pull_request:
     branches: [master, dev, release-*]
     paths:
       - ".github/workflows/platform-backend-ci.yml"
+      - ".github/workflows/scripts/get_package_version_from_lockfile.py"
       - "autogpt_platform/backend/**"
       - "autogpt_platform/autogpt_libs/**"
   merge_group:
@@ -25,10 +27,91 @@ defaults:
     working-directory: autogpt_platform/backend
 
 jobs:
+  lint:
+    permissions:
+      contents: read
+    timeout-minutes: 10
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v6
+
+      - name: Set up Python 3.12
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+
+      - name: Set up Python dependency cache
+        uses: actions/cache@v5
+        with:
+          path: ~/.cache/pypoetry
+          key: poetry-${{ runner.os }}-py3.12-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
+
+      - name: Install Poetry
+        run: |
+          HEAD_POETRY_VERSION=$(python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
+          echo "Using Poetry version ${HEAD_POETRY_VERSION}"
+          curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
+
+      - name: Install Python dependencies
+        run: poetry install
+
+      - name: Run Linters
+        run: poetry run lint --skip-pyright
+
+    env:
+      CI: true
+      PLAIN_OUTPUT: True
+
+  type-check:
+    permissions:
+      contents: read
+    timeout-minutes: 10
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.11", "3.12", "3.13"]
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v6
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Set up Python dependency cache
+        uses: actions/cache@v5
+        with:
+          path: ~/.cache/pypoetry
+          key: poetry-${{ runner.os }}-py${{ matrix.python-version }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
+
+      - name: Install Poetry
+        run: |
+          HEAD_POETRY_VERSION=$(python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
+          echo "Using Poetry version ${HEAD_POETRY_VERSION}"
+          curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
+
+      - name: Install Python dependencies
+        run: poetry install
+
+      - name: Generate Prisma Client
+        run: poetry run prisma generate && poetry run gen-prisma-stub
+
+      - name: Run Pyright
+        run: poetry run pyright --pythonversion ${{ matrix.python-version }}
+
+    env:
+      CI: true
+      PLAIN_OUTPUT: True
+
   test:
     permissions:
       contents: read
-    timeout-minutes: 30
+    timeout-minutes: 15
     strategy:
       fail-fast: false
       matrix:
@@ -96,9 +179,9 @@ jobs:
         uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
-          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
+          key: poetry-${{ runner.os }}-py${{ matrix.python-version }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
 
-      - name: Install Poetry (Unix)
+      - name: Install Poetry
         run: |
           # Extract Poetry version from backend/poetry.lock
           HEAD_POETRY_VERSION=$(python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
@@ -156,22 +239,22 @@ jobs:
           echo "Waiting for ClamAV daemon to start..."
           max_attempts=60
           attempt=0
-          
+
           until nc -z localhost 3310 || [ $attempt -eq $max_attempts ]; do
             echo "ClamAV is unavailable - sleeping (attempt $((attempt+1))/$max_attempts)"
             sleep 5
             attempt=$((attempt+1))
           done
-          
+
           if [ $attempt -eq $max_attempts ]; then
             echo "ClamAV failed to start after $((max_attempts*5)) seconds"
             echo "Checking ClamAV service logs..."
             docker logs $(docker ps -q --filter "ancestor=clamav/clamav-debian:latest") 2>&1 | tail -50 || echo "No ClamAV container found"
             exit 1
           fi
-          
+
           echo "ClamAV is ready!"
-          
+
           # Verify ClamAV is responsive
           echo "Testing ClamAV connection..."
           timeout 10 bash -c 'echo "PING" | nc localhost 3310' || {
@@ -186,18 +269,13 @@ jobs:
           DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
           DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}
 
-      - id: lint
-        name: Run Linter
-        run: poetry run lint
-
-      - name: Run pytest with coverage
+      - name: Run pytest
         run: |
           if [[ "${{ runner.debug }}" == "1" ]]; then
             poetry run pytest -s -vv -o log_cli=true -o log_cli_level=DEBUG
           else
             poetry run pytest -s -vv
           fi
-        if: success() || (failure() && steps.lint.outcome == 'failure')
         env:
           LOG_LEVEL: ${{ runner.debug && 'DEBUG' || 'INFO' }}
           DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
@@ -209,6 +287,12 @@ jobs:
           REDIS_PORT: "6379"
           ENCRYPTION_KEY: "dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw=" # DO NOT USE IN PRODUCTION!!
 
+      # - name: Upload coverage reports to Codecov
+      #   uses: codecov/codecov-action@v4
+      #   with:
+      #     token: ${{ secrets.CODECOV_TOKEN }}
+      #     flags: backend,${{ runner.os }}
+
     env:
       CI: true
       PLAIN_OUTPUT: True
@@ -222,9 +306,3 @@ jobs:
       # the backend service, docker composes, and examples
       RABBITMQ_DEFAULT_USER: "rabbitmq_user_default"
       RABBITMQ_DEFAULT_PASS: "k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7"
-
-      # - name: Upload coverage reports to Codecov
-      #   uses: codecov/codecov-action@v4
-      #   with:
-      #     token: ${{ secrets.CODECOV_TOKEN }}
-      #     flags: backend,${{ runner.os }}

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

@@ -120,175 +120,6 @@ jobs:
           token: ${{ secrets.GITHUB_TOKEN }}
           exitOnceUploaded: true
 
-  e2e_test:
-    name: end-to-end tests
-    runs-on: big-boi
-
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v6
-        with:
-          submodules: recursive
-
-      - name: Set up Platform - Copy default supabase .env
-        run: |
-          cp ../.env.default ../.env
-
-      - name: Set up Platform - Copy backend .env and set OpenAI API key
-        run: |
-          cp ../backend/.env.default ../backend/.env
-          echo "OPENAI_INTERNAL_API_KEY=${{ secrets.OPENAI_API_KEY }}" >> ../backend/.env
-        env:
-          # Used by E2E test data script to generate embeddings for approved store agents
-          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-
-      - name: Set up Platform - Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
-        with:
-          driver: docker-container
-          driver-opts: network=host
-
-      - name: Set up Platform - Expose GHA cache to docker buildx CLI
-        uses: crazy-max/ghaction-github-runtime@v4
-
-      - name: Set up Platform - Build Docker images (with cache)
-        working-directory: autogpt_platform
-        run: |
-          pip install pyyaml
-
-          # Resolve extends and generate a flat compose file that bake can understand
-          docker compose -f docker-compose.yml config > docker-compose.resolved.yml
-
-          # Add cache configuration to the resolved compose file
-          python ../.github/workflows/scripts/docker-ci-fix-compose-build-cache.py \
-            --source docker-compose.resolved.yml \
-            --cache-from "type=gha" \
-            --cache-to "type=gha,mode=max" \
-            --backend-hash "${{ hashFiles('autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/poetry.lock', 'autogpt_platform/backend/backend') }}" \
-            --frontend-hash "${{ hashFiles('autogpt_platform/frontend/Dockerfile', 'autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/src') }}" \
-            --git-ref "${{ github.ref }}"
-
-          # Build with bake using the resolved compose file (now includes cache config)
-          docker buildx bake --allow=fs.read=.. -f docker-compose.resolved.yml --load
-        env:
-          NEXT_PUBLIC_PW_TEST: true
-
-      - name: Set up tests - Cache E2E test data
-        id: e2e-data-cache
-        uses: actions/cache@v5
-        with:
-          path: /tmp/e2e_test_data.sql
-          key: e2e-test-data-${{ hashFiles('autogpt_platform/backend/test/e2e_test_data.py', 'autogpt_platform/backend/migrations/**', '.github/workflows/platform-frontend-ci.yml') }}
-
-      - name: Set up Platform - Start Supabase DB + Auth
-        run: |
-          docker compose -f ../docker-compose.resolved.yml up -d db auth --no-build
-          echo "Waiting for database to be ready..."
-          timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done'
-          echo "Waiting for auth service to be ready..."
-          timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -c "SELECT 1 FROM auth.users LIMIT 1" 2>/dev/null; do sleep 2; done' || echo "Auth schema check timeout, continuing..."
-
-      - name: Set up Platform - Run migrations
-        run: |
-          echo "Running migrations..."
-          docker compose -f ../docker-compose.resolved.yml run --rm migrate
-          echo "✅ Migrations completed"
-        env:
-          NEXT_PUBLIC_PW_TEST: true
-
-      - name: Set up tests - Load cached E2E test data
-        if: steps.e2e-data-cache.outputs.cache-hit == 'true'
-        run: |
-          echo "✅ Found cached E2E test data, restoring..."
-          {
-            echo "SET session_replication_role = 'replica';"
-            cat /tmp/e2e_test_data.sql
-            echo "SET session_replication_role = 'origin';"
-          } | docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -b
-          # Refresh materialized views after restore
-          docker compose -f ../docker-compose.resolved.yml exec -T db \
-            psql -U postgres -d postgres -b -c "SET search_path TO platform; SELECT refresh_store_materialized_views();" || true
-
-          echo "✅ E2E test data restored from cache"
-
-      - name: Set up Platform - Start (all other services)
-        run: |
-          docker compose -f ../docker-compose.resolved.yml up -d --no-build
-          echo "Waiting for rest_server to be ready..."
-          timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
-        env:
-          NEXT_PUBLIC_PW_TEST: true
-
-      - name: Set up tests - Create E2E test data
-        if: steps.e2e-data-cache.outputs.cache-hit != 'true'
-        run: |
-          echo "Creating E2E test data..."
-          docker cp ../backend/test/e2e_test_data.py $(docker compose -f ../docker-compose.resolved.yml ps -q rest_server):/tmp/e2e_test_data.py
-          docker compose -f ../docker-compose.resolved.yml exec -T rest_server sh -c "cd /app/autogpt_platform && python /tmp/e2e_test_data.py" || {
-            echo "❌ E2E test data creation failed!"
-            docker compose -f ../docker-compose.resolved.yml logs --tail=50 rest_server
-            exit 1
-          }
-
-          # Dump auth.users + platform schema for cache (two separate dumps)
-          echo "Dumping database for cache..."
-          {
-            docker compose -f ../docker-compose.resolved.yml exec -T db \
-              pg_dump -U postgres --data-only --column-inserts \
-              --table='auth.users' postgres
-            docker compose -f ../docker-compose.resolved.yml exec -T db \
-              pg_dump -U postgres --data-only --column-inserts \
-              --schema=platform \
-              --exclude-table='platform._prisma_migrations' \
-              --exclude-table='platform.apscheduler_jobs' \
-              --exclude-table='platform.apscheduler_jobs_batched_notifications' \
-              postgres
-          } > /tmp/e2e_test_data.sql
-
-          echo "✅ Database dump created for caching ($(wc -l < /tmp/e2e_test_data.sql) lines)"
-
-      - name: Set up tests - Enable corepack
-        run: corepack enable
-
-      - name: Set up tests - Set up Node
-        uses: actions/setup-node@v6
-        with:
-          node-version: "22.18.0"
-          cache: "pnpm"
-          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
-
-      - name: Set up tests - Install dependencies
-        run: pnpm install --frozen-lockfile
-
-      - name: Set up tests - Install browser 'chromium'
-        run: pnpm playwright install --with-deps chromium
-
-      - name: Run Playwright tests
-        run: pnpm test:no-build
-        continue-on-error: false
-
-      - name: Upload Playwright report
-        if: always()
-        uses: actions/upload-artifact@v4
-        with:
-          name: playwright-report
-          path: playwright-report
-          if-no-files-found: ignore
-          retention-days: 3
-
-      - name: Upload Playwright test results
-        if: always()
-        uses: actions/upload-artifact@v4
-        with:
-          name: playwright-test-results
-          path: test-results
-          if-no-files-found: ignore
-          retention-days: 3
-
-      - name: Print Final Docker Compose logs
-        if: always()
-        run: docker compose -f ../docker-compose.resolved.yml logs
-
   integration_test:
     runs-on: ubuntu-latest
     needs: setup

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

@@ -1,14 +1,18 @@
-name: AutoGPT Platform - Frontend CI
+name: AutoGPT Platform - Full-stack CI
 
 on:
   push:
     branches: [master, dev]
     paths:
       - ".github/workflows/platform-fullstack-ci.yml"
+      - ".github/workflows/scripts/docker-ci-fix-compose-build-cache.py"
+      - ".github/workflows/scripts/get_package_version_from_lockfile.py"
       - "autogpt_platform/**"
   pull_request:
     paths:
       - ".github/workflows/platform-fullstack-ci.yml"
+      - ".github/workflows/scripts/docker-ci-fix-compose-build-cache.py"
+      - ".github/workflows/scripts/get_package_version_from_lockfile.py"
       - "autogpt_platform/**"
   merge_group:
 
@@ -24,42 +28,28 @@ defaults:
 jobs:
   setup:
     runs-on: ubuntu-latest
-    outputs:
-      cache-key: ${{ steps.cache-key.outputs.key }}
 
     steps:
       - name: Checkout repository
         uses: actions/checkout@v6
 
-      - name: Set up Node.js
-        uses: actions/setup-node@v6
-        with:
-          node-version: "22.18.0"
-
       - name: Enable corepack
         run: corepack enable
 
-      - name: Generate cache key
-        id: cache-key
-        run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}" >> $GITHUB_OUTPUT
-
-      - name: Cache dependencies
-        uses: actions/cache@v5
+      - name: Set up Node
+        uses: actions/setup-node@v6
         with:
-          path: ~/.pnpm-store
-          key: ${{ steps.cache-key.outputs.key }}
-          restore-keys: |
-            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
-            ${{ runner.os }}-pnpm-
+          node-version: "22.18.0"
+          cache: "pnpm"
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
 
-      - name: Install dependencies
+      - name: Install dependencies to populate cache
         run: pnpm install --frozen-lockfile
 
-  types:
-    runs-on: big-boi
+  check-api-types:
+    name: check API types
+    runs-on: ubuntu-latest
     needs: setup
-    strategy:
-      fail-fast: false
 
     steps:
       - name: Checkout repository
@@ -67,70 +57,256 @@ jobs:
         with:
           submodules: recursive
 
-      - name: Set up Node.js
+      # ------------------------ Backend setup ------------------------
+
+      - name: Set up Backend - Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+
+      - name: Set up Backend - Install Poetry
+        working-directory: autogpt_platform/backend
+        run: |
+          POETRY_VERSION=$(python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
+          echo "Installing Poetry version ${POETRY_VERSION}"
+          curl -sSL https://install.python-poetry.org | POETRY_VERSION=$POETRY_VERSION python3 -
+
+      - name: Set up Backend - Set up dependency cache
+        uses: actions/cache@v5
+        with:
+          path: ~/.cache/pypoetry
+          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
+
+      - name: Set up Backend - Install dependencies
+        working-directory: autogpt_platform/backend
+        run: poetry install
+
+      - name: Set up Backend - Generate Prisma client
+        working-directory: autogpt_platform/backend
+        run: poetry run prisma generate && poetry run gen-prisma-stub
+
+      - name: Set up Frontend - Export OpenAPI schema from Backend
+        working-directory: autogpt_platform/backend
+        run: poetry run export-api-schema --output ../frontend/src/app/api/openapi.json
+
+      # ------------------------ Frontend setup ------------------------
+
+      - name: Set up Frontend - Enable corepack
+        run: corepack enable
+
+      - name: Set up Frontend - Set up Node
         uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
+          cache: "pnpm"
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
 
-      - name: Enable corepack
-        run: corepack enable
-
-      - name: Copy default supabase .env
-        run: |
-          cp ../.env.default ../.env
-
-      - name: Copy backend .env
-        run: |
-          cp ../backend/.env.default ../backend/.env
-
-      - name: Run docker compose
-        run: |
-          docker compose -f ../docker-compose.yml --profile local up -d deps_backend
-
-      - name: Restore dependencies cache
-        uses: actions/cache@v5
-        with:
-          path: ~/.pnpm-store
-          key: ${{ needs.setup.outputs.cache-key }}
-          restore-keys: |
-            ${{ runner.os }}-pnpm-
-
-      - name: Install dependencies
+      - name: Set up Frontend - Install dependencies
         run: pnpm install --frozen-lockfile
 
-      - name: Setup .env
-        run: cp .env.default .env
-
-      - name: Wait for services to be ready
-        run: |
-          echo "Waiting for rest_server to be ready..."
-          timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
-          echo "Waiting for database to be ready..."
-          timeout 60 sh -c 'until docker compose -f ../docker-compose.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done' || echo "Database ready check timeout, continuing..."
-
-      - name: Generate API queries
-        run: pnpm generate:api:force
+      - name: Set up Frontend - Format OpenAPI schema
+        id: format-schema
+        run: pnpm prettier --write ./src/app/api/openapi.json
 
       - name: Check for API schema changes
         run: |
           if ! git diff --exit-code src/app/api/openapi.json; then
             echo "❌ API schema changes detected in src/app/api/openapi.json"
             echo ""
-            echo "The openapi.json file has been modified after running 'pnpm generate:api-all'."
+            echo "The openapi.json file has been modified after exporting the API schema."
             echo "This usually means changes have been made in the BE endpoints without updating the Frontend."
             echo "The API schema is now out of sync with the Front-end queries."
             echo ""
             echo "To fix this:"
-            echo "1. Pull the backend 'docker compose pull && docker compose up -d --build --force-recreate'"
-            echo "2. Run 'pnpm generate:api' locally"
-            echo "3. Run 'pnpm types' locally"
-            echo "4. Fix any TypeScript errors that may have been introduced"
-            echo "5. Commit and push your changes"
+            echo "\nIn the backend directory:"
+            echo "1. Run 'poetry run export-api-schema --output ../frontend/src/app/api/openapi.json'"
+            echo "\nIn the frontend directory:"
+            echo "2. Run 'pnpm prettier --write src/app/api/openapi.json'"
+            echo "3. Run 'pnpm generate:api'"
+            echo "4. Run 'pnpm types'"
+            echo "5. Fix any TypeScript errors that may have been introduced"
+            echo "6. Commit and push your changes"
             echo ""
             exit 1
           else
             echo "✅ No API schema changes detected"
           fi
 
-      - name: Run Typescript checks
+      - name: Set up Frontend - Generate API client
+        id: generate-api-client
+        run: pnpm orval --config ./orval.config.ts
+        # Continue with type generation & check even if there are schema changes
+        if: success() || (steps.format-schema.outcome == 'success')
+
+      - name: Check for TypeScript errors
         run: pnpm types
+        if: success() || (steps.generate-api-client.outcome == 'success')
+
+  e2e_test:
+    name: end-to-end tests
+    runs-on: big-boi
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v6
+        with:
+          submodules: recursive
+
+      - name: Set up Platform - Copy default supabase .env
+        run: |
+          cp ../.env.default ../.env
+
+      - name: Set up Platform - Copy backend .env and set OpenAI API key
+        run: |
+          cp ../backend/.env.default ../backend/.env
+          echo "OPENAI_INTERNAL_API_KEY=${{ secrets.OPENAI_API_KEY }}" >> ../backend/.env
+        env:
+          # Used by E2E test data script to generate embeddings for approved store agents
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+
+      - name: Set up Platform - Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+        with:
+          driver: docker-container
+          driver-opts: network=host
+
+      - name: Set up Platform - Expose GHA cache to docker buildx CLI
+        uses: crazy-max/ghaction-github-runtime@v4
+
+      - name: Set up Platform - Build Docker images (with cache)
+        working-directory: autogpt_platform
+        run: |
+          pip install pyyaml
+
+          # Resolve extends and generate a flat compose file that bake can understand
+          docker compose -f docker-compose.yml config > docker-compose.resolved.yml
+
+          # Add cache configuration to the resolved compose file
+          python ../.github/workflows/scripts/docker-ci-fix-compose-build-cache.py \
+            --source docker-compose.resolved.yml \
+            --cache-from "type=gha" \
+            --cache-to "type=gha,mode=max" \
+            --backend-hash "${{ hashFiles('autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/poetry.lock', 'autogpt_platform/backend/backend/**') }}" \
+            --frontend-hash "${{ hashFiles('autogpt_platform/frontend/Dockerfile', 'autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/src/**') }}" \
+            --git-ref "${{ github.ref }}"
+
+          # Build with bake using the resolved compose file (now includes cache config)
+          docker buildx bake --allow=fs.read=.. -f docker-compose.resolved.yml --load
+        env:
+          NEXT_PUBLIC_PW_TEST: true
+
+      - name: Set up tests - Cache E2E test data
+        id: e2e-data-cache
+        uses: actions/cache@v5
+        with:
+          path: /tmp/e2e_test_data.sql
+          key: e2e-test-data-${{ hashFiles('autogpt_platform/backend/test/e2e_test_data.py', 'autogpt_platform/backend/migrations/**', '.github/workflows/platform-fullstack-ci.yml') }}
+
+      - name: Set up Platform - Start Supabase DB + Auth
+        run: |
+          docker compose -f ../docker-compose.resolved.yml up -d db auth --no-build
+          echo "Waiting for database to be ready..."
+          timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done'
+          echo "Waiting for auth service to be ready..."
+          timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -c "SELECT 1 FROM auth.users LIMIT 1" 2>/dev/null; do sleep 2; done' || echo "Auth schema check timeout, continuing..."
+
+      - name: Set up Platform - Run migrations
+        run: |
+          echo "Running migrations..."
+          docker compose -f ../docker-compose.resolved.yml run --rm migrate
+          echo "✅ Migrations completed"
+        env:
+          NEXT_PUBLIC_PW_TEST: true
+
+      - name: Set up tests - Load cached E2E test data
+        if: steps.e2e-data-cache.outputs.cache-hit == 'true'
+        run: |
+          echo "✅ Found cached E2E test data, restoring..."
+          {
+            echo "SET session_replication_role = 'replica';"
+            cat /tmp/e2e_test_data.sql
+            echo "SET session_replication_role = 'origin';"
+          } | docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -b
+          # Refresh materialized views after restore
+          docker compose -f ../docker-compose.resolved.yml exec -T db \
+            psql -U postgres -d postgres -b -c "SET search_path TO platform; SELECT refresh_store_materialized_views();" || true
+
+          echo "✅ E2E test data restored from cache"
+
+      - name: Set up Platform - Start (all other services)
+        run: |
+          docker compose -f ../docker-compose.resolved.yml up -d --no-build
+          echo "Waiting for rest_server to be ready..."
+          timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
+        env:
+          NEXT_PUBLIC_PW_TEST: true
+
+      - name: Set up tests - Create E2E test data
+        if: steps.e2e-data-cache.outputs.cache-hit != 'true'
+        run: |
+          echo "Creating E2E test data..."
+          docker cp ../backend/test/e2e_test_data.py $(docker compose -f ../docker-compose.resolved.yml ps -q rest_server):/tmp/e2e_test_data.py
+          docker compose -f ../docker-compose.resolved.yml exec -T rest_server sh -c "cd /app/autogpt_platform && python /tmp/e2e_test_data.py" || {
+            echo "❌ E2E test data creation failed!"
+            docker compose -f ../docker-compose.resolved.yml logs --tail=50 rest_server
+            exit 1
+          }
+
+          # Dump auth.users + platform schema for cache (two separate dumps)
+          echo "Dumping database for cache..."
+          {
+            docker compose -f ../docker-compose.resolved.yml exec -T db \
+              pg_dump -U postgres --data-only --column-inserts \
+              --table='auth.users' postgres
+            docker compose -f ../docker-compose.resolved.yml exec -T db \
+              pg_dump -U postgres --data-only --column-inserts \
+              --schema=platform \
+              --exclude-table='platform._prisma_migrations' \
+              --exclude-table='platform.apscheduler_jobs' \
+              --exclude-table='platform.apscheduler_jobs_batched_notifications' \
+              postgres
+          } > /tmp/e2e_test_data.sql
+
+          echo "✅ Database dump created for caching ($(wc -l < /tmp/e2e_test_data.sql) lines)"
+
+      - name: Set up tests - Enable corepack
+        run: corepack enable
+
+      - name: Set up tests - Set up Node
+        uses: actions/setup-node@v6
+        with:
+          node-version: "22.18.0"
+          cache: "pnpm"
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
+
+      - name: Set up tests - Install dependencies
+        run: pnpm install --frozen-lockfile
+
+      - name: Set up tests - Install browser 'chromium'
+        run: pnpm playwright install --with-deps chromium
+
+      - name: Run Playwright tests
+        run: pnpm test:no-build
+        continue-on-error: false
+
+      - name: Upload Playwright report
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: playwright-report
+          path: autogpt_platform/frontend/playwright-report
+          if-no-files-found: ignore
+          retention-days: 3
+
+      - name: Upload Playwright test results
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: playwright-test-results
+          path: autogpt_platform/frontend/test-results
+          if-no-files-found: ignore
+          retention-days: 3
+
+      - name: Print Final Docker Compose logs
+        if: always()
+        run: docker compose -f ../docker-compose.resolved.yml logs

autogpt_platform/CLAUDE.md

@@ -56,13 +56,36 @@ AutoGPT Platform is a monorepo containing:
 - Ensure the branch name is descriptive (e.g., `feature/add-new-block`)
 - Use conventional commit messages (see below)
 - 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
 
-- When the user runs /pr-comments or tries to fetch them, also run gh api /repos/Significant-Gravitas/AutoGPT/pulls/[issuenum]/reviews to get the reviews
-- Use gh api /repos/Significant-Gravitas/AutoGPT/pulls/[issuenum]/reviews/[review_id]/comments to get the review contents
-- Use gh api /repos/Significant-Gravitas/AutoGPT/issues/9924/comments to get the pr specific comments
+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/issues/{N}/comments` — PR conversation comments
 
 ### Conventional Commits
 

autogpt_platform/analytics/queries/auth_activities.sql

@@ -0,0 +1,40 @@
+-- =============================================================
+-- View: analytics.auth_activities
+-- Looker source alias: ds49  |  Charts: 1
+-- =============================================================
+-- DESCRIPTION
+--   Tracks authentication events (login, logout, SSO, password
+--   reset, etc.) from Supabase's internal audit log.
+--   Useful for monitoring sign-in patterns and detecting anomalies.
+--
+-- SOURCE TABLES
+--   auth.audit_log_entries  — Supabase internal auth event log
+--
+-- OUTPUT COLUMNS
+--   created_at      TIMESTAMPTZ  When the auth event occurred
+--   actor_id        TEXT         User ID who triggered the event
+--   actor_via_sso   TEXT         Whether the action was via SSO ('true'/'false')
+--   action          TEXT         Event type (e.g. 'login', 'logout', 'token_refreshed')
+--
+-- WINDOW
+--   Rolling 90 days from current date
+--
+-- EXAMPLE QUERIES
+--   -- Daily login counts
+--   SELECT DATE_TRUNC('day', created_at) AS day, COUNT(*) AS logins
+--   FROM analytics.auth_activities
+--   WHERE action = 'login'
+--   GROUP BY 1 ORDER BY 1;
+--
+--   -- SSO vs password login breakdown
+--   SELECT actor_via_sso, COUNT(*) FROM analytics.auth_activities
+--   WHERE action = 'login' GROUP BY 1;
+-- =============================================================
+
+SELECT
+    created_at,
+    payload->>'actor_id'      AS actor_id,
+    payload->>'actor_via_sso' AS actor_via_sso,
+    payload->>'action'        AS action
+FROM auth.audit_log_entries
+WHERE created_at >= NOW() - INTERVAL '90 days'

autogpt_platform/analytics/queries/graph_execution.sql

@@ -0,0 +1,105 @@
+-- =============================================================
+-- View: analytics.graph_execution
+-- Looker source alias: ds16  |  Charts: 21
+-- =============================================================
+-- DESCRIPTION
+--   One row per agent graph execution (last 90 days).
+--   Unpacks the JSONB stats column into individual numeric columns
+--   and normalises the executionStatus — runs that failed due to
+--   insufficient credits are reclassified as 'NO_CREDITS' for
+--   easier filtering.  Error messages are scrubbed of IDs and URLs
+--   to allow safe grouping.
+--
+-- SOURCE TABLES
+--   platform.AgentGraphExecution  — Execution records
+--   platform.AgentGraph           — Agent graph metadata (for name)
+--   platform.LibraryAgent         — To flag possibly-AI (safe-mode) agents
+--
+-- OUTPUT COLUMNS
+--   id                TEXT         Execution UUID
+--   agentGraphId      TEXT         Agent graph UUID
+--   agentGraphVersion INT          Graph version number
+--   executionStatus   TEXT         COMPLETED | FAILED | NO_CREDITS | RUNNING | QUEUED | TERMINATED
+--   createdAt         TIMESTAMPTZ  When the execution was queued
+--   updatedAt         TIMESTAMPTZ  Last status update time
+--   userId            TEXT         Owner user UUID
+--   agentGraphName    TEXT         Human-readable agent name
+--   cputime           DECIMAL      Total CPU seconds consumed
+--   walltime          DECIMAL      Total wall-clock seconds
+--   node_count        DECIMAL      Number of nodes in the graph
+--   nodes_cputime     DECIMAL      CPU time across all nodes
+--   nodes_walltime    DECIMAL      Wall time across all nodes
+--   execution_cost    DECIMAL      Credit cost of this execution
+--   correctness_score FLOAT        AI correctness score (if available)
+--   possibly_ai       BOOLEAN      True if agent has sensitive_action_safe_mode enabled
+--   groupedErrorMessage TEXT       Scrubbed error string (IDs/URLs replaced with wildcards)
+--
+-- WINDOW
+--   Rolling 90 days (createdAt > CURRENT_DATE - 90 days)
+--
+-- EXAMPLE QUERIES
+--   -- Daily execution counts by status
+--   SELECT DATE_TRUNC('day', "createdAt") AS day, "executionStatus", COUNT(*)
+--   FROM analytics.graph_execution
+--   GROUP BY 1, 2 ORDER BY 1;
+--
+--   -- Average cost per execution by agent
+--   SELECT "agentGraphName", AVG("execution_cost") AS avg_cost, COUNT(*) AS runs
+--   FROM analytics.graph_execution
+--   WHERE "executionStatus" = 'COMPLETED'
+--   GROUP BY 1 ORDER BY avg_cost DESC;
+--
+--   -- Top error messages
+--   SELECT "groupedErrorMessage", COUNT(*) AS occurrences
+--   FROM analytics.graph_execution
+--   WHERE "executionStatus" = 'FAILED'
+--   GROUP BY 1 ORDER BY 2 DESC LIMIT 20;
+-- =============================================================
+
+SELECT
+    ge."id"                                                        AS id,
+    ge."agentGraphId"                                              AS agentGraphId,
+    ge."agentGraphVersion"                                         AS agentGraphVersion,
+    CASE
+        WHEN jsonb_exists(ge."stats"::jsonb, 'error')
+         AND (
+               (ge."stats"::jsonb->>'error') ILIKE '%insufficient balance%'
+            OR (ge."stats"::jsonb->>'error') ILIKE '%you have no credits left%'
+             )
+        THEN 'NO_CREDITS'
+        ELSE CAST(ge."executionStatus" AS TEXT)
+    END                                                            AS executionStatus,
+    ge."createdAt"                                                 AS createdAt,
+    ge."updatedAt"                                                 AS updatedAt,
+    ge."userId"                                                    AS userId,
+    g."name"                                                       AS agentGraphName,
+    (ge."stats"::jsonb->>'cputime')::decimal                       AS cputime,
+    (ge."stats"::jsonb->>'walltime')::decimal                      AS walltime,
+    (ge."stats"::jsonb->>'node_count')::decimal                    AS node_count,
+    (ge."stats"::jsonb->>'nodes_cputime')::decimal                 AS nodes_cputime,
+    (ge."stats"::jsonb->>'nodes_walltime')::decimal                AS nodes_walltime,
+    (ge."stats"::jsonb->>'cost')::decimal                          AS execution_cost,
+    (ge."stats"::jsonb->>'correctness_score')::float               AS correctness_score,
+    COALESCE(la.possibly_ai, FALSE)                                AS possibly_ai,
+    REGEXP_REPLACE(
+        REGEXP_REPLACE(
+            TRIM(BOTH '"' FROM ge."stats"::jsonb->>'error'),
+            '(https?://)([A-Za-z0-9.-]+)(:[0-9]+)?(/[^\s]*)?',
+            '\1\2/...', 'gi'
+        ),
+        '[a-zA-Z0-9_:-]*\d[a-zA-Z0-9_:-]*', '*', 'g'
+    )                                                              AS groupedErrorMessage
+FROM platform."AgentGraphExecution" ge
+LEFT JOIN platform."AgentGraph" g
+       ON ge."agentGraphId" = g."id"
+      AND ge."agentGraphVersion" = g."version"
+LEFT JOIN (
+    SELECT DISTINCT ON ("userId", "agentGraphId")
+           "userId", "agentGraphId",
+           ("settings"::jsonb->>'sensitive_action_safe_mode')::boolean AS possibly_ai
+    FROM platform."LibraryAgent"
+    WHERE "isDeleted"  = FALSE
+      AND "isArchived" = FALSE
+    ORDER BY "userId", "agentGraphId", "agentGraphVersion" DESC
+) la ON la."userId" = ge."userId" AND la."agentGraphId" = ge."agentGraphId"
+WHERE ge."createdAt" > CURRENT_DATE - INTERVAL '90 days'

autogpt_platform/analytics/queries/node_block_execution.sql

@@ -0,0 +1,101 @@
+-- =============================================================
+-- View: analytics.node_block_execution
+-- Looker source alias: ds14  |  Charts: 11
+-- =============================================================
+-- DESCRIPTION
+--   One row per node (block) execution (last 90 days).
+--   Unpacks stats JSONB and joins to identify which block type
+--   was run.  For failed nodes, joins the error output and
+--   scrubs it for safe grouping.
+--
+-- SOURCE TABLES
+--   platform.AgentNodeExecution              — Node execution records
+--   platform.AgentNode                       — Node → block mapping
+--   platform.AgentBlock                      — Block name/ID
+--   platform.AgentNodeExecutionInputOutput   — Error output values
+--
+-- OUTPUT COLUMNS
+--   id                    TEXT         Node execution UUID
+--   agentGraphExecutionId TEXT         Parent graph execution UUID
+--   agentNodeId           TEXT         Node UUID within the graph
+--   executionStatus       TEXT         COMPLETED | FAILED | QUEUED | RUNNING | TERMINATED
+--   addedTime             TIMESTAMPTZ  When the node was queued
+--   queuedTime            TIMESTAMPTZ  When it entered the queue
+--   startedTime           TIMESTAMPTZ  When execution started
+--   endedTime             TIMESTAMPTZ  When execution finished
+--   inputSize             BIGINT       Input payload size in bytes
+--   outputSize            BIGINT       Output payload size in bytes
+--   walltime              NUMERIC      Wall-clock seconds for this node
+--   cputime               NUMERIC      CPU seconds for this node
+--   llmRetryCount         INT          Number of LLM retries
+--   llmCallCount          INT          Number of LLM API calls made
+--   inputTokenCount       BIGINT       LLM input tokens consumed
+--   outputTokenCount      BIGINT       LLM output tokens produced
+--   blockName             TEXT         Human-readable block name (e.g. 'OpenAIBlock')
+--   blockId               TEXT         Block UUID
+--   groupedErrorMessage   TEXT         Scrubbed error (IDs/URLs wildcarded)
+--   errorMessage          TEXT         Raw error output (only set when FAILED)
+--
+-- WINDOW
+--   Rolling 90 days (addedTime > CURRENT_DATE - 90 days)
+--
+-- EXAMPLE QUERIES
+--   -- Most-used blocks by execution count
+--   SELECT "blockName", COUNT(*) AS executions,
+--          COUNT(*) FILTER (WHERE "executionStatus"='FAILED') AS failures
+--   FROM analytics.node_block_execution
+--   GROUP BY 1 ORDER BY executions DESC LIMIT 20;
+--
+--   -- Average LLM token usage per block
+--   SELECT "blockName",
+--          AVG("inputTokenCount") AS avg_input_tokens,
+--          AVG("outputTokenCount") AS avg_output_tokens
+--   FROM analytics.node_block_execution
+--   WHERE "llmCallCount" > 0
+--   GROUP BY 1 ORDER BY avg_input_tokens DESC;
+--
+--   -- Top failure reasons
+--   SELECT "blockName", "groupedErrorMessage", COUNT(*) AS count
+--   FROM analytics.node_block_execution
+--   WHERE "executionStatus" = 'FAILED'
+--   GROUP BY 1, 2 ORDER BY count DESC LIMIT 20;
+-- =============================================================
+
+SELECT
+    ne."id"                                                            AS id,
+    ne."agentGraphExecutionId"                                         AS agentGraphExecutionId,
+    ne."agentNodeId"                                                   AS agentNodeId,
+    CAST(ne."executionStatus" AS TEXT)                                 AS executionStatus,
+    ne."addedTime"                                                     AS addedTime,
+    ne."queuedTime"                                                    AS queuedTime,
+    ne."startedTime"                                                   AS startedTime,
+    ne."endedTime"                                                     AS endedTime,
+    (ne."stats"::jsonb->>'input_size')::bigint                         AS inputSize,
+    (ne."stats"::jsonb->>'output_size')::bigint                        AS outputSize,
+    (ne."stats"::jsonb->>'walltime')::numeric                          AS walltime,
+    (ne."stats"::jsonb->>'cputime')::numeric                           AS cputime,
+    (ne."stats"::jsonb->>'llm_retry_count')::int                       AS llmRetryCount,
+    (ne."stats"::jsonb->>'llm_call_count')::int                        AS llmCallCount,
+    (ne."stats"::jsonb->>'input_token_count')::bigint                  AS inputTokenCount,
+    (ne."stats"::jsonb->>'output_token_count')::bigint                 AS outputTokenCount,
+    b."name"                                                           AS blockName,
+    b."id"                                                             AS blockId,
+    REGEXP_REPLACE(
+        REGEXP_REPLACE(
+            TRIM(BOTH '"' FROM eio."data"::text),
+            '(https?://)([A-Za-z0-9.-]+)(:[0-9]+)?(/[^\s]*)?',
+            '\1\2/...', 'gi'
+        ),
+        '[a-zA-Z0-9_:-]*\d[a-zA-Z0-9_:-]*', '*', 'g'
+    )                                                                  AS groupedErrorMessage,
+    eio."data"                                                         AS errorMessage
+FROM platform."AgentNodeExecution" ne
+LEFT JOIN platform."AgentNode" nd
+       ON ne."agentNodeId" = nd."id"
+LEFT JOIN platform."AgentBlock" b
+       ON nd."agentBlockId" = b."id"
+LEFT JOIN platform."AgentNodeExecutionInputOutput" eio
+       ON eio."referencedByOutputExecId" = ne."id"
+      AND eio."name" = 'error'
+      AND ne."executionStatus" = 'FAILED'
+WHERE ne."addedTime" > CURRENT_DATE - INTERVAL '90 days'

autogpt_platform/analytics/queries/retention_agent.sql

@@ -0,0 +1,97 @@
+-- =============================================================
+-- View: analytics.retention_agent
+-- Looker source alias: ds35  |  Charts: 2
+-- =============================================================
+-- DESCRIPTION
+--   Weekly cohort retention broken down per individual agent.
+--   Cohort = week of a user's first use of THAT specific agent.
+--   Tells you which agents keep users coming back vs. one-shot
+--   use. Only includes cohorts from the last 180 days.
+--
+-- SOURCE TABLES
+--   platform.AgentGraphExecution  — Execution records (user × agent × time)
+--   platform.AgentGraph           — Agent names
+--
+-- OUTPUT COLUMNS
+--   agent_id            TEXT   Agent graph UUID
+--   agent_label         TEXT   'AgentName [first8chars]'
+--   agent_label_n       TEXT   'AgentName [first8chars] (n=total_users)'
+--   cohort_week_start   DATE   Week users first ran this agent
+--   cohort_label        TEXT   ISO week label
+--   cohort_label_n      TEXT   ISO week label with cohort size
+--   user_lifetime_week  INT    Weeks since first use of this agent
+--   cohort_users        BIGINT Users in this cohort for this agent
+--   active_users        BIGINT Users who ran the agent again in week k
+--   retention_rate      FLOAT  active_users / cohort_users
+--   cohort_users_w0     BIGINT cohort_users only at week 0 (safe to SUM)
+--   agent_total_users   BIGINT Total users across all cohorts for this agent
+--
+-- EXAMPLE QUERIES
+--   -- Best-retained agents at week 2
+--   SELECT agent_label, AVG(retention_rate) AS w2_retention
+--   FROM analytics.retention_agent
+--   WHERE user_lifetime_week = 2 AND cohort_users >= 10
+--   GROUP BY 1 ORDER BY w2_retention DESC LIMIT 10;
+--
+--   -- Agents with most unique users
+--   SELECT DISTINCT agent_label, agent_total_users
+--   FROM analytics.retention_agent
+--   ORDER BY agent_total_users DESC LIMIT 20;
+-- =============================================================
+
+WITH params AS (SELECT 12::int AS max_weeks, (CURRENT_DATE - INTERVAL '180 days') AS cohort_start),
+events AS (
+  SELECT e."userId"::text AS user_id, e."agentGraphId" AS agent_id,
+         e."createdAt"::timestamptz AS created_at,
+         DATE_TRUNC('week', e."createdAt")::date AS week_start
+  FROM platform."AgentGraphExecution" e
+),
+first_use AS (
+  SELECT user_id, agent_id, MIN(created_at) AS first_use_at,
+         DATE_TRUNC('week', MIN(created_at))::date AS cohort_week_start
+  FROM events GROUP BY 1,2
+  HAVING MIN(created_at) >= (SELECT cohort_start FROM params)
+),
+activity_weeks AS (SELECT DISTINCT user_id, agent_id, week_start FROM events),
+user_week_age AS (
+  SELECT aw.user_id, aw.agent_id, fu.cohort_week_start,
+         ((aw.week_start - DATE_TRUNC('week',fu.first_use_at)::date)/7)::int AS user_lifetime_week
+  FROM activity_weeks aw JOIN first_use fu USING (user_id, agent_id)
+  WHERE aw.week_start >= DATE_TRUNC('week',fu.first_use_at)::date
+),
+active_counts AS (
+  SELECT agent_id, cohort_week_start, user_lifetime_week, COUNT(DISTINCT user_id) AS active_users
+  FROM user_week_age WHERE user_lifetime_week >= 0 GROUP BY 1,2,3
+),
+cohort_sizes AS (
+  SELECT agent_id, cohort_week_start, COUNT(DISTINCT user_id) AS cohort_users FROM first_use GROUP BY 1,2
+),
+cohort_caps AS (
+  SELECT cs.agent_id, cs.cohort_week_start, cs.cohort_users,
+         LEAST((SELECT max_weeks FROM params),
+               GREATEST(0,((DATE_TRUNC('week',CURRENT_DATE)::date-cs.cohort_week_start)/7)::int)) AS cap_weeks
+  FROM cohort_sizes cs
+),
+grid AS (
+  SELECT cc.agent_id, cc.cohort_week_start, gs AS user_lifetime_week, cc.cohort_users
+  FROM cohort_caps cc CROSS JOIN LATERAL generate_series(0, cc.cap_weeks) gs
+),
+agent_names AS (SELECT DISTINCT ON (g."id") g."id" AS agent_id, g."name" AS agent_name FROM platform."AgentGraph" g ORDER BY g."id", g."version" DESC),
+agent_total_users AS (SELECT agent_id, SUM(cohort_users) AS agent_total_users FROM cohort_sizes GROUP BY 1)
+SELECT
+  g.agent_id,
+  COALESCE(an.agent_name,'(unnamed)')||' ['||LEFT(g.agent_id::text,8)||']'  AS agent_label,
+  COALESCE(an.agent_name,'(unnamed)')||' ['||LEFT(g.agent_id::text,8)||'] (n='||COALESCE(atu.agent_total_users,0)||')' AS agent_label_n,
+  g.cohort_week_start,
+  TO_CHAR(g.cohort_week_start,'IYYY-"W"IW')                               AS cohort_label,
+  TO_CHAR(g.cohort_week_start,'IYYY-"W"IW')||' (n='||g.cohort_users||')'  AS cohort_label_n,
+  g.user_lifetime_week, g.cohort_users,
+  COALESCE(ac.active_users,0)                                              AS active_users,
+  COALESCE(ac.active_users,0)::float / NULLIF(g.cohort_users,0)           AS retention_rate,
+  CASE WHEN g.user_lifetime_week=0 THEN g.cohort_users ELSE 0 END         AS cohort_users_w0,
+  COALESCE(atu.agent_total_users,0)                                        AS agent_total_users
+FROM grid g
+LEFT JOIN active_counts     ac  ON ac.agent_id=g.agent_id AND ac.cohort_week_start=g.cohort_week_start AND ac.user_lifetime_week=g.user_lifetime_week
+LEFT JOIN agent_names       an  ON an.agent_id=g.agent_id
+LEFT JOIN agent_total_users atu ON atu.agent_id=g.agent_id
+ORDER BY agent_label, g.cohort_week_start, g.user_lifetime_week;

autogpt_platform/analytics/queries/retention_execution_daily.sql

@@ -0,0 +1,81 @@
+-- =============================================================
+-- View: analytics.retention_execution_daily
+-- Looker source alias: ds111  |  Charts: 1
+-- =============================================================
+-- DESCRIPTION
+--   Daily cohort retention based on agent executions.
+--   Cohort anchor = day of user's FIRST ever execution.
+--   Only includes cohorts from the last 90 days, up to day 30.
+--   Great for early engagement analysis (did users run another
+--   agent the next day?).
+--
+-- SOURCE TABLES
+--   platform.AgentGraphExecution  — Execution records
+--
+-- OUTPUT COLUMNS
+--   Same pattern as retention_login_daily.
+--   cohort_day_start = day of first execution (not first login)
+--
+-- EXAMPLE QUERIES
+--   -- Day-3 execution retention
+--   SELECT cohort_label, retention_rate_bounded AS d3_retention
+--   FROM analytics.retention_execution_daily
+--   WHERE user_lifetime_day = 3 ORDER BY cohort_day_start;
+-- =============================================================
+
+WITH params AS (SELECT 30::int AS max_days, (CURRENT_DATE - INTERVAL '90 days') AS cohort_start),
+events AS (
+  SELECT e."userId"::text AS user_id, e."createdAt"::timestamptz AS created_at,
+         DATE_TRUNC('day', e."createdAt")::date AS day_start
+  FROM platform."AgentGraphExecution" e WHERE e."userId" IS NOT NULL
+),
+first_exec AS (
+  SELECT user_id, MIN(created_at) AS first_exec_at,
+         DATE_TRUNC('day', MIN(created_at))::date AS cohort_day_start
+  FROM events GROUP BY 1
+  HAVING MIN(created_at) >= (SELECT cohort_start FROM params)
+),
+activity_days AS (SELECT DISTINCT user_id, day_start FROM events),
+user_day_age AS (
+  SELECT ad.user_id, fe.cohort_day_start,
+         (ad.day_start - DATE_TRUNC('day',fe.first_exec_at)::date)::int AS user_lifetime_day
+  FROM activity_days ad JOIN first_exec fe USING (user_id)
+  WHERE ad.day_start >= DATE_TRUNC('day',fe.first_exec_at)::date
+),
+bounded_counts AS (
+  SELECT cohort_day_start, user_lifetime_day, COUNT(DISTINCT user_id) AS active_users_bounded
+  FROM user_day_age WHERE user_lifetime_day >= 0 GROUP BY 1,2
+),
+last_active AS (
+  SELECT cohort_day_start, user_id, MAX(user_lifetime_day) AS last_active_day FROM user_day_age GROUP BY 1,2
+),
+unbounded_counts AS (
+  SELECT la.cohort_day_start, gs AS user_lifetime_day, COUNT(*) AS retained_users_unbounded
+  FROM last_active la
+  CROSS JOIN LATERAL generate_series(0, LEAST(la.last_active_day,(SELECT max_days FROM params))) gs
+  GROUP BY 1,2
+),
+cohort_sizes AS (SELECT cohort_day_start, COUNT(DISTINCT user_id) AS cohort_users FROM first_exec GROUP BY 1),
+cohort_caps AS (
+  SELECT cs.cohort_day_start, cs.cohort_users,
+         LEAST((SELECT max_days FROM params), GREATEST(0,(CURRENT_DATE-cs.cohort_day_start)::int)) AS cap_days
+  FROM cohort_sizes cs
+),
+grid AS (
+  SELECT cc.cohort_day_start, gs AS user_lifetime_day, cc.cohort_users
+  FROM cohort_caps cc CROSS JOIN LATERAL generate_series(0, cc.cap_days) gs
+)
+SELECT
+  g.cohort_day_start,
+  TO_CHAR(g.cohort_day_start,'YYYY-MM-DD')                                AS cohort_label,
+  TO_CHAR(g.cohort_day_start,'YYYY-MM-DD')||' (n='||g.cohort_users||')'   AS cohort_label_n,
+  g.user_lifetime_day, g.cohort_users,
+  COALESCE(b.active_users_bounded,0)     AS active_users_bounded,
+  COALESCE(u.retained_users_unbounded,0) AS retained_users_unbounded,
+  CASE WHEN g.cohort_users>0 THEN COALESCE(b.active_users_bounded,0)::float/g.cohort_users END    AS retention_rate_bounded,
+  CASE WHEN g.cohort_users>0 THEN COALESCE(u.retained_users_unbounded,0)::float/g.cohort_users END AS retention_rate_unbounded,
+  CASE WHEN g.user_lifetime_day=0 THEN g.cohort_users ELSE 0 END          AS cohort_users_d0
+FROM grid g
+LEFT JOIN bounded_counts   b ON b.cohort_day_start=g.cohort_day_start AND b.user_lifetime_day=g.user_lifetime_day
+LEFT JOIN unbounded_counts u ON u.cohort_day_start=g.cohort_day_start AND u.user_lifetime_day=g.user_lifetime_day
+ORDER BY g.cohort_day_start, g.user_lifetime_day;

autogpt_platform/analytics/queries/retention_execution_weekly.sql

@@ -0,0 +1,81 @@
+-- =============================================================
+-- View: analytics.retention_execution_weekly
+-- Looker source alias: ds92  |  Charts: 2
+-- =============================================================
+-- DESCRIPTION
+--   Weekly cohort retention based on agent executions.
+--   Cohort anchor = week of user's FIRST ever agent execution
+--   (not first login). Only includes cohorts from the last 180 days.
+--   Useful when you care about product engagement, not just visits.
+--
+-- SOURCE TABLES
+--   platform.AgentGraphExecution  — Execution records
+--
+-- OUTPUT COLUMNS
+--   Same pattern as retention_login_weekly.
+--   cohort_week_start = week of first execution (not first login)
+--
+-- EXAMPLE QUERIES
+--   -- Week-2 execution retention
+--   SELECT cohort_label, retention_rate_bounded
+--   FROM analytics.retention_execution_weekly
+--   WHERE user_lifetime_week = 2 ORDER BY cohort_week_start;
+-- =============================================================
+
+WITH params AS (SELECT 12::int AS max_weeks, (CURRENT_DATE - INTERVAL '180 days') AS cohort_start),
+events AS (
+  SELECT e."userId"::text AS user_id, e."createdAt"::timestamptz AS created_at,
+         DATE_TRUNC('week', e."createdAt")::date AS week_start
+  FROM platform."AgentGraphExecution" e WHERE e."userId" IS NOT NULL
+),
+first_exec AS (
+  SELECT user_id, MIN(created_at) AS first_exec_at,
+         DATE_TRUNC('week', MIN(created_at))::date AS cohort_week_start
+  FROM events GROUP BY 1
+  HAVING MIN(created_at) >= (SELECT cohort_start FROM params)
+),
+activity_weeks AS (SELECT DISTINCT user_id, week_start FROM events),
+user_week_age AS (
+  SELECT aw.user_id, fe.cohort_week_start,
+         ((aw.week_start - DATE_TRUNC('week',fe.first_exec_at)::date)/7)::int AS user_lifetime_week
+  FROM activity_weeks aw JOIN first_exec fe USING (user_id)
+  WHERE aw.week_start >= DATE_TRUNC('week',fe.first_exec_at)::date
+),
+bounded_counts AS (
+  SELECT cohort_week_start, user_lifetime_week, COUNT(DISTINCT user_id) AS active_users_bounded
+  FROM user_week_age WHERE user_lifetime_week >= 0 GROUP BY 1,2
+),
+last_active AS (
+  SELECT cohort_week_start, user_id, MAX(user_lifetime_week) AS last_active_week FROM user_week_age GROUP BY 1,2
+),
+unbounded_counts AS (
+  SELECT la.cohort_week_start, gs AS user_lifetime_week, COUNT(*) AS retained_users_unbounded
+  FROM last_active la
+  CROSS JOIN LATERAL generate_series(0, LEAST(la.last_active_week,(SELECT max_weeks FROM params))) gs
+  GROUP BY 1,2
+),
+cohort_sizes AS (SELECT cohort_week_start, COUNT(DISTINCT user_id) AS cohort_users FROM first_exec GROUP BY 1),
+cohort_caps AS (
+  SELECT cs.cohort_week_start, cs.cohort_users,
+         LEAST((SELECT max_weeks FROM params),
+               GREATEST(0,((DATE_TRUNC('week',CURRENT_DATE)::date-cs.cohort_week_start)/7)::int)) AS cap_weeks
+  FROM cohort_sizes cs
+),
+grid AS (
+  SELECT cc.cohort_week_start, gs AS user_lifetime_week, cc.cohort_users
+  FROM cohort_caps cc CROSS JOIN LATERAL generate_series(0, cc.cap_weeks) gs
+)
+SELECT
+  g.cohort_week_start,
+  TO_CHAR(g.cohort_week_start,'IYYY-"W"IW')                               AS cohort_label,
+  TO_CHAR(g.cohort_week_start,'IYYY-"W"IW')||' (n='||g.cohort_users||')'  AS cohort_label_n,
+  g.user_lifetime_week, g.cohort_users,
+  COALESCE(b.active_users_bounded,0)     AS active_users_bounded,
+  COALESCE(u.retained_users_unbounded,0) AS retained_users_unbounded,
+  CASE WHEN g.cohort_users>0 THEN COALESCE(b.active_users_bounded,0)::float/g.cohort_users END    AS retention_rate_bounded,
+  CASE WHEN g.cohort_users>0 THEN COALESCE(u.retained_users_unbounded,0)::float/g.cohort_users END AS retention_rate_unbounded,
+  CASE WHEN g.user_lifetime_week=0 THEN g.cohort_users ELSE 0 END         AS cohort_users_w0
+FROM grid g
+LEFT JOIN bounded_counts   b ON b.cohort_week_start=g.cohort_week_start AND b.user_lifetime_week=g.user_lifetime_week
+LEFT JOIN unbounded_counts u ON u.cohort_week_start=g.cohort_week_start AND u.user_lifetime_week=g.user_lifetime_week
+ORDER BY g.cohort_week_start, g.user_lifetime_week;

autogpt_platform/analytics/queries/retention_login_daily.sql

@@ -0,0 +1,94 @@
+-- =============================================================
+-- View: analytics.retention_login_daily
+-- Looker source alias: ds112  |  Charts: 1
+-- =============================================================
+-- DESCRIPTION
+--   Daily cohort retention based on login sessions.
+--   Same logic as retention_login_weekly but at day granularity,
+--   showing up to day 30 for cohorts from the last 90 days.
+--   Useful for analysing early activation (days 1-7) in detail.
+--
+-- SOURCE TABLES
+--   auth.sessions  — Login session records
+--
+-- OUTPUT COLUMNS (same pattern as retention_login_weekly)
+--   cohort_day_start          DATE     First day the cohort logged in
+--   cohort_label              TEXT     Date string (e.g. '2025-03-01')
+--   cohort_label_n            TEXT     Date + cohort size (e.g. '2025-03-01 (n=12)')
+--   user_lifetime_day         INT      Days since first login (0 = signup day)
+--   cohort_users              BIGINT   Total users in cohort
+--   active_users_bounded      BIGINT   Users active on exactly day k
+--   retained_users_unbounded  BIGINT   Users active any time on/after day k
+--   retention_rate_bounded    FLOAT    bounded / cohort_users
+--   retention_rate_unbounded  FLOAT    unbounded / cohort_users
+--   cohort_users_d0           BIGINT   cohort_users only at day 0, else 0 (safe to SUM)
+--
+-- EXAMPLE QUERIES
+--   -- Day-1 retention rate (came back next day)
+--   SELECT cohort_label, retention_rate_bounded AS d1_retention
+--   FROM analytics.retention_login_daily
+--   WHERE user_lifetime_day = 1 ORDER BY cohort_day_start;
+--
+--   -- Average retention curve across all cohorts
+--   SELECT user_lifetime_day,
+--          SUM(active_users_bounded)::float / NULLIF(SUM(cohort_users_d0), 0) AS avg_retention
+--   FROM analytics.retention_login_daily
+--   GROUP BY 1 ORDER BY 1;
+-- =============================================================
+
+WITH params AS (SELECT 30::int AS max_days, (CURRENT_DATE - INTERVAL '90 days')::date AS cohort_start),
+events AS (
+  SELECT s.user_id::text AS user_id, s.created_at::timestamptz AS created_at,
+         DATE_TRUNC('day', s.created_at)::date AS day_start
+  FROM auth.sessions s WHERE s.user_id IS NOT NULL
+),
+first_login AS (
+  SELECT user_id, MIN(created_at) AS first_login_time,
+         DATE_TRUNC('day', MIN(created_at))::date AS cohort_day_start
+  FROM events GROUP BY 1
+  HAVING MIN(created_at) >= (SELECT cohort_start FROM params)
+),
+activity_days AS (SELECT DISTINCT user_id, day_start FROM events),
+user_day_age AS (
+  SELECT ad.user_id, fl.cohort_day_start,
+         (ad.day_start - DATE_TRUNC('day', fl.first_login_time)::date)::int AS user_lifetime_day
+  FROM activity_days ad JOIN first_login fl USING (user_id)
+  WHERE ad.day_start >= DATE_TRUNC('day', fl.first_login_time)::date
+),
+bounded_counts AS (
+  SELECT cohort_day_start, user_lifetime_day, COUNT(DISTINCT user_id) AS active_users_bounded
+  FROM user_day_age WHERE user_lifetime_day >= 0 GROUP BY 1,2
+),
+last_active AS (
+  SELECT cohort_day_start, user_id, MAX(user_lifetime_day) AS last_active_day FROM user_day_age GROUP BY 1,2
+),
+unbounded_counts AS (
+  SELECT la.cohort_day_start, gs AS user_lifetime_day, COUNT(*) AS retained_users_unbounded
+  FROM last_active la
+  CROSS JOIN LATERAL generate_series(0, LEAST(la.last_active_day,(SELECT max_days FROM params))) gs
+  GROUP BY 1,2
+),
+cohort_sizes AS (SELECT cohort_day_start, COUNT(DISTINCT user_id) AS cohort_users FROM first_login GROUP BY 1),
+cohort_caps AS (
+  SELECT cs.cohort_day_start, cs.cohort_users,
+         LEAST((SELECT max_days FROM params), GREATEST(0,(CURRENT_DATE-cs.cohort_day_start)::int)) AS cap_days
+  FROM cohort_sizes cs
+),
+grid AS (
+  SELECT cc.cohort_day_start, gs AS user_lifetime_day, cc.cohort_users
+  FROM cohort_caps cc CROSS JOIN LATERAL generate_series(0, cc.cap_days) gs
+)
+SELECT
+  g.cohort_day_start,
+  TO_CHAR(g.cohort_day_start,'YYYY-MM-DD')                                  AS cohort_label,
+  TO_CHAR(g.cohort_day_start,'YYYY-MM-DD')||' (n='||g.cohort_users||')'     AS cohort_label_n,
+  g.user_lifetime_day, g.cohort_users,
+  COALESCE(b.active_users_bounded,0)     AS active_users_bounded,
+  COALESCE(u.retained_users_unbounded,0) AS retained_users_unbounded,
+  CASE WHEN g.cohort_users>0 THEN COALESCE(b.active_users_bounded,0)::float/g.cohort_users END    AS retention_rate_bounded,
+  CASE WHEN g.cohort_users>0 THEN COALESCE(u.retained_users_unbounded,0)::float/g.cohort_users END AS retention_rate_unbounded,
+  CASE WHEN g.user_lifetime_day=0 THEN g.cohort_users ELSE 0 END            AS cohort_users_d0
+FROM grid g
+LEFT JOIN bounded_counts   b ON b.cohort_day_start=g.cohort_day_start AND b.user_lifetime_day=g.user_lifetime_day
+LEFT JOIN unbounded_counts u ON u.cohort_day_start=g.cohort_day_start AND u.user_lifetime_day=g.user_lifetime_day
+ORDER BY g.cohort_day_start, g.user_lifetime_day;

autogpt_platform/analytics/queries/retention_login_onboarded_weekly.sql

@@ -0,0 +1,96 @@
+-- =============================================================
+-- View: analytics.retention_login_onboarded_weekly
+-- Looker source alias: ds101  |  Charts: 2
+-- =============================================================
+-- DESCRIPTION
+--   Weekly cohort retention from login sessions, restricted to
+--   users who "onboarded" — defined as running at least one
+--   agent within 365 days of their first login.
+--   Filters out users who signed up but never activated,
+--   giving a cleaner view of engaged-user retention.
+--
+-- SOURCE TABLES
+--   auth.sessions                  — Login session records
+--   platform.AgentGraphExecution   — Used to identify onboarders
+--
+-- OUTPUT COLUMNS
+--   Same as retention_login_weekly (cohort_week_start, user_lifetime_week,
+--   retention_rate_bounded, retention_rate_unbounded, etc.)
+--   Only difference: cohort is filtered to onboarded users only.
+--
+-- EXAMPLE QUERIES
+--   -- Compare week-4 retention: all users vs onboarded only
+--   SELECT 'all_users' AS segment, AVG(retention_rate_bounded) AS w4_retention
+--   FROM analytics.retention_login_weekly WHERE user_lifetime_week = 4
+--   UNION ALL
+--   SELECT 'onboarded', AVG(retention_rate_bounded)
+--   FROM analytics.retention_login_onboarded_weekly WHERE user_lifetime_week = 4;
+-- =============================================================
+
+WITH params AS (SELECT 12::int AS max_weeks, 365::int AS onboarding_window_days),
+events AS (
+  SELECT s.user_id::text AS user_id, s.created_at::timestamptz AS created_at,
+         DATE_TRUNC('week', s.created_at)::date AS week_start
+  FROM auth.sessions s WHERE s.user_id IS NOT NULL
+),
+first_login_all AS (
+  SELECT user_id, MIN(created_at) AS first_login_time,
+         DATE_TRUNC('week', MIN(created_at))::date AS cohort_week_start
+  FROM events GROUP BY 1
+),
+onboarders AS (
+  SELECT fl.user_id FROM first_login_all fl
+  WHERE EXISTS (
+    SELECT 1 FROM platform."AgentGraphExecution" e
+    WHERE e."userId"::text = fl.user_id
+      AND e."createdAt" >= fl.first_login_time
+      AND e."createdAt" < fl.first_login_time
+          + make_interval(days => (SELECT onboarding_window_days FROM params))
+  )
+),
+first_login AS (SELECT * FROM first_login_all WHERE user_id IN (SELECT user_id FROM onboarders)),
+activity_weeks AS (SELECT DISTINCT user_id, week_start FROM events),
+user_week_age AS (
+  SELECT aw.user_id, fl.cohort_week_start,
+         ((aw.week_start - DATE_TRUNC('week',fl.first_login_time)::date)/7)::int AS user_lifetime_week
+  FROM activity_weeks aw JOIN first_login fl USING (user_id)
+  WHERE aw.week_start >= DATE_TRUNC('week',fl.first_login_time)::date
+),
+bounded_counts AS (
+  SELECT cohort_week_start, user_lifetime_week, COUNT(DISTINCT user_id) AS active_users_bounded
+  FROM user_week_age WHERE user_lifetime_week >= 0 GROUP BY 1,2
+),
+last_active AS (
+  SELECT cohort_week_start, user_id, MAX(user_lifetime_week) AS last_active_week FROM user_week_age GROUP BY 1,2
+),
+unbounded_counts AS (
+  SELECT la.cohort_week_start, gs AS user_lifetime_week, COUNT(*) AS retained_users_unbounded
+  FROM last_active la
+  CROSS JOIN LATERAL generate_series(0, LEAST(la.last_active_week,(SELECT max_weeks FROM params))) gs
+  GROUP BY 1,2
+),
+cohort_sizes AS (SELECT cohort_week_start, COUNT(DISTINCT user_id) AS cohort_users FROM first_login GROUP BY 1),
+cohort_caps AS (
+  SELECT cs.cohort_week_start, cs.cohort_users,
+         LEAST((SELECT max_weeks FROM params),
+               GREATEST(0,((DATE_TRUNC('week',CURRENT_DATE)::date-cs.cohort_week_start)/7)::int)) AS cap_weeks
+  FROM cohort_sizes cs
+),
+grid AS (
+  SELECT cc.cohort_week_start, gs AS user_lifetime_week, cc.cohort_users
+  FROM cohort_caps cc CROSS JOIN LATERAL generate_series(0, cc.cap_weeks) gs
+)
+SELECT
+  g.cohort_week_start,
+  TO_CHAR(g.cohort_week_start,'IYYY-"W"IW')                               AS cohort_label,
+  TO_CHAR(g.cohort_week_start,'IYYY-"W"IW')||' (n='||g.cohort_users||')'  AS cohort_label_n,
+  g.user_lifetime_week, g.cohort_users,
+  COALESCE(b.active_users_bounded,0)     AS active_users_bounded,
+  COALESCE(u.retained_users_unbounded,0) AS retained_users_unbounded,
+  CASE WHEN g.cohort_users>0 THEN COALESCE(b.active_users_bounded,0)::float/g.cohort_users END    AS retention_rate_bounded,
+  CASE WHEN g.cohort_users>0 THEN COALESCE(u.retained_users_unbounded,0)::float/g.cohort_users END AS retention_rate_unbounded,
+  CASE WHEN g.user_lifetime_week=0 THEN g.cohort_users ELSE 0 END         AS cohort_users_w0
+FROM grid g
+LEFT JOIN bounded_counts   b ON b.cohort_week_start=g.cohort_week_start AND b.user_lifetime_week=g.user_lifetime_week
+LEFT JOIN unbounded_counts u ON u.cohort_week_start=g.cohort_week_start AND u.user_lifetime_week=g.user_lifetime_week
+ORDER BY g.cohort_week_start, g.user_lifetime_week;

autogpt_platform/analytics/queries/retention_login_weekly.sql

@@ -0,0 +1,103 @@
+-- =============================================================
+-- View: analytics.retention_login_weekly
+-- Looker source alias: ds83  |  Charts: 2
+-- =============================================================
+-- DESCRIPTION
+--   Weekly cohort retention based on login sessions.
+--   Users are grouped by the ISO week of their first ever login.
+--   For each cohort × lifetime-week combination, outputs both:
+--     - bounded rate: % active in exactly that week
+--     - unbounded rate: % who were ever active on or after that week
+--   Weeks are capped to the cohort's actual age (no future data points).
+--
+-- SOURCE TABLES
+--   auth.sessions  — Login session records
+--
+-- HOW TO READ THE OUTPUT
+--   cohort_week_start   The Monday of the week users first logged in
+--   user_lifetime_week  0 = signup week, 1 = one week later, etc.
+--   retention_rate_bounded   = active_users_bounded / cohort_users
+--   retention_rate_unbounded = retained_users_unbounded / cohort_users
+--
+-- OUTPUT COLUMNS
+--   cohort_week_start         DATE     First day of the cohort's signup week
+--   cohort_label              TEXT     ISO week label (e.g. '2025-W01')
+--   cohort_label_n            TEXT     ISO week label with cohort size (e.g. '2025-W01 (n=42)')
+--   user_lifetime_week        INT      Weeks since first login (0 = signup week)
+--   cohort_users              BIGINT   Total users in this cohort (denominator)
+--   active_users_bounded      BIGINT   Users active in exactly week k
+--   retained_users_unbounded  BIGINT   Users active any time on/after week k
+--   retention_rate_bounded    FLOAT    bounded active / cohort_users
+--   retention_rate_unbounded  FLOAT    unbounded retained / cohort_users
+--   cohort_users_w0           BIGINT   cohort_users only at week 0, else 0 (safe to SUM in pivot tables)
+--
+-- EXAMPLE QUERIES
+--   -- Week-1 retention rate per cohort
+--   SELECT cohort_label, retention_rate_bounded AS w1_retention
+--   FROM analytics.retention_login_weekly
+--   WHERE user_lifetime_week = 1
+--   ORDER BY cohort_week_start;
+--
+--   -- Overall average retention curve (all cohorts combined)
+--   SELECT user_lifetime_week,
+--          SUM(active_users_bounded)::float / NULLIF(SUM(cohort_users_w0), 0) AS avg_retention
+--   FROM analytics.retention_login_weekly
+--   GROUP BY 1 ORDER BY 1;
+-- =============================================================
+
+WITH params AS (SELECT 12::int AS max_weeks),
+events AS (
+  SELECT s.user_id::text AS user_id, s.created_at::timestamptz AS created_at,
+         DATE_TRUNC('week', s.created_at)::date AS week_start
+  FROM auth.sessions s WHERE s.user_id IS NOT NULL
+),
+first_login AS (
+  SELECT user_id, MIN(created_at) AS first_login_time,
+         DATE_TRUNC('week', MIN(created_at))::date AS cohort_week_start
+  FROM events GROUP BY 1
+),
+activity_weeks AS (SELECT DISTINCT user_id, week_start FROM events),
+user_week_age AS (
+  SELECT aw.user_id, fl.cohort_week_start,
+         ((aw.week_start - DATE_TRUNC('week', fl.first_login_time)::date) / 7)::int AS user_lifetime_week
+  FROM activity_weeks aw JOIN first_login fl USING (user_id)
+  WHERE aw.week_start >= DATE_TRUNC('week', fl.first_login_time)::date
+),
+bounded_counts AS (
+  SELECT cohort_week_start, user_lifetime_week, COUNT(DISTINCT user_id) AS active_users_bounded
+  FROM user_week_age WHERE user_lifetime_week >= 0 GROUP BY 1,2
+),
+last_active AS (
+  SELECT cohort_week_start, user_id, MAX(user_lifetime_week) AS last_active_week FROM user_week_age GROUP BY 1,2
+),
+unbounded_counts AS (
+  SELECT la.cohort_week_start, gs AS user_lifetime_week, COUNT(*) AS retained_users_unbounded
+  FROM last_active la
+  CROSS JOIN LATERAL generate_series(0, LEAST(la.last_active_week,(SELECT max_weeks FROM params))) gs
+  GROUP BY 1,2
+),
+cohort_sizes AS (SELECT cohort_week_start, COUNT(DISTINCT user_id) AS cohort_users FROM first_login GROUP BY 1),
+cohort_caps AS (
+  SELECT cs.cohort_week_start, cs.cohort_users,
+         LEAST((SELECT max_weeks FROM params),
+               GREATEST(0,((DATE_TRUNC('week',CURRENT_DATE)::date - cs.cohort_week_start)/7)::int)) AS cap_weeks
+  FROM cohort_sizes cs
+),
+grid AS (
+  SELECT cc.cohort_week_start, gs AS user_lifetime_week, cc.cohort_users
+  FROM cohort_caps cc CROSS JOIN LATERAL generate_series(0, cc.cap_weeks) gs
+)
+SELECT
+  g.cohort_week_start,
+  TO_CHAR(g.cohort_week_start,'IYYY-"W"IW')                                    AS cohort_label,
+  TO_CHAR(g.cohort_week_start,'IYYY-"W"IW')||' (n='||g.cohort_users||')'       AS cohort_label_n,
+  g.user_lifetime_week, g.cohort_users,
+  COALESCE(b.active_users_bounded,0)     AS active_users_bounded,
+  COALESCE(u.retained_users_unbounded,0) AS retained_users_unbounded,
+  CASE WHEN g.cohort_users>0 THEN COALESCE(b.active_users_bounded,0)::float/g.cohort_users END    AS retention_rate_bounded,
+  CASE WHEN g.cohort_users>0 THEN COALESCE(u.retained_users_unbounded,0)::float/g.cohort_users END AS retention_rate_unbounded,
+  CASE WHEN g.user_lifetime_week=0 THEN g.cohort_users ELSE 0 END               AS cohort_users_w0
+FROM grid g
+LEFT JOIN bounded_counts   b ON b.cohort_week_start=g.cohort_week_start AND b.user_lifetime_week=g.user_lifetime_week
+LEFT JOIN unbounded_counts u ON u.cohort_week_start=g.cohort_week_start AND u.user_lifetime_week=g.user_lifetime_week
+ORDER BY g.cohort_week_start, g.user_lifetime_week

autogpt_platform/analytics/queries/user_block_spending.sql

@@ -0,0 +1,71 @@
+-- =============================================================
+-- View: analytics.user_block_spending
+-- Looker source alias: ds6  |  Charts: 5
+-- =============================================================
+-- DESCRIPTION
+--   One row per credit transaction (last 90 days).
+--   Shows how users spend credits broken down by block type,
+--   LLM provider and model.  Joins node execution stats for
+--   token-level detail.
+--
+-- SOURCE TABLES
+--   platform.CreditTransaction   — Credit debit/credit records
+--   platform.AgentNodeExecution  — Node execution stats (for token counts)
+--
+-- OUTPUT COLUMNS
+--   transactionKey        TEXT         Unique transaction identifier
+--   userId                TEXT         User who was charged
+--   amount                DECIMAL      Credit amount (positive = credit, negative = debit)
+--   negativeAmount        DECIMAL      amount * -1 (convenience for spend charts)
+--   transactionType       TEXT         Transaction type (e.g. 'USAGE', 'REFUND', 'TOP_UP')
+--   transactionTime       TIMESTAMPTZ  When the transaction was recorded
+--   blockId               TEXT         Block UUID that triggered the spend
+--   blockName             TEXT         Human-readable block name
+--   llm_provider          TEXT         LLM provider (e.g. 'openai', 'anthropic')
+--   llm_model             TEXT         Model name (e.g. 'gpt-4o', 'claude-3-5-sonnet')
+--   node_exec_id          TEXT         Linked node execution UUID
+--   llm_call_count        INT          LLM API calls made in that execution
+--   llm_retry_count       INT          LLM retries in that execution
+--   llm_input_token_count INT          Input tokens consumed
+--   llm_output_token_count INT         Output tokens produced
+--
+-- WINDOW
+--   Rolling 90 days (createdAt > CURRENT_DATE - 90 days)
+--
+-- EXAMPLE QUERIES
+--   -- Total spend per user (last 90 days)
+--   SELECT "userId", SUM("negativeAmount") AS total_spent
+--   FROM analytics.user_block_spending
+--   WHERE "transactionType" = 'USAGE'
+--   GROUP BY 1 ORDER BY total_spent DESC;
+--
+--   -- Spend by LLM provider + model
+--   SELECT "llm_provider", "llm_model",
+--          SUM("negativeAmount") AS total_cost,
+--          SUM("llm_input_token_count") AS input_tokens,
+--          SUM("llm_output_token_count") AS output_tokens
+--   FROM analytics.user_block_spending
+--   WHERE "llm_provider" IS NOT NULL
+--   GROUP BY 1, 2 ORDER BY total_cost DESC;
+-- =============================================================
+
+SELECT
+    c."transactionKey"                                        AS transactionKey,
+    c."userId"                                                AS userId,
+    c."amount"                                                AS amount,
+    c."amount" * -1                                           AS negativeAmount,
+    c."type"                                                  AS transactionType,
+    c."createdAt"                                             AS transactionTime,
+    c.metadata->>'block_id'                                   AS blockId,
+    c.metadata->>'block'                                      AS blockName,
+    c.metadata->'input'->'credentials'->>'provider'           AS llm_provider,
+    c.metadata->'input'->>'model'                             AS llm_model,
+    c.metadata->>'node_exec_id'                               AS node_exec_id,
+    (ne."stats"->>'llm_call_count')::int                       AS llm_call_count,
+    (ne."stats"->>'llm_retry_count')::int                      AS llm_retry_count,
+    (ne."stats"->>'input_token_count')::int                    AS llm_input_token_count,
+    (ne."stats"->>'output_token_count')::int                   AS llm_output_token_count
+FROM platform."CreditTransaction" c
+LEFT JOIN platform."AgentNodeExecution" ne
+       ON (c.metadata->>'node_exec_id') = ne."id"::text
+WHERE c."createdAt" > CURRENT_DATE - INTERVAL '90 days'

autogpt_platform/analytics/queries/user_onboarding.sql

@@ -0,0 +1,45 @@
+-- =============================================================
+-- View: analytics.user_onboarding
+-- Looker source alias: ds68  |  Charts: 3
+-- =============================================================
+-- DESCRIPTION
+--   One row per user onboarding record.  Contains the user's
+--   stated usage reason, selected integrations, completed
+--   onboarding steps and optional first agent selection.
+--   Full history (no date filter) since onboarding happens
+--   once per user.
+--
+-- SOURCE TABLES
+--   platform.UserOnboarding  — Onboarding state per user
+--
+-- OUTPUT COLUMNS
+--   id                            TEXT         Onboarding record UUID
+--   createdAt                     TIMESTAMPTZ  When onboarding started
+--   updatedAt                     TIMESTAMPTZ  Last update to onboarding state
+--   usageReason                   TEXT         Why user signed up (e.g. 'work', 'personal')
+--   integrations                  TEXT[]       Array of integration names the user selected
+--   userId                        TEXT         User UUID
+--   completedSteps                TEXT[]       Array of onboarding step enums completed
+--   selectedStoreListingVersionId TEXT         First marketplace agent the user chose (if any)
+--
+-- EXAMPLE QUERIES
+--   -- Usage reason breakdown
+--   SELECT "usageReason", COUNT(*) FROM analytics.user_onboarding GROUP BY 1;
+--
+--   -- Completion rate per step
+--   SELECT step, COUNT(*) AS users_completed
+--   FROM analytics.user_onboarding
+--   CROSS JOIN LATERAL UNNEST("completedSteps") AS step
+--   GROUP BY 1 ORDER BY users_completed DESC;
+-- =============================================================
+
+SELECT
+    id,
+    "createdAt",
+    "updatedAt",
+    "usageReason",
+    integrations,
+    "userId",
+    "completedSteps",
+    "selectedStoreListingVersionId"
+FROM platform."UserOnboarding"

autogpt_platform/analytics/queries/user_onboarding_funnel.sql

@@ -0,0 +1,100 @@
+-- =============================================================
+-- View: analytics.user_onboarding_funnel
+-- Looker source alias: ds74  |  Charts: 1
+-- =============================================================
+-- DESCRIPTION
+--   Pre-aggregated onboarding funnel showing how many users
+--   completed each step and the drop-off percentage from the
+--   previous step.  One row per onboarding step (all 22 steps
+--   always present, even with 0 completions — prevents sparse
+--   gaps from making LAG compare the wrong predecessors).
+--
+-- SOURCE TABLES
+--   platform.UserOnboarding  — Onboarding records with completedSteps array
+--
+-- OUTPUT COLUMNS
+--   step             TEXT     Onboarding step enum name (e.g. 'WELCOME', 'CONGRATS')
+--   step_order       INT      Numeric position in the funnel (1=first, 22=last)
+--   users_completed  BIGINT   Distinct users who completed this step
+--   pct_from_prev    NUMERIC  % of users from the previous step who reached this one
+--
+-- STEP ORDER
+--   1  WELCOME               9  MARKETPLACE_VISIT     17  SCHEDULE_AGENT
+--   2  USAGE_REASON         10  MARKETPLACE_ADD_AGENT  18  RUN_AGENTS
+--   3  INTEGRATIONS         11  MARKETPLACE_RUN_AGENT  19  RUN_3_DAYS
+--   4  AGENT_CHOICE         12  BUILDER_OPEN           20  TRIGGER_WEBHOOK
+--   5  AGENT_NEW_RUN        13  BUILDER_SAVE_AGENT     21  RUN_14_DAYS
+--   6  AGENT_INPUT          14  BUILDER_RUN_AGENT      22  RUN_AGENTS_100
+--   7  CONGRATS             15  VISIT_COPILOT
+--   8  GET_RESULTS          16  RE_RUN_AGENT
+--
+-- WINDOW
+--   Users who started onboarding in the last 90 days
+--
+-- EXAMPLE QUERIES
+--   -- Full funnel
+--   SELECT * FROM analytics.user_onboarding_funnel ORDER BY step_order;
+--
+--   -- Biggest drop-off point
+--   SELECT step, pct_from_prev FROM analytics.user_onboarding_funnel
+--   ORDER BY pct_from_prev ASC LIMIT 3;
+-- =============================================================
+
+WITH all_steps AS (
+  -- Complete ordered grid of all 22 steps so zero-completion steps
+  -- are always present, keeping LAG comparisons correct.
+  SELECT step_name, step_order
+  FROM (VALUES
+    ('WELCOME',               1),
+    ('USAGE_REASON',          2),
+    ('INTEGRATIONS',          3),
+    ('AGENT_CHOICE',          4),
+    ('AGENT_NEW_RUN',         5),
+    ('AGENT_INPUT',           6),
+    ('CONGRATS',              7),
+    ('GET_RESULTS',           8),
+    ('MARKETPLACE_VISIT',     9),
+    ('MARKETPLACE_ADD_AGENT', 10),
+    ('MARKETPLACE_RUN_AGENT', 11),
+    ('BUILDER_OPEN',          12),
+    ('BUILDER_SAVE_AGENT',    13),
+    ('BUILDER_RUN_AGENT',     14),
+    ('VISIT_COPILOT',         15),
+    ('RE_RUN_AGENT',          16),
+    ('SCHEDULE_AGENT',        17),
+    ('RUN_AGENTS',            18),
+    ('RUN_3_DAYS',            19),
+    ('TRIGGER_WEBHOOK',       20),
+    ('RUN_14_DAYS',           21),
+    ('RUN_AGENTS_100',        22)
+  ) AS t(step_name, step_order)
+),
+raw AS (
+  SELECT
+      u."userId",
+      step_txt::text AS step
+  FROM platform."UserOnboarding" u
+  CROSS JOIN LATERAL UNNEST(u."completedSteps") AS step_txt
+  WHERE u."createdAt" >= CURRENT_DATE - INTERVAL '90 days'
+),
+step_counts AS (
+  SELECT step, COUNT(DISTINCT "userId") AS users_completed
+  FROM raw GROUP BY step
+),
+funnel AS (
+  SELECT
+      a.step_name                          AS step,
+      a.step_order,
+      COALESCE(sc.users_completed, 0)      AS users_completed,
+      ROUND(
+        100.0 * COALESCE(sc.users_completed, 0)
+        / NULLIF(
+            LAG(COALESCE(sc.users_completed, 0)) OVER (ORDER BY a.step_order),
+            0
+          ),
+        2
+      )                                    AS pct_from_prev
+  FROM all_steps a
+  LEFT JOIN step_counts sc ON sc.step = a.step_name
+)
+SELECT * FROM funnel ORDER BY step_order

autogpt_platform/analytics/queries/user_onboarding_integration.sql

@@ -0,0 +1,41 @@
+-- =============================================================
+-- View: analytics.user_onboarding_integration
+-- Looker source alias: ds75  |  Charts: 1
+-- =============================================================
+-- DESCRIPTION
+--   Pre-aggregated count of users who selected each integration
+--   during onboarding.  One row per integration type, sorted
+--   by popularity.
+--
+-- SOURCE TABLES
+--   platform.UserOnboarding  — integrations array column
+--
+-- OUTPUT COLUMNS
+--   integration            TEXT    Integration name (e.g. 'github', 'slack', 'notion')
+--   users_with_integration BIGINT  Distinct users who selected this integration
+--
+-- WINDOW
+--   Users who started onboarding in the last 90 days
+--
+-- EXAMPLE QUERIES
+--   -- Full integration popularity ranking
+--   SELECT * FROM analytics.user_onboarding_integration;
+--
+--   -- Top 5 integrations
+--   SELECT * FROM analytics.user_onboarding_integration LIMIT 5;
+-- =============================================================
+
+WITH exploded AS (
+  SELECT
+      u."userId" AS user_id,
+      UNNEST(u."integrations") AS integration
+  FROM platform."UserOnboarding" u
+  WHERE u."createdAt" >= CURRENT_DATE - INTERVAL '90 days'
+)
+SELECT
+    integration,
+    COUNT(DISTINCT user_id) AS users_with_integration
+FROM exploded
+WHERE integration IS NOT NULL AND integration <> ''
+GROUP BY integration
+ORDER BY users_with_integration DESC

autogpt_platform/analytics/queries/users_activities.sql

@@ -0,0 +1,145 @@
+-- =============================================================
+-- View: analytics.users_activities
+-- Looker source alias: ds56  |  Charts: 5
+-- =============================================================
+-- DESCRIPTION
+--   One row per user with lifetime activity summary.
+--   Joins login sessions with agent graphs, executions and
+--   node-level runs to give a full picture of how engaged
+--   each user is.  Includes a convenience flag for 7-day
+--   activation (did the user return at least 7 days after
+--   their first login?).
+--
+-- SOURCE TABLES
+--   auth.sessions                    — Login/session records
+--   platform.AgentGraph              — Graphs (agents) built by the user
+--   platform.AgentGraphExecution     — Agent run history
+--   platform.AgentNodeExecution      — Individual block execution history
+--
+-- PERFORMANCE NOTE
+--   Each CTE aggregates its own table independently by userId.
+--   This avoids the fan-out that occurs when driving every join
+--   from user_logins across the two largest tables
+--   (AgentGraphExecution and AgentNodeExecution).
+--
+-- OUTPUT COLUMNS
+--   user_id                   TEXT         Supabase user UUID
+--   first_login_time          TIMESTAMPTZ  First ever session created_at
+--   last_login_time           TIMESTAMPTZ  Most recent session created_at
+--   last_visit_time           TIMESTAMPTZ  Max of last refresh or login
+--   last_agent_save_time      TIMESTAMPTZ  Last time user saved an agent graph
+--   agent_count               BIGINT       Number of distinct active graphs built (0 if none)
+--   first_agent_run_time      TIMESTAMPTZ  First ever graph execution
+--   last_agent_run_time       TIMESTAMPTZ  Most recent graph execution
+--   unique_agent_runs         BIGINT       Distinct agent graphs ever run (0 if none)
+--   agent_runs                BIGINT       Total graph execution count (0 if none)
+--   node_execution_count      BIGINT       Total node executions across all runs
+--   node_execution_failed     BIGINT       Node executions with FAILED status
+--   node_execution_completed  BIGINT       Node executions with COMPLETED status
+--   node_execution_terminated BIGINT       Node executions with TERMINATED status
+--   node_execution_queued     BIGINT       Node executions with QUEUED status
+--   node_execution_running    BIGINT       Node executions with RUNNING status
+--   is_active_after_7d        INT          1=returned after day 7, 0=did not, NULL=too early to tell
+--   node_execution_incomplete BIGINT       Node executions with INCOMPLETE status
+--   node_execution_review     BIGINT       Node executions with REVIEW status
+--
+-- EXAMPLE QUERIES
+--   -- Users who ran at least one agent and returned after 7 days
+--   SELECT COUNT(*) FROM analytics.users_activities
+--   WHERE agent_runs > 0 AND is_active_after_7d = 1;
+--
+--   -- Top 10 most active users by agent runs
+--   SELECT user_id, agent_runs, node_execution_count
+--   FROM analytics.users_activities
+--   ORDER BY agent_runs DESC LIMIT 10;
+--
+--   -- 7-day activation rate
+--   SELECT
+--     SUM(CASE WHEN is_active_after_7d = 1 THEN 1 ELSE 0 END)::float
+--     / NULLIF(COUNT(CASE WHEN is_active_after_7d IS NOT NULL THEN 1 END), 0)
+--     AS activation_rate
+--   FROM analytics.users_activities;
+-- =============================================================
+
+WITH user_logins AS (
+  SELECT
+    user_id::text                                    AS user_id,
+    MIN(created_at)                                  AS first_login_time,
+    MAX(created_at)                                  AS last_login_time,
+    GREATEST(
+      MAX(refreshed_at)::timestamptz,
+      MAX(created_at)::timestamptz
+    )                                                AS last_visit_time
+  FROM auth.sessions
+  GROUP BY user_id
+),
+user_agents AS (
+  -- Aggregate AgentGraph directly by userId (no fan-out from user_logins)
+  SELECT
+    "userId"::text                AS user_id,
+    MAX("updatedAt")              AS last_agent_save_time,
+    COUNT(DISTINCT "id")          AS agent_count
+  FROM platform."AgentGraph"
+  WHERE "isActive"
+  GROUP BY "userId"
+),
+user_graph_runs AS (
+  -- Aggregate AgentGraphExecution directly by userId
+  SELECT
+    "userId"::text                        AS user_id,
+    MIN("createdAt")                      AS first_agent_run_time,
+    MAX("createdAt")                      AS last_agent_run_time,
+    COUNT(DISTINCT "agentGraphId")        AS unique_agent_runs,
+    COUNT("id")                           AS agent_runs
+  FROM platform."AgentGraphExecution"
+  GROUP BY "userId"
+),
+user_node_runs AS (
+  -- Aggregate AgentNodeExecution directly; resolve userId via a
+  -- single join to AgentGraphExecution instead of fanning out from
+  -- user_logins through both large tables.
+  SELECT
+    g."userId"::text                                                   AS user_id,
+    COUNT(*)                                                           AS node_execution_count,
+    COUNT(*) FILTER (WHERE n."executionStatus" = 'FAILED')             AS node_execution_failed,
+    COUNT(*) FILTER (WHERE n."executionStatus" = 'COMPLETED')          AS node_execution_completed,
+    COUNT(*) FILTER (WHERE n."executionStatus" = 'TERMINATED')         AS node_execution_terminated,
+    COUNT(*) FILTER (WHERE n."executionStatus" = 'QUEUED')             AS node_execution_queued,
+    COUNT(*) FILTER (WHERE n."executionStatus" = 'RUNNING')            AS node_execution_running,
+    COUNT(*) FILTER (WHERE n."executionStatus" = 'INCOMPLETE')         AS node_execution_incomplete,
+    COUNT(*) FILTER (WHERE n."executionStatus" = 'REVIEW')             AS node_execution_review
+  FROM platform."AgentNodeExecution" n
+  JOIN platform."AgentGraphExecution" g
+    ON g."id" = n."agentGraphExecutionId"
+  GROUP BY g."userId"
+)
+SELECT
+  ul.user_id,
+  ul.first_login_time,
+  ul.last_login_time,
+  ul.last_visit_time,
+  ua.last_agent_save_time,
+  COALESCE(ua.agent_count, 0)             AS agent_count,
+  gr.first_agent_run_time,
+  gr.last_agent_run_time,
+  COALESCE(gr.unique_agent_runs, 0)       AS unique_agent_runs,
+  COALESCE(gr.agent_runs, 0)              AS agent_runs,
+  COALESCE(nr.node_execution_count, 0)      AS node_execution_count,
+  COALESCE(nr.node_execution_failed, 0)     AS node_execution_failed,
+  COALESCE(nr.node_execution_completed, 0)  AS node_execution_completed,
+  COALESCE(nr.node_execution_terminated, 0) AS node_execution_terminated,
+  COALESCE(nr.node_execution_queued, 0)     AS node_execution_queued,
+  COALESCE(nr.node_execution_running, 0)    AS node_execution_running,
+  CASE
+    WHEN ul.first_login_time < NOW() - INTERVAL '7 days'
+     AND ul.last_visit_time  >= ul.first_login_time + INTERVAL '7 days' THEN 1
+    WHEN ul.first_login_time < NOW() - INTERVAL '7 days'
+     AND ul.last_visit_time  <  ul.first_login_time + INTERVAL '7 days' THEN 0
+    ELSE NULL
+  END AS is_active_after_7d,
+  COALESCE(nr.node_execution_incomplete, 0) AS node_execution_incomplete,
+  COALESCE(nr.node_execution_review, 0)     AS node_execution_review
+FROM user_logins ul
+LEFT JOIN user_agents     ua ON ul.user_id = ua.user_id
+LEFT JOIN user_graph_runs gr ON ul.user_id = gr.user_id
+LEFT JOIN user_node_runs  nr ON ul.user_id = nr.user_id

autogpt_platform/backend/CLAUDE.md

@@ -58,10 +58,56 @@ poetry run pytest path/to/test.py --snapshot-update
 - **Authentication**: JWT-based with Supabase integration
 - **Security**: Cache protection middleware prevents sensitive data caching in browsers/proxies
 
+## Code Style
+
+- **Top-level imports only** — no local/inner imports (lazy imports only for heavy optional deps like `openpyxl`)
+- **No duck typing** — no `hasattr`/`getattr`/`isinstance` for type dispatch; use typed interfaces/unions/protocols
+- **Pydantic models** over dataclass/namedtuple/dict for structured data
+- **No linter suppressors** — no `# type: ignore`, `# noqa`, `# pyright: ignore`; fix the type/code
+- **List comprehensions** over manual loop-and-append
+- **Early return** — guard clauses first, avoid deep nesting
+- **f-strings vs printf syntax in log statements** — Use `%s` for deferred interpolation in `debug` statements, f-strings elsewhere for readability: `logger.debug("Processing %s items", count)`, `logger.info(f"Processing {count} items")`
+- **Sanitize error paths** — `os.path.basename()` in error messages to avoid leaking directory structure
+- **TOCTOU awareness** — avoid check-then-act patterns for file access and credit charging
+- **`Security()` vs `Depends()`** — use `Security()` for auth deps to get proper OpenAPI security spec
+- **Redis pipelines** — `transaction=True` for atomicity on multi-step operations
+- **`max(0, value)` guards** — for computed values that should never be negative
+- **SSE protocol** — `data:` lines for frontend-parsed events (must match Zod schema), `: comment` lines for heartbeats/status
+- **File length** — keep files under ~300 lines; if a file grows beyond this, split by responsibility (e.g. extract helpers, models, or a sub-module into a new file). Never keep appending to a long file.
+- **Function length** — keep functions under ~40 lines; extract named helpers when a function grows longer. Long functions are a sign of mixed concerns, not complexity.
+- **Top-down ordering** — define the main/public function or class first, then the helpers it uses below. A reader should encounter high-level logic before implementation details.
+
 ## Testing Approach
 
 - Uses pytest with snapshot testing for API responses
 - Test files are colocated with source files (`*_test.py`)
+- Mock at boundaries — mock where the symbol is **used**, not where it's **defined**
+- 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
 
@@ -157,6 +203,16 @@ yield "image_url", result_url
 3. Write tests alongside the route file
 4. Run `poetry run test` to verify
 
+## Workspace & Media Files
+
+**Read [Workspace & Media Architecture](../../docs/platform/workspace-media-architecture.md) when:**
+- Working on CoPilot file upload/download features
+- Building blocks that handle `MediaFileType` inputs/outputs
+- Modifying `WorkspaceManager` or `store_media_file()`
+- Debugging file persistence or virus scanning issues
+
+Covers: `WorkspaceManager` (persistent storage with session scoping), `store_media_file()` (media normalization pipeline), and responsibility boundaries for virus scanning and persistence.
+
 ## Security Implementation
 
 ### Cache Protection Middleware

autogpt_platform/backend/Dockerfile

@@ -50,7 +50,7 @@ RUN poetry install --no-ansi --no-root
 # Generate Prisma client
 COPY autogpt_platform/backend/schema.prisma ./
 COPY autogpt_platform/backend/backend/data/partial_types.py ./backend/data/partial_types.py
-COPY autogpt_platform/backend/gen_prisma_types_stub.py ./
+COPY autogpt_platform/backend/scripts/gen_prisma_types_stub.py ./scripts/
 RUN poetry run prisma generate && poetry run gen-prisma-stub
 
 # =============================== DB MIGRATOR =============================== #
@@ -82,7 +82,7 @@ RUN pip3 install prisma>=0.15.0 --break-system-packages
 
 COPY autogpt_platform/backend/schema.prisma ./
 COPY autogpt_platform/backend/backend/data/partial_types.py ./backend/data/partial_types.py
-COPY autogpt_platform/backend/gen_prisma_types_stub.py ./
+COPY autogpt_platform/backend/scripts/gen_prisma_types_stub.py ./scripts/
 COPY autogpt_platform/backend/migrations ./migrations
 
 # ============================== BACKEND SERVER ============================== #
@@ -121,19 +121,37 @@ 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) + 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 \
+# Install agent-browser (Copilot browser tool) + Chromium.
+# On amd64: install runtime libs + run `agent-browser install` to download
+#   Chrome for Testing (pinned version, tested with Playwright).
+# On arm64: install system chromium package — Chrome for Testing has no ARM64
+#   binary. AGENT_BROWSER_EXECUTABLE_PATH is set at runtime by the entrypoint
+#   script (below) to redirect agent-browser to the system binary.
+ARG TARGETARCH
+RUN apt-get update \
+    && if [ "$TARGETARCH" = "arm64" ]; then \
+         apt-get install -y --no-install-recommends chromium fonts-liberation; \
+       else \
+         apt-get install -y --no-install-recommends \
+           libnss3 libnspr4 libatk1.0-0 libatk-bridge2.0-0 libcups2 libdrm2 \
+           libdbus-1-3 libxkbcommon0 libatspi2.0-0t64 libxcomposite1 libxdamage1 \
+           libxfixes3 libxrandr2 libgbm1 libasound2t64 libpango-1.0-0 libcairo2 \
+           libx11-6 libx11-xcb1 libxcb1 libxext6 libglib2.0-0t64 \
+           fonts-liberation libfontconfig1; \
+       fi \
     && rm -rf /var/lib/apt/lists/* \
     && npm install -g agent-browser \
-    && agent-browser install \
+    && ([ "$TARGETARCH" = "arm64" ] || agent-browser install) \
     && rm -rf /tmp/* /root/.npm
 
+# On arm64 the system chromium is at /usr/bin/chromium; set
+# AGENT_BROWSER_EXECUTABLE_PATH so agent-browser's daemon uses it instead of
+# Chrome for Testing (which has no ARM64 binary). On amd64 the variable is left
+# unset so agent-browser uses the Chrome for Testing binary it downloaded above.
+RUN printf '#!/bin/sh\n[ -x /usr/bin/chromium ] && export AGENT_BROWSER_EXECUTABLE_PATH=/usr/bin/chromium\nexec "$@"\n' \
+    > /usr/local/bin/entrypoint.sh \
+    && chmod +x /usr/local/bin/entrypoint.sh
+
 WORKDIR /app/autogpt_platform/backend
 
 # Copy only the .venv from builder (not the entire /app directory)
@@ -155,4 +173,5 @@ RUN POETRY_VIRTUALENVS_CREATE=true POETRY_VIRTUALENVS_IN_PROJECT=true \
 
 ENV PORT=8000
 
+ENTRYPOINT ["/usr/local/bin/entrypoint.sh"]
 CMD ["rest"]

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

@@ -1,7 +1,7 @@
 import logging
 import urllib.parse
 from collections import defaultdict
-from typing import Annotated, Any, Literal, Optional, Sequence
+from typing import Annotated, Any, Optional, Sequence
 
 from fastapi import APIRouter, Body, HTTPException, Security
 from prisma.enums import AgentExecutionStatus, APIKeyPermission
@@ -9,9 +9,10 @@ from pydantic import BaseModel, Field
 from typing_extensions import TypedDict
 
 import backend.api.features.store.cache as store_cache
+import backend.api.features.store.db as store_db
 import backend.api.features.store.model as store_model
 import backend.blocks
-from backend.api.external.middleware import require_permission
+from backend.api.external.middleware import require_auth, require_permission
 from backend.data import execution as execution_db
 from backend.data import graph as graph_db
 from backend.data import user as user_db
@@ -230,13 +231,13 @@ async def get_graph_execution_results(
 @v1_router.get(
     path="/store/agents",
     tags=["store"],
-    dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
+    dependencies=[Security(require_auth)],  # data is public; auth required as anti-DDoS
     response_model=store_model.StoreAgentsResponse,
 )
 async def get_store_agents(
     featured: bool = False,
     creator: str | None = None,
-    sorted_by: Literal["rating", "runs", "name", "updated_at"] | None = None,
+    sorted_by: store_db.StoreAgentsSortOptions | None = None,
     search_query: str | None = None,
     category: str | None = None,
     page: int = 1,
@@ -278,7 +279,7 @@ async def get_store_agents(
 @v1_router.get(
     path="/store/agents/{username}/{agent_name}",
     tags=["store"],
-    dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
+    dependencies=[Security(require_auth)],  # data is public; auth required as anti-DDoS
     response_model=store_model.StoreAgentDetails,
 )
 async def get_store_agent(
@@ -306,13 +307,13 @@ async def get_store_agent(
 @v1_router.get(
     path="/store/creators",
     tags=["store"],
-    dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
+    dependencies=[Security(require_auth)],  # data is public; auth required as anti-DDoS
     response_model=store_model.CreatorsResponse,
 )
 async def get_store_creators(
     featured: bool = False,
     search_query: str | None = None,
-    sorted_by: Literal["agent_rating", "agent_runs", "num_agents"] | None = None,
+    sorted_by: store_db.StoreCreatorsSortOptions | None = None,
     page: int = 1,
     page_size: int = 20,
 ) -> store_model.CreatorsResponse:
@@ -348,7 +349,7 @@ async def get_store_creators(
 @v1_router.get(
     path="/store/creators/{username}",
     tags=["store"],
-    dependencies=[Security(require_permission(APIKeyPermission.READ_STORE))],
+    dependencies=[Security(require_auth)],  # data is public; auth required as anti-DDoS
     response_model=store_model.CreatorDetails,
 )
 async def get_store_creator(

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

@@ -24,14 +24,13 @@ router = fastapi.APIRouter(
 @router.get(
     "/listings",
     summary="Get Admin Listings History",
-    response_model=store_model.StoreListingsWithVersionsResponse,
 )
 async def get_admin_listings_with_versions(
     status: typing.Optional[prisma.enums.SubmissionStatus] = None,
     search: typing.Optional[str] = None,
     page: int = 1,
     page_size: int = 20,
-):
+) -> store_model.StoreListingsWithVersionsAdminViewResponse:
     """
     Get store listings with their version history for admins.
 
@@ -45,36 +44,26 @@ async def get_admin_listings_with_versions(
         page_size: Number of items per page
 
     Returns:
-        StoreListingsWithVersionsResponse with listings and their versions
+        Paginated listings with their versions
     """
-    try:
-        listings = await store_db.get_admin_listings_with_versions(
-            status=status,
-            search_query=search,
-            page=page,
-            page_size=page_size,
-        )
-        return listings
-    except Exception as e:
-        logger.exception("Error getting admin listings with versions: %s", e)
-        return fastapi.responses.JSONResponse(
-            status_code=500,
-            content={
-                "detail": "An error occurred while retrieving listings with versions"
-            },
-        )
+    listings = await store_db.get_admin_listings_with_versions(
+        status=status,
+        search_query=search,
+        page=page,
+        page_size=page_size,
+    )
+    return listings
 
 
 @router.post(
     "/submissions/{store_listing_version_id}/review",
     summary="Review Store Submission",
-    response_model=store_model.StoreSubmission,
 )
 async def review_submission(
     store_listing_version_id: str,
     request: store_model.ReviewSubmissionRequest,
     user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-):
+) -> store_model.StoreSubmissionAdminView:
     """
     Review a store listing submission.
 
@@ -84,31 +73,24 @@ async def review_submission(
         user_id: Authenticated admin user performing the review
 
     Returns:
-        StoreSubmission with updated review information
+        StoreSubmissionAdminView with updated review information
     """
-    try:
-        already_approved = await store_db.check_submission_already_approved(
-            store_listing_version_id=store_listing_version_id,
-        )
-        submission = await store_db.review_store_submission(
-            store_listing_version_id=store_listing_version_id,
-            is_approved=request.is_approved,
-            external_comments=request.comments,
-            internal_comments=request.internal_comments or "",
-            reviewer_id=user_id,
-        )
+    already_approved = await store_db.check_submission_already_approved(
+        store_listing_version_id=store_listing_version_id,
+    )
+    submission = await store_db.review_store_submission(
+        store_listing_version_id=store_listing_version_id,
+        is_approved=request.is_approved,
+        external_comments=request.comments,
+        internal_comments=request.internal_comments or "",
+        reviewer_id=user_id,
+    )
 
-        state_changed = already_approved != request.is_approved
-        # Clear caches when the request is approved as it updates what is shown on the store
-        if state_changed:
-            store_cache.clear_all_caches()
-        return submission
-    except Exception as e:
-        logger.exception("Error reviewing submission: %s", e)
-        return fastapi.responses.JSONResponse(
-            status_code=500,
-            content={"detail": "An error occurred while reviewing the submission"},
-        )
+    state_changed = already_approved != request.is_approved
+    # Clear caches whenever approval state changes, since store visibility can change
+    if state_changed:
+        store_cache.clear_all_caches()
+    return submission
 
 
 @router.get(

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

@@ -4,14 +4,12 @@ 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,
@@ -24,6 +22,7 @@ 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,
@@ -271,7 +270,7 @@ 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 _hybrid_search_blocks(
+        block_results, block_total, integration_total = await _text_search_blocks(
             query=search_query,
             include_blocks=include_blocks,
             include_integrations=include_integrations,
@@ -383,117 +382,75 @@ def _collect_block_results(
     return results, block_count, integration_count
 
 
-async def _hybrid_search_blocks(
+async def _text_search_blocks(
     *,
     query: str,
     include_blocks: bool,
     include_integrations: bool,
 ) -> tuple[list[_ScoredItem], int, int]:
     """
-    Search blocks using hybrid search with builder-specific filtering.
+    Search blocks using in-memory text matching over the block registry.
 
-    Uses unified_hybrid_search for semantic + lexical search, then applies
-    post-filtering for block/integration types and scoring adjustments.
+    All blocks are already loaded in memory, so this is fast and reliable
+    regardless of whether OpenAI embeddings are available.
 
     Scoring:
-        - Base: hybrid relevance score (0-1) scaled to 0-100, plus BLOCK_SCORE_BOOST
+        - Base: text relevance via _score_primary_fields, 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, block_count, integration_count
+        return results, 0, 0
 
     normalized_query = query.strip().lower()
 
-    # 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,
+    all_results, _, _ = _collect_block_results(
+        include_blocks=include_blocks,
+        include_integrations=include_integrations,
     )
 
-    # Load all blocks for getting BlockInfo
     all_blocks = load_all_blocks()
 
-    for result in search_results:
-        block_id = result["content_id"]
+    for item in all_results:
+        block_info = item.item
+        assert isinstance(block_info, BlockInfo)
+        name = split_camelcase(block_info.name).lower()
 
-        # Skip excluded blocks
-        if block_id in EXCLUDED_BLOCK_IDS:
-            continue
+        # 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()
 
-        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
+        score = _score_primary_fields(name, description, normalized_query)
 
         # Add LLM model match bonus
-        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 block_cls is not None and _matches_llm_model(
+            block_cls().input_schema, normalized_query
+        ):
+            score += 20
 
-        # 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,
+        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,
+                )
             )
-        )
 
+    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

@@ -8,10 +8,10 @@ from typing import Annotated
 from uuid import uuid4
 
 from autogpt_libs import auth
-from fastapi import APIRouter, Depends, HTTPException, Query, Response, Security
+from fastapi import APIRouter, HTTPException, Query, Response, Security
 from fastapi.responses import StreamingResponse
 from prisma.models import UserWorkspaceFile
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, Field, field_validator
 
 from backend.copilot import service as chat_service
 from backend.copilot import stream_registry
@@ -25,8 +25,16 @@ from backend.copilot.model import (
     delete_chat_session,
     get_chat_session,
     get_user_sessions,
+    update_session_title,
+)
+from backend.copilot.rate_limit import (
+    CoPilotUsageStatus,
+    RateLimitExceeded,
+    check_rate_limit,
+    get_usage_status,
 )
 from backend.copilot.response_model import StreamError, StreamFinish, StreamHeartbeat
+from backend.copilot.tools.e2b_sandbox import kill_sandbox
 from backend.copilot.tools.models import (
     AgentDetailsResponse,
     AgentOutputResponse,
@@ -51,6 +59,7 @@ from backend.copilot.tools.models import (
     UnderstandingUpdatedResponse,
 )
 from backend.copilot.tracking import track_user_message
+from backend.data.redis_client import get_redis_async
 from backend.data.workspace import get_or_create_workspace
 from backend.util.exceptions import NotFoundError
 
@@ -116,6 +125,8 @@ class SessionDetailResponse(BaseModel):
     user_id: str | None
     messages: list[dict]
     active_stream: ActiveStreamInfo | None = None  # Present if stream is still active
+    total_prompt_tokens: int = 0
+    total_completion_tokens: int = 0
 
 
 class SessionSummaryResponse(BaseModel):
@@ -125,6 +136,7 @@ class SessionSummaryResponse(BaseModel):
     created_at: str
     updated_at: str
     title: str | None = None
+    is_processing: bool
 
 
 class ListSessionsResponse(BaseModel):
@@ -141,6 +153,20 @@ class CancelSessionResponse(BaseModel):
     reason: str | None = None
 
 
+class UpdateSessionTitleRequest(BaseModel):
+    """Request model for updating a session's title."""
+
+    title: str
+
+    @field_validator("title")
+    @classmethod
+    def title_must_not_be_blank(cls, v: str) -> str:
+        stripped = v.strip()
+        if not stripped:
+            raise ValueError("Title must not be blank")
+        return stripped
+
+
 # ========== Routes ==========
 
 
@@ -169,6 +195,28 @@ async def list_sessions(
     """
     sessions, total_count = await get_user_sessions(user_id, limit, offset)
 
+    # Batch-check Redis for active stream status on each session
+    processing_set: set[str] = set()
+    if sessions:
+        try:
+            redis = await get_redis_async()
+            pipe = redis.pipeline(transaction=False)
+            for session in sessions:
+                pipe.hget(
+                    f"{config.session_meta_prefix}{session.session_id}",
+                    "status",
+                )
+            statuses = await pipe.execute()
+            processing_set = {
+                session.session_id
+                for session, st in zip(sessions, statuses)
+                if st == "running"
+            }
+        except Exception:
+            logger.warning(
+                "Failed to fetch processing status from Redis; defaulting to empty"
+            )
+
     return ListSessionsResponse(
         sessions=[
             SessionSummaryResponse(
@@ -176,6 +224,7 @@ async def list_sessions(
                 created_at=session.started_at.isoformat(),
                 updated_at=session.updated_at.isoformat(),
                 title=session.title,
+                is_processing=session.session_id in processing_set,
             )
             for session in sessions
         ],
@@ -187,7 +236,7 @@ async def list_sessions(
     "/sessions",
 )
 async def create_session(
-    user_id: Annotated[str, Depends(auth.get_user_id)],
+    user_id: Annotated[str, Security(auth.get_user_id)],
 ) -> CreateSessionResponse:
     """
     Create a new chat session.
@@ -250,12 +299,12 @@ async def delete_session(
         )
 
     # Best-effort cleanup of the E2B sandbox (if any).
-    config = ChatConfig()
-    if config.use_e2b_sandbox and config.e2b_api_key:
-        from backend.copilot.tools.e2b_sandbox import kill_sandbox
-
+    # sandbox_id is in Redis; kill_sandbox() fetches it from there.
+    e2b_cfg = ChatConfig()
+    if e2b_cfg.e2b_active:
+        assert e2b_cfg.e2b_api_key  # guaranteed by e2b_active check
         try:
-            await kill_sandbox(session_id, config.e2b_api_key)
+            await kill_sandbox(session_id, e2b_cfg.e2b_api_key)
         except Exception:
             logger.warning(
                 "[E2B] Failed to kill sandbox for session %s", session_id[:12]
@@ -264,12 +313,49 @@ async def delete_session(
     return Response(status_code=204)
 
 
+@router.patch(
+    "/sessions/{session_id}/title",
+    summary="Update session title",
+    dependencies=[Security(auth.requires_user)],
+    status_code=200,
+    responses={404: {"description": "Session not found or access denied"}},
+)
+async def update_session_title_route(
+    session_id: str,
+    request: UpdateSessionTitleRequest,
+    user_id: Annotated[str, Security(auth.get_user_id)],
+) -> dict:
+    """
+    Update the title of a chat session.
+
+    Allows the user to rename their chat session.
+
+    Args:
+        session_id: The session ID to update.
+        request: Request body containing the new title.
+        user_id: The authenticated user's ID.
+
+    Returns:
+        dict: Status of the update.
+
+    Raises:
+        HTTPException: 404 if session not found or not owned by user.
+    """
+    success = await update_session_title(session_id, user_id, request.title)
+    if not success:
+        raise HTTPException(
+            status_code=404,
+            detail=f"Session {session_id} not found or access denied",
+        )
+    return {"status": "ok"}
+
+
 @router.get(
     "/sessions/{session_id}",
 )
 async def get_session(
     session_id: str,
-    user_id: Annotated[str | None, Depends(auth.get_user_id)],
+    user_id: Annotated[str, Security(auth.get_user_id)],
 ) -> SessionDetailResponse:
     """
     Retrieve the details of a specific chat session.
@@ -310,6 +396,10 @@ async def get_session(
             last_message_id=last_message_id,
         )
 
+    # Sum token usage from session
+    total_prompt = sum(u.prompt_tokens for u in session.usage)
+    total_completion = sum(u.completion_tokens for u in session.usage)
+
     return SessionDetailResponse(
         id=session.session_id,
         created_at=session.started_at.isoformat(),
@@ -317,6 +407,25 @@ async def get_session(
         user_id=session.user_id or None,
         messages=messages,
         active_stream=active_stream_info,
+        total_prompt_tokens=total_prompt,
+        total_completion_tokens=total_completion,
+    )
+
+
+@router.get(
+    "/usage",
+)
+async def get_copilot_usage(
+    user_id: Annotated[str, Security(auth.get_user_id)],
+) -> CoPilotUsageStatus:
+    """Get CoPilot usage status for the authenticated user.
+
+    Returns current token usage vs limits for daily and weekly windows.
+    """
+    return await get_usage_status(
+        user_id=user_id,
+        daily_token_limit=config.daily_token_limit,
+        weekly_token_limit=config.weekly_token_limit,
     )
 
 
@@ -326,7 +435,7 @@ async def get_session(
 )
 async def cancel_session_task(
     session_id: str,
-    user_id: Annotated[str | None, Depends(auth.get_user_id)],
+    user_id: Annotated[str, Security(auth.get_user_id)],
 ) -> CancelSessionResponse:
     """Cancel the active streaming task for a session.
 
@@ -371,7 +480,7 @@ async def cancel_session_task(
 async def stream_chat_post(
     session_id: str,
     request: StreamChatRequest,
-    user_id: str | None = Depends(auth.get_user_id),
+    user_id: str = Security(auth.get_user_id),
 ):
     """
     Stream chat responses for a session (POST with context support).
@@ -388,7 +497,7 @@ async def stream_chat_post(
     Args:
         session_id: The chat session identifier to associate with the streamed messages.
         request: Request body containing message, is_user_message, and optional context.
-        user_id: Optional authenticated user ID.
+        user_id: Authenticated user ID.
     Returns:
         StreamingResponse: SSE-formatted response chunks.
 
@@ -397,9 +506,7 @@ async def stream_chat_post(
     import time
 
     stream_start_time = time.perf_counter()
-    log_meta = {"component": "ChatStream", "session_id": session_id}
-    if user_id:
-        log_meta["user_id"] = user_id
+    log_meta = {"component": "ChatStream", "session_id": session_id, "user_id": user_id}
 
     logger.info(
         f"[TIMING] stream_chat_post STARTED, session={session_id}, "
@@ -417,6 +524,18 @@ async def stream_chat_post(
         },
     )
 
+    # Pre-turn rate limit check (token-based).
+    # check_rate_limit short-circuits internally when both limits are 0.
+    if user_id:
+        try:
+            await check_rate_limit(
+                user_id=user_id,
+                daily_token_limit=config.daily_token_limit,
+                weekly_token_limit=config.weekly_token_limit,
+            )
+        except RateLimitExceeded as e:
+            raise HTTPException(status_code=429, detail=str(e)) from e
+
     # Enrich message with file metadata if file_ids are provided.
     # Also sanitise file_ids so only validated, workspace-scoped IDs are
     # forwarded downstream (e.g. to the executor via enqueue_copilot_turn).
@@ -651,7 +770,7 @@ async def stream_chat_post(
 )
 async def resume_session_stream(
     session_id: str,
-    user_id: str | None = Depends(auth.get_user_id),
+    user_id: str = Security(auth.get_user_id),
 ):
     """
     Resume an active stream for a session.
@@ -753,7 +872,6 @@ async def resume_session_stream(
 @router.patch(
     "/sessions/{session_id}/assign-user",
     dependencies=[Security(auth.requires_user)],
-    status_code=200,
 )
 async def session_assign_user(
     session_id: str,

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

@@ -1,4 +1,7 @@
-"""Tests for chat route file_ids validation and enrichment."""
+"""Tests for chat API routes: session title update, file attachment validation, usage, and rate limiting."""
+
+from datetime import UTC, datetime, timedelta
+from unittest.mock import AsyncMock
 
 import fastapi
 import fastapi.testclient
@@ -17,6 +20,7 @@ TEST_USER_ID = "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
 
 @pytest.fixture(autouse=True)
 def setup_app_auth(mock_jwt_user):
+    """Setup auth overrides for all tests in this module"""
     from autogpt_libs.auth.jwt_utils import get_jwt_payload
 
     app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
@@ -24,7 +28,95 @@ def setup_app_auth(mock_jwt_user):
     app.dependency_overrides.clear()
 
 
-# ---- file_ids Pydantic validation (B1) ----
+def _mock_update_session_title(
+    mocker: pytest_mock.MockerFixture, *, success: bool = True
+):
+    """Mock update_session_title."""
+    return mocker.patch(
+        "backend.api.features.chat.routes.update_session_title",
+        new_callable=AsyncMock,
+        return_value=success,
+    )
+
+
+# ─── Update title: success ─────────────────────────────────────────────
+
+
+def test_update_title_success(
+    mocker: pytest_mock.MockerFixture,
+    test_user_id: str,
+) -> None:
+    mock_update = _mock_update_session_title(mocker, success=True)
+
+    response = client.patch(
+        "/sessions/sess-1/title",
+        json={"title": "My project"},
+    )
+
+    assert response.status_code == 200
+    assert response.json() == {"status": "ok"}
+    mock_update.assert_called_once_with("sess-1", test_user_id, "My project")
+
+
+def test_update_title_trims_whitespace(
+    mocker: pytest_mock.MockerFixture,
+    test_user_id: str,
+) -> None:
+    mock_update = _mock_update_session_title(mocker, success=True)
+
+    response = client.patch(
+        "/sessions/sess-1/title",
+        json={"title": "  trimmed  "},
+    )
+
+    assert response.status_code == 200
+    mock_update.assert_called_once_with("sess-1", test_user_id, "trimmed")
+
+
+# ─── Update title: blank / whitespace-only → 422 ──────────────────────
+
+
+def test_update_title_blank_rejected(
+    test_user_id: str,
+) -> None:
+    """Whitespace-only titles must be rejected before hitting the DB."""
+    response = client.patch(
+        "/sessions/sess-1/title",
+        json={"title": "   "},
+    )
+
+    assert response.status_code == 422
+
+
+def test_update_title_empty_rejected(
+    test_user_id: str,
+) -> None:
+    response = client.patch(
+        "/sessions/sess-1/title",
+        json={"title": ""},
+    )
+
+    assert response.status_code == 422
+
+
+# ─── Update title: session not found or wrong user → 404 ──────────────
+
+
+def test_update_title_not_found(
+    mocker: pytest_mock.MockerFixture,
+    test_user_id: str,
+) -> None:
+    _mock_update_session_title(mocker, success=False)
+
+    response = client.patch(
+        "/sessions/sess-1/title",
+        json={"title": "New name"},
+    )
+
+    assert response.status_code == 404
+
+
+# ─── file_ids Pydantic validation ─────────────────────────────────────
 
 
 def test_stream_chat_rejects_too_many_file_ids():
@@ -92,7 +184,7 @@ def test_stream_chat_accepts_20_file_ids(mocker: pytest_mock.MockFixture):
     assert response.status_code == 200
 
 
-# ---- UUID format filtering ----
+# ─── UUID format filtering ─────────────────────────────────────────────
 
 
 def test_file_ids_filters_invalid_uuids(mocker: pytest_mock.MockFixture):
@@ -131,7 +223,7 @@ def test_file_ids_filters_invalid_uuids(mocker: pytest_mock.MockFixture):
     assert call_kwargs["where"]["id"]["in"] == [valid_id]
 
 
-# ---- Cross-workspace file_ids ----
+# ─── Cross-workspace file_ids ─────────────────────────────────────────
 
 
 def test_file_ids_scoped_to_workspace(mocker: pytest_mock.MockFixture):
@@ -158,3 +250,153 @@ def test_file_ids_scoped_to_workspace(mocker: pytest_mock.MockFixture):
     call_kwargs = mock_prisma.find_many.call_args[1]
     assert call_kwargs["where"]["workspaceId"] == "my-workspace-id"
     assert call_kwargs["where"]["isDeleted"] is False
+
+
+# ─── Rate limit → 429 ─────────────────────────────────────────────────
+
+
+def test_stream_chat_returns_429_on_daily_rate_limit(mocker: pytest_mock.MockFixture):
+    """When check_rate_limit raises RateLimitExceeded for daily limit the endpoint returns 429."""
+    from backend.copilot.rate_limit import RateLimitExceeded
+
+    _mock_stream_internals(mocker)
+    # Ensure the rate-limit branch is entered by setting a non-zero limit.
+    mocker.patch.object(chat_routes.config, "daily_token_limit", 10000)
+    mocker.patch.object(chat_routes.config, "weekly_token_limit", 50000)
+    mocker.patch(
+        "backend.api.features.chat.routes.check_rate_limit",
+        side_effect=RateLimitExceeded("daily", datetime.now(UTC) + timedelta(hours=1)),
+    )
+
+    response = client.post(
+        "/sessions/sess-1/stream",
+        json={"message": "hello"},
+    )
+    assert response.status_code == 429
+    assert "daily" in response.json()["detail"].lower()
+
+
+def test_stream_chat_returns_429_on_weekly_rate_limit(mocker: pytest_mock.MockFixture):
+    """When check_rate_limit raises RateLimitExceeded for weekly limit the endpoint returns 429."""
+    from backend.copilot.rate_limit import RateLimitExceeded
+
+    _mock_stream_internals(mocker)
+    mocker.patch.object(chat_routes.config, "daily_token_limit", 10000)
+    mocker.patch.object(chat_routes.config, "weekly_token_limit", 50000)
+    resets_at = datetime.now(UTC) + timedelta(days=3)
+    mocker.patch(
+        "backend.api.features.chat.routes.check_rate_limit",
+        side_effect=RateLimitExceeded("weekly", resets_at),
+    )
+
+    response = client.post(
+        "/sessions/sess-1/stream",
+        json={"message": "hello"},
+    )
+    assert response.status_code == 429
+    detail = response.json()["detail"].lower()
+    assert "weekly" in detail
+    assert "resets in" in detail
+
+
+def test_stream_chat_429_includes_reset_time(mocker: pytest_mock.MockFixture):
+    """The 429 response detail should include the human-readable reset time."""
+    from backend.copilot.rate_limit import RateLimitExceeded
+
+    _mock_stream_internals(mocker)
+    mocker.patch.object(chat_routes.config, "daily_token_limit", 10000)
+    mocker.patch.object(chat_routes.config, "weekly_token_limit", 50000)
+    mocker.patch(
+        "backend.api.features.chat.routes.check_rate_limit",
+        side_effect=RateLimitExceeded(
+            "daily", datetime.now(UTC) + timedelta(hours=2, minutes=30)
+        ),
+    )
+
+    response = client.post(
+        "/sessions/sess-1/stream",
+        json={"message": "hello"},
+    )
+    assert response.status_code == 429
+    detail = response.json()["detail"]
+    assert "2h" in detail
+    assert "Resets in" in detail
+
+
+# ─── Usage endpoint ───────────────────────────────────────────────────
+
+
+def _mock_usage(
+    mocker: pytest_mock.MockerFixture,
+    *,
+    daily_used: int = 500,
+    weekly_used: int = 2000,
+) -> AsyncMock:
+    """Mock get_usage_status to return a predictable CoPilotUsageStatus."""
+    from backend.copilot.rate_limit import CoPilotUsageStatus, UsageWindow
+
+    resets_at = datetime.now(UTC) + timedelta(days=1)
+    status = CoPilotUsageStatus(
+        daily=UsageWindow(used=daily_used, limit=10000, resets_at=resets_at),
+        weekly=UsageWindow(used=weekly_used, limit=50000, resets_at=resets_at),
+    )
+    return mocker.patch(
+        "backend.api.features.chat.routes.get_usage_status",
+        new_callable=AsyncMock,
+        return_value=status,
+    )
+
+
+def test_usage_returns_daily_and_weekly(
+    mocker: pytest_mock.MockerFixture,
+    test_user_id: str,
+) -> None:
+    """GET /usage returns daily and weekly usage."""
+    mock_get = _mock_usage(mocker, daily_used=500, weekly_used=2000)
+
+    mocker.patch.object(chat_routes.config, "daily_token_limit", 10000)
+    mocker.patch.object(chat_routes.config, "weekly_token_limit", 50000)
+
+    response = client.get("/usage")
+
+    assert response.status_code == 200
+    data = response.json()
+    assert data["daily"]["used"] == 500
+    assert data["weekly"]["used"] == 2000
+
+    mock_get.assert_called_once_with(
+        user_id=test_user_id,
+        daily_token_limit=10000,
+        weekly_token_limit=50000,
+    )
+
+
+def test_usage_uses_config_limits(
+    mocker: pytest_mock.MockerFixture,
+    test_user_id: str,
+) -> None:
+    """The endpoint forwards daily_token_limit and weekly_token_limit from config."""
+    mock_get = _mock_usage(mocker)
+
+    mocker.patch.object(chat_routes.config, "daily_token_limit", 99999)
+    mocker.patch.object(chat_routes.config, "weekly_token_limit", 77777)
+
+    response = client.get("/usage")
+
+    assert response.status_code == 200
+    mock_get.assert_called_once_with(
+        user_id=test_user_id,
+        daily_token_limit=99999,
+        weekly_token_limit=77777,
+    )
+
+
+def test_usage_rejects_unauthenticated_request() -> None:
+    """GET /usage should return 401 when no valid JWT is provided."""
+    unauthenticated_app = fastapi.FastAPI()
+    unauthenticated_app.include_router(chat_routes.router)
+    unauthenticated_client = fastapi.testclient.TestClient(unauthenticated_app)
+
+    response = unauthenticated_client.get("/usage")
+
+    assert response.status_code == 401

autogpt_platform/backend/backend/api/features/executions/review/review_routes_test.py

@@ -638,7 +638,7 @@ async def test_process_review_action_auto_approve_creates_auto_approval_records(
 
     # Mock get_node_executions to return node_id mapping
     mock_get_node_executions = mocker.patch(
-        "backend.data.execution.get_node_executions"
+        "backend.api.features.executions.review.routes.get_node_executions"
     )
     mock_node_exec = mocker.Mock(spec=NodeExecutionResult)
     mock_node_exec.node_exec_id = "test_node_123"
@@ -936,7 +936,7 @@ async def test_process_review_action_auto_approve_only_applies_to_approved_revie
 
     # Mock get_node_executions to return node_id mapping
     mock_get_node_executions = mocker.patch(
-        "backend.data.execution.get_node_executions"
+        "backend.api.features.executions.review.routes.get_node_executions"
     )
     mock_node_exec = mocker.Mock(spec=NodeExecutionResult)
     mock_node_exec.node_exec_id = "node_exec_approved"
@@ -1148,7 +1148,7 @@ async def test_process_review_action_per_review_auto_approve_granularity(
 
     # Mock get_node_executions to return batch node data
     mock_get_node_executions = mocker.patch(
-        "backend.data.execution.get_node_executions"
+        "backend.api.features.executions.review.routes.get_node_executions"
     )
     # Create mock node executions for each review
     mock_node_execs = []

autogpt_platform/backend/backend/api/features/executions/review/routes.py

@@ -6,10 +6,15 @@ import autogpt_libs.auth as autogpt_auth_lib
 from fastapi import APIRouter, HTTPException, Query, Security, status
 from prisma.enums import ReviewStatus
 
+from backend.copilot.constants import (
+    is_copilot_synthetic_id,
+    parse_node_id_from_exec_id,
+)
 from backend.data.execution import (
     ExecutionContext,
     ExecutionStatus,
     get_graph_execution_meta,
+    get_node_executions,
 )
 from backend.data.graph import get_graph_settings
 from backend.data.human_review import (
@@ -36,6 +41,38 @@ router = APIRouter(
 )
 
 
+async def _resolve_node_ids(
+    node_exec_ids: list[str],
+    graph_exec_id: str,
+    is_copilot: bool,
+) -> dict[str, str]:
+    """Resolve node_exec_id -> node_id for auto-approval records.
+
+    CoPilot synthetic IDs encode node_id in the format "{node_id}:{random}".
+    Graph executions look up node_id from NodeExecution records.
+    """
+    if not node_exec_ids:
+        return {}
+
+    if is_copilot:
+        return {neid: parse_node_id_from_exec_id(neid) for neid in node_exec_ids}
+
+    node_execs = await get_node_executions(
+        graph_exec_id=graph_exec_id, include_exec_data=False
+    )
+    node_exec_map = {ne.node_exec_id: ne.node_id for ne in node_execs}
+
+    result = {}
+    for neid in node_exec_ids:
+        if neid in node_exec_map:
+            result[neid] = node_exec_map[neid]
+        else:
+            logger.error(
+                f"Failed to resolve node_id for {neid}: Node execution not found."
+            )
+    return result
+
+
 @router.get(
     "/pending",
     summary="Get Pending Reviews",
@@ -110,14 +147,16 @@ async def list_pending_reviews_for_execution(
     """
 
     # Verify user owns the graph execution before returning reviews
-    graph_exec = await get_graph_execution_meta(
-        user_id=user_id, execution_id=graph_exec_id
-    )
-    if not graph_exec:
-        raise HTTPException(
-            status_code=status.HTTP_404_NOT_FOUND,
-            detail=f"Graph execution #{graph_exec_id} not found",
+    # (CoPilot synthetic IDs don't have graph execution records)
+    if not is_copilot_synthetic_id(graph_exec_id):
+        graph_exec = await get_graph_execution_meta(
+            user_id=user_id, execution_id=graph_exec_id
         )
+        if not graph_exec:
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND,
+                detail=f"Graph execution #{graph_exec_id} not found",
+            )
 
     return await get_pending_reviews_for_execution(graph_exec_id, user_id)
 
@@ -160,30 +199,26 @@ async def process_review_action(
         )
 
     graph_exec_id = next(iter(graph_exec_ids))
+    is_copilot = is_copilot_synthetic_id(graph_exec_id)
 
-    # Validate execution status before processing reviews
-    graph_exec_meta = await get_graph_execution_meta(
-        user_id=user_id, execution_id=graph_exec_id
-    )
-
-    if not graph_exec_meta:
-        raise HTTPException(
-            status_code=status.HTTP_404_NOT_FOUND,
-            detail=f"Graph execution #{graph_exec_id} not found",
-        )
-
-    # Only allow processing reviews if execution is paused for review
-    # or incomplete (partial execution with some reviews already processed)
-    if graph_exec_meta.status not in (
-        ExecutionStatus.REVIEW,
-        ExecutionStatus.INCOMPLETE,
-    ):
-        raise HTTPException(
-            status_code=status.HTTP_409_CONFLICT,
-            detail=f"Cannot process reviews while execution status is {graph_exec_meta.status}. "
-            f"Reviews can only be processed when execution is paused (REVIEW status). "
-            f"Current status: {graph_exec_meta.status}",
+    # Validate execution status for graph executions (skip for CoPilot synthetic IDs)
+    if not is_copilot:
+        graph_exec_meta = await get_graph_execution_meta(
+            user_id=user_id, execution_id=graph_exec_id
         )
+        if not graph_exec_meta:
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND,
+                detail=f"Graph execution #{graph_exec_id} not found",
+            )
+        if graph_exec_meta.status not in (
+            ExecutionStatus.REVIEW,
+            ExecutionStatus.INCOMPLETE,
+        ):
+            raise HTTPException(
+                status_code=status.HTTP_409_CONFLICT,
+                detail=f"Cannot process reviews while execution status is {graph_exec_meta.status}",
+            )
 
     # Build review decisions map and track which reviews requested auto-approval
     # Auto-approved reviews use original data (no modifications allowed)
@@ -236,7 +271,7 @@ async def process_review_action(
             )
             return (node_id, False)
 
-    # Collect node_exec_ids that need auto-approval
+    # Collect node_exec_ids that need auto-approval and resolve their node_ids
     node_exec_ids_needing_auto_approval = [
         node_exec_id
         for node_exec_id, review_result in updated_reviews.items()
@@ -244,29 +279,16 @@ async def process_review_action(
         and auto_approve_requests.get(node_exec_id, False)
     ]
 
-    # Batch-fetch node executions to get node_ids
+    node_id_map = await _resolve_node_ids(
+        node_exec_ids_needing_auto_approval, graph_exec_id, is_copilot
+    )
+
+    # Deduplicate by node_id — one auto-approval per node
     nodes_needing_auto_approval: dict[str, Any] = {}
-    if node_exec_ids_needing_auto_approval:
-        from backend.data.execution import get_node_executions
-
-        node_execs = await get_node_executions(
-            graph_exec_id=graph_exec_id, include_exec_data=False
-        )
-        node_exec_map = {node_exec.node_exec_id: node_exec for node_exec in node_execs}
-
-        for node_exec_id in node_exec_ids_needing_auto_approval:
-            node_exec = node_exec_map.get(node_exec_id)
-            if node_exec:
-                review_result = updated_reviews[node_exec_id]
-                # Use the first approved review for this node (deduplicate by node_id)
-                if node_exec.node_id not in nodes_needing_auto_approval:
-                    nodes_needing_auto_approval[node_exec.node_id] = review_result
-            else:
-                logger.error(
-                    f"Failed to create auto-approval record for {node_exec_id}: "
-                    f"Node execution not found. This may indicate a race condition "
-                    f"or data inconsistency."
-                )
+    for node_exec_id in node_exec_ids_needing_auto_approval:
+        node_id = node_id_map.get(node_exec_id)
+        if node_id and node_id not in nodes_needing_auto_approval:
+            nodes_needing_auto_approval[node_id] = updated_reviews[node_exec_id]
 
     # Execute all auto-approval creations in parallel (deduplicated by node_id)
     auto_approval_results = await asyncio.gather(
@@ -281,13 +303,11 @@ async def process_review_action(
     auto_approval_failed_count = 0
     for result in auto_approval_results:
         if isinstance(result, Exception):
-            # Unexpected exception during auto-approval creation
             auto_approval_failed_count += 1
             logger.error(
                 f"Unexpected exception during auto-approval creation: {result}"
             )
         elif isinstance(result, tuple) and len(result) == 2 and not result[1]:
-            # Auto-approval creation failed (returned False)
             auto_approval_failed_count += 1
 
     # Count results
@@ -302,22 +322,20 @@ async def process_review_action(
         if review.status == ReviewStatus.REJECTED
     )
 
-    # Resume execution only if ALL pending reviews for this execution have been processed
-    if updated_reviews:
+    # Resume graph execution only for real graph executions (not CoPilot)
+    # CoPilot sessions are resumed by the LLM retrying run_block with review_id
+    if not is_copilot and updated_reviews:
         still_has_pending = await has_pending_reviews_for_graph_exec(graph_exec_id)
 
         if not still_has_pending:
-            # Get the graph_id from any processed review
             first_review = next(iter(updated_reviews.values()))
 
             try:
-                # Fetch user and settings to build complete execution context
                 user = await get_user_by_id(user_id)
                 settings = await get_graph_settings(
                     user_id=user_id, graph_id=first_review.graph_id
                 )
 
-                # Preserve user's timezone preference when resuming execution
                 user_timezone = (
                     user.timezone if user.timezone != USER_TIMEZONE_NOT_SET else "UTC"
                 )

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

@@ -8,7 +8,6 @@ import prisma.errors
 import prisma.models
 import prisma.types
 
-import backend.api.features.store.exceptions as store_exceptions
 import backend.api.features.store.image_gen as store_image_gen
 import backend.api.features.store.media as store_media
 import backend.data.graph as graph_db
@@ -251,7 +250,7 @@ async def get_library_agent(id: str, user_id: str) -> library_model.LibraryAgent
         The requested LibraryAgent.
 
     Raises:
-        AgentNotFoundError: If the specified agent does not exist.
+        NotFoundError: If the specified agent does not exist.
         DatabaseError: If there's an error during retrieval.
     """
     library_agent = await prisma.models.LibraryAgent.prisma().find_first(
@@ -398,6 +397,7 @@ async def create_library_agent(
     hitl_safe_mode: bool = True,
     sensitive_action_safe_mode: bool = False,
     create_library_agents_for_sub_graphs: bool = True,
+    folder_id: str | None = None,
 ) -> list[library_model.LibraryAgent]:
     """
     Adds an agent to the user's library (LibraryAgent table).
@@ -414,12 +414,18 @@ async def create_library_agent(
         If the graph has sub-graphs, the parent graph will always be the first entry in the list.
 
     Raises:
-        AgentNotFoundError: If the specified agent does not exist.
+        NotFoundError: If the specified agent does not exist.
         DatabaseError: If there's an error during creation or if image generation fails.
     """
     logger.info(
         f"Creating library agent for graph #{graph.id} v{graph.version}; user:<redacted>"
     )
+
+    # Authorization: FK only checks existence, not ownership.
+    # Verify the folder belongs to this user to prevent cross-user nesting.
+    if folder_id:
+        await get_folder(folder_id, user_id)
+
     graph_entries = (
         [graph, *graph.sub_graphs] if create_library_agents_for_sub_graphs else [graph]
     )
@@ -432,7 +438,6 @@ async def create_library_agent(
                         isCreatedByUser=(user_id == user_id),
                         useGraphIsActiveVersion=True,
                         User={"connect": {"id": user_id}},
-                        # Creator={"connect": {"id": user_id}},
                         AgentGraph={
                             "connect": {
                                 "graphVersionId": {
@@ -448,6 +453,11 @@ async def create_library_agent(
                                 sensitive_action_safe_mode=sensitive_action_safe_mode,
                             ).model_dump()
                         ),
+                        **(
+                            {"Folder": {"connect": {"id": folder_id}}}
+                            if folder_id and graph_entry is graph
+                            else {}
+                        ),
                     ),
                     include=library_agent_include(
                         user_id, include_nodes=False, include_executions=False
@@ -529,6 +539,7 @@ async def update_agent_version_in_library(
 async def create_graph_in_library(
     graph: graph_db.Graph,
     user_id: str,
+    folder_id: str | None = None,
 ) -> tuple[graph_db.GraphModel, library_model.LibraryAgent]:
     """Create a new graph and add it to the user's library."""
     graph.version = 1
@@ -542,6 +553,7 @@ async def create_graph_in_library(
         user_id=user_id,
         sensitive_action_safe_mode=True,
         create_library_agents_for_sub_graphs=False,
+        folder_id=folder_id,
     )
 
     if created_graph.is_active:
@@ -817,7 +829,7 @@ async def add_store_agent_to_library(
         The newly created LibraryAgent if successfully added, the existing corresponding one if any.
 
     Raises:
-        AgentNotFoundError: If the store listing or associated agent is not found.
+        NotFoundError: If the store listing or associated agent is not found.
         DatabaseError: If there's an issue creating the LibraryAgent record.
     """
     logger.debug(
@@ -832,7 +844,7 @@ async def add_store_agent_to_library(
     )
     if not store_listing_version or not store_listing_version.AgentGraph:
         logger.warning(f"Store listing version not found: {store_listing_version_id}")
-        raise store_exceptions.AgentNotFoundError(
+        raise NotFoundError(
             f"Store listing version {store_listing_version_id} not found or invalid"
         )
 
@@ -846,7 +858,7 @@ async def add_store_agent_to_library(
         include_subgraphs=False,
     )
     if not graph_model:
-        raise store_exceptions.AgentNotFoundError(
+        raise NotFoundError(
             f"Graph #{graph.id} v{graph.version} not found or accessible"
         )
 
@@ -1481,6 +1493,67 @@ async def bulk_move_agents_to_folder(
     return [library_model.LibraryAgent.from_db(agent) for agent in agents]
 
 
+def collect_tree_ids(
+    nodes: list[library_model.LibraryFolderTree],
+    visited: set[str] | None = None,
+) -> list[str]:
+    """Collect all folder IDs from a folder tree."""
+    if visited is None:
+        visited = set()
+    ids: list[str] = []
+    for n in nodes:
+        if n.id in visited:
+            continue
+        visited.add(n.id)
+        ids.append(n.id)
+        ids.extend(collect_tree_ids(n.children, visited))
+    return ids
+
+
+async def get_folder_agent_summaries(
+    user_id: str, folder_id: str
+) -> list[dict[str, str | None]]:
+    """Get a lightweight list of agents in a folder (id, name, description)."""
+    all_agents: list[library_model.LibraryAgent] = []
+    for page in itertools.count(1):
+        resp = await list_library_agents(
+            user_id=user_id, folder_id=folder_id, page=page
+        )
+        all_agents.extend(resp.agents)
+        if page >= resp.pagination.total_pages:
+            break
+    return [
+        {"id": a.id, "name": a.name, "description": a.description} for a in all_agents
+    ]
+
+
+async def get_root_agent_summaries(
+    user_id: str,
+) -> list[dict[str, str | None]]:
+    """Get a lightweight list of root-level agents (folderId IS NULL)."""
+    all_agents: list[library_model.LibraryAgent] = []
+    for page in itertools.count(1):
+        resp = await list_library_agents(
+            user_id=user_id, include_root_only=True, page=page
+        )
+        all_agents.extend(resp.agents)
+        if page >= resp.pagination.total_pages:
+            break
+    return [
+        {"id": a.id, "name": a.name, "description": a.description} for a in all_agents
+    ]
+
+
+async def get_folder_agents_map(
+    user_id: str, folder_ids: list[str]
+) -> dict[str, list[dict[str, str | None]]]:
+    """Get agent summaries for multiple folders concurrently."""
+    results = await asyncio.gather(
+        *(get_folder_agent_summaries(user_id, fid) for fid in folder_ids)
+    )
+    return dict(zip(folder_ids, results))
+
+
 ##############################################
 ########### Presets DB Functions #############
 ##############################################

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

@@ -4,7 +4,6 @@ import prisma.enums
 import prisma.models
 import pytest
 
-import backend.api.features.store.exceptions
 from backend.data.db import connect
 from backend.data.includes import library_agent_include
 
@@ -218,7 +217,7 @@ async def test_add_agent_to_library_not_found(mocker):
     )
 
     # Call function and verify exception
-    with pytest.raises(backend.api.features.store.exceptions.AgentNotFoundError):
+    with pytest.raises(db.NotFoundError):
         await db.add_store_agent_to_library("version123", "test-user")
 
     # Verify mock called correctly

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

@@ -165,7 +165,6 @@ class LibraryAgent(pydantic.BaseModel):
     id: str
     graph_id: str
     graph_version: int
-    owner_user_id: str
 
     image_url: str | None
 
@@ -206,7 +205,9 @@ class LibraryAgent(pydantic.BaseModel):
         default_factory=list,
         description="List of recent executions with status, score, and summary",
     )
-    can_access_graph: bool
+    can_access_graph: bool = pydantic.Field(
+        description="Indicates whether the same user owns the corresponding graph"
+    )
     is_latest_version: bool
     is_favorite: bool
     folder_id: str | None = None
@@ -324,7 +325,6 @@ class LibraryAgent(pydantic.BaseModel):
             id=agent.id,
             graph_id=agent.agentGraphId,
             graph_version=agent.agentGraphVersion,
-            owner_user_id=agent.userId,
             image_url=agent.imageUrl,
             creator_name=creator_name,
             creator_image_url=creator_image_url,

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

@@ -42,7 +42,6 @@ async def test_get_library_agents_success(
                 id="test-agent-1",
                 graph_id="test-agent-1",
                 graph_version=1,
-                owner_user_id=test_user_id,
                 name="Test Agent 1",
                 description="Test Description 1",
                 image_url=None,
@@ -67,7 +66,6 @@ async def test_get_library_agents_success(
                 id="test-agent-2",
                 graph_id="test-agent-2",
                 graph_version=1,
-                owner_user_id=test_user_id,
                 name="Test Agent 2",
                 description="Test Description 2",
                 image_url=None,
@@ -131,7 +129,6 @@ async def test_get_favorite_library_agents_success(
                 id="test-agent-1",
                 graph_id="test-agent-1",
                 graph_version=1,
-                owner_user_id=test_user_id,
                 name="Favorite Agent 1",
                 description="Test Favorite Description 1",
                 image_url=None,
@@ -184,7 +181,6 @@ def test_add_agent_to_library_success(
         id="test-library-agent-id",
         graph_id="test-agent-1",
         graph_version=1,
-        owner_user_id=test_user_id,
         name="Test Agent 1",
         description="Test Description 1",
         image_url=None,

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

@@ -24,7 +24,7 @@ from backend.blocks.mcp.oauth import MCPOAuthHandler
 from backend.data.model import OAuth2Credentials
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.integrations.providers import ProviderName
-from backend.util.request import HTTPClientError, Requests, validate_url
+from backend.util.request import HTTPClientError, Requests, validate_url_host
 from backend.util.settings import Settings
 
 logger = logging.getLogger(__name__)
@@ -80,7 +80,7 @@ async def discover_tools(
     """
     # Validate URL to prevent SSRF — blocks loopback and private IP ranges.
     try:
-        await validate_url(request.server_url, trusted_origins=[])
+        await validate_url_host(request.server_url)
     except ValueError as e:
         raise fastapi.HTTPException(status_code=400, detail=f"Invalid server URL: {e}")
 
@@ -167,7 +167,7 @@ async def mcp_oauth_login(
     """
     # Validate URL to prevent SSRF — blocks loopback and private IP ranges.
     try:
-        await validate_url(request.server_url, trusted_origins=[])
+        await validate_url_host(request.server_url)
     except ValueError as e:
         raise fastapi.HTTPException(status_code=400, detail=f"Invalid server URL: {e}")
 
@@ -187,7 +187,7 @@ async def mcp_oauth_login(
 
         # Validate the auth server URL from metadata to prevent SSRF.
         try:
-            await validate_url(auth_server_url, trusted_origins=[])
+            await validate_url_host(auth_server_url)
         except ValueError as e:
             raise fastapi.HTTPException(
                 status_code=400,
@@ -234,7 +234,7 @@ async def mcp_oauth_login(
     if registration_endpoint:
         # Validate the registration endpoint to prevent SSRF via metadata.
         try:
-            await validate_url(registration_endpoint, trusted_origins=[])
+            await validate_url_host(registration_endpoint)
         except ValueError:
             pass  # Skip registration, fall back to default client_id
         else:
@@ -429,7 +429,7 @@ async def mcp_store_token(
 
     # Validate URL to prevent SSRF — blocks loopback and private IP ranges.
     try:
-        await validate_url(request.server_url, trusted_origins=[])
+        await validate_url_host(request.server_url)
     except ValueError as e:
         raise fastapi.HTTPException(status_code=400, detail=f"Invalid server URL: {e}")
 

autogpt_platform/backend/backend/api/features/mcp/test_routes.py

@@ -32,9 +32,9 @@ async def client():
 
 @pytest.fixture(autouse=True)
 def _bypass_ssrf_validation():
-    """Bypass validate_url in all route tests (test URLs don't resolve)."""
+    """Bypass validate_url_host in all route tests (test URLs don't resolve)."""
     with patch(
-        "backend.api.features.mcp.routes.validate_url",
+        "backend.api.features.mcp.routes.validate_url_host",
         new_callable=AsyncMock,
     ):
         yield
@@ -521,12 +521,12 @@ class TestStoreToken:
 
 
 class TestSSRFValidation:
-    """Verify that validate_url is enforced on all endpoints."""
+    """Verify that validate_url_host is enforced on all endpoints."""
 
     @pytest.mark.asyncio(loop_scope="session")
     async def test_discover_tools_ssrf_blocked(self, client):
         with patch(
-            "backend.api.features.mcp.routes.validate_url",
+            "backend.api.features.mcp.routes.validate_url_host",
             new_callable=AsyncMock,
             side_effect=ValueError("blocked loopback"),
         ):
@@ -541,7 +541,7 @@ class TestSSRFValidation:
     @pytest.mark.asyncio(loop_scope="session")
     async def test_oauth_login_ssrf_blocked(self, client):
         with patch(
-            "backend.api.features.mcp.routes.validate_url",
+            "backend.api.features.mcp.routes.validate_url_host",
             new_callable=AsyncMock,
             side_effect=ValueError("blocked private IP"),
         ):
@@ -556,7 +556,7 @@ class TestSSRFValidation:
     @pytest.mark.asyncio(loop_scope="session")
     async def test_store_token_ssrf_blocked(self, client):
         with patch(
-            "backend.api.features.mcp.routes.validate_url",
+            "backend.api.features.mcp.routes.validate_url_host",
             new_callable=AsyncMock,
             side_effect=ValueError("blocked loopback"),
         ):

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

@@ -1,5 +1,3 @@
-from typing import Literal
-
 from backend.util.cache import cached
 
 from . import db as store_db
@@ -23,7 +21,7 @@ def clear_all_caches():
 async def _get_cached_store_agents(
     featured: bool,
     creator: str | None,
-    sorted_by: Literal["rating", "runs", "name", "updated_at"] | None,
+    sorted_by: store_db.StoreAgentsSortOptions | None,
     search_query: str | None,
     category: str | None,
     page: int,
@@ -57,7 +55,7 @@ async def _get_cached_agent_details(
 async def _get_cached_store_creators(
     featured: bool,
     search_query: str | None,
-    sorted_by: Literal["agent_rating", "agent_runs", "num_agents"] | None,
+    sorted_by: store_db.StoreCreatorsSortOptions | None,
     page: int,
     page_size: int,
 ):
@@ -75,4 +73,4 @@ async def _get_cached_store_creators(
 @cached(maxsize=100, ttl_seconds=300, shared_cache=True)
 async def _get_cached_creator_details(username: str):
     """Cached helper to get creator details."""
-    return await store_db.get_store_creator_details(username=username.lower())
+    return await store_db.get_store_creator(username=username.lower())

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

@@ -5,16 +5,26 @@ Pluggable system for different content sources (store agents, blocks, docs).
 Each handler knows how to fetch and process its content type for embedding.
 """
 
+from __future__ import annotations
+
+import asyncio
+import functools
+import itertools
 import logging
 from abc import ABC, abstractmethod
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Any, get_args, get_origin
+from typing import TYPE_CHECKING, Any, get_args, get_origin
 
 from prisma.enums import ContentType
 
+from backend.blocks import get_blocks
 from backend.blocks.llm import LlmModel
 from backend.data.db import query_raw_with_schema
+from backend.util.text import split_camelcase
+
+if TYPE_CHECKING:
+    from backend.blocks._base import AnyBlockSchema
 
 logger = logging.getLogger(__name__)
 
@@ -154,6 +164,28 @@ class StoreAgentHandler(ContentHandler):
         }
 
 
+@functools.lru_cache(maxsize=1)
+def _get_enabled_blocks() -> dict[str, AnyBlockSchema]:
+    """Return ``{block_id: block_instance}`` for all enabled, instantiable blocks.
+
+    Disabled blocks and blocks that fail to instantiate are silently skipped
+    (with a warning log), so callers never need their own try/except loop.
+
+    Results are cached for the process lifetime via ``lru_cache`` because
+    blocks are registered at import time and never change while running.
+    """
+    enabled: dict[str, AnyBlockSchema] = {}
+    for block_id, block_cls in get_blocks().items():
+        try:
+            instance = block_cls()
+        except Exception as e:
+            logger.warning(f"Skipping block {block_id}: init failed: {e}")
+            continue
+        if not instance.disabled:
+            enabled[block_id] = instance
+    return enabled
+
+
 class BlockHandler(ContentHandler):
     """Handler for block definitions (Python classes)."""
 
@@ -163,16 +195,14 @@ class BlockHandler(ContentHandler):
 
     async def get_missing_items(self, batch_size: int) -> list[ContentItem]:
         """Fetch blocks without embeddings."""
-        from backend.blocks import get_blocks
-
-        # Get all available blocks
-        all_blocks = get_blocks()
-
-        # Check which ones have embeddings
-        if not all_blocks:
+        # to_thread keeps the first (heavy) call off the event loop.  On
+        # subsequent calls the lru_cache makes this a dict lookup, so the
+        # thread-pool overhead is negligible compared to the DB queries below.
+        enabled = await asyncio.to_thread(_get_enabled_blocks)
+        if not enabled:
             return []
 
-        block_ids = list(all_blocks.keys())
+        block_ids = list(enabled.keys())
 
         # Query for existing embeddings
         placeholders = ",".join([f"${i+1}" for i in range(len(block_ids))])
@@ -187,52 +217,42 @@ class BlockHandler(ContentHandler):
         )
 
         existing_ids = {row["contentId"] for row in existing_result}
-        missing_blocks = [
-            (block_id, block_cls)
-            for block_id, block_cls in all_blocks.items()
-            if block_id not in existing_ids
-        ]
 
-        # Convert to ContentItem
+        # Convert to ContentItem — disabled filtering already done by
+        # _get_enabled_blocks so batch_size won't be exhausted by disabled blocks.
+        missing = ((bid, b) for bid, b in enabled.items() if bid not in existing_ids)
         items = []
-        for block_id, block_cls in missing_blocks[:batch_size]:
+        for block_id, block in itertools.islice(missing, batch_size):
             try:
-                block_instance = block_cls()
-
-                if block_instance.disabled:
-                    continue
-
                 # Build searchable text from block metadata
-                parts = []
-                if block_instance.name:
-                    parts.append(block_instance.name)
-                if block_instance.description:
-                    parts.append(block_instance.description)
-                if block_instance.categories:
-                    parts.append(
-                        " ".join(str(cat.value) for cat in block_instance.categories)
+                if not block.name:
+                    logger.warning(
+                        f"Block {block_id} has no name — using block_id as fallback"
                     )
+                display_name = split_camelcase(block.name) if block.name else ""
+                parts = []
+                if display_name:
+                    parts.append(display_name)
+                if block.description:
+                    parts.append(block.description)
+                if block.categories:
+                    parts.append(" ".join(str(cat.value) for cat in block.categories))
 
                 # Add input schema field descriptions
-                block_input_fields = block_instance.input_schema.model_fields
                 parts += [
                     f"{field_name}: {field_info.description}"
-                    for field_name, field_info in block_input_fields.items()
+                    for field_name, field_info in block.input_schema.model_fields.items()
                     if field_info.description
                 ]
 
                 searchable_text = " ".join(parts)
 
                 categories_list = (
-                    [cat.value for cat in block_instance.categories]
-                    if block_instance.categories
-                    else []
+                    [cat.value for cat in block.categories] if block.categories else []
                 )
 
                 # Extract provider names from credentials fields
-                credentials_info = (
-                    block_instance.input_schema.get_credentials_fields_info()
-                )
+                credentials_info = block.input_schema.get_credentials_fields_info()
                 is_integration = len(credentials_info) > 0
                 provider_names = [
                     provider.value.lower()
@@ -243,7 +263,7 @@ class BlockHandler(ContentHandler):
                 # Check if block has LlmModel field in input schema
                 has_llm_model_field = any(
                     _contains_type(field.annotation, LlmModel)
-                    for field in block_instance.input_schema.model_fields.values()
+                    for field in block.input_schema.model_fields.values()
                 )
 
                 items.append(
@@ -252,13 +272,13 @@ class BlockHandler(ContentHandler):
                         content_type=ContentType.BLOCK,
                         searchable_text=searchable_text,
                         metadata={
-                            "name": block_instance.name,
+                            "name": display_name or block.name or block_id,
                             "categories": categories_list,
                             "providers": provider_names,
                             "has_llm_model_field": has_llm_model_field,
                             "is_integration": is_integration,
                         },
-                        user_id=None,  # Blocks are public
+                        user_id=None,
                     )
                 )
             except Exception as e:
@@ -269,22 +289,13 @@ class BlockHandler(ContentHandler):
 
     async def get_stats(self) -> dict[str, int]:
         """Get statistics about block embedding coverage."""
-        from backend.blocks import get_blocks
-
-        all_blocks = get_blocks()
-
-        # Filter out disabled blocks - they're not indexed
-        enabled_block_ids = [
-            block_id
-            for block_id, block_cls in all_blocks.items()
-            if not block_cls().disabled
-        ]
-        total_blocks = len(enabled_block_ids)
+        enabled = await asyncio.to_thread(_get_enabled_blocks)
+        total_blocks = len(enabled)
 
         if total_blocks == 0:
             return {"total": 0, "with_embeddings": 0, "without_embeddings": 0}
 
-        block_ids = enabled_block_ids
+        block_ids = list(enabled.keys())
         placeholders = ",".join([f"${i+1}" for i in range(len(block_ids))])
 
         embedded_result = await query_raw_with_schema(

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

@@ -1,7 +1,5 @@
 """
-E2E tests for content handlers (blocks, store agents, documentation).
-
-Tests the full flow: discovering content → generating embeddings → storing.
+Tests for content handlers (blocks, store agents, documentation).
 """
 
 from pathlib import Path
@@ -15,15 +13,103 @@ from backend.api.features.store.content_handlers import (
     BlockHandler,
     DocumentationHandler,
     StoreAgentHandler,
+    _get_enabled_blocks,
 )
 
 
+@pytest.fixture(autouse=True)
+def _clear_block_cache():
+    """Clear the lru_cache on _get_enabled_blocks before each test."""
+    _get_enabled_blocks.cache_clear()
+    yield
+    _get_enabled_blocks.cache_clear()
+
+
+# ---------------------------------------------------------------------------
+# Helper to build a mock block class that returns a pre-configured instance
+# ---------------------------------------------------------------------------
+
+
+def _make_block_class(
+    *,
+    name: str = "Block",
+    description: str = "",
+    disabled: bool = False,
+    categories: list[MagicMock] | None = None,
+    fields: dict[str, str] | None = None,
+    raise_on_init: Exception | None = None,
+) -> MagicMock:
+    cls = MagicMock()
+    if raise_on_init is not None:
+        cls.side_effect = raise_on_init
+        return cls
+    inst = MagicMock()
+    inst.name = name
+    inst.disabled = disabled
+    inst.description = description
+    inst.categories = categories or []
+    field_mocks = {
+        fname: MagicMock(description=fdesc) for fname, fdesc in (fields or {}).items()
+    }
+    inst.input_schema.model_fields = field_mocks
+    inst.input_schema.get_credentials_fields_info.return_value = {}
+    cls.return_value = inst
+    return cls
+
+
+# ---------------------------------------------------------------------------
+# _get_enabled_blocks
+# ---------------------------------------------------------------------------
+
+
+def test_get_enabled_blocks_filters_disabled():
+    """Disabled blocks are excluded."""
+    blocks = {
+        "enabled": _make_block_class(name="E", disabled=False),
+        "disabled": _make_block_class(name="D", disabled=True),
+    }
+    with patch(
+        "backend.api.features.store.content_handlers.get_blocks", return_value=blocks
+    ):
+        result = _get_enabled_blocks()
+    assert list(result.keys()) == ["enabled"]
+
+
+def test_get_enabled_blocks_skips_broken():
+    """Blocks that raise on init are skipped without crashing."""
+    blocks = {
+        "good": _make_block_class(name="Good"),
+        "bad": _make_block_class(raise_on_init=RuntimeError("boom")),
+    }
+    with patch(
+        "backend.api.features.store.content_handlers.get_blocks", return_value=blocks
+    ):
+        result = _get_enabled_blocks()
+    assert list(result.keys()) == ["good"]
+
+
+def test_get_enabled_blocks_cached():
+    """_get_enabled_blocks() calls get_blocks() only once across multiple calls."""
+    blocks = {"b1": _make_block_class(name="B1")}
+    with patch(
+        "backend.api.features.store.content_handlers.get_blocks", return_value=blocks
+    ) as mock_get_blocks:
+        result1 = _get_enabled_blocks()
+        result2 = _get_enabled_blocks()
+    assert result1 is result2
+    mock_get_blocks.assert_called_once()
+
+
+# ---------------------------------------------------------------------------
+# StoreAgentHandler
+# ---------------------------------------------------------------------------
+
+
 @pytest.mark.asyncio(loop_scope="session")
 async def test_store_agent_handler_get_missing_items(mocker):
     """Test StoreAgentHandler fetches approved agents without embeddings."""
     handler = StoreAgentHandler()
 
-    # Mock database query
     mock_missing = [
         {
             "id": "agent-1",
@@ -54,9 +140,7 @@ async def test_store_agent_handler_get_stats(mocker):
     """Test StoreAgentHandler returns correct stats."""
     handler = StoreAgentHandler()
 
-    # Mock approved count query
     mock_approved = [{"count": 50}]
-    # Mock embedded count query
     mock_embedded = [{"count": 30}]
 
     with patch(
@@ -70,74 +154,130 @@ async def test_store_agent_handler_get_stats(mocker):
         assert stats["without_embeddings"] == 20
 
 
+# ---------------------------------------------------------------------------
+# BlockHandler
+# ---------------------------------------------------------------------------
+
+
 @pytest.mark.asyncio(loop_scope="session")
-async def test_block_handler_get_missing_items(mocker):
+async def test_block_handler_get_missing_items():
     """Test BlockHandler discovers blocks without embeddings."""
     handler = BlockHandler()
 
-    # Mock get_blocks to return test blocks
-    mock_block_class = MagicMock()
-    mock_block_instance = MagicMock()
-    mock_block_instance.name = "Calculator Block"
-    mock_block_instance.description = "Performs calculations"
-    mock_block_instance.categories = [MagicMock(value="MATH")]
-    mock_block_instance.disabled = False
-    mock_field = MagicMock()
-    mock_field.description = "Math expression to evaluate"
-    mock_block_instance.input_schema.model_fields = {"expression": mock_field}
-    mock_block_instance.input_schema.get_credentials_fields_info.return_value = {}
-    mock_block_class.return_value = mock_block_instance
-
-    mock_blocks = {"block-uuid-1": mock_block_class}
-
-    # Mock existing embeddings query (no embeddings exist)
-    mock_existing = []
+    blocks = {
+        "block-uuid-1": _make_block_class(
+            name="CalculatorBlock",
+            description="Performs calculations",
+            categories=[MagicMock(value="MATH")],
+            fields={"expression": "Math expression to evaluate"},
+        ),
+    }
 
     with patch(
-        "backend.blocks.get_blocks",
-        return_value=mock_blocks,
+        "backend.api.features.store.content_handlers.get_blocks", return_value=blocks
     ):
         with patch(
             "backend.api.features.store.content_handlers.query_raw_with_schema",
-            return_value=mock_existing,
+            return_value=[],
         ):
             items = await handler.get_missing_items(batch_size=10)
 
             assert len(items) == 1
             assert items[0].content_id == "block-uuid-1"
             assert items[0].content_type == ContentType.BLOCK
+            # CamelCase should be split in searchable text and metadata name
             assert "Calculator Block" in items[0].searchable_text
             assert "Performs calculations" in items[0].searchable_text
             assert "MATH" in items[0].searchable_text
             assert "expression: Math expression" in items[0].searchable_text
+            assert items[0].metadata["name"] == "Calculator Block"
             assert items[0].user_id is None
 
 
 @pytest.mark.asyncio(loop_scope="session")
-async def test_block_handler_get_stats(mocker):
+async def test_block_handler_get_missing_items_splits_camelcase():
+    """CamelCase block names are split for better search indexing."""
+    handler = BlockHandler()
+
+    blocks = {
+        "ai-block": _make_block_class(name="AITextGeneratorBlock"),
+    }
+
+    with patch(
+        "backend.api.features.store.content_handlers.get_blocks", return_value=blocks
+    ):
+        with patch(
+            "backend.api.features.store.content_handlers.query_raw_with_schema",
+            return_value=[],
+        ):
+            items = await handler.get_missing_items(batch_size=10)
+
+            assert len(items) == 1
+            assert "AI Text Generator Block" in items[0].searchable_text
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_block_handler_get_missing_items_batch_size_zero():
+    """batch_size=0 returns an empty list; the DB is still queried to find missing IDs."""
+    handler = BlockHandler()
+
+    blocks = {"b1": _make_block_class(name="B1")}
+
+    with patch(
+        "backend.api.features.store.content_handlers.get_blocks", return_value=blocks
+    ):
+        with patch(
+            "backend.api.features.store.content_handlers.query_raw_with_schema",
+            return_value=[],
+        ) as mock_query:
+            items = await handler.get_missing_items(batch_size=0)
+            assert items == []
+            # DB query is still issued to learn which blocks lack embeddings;
+            # the empty result comes from itertools.islice limiting to 0 items.
+            mock_query.assert_called_once()
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_block_handler_disabled_dont_exhaust_batch():
+    """Disabled blocks don't consume batch budget, so enabled blocks get indexed."""
+    handler = BlockHandler()
+
+    # 5 disabled + 3 enabled, batch_size=2
+    blocks = {
+        **{
+            f"dis-{i}": _make_block_class(name=f"D{i}", disabled=True) for i in range(5)
+        },
+        **{f"en-{i}": _make_block_class(name=f"E{i}") for i in range(3)},
+    }
+
+    with patch(
+        "backend.api.features.store.content_handlers.get_blocks", return_value=blocks
+    ):
+        with patch(
+            "backend.api.features.store.content_handlers.query_raw_with_schema",
+            return_value=[],
+        ):
+            items = await handler.get_missing_items(batch_size=2)
+
+            assert len(items) == 2
+            assert all(item.content_id.startswith("en-") for item in items)
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_block_handler_get_stats():
     """Test BlockHandler returns correct stats."""
     handler = BlockHandler()
 
-    # Mock get_blocks - each block class returns an instance with disabled=False
-    def make_mock_block_class():
-        mock_class = MagicMock()
-        mock_instance = MagicMock()
-        mock_instance.disabled = False
-        mock_class.return_value = mock_instance
-        return mock_class
-
-    mock_blocks = {
-        "block-1": make_mock_block_class(),
-        "block-2": make_mock_block_class(),
-        "block-3": make_mock_block_class(),
+    blocks = {
+        "block-1": _make_block_class(name="B1"),
+        "block-2": _make_block_class(name="B2"),
+        "block-3": _make_block_class(name="B3"),
     }
 
-    # Mock embedded count query (2 blocks have embeddings)
     mock_embedded = [{"count": 2}]
 
     with patch(
-        "backend.blocks.get_blocks",
-        return_value=mock_blocks,
+        "backend.api.features.store.content_handlers.get_blocks", return_value=blocks
     ):
         with patch(
             "backend.api.features.store.content_handlers.query_raw_with_schema",
@@ -150,21 +290,123 @@ async def test_block_handler_get_stats(mocker):
             assert stats["without_embeddings"] == 1
 
 
+@pytest.mark.asyncio(loop_scope="session")
+async def test_block_handler_get_stats_skips_broken():
+    """get_stats skips broken blocks instead of crashing."""
+    handler = BlockHandler()
+
+    blocks = {
+        "good": _make_block_class(name="Good"),
+        "bad": _make_block_class(raise_on_init=RuntimeError("boom")),
+    }
+
+    mock_embedded = [{"count": 1}]
+
+    with patch(
+        "backend.api.features.store.content_handlers.get_blocks", return_value=blocks
+    ):
+        with patch(
+            "backend.api.features.store.content_handlers.query_raw_with_schema",
+            return_value=mock_embedded,
+        ):
+            stats = await handler.get_stats()
+
+            assert stats["total"] == 1  # only the good block
+            assert stats["with_embeddings"] == 1
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_block_handler_handles_none_name():
+    """When block.name is None the fallback display name logic is used."""
+    handler = BlockHandler()
+
+    blocks = {
+        "none-name-block": _make_block_class(
+            name="placeholder",  # will be overridden to None below
+            description="A block with no name",
+        ),
+    }
+    # Override the name to None after construction so _make_block_class
+    # doesn't interfere with the mock wiring.
+    blocks["none-name-block"].return_value.name = None
+
+    with patch(
+        "backend.api.features.store.content_handlers.get_blocks", return_value=blocks
+    ):
+        with patch(
+            "backend.api.features.store.content_handlers.query_raw_with_schema",
+            return_value=[],
+        ):
+            items = await handler.get_missing_items(batch_size=10)
+
+            assert len(items) == 1
+            # display_name should be "" because block.name is None
+            # searchable_text should still contain the description
+            assert "A block with no name" in items[0].searchable_text
+            # metadata["name"] falls back to block_id when both display_name
+            # and block.name are falsy, ensuring it is always a non-empty string.
+            assert items[0].metadata["name"] == "none-name-block"
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_block_handler_handles_empty_attributes():
+    """Test BlockHandler handles blocks with empty/falsy attribute values."""
+    handler = BlockHandler()
+
+    blocks = {"block-minimal": _make_block_class(name="Minimal Block")}
+
+    with patch(
+        "backend.api.features.store.content_handlers.get_blocks", return_value=blocks
+    ):
+        with patch(
+            "backend.api.features.store.content_handlers.query_raw_with_schema",
+            return_value=[],
+        ):
+            items = await handler.get_missing_items(batch_size=10)
+
+            assert len(items) == 1
+            assert items[0].searchable_text == "Minimal Block"
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_block_handler_skips_failed_blocks():
+    """Test BlockHandler skips blocks that fail to instantiate."""
+    handler = BlockHandler()
+
+    blocks = {
+        "good-block": _make_block_class(name="Good Block", description="Works fine"),
+        "bad-block": _make_block_class(raise_on_init=Exception("Instantiation failed")),
+    }
+
+    with patch(
+        "backend.api.features.store.content_handlers.get_blocks", return_value=blocks
+    ):
+        with patch(
+            "backend.api.features.store.content_handlers.query_raw_with_schema",
+            return_value=[],
+        ):
+            items = await handler.get_missing_items(batch_size=10)
+
+            assert len(items) == 1
+            assert items[0].content_id == "good-block"
+
+
+# ---------------------------------------------------------------------------
+# DocumentationHandler
+# ---------------------------------------------------------------------------
+
+
 @pytest.mark.asyncio(loop_scope="session")
 async def test_documentation_handler_get_missing_items(tmp_path, mocker):
     """Test DocumentationHandler discovers docs without embeddings."""
     handler = DocumentationHandler()
 
-    # Create temporary docs directory with test files
     docs_root = tmp_path / "docs"
     docs_root.mkdir()
-
     (docs_root / "guide.md").write_text("# Getting Started\n\nThis is a guide.")
     (docs_root / "api.mdx").write_text("# API Reference\n\nAPI documentation.")
 
-    # Mock _get_docs_root to return temp dir
     with patch.object(handler, "_get_docs_root", return_value=docs_root):
-        # Mock existing embeddings query (no embeddings exist)
         with patch(
             "backend.api.features.store.content_handlers.query_raw_with_schema",
             return_value=[],
@@ -173,7 +415,6 @@ async def test_documentation_handler_get_missing_items(tmp_path, mocker):
 
             assert len(items) == 2
 
-            # Check guide.md (content_id format: doc_path::section_index)
             guide_item = next(
                 (item for item in items if item.content_id == "guide.md::0"), None
             )
@@ -184,7 +425,6 @@ async def test_documentation_handler_get_missing_items(tmp_path, mocker):
             assert guide_item.metadata["doc_title"] == "Getting Started"
             assert guide_item.user_id is None
 
-            # Check api.mdx (content_id format: doc_path::section_index)
             api_item = next(
                 (item for item in items if item.content_id == "api.mdx::0"), None
             )
@@ -197,14 +437,12 @@ async def test_documentation_handler_get_stats(tmp_path, mocker):
     """Test DocumentationHandler returns correct stats."""
     handler = DocumentationHandler()
 
-    # Create temporary docs directory
     docs_root = tmp_path / "docs"
     docs_root.mkdir()
     (docs_root / "doc1.md").write_text("# Doc 1")
     (docs_root / "doc2.md").write_text("# Doc 2")
     (docs_root / "doc3.mdx").write_text("# Doc 3")
 
-    # Mock embedded count query (1 doc has embedding)
     mock_embedded = [{"count": 1}]
 
     with patch.object(handler, "_get_docs_root", return_value=docs_root):
@@ -224,13 +462,11 @@ async def test_documentation_handler_title_extraction(tmp_path):
     """Test DocumentationHandler extracts title from markdown heading."""
     handler = DocumentationHandler()
 
-    # Test with heading
     doc_with_heading = tmp_path / "with_heading.md"
     doc_with_heading.write_text("# My Title\n\nContent here")
     title = handler._extract_doc_title(doc_with_heading)
     assert title == "My Title"
 
-    # Test without heading
     doc_without_heading = tmp_path / "no-heading.md"
     doc_without_heading.write_text("Just content, no heading")
     title = handler._extract_doc_title(doc_without_heading)
@@ -242,7 +478,6 @@ async def test_documentation_handler_markdown_chunking(tmp_path):
     """Test DocumentationHandler chunks markdown by headings."""
     handler = DocumentationHandler()
 
-    # Test document with multiple sections
     doc_with_sections = tmp_path / "sections.md"
     doc_with_sections.write_text(
         "# Document Title\n\n"
@@ -254,7 +489,6 @@ async def test_documentation_handler_markdown_chunking(tmp_path):
     )
     sections = handler._chunk_markdown_by_headings(doc_with_sections)
 
-    # Should have 3 sections: intro (with doc title), section one, section two
     assert len(sections) == 3
     assert sections[0].title == "Document Title"
     assert sections[0].index == 0
@@ -268,7 +502,6 @@ async def test_documentation_handler_markdown_chunking(tmp_path):
     assert sections[2].index == 2
     assert "Content for section two" in sections[2].content
 
-    # Test document without headings
     doc_no_sections = tmp_path / "no-sections.md"
     doc_no_sections.write_text("Just plain content without any headings.")
     sections = handler._chunk_markdown_by_headings(doc_no_sections)
@@ -282,21 +515,39 @@ async def test_documentation_handler_section_content_ids():
     """Test DocumentationHandler creates and parses section content IDs."""
     handler = DocumentationHandler()
 
-    # Test making content ID
     content_id = handler._make_section_content_id("docs/guide.md", 2)
     assert content_id == "docs/guide.md::2"
 
-    # Test parsing content ID
     doc_path, section_index = handler._parse_section_content_id("docs/guide.md::2")
     assert doc_path == "docs/guide.md"
     assert section_index == 2
 
-    # Test parsing legacy format (no section index)
     doc_path, section_index = handler._parse_section_content_id("docs/old-format.md")
     assert doc_path == "docs/old-format.md"
     assert section_index == 0
 
 
+@pytest.mark.asyncio(loop_scope="session")
+async def test_documentation_handler_missing_docs_directory():
+    """Test DocumentationHandler handles missing docs directory gracefully."""
+    handler = DocumentationHandler()
+
+    fake_path = Path("/nonexistent/docs")
+    with patch.object(handler, "_get_docs_root", return_value=fake_path):
+        items = await handler.get_missing_items(batch_size=10)
+        assert items == []
+
+        stats = await handler.get_stats()
+        assert stats["total"] == 0
+        assert stats["with_embeddings"] == 0
+        assert stats["without_embeddings"] == 0
+
+
+# ---------------------------------------------------------------------------
+# Registry
+# ---------------------------------------------------------------------------
+
+
 @pytest.mark.asyncio(loop_scope="session")
 async def test_content_handlers_registry():
     """Test all content types are registered."""
@@ -307,88 +558,3 @@ async def test_content_handlers_registry():
     assert isinstance(CONTENT_HANDLERS[ContentType.STORE_AGENT], StoreAgentHandler)
     assert isinstance(CONTENT_HANDLERS[ContentType.BLOCK], BlockHandler)
     assert isinstance(CONTENT_HANDLERS[ContentType.DOCUMENTATION], DocumentationHandler)
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_block_handler_handles_empty_attributes():
-    """Test BlockHandler handles blocks with empty/falsy attribute values."""
-    handler = BlockHandler()
-
-    # Mock block with empty values (all attributes exist but are falsy)
-    mock_block_class = MagicMock()
-    mock_block_instance = MagicMock()
-    mock_block_instance.name = "Minimal Block"
-    mock_block_instance.disabled = False
-    mock_block_instance.description = ""
-    mock_block_instance.categories = set()
-    mock_block_instance.input_schema.model_fields = {}
-    mock_block_instance.input_schema.get_credentials_fields_info.return_value = {}
-    mock_block_class.return_value = mock_block_instance
-
-    mock_blocks = {"block-minimal": mock_block_class}
-
-    with patch(
-        "backend.blocks.get_blocks",
-        return_value=mock_blocks,
-    ):
-        with patch(
-            "backend.api.features.store.content_handlers.query_raw_with_schema",
-            return_value=[],
-        ):
-            items = await handler.get_missing_items(batch_size=10)
-
-            assert len(items) == 1
-            assert items[0].searchable_text == "Minimal Block"
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_block_handler_skips_failed_blocks():
-    """Test BlockHandler skips blocks that fail to instantiate."""
-    handler = BlockHandler()
-
-    # Mock one good block and one bad block
-    good_block = MagicMock()
-    good_instance = MagicMock()
-    good_instance.name = "Good Block"
-    good_instance.description = "Works fine"
-    good_instance.categories = []
-    good_instance.disabled = False
-    good_instance.input_schema.model_fields = {}
-    good_instance.input_schema.get_credentials_fields_info.return_value = {}
-    good_block.return_value = good_instance
-
-    bad_block = MagicMock()
-    bad_block.side_effect = Exception("Instantiation failed")
-
-    mock_blocks = {"good-block": good_block, "bad-block": bad_block}
-
-    with patch(
-        "backend.blocks.get_blocks",
-        return_value=mock_blocks,
-    ):
-        with patch(
-            "backend.api.features.store.content_handlers.query_raw_with_schema",
-            return_value=[],
-        ):
-            items = await handler.get_missing_items(batch_size=10)
-
-            # Should only get the good block
-            assert len(items) == 1
-            assert items[0].content_id == "good-block"
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_documentation_handler_missing_docs_directory():
-    """Test DocumentationHandler handles missing docs directory gracefully."""
-    handler = DocumentationHandler()
-
-    # Mock _get_docs_root to return non-existent path
-    fake_path = Path("/nonexistent/docs")
-    with patch.object(handler, "_get_docs_root", return_value=fake_path):
-        items = await handler.get_missing_items(batch_size=10)
-        assert items == []
-
-        stats = await handler.get_stats()
-        assert stats["total"] == 0
-        assert stats["with_embeddings"] == 0
-        assert stats["without_embeddings"] == 0

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

@@ -26,7 +26,7 @@ async def test_get_store_agents(mocker):
     mock_agents = [
         prisma.models.StoreAgent(
             listing_id="test-id",
-            storeListingVersionId="version123",
+            listing_version_id="version123",
             slug="test-agent",
             agent_name="Test Agent",
             agent_video=None,
@@ -40,11 +40,11 @@ async def test_get_store_agents(mocker):
             runs=10,
             rating=4.5,
             versions=["1.0"],
-            agentGraphVersions=["1"],
-            agentGraphId="test-graph-id",
+            graph_id="test-graph-id",
+            graph_versions=["1"],
             updated_at=datetime.now(),
             is_available=False,
-            useForOnboarding=False,
+            use_for_onboarding=False,
         )
     ]
 
@@ -68,10 +68,10 @@ async def test_get_store_agents(mocker):
 
 @pytest.mark.asyncio(loop_scope="session")
 async def test_get_store_agent_details(mocker):
-    # Mock data
+    # Mock data - StoreAgent view already contains the active version data
     mock_agent = prisma.models.StoreAgent(
         listing_id="test-id",
-        storeListingVersionId="version123",
+        listing_version_id="version123",
         slug="test-agent",
         agent_name="Test Agent",
         agent_video="video.mp4",
@@ -85,102 +85,38 @@ async def test_get_store_agent_details(mocker):
         runs=10,
         rating=4.5,
         versions=["1.0"],
-        agentGraphVersions=["1"],
-        agentGraphId="test-graph-id",
-        updated_at=datetime.now(),
-        is_available=False,
-        useForOnboarding=False,
-    )
-
-    # Mock active version agent (what we want to return for active version)
-    mock_active_agent = prisma.models.StoreAgent(
-        listing_id="test-id",
-        storeListingVersionId="active-version-id",
-        slug="test-agent",
-        agent_name="Test Agent Active",
-        agent_video="active_video.mp4",
-        agent_image=["active_image.jpg"],
-        featured=False,
-        creator_username="creator",
-        creator_avatar="avatar.jpg",
-        sub_heading="Test heading active",
-        description="Test description active",
-        categories=["test"],
-        runs=15,
-        rating=4.8,
-        versions=["1.0", "2.0"],
-        agentGraphVersions=["1", "2"],
-        agentGraphId="test-graph-id-active",
+        graph_id="test-graph-id",
+        graph_versions=["1"],
         updated_at=datetime.now(),
         is_available=True,
-        useForOnboarding=False,
+        use_for_onboarding=False,
     )
 
-    # Create a mock StoreListing result
-    mock_store_listing = mocker.MagicMock()
-    mock_store_listing.activeVersionId = "active-version-id"
-    mock_store_listing.hasApprovedVersion = True
-    mock_store_listing.ActiveVersion = mocker.MagicMock()
-    mock_store_listing.ActiveVersion.recommendedScheduleCron = None
-
-    # Mock StoreAgent prisma call - need to handle multiple calls
+    # Mock StoreAgent prisma call
     mock_store_agent = mocker.patch("prisma.models.StoreAgent.prisma")
-
-    # Set up side_effect to return different results for different calls
-    def mock_find_first_side_effect(*args, **kwargs):
-        where_clause = kwargs.get("where", {})
-        if "storeListingVersionId" in where_clause:
-            # Second call for active version
-            return mock_active_agent
-        else:
-            # First call for initial lookup
-            return mock_agent
-
-    mock_store_agent.return_value.find_first = mocker.AsyncMock(
-        side_effect=mock_find_first_side_effect
-    )
-
-    # Mock Profile prisma call
-    mock_profile = mocker.MagicMock()
-    mock_profile.userId = "user-id-123"
-    mock_profile_db = mocker.patch("prisma.models.Profile.prisma")
-    mock_profile_db.return_value.find_first = mocker.AsyncMock(
-        return_value=mock_profile
-    )
-
-    # Mock StoreListing prisma call
-    mock_store_listing_db = mocker.patch("prisma.models.StoreListing.prisma")
-    mock_store_listing_db.return_value.find_first = mocker.AsyncMock(
-        return_value=mock_store_listing
-    )
+    mock_store_agent.return_value.find_first = mocker.AsyncMock(return_value=mock_agent)
 
     # Call function
     result = await db.get_store_agent_details("creator", "test-agent")
 
-    # Verify results - should use active version data
+    # Verify results - constructed from the StoreAgent view
     assert result.slug == "test-agent"
-    assert result.agent_name == "Test Agent Active"  # From active version
-    assert result.active_version_id == "active-version-id"
+    assert result.agent_name == "Test Agent"
+    assert result.active_version_id == "version123"
     assert result.has_approved_version is True
-    assert (
-        result.store_listing_version_id == "active-version-id"
-    )  # Should be active version ID
+    assert result.store_listing_version_id == "version123"
+    assert result.graph_id == "test-graph-id"
+    assert result.runs == 10
+    assert result.rating == 4.5
 
-    # Verify mocks called correctly - now expecting 2 calls
-    assert mock_store_agent.return_value.find_first.call_count == 2
-
-    # Check the specific calls
-    calls = mock_store_agent.return_value.find_first.call_args_list
-    assert calls[0] == mocker.call(
+    # Verify single StoreAgent lookup
+    mock_store_agent.return_value.find_first.assert_called_once_with(
         where={"creator_username": "creator", "slug": "test-agent"}
     )
-    assert calls[1] == mocker.call(where={"storeListingVersionId": "active-version-id"})
-
-    mock_store_listing_db.return_value.find_first.assert_called_once()
 
 
 @pytest.mark.asyncio(loop_scope="session")
-async def test_get_store_creator_details(mocker):
+async def test_get_store_creator(mocker):
     # Mock data
     mock_creator_data = prisma.models.Creator(
         name="Test Creator",
@@ -202,7 +138,7 @@ async def test_get_store_creator_details(mocker):
     mock_creator.return_value.find_unique.return_value = mock_creator_data
 
     # Call function
-    result = await db.get_store_creator_details("creator")
+    result = await db.get_store_creator("creator")
 
     # Verify results
     assert result.username == "creator"
@@ -218,61 +154,110 @@ async def test_get_store_creator_details(mocker):
 
 @pytest.mark.asyncio(loop_scope="session")
 async def test_create_store_submission(mocker):
-    # Mock data
+    now = datetime.now()
+
+    # Mock agent graph (with no pending submissions) and user with profile
+    mock_profile = prisma.models.Profile(
+        id="profile-id",
+        userId="user-id",
+        name="Test User",
+        username="testuser",
+        description="Test",
+        isFeatured=False,
+        links=[],
+        createdAt=now,
+        updatedAt=now,
+    )
+    mock_user = prisma.models.User(
+        id="user-id",
+        email="test@example.com",
+        createdAt=now,
+        updatedAt=now,
+        Profile=[mock_profile],
+        emailVerified=True,
+        metadata="{}",  # type: ignore[reportArgumentType]
+        integrations="",
+        maxEmailsPerDay=1,
+        notifyOnAgentRun=True,
+        notifyOnZeroBalance=True,
+        notifyOnLowBalance=True,
+        notifyOnBlockExecutionFailed=True,
+        notifyOnContinuousAgentError=True,
+        notifyOnDailySummary=True,
+        notifyOnWeeklySummary=True,
+        notifyOnMonthlySummary=True,
+        notifyOnAgentApproved=True,
+        notifyOnAgentRejected=True,
+        timezone="Europe/Delft",
+    )
     mock_agent = prisma.models.AgentGraph(
         id="agent-id",
         version=1,
         userId="user-id",
-        createdAt=datetime.now(),
+        createdAt=now,
         isActive=True,
+        StoreListingVersions=[],
+        User=mock_user,
     )
 
-    mock_listing = prisma.models.StoreListing(
+    # Mock the created StoreListingVersion (returned by create)
+    mock_store_listing_obj = prisma.models.StoreListing(
         id="listing-id",
-        createdAt=datetime.now(),
-        updatedAt=datetime.now(),
+        createdAt=now,
+        updatedAt=now,
         isDeleted=False,
         hasApprovedVersion=False,
         slug="test-agent",
         agentGraphId="agent-id",
-        agentGraphVersion=1,
         owningUserId="user-id",
-        Versions=[
-            prisma.models.StoreListingVersion(
-                id="version-id",
-                agentGraphId="agent-id",
-                agentGraphVersion=1,
-                name="Test Agent",
-                description="Test description",
-                createdAt=datetime.now(),
-                updatedAt=datetime.now(),
-                subHeading="Test heading",
-                imageUrls=["image.jpg"],
-                categories=["test"],
-                isFeatured=False,
-                isDeleted=False,
-                version=1,
-                storeListingId="listing-id",
-                submissionStatus=prisma.enums.SubmissionStatus.PENDING,
-                isAvailable=True,
-            )
-        ],
         useForOnboarding=False,
     )
+    mock_version = prisma.models.StoreListingVersion(
+        id="version-id",
+        agentGraphId="agent-id",
+        agentGraphVersion=1,
+        name="Test Agent",
+        description="Test description",
+        createdAt=now,
+        updatedAt=now,
+        subHeading="",
+        imageUrls=[],
+        categories=[],
+        isFeatured=False,
+        isDeleted=False,
+        version=1,
+        storeListingId="listing-id",
+        submissionStatus=prisma.enums.SubmissionStatus.PENDING,
+        isAvailable=True,
+        submittedAt=now,
+        StoreListing=mock_store_listing_obj,
+    )
 
     # Mock prisma calls
     mock_agent_graph = mocker.patch("prisma.models.AgentGraph.prisma")
     mock_agent_graph.return_value.find_first = mocker.AsyncMock(return_value=mock_agent)
 
-    mock_store_listing = mocker.patch("prisma.models.StoreListing.prisma")
-    mock_store_listing.return_value.find_first = mocker.AsyncMock(return_value=None)
-    mock_store_listing.return_value.create = mocker.AsyncMock(return_value=mock_listing)
+    # Mock transaction context manager
+    mock_tx = mocker.MagicMock()
+    mocker.patch(
+        "backend.api.features.store.db.transaction",
+        return_value=mocker.AsyncMock(
+            __aenter__=mocker.AsyncMock(return_value=mock_tx),
+            __aexit__=mocker.AsyncMock(return_value=False),
+        ),
+    )
+
+    mock_sl = mocker.patch("prisma.models.StoreListing.prisma")
+    mock_sl.return_value.find_unique = mocker.AsyncMock(return_value=None)
+
+    mock_slv = mocker.patch("prisma.models.StoreListingVersion.prisma")
+    mock_slv.return_value.create = mocker.AsyncMock(return_value=mock_version)
 
     # Call function
     result = await db.create_store_submission(
         user_id="user-id",
-        agent_id="agent-id",
-        agent_version=1,
+        graph_id="agent-id",
+        graph_version=1,
         slug="test-agent",
         name="Test Agent",
         description="Test description",
@@ -281,11 +266,11 @@ async def test_create_store_submission(mocker):
     # Verify results
     assert result.name == "Test Agent"
     assert result.description == "Test description"
-    assert result.store_listing_version_id == "version-id"
+    assert result.listing_version_id == "version-id"
 
     # Verify mocks called correctly
     mock_agent_graph.return_value.find_first.assert_called_once()
-    mock_store_listing.return_value.create.assert_called_once()
+    mock_slv.return_value.create.assert_called_once()
 
 
 @pytest.mark.asyncio(loop_scope="session")
@@ -318,7 +303,6 @@ async def test_update_profile(mocker):
         description="Test description",
         links=["link1"],
         avatar_url="avatar.jpg",
-        is_featured=False,
     )
 
     # Call function
@@ -389,7 +373,7 @@ async def test_get_store_agents_with_search_and_filters_parameterized():
         creators=["creator1'; DROP TABLE Users; --", "creator2"],
         category="AI'; DELETE FROM StoreAgent; --",
         featured=True,
-        sorted_by="rating",
+        sorted_by=db.StoreAgentsSortOptions.RATING,
         page=1,
         page_size=20,
     )

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

@@ -15,6 +15,7 @@ from prisma.enums import ContentType
 from tiktoken import encoding_for_model
 
 from backend.api.features.store.content_handlers import CONTENT_HANDLERS
+from backend.blocks import get_blocks
 from backend.data.db import execute_raw_with_schema, query_raw_with_schema
 from backend.util.clients import get_openai_client
 from backend.util.json import dumps
@@ -662,8 +663,6 @@ async def cleanup_orphaned_embeddings() -> dict[str, Any]:
                 )
                 current_ids = {row["id"] for row in valid_agents}
             elif content_type == ContentType.BLOCK:
-                from backend.blocks import get_blocks
-
                 current_ids = set(get_blocks().keys())
             elif content_type == ContentType.DOCUMENTATION:
                 # Use DocumentationHandler to get section-based content IDs

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

@@ -57,12 +57,6 @@ class StoreError(ValueError):
     pass
 
 
-class AgentNotFoundError(NotFoundError):
-    """Raised when an agent is not found"""
-
-    pass
-
-
 class CreatorNotFoundError(NotFoundError):
     """Raised when a creator is not found"""
 

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

@@ -31,12 +31,10 @@ logger = logging.getLogger(__name__)
 
 
 def tokenize(text: str) -> list[str]:
-    """Simple tokenizer for BM25 - lowercase and split on non-alphanumeric."""
+    """Tokenize text for BM25."""
     if not text:
         return []
-    # Lowercase and split on non-alphanumeric characters
-    tokens = re.findall(r"\b\w+\b", text.lower())
-    return tokens
+    return re.findall(r"\b\w+\b", text.lower())
 
 
 def bm25_rerank(
@@ -568,7 +566,7 @@ async def hybrid_search(
             SELECT uce."contentId" as "storeListingVersionId"
             FROM {{schema_prefix}}"UnifiedContentEmbedding" uce
             INNER JOIN {{schema_prefix}}"StoreAgent" sa
-                ON uce."contentId" = sa."storeListingVersionId"
+                ON uce."contentId" = sa.listing_version_id
             WHERE uce."contentType" = 'STORE_AGENT'::{{schema_prefix}}"ContentType"
             AND uce."userId" IS NULL
             AND uce.search @@ plainto_tsquery('english', {query_param})
@@ -582,7 +580,7 @@ async def hybrid_search(
                 SELECT uce."contentId", uce.embedding
                 FROM {{schema_prefix}}"UnifiedContentEmbedding" uce
                 INNER JOIN {{schema_prefix}}"StoreAgent" sa
-                    ON uce."contentId" = sa."storeListingVersionId"
+                    ON uce."contentId" = sa.listing_version_id
                 WHERE uce."contentType" = 'STORE_AGENT'::{{schema_prefix}}"ContentType"
                 AND uce."userId" IS NULL
                 AND {where_clause}
@@ -605,7 +603,7 @@ async def hybrid_search(
                 sa.featured,
                 sa.is_available,
                 sa.updated_at,
-                sa."agentGraphId",
+                sa.graph_id,
                 -- Searchable text for BM25 reranking
                 COALESCE(sa.agent_name, '') || ' ' || COALESCE(sa.sub_heading, '') || ' ' || COALESCE(sa.description, '') as searchable_text,
                 -- Semantic score
@@ -627,9 +625,9 @@ async def hybrid_search(
                 sa.runs as popularity_raw
             FROM candidates c
             INNER JOIN {{schema_prefix}}"StoreAgent" sa
-                ON c."storeListingVersionId" = sa."storeListingVersionId"
+                ON c."storeListingVersionId" = sa.listing_version_id
             INNER JOIN {{schema_prefix}}"UnifiedContentEmbedding" uce
-                ON sa."storeListingVersionId" = uce."contentId"
+                ON sa.listing_version_id = uce."contentId"
                 AND uce."contentType" = 'STORE_AGENT'::{{schema_prefix}}"ContentType"
         ),
         max_vals AS (
@@ -665,7 +663,7 @@ async def hybrid_search(
                 featured,
                 is_available,
                 updated_at,
-                "agentGraphId",
+                graph_id,
                 searchable_text,
                 semantic_score,
                 lexical_score,

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

@@ -14,9 +14,27 @@ from backend.api.features.store.hybrid_search import (
     HybridSearchWeights,
     UnifiedSearchWeights,
     hybrid_search,
+    tokenize,
     unified_hybrid_search,
 )
 
+# ---------------------------------------------------------------------------
+# tokenize (BM25)
+# ---------------------------------------------------------------------------
+
+
+@pytest.mark.parametrize(
+    "input_text, expected",
+    [
+        ("AITextGeneratorBlock", ["aitextgeneratorblock"]),
+        ("hello world", ["hello", "world"]),
+        ("", []),
+        ("HTTPRequest", ["httprequest"]),
+    ],
+)
+def test_tokenize(input_text: str, expected: list[str]):
+    assert tokenize(input_text) == expected
+
 
 @pytest.mark.asyncio(loop_scope="session")
 @pytest.mark.integration

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

@@ -1,11 +1,14 @@
 import datetime
-from typing import List
+from typing import TYPE_CHECKING, List, Self
 
 import prisma.enums
 import pydantic
 
 from backend.util.models import Pagination
 
+if TYPE_CHECKING:
+    import prisma.models
+
 
 class ChangelogEntry(pydantic.BaseModel):
     version: str
@@ -13,9 +16,9 @@ class ChangelogEntry(pydantic.BaseModel):
     date: datetime.datetime
 
 
-class MyAgent(pydantic.BaseModel):
-    agent_id: str
-    agent_version: int
+class MyUnpublishedAgent(pydantic.BaseModel):
+    graph_id: str
+    graph_version: int
     agent_name: str
     agent_image: str | None = None
     description: str
@@ -23,8 +26,8 @@ class MyAgent(pydantic.BaseModel):
     recommended_schedule_cron: str | None = None
 
 
-class MyAgentsResponse(pydantic.BaseModel):
-    agents: list[MyAgent]
+class MyUnpublishedAgentsResponse(pydantic.BaseModel):
+    agents: list[MyUnpublishedAgent]
     pagination: Pagination
 
 
@@ -40,6 +43,21 @@ class StoreAgent(pydantic.BaseModel):
     rating: float
     agent_graph_id: str
 
+    @classmethod
+    def from_db(cls, agent: "prisma.models.StoreAgent") -> "StoreAgent":
+        return cls(
+            slug=agent.slug,
+            agent_name=agent.agent_name,
+            agent_image=agent.agent_image[0] if agent.agent_image else "",
+            creator=agent.creator_username or "Needs Profile",
+            creator_avatar=agent.creator_avatar or "",
+            sub_heading=agent.sub_heading,
+            description=agent.description,
+            runs=agent.runs,
+            rating=agent.rating,
+            agent_graph_id=agent.graph_id,
+        )
+
 
 class StoreAgentsResponse(pydantic.BaseModel):
     agents: list[StoreAgent]
@@ -62,81 +80,192 @@ class StoreAgentDetails(pydantic.BaseModel):
     runs: int
     rating: float
     versions: list[str]
-    agentGraphVersions: list[str]
-    agentGraphId: str
+    graph_id: str
+    graph_versions: list[str]
     last_updated: datetime.datetime
     recommended_schedule_cron: str | None = None
 
-    active_version_id: str | None = None
-    has_approved_version: bool = False
+    active_version_id: str
+    has_approved_version: bool
 
     # Optional changelog data when include_changelog=True
     changelog: list[ChangelogEntry] | None = None
 
-
-class Creator(pydantic.BaseModel):
-    name: str
-    username: str
-    description: str
-    avatar_url: str
-    num_agents: int
-    agent_rating: float
-    agent_runs: int
-    is_featured: bool
-
-
-class CreatorsResponse(pydantic.BaseModel):
-    creators: List[Creator]
-    pagination: Pagination
-
-
-class CreatorDetails(pydantic.BaseModel):
-    name: str
-    username: str
-    description: str
-    links: list[str]
-    avatar_url: str
-    agent_rating: float
-    agent_runs: int
-    top_categories: list[str]
+    @classmethod
+    def from_db(cls, agent: "prisma.models.StoreAgent") -> "StoreAgentDetails":
+        return cls(
+            store_listing_version_id=agent.listing_version_id,
+            slug=agent.slug,
+            agent_name=agent.agent_name,
+            agent_video=agent.agent_video or "",
+            agent_output_demo=agent.agent_output_demo or "",
+            agent_image=agent.agent_image,
+            creator=agent.creator_username or "",
+            creator_avatar=agent.creator_avatar or "",
+            sub_heading=agent.sub_heading,
+            description=agent.description,
+            categories=agent.categories,
+            runs=agent.runs,
+            rating=agent.rating,
+            versions=agent.versions,
+            graph_id=agent.graph_id,
+            graph_versions=agent.graph_versions,
+            last_updated=agent.updated_at,
+            recommended_schedule_cron=agent.recommended_schedule_cron,
+            active_version_id=agent.listing_version_id,
+            has_approved_version=True,  # StoreAgent view only has approved agents
+        )
 
 
 class Profile(pydantic.BaseModel):
-    name: str
+    """Marketplace user profile (only attributes that the user can update)"""
+
     username: str
+    name: str
     description: str
+    avatar_url: str | None
     links: list[str]
-    avatar_url: str
-    is_featured: bool = False
+
+
+class ProfileDetails(Profile):
+    """Marketplace user profile (including read-only fields)"""
+
+    is_featured: bool
+
+    @classmethod
+    def from_db(cls, profile: "prisma.models.Profile") -> "ProfileDetails":
+        return cls(
+            name=profile.name,
+            username=profile.username,
+            avatar_url=profile.avatarUrl,
+            description=profile.description,
+            links=profile.links,
+            is_featured=profile.isFeatured,
+        )
+
+
+class CreatorDetails(ProfileDetails):
+    """Marketplace creator profile details, including aggregated stats"""
+
+    num_agents: int
+    agent_runs: int
+    agent_rating: float
+    top_categories: list[str]
+
+    @classmethod
+    def from_db(cls, creator: "prisma.models.Creator") -> "CreatorDetails":  # type: ignore[override]
+        return cls(
+            name=creator.name,
+            username=creator.username,
+            avatar_url=creator.avatar_url,
+            description=creator.description,
+            links=creator.links,
+            is_featured=creator.is_featured,
+            num_agents=creator.num_agents,
+            agent_runs=creator.agent_runs,
+            agent_rating=creator.agent_rating,
+            top_categories=creator.top_categories,
+        )
+
+
+class CreatorsResponse(pydantic.BaseModel):
+    creators: List[CreatorDetails]
+    pagination: Pagination
 
 
 class StoreSubmission(pydantic.BaseModel):
+    # From StoreListing:
     listing_id: str
-    agent_id: str
-    agent_version: int
+    user_id: str
+    slug: str
+
+    # From StoreListingVersion:
+    listing_version_id: str
+    listing_version: int
+    graph_id: str
+    graph_version: int
     name: str
     sub_heading: str
-    slug: str
     description: str
-    instructions: str | None = None
+    instructions: str | None
+    categories: list[str]
     image_urls: list[str]
-    date_submitted: datetime.datetime
-    status: prisma.enums.SubmissionStatus
-    runs: int
-    rating: float
-    store_listing_version_id: str | None = None
-    version: int | None = None  # Actual version number from the database
+    video_url: str | None
+    agent_output_demo_url: str | None
 
+    submitted_at: datetime.datetime | None
+    changes_summary: str | None
+    status: prisma.enums.SubmissionStatus
+    reviewed_at: datetime.datetime | None = None
     reviewer_id: str | None = None
     review_comments: str | None = None  # External comments visible to creator
-    internal_comments: str | None = None  # Private notes for admin use only
-    reviewed_at: datetime.datetime | None = None
-    changes_summary: str | None = None
 
-    # Additional fields for editing
-    video_url: str | None = None
-    agent_output_demo_url: str | None = None
-    categories: list[str] = []
+    # Aggregated from AgentGraphExecutions and StoreListingReviews:
+    run_count: int = 0
+    review_count: int = 0
+    review_avg_rating: float = 0.0
+
+    @classmethod
+    def from_db(cls, _sub: "prisma.models.StoreSubmission") -> Self:
+        """Construct from the StoreSubmission Prisma view."""
+        return cls(
+            listing_id=_sub.listing_id,
+            user_id=_sub.user_id,
+            slug=_sub.slug,
+            listing_version_id=_sub.listing_version_id,
+            listing_version=_sub.listing_version,
+            graph_id=_sub.graph_id,
+            graph_version=_sub.graph_version,
+            name=_sub.name,
+            sub_heading=_sub.sub_heading,
+            description=_sub.description,
+            instructions=_sub.instructions,
+            categories=_sub.categories,
+            image_urls=_sub.image_urls,
+            video_url=_sub.video_url,
+            agent_output_demo_url=_sub.agent_output_demo_url,
+            submitted_at=_sub.submitted_at,
+            changes_summary=_sub.changes_summary,
+            status=_sub.status,
+            reviewed_at=_sub.reviewed_at,
+            reviewer_id=_sub.reviewer_id,
+            review_comments=_sub.review_comments,
+            run_count=_sub.run_count,
+            review_count=_sub.review_count,
+            review_avg_rating=_sub.review_avg_rating,
+        )
+
+    @classmethod
+    def from_listing_version(cls, _lv: "prisma.models.StoreListingVersion") -> Self:
+        """
+        Construct from the StoreListingVersion Prisma model (with StoreListing included)
+        """
+        if not (_l := _lv.StoreListing):
+            raise ValueError("StoreListingVersion must have included StoreListing")
+
+        return cls(
+            listing_id=_l.id,
+            user_id=_l.owningUserId,
+            slug=_l.slug,
+            listing_version_id=_lv.id,
+            listing_version=_lv.version,
+            graph_id=_lv.agentGraphId,
+            graph_version=_lv.agentGraphVersion,
+            name=_lv.name,
+            sub_heading=_lv.subHeading,
+            description=_lv.description,
+            instructions=_lv.instructions,
+            categories=_lv.categories,
+            image_urls=_lv.imageUrls,
+            video_url=_lv.videoUrl,
+            agent_output_demo_url=_lv.agentOutputDemoUrl,
+            submitted_at=_lv.submittedAt,
+            changes_summary=_lv.changesSummary,
+            status=_lv.submissionStatus,
+            reviewed_at=_lv.reviewedAt,
+            reviewer_id=_lv.reviewerId,
+            review_comments=_lv.reviewComments,
+        )
 
 
 class StoreSubmissionsResponse(pydantic.BaseModel):
@@ -144,33 +273,12 @@ class StoreSubmissionsResponse(pydantic.BaseModel):
     pagination: Pagination
 
 
-class StoreListingWithVersions(pydantic.BaseModel):
-    """A store listing with its version history"""
-
-    listing_id: str
-    slug: str
-    agent_id: str
-    agent_version: int
-    active_version_id: str | None = None
-    has_approved_version: bool = False
-    creator_email: str | None = None
-    latest_version: StoreSubmission | None = None
-    versions: list[StoreSubmission] = []
-
-
-class StoreListingsWithVersionsResponse(pydantic.BaseModel):
-    """Response model for listings with version history"""
-
-    listings: list[StoreListingWithVersions]
-    pagination: Pagination
-
-
 class StoreSubmissionRequest(pydantic.BaseModel):
-    agent_id: str = pydantic.Field(
-        ..., min_length=1, description="Agent ID cannot be empty"
+    graph_id: str = pydantic.Field(
+        ..., min_length=1, description="Graph ID cannot be empty"
     )
-    agent_version: int = pydantic.Field(
-        ..., gt=0, description="Agent version must be greater than 0"
+    graph_version: int = pydantic.Field(
+        ..., gt=0, description="Graph version must be greater than 0"
     )
     slug: str
     name: str
@@ -198,12 +306,42 @@ class StoreSubmissionEditRequest(pydantic.BaseModel):
     recommended_schedule_cron: str | None = None
 
 
-class ProfileDetails(pydantic.BaseModel):
-    name: str
-    username: str
-    description: str
-    links: list[str]
-    avatar_url: str | None = None
+class StoreSubmissionAdminView(StoreSubmission):
+    internal_comments: str | None  # Private admin notes
+
+    @classmethod
+    def from_db(cls, _sub: "prisma.models.StoreSubmission") -> Self:
+        return cls(
+            **StoreSubmission.from_db(_sub).model_dump(),
+            internal_comments=_sub.internal_comments,
+        )
+
+    @classmethod
+    def from_listing_version(cls, _lv: "prisma.models.StoreListingVersion") -> Self:
+        return cls(
+            **StoreSubmission.from_listing_version(_lv).model_dump(),
+            internal_comments=_lv.internalComments,
+        )
+
+
+class StoreListingWithVersionsAdminView(pydantic.BaseModel):
+    """A store listing with its version history"""
+
+    listing_id: str
+    graph_id: str
+    slug: str
+    active_listing_version_id: str | None = None
+    has_approved_version: bool = False
+    creator_email: str | None = None
+    latest_version: StoreSubmissionAdminView | None = None
+    versions: list[StoreSubmissionAdminView] = []
+
+
+class StoreListingsWithVersionsAdminViewResponse(pydantic.BaseModel):
+    """Response model for listings with version history"""
+
+    listings: list[StoreListingWithVersionsAdminView]
+    pagination: Pagination
 
 
 class StoreReview(pydantic.BaseModel):

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

@@ -1,203 +0,0 @@
-import datetime
-
-import prisma.enums
-
-from . import model as store_model
-
-
-def test_pagination():
-    pagination = store_model.Pagination(
-        total_items=100, total_pages=5, current_page=2, page_size=20
-    )
-    assert pagination.total_items == 100
-    assert pagination.total_pages == 5
-    assert pagination.current_page == 2
-    assert pagination.page_size == 20
-
-
-def test_store_agent():
-    agent = store_model.StoreAgent(
-        slug="test-agent",
-        agent_name="Test Agent",
-        agent_image="test.jpg",
-        creator="creator1",
-        creator_avatar="avatar.jpg",
-        sub_heading="Test subheading",
-        description="Test description",
-        runs=50,
-        rating=4.5,
-        agent_graph_id="test-graph-id",
-    )
-    assert agent.slug == "test-agent"
-    assert agent.agent_name == "Test Agent"
-    assert agent.runs == 50
-    assert agent.rating == 4.5
-    assert agent.agent_graph_id == "test-graph-id"
-
-
-def test_store_agents_response():
-    response = store_model.StoreAgentsResponse(
-        agents=[
-            store_model.StoreAgent(
-                slug="test-agent",
-                agent_name="Test Agent",
-                agent_image="test.jpg",
-                creator="creator1",
-                creator_avatar="avatar.jpg",
-                sub_heading="Test subheading",
-                description="Test description",
-                runs=50,
-                rating=4.5,
-                agent_graph_id="test-graph-id",
-            )
-        ],
-        pagination=store_model.Pagination(
-            total_items=1, total_pages=1, current_page=1, page_size=20
-        ),
-    )
-    assert len(response.agents) == 1
-    assert response.pagination.total_items == 1
-
-
-def test_store_agent_details():
-    details = store_model.StoreAgentDetails(
-        store_listing_version_id="version123",
-        slug="test-agent",
-        agent_name="Test Agent",
-        agent_video="video.mp4",
-        agent_output_demo="demo.mp4",
-        agent_image=["image1.jpg", "image2.jpg"],
-        creator="creator1",
-        creator_avatar="avatar.jpg",
-        sub_heading="Test subheading",
-        description="Test description",
-        categories=["cat1", "cat2"],
-        runs=50,
-        rating=4.5,
-        versions=["1.0", "2.0"],
-        agentGraphVersions=["1", "2"],
-        agentGraphId="test-graph-id",
-        last_updated=datetime.datetime.now(),
-    )
-    assert details.slug == "test-agent"
-    assert len(details.agent_image) == 2
-    assert len(details.categories) == 2
-    assert len(details.versions) == 2
-
-
-def test_creator():
-    creator = store_model.Creator(
-        agent_rating=4.8,
-        agent_runs=1000,
-        name="Test Creator",
-        username="creator1",
-        description="Test description",
-        avatar_url="avatar.jpg",
-        num_agents=5,
-        is_featured=False,
-    )
-    assert creator.name == "Test Creator"
-    assert creator.num_agents == 5
-
-
-def test_creators_response():
-    response = store_model.CreatorsResponse(
-        creators=[
-            store_model.Creator(
-                agent_rating=4.8,
-                agent_runs=1000,
-                name="Test Creator",
-                username="creator1",
-                description="Test description",
-                avatar_url="avatar.jpg",
-                num_agents=5,
-                is_featured=False,
-            )
-        ],
-        pagination=store_model.Pagination(
-            total_items=1, total_pages=1, current_page=1, page_size=20
-        ),
-    )
-    assert len(response.creators) == 1
-    assert response.pagination.total_items == 1
-
-
-def test_creator_details():
-    details = store_model.CreatorDetails(
-        name="Test Creator",
-        username="creator1",
-        description="Test description",
-        links=["link1.com", "link2.com"],
-        avatar_url="avatar.jpg",
-        agent_rating=4.8,
-        agent_runs=1000,
-        top_categories=["cat1", "cat2"],
-    )
-    assert details.name == "Test Creator"
-    assert len(details.links) == 2
-    assert details.agent_rating == 4.8
-    assert len(details.top_categories) == 2
-
-
-def test_store_submission():
-    submission = store_model.StoreSubmission(
-        listing_id="listing123",
-        agent_id="agent123",
-        agent_version=1,
-        sub_heading="Test subheading",
-        name="Test Agent",
-        slug="test-agent",
-        description="Test description",
-        image_urls=["image1.jpg", "image2.jpg"],
-        date_submitted=datetime.datetime(2023, 1, 1),
-        status=prisma.enums.SubmissionStatus.PENDING,
-        runs=50,
-        rating=4.5,
-    )
-    assert submission.name == "Test Agent"
-    assert len(submission.image_urls) == 2
-    assert submission.status == prisma.enums.SubmissionStatus.PENDING
-
-
-def test_store_submissions_response():
-    response = store_model.StoreSubmissionsResponse(
-        submissions=[
-            store_model.StoreSubmission(
-                listing_id="listing123",
-                agent_id="agent123",
-                agent_version=1,
-                sub_heading="Test subheading",
-                name="Test Agent",
-                slug="test-agent",
-                description="Test description",
-                image_urls=["image1.jpg"],
-                date_submitted=datetime.datetime(2023, 1, 1),
-                status=prisma.enums.SubmissionStatus.PENDING,
-                runs=50,
-                rating=4.5,
-            )
-        ],
-        pagination=store_model.Pagination(
-            total_items=1, total_pages=1, current_page=1, page_size=20
-        ),
-    )
-    assert len(response.submissions) == 1
-    assert response.pagination.total_items == 1
-
-
-def test_store_submission_request():
-    request = store_model.StoreSubmissionRequest(
-        agent_id="agent123",
-        agent_version=1,
-        slug="test-agent",
-        name="Test Agent",
-        sub_heading="Test subheading",
-        video_url="video.mp4",
-        image_urls=["image1.jpg", "image2.jpg"],
-        description="Test description",
-        categories=["cat1", "cat2"],
-    )
-    assert request.agent_id == "agent123"
-    assert request.agent_version == 1
-    assert len(request.image_urls) == 2
-    assert len(request.categories) == 2

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

@@ -1,16 +1,16 @@
 import logging
-import tempfile
-import typing
 import urllib.parse
-from typing import Literal
 
 import autogpt_libs.auth
 import fastapi
 import fastapi.responses
 import prisma.enums
+from fastapi import Query, Security
+from pydantic import BaseModel
 
 import backend.data.graph
 import backend.util.json
+from backend.util.exceptions import NotFoundError
 from backend.util.models import Pagination
 
 from . import cache as store_cache
@@ -34,22 +34,15 @@ router = fastapi.APIRouter()
     "/profile",
     summary="Get user profile",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=store_model.ProfileDetails,
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
 async def get_profile(
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-):
-    """
-    Get the profile details for the authenticated user.
-    Cached for 1 hour per user.
-    """
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+) -> store_model.ProfileDetails:
+    """Get the profile details for the authenticated user."""
     profile = await store_db.get_user_profile(user_id)
     if profile is None:
-        return fastapi.responses.JSONResponse(
-            status_code=404,
-            content={"detail": "Profile not found"},
-        )
+        raise NotFoundError("User does not have a profile yet")
     return profile
 
 
@@ -57,98 +50,17 @@ async def get_profile(
     "/profile",
     summary="Update user profile",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=store_model.CreatorDetails,
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
 async def update_or_create_profile(
     profile: store_model.Profile,
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-):
-    """
-    Update the store profile for the authenticated user.
-
-    Args:
-        profile (Profile): The updated profile details
-        user_id (str): ID of the authenticated user
-
-    Returns:
-        CreatorDetails: The updated profile
-
-    Raises:
-        HTTPException: If there is an error updating the profile
-    """
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+) -> store_model.ProfileDetails:
+    """Update the store profile for the authenticated user."""
     updated_profile = await store_db.update_profile(user_id=user_id, profile=profile)
     return updated_profile
 
 
-##############################################
-############### Agent Endpoints ##############
-##############################################
-
-
-@router.get(
-    "/agents",
-    summary="List store agents",
-    tags=["store", "public"],
-    response_model=store_model.StoreAgentsResponse,
-)
-async def get_agents(
-    featured: bool = False,
-    creator: str | None = None,
-    sorted_by: Literal["rating", "runs", "name", "updated_at"] | None = None,
-    search_query: str | None = None,
-    category: str | None = None,
-    page: int = 1,
-    page_size: int = 20,
-):
-    """
-    Get a paginated list of agents from the store with optional filtering and sorting.
-
-    Args:
-        featured (bool, optional): Filter to only show featured agents. Defaults to False.
-        creator (str | None, optional): Filter agents by creator username. Defaults to None.
-        sorted_by (str | None, optional): Sort agents by "runs" or "rating". Defaults to None.
-        search_query (str | None, optional): Search agents by name, subheading and description. Defaults to None.
-        category (str | None, optional): Filter agents by category. Defaults to None.
-        page (int, optional): Page number for pagination. Defaults to 1.
-        page_size (int, optional): Number of agents per page. Defaults to 20.
-
-    Returns:
-        StoreAgentsResponse: Paginated list of agents matching the filters
-
-    Raises:
-        HTTPException: If page or page_size are less than 1
-
-    Used for:
-    - Home Page Featured Agents
-    - Home Page Top Agents
-    - Search Results
-    - Agent Details - Other Agents By Creator
-    - Agent Details - Similar Agents
-    - Creator Details - Agents By Creator
-    """
-    if page < 1:
-        raise fastapi.HTTPException(
-            status_code=422, detail="Page must be greater than 0"
-        )
-
-    if page_size < 1:
-        raise fastapi.HTTPException(
-            status_code=422, detail="Page size must be greater than 0"
-        )
-
-    agents = await store_cache._get_cached_store_agents(
-        featured=featured,
-        creator=creator,
-        sorted_by=sorted_by,
-        search_query=search_query,
-        category=category,
-        page=page,
-        page_size=page_size,
-    )
-    return agents
-
-
 ##############################################
 ############### Search Endpoints #############
 ##############################################
@@ -158,60 +70,30 @@ async def get_agents(
     "/search",
     summary="Unified search across all content types",
     tags=["store", "public"],
-    response_model=store_model.UnifiedSearchResponse,
 )
 async def unified_search(
     query: str,
-    content_types: list[str] | None = fastapi.Query(
+    content_types: list[prisma.enums.ContentType] | None = Query(
         default=None,
-        description="Content types to search: STORE_AGENT, BLOCK, DOCUMENTATION. If not specified, searches all.",
+        description="Content types to search. If not specified, searches all.",
     ),
-    page: int = 1,
-    page_size: int = 20,
-    user_id: str | None = fastapi.Security(
+    page: int = Query(ge=1, default=1),
+    page_size: int = Query(ge=1, default=20),
+    user_id: str | None = Security(
         autogpt_libs.auth.get_optional_user_id, use_cache=False
     ),
-):
+) -> store_model.UnifiedSearchResponse:
     """
-    Search across all content types (store agents, blocks, documentation) using hybrid search.
+    Search across all content types (marketplace agents, blocks, documentation)
+    using hybrid search.
 
     Combines semantic (embedding-based) and lexical (text-based) search for best results.
-
-    Args:
-        query: The search query string
-        content_types: Optional list of content types to filter by (STORE_AGENT, BLOCK, DOCUMENTATION)
-        page: Page number for pagination (default 1)
-        page_size: Number of results per page (default 20)
-        user_id: Optional authenticated user ID (for user-scoped content in future)
-
-    Returns:
-        UnifiedSearchResponse: Paginated list of search results with relevance scores
     """
-    if page < 1:
-        raise fastapi.HTTPException(
-            status_code=422, detail="Page must be greater than 0"
-        )
-
-    if page_size < 1:
-        raise fastapi.HTTPException(
-            status_code=422, detail="Page size must be greater than 0"
-        )
-
-    # Convert string content types to enum
-    content_type_enums: list[prisma.enums.ContentType] | None = None
-    if content_types:
-        try:
-            content_type_enums = [prisma.enums.ContentType(ct) for ct in content_types]
-        except ValueError as e:
-            raise fastapi.HTTPException(
-                status_code=422,
-                detail=f"Invalid content type. Valid values: STORE_AGENT, BLOCK, DOCUMENTATION. Error: {e}",
-            )
 
     # Perform unified hybrid search
     results, total = await store_hybrid_search.unified_hybrid_search(
         query=query,
-        content_types=content_type_enums,
+        content_types=content_types,
         user_id=user_id,
         page=page,
         page_size=page_size,
@@ -245,22 +127,69 @@ async def unified_search(
     )
 
 
+##############################################
+############### Agent Endpoints ##############
+##############################################
+
+
+@router.get(
+    "/agents",
+    summary="List store agents",
+    tags=["store", "public"],
+)
+async def get_agents(
+    featured: bool = Query(
+        default=False, description="Filter to only show featured agents"
+    ),
+    creator: str | None = Query(
+        default=None, description="Filter agents by creator username"
+    ),
+    category: str | None = Query(default=None, description="Filter agents by category"),
+    search_query: str | None = Query(
+        default=None, description="Literal + semantic search on names and descriptions"
+    ),
+    sorted_by: store_db.StoreAgentsSortOptions | None = Query(
+        default=None,
+        description="Property to sort results by. Ignored if search_query is provided.",
+    ),
+    page: int = Query(ge=1, default=1),
+    page_size: int = Query(ge=1, default=20),
+) -> store_model.StoreAgentsResponse:
+    """
+    Get a paginated list of agents from the marketplace,
+    with optional filtering and sorting.
+
+    Used for:
+    - Home Page Featured Agents
+    - Home Page Top Agents
+    - Search Results
+    - Agent Details - Other Agents By Creator
+    - Agent Details - Similar Agents
+    - Creator Details - Agents By Creator
+    """
+    agents = await store_cache._get_cached_store_agents(
+        featured=featured,
+        creator=creator,
+        sorted_by=sorted_by,
+        search_query=search_query,
+        category=category,
+        page=page,
+        page_size=page_size,
+    )
+    return agents
+
+
 @router.get(
     "/agents/{username}/{agent_name}",
     summary="Get specific agent",
     tags=["store", "public"],
-    response_model=store_model.StoreAgentDetails,
 )
-async def get_agent(
+async def get_agent_by_name(
     username: str,
     agent_name: str,
-    include_changelog: bool = fastapi.Query(default=False),
-):
-    """
-    This is only used on the AgentDetails Page.
-
-    It returns the store listing agents details.
-    """
+    include_changelog: bool = Query(default=False),
+) -> store_model.StoreAgentDetails:
+    """Get details of a marketplace agent"""
     username = urllib.parse.unquote(username).lower()
     # URL decode the agent name since it comes from the URL path
     agent_name = urllib.parse.unquote(agent_name).lower()
@@ -270,76 +199,79 @@ async def get_agent(
     return agent
 
 
-@router.get(
-    "/graph/{store_listing_version_id}",
-    summary="Get agent graph",
-    tags=["store"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-)
-async def get_graph_meta_by_store_listing_version_id(
-    store_listing_version_id: str,
-) -> backend.data.graph.GraphModelWithoutNodes:
-    """
-    Get Agent Graph from Store Listing Version ID.
-    """
-    graph = await store_db.get_available_graph(store_listing_version_id)
-    return graph
-
-
-@router.get(
-    "/agents/{store_listing_version_id}",
-    summary="Get agent by version",
-    tags=["store"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=store_model.StoreAgentDetails,
-)
-async def get_store_agent(store_listing_version_id: str):
-    """
-    Get Store Agent Details from Store Listing Version ID.
-    """
-    agent = await store_db.get_store_agent_by_version_id(store_listing_version_id)
-
-    return agent
-
-
 @router.post(
     "/agents/{username}/{agent_name}/review",
     summary="Create agent review",
     tags=["store"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=store_model.StoreReview,
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
-async def create_review(
+async def post_user_review_for_agent(
     username: str,
     agent_name: str,
     review: store_model.StoreReviewCreate,
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-):
-    """
-    Create a review for a store agent.
-
-    Args:
-        username: Creator's username
-        agent_name: Name/slug of the agent
-        review: Review details including score and optional comments
-        user_id: ID of authenticated user creating the review
-
-    Returns:
-        The created review
-    """
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+) -> store_model.StoreReview:
+    """Post a user review on a marketplace agent listing"""
     username = urllib.parse.unquote(username).lower()
     agent_name = urllib.parse.unquote(agent_name).lower()
-    # Create the review
+
     created_review = await store_db.create_store_review(
         user_id=user_id,
         store_listing_version_id=review.store_listing_version_id,
         score=review.score,
         comments=review.comments,
     )
-
     return created_review
 
 
+@router.get(
+    "/listings/versions/{store_listing_version_id}",
+    summary="Get agent by version",
+    tags=["store"],
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
+)
+async def get_agent_by_listing_version(
+    store_listing_version_id: str,
+) -> store_model.StoreAgentDetails:
+    agent = await store_db.get_store_agent_by_version_id(store_listing_version_id)
+    return agent
+
+
+@router.get(
+    "/listings/versions/{store_listing_version_id}/graph",
+    summary="Get agent graph",
+    tags=["store"],
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
+)
+async def get_graph_meta_by_store_listing_version_id(
+    store_listing_version_id: str,
+) -> backend.data.graph.GraphModelWithoutNodes:
+    """Get outline of graph belonging to a specific marketplace listing version"""
+    graph = await store_db.get_available_graph(store_listing_version_id)
+    return graph
+
+
+@router.get(
+    "/listings/versions/{store_listing_version_id}/graph/download",
+    summary="Download agent file",
+    tags=["store", "public"],
+)
+async def download_agent_file(
+    store_listing_version_id: str,
+) -> fastapi.responses.Response:
+    """Download agent graph file for a specific marketplace listing version"""
+    graph_data = await store_db.get_agent(store_listing_version_id)
+    file_name = f"agent_{graph_data.id}_v{graph_data.version or 'latest'}.json"
+
+    return fastapi.responses.Response(
+        content=backend.util.json.dumps(graph_data),
+        media_type="application/json",
+        headers={
+            "Content-Disposition": f'attachment; filename="{file_name}"',
+        },
+    )
+
+
 ##############################################
 ############# Creator Endpoints #############
 ##############################################
@@ -349,37 +281,19 @@ async def create_review(
     "/creators",
     summary="List store creators",
     tags=["store", "public"],
-    response_model=store_model.CreatorsResponse,
 )
 async def get_creators(
-    featured: bool = False,
-    search_query: str | None = None,
-    sorted_by: Literal["agent_rating", "agent_runs", "num_agents"] | None = None,
-    page: int = 1,
-    page_size: int = 20,
-):
-    """
-    This is needed for:
-    - Home Page Featured Creators
-    - Search Results Page
-
-    ---
-
-    To support this functionality we need:
-    - featured: bool - to limit the list to just featured agents
-    - search_query: str - vector search based on the creators profile description.
-    - sorted_by: [agent_rating, agent_runs] -
-    """
-    if page < 1:
-        raise fastapi.HTTPException(
-            status_code=422, detail="Page must be greater than 0"
-        )
-
-    if page_size < 1:
-        raise fastapi.HTTPException(
-            status_code=422, detail="Page size must be greater than 0"
-        )
-
+    featured: bool = Query(
+        default=False, description="Filter to only show featured creators"
+    ),
+    search_query: str | None = Query(
+        default=None, description="Literal + semantic search on names and descriptions"
+    ),
+    sorted_by: store_db.StoreCreatorsSortOptions | None = None,
+    page: int = Query(ge=1, default=1),
+    page_size: int = Query(ge=1, default=20),
+) -> store_model.CreatorsResponse:
+    """List or search marketplace creators"""
     creators = await store_cache._get_cached_store_creators(
         featured=featured,
         search_query=search_query,
@@ -391,18 +305,12 @@ async def get_creators(
 
 
 @router.get(
-    "/creator/{username}",
+    "/creators/{username}",
     summary="Get creator details",
     tags=["store", "public"],
-    response_model=store_model.CreatorDetails,
 )
-async def get_creator(
-    username: str,
-):
-    """
-    Get the details of a creator.
-    - Creator Details Page
-    """
+async def get_creator(username: str) -> store_model.CreatorDetails:
+    """Get details on a marketplace creator"""
     username = urllib.parse.unquote(username).lower()
     creator = await store_cache._get_cached_creator_details(username=username)
     return creator
@@ -414,20 +322,17 @@ async def get_creator(
 
 
 @router.get(
-    "/myagents",
+    "/my-unpublished-agents",
     summary="Get my agents",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=store_model.MyAgentsResponse,
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
-async def get_my_agents(
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-    page: typing.Annotated[int, fastapi.Query(ge=1)] = 1,
-    page_size: typing.Annotated[int, fastapi.Query(ge=1)] = 20,
-):
-    """
-    Get user's own agents.
-    """
+async def get_my_unpublished_agents(
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+    page: int = Query(ge=1, default=1),
+    page_size: int = Query(ge=1, default=20),
+) -> store_model.MyUnpublishedAgentsResponse:
+    """List the authenticated user's unpublished agents"""
     agents = await store_db.get_my_agents(user_id, page=page, page_size=page_size)
     return agents
 
@@ -436,28 +341,17 @@ async def get_my_agents(
     "/submissions/{submission_id}",
     summary="Delete store submission",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=bool,
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
 async def delete_submission(
     submission_id: str,
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-):
-    """
-    Delete a store listing submission.
-
-    Args:
-        user_id (str): ID of the authenticated user
-        submission_id (str): ID of the submission to be deleted
-
-    Returns:
-        bool: True if the submission was successfully deleted, False otherwise
-    """
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+) -> bool:
+    """Delete a marketplace listing submission"""
     result = await store_db.delete_store_submission(
         user_id=user_id,
         submission_id=submission_id,
     )
-
     return result
 
 
@@ -465,37 +359,14 @@ async def delete_submission(
     "/submissions",
     summary="List my submissions",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=store_model.StoreSubmissionsResponse,
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
 async def get_submissions(
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-    page: int = 1,
-    page_size: int = 20,
-):
-    """
-    Get a paginated list of store submissions for the authenticated user.
-
-    Args:
-        user_id (str): ID of the authenticated user
-        page (int, optional): Page number for pagination. Defaults to 1.
-        page_size (int, optional): Number of submissions per page. Defaults to 20.
-
-    Returns:
-        StoreListingsResponse: Paginated list of store submissions
-
-    Raises:
-        HTTPException: If page or page_size are less than 1
-    """
-    if page < 1:
-        raise fastapi.HTTPException(
-            status_code=422, detail="Page must be greater than 0"
-        )
-
-    if page_size < 1:
-        raise fastapi.HTTPException(
-            status_code=422, detail="Page size must be greater than 0"
-        )
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+    page: int = Query(ge=1, default=1),
+    page_size: int = Query(ge=1, default=20),
+) -> store_model.StoreSubmissionsResponse:
+    """List the authenticated user's marketplace listing submissions"""
     listings = await store_db.get_store_submissions(
         user_id=user_id,
         page=page,
@@ -508,30 +379,17 @@ async def get_submissions(
     "/submissions",
     summary="Create store submission",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=store_model.StoreSubmission,
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
 async def create_submission(
     submission_request: store_model.StoreSubmissionRequest,
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-):
-    """
-    Create a new store listing submission.
-
-    Args:
-        submission_request (StoreSubmissionRequest): The submission details
-        user_id (str): ID of the authenticated user submitting the listing
-
-    Returns:
-        StoreSubmission: The created store submission
-
-    Raises:
-        HTTPException: If there is an error creating the submission
-    """
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+) -> store_model.StoreSubmission:
+    """Submit a new marketplace listing for review"""
     result = await store_db.create_store_submission(
         user_id=user_id,
-        agent_id=submission_request.agent_id,
-        agent_version=submission_request.agent_version,
+        graph_id=submission_request.graph_id,
+        graph_version=submission_request.graph_version,
         slug=submission_request.slug,
         name=submission_request.name,
         video_url=submission_request.video_url,
@@ -544,7 +402,6 @@ async def create_submission(
         changes_summary=submission_request.changes_summary or "Initial Submission",
         recommended_schedule_cron=submission_request.recommended_schedule_cron,
     )
-
     return result
 
 
@@ -552,28 +409,14 @@ async def create_submission(
     "/submissions/{store_listing_version_id}",
     summary="Edit store submission",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
-    response_model=store_model.StoreSubmission,
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
 async def edit_submission(
     store_listing_version_id: str,
     submission_request: store_model.StoreSubmissionEditRequest,
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-):
-    """
-    Edit an existing store listing submission.
-
-    Args:
-        store_listing_version_id (str): ID of the store listing version to edit
-        submission_request (StoreSubmissionRequest): The updated submission details
-        user_id (str): ID of the authenticated user editing the listing
-
-    Returns:
-        StoreSubmission: The updated store submission
-
-    Raises:
-        HTTPException: If there is an error editing the submission
-    """
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+) -> store_model.StoreSubmission:
+    """Update a pending marketplace listing submission"""
     result = await store_db.edit_store_submission(
         user_id=user_id,
         store_listing_version_id=store_listing_version_id,
@@ -588,7 +431,6 @@ async def edit_submission(
         changes_summary=submission_request.changes_summary,
         recommended_schedule_cron=submission_request.recommended_schedule_cron,
     )
-
     return result
 
 
@@ -596,115 +438,61 @@ async def edit_submission(
     "/submissions/media",
     summary="Upload submission media",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
 async def upload_submission_media(
     file: fastapi.UploadFile,
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-):
-    """
-    Upload media (images/videos) for a store listing submission.
-
-    Args:
-        file (UploadFile): The media file to upload
-        user_id (str): ID of the authenticated user uploading the media
-
-    Returns:
-        str: URL of the uploaded media file
-
-    Raises:
-        HTTPException: If there is an error uploading the media
-    """
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+) -> str:
+    """Upload media for a marketplace listing submission"""
     media_url = await store_media.upload_media(user_id=user_id, file=file)
     return media_url
 
 
+class ImageURLResponse(BaseModel):
+    image_url: str
+
+
 @router.post(
     "/submissions/generate_image",
     summary="Generate submission image",
     tags=["store", "private"],
-    dependencies=[fastapi.Security(autogpt_libs.auth.requires_user)],
+    dependencies=[Security(autogpt_libs.auth.requires_user)],
 )
 async def generate_image(
-    agent_id: str,
-    user_id: str = fastapi.Security(autogpt_libs.auth.get_user_id),
-) -> fastapi.responses.Response:
+    graph_id: str,
+    user_id: str = Security(autogpt_libs.auth.get_user_id),
+) -> ImageURLResponse:
     """
-    Generate an image for a store listing submission.
-
-    Args:
-        agent_id (str): ID of the agent to generate an image for
-        user_id (str): ID of the authenticated user
-
-    Returns:
-        JSONResponse: JSON containing the URL of the generated image
+    Generate an image for a marketplace listing submission based on the properties
+    of a given graph.
     """
-    agent = await backend.data.graph.get_graph(
-        graph_id=agent_id, version=None, user_id=user_id
+    graph = await backend.data.graph.get_graph(
+        graph_id=graph_id, version=None, user_id=user_id
     )
 
-    if not agent:
-        raise fastapi.HTTPException(
-            status_code=404, detail=f"Agent with ID {agent_id} not found"
-        )
+    if not graph:
+        raise NotFoundError(f"Agent graph #{graph_id} not found")
     # Use .jpeg here since we are generating JPEG images
-    filename = f"agent_{agent_id}.jpeg"
+    filename = f"agent_{graph_id}.jpeg"
 
     existing_url = await store_media.check_media_exists(user_id, filename)
     if existing_url:
-        logger.info(f"Using existing image for agent {agent_id}")
-        return fastapi.responses.JSONResponse(content={"image_url": existing_url})
+        logger.info(f"Using existing image for agent graph {graph_id}")
+        return ImageURLResponse(image_url=existing_url)
     # Generate agent image as JPEG
-    image = await store_image_gen.generate_agent_image(agent=agent)
+    image = await store_image_gen.generate_agent_image(agent=graph)
 
     # Create UploadFile with the correct filename and content_type
     image_file = fastapi.UploadFile(
         file=image,
         filename=filename,
     )
-
     image_url = await store_media.upload_media(
         user_id=user_id, file=image_file, use_file_name=True
     )
 
-    return fastapi.responses.JSONResponse(content={"image_url": image_url})
-
-
-@router.get(
-    "/download/agents/{store_listing_version_id}",
-    summary="Download agent file",
-    tags=["store", "public"],
-)
-async def download_agent_file(
-    store_listing_version_id: str = fastapi.Path(
-        ..., description="The ID of the agent to download"
-    ),
-) -> fastapi.responses.FileResponse:
-    """
-    Download the agent file by streaming its content.
-
-    Args:
-        store_listing_version_id (str): The ID of the agent to download
-
-    Returns:
-        StreamingResponse: A streaming response containing the agent's graph data.
-
-    Raises:
-        HTTPException: If the agent is not found or an unexpected error occurs.
-    """
-    graph_data = await store_db.get_agent(store_listing_version_id)
-    file_name = f"agent_{graph_data.id}_v{graph_data.version or 'latest'}.json"
-
-    # Sending graph as a stream (similar to marketplace v1)
-    with tempfile.NamedTemporaryFile(
-        mode="w", suffix=".json", delete=False
-    ) as tmp_file:
-        tmp_file.write(backend.util.json.dumps(graph_data))
-        tmp_file.flush()
-
-        return fastapi.responses.FileResponse(
-            tmp_file.name, filename=file_name, media_type="application/json"
-        )
+    return ImageURLResponse(image_url=image_url)
 
 
 ##############################################

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

@@ -8,6 +8,8 @@ import pytest
 import pytest_mock
 from pytest_snapshot.plugin import Snapshot
 
+from backend.api.features.store.db import StoreAgentsSortOptions
+
 from . import model as store_model
 from . import routes as store_routes
 
@@ -196,7 +198,7 @@ def test_get_agents_sorted(
     mock_db_call.assert_called_once_with(
         featured=False,
         creators=None,
-        sorted_by="runs",
+        sorted_by=StoreAgentsSortOptions.RUNS,
         search_query=None,
         category=None,
         page=1,
@@ -380,9 +382,11 @@ def test_get_agent_details(
         runs=100,
         rating=4.5,
         versions=["1.0.0", "1.1.0"],
-        agentGraphVersions=["1", "2"],
-        agentGraphId="test-graph-id",
+        graph_versions=["1", "2"],
+        graph_id="test-graph-id",
         last_updated=FIXED_NOW,
+        active_version_id="test-version-id",
+        has_approved_version=True,
     )
     mock_db_call = mocker.patch("backend.api.features.store.db.get_store_agent_details")
     mock_db_call.return_value = mocked_value
@@ -435,15 +439,17 @@ def test_get_creators_pagination(
 ) -> None:
     mocked_value = store_model.CreatorsResponse(
         creators=[
-            store_model.Creator(
+            store_model.CreatorDetails(
                 name=f"Creator {i}",
                 username=f"creator{i}",
-                description=f"Creator {i} description",
                 avatar_url=f"avatar{i}.jpg",
-                num_agents=1,
-                agent_rating=4.5,
-                agent_runs=100,
+                description=f"Creator {i} description",
+                links=[f"user{i}.link.com"],
                 is_featured=False,
+                num_agents=1,
+                agent_runs=100,
+                agent_rating=4.5,
+                top_categories=["cat1", "cat2", "cat3"],
             )
             for i in range(5)
         ],
@@ -496,19 +502,19 @@ def test_get_creator_details(
     mocked_value = store_model.CreatorDetails(
         name="Test User",
         username="creator1",
+        avatar_url="avatar.jpg",
         description="Test creator description",
         links=["link1.com", "link2.com"],
-        avatar_url="avatar.jpg",
-        agent_rating=4.8,
+        is_featured=True,
+        num_agents=5,
         agent_runs=1000,
+        agent_rating=4.8,
         top_categories=["category1", "category2"],
     )
-    mock_db_call = mocker.patch(
-        "backend.api.features.store.db.get_store_creator_details"
-    )
+    mock_db_call = mocker.patch("backend.api.features.store.db.get_store_creator")
     mock_db_call.return_value = mocked_value
 
-    response = client.get("/creator/creator1")
+    response = client.get("/creators/creator1")
     assert response.status_code == 200
 
     data = store_model.CreatorDetails.model_validate(response.json())
@@ -528,19 +534,26 @@ def test_get_submissions_success(
         submissions=[
             store_model.StoreSubmission(
                 listing_id="test-listing-id",
-                name="Test Agent",
-                description="Test agent description",
-                image_urls=["test.jpg"],
-                date_submitted=FIXED_NOW,
-                status=prisma.enums.SubmissionStatus.APPROVED,
-                runs=50,
-                rating=4.2,
-                agent_id="test-agent-id",
-                agent_version=1,
-                sub_heading="Test agent subheading",
+                user_id="test-user-id",
                 slug="test-agent",
-                video_url="test.mp4",
+                listing_version_id="test-version-id",
+                listing_version=1,
+                graph_id="test-agent-id",
+                graph_version=1,
+                name="Test Agent",
+                sub_heading="Test agent subheading",
+                description="Test agent description",
+                instructions="Click the button!",
                 categories=["test-category"],
+                image_urls=["test.jpg"],
+                video_url="test.mp4",
+                agent_output_demo_url="demo_video.mp4",
+                submitted_at=FIXED_NOW,
+                changes_summary="Initial Submission",
+                status=prisma.enums.SubmissionStatus.APPROVED,
+                run_count=50,
+                review_count=5,
+                review_avg_rating=4.2,
             )
         ],
         pagination=store_model.Pagination(

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

@@ -11,6 +11,7 @@ import pytest
 from backend.util.models import Pagination
 
 from . import cache as store_cache
+from .db import StoreAgentsSortOptions
 from .model import StoreAgent, StoreAgentsResponse
 
 
@@ -215,7 +216,7 @@ class TestCacheDeletion:
             await store_cache._get_cached_store_agents(
                 featured=True,
                 creator="testuser",
-                sorted_by="rating",
+                sorted_by=StoreAgentsSortOptions.RATING,
                 search_query="AI assistant",
                 category="productivity",
                 page=2,
@@ -227,7 +228,7 @@ class TestCacheDeletion:
             deleted = store_cache._get_cached_store_agents.cache_delete(
                 featured=True,
                 creator="testuser",
-                sorted_by="rating",
+                sorted_by=StoreAgentsSortOptions.RATING,
                 search_query="AI assistant",
                 category="productivity",
                 page=2,
@@ -239,7 +240,7 @@ class TestCacheDeletion:
             deleted = store_cache._get_cached_store_agents.cache_delete(
                 featured=True,
                 creator="testuser",
-                sorted_by="rating",
+                sorted_by=StoreAgentsSortOptions.RATING,
                 search_query="AI assistant",
                 category="productivity",
                 page=2,

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

@@ -0,0 +1,5 @@
+"""Backward-compatibility shim — ``split_camelcase`` now lives in backend.util.text."""
+
+from backend.util.text import split_camelcase  # noqa: F401
+
+__all__ = ["split_camelcase"]

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

@@ -0,0 +1,49 @@
+"""Tests for split_camelcase (now in backend.util.text)."""
+
+import pytest
+
+from backend.util.text import split_camelcase
+
+# ---------------------------------------------------------------------------
+# split_camelcase
+# ---------------------------------------------------------------------------
+
+
+@pytest.mark.parametrize(
+    "input_text, expected",
+    [
+        ("AITextGeneratorBlock", "AI Text Generator Block"),
+        ("HTTPRequestBlock", "HTTP Request Block"),
+        ("simpleWord", "simple Word"),
+        ("already spaced", "already spaced"),
+        ("XMLParser", "XML Parser"),
+        ("getHTTPResponse", "get HTTP Response"),
+        ("Block", "Block"),
+        ("", ""),
+        ("OAuth2Block", "OAuth2 Block"),
+        ("IOError", "IO Error"),
+        ("getHTTPSResponse", "get HTTPS Response"),
+        # Known limitation: single-letter uppercase prefixes are NOT split.
+        # "ABlock" stays "ABlock" because the algorithm requires the left
+        # part of an uppercase run to retain at least 2 uppercase chars.
+        ("ABlock", "ABlock"),
+        # Digit-to-uppercase transitions
+        ("Base64Encoder", "Base64 Encoder"),
+        ("UTF8Decoder", "UTF8 Decoder"),
+        # Pure digits — no camelCase boundaries to split
+        ("123", "123"),
+        # Known limitation: single-letter uppercase segments after digits
+        # are not split from the following word.  "3D" is only 1 uppercase
+        # char so the uppercase-run rule cannot fire, producing "3 DRenderer"
+        # rather than the ideal "3D Renderer".
+        ("3DRenderer", "3 DRenderer"),
+        # Exception list — compound terms that should stay together
+        ("YouTubeBlock", "YouTube Block"),
+        ("OpenAIBlock", "OpenAI Block"),
+        ("AutoGPTAgent", "AutoGPT Agent"),
+        ("GitHubIntegration", "GitHub Integration"),
+        ("LinkedInBlock", "LinkedIn Block"),
+    ],
+)
+def test_split_camelcase(input_text: str, expected: str):
+    assert split_camelcase(input_text) == expected

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

@@ -449,7 +449,6 @@ async def execute_graph_block(
 async def upload_file(
     user_id: Annotated[str, Security(get_user_id)],
     file: UploadFile = File(...),
-    provider: str = "gcs",
     expiration_hours: int = 24,
 ) -> UploadFileResponse:
     """
@@ -512,7 +511,6 @@ async def upload_file(
     storage_path = await cloud_storage.store_file(
         content=content,
         filename=file_name,
-        provider=provider,
         expiration_hours=expiration_hours,
         user_id=user_id,
     )

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

@@ -515,7 +515,6 @@ async def test_upload_file_success(test_user_id: str):
         result = await upload_file(
             file=upload_file_mock,
             user_id=test_user_id,
-            provider="gcs",
             expiration_hours=24,
         )
 
@@ -533,7 +532,6 @@ async def test_upload_file_success(test_user_id: str):
         mock_handler.store_file.assert_called_once_with(
             content=file_content,
             filename="test.txt",
-            provider="gcs",
             expiration_hours=24,
             user_id=test_user_id,
         )

autogpt_platform/backend/backend/api/model.py

@@ -94,3 +94,8 @@ class NotificationPayload(pydantic.BaseModel):
 
 class OnboardingNotificationPayload(NotificationPayload):
     step: OnboardingStep | None
+
+
+class CopilotCompletionPayload(NotificationPayload):
+    session_id: str
+    status: Literal["completed", "failed"]

autogpt_platform/backend/backend/api/rest_api.py

@@ -55,6 +55,7 @@ from backend.util.exceptions import (
     MissingConfigError,
     NotAuthorizedError,
     NotFoundError,
+    PreconditionFailed,
 )
 from backend.util.feature_flag import initialize_launchdarkly, shutdown_launchdarkly
 from backend.util.service import UnhealthyServiceError
@@ -275,6 +276,7 @@ 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))
 app.add_exception_handler(ValueError, handle_internal_http_error(400))
+app.add_exception_handler(PreconditionFailed, handle_internal_http_error(428))
 app.add_exception_handler(Exception, handle_internal_http_error(500))
 
 app.include_router(backend.api.features.v1.v1_router, tags=["v1"], prefix="/api")

autogpt_platform/backend/backend/blocks/_base.py

@@ -418,6 +418,8 @@ class BlockWebhookConfig(BlockManualWebhookConfig):
 
 
 class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
+    _optimized_description: ClassVar[str | None] = None
+
     def __init__(
         self,
         id: str = "",
@@ -470,6 +472,8 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
         self.block_type = block_type
         self.webhook_config = webhook_config
         self.is_sensitive_action = is_sensitive_action
+        # Read from ClassVar set by initialize_blocks()
+        self.optimized_description: str | None = type(self)._optimized_description
         self.execution_stats: "NodeExecutionStats" = NodeExecutionStats()
 
         if self.webhook_config:
@@ -620,6 +624,7 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
         graph_id: str,
         graph_version: int,
         execution_context: "ExecutionContext",
+        is_graph_execution: bool = True,
         **kwargs,
     ) -> tuple[bool, BlockInput]:
         """
@@ -648,6 +653,7 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
             graph_version=graph_version,
             block_name=self.name,
             editable=True,
+            is_graph_execution=is_graph_execution,
         )
 
         if decision is None:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

autogpt_platform/backend/backend/blocks/ai_image_customizer.py

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

autogpt_platform/backend/backend/blocks/ai_image_generator_block.py

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

autogpt_platform/backend/backend/blocks/autopilot.py

@@ -0,0 +1,376 @@
+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/basic.py

@@ -126,7 +126,7 @@ class PrintToConsoleBlock(Block):
             output_schema=PrintToConsoleBlock.Output,
             test_input={"text": "Hello, World!"},
             is_sensitive_action=True,
-            disabled=True,  # Disabled per Nick Tindle's request (OPEN-3000)
+            disabled=True,
             test_output=[
                 ("output", "Hello, World!"),
                 ("status", "printed"),

autogpt_platform/backend/backend/blocks/code_executor.py

@@ -142,7 +142,7 @@ class BaseE2BExecutorMixin:
                 start_timestamp = ts_result.stdout.strip() if ts_result.stdout else None
 
             # Execute the code
-            execution = await sandbox.run_code(
+            execution = await sandbox.run_code(  # type: ignore[attr-defined]
                 code,
                 language=language.value,
                 on_error=lambda e: sandbox.kill(),  # Kill the sandbox on error

autogpt_platform/backend/backend/blocks/data_manipulation.py

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

autogpt_platform/backend/backend/blocks/email_block.py

@@ -21,6 +21,7 @@ from backend.data.model import (
     UserPasswordCredentials,
 )
 from backend.integrations.providers import ProviderName
+from backend.util.request import resolve_and_check_blocked
 
 TEST_CREDENTIALS = UserPasswordCredentials(
     id="01234567-89ab-cdef-0123-456789abcdef",
@@ -96,8 +97,11 @@ class SendEmailBlock(Block):
             test_credentials=TEST_CREDENTIALS,
             test_output=[("status", "Email sent successfully")],
             test_mock={"send_email": lambda *args, **kwargs: "Email sent successfully"},
+            is_sensitive_action=True,
         )
 
+    ALLOWED_SMTP_PORTS = {25, 465, 587, 2525}
+
     @staticmethod
     def send_email(
         config: SMTPConfig,
@@ -128,6 +132,17 @@ class SendEmailBlock(Block):
         self, input_data: Input, *, credentials: SMTPCredentials, **kwargs
     ) -> BlockOutput:
         try:
+            # --- SSRF Protection ---
+            smtp_port = input_data.config.smtp_port
+            if smtp_port not in self.ALLOWED_SMTP_PORTS:
+                yield "error", (
+                    f"SMTP port {smtp_port} is not allowed. "
+                    f"Allowed ports: {sorted(self.ALLOWED_SMTP_PORTS)}"
+                )
+                return
+
+            await resolve_and_check_blocked(input_data.config.smtp_server)
+
             status = self.send_email(
                 config=input_data.config,
                 to_email=input_data.to_email,
@@ -179,7 +194,19 @@ class SendEmailBlock(Block):
                 "was rejected by the server. "
                 "Please verify your account is authorized to send emails."
             )
+        except smtplib.SMTPConnectError:
+            yield "error", (
+                f"Cannot connect to SMTP server '{input_data.config.smtp_server}' "
+                f"on port {input_data.config.smtp_port}."
+            )
+        except smtplib.SMTPServerDisconnected:
+            yield "error", (
+                f"SMTP server '{input_data.config.smtp_server}' "
+                "disconnected unexpectedly."
+            )
         except smtplib.SMTPDataError as e:
             yield "error", f"Email data rejected by server: {str(e)}"
+        except ValueError as e:
+            yield "error", str(e)
         except Exception as e:
             raise e

autogpt_platform/backend/backend/blocks/flux_kontext.py

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

autogpt_platform/backend/backend/blocks/github/_utils.py

@@ -0,0 +1,3 @@
+def github_repo_path(repo_url: str) -> str:
+    """Extract 'owner/repo' from a GitHub repository URL."""
+    return repo_url.replace("https://github.com/", "")

autogpt_platform/backend/backend/blocks/github/commits.py

@@ -0,0 +1,408 @@
+import asyncio
+from enum import StrEnum
+from urllib.parse import quote
+
+from typing_extensions import TypedDict
+
+from backend.blocks._base import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
+from backend.data.execution import ExecutionContext
+from backend.data.model import SchemaField
+from backend.util.file import parse_data_uri, resolve_media_content
+from backend.util.type import MediaFileType
+
+from ._api import get_api
+from ._auth import (
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    GithubCredentials,
+    GithubCredentialsField,
+    GithubCredentialsInput,
+)
+from ._utils import github_repo_path
+
+
+class GithubListCommitsBlock(Block):
+    class Input(BlockSchemaInput):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        repo_url: str = SchemaField(
+            description="URL of the GitHub repository",
+            placeholder="https://github.com/owner/repo",
+        )
+        branch: str = SchemaField(
+            description="Branch name to list commits from",
+            default="main",
+        )
+        per_page: int = SchemaField(
+            description="Number of commits to return (max 100)",
+            default=30,
+            ge=1,
+            le=100,
+        )
+        page: int = SchemaField(
+            description="Page number for pagination",
+            default=1,
+            ge=1,
+        )
+
+    class Output(BlockSchemaOutput):
+        class CommitItem(TypedDict):
+            sha: str
+            message: str
+            author: str
+            date: str
+            url: str
+
+        commit: CommitItem = SchemaField(
+            title="Commit", description="A commit with its details"
+        )
+        commits: list[CommitItem] = SchemaField(
+            description="List of commits with their details"
+        )
+        error: str = SchemaField(description="Error message if listing commits failed")
+
+    def __init__(self):
+        super().__init__(
+            id="8b13f579-d8b6-4dc2-a140-f770428805de",
+            description="This block lists commits on a branch in a GitHub repository.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubListCommitsBlock.Input,
+            output_schema=GithubListCommitsBlock.Output,
+            test_input={
+                "repo_url": "https://github.com/owner/repo",
+                "branch": "main",
+                "per_page": 30,
+                "page": 1,
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                (
+                    "commits",
+                    [
+                        {
+                            "sha": "abc123",
+                            "message": "Initial commit",
+                            "author": "octocat",
+                            "date": "2024-01-01T00:00:00Z",
+                            "url": "https://github.com/owner/repo/commit/abc123",
+                        }
+                    ],
+                ),
+                (
+                    "commit",
+                    {
+                        "sha": "abc123",
+                        "message": "Initial commit",
+                        "author": "octocat",
+                        "date": "2024-01-01T00:00:00Z",
+                        "url": "https://github.com/owner/repo/commit/abc123",
+                    },
+                ),
+            ],
+            test_mock={
+                "list_commits": lambda *args, **kwargs: [
+                    {
+                        "sha": "abc123",
+                        "message": "Initial commit",
+                        "author": "octocat",
+                        "date": "2024-01-01T00:00:00Z",
+                        "url": "https://github.com/owner/repo/commit/abc123",
+                    }
+                ]
+            },
+        )
+
+    @staticmethod
+    async def list_commits(
+        credentials: GithubCredentials,
+        repo_url: str,
+        branch: str,
+        per_page: int,
+        page: int,
+    ) -> list[Output.CommitItem]:
+        api = get_api(credentials)
+        commits_url = repo_url + "/commits"
+        params = {"sha": branch, "per_page": str(per_page), "page": str(page)}
+        response = await api.get(commits_url, params=params)
+        data = response.json()
+        repo_path = github_repo_path(repo_url)
+        return [
+            GithubListCommitsBlock.Output.CommitItem(
+                sha=c["sha"],
+                message=c["commit"]["message"],
+                author=(c["commit"].get("author") or {}).get("name", "Unknown"),
+                date=(c["commit"].get("author") or {}).get("date", ""),
+                url=f"https://github.com/{repo_path}/commit/{c['sha']}",
+            )
+            for c in data
+        ]
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            commits = await self.list_commits(
+                credentials,
+                input_data.repo_url,
+                input_data.branch,
+                input_data.per_page,
+                input_data.page,
+            )
+            yield "commits", commits
+            for commit in commits:
+                yield "commit", commit
+        except Exception as e:
+            yield "error", str(e)
+
+
+class FileOperation(StrEnum):
+    """File operations for GithubMultiFileCommitBlock.
+
+    UPSERT creates or overwrites a file (the Git Trees API does not distinguish
+    between creation and update — the blob is placed at the given path regardless
+    of whether a file already exists there).
+
+    DELETE removes a file from the tree.
+    """
+
+    UPSERT = "upsert"
+    DELETE = "delete"
+
+
+class FileOperationInput(TypedDict):
+    path: str
+    # MediaFileType is a str NewType — no runtime breakage for existing callers.
+    content: MediaFileType
+    operation: FileOperation
+
+
+class GithubMultiFileCommitBlock(Block):
+    class Input(BlockSchemaInput):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        repo_url: str = SchemaField(
+            description="URL of the GitHub repository",
+            placeholder="https://github.com/owner/repo",
+        )
+        branch: str = SchemaField(
+            description="Branch to commit to",
+            placeholder="feature-branch",
+        )
+        commit_message: str = SchemaField(
+            description="Commit message",
+            placeholder="Add new feature",
+        )
+        files: list[FileOperationInput] = SchemaField(
+            description=(
+                "List of file operations. Each item has: "
+                "'path' (file path), 'content' (file content, ignored for delete), "
+                "'operation' (upsert/delete)"
+            ),
+        )
+
+    class Output(BlockSchemaOutput):
+        sha: str = SchemaField(description="SHA of the new commit")
+        url: str = SchemaField(description="URL of the new commit")
+        error: str = SchemaField(description="Error message if the commit failed")
+
+    def __init__(self):
+        super().__init__(
+            id="389eee51-a95e-4230-9bed-92167a327802",
+            description=(
+                "This block creates a single commit with multiple file "
+                "upsert/delete operations using the Git Trees API."
+            ),
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubMultiFileCommitBlock.Input,
+            output_schema=GithubMultiFileCommitBlock.Output,
+            test_input={
+                "repo_url": "https://github.com/owner/repo",
+                "branch": "feature",
+                "commit_message": "Add files",
+                "files": [
+                    {
+                        "path": "src/new.py",
+                        "content": "print('hello')",
+                        "operation": "upsert",
+                    },
+                    {
+                        "path": "src/old.py",
+                        "content": "",
+                        "operation": "delete",
+                    },
+                ],
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("sha", "newcommitsha"),
+                ("url", "https://github.com/owner/repo/commit/newcommitsha"),
+            ],
+            test_mock={
+                "multi_file_commit": lambda *args, **kwargs: (
+                    "newcommitsha",
+                    "https://github.com/owner/repo/commit/newcommitsha",
+                )
+            },
+        )
+
+    @staticmethod
+    async def multi_file_commit(
+        credentials: GithubCredentials,
+        repo_url: str,
+        branch: str,
+        commit_message: str,
+        files: list[FileOperationInput],
+    ) -> tuple[str, str]:
+        api = get_api(credentials)
+        safe_branch = quote(branch, safe="")
+
+        # 1. Get the latest commit SHA for the branch
+        ref_url = repo_url + f"/git/refs/heads/{safe_branch}"
+        response = await api.get(ref_url)
+        ref_data = response.json()
+        latest_commit_sha = ref_data["object"]["sha"]
+
+        # 2. Get the tree SHA of the latest commit
+        commit_url = repo_url + f"/git/commits/{latest_commit_sha}"
+        response = await api.get(commit_url)
+        commit_data = response.json()
+        base_tree_sha = commit_data["tree"]["sha"]
+
+        # 3. Build tree entries for each file operation (blobs created concurrently)
+        async def _create_blob(content: str, encoding: str = "utf-8") -> str:
+            blob_url = repo_url + "/git/blobs"
+            blob_response = await api.post(
+                blob_url,
+                json={"content": content, "encoding": encoding},
+            )
+            return blob_response.json()["sha"]
+
+        tree_entries: list[dict] = []
+        upsert_files = []
+        for file_op in files:
+            path = file_op["path"]
+            operation = FileOperation(file_op.get("operation", "upsert"))
+
+            if operation == FileOperation.DELETE:
+                tree_entries.append(
+                    {
+                        "path": path,
+                        "mode": "100644",
+                        "type": "blob",
+                        "sha": None,  # null SHA = delete
+                    }
+                )
+            else:
+                upsert_files.append((path, file_op.get("content", "")))
+
+        # Create all blobs concurrently. Data URIs (from store_media_file)
+        # are sent as base64 blobs to preserve binary content.
+        if upsert_files:
+
+            async def _make_blob(content: str) -> str:
+                parsed = parse_data_uri(content)
+                if parsed is not None:
+                    _, b64_payload = parsed
+                    return await _create_blob(b64_payload, encoding="base64")
+                return await _create_blob(content)
+
+            blob_shas = await asyncio.gather(
+                *[_make_blob(content) for _, content in upsert_files]
+            )
+            for (path, _), blob_sha in zip(upsert_files, blob_shas):
+                tree_entries.append(
+                    {
+                        "path": path,
+                        "mode": "100644",
+                        "type": "blob",
+                        "sha": blob_sha,
+                    }
+                )
+
+        # 4. Create a new tree
+        tree_url = repo_url + "/git/trees"
+        tree_response = await api.post(
+            tree_url,
+            json={"base_tree": base_tree_sha, "tree": tree_entries},
+        )
+        new_tree_sha = tree_response.json()["sha"]
+
+        # 5. Create a new commit
+        new_commit_url = repo_url + "/git/commits"
+        commit_response = await api.post(
+            new_commit_url,
+            json={
+                "message": commit_message,
+                "tree": new_tree_sha,
+                "parents": [latest_commit_sha],
+            },
+        )
+        new_commit_sha = commit_response.json()["sha"]
+
+        # 6. Update the branch reference
+        try:
+            await api.patch(
+                ref_url,
+                json={"sha": new_commit_sha},
+            )
+        except Exception as e:
+            raise RuntimeError(
+                f"Commit {new_commit_sha} was created but failed to update "
+                f"ref heads/{branch}: {e}. "
+                f"You can recover by manually updating the branch to {new_commit_sha}."
+            ) from e
+
+        repo_path = github_repo_path(repo_url)
+        commit_web_url = f"https://github.com/{repo_path}/commit/{new_commit_sha}"
+        return new_commit_sha, commit_web_url
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        execution_context: ExecutionContext,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            # Resolve media references (workspace://, data:, URLs) to data
+            # URIs so _make_blob can send binary content correctly.
+            resolved_files: list[FileOperationInput] = []
+            for file_op in input_data.files:
+                content = file_op.get("content", "")
+                operation = FileOperation(file_op.get("operation", "upsert"))
+                if operation != FileOperation.DELETE:
+                    content = await resolve_media_content(
+                        MediaFileType(content),
+                        execution_context,
+                        return_format="for_external_api",
+                    )
+                resolved_files.append(
+                    FileOperationInput(
+                        path=file_op["path"],
+                        content=MediaFileType(content),
+                        operation=operation,
+                    )
+                )
+
+            sha, url = await self.multi_file_commit(
+                credentials,
+                input_data.repo_url,
+                input_data.branch,
+                input_data.commit_message,
+                resolved_files,
+            )
+            yield "sha", sha
+            yield "url", url
+        except Exception as e:
+            yield "error", str(e)

autogpt_platform/backend/backend/blocks/github/pull_requests.py

@@ -1,4 +1,5 @@
 import re
+from typing import Literal
 
 from typing_extensions import TypedDict
 
@@ -20,6 +21,8 @@ from ._auth import (
     GithubCredentialsInput,
 )
 
+MergeMethod = Literal["merge", "squash", "rebase"]
+
 
 class GithubListPullRequestsBlock(Block):
     class Input(BlockSchemaInput):
@@ -558,12 +561,109 @@ class GithubListPRReviewersBlock(Block):
             yield "reviewer", reviewer
 
 
+class GithubMergePullRequestBlock(Block):
+    class Input(BlockSchemaInput):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        pr_url: str = SchemaField(
+            description="URL of the GitHub pull request",
+            placeholder="https://github.com/owner/repo/pull/1",
+        )
+        merge_method: MergeMethod = SchemaField(
+            description="Merge method to use: merge, squash, or rebase",
+            default="merge",
+        )
+        commit_title: str = SchemaField(
+            description="Title for the merge commit (optional, used for merge and squash)",
+            default="",
+        )
+        commit_message: str = SchemaField(
+            description="Message for the merge commit (optional, used for merge and squash)",
+            default="",
+        )
+
+    class Output(BlockSchemaOutput):
+        sha: str = SchemaField(description="SHA of the merge commit")
+        merged: bool = SchemaField(description="Whether the PR was merged")
+        message: str = SchemaField(description="Merge status message")
+        error: str = SchemaField(description="Error message if the merge failed")
+
+    def __init__(self):
+        super().__init__(
+            id="77456c22-33d8-4fd4-9eef-50b46a35bb48",
+            description="This block merges a pull request using merge, squash, or rebase.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubMergePullRequestBlock.Input,
+            output_schema=GithubMergePullRequestBlock.Output,
+            test_input={
+                "pr_url": "https://github.com/owner/repo/pull/1",
+                "merge_method": "squash",
+                "commit_title": "",
+                "commit_message": "",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("sha", "abc123"),
+                ("merged", True),
+                ("message", "Pull Request successfully merged"),
+            ],
+            test_mock={
+                "merge_pr": lambda *args, **kwargs: (
+                    "abc123",
+                    True,
+                    "Pull Request successfully merged",
+                )
+            },
+            is_sensitive_action=True,
+        )
+
+    @staticmethod
+    async def merge_pr(
+        credentials: GithubCredentials,
+        pr_url: str,
+        merge_method: MergeMethod,
+        commit_title: str,
+        commit_message: str,
+    ) -> tuple[str, bool, str]:
+        api = get_api(credentials)
+        merge_url = prepare_pr_api_url(pr_url=pr_url, path="merge")
+        data: dict[str, str] = {"merge_method": merge_method}
+        if commit_title:
+            data["commit_title"] = commit_title
+        if commit_message:
+            data["commit_message"] = commit_message
+        response = await api.put(merge_url, json=data)
+        result = response.json()
+        return result["sha"], result["merged"], result["message"]
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            sha, merged, message = await self.merge_pr(
+                credentials,
+                input_data.pr_url,
+                input_data.merge_method,
+                input_data.commit_title,
+                input_data.commit_message,
+            )
+            yield "sha", sha
+            yield "merged", merged
+            yield "message", message
+        except Exception as e:
+            yield "error", str(e)
+
+
 def prepare_pr_api_url(pr_url: str, path: str) -> str:
     # Pattern to capture the base repository URL and the pull request number
-    pattern = r"^(?:https?://)?([^/]+/[^/]+/[^/]+)/pull/(\d+)"
+    pattern = r"^(?:(https?)://)?([^/]+/[^/]+/[^/]+)/pull/(\d+)"
     match = re.match(pattern, pr_url)
     if not match:
         return pr_url
 
-    base_url, pr_number = match.groups()
-    return f"{base_url}/pulls/{pr_number}/{path}"
+    scheme, base_url, pr_number = match.groups()
+    return f"{scheme or 'https'}://{base_url}/pulls/{pr_number}/{path}"

autogpt_platform/backend/backend/blocks/github/repo.py

@@ -1,5 +1,3 @@
-import base64
-
 from typing_extensions import TypedDict
 
 from backend.blocks._base import (
@@ -19,6 +17,7 @@ from ._auth import (
     GithubCredentialsField,
     GithubCredentialsInput,
 )
+from ._utils import github_repo_path
 
 
 class GithubListTagsBlock(Block):
@@ -89,7 +88,7 @@ class GithubListTagsBlock(Block):
         tags_url = repo_url + "/tags"
         response = await api.get(tags_url)
         data = response.json()
-        repo_path = repo_url.replace("https://github.com/", "")
+        repo_path = github_repo_path(repo_url)
         tags: list[GithubListTagsBlock.Output.TagItem] = [
             {
                 "name": tag["name"],
@@ -115,101 +114,6 @@ class GithubListTagsBlock(Block):
             yield "tag", tag
 
 
-class GithubListBranchesBlock(Block):
-    class Input(BlockSchemaInput):
-        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
-        repo_url: str = SchemaField(
-            description="URL of the GitHub repository",
-            placeholder="https://github.com/owner/repo",
-        )
-
-    class Output(BlockSchemaOutput):
-        class BranchItem(TypedDict):
-            name: str
-            url: str
-
-        branch: BranchItem = SchemaField(
-            title="Branch",
-            description="Branches with their name and file tree browser URL",
-        )
-        branches: list[BranchItem] = SchemaField(
-            description="List of branches with their name and file tree browser URL"
-        )
-
-    def __init__(self):
-        super().__init__(
-            id="74243e49-2bec-4916-8bf4-db43d44aead5",
-            description="This block lists all branches for a specified GitHub repository.",
-            categories={BlockCategory.DEVELOPER_TOOLS},
-            input_schema=GithubListBranchesBlock.Input,
-            output_schema=GithubListBranchesBlock.Output,
-            test_input={
-                "repo_url": "https://github.com/owner/repo",
-                "credentials": TEST_CREDENTIALS_INPUT,
-            },
-            test_credentials=TEST_CREDENTIALS,
-            test_output=[
-                (
-                    "branches",
-                    [
-                        {
-                            "name": "main",
-                            "url": "https://github.com/owner/repo/tree/main",
-                        }
-                    ],
-                ),
-                (
-                    "branch",
-                    {
-                        "name": "main",
-                        "url": "https://github.com/owner/repo/tree/main",
-                    },
-                ),
-            ],
-            test_mock={
-                "list_branches": lambda *args, **kwargs: [
-                    {
-                        "name": "main",
-                        "url": "https://github.com/owner/repo/tree/main",
-                    }
-                ]
-            },
-        )
-
-    @staticmethod
-    async def list_branches(
-        credentials: GithubCredentials, repo_url: str
-    ) -> list[Output.BranchItem]:
-        api = get_api(credentials)
-        branches_url = repo_url + "/branches"
-        response = await api.get(branches_url)
-        data = response.json()
-        repo_path = repo_url.replace("https://github.com/", "")
-        branches: list[GithubListBranchesBlock.Output.BranchItem] = [
-            {
-                "name": branch["name"],
-                "url": f"https://github.com/{repo_path}/tree/{branch['name']}",
-            }
-            for branch in data
-        ]
-        return branches
-
-    async def run(
-        self,
-        input_data: Input,
-        *,
-        credentials: GithubCredentials,
-        **kwargs,
-    ) -> BlockOutput:
-        branches = await self.list_branches(
-            credentials,
-            input_data.repo_url,
-        )
-        yield "branches", branches
-        for branch in branches:
-            yield "branch", branch
-
-
 class GithubListDiscussionsBlock(Block):
     class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
@@ -283,7 +187,7 @@ class GithubListDiscussionsBlock(Block):
     ) -> list[Output.DiscussionItem]:
         api = get_api(credentials)
         # GitHub GraphQL API endpoint is different; we'll use api.post with custom URL
-        repo_path = repo_url.replace("https://github.com/", "")
+        repo_path = github_repo_path(repo_url)
         owner, repo = repo_path.split("/")
         query = """
         query($owner: String!, $repo: String!, $num: Int!) {
@@ -416,564 +320,6 @@ class GithubListReleasesBlock(Block):
             yield "release", release
 
 
-class GithubReadFileBlock(Block):
-    class Input(BlockSchemaInput):
-        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
-        repo_url: str = SchemaField(
-            description="URL of the GitHub repository",
-            placeholder="https://github.com/owner/repo",
-        )
-        file_path: str = SchemaField(
-            description="Path to the file in the repository",
-            placeholder="path/to/file",
-        )
-        branch: str = SchemaField(
-            description="Branch to read from",
-            placeholder="branch_name",
-            default="master",
-        )
-
-    class Output(BlockSchemaOutput):
-        text_content: str = SchemaField(
-            description="Content of the file (decoded as UTF-8 text)"
-        )
-        raw_content: str = SchemaField(
-            description="Raw base64-encoded content of the file"
-        )
-        size: int = SchemaField(description="The size of the file (in bytes)")
-
-    def __init__(self):
-        super().__init__(
-            id="87ce6c27-5752-4bbc-8e26-6da40a3dcfd3",
-            description="This block reads the content of a specified file from a GitHub repository.",
-            categories={BlockCategory.DEVELOPER_TOOLS},
-            input_schema=GithubReadFileBlock.Input,
-            output_schema=GithubReadFileBlock.Output,
-            test_input={
-                "repo_url": "https://github.com/owner/repo",
-                "file_path": "path/to/file",
-                "branch": "master",
-                "credentials": TEST_CREDENTIALS_INPUT,
-            },
-            test_credentials=TEST_CREDENTIALS,
-            test_output=[
-                ("raw_content", "RmlsZSBjb250ZW50"),
-                ("text_content", "File content"),
-                ("size", 13),
-            ],
-            test_mock={"read_file": lambda *args, **kwargs: ("RmlsZSBjb250ZW50", 13)},
-        )
-
-    @staticmethod
-    async def read_file(
-        credentials: GithubCredentials, repo_url: str, file_path: str, branch: str
-    ) -> tuple[str, int]:
-        api = get_api(credentials)
-        content_url = repo_url + f"/contents/{file_path}?ref={branch}"
-        response = await api.get(content_url)
-        data = response.json()
-
-        if isinstance(data, list):
-            # Multiple entries of different types exist at this path
-            if not (file := next((f for f in data if f["type"] == "file"), None)):
-                raise TypeError("Not a file")
-            data = file
-
-        if data["type"] != "file":
-            raise TypeError("Not a file")
-
-        return data["content"], data["size"]
-
-    async def run(
-        self,
-        input_data: Input,
-        *,
-        credentials: GithubCredentials,
-        **kwargs,
-    ) -> BlockOutput:
-        content, size = await self.read_file(
-            credentials,
-            input_data.repo_url,
-            input_data.file_path,
-            input_data.branch,
-        )
-        yield "raw_content", content
-        yield "text_content", base64.b64decode(content).decode("utf-8")
-        yield "size", size
-
-
-class GithubReadFolderBlock(Block):
-    class Input(BlockSchemaInput):
-        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
-        repo_url: str = SchemaField(
-            description="URL of the GitHub repository",
-            placeholder="https://github.com/owner/repo",
-        )
-        folder_path: str = SchemaField(
-            description="Path to the folder in the repository",
-            placeholder="path/to/folder",
-        )
-        branch: str = SchemaField(
-            description="Branch name to read from (defaults to master)",
-            placeholder="branch_name",
-            default="master",
-        )
-
-    class Output(BlockSchemaOutput):
-        class DirEntry(TypedDict):
-            name: str
-            path: str
-
-        class FileEntry(TypedDict):
-            name: str
-            path: str
-            size: int
-
-        file: FileEntry = SchemaField(description="Files in the folder")
-        dir: DirEntry = SchemaField(description="Directories in the folder")
-        error: str = SchemaField(
-            description="Error message if reading the folder failed"
-        )
-
-    def __init__(self):
-        super().__init__(
-            id="1355f863-2db3-4d75-9fba-f91e8a8ca400",
-            description="This block reads the content of a specified folder from a GitHub repository.",
-            categories={BlockCategory.DEVELOPER_TOOLS},
-            input_schema=GithubReadFolderBlock.Input,
-            output_schema=GithubReadFolderBlock.Output,
-            test_input={
-                "repo_url": "https://github.com/owner/repo",
-                "folder_path": "path/to/folder",
-                "branch": "master",
-                "credentials": TEST_CREDENTIALS_INPUT,
-            },
-            test_credentials=TEST_CREDENTIALS,
-            test_output=[
-                (
-                    "file",
-                    {
-                        "name": "file1.txt",
-                        "path": "path/to/folder/file1.txt",
-                        "size": 1337,
-                    },
-                ),
-                ("dir", {"name": "dir2", "path": "path/to/folder/dir2"}),
-            ],
-            test_mock={
-                "read_folder": lambda *args, **kwargs: (
-                    [
-                        {
-                            "name": "file1.txt",
-                            "path": "path/to/folder/file1.txt",
-                            "size": 1337,
-                        }
-                    ],
-                    [{"name": "dir2", "path": "path/to/folder/dir2"}],
-                )
-            },
-        )
-
-    @staticmethod
-    async def read_folder(
-        credentials: GithubCredentials, repo_url: str, folder_path: str, branch: str
-    ) -> tuple[list[Output.FileEntry], list[Output.DirEntry]]:
-        api = get_api(credentials)
-        contents_url = repo_url + f"/contents/{folder_path}?ref={branch}"
-        response = await api.get(contents_url)
-        data = response.json()
-
-        if not isinstance(data, list):
-            raise TypeError("Not a folder")
-
-        files: list[GithubReadFolderBlock.Output.FileEntry] = [
-            GithubReadFolderBlock.Output.FileEntry(
-                name=entry["name"],
-                path=entry["path"],
-                size=entry["size"],
-            )
-            for entry in data
-            if entry["type"] == "file"
-        ]
-
-        dirs: list[GithubReadFolderBlock.Output.DirEntry] = [
-            GithubReadFolderBlock.Output.DirEntry(
-                name=entry["name"],
-                path=entry["path"],
-            )
-            for entry in data
-            if entry["type"] == "dir"
-        ]
-
-        return files, dirs
-
-    async def run(
-        self,
-        input_data: Input,
-        *,
-        credentials: GithubCredentials,
-        **kwargs,
-    ) -> BlockOutput:
-        files, dirs = await self.read_folder(
-            credentials,
-            input_data.repo_url,
-            input_data.folder_path.lstrip("/"),
-            input_data.branch,
-        )
-        for file in files:
-            yield "file", file
-        for dir in dirs:
-            yield "dir", dir
-
-
-class GithubMakeBranchBlock(Block):
-    class Input(BlockSchemaInput):
-        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
-        repo_url: str = SchemaField(
-            description="URL of the GitHub repository",
-            placeholder="https://github.com/owner/repo",
-        )
-        new_branch: str = SchemaField(
-            description="Name of the new branch",
-            placeholder="new_branch_name",
-        )
-        source_branch: str = SchemaField(
-            description="Name of the source branch",
-            placeholder="source_branch_name",
-        )
-
-    class Output(BlockSchemaOutput):
-        status: str = SchemaField(description="Status of the branch creation operation")
-        error: str = SchemaField(
-            description="Error message if the branch creation failed"
-        )
-
-    def __init__(self):
-        super().__init__(
-            id="944cc076-95e7-4d1b-b6b6-b15d8ee5448d",
-            description="This block creates a new branch from a specified source branch.",
-            categories={BlockCategory.DEVELOPER_TOOLS},
-            input_schema=GithubMakeBranchBlock.Input,
-            output_schema=GithubMakeBranchBlock.Output,
-            test_input={
-                "repo_url": "https://github.com/owner/repo",
-                "new_branch": "new_branch_name",
-                "source_branch": "source_branch_name",
-                "credentials": TEST_CREDENTIALS_INPUT,
-            },
-            test_credentials=TEST_CREDENTIALS,
-            test_output=[("status", "Branch created successfully")],
-            test_mock={
-                "create_branch": lambda *args, **kwargs: "Branch created successfully"
-            },
-        )
-
-    @staticmethod
-    async def create_branch(
-        credentials: GithubCredentials,
-        repo_url: str,
-        new_branch: str,
-        source_branch: str,
-    ) -> str:
-        api = get_api(credentials)
-        ref_url = repo_url + f"/git/refs/heads/{source_branch}"
-        response = await api.get(ref_url)
-        data = response.json()
-        sha = data["object"]["sha"]
-
-        # Create the new branch
-        new_ref_url = repo_url + "/git/refs"
-        data = {
-            "ref": f"refs/heads/{new_branch}",
-            "sha": sha,
-        }
-        response = await api.post(new_ref_url, json=data)
-        return "Branch created successfully"
-
-    async def run(
-        self,
-        input_data: Input,
-        *,
-        credentials: GithubCredentials,
-        **kwargs,
-    ) -> BlockOutput:
-        status = await self.create_branch(
-            credentials,
-            input_data.repo_url,
-            input_data.new_branch,
-            input_data.source_branch,
-        )
-        yield "status", status
-
-
-class GithubDeleteBranchBlock(Block):
-    class Input(BlockSchemaInput):
-        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
-        repo_url: str = SchemaField(
-            description="URL of the GitHub repository",
-            placeholder="https://github.com/owner/repo",
-        )
-        branch: str = SchemaField(
-            description="Name of the branch to delete",
-            placeholder="branch_name",
-        )
-
-    class Output(BlockSchemaOutput):
-        status: str = SchemaField(description="Status of the branch deletion operation")
-        error: str = SchemaField(
-            description="Error message if the branch deletion failed"
-        )
-
-    def __init__(self):
-        super().__init__(
-            id="0d4130f7-e0ab-4d55-adc3-0a40225e80f4",
-            description="This block deletes a specified branch.",
-            categories={BlockCategory.DEVELOPER_TOOLS},
-            input_schema=GithubDeleteBranchBlock.Input,
-            output_schema=GithubDeleteBranchBlock.Output,
-            test_input={
-                "repo_url": "https://github.com/owner/repo",
-                "branch": "branch_name",
-                "credentials": TEST_CREDENTIALS_INPUT,
-            },
-            test_credentials=TEST_CREDENTIALS,
-            test_output=[("status", "Branch deleted successfully")],
-            test_mock={
-                "delete_branch": lambda *args, **kwargs: "Branch deleted successfully"
-            },
-        )
-
-    @staticmethod
-    async def delete_branch(
-        credentials: GithubCredentials, repo_url: str, branch: str
-    ) -> str:
-        api = get_api(credentials)
-        ref_url = repo_url + f"/git/refs/heads/{branch}"
-        await api.delete(ref_url)
-        return "Branch deleted successfully"
-
-    async def run(
-        self,
-        input_data: Input,
-        *,
-        credentials: GithubCredentials,
-        **kwargs,
-    ) -> BlockOutput:
-        status = await self.delete_branch(
-            credentials,
-            input_data.repo_url,
-            input_data.branch,
-        )
-        yield "status", status
-
-
-class GithubCreateFileBlock(Block):
-    class Input(BlockSchemaInput):
-        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
-        repo_url: str = SchemaField(
-            description="URL of the GitHub repository",
-            placeholder="https://github.com/owner/repo",
-        )
-        file_path: str = SchemaField(
-            description="Path where the file should be created",
-            placeholder="path/to/file.txt",
-        )
-        content: str = SchemaField(
-            description="Content to write to the file",
-            placeholder="File content here",
-        )
-        branch: str = SchemaField(
-            description="Branch where the file should be created",
-            default="main",
-        )
-        commit_message: str = SchemaField(
-            description="Message for the commit",
-            default="Create new file",
-        )
-
-    class Output(BlockSchemaOutput):
-        url: str = SchemaField(description="URL of the created file")
-        sha: str = SchemaField(description="SHA of the commit")
-        error: str = SchemaField(
-            description="Error message if the file creation failed"
-        )
-
-    def __init__(self):
-        super().__init__(
-            id="8fd132ac-b917-428a-8159-d62893e8a3fe",
-            description="This block creates a new file in a GitHub repository.",
-            categories={BlockCategory.DEVELOPER_TOOLS},
-            input_schema=GithubCreateFileBlock.Input,
-            output_schema=GithubCreateFileBlock.Output,
-            test_input={
-                "repo_url": "https://github.com/owner/repo",
-                "file_path": "test/file.txt",
-                "content": "Test content",
-                "branch": "main",
-                "commit_message": "Create test file",
-                "credentials": TEST_CREDENTIALS_INPUT,
-            },
-            test_credentials=TEST_CREDENTIALS,
-            test_output=[
-                ("url", "https://github.com/owner/repo/blob/main/test/file.txt"),
-                ("sha", "abc123"),
-            ],
-            test_mock={
-                "create_file": lambda *args, **kwargs: (
-                    "https://github.com/owner/repo/blob/main/test/file.txt",
-                    "abc123",
-                )
-            },
-        )
-
-    @staticmethod
-    async def create_file(
-        credentials: GithubCredentials,
-        repo_url: str,
-        file_path: str,
-        content: str,
-        branch: str,
-        commit_message: str,
-    ) -> tuple[str, str]:
-        api = get_api(credentials)
-        contents_url = repo_url + f"/contents/{file_path}"
-        content_base64 = base64.b64encode(content.encode()).decode()
-        data = {
-            "message": commit_message,
-            "content": content_base64,
-            "branch": branch,
-        }
-        response = await api.put(contents_url, json=data)
-        data = response.json()
-        return data["content"]["html_url"], data["commit"]["sha"]
-
-    async def run(
-        self,
-        input_data: Input,
-        *,
-        credentials: GithubCredentials,
-        **kwargs,
-    ) -> BlockOutput:
-        try:
-            url, sha = await self.create_file(
-                credentials,
-                input_data.repo_url,
-                input_data.file_path,
-                input_data.content,
-                input_data.branch,
-                input_data.commit_message,
-            )
-            yield "url", url
-            yield "sha", sha
-        except Exception as e:
-            yield "error", str(e)
-
-
-class GithubUpdateFileBlock(Block):
-    class Input(BlockSchemaInput):
-        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
-        repo_url: str = SchemaField(
-            description="URL of the GitHub repository",
-            placeholder="https://github.com/owner/repo",
-        )
-        file_path: str = SchemaField(
-            description="Path to the file to update",
-            placeholder="path/to/file.txt",
-        )
-        content: str = SchemaField(
-            description="New content for the file",
-            placeholder="Updated content here",
-        )
-        branch: str = SchemaField(
-            description="Branch containing the file",
-            default="main",
-        )
-        commit_message: str = SchemaField(
-            description="Message for the commit",
-            default="Update file",
-        )
-
-    class Output(BlockSchemaOutput):
-        url: str = SchemaField(description="URL of the updated file")
-        sha: str = SchemaField(description="SHA of the commit")
-
-    def __init__(self):
-        super().__init__(
-            id="30be12a4-57cb-4aa4-baf5-fcc68d136076",
-            description="This block updates an existing file in a GitHub repository.",
-            categories={BlockCategory.DEVELOPER_TOOLS},
-            input_schema=GithubUpdateFileBlock.Input,
-            output_schema=GithubUpdateFileBlock.Output,
-            test_input={
-                "repo_url": "https://github.com/owner/repo",
-                "file_path": "test/file.txt",
-                "content": "Updated content",
-                "branch": "main",
-                "commit_message": "Update test file",
-                "credentials": TEST_CREDENTIALS_INPUT,
-            },
-            test_credentials=TEST_CREDENTIALS,
-            test_output=[
-                ("url", "https://github.com/owner/repo/blob/main/test/file.txt"),
-                ("sha", "def456"),
-            ],
-            test_mock={
-                "update_file": lambda *args, **kwargs: (
-                    "https://github.com/owner/repo/blob/main/test/file.txt",
-                    "def456",
-                )
-            },
-        )
-
-    @staticmethod
-    async def update_file(
-        credentials: GithubCredentials,
-        repo_url: str,
-        file_path: str,
-        content: str,
-        branch: str,
-        commit_message: str,
-    ) -> tuple[str, str]:
-        api = get_api(credentials)
-        contents_url = repo_url + f"/contents/{file_path}"
-        params = {"ref": branch}
-        response = await api.get(contents_url, params=params)
-        data = response.json()
-
-        # Convert new content to base64
-        content_base64 = base64.b64encode(content.encode()).decode()
-        data = {
-            "message": commit_message,
-            "content": content_base64,
-            "sha": data["sha"],
-            "branch": branch,
-        }
-        response = await api.put(contents_url, json=data)
-        data = response.json()
-        return data["content"]["html_url"], data["commit"]["sha"]
-
-    async def run(
-        self,
-        input_data: Input,
-        *,
-        credentials: GithubCredentials,
-        **kwargs,
-    ) -> BlockOutput:
-        try:
-            url, sha = await self.update_file(
-                credentials,
-                input_data.repo_url,
-                input_data.file_path,
-                input_data.content,
-                input_data.branch,
-                input_data.commit_message,
-            )
-            yield "url", url
-            yield "sha", sha
-        except Exception as e:
-            yield "error", str(e)
-
-
 class GithubCreateRepositoryBlock(Block):
     class Input(BlockSchemaInput):
         credentials: GithubCredentialsInput = GithubCredentialsField("repo")
@@ -1103,7 +449,7 @@ class GithubListStargazersBlock(Block):
 
     def __init__(self):
         super().__init__(
-            id="a4b9c2d1-e5f6-4g7h-8i9j-0k1l2m3n4o5p",  # Generated unique UUID
+            id="e96d01ec-b55e-4a99-8ce8-c8776dce850b",  # Generated unique UUID
             description="This block lists all users who have starred a specified GitHub repository.",
             categories={BlockCategory.DEVELOPER_TOOLS},
             input_schema=GithubListStargazersBlock.Input,
@@ -1172,3 +518,230 @@ class GithubListStargazersBlock(Block):
         yield "stargazers", stargazers
         for stargazer in stargazers:
             yield "stargazer", stargazer
+
+
+class GithubGetRepositoryInfoBlock(Block):
+    class Input(BlockSchemaInput):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        repo_url: str = SchemaField(
+            description="URL of the GitHub repository",
+            placeholder="https://github.com/owner/repo",
+        )
+
+    class Output(BlockSchemaOutput):
+        name: str = SchemaField(description="Repository name")
+        full_name: str = SchemaField(description="Full repository name (owner/repo)")
+        description: str = SchemaField(description="Repository description")
+        default_branch: str = SchemaField(description="Default branch name (e.g. main)")
+        private: bool = SchemaField(description="Whether the repository is private")
+        html_url: str = SchemaField(description="Web URL of the repository")
+        clone_url: str = SchemaField(description="Git clone URL")
+        stars: int = SchemaField(description="Number of stars")
+        forks: int = SchemaField(description="Number of forks")
+        open_issues: int = SchemaField(description="Number of open issues")
+        error: str = SchemaField(
+            description="Error message if fetching repo info failed"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="59d4f241-968a-4040-95da-348ac5c5ce27",
+            description="This block retrieves metadata about a GitHub repository.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubGetRepositoryInfoBlock.Input,
+            output_schema=GithubGetRepositoryInfoBlock.Output,
+            test_input={
+                "repo_url": "https://github.com/owner/repo",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("name", "repo"),
+                ("full_name", "owner/repo"),
+                ("description", "A test repo"),
+                ("default_branch", "main"),
+                ("private", False),
+                ("html_url", "https://github.com/owner/repo"),
+                ("clone_url", "https://github.com/owner/repo.git"),
+                ("stars", 42),
+                ("forks", 5),
+                ("open_issues", 3),
+            ],
+            test_mock={
+                "get_repo_info": lambda *args, **kwargs: {
+                    "name": "repo",
+                    "full_name": "owner/repo",
+                    "description": "A test repo",
+                    "default_branch": "main",
+                    "private": False,
+                    "html_url": "https://github.com/owner/repo",
+                    "clone_url": "https://github.com/owner/repo.git",
+                    "stargazers_count": 42,
+                    "forks_count": 5,
+                    "open_issues_count": 3,
+                }
+            },
+        )
+
+    @staticmethod
+    async def get_repo_info(credentials: GithubCredentials, repo_url: str) -> dict:
+        api = get_api(credentials)
+        response = await api.get(repo_url)
+        return response.json()
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            data = await self.get_repo_info(credentials, input_data.repo_url)
+            yield "name", data["name"]
+            yield "full_name", data["full_name"]
+            yield "description", data.get("description", "") or ""
+            yield "default_branch", data["default_branch"]
+            yield "private", data["private"]
+            yield "html_url", data["html_url"]
+            yield "clone_url", data["clone_url"]
+            yield "stars", data["stargazers_count"]
+            yield "forks", data["forks_count"]
+            yield "open_issues", data["open_issues_count"]
+        except Exception as e:
+            yield "error", str(e)
+
+
+class GithubForkRepositoryBlock(Block):
+    class Input(BlockSchemaInput):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        repo_url: str = SchemaField(
+            description="URL of the GitHub repository to fork",
+            placeholder="https://github.com/owner/repo",
+        )
+        organization: str = SchemaField(
+            description="Organization to fork into (leave empty to fork to your account)",
+            default="",
+        )
+
+    class Output(BlockSchemaOutput):
+        url: str = SchemaField(description="URL of the forked repository")
+        clone_url: str = SchemaField(description="Git clone URL of the fork")
+        full_name: str = SchemaField(description="Full name of the fork (owner/repo)")
+        error: str = SchemaField(description="Error message if the fork failed")
+
+    def __init__(self):
+        super().__init__(
+            id="a439f2f4-835f-4dae-ba7b-0205ffa70be6",
+            description="This block forks a GitHub repository to your account or an organization.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubForkRepositoryBlock.Input,
+            output_schema=GithubForkRepositoryBlock.Output,
+            test_input={
+                "repo_url": "https://github.com/owner/repo",
+                "organization": "",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("url", "https://github.com/myuser/repo"),
+                ("clone_url", "https://github.com/myuser/repo.git"),
+                ("full_name", "myuser/repo"),
+            ],
+            test_mock={
+                "fork_repo": lambda *args, **kwargs: (
+                    "https://github.com/myuser/repo",
+                    "https://github.com/myuser/repo.git",
+                    "myuser/repo",
+                )
+            },
+        )
+
+    @staticmethod
+    async def fork_repo(
+        credentials: GithubCredentials,
+        repo_url: str,
+        organization: str,
+    ) -> tuple[str, str, str]:
+        api = get_api(credentials)
+        forks_url = repo_url + "/forks"
+        data: dict[str, str] = {}
+        if organization:
+            data["organization"] = organization
+        response = await api.post(forks_url, json=data)
+        result = response.json()
+        return result["html_url"], result["clone_url"], result["full_name"]
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            url, clone_url, full_name = await self.fork_repo(
+                credentials,
+                input_data.repo_url,
+                input_data.organization,
+            )
+            yield "url", url
+            yield "clone_url", clone_url
+            yield "full_name", full_name
+        except Exception as e:
+            yield "error", str(e)
+
+
+class GithubStarRepositoryBlock(Block):
+    class Input(BlockSchemaInput):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        repo_url: str = SchemaField(
+            description="URL of the GitHub repository to star",
+            placeholder="https://github.com/owner/repo",
+        )
+
+    class Output(BlockSchemaOutput):
+        status: str = SchemaField(description="Status of the star operation")
+        error: str = SchemaField(description="Error message if starring failed")
+
+    def __init__(self):
+        super().__init__(
+            id="bd700764-53e3-44dd-a969-d1854088458f",
+            description="This block stars a GitHub repository.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubStarRepositoryBlock.Input,
+            output_schema=GithubStarRepositoryBlock.Output,
+            test_input={
+                "repo_url": "https://github.com/owner/repo",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[("status", "Repository starred successfully")],
+            test_mock={
+                "star_repo": lambda *args, **kwargs: "Repository starred successfully"
+            },
+        )
+
+    @staticmethod
+    async def star_repo(credentials: GithubCredentials, repo_url: str) -> str:
+        api = get_api(credentials, convert_urls=False)
+        repo_path = github_repo_path(repo_url)
+        owner, repo = repo_path.split("/")
+        await api.put(
+            f"https://api.github.com/user/starred/{owner}/{repo}",
+            headers={"Content-Length": "0"},
+        )
+        return "Repository starred successfully"
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            status = await self.star_repo(credentials, input_data.repo_url)
+            yield "status", status
+        except Exception as e:
+            yield "error", str(e)

autogpt_platform/backend/backend/blocks/github/repo_branches.py

@@ -0,0 +1,452 @@
+from urllib.parse import quote
+
+from typing_extensions import TypedDict
+
+from backend.blocks._base import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
+from backend.data.model import SchemaField
+
+from ._api import get_api
+from ._auth import (
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    GithubCredentials,
+    GithubCredentialsField,
+    GithubCredentialsInput,
+)
+from ._utils import github_repo_path
+
+
+class GithubListBranchesBlock(Block):
+    class Input(BlockSchemaInput):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        repo_url: str = SchemaField(
+            description="URL of the GitHub repository",
+            placeholder="https://github.com/owner/repo",
+        )
+        per_page: int = SchemaField(
+            description="Number of branches to return per page (max 100)",
+            default=30,
+            ge=1,
+            le=100,
+        )
+        page: int = SchemaField(
+            description="Page number for pagination",
+            default=1,
+            ge=1,
+        )
+
+    class Output(BlockSchemaOutput):
+        class BranchItem(TypedDict):
+            name: str
+            url: str
+
+        branch: BranchItem = SchemaField(
+            title="Branch",
+            description="Branches with their name and file tree browser URL",
+        )
+        branches: list[BranchItem] = SchemaField(
+            description="List of branches with their name and file tree browser URL"
+        )
+        error: str = SchemaField(description="Error message if listing branches failed")
+
+    def __init__(self):
+        super().__init__(
+            id="74243e49-2bec-4916-8bf4-db43d44aead5",
+            description="This block lists all branches for a specified GitHub repository.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubListBranchesBlock.Input,
+            output_schema=GithubListBranchesBlock.Output,
+            test_input={
+                "repo_url": "https://github.com/owner/repo",
+                "per_page": 30,
+                "page": 1,
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                (
+                    "branches",
+                    [
+                        {
+                            "name": "main",
+                            "url": "https://github.com/owner/repo/tree/main",
+                        }
+                    ],
+                ),
+                (
+                    "branch",
+                    {
+                        "name": "main",
+                        "url": "https://github.com/owner/repo/tree/main",
+                    },
+                ),
+            ],
+            test_mock={
+                "list_branches": lambda *args, **kwargs: [
+                    {
+                        "name": "main",
+                        "url": "https://github.com/owner/repo/tree/main",
+                    }
+                ]
+            },
+        )
+
+    @staticmethod
+    async def list_branches(
+        credentials: GithubCredentials, repo_url: str, per_page: int, page: int
+    ) -> list[Output.BranchItem]:
+        api = get_api(credentials)
+        branches_url = repo_url + "/branches"
+        response = await api.get(
+            branches_url, params={"per_page": str(per_page), "page": str(page)}
+        )
+        data = response.json()
+        repo_path = github_repo_path(repo_url)
+        branches: list[GithubListBranchesBlock.Output.BranchItem] = [
+            {
+                "name": branch["name"],
+                "url": f"https://github.com/{repo_path}/tree/{branch['name']}",
+            }
+            for branch in data
+        ]
+        return branches
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            branches = await self.list_branches(
+                credentials,
+                input_data.repo_url,
+                input_data.per_page,
+                input_data.page,
+            )
+            yield "branches", branches
+            for branch in branches:
+                yield "branch", branch
+        except Exception as e:
+            yield "error", str(e)
+
+
+class GithubMakeBranchBlock(Block):
+    class Input(BlockSchemaInput):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        repo_url: str = SchemaField(
+            description="URL of the GitHub repository",
+            placeholder="https://github.com/owner/repo",
+        )
+        new_branch: str = SchemaField(
+            description="Name of the new branch",
+            placeholder="new_branch_name",
+        )
+        source_branch: str = SchemaField(
+            description="Name of the source branch",
+            placeholder="source_branch_name",
+        )
+
+    class Output(BlockSchemaOutput):
+        status: str = SchemaField(description="Status of the branch creation operation")
+        error: str = SchemaField(
+            description="Error message if the branch creation failed"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="944cc076-95e7-4d1b-b6b6-b15d8ee5448d",
+            description="This block creates a new branch from a specified source branch.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubMakeBranchBlock.Input,
+            output_schema=GithubMakeBranchBlock.Output,
+            test_input={
+                "repo_url": "https://github.com/owner/repo",
+                "new_branch": "new_branch_name",
+                "source_branch": "source_branch_name",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[("status", "Branch created successfully")],
+            test_mock={
+                "create_branch": lambda *args, **kwargs: "Branch created successfully"
+            },
+        )
+
+    @staticmethod
+    async def create_branch(
+        credentials: GithubCredentials,
+        repo_url: str,
+        new_branch: str,
+        source_branch: str,
+    ) -> str:
+        api = get_api(credentials)
+        ref_url = repo_url + f"/git/refs/heads/{quote(source_branch, safe='')}"
+        response = await api.get(ref_url)
+        data = response.json()
+        sha = data["object"]["sha"]
+
+        # Create the new branch
+        new_ref_url = repo_url + "/git/refs"
+        data = {
+            "ref": f"refs/heads/{new_branch}",
+            "sha": sha,
+        }
+        response = await api.post(new_ref_url, json=data)
+        return "Branch created successfully"
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            status = await self.create_branch(
+                credentials,
+                input_data.repo_url,
+                input_data.new_branch,
+                input_data.source_branch,
+            )
+            yield "status", status
+        except Exception as e:
+            yield "error", str(e)
+
+
+class GithubDeleteBranchBlock(Block):
+    class Input(BlockSchemaInput):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        repo_url: str = SchemaField(
+            description="URL of the GitHub repository",
+            placeholder="https://github.com/owner/repo",
+        )
+        branch: str = SchemaField(
+            description="Name of the branch to delete",
+            placeholder="branch_name",
+        )
+
+    class Output(BlockSchemaOutput):
+        status: str = SchemaField(description="Status of the branch deletion operation")
+        error: str = SchemaField(
+            description="Error message if the branch deletion failed"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="0d4130f7-e0ab-4d55-adc3-0a40225e80f4",
+            description="This block deletes a specified branch.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubDeleteBranchBlock.Input,
+            output_schema=GithubDeleteBranchBlock.Output,
+            test_input={
+                "repo_url": "https://github.com/owner/repo",
+                "branch": "branch_name",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[("status", "Branch deleted successfully")],
+            test_mock={
+                "delete_branch": lambda *args, **kwargs: "Branch deleted successfully"
+            },
+            is_sensitive_action=True,
+        )
+
+    @staticmethod
+    async def delete_branch(
+        credentials: GithubCredentials, repo_url: str, branch: str
+    ) -> str:
+        api = get_api(credentials)
+        ref_url = repo_url + f"/git/refs/heads/{quote(branch, safe='')}"
+        await api.delete(ref_url)
+        return "Branch deleted successfully"
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            status = await self.delete_branch(
+                credentials,
+                input_data.repo_url,
+                input_data.branch,
+            )
+            yield "status", status
+        except Exception as e:
+            yield "error", str(e)
+
+
+class GithubCompareBranchesBlock(Block):
+    class Input(BlockSchemaInput):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        repo_url: str = SchemaField(
+            description="URL of the GitHub repository",
+            placeholder="https://github.com/owner/repo",
+        )
+        base: str = SchemaField(
+            description="Base branch or commit SHA",
+            placeholder="main",
+        )
+        head: str = SchemaField(
+            description="Head branch or commit SHA to compare against base",
+            placeholder="feature-branch",
+        )
+
+    class Output(BlockSchemaOutput):
+        class FileChange(TypedDict):
+            filename: str
+            status: str
+            additions: int
+            deletions: int
+            patch: str
+
+        status: str = SchemaField(
+            description="Comparison status: ahead, behind, diverged, or identical"
+        )
+        ahead_by: int = SchemaField(
+            description="Number of commits head is ahead of base"
+        )
+        behind_by: int = SchemaField(
+            description="Number of commits head is behind base"
+        )
+        total_commits: int = SchemaField(
+            description="Total number of commits in the comparison"
+        )
+        diff: str = SchemaField(description="Unified diff of all file changes")
+        file: FileChange = SchemaField(
+            title="Changed File", description="A changed file with its diff"
+        )
+        files: list[FileChange] = SchemaField(
+            description="List of changed files with their diffs"
+        )
+        error: str = SchemaField(description="Error message if comparison failed")
+
+    def __init__(self):
+        super().__init__(
+            id="2e4faa8c-6086-4546-ba77-172d1d560186",
+            description="This block compares two branches or commits in a GitHub repository.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubCompareBranchesBlock.Input,
+            output_schema=GithubCompareBranchesBlock.Output,
+            test_input={
+                "repo_url": "https://github.com/owner/repo",
+                "base": "main",
+                "head": "feature",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("status", "ahead"),
+                ("ahead_by", 2),
+                ("behind_by", 0),
+                ("total_commits", 2),
+                ("diff", "+++ b/file.py\n+new line"),
+                (
+                    "files",
+                    [
+                        {
+                            "filename": "file.py",
+                            "status": "modified",
+                            "additions": 1,
+                            "deletions": 0,
+                            "patch": "+new line",
+                        }
+                    ],
+                ),
+                (
+                    "file",
+                    {
+                        "filename": "file.py",
+                        "status": "modified",
+                        "additions": 1,
+                        "deletions": 0,
+                        "patch": "+new line",
+                    },
+                ),
+            ],
+            test_mock={
+                "compare_branches": lambda *args, **kwargs: {
+                    "status": "ahead",
+                    "ahead_by": 2,
+                    "behind_by": 0,
+                    "total_commits": 2,
+                    "files": [
+                        {
+                            "filename": "file.py",
+                            "status": "modified",
+                            "additions": 1,
+                            "deletions": 0,
+                            "patch": "+new line",
+                        }
+                    ],
+                }
+            },
+        )
+
+    @staticmethod
+    async def compare_branches(
+        credentials: GithubCredentials,
+        repo_url: str,
+        base: str,
+        head: str,
+    ) -> dict:
+        api = get_api(credentials)
+        safe_base = quote(base, safe="")
+        safe_head = quote(head, safe="")
+        compare_url = repo_url + f"/compare/{safe_base}...{safe_head}"
+        response = await api.get(compare_url)
+        return response.json()
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            data = await self.compare_branches(
+                credentials,
+                input_data.repo_url,
+                input_data.base,
+                input_data.head,
+            )
+            yield "status", data["status"]
+            yield "ahead_by", data["ahead_by"]
+            yield "behind_by", data["behind_by"]
+            yield "total_commits", data["total_commits"]
+
+            files: list[GithubCompareBranchesBlock.Output.FileChange] = [
+                GithubCompareBranchesBlock.Output.FileChange(
+                    filename=f["filename"],
+                    status=f["status"],
+                    additions=f["additions"],
+                    deletions=f["deletions"],
+                    patch=f.get("patch", ""),
+                )
+                for f in data.get("files", [])
+            ]
+
+            # Build unified diff
+            diff_parts = []
+            for f in data.get("files", []):
+                patch = f.get("patch", "")
+                if patch:
+                    diff_parts.append(f"+++ b/{f['filename']}\n{patch}")
+            yield "diff", "\n".join(diff_parts)
+
+            yield "files", files
+            for file in files:
+                yield "file", file
+        except Exception as e:
+            yield "error", str(e)

autogpt_platform/backend/backend/blocks/github/repo_files.py

@@ -0,0 +1,720 @@
+import base64
+from urllib.parse import quote
+
+from typing_extensions import TypedDict
+
+from backend.blocks._base import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
+from backend.data.model import SchemaField
+
+from ._api import get_api
+from ._auth import (
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    GithubCredentials,
+    GithubCredentialsField,
+    GithubCredentialsInput,
+)
+
+
+class GithubReadFileBlock(Block):
+    class Input(BlockSchemaInput):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        repo_url: str = SchemaField(
+            description="URL of the GitHub repository",
+            placeholder="https://github.com/owner/repo",
+        )
+        file_path: str = SchemaField(
+            description="Path to the file in the repository",
+            placeholder="path/to/file",
+        )
+        branch: str = SchemaField(
+            description="Branch to read from",
+            placeholder="branch_name",
+            default="main",
+        )
+
+    class Output(BlockSchemaOutput):
+        text_content: str = SchemaField(
+            description="Content of the file (decoded as UTF-8 text)"
+        )
+        raw_content: str = SchemaField(
+            description="Raw base64-encoded content of the file"
+        )
+        size: int = SchemaField(description="The size of the file (in bytes)")
+        error: str = SchemaField(description="Error message if reading the file failed")
+
+    def __init__(self):
+        super().__init__(
+            id="87ce6c27-5752-4bbc-8e26-6da40a3dcfd3",
+            description="This block reads the content of a specified file from a GitHub repository.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubReadFileBlock.Input,
+            output_schema=GithubReadFileBlock.Output,
+            test_input={
+                "repo_url": "https://github.com/owner/repo",
+                "file_path": "path/to/file",
+                "branch": "main",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("raw_content", "RmlsZSBjb250ZW50"),
+                ("text_content", "File content"),
+                ("size", 13),
+            ],
+            test_mock={"read_file": lambda *args, **kwargs: ("RmlsZSBjb250ZW50", 13)},
+        )
+
+    @staticmethod
+    async def read_file(
+        credentials: GithubCredentials, repo_url: str, file_path: str, branch: str
+    ) -> tuple[str, int]:
+        api = get_api(credentials)
+        content_url = (
+            repo_url
+            + f"/contents/{quote(file_path, safe='')}?ref={quote(branch, safe='')}"
+        )
+        response = await api.get(content_url)
+        data = response.json()
+
+        if isinstance(data, list):
+            # Multiple entries of different types exist at this path
+            if not (file := next((f for f in data if f["type"] == "file"), None)):
+                raise TypeError("Not a file")
+            data = file
+
+        if data["type"] != "file":
+            raise TypeError("Not a file")
+
+        return data["content"], data["size"]
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            content, size = await self.read_file(
+                credentials,
+                input_data.repo_url,
+                input_data.file_path,
+                input_data.branch,
+            )
+            yield "raw_content", content
+            yield "text_content", base64.b64decode(content).decode("utf-8")
+            yield "size", size
+        except Exception as e:
+            yield "error", str(e)
+
+
+class GithubReadFolderBlock(Block):
+    class Input(BlockSchemaInput):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        repo_url: str = SchemaField(
+            description="URL of the GitHub repository",
+            placeholder="https://github.com/owner/repo",
+        )
+        folder_path: str = SchemaField(
+            description="Path to the folder in the repository",
+            placeholder="path/to/folder",
+        )
+        branch: str = SchemaField(
+            description="Branch name to read from (defaults to main)",
+            placeholder="branch_name",
+            default="main",
+        )
+
+    class Output(BlockSchemaOutput):
+        class DirEntry(TypedDict):
+            name: str
+            path: str
+
+        class FileEntry(TypedDict):
+            name: str
+            path: str
+            size: int
+
+        file: FileEntry = SchemaField(description="Files in the folder")
+        dir: DirEntry = SchemaField(description="Directories in the folder")
+        error: str = SchemaField(
+            description="Error message if reading the folder failed"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="1355f863-2db3-4d75-9fba-f91e8a8ca400",
+            description="This block reads the content of a specified folder from a GitHub repository.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubReadFolderBlock.Input,
+            output_schema=GithubReadFolderBlock.Output,
+            test_input={
+                "repo_url": "https://github.com/owner/repo",
+                "folder_path": "path/to/folder",
+                "branch": "main",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                (
+                    "file",
+                    {
+                        "name": "file1.txt",
+                        "path": "path/to/folder/file1.txt",
+                        "size": 1337,
+                    },
+                ),
+                ("dir", {"name": "dir2", "path": "path/to/folder/dir2"}),
+            ],
+            test_mock={
+                "read_folder": lambda *args, **kwargs: (
+                    [
+                        {
+                            "name": "file1.txt",
+                            "path": "path/to/folder/file1.txt",
+                            "size": 1337,
+                        }
+                    ],
+                    [{"name": "dir2", "path": "path/to/folder/dir2"}],
+                )
+            },
+        )
+
+    @staticmethod
+    async def read_folder(
+        credentials: GithubCredentials, repo_url: str, folder_path: str, branch: str
+    ) -> tuple[list[Output.FileEntry], list[Output.DirEntry]]:
+        api = get_api(credentials)
+        contents_url = (
+            repo_url
+            + f"/contents/{quote(folder_path, safe='/')}?ref={quote(branch, safe='')}"
+        )
+        response = await api.get(contents_url)
+        data = response.json()
+
+        if not isinstance(data, list):
+            raise TypeError("Not a folder")
+
+        files: list[GithubReadFolderBlock.Output.FileEntry] = [
+            GithubReadFolderBlock.Output.FileEntry(
+                name=entry["name"],
+                path=entry["path"],
+                size=entry["size"],
+            )
+            for entry in data
+            if entry["type"] == "file"
+        ]
+
+        dirs: list[GithubReadFolderBlock.Output.DirEntry] = [
+            GithubReadFolderBlock.Output.DirEntry(
+                name=entry["name"],
+                path=entry["path"],
+            )
+            for entry in data
+            if entry["type"] == "dir"
+        ]
+
+        return files, dirs
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            files, dirs = await self.read_folder(
+                credentials,
+                input_data.repo_url,
+                input_data.folder_path.lstrip("/"),
+                input_data.branch,
+            )
+            for file in files:
+                yield "file", file
+            for dir in dirs:
+                yield "dir", dir
+        except Exception as e:
+            yield "error", str(e)
+
+
+class GithubCreateFileBlock(Block):
+    class Input(BlockSchemaInput):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        repo_url: str = SchemaField(
+            description="URL of the GitHub repository",
+            placeholder="https://github.com/owner/repo",
+        )
+        file_path: str = SchemaField(
+            description="Path where the file should be created",
+            placeholder="path/to/file.txt",
+        )
+        content: str = SchemaField(
+            description="Content to write to the file",
+            placeholder="File content here",
+        )
+        branch: str = SchemaField(
+            description="Branch where the file should be created",
+            default="main",
+        )
+        commit_message: str = SchemaField(
+            description="Message for the commit",
+            default="Create new file",
+        )
+
+    class Output(BlockSchemaOutput):
+        url: str = SchemaField(description="URL of the created file")
+        sha: str = SchemaField(description="SHA of the commit")
+        error: str = SchemaField(
+            description="Error message if the file creation failed"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="8fd132ac-b917-428a-8159-d62893e8a3fe",
+            description="This block creates a new file in a GitHub repository.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubCreateFileBlock.Input,
+            output_schema=GithubCreateFileBlock.Output,
+            test_input={
+                "repo_url": "https://github.com/owner/repo",
+                "file_path": "test/file.txt",
+                "content": "Test content",
+                "branch": "main",
+                "commit_message": "Create test file",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("url", "https://github.com/owner/repo/blob/main/test/file.txt"),
+                ("sha", "abc123"),
+            ],
+            test_mock={
+                "create_file": lambda *args, **kwargs: (
+                    "https://github.com/owner/repo/blob/main/test/file.txt",
+                    "abc123",
+                )
+            },
+        )
+
+    @staticmethod
+    async def create_file(
+        credentials: GithubCredentials,
+        repo_url: str,
+        file_path: str,
+        content: str,
+        branch: str,
+        commit_message: str,
+    ) -> tuple[str, str]:
+        api = get_api(credentials)
+        contents_url = repo_url + f"/contents/{quote(file_path, safe='/')}"
+        content_base64 = base64.b64encode(content.encode()).decode()
+        data = {
+            "message": commit_message,
+            "content": content_base64,
+            "branch": branch,
+        }
+        response = await api.put(contents_url, json=data)
+        data = response.json()
+        return data["content"]["html_url"], data["commit"]["sha"]
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            url, sha = await self.create_file(
+                credentials,
+                input_data.repo_url,
+                input_data.file_path,
+                input_data.content,
+                input_data.branch,
+                input_data.commit_message,
+            )
+            yield "url", url
+            yield "sha", sha
+        except Exception as e:
+            yield "error", str(e)
+
+
+class GithubUpdateFileBlock(Block):
+    class Input(BlockSchemaInput):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        repo_url: str = SchemaField(
+            description="URL of the GitHub repository",
+            placeholder="https://github.com/owner/repo",
+        )
+        file_path: str = SchemaField(
+            description="Path to the file to update",
+            placeholder="path/to/file.txt",
+        )
+        content: str = SchemaField(
+            description="New content for the file",
+            placeholder="Updated content here",
+        )
+        branch: str = SchemaField(
+            description="Branch containing the file",
+            default="main",
+        )
+        commit_message: str = SchemaField(
+            description="Message for the commit",
+            default="Update file",
+        )
+
+    class Output(BlockSchemaOutput):
+        url: str = SchemaField(description="URL of the updated file")
+        sha: str = SchemaField(description="SHA of the commit")
+
+    def __init__(self):
+        super().__init__(
+            id="30be12a4-57cb-4aa4-baf5-fcc68d136076",
+            description="This block updates an existing file in a GitHub repository.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubUpdateFileBlock.Input,
+            output_schema=GithubUpdateFileBlock.Output,
+            test_input={
+                "repo_url": "https://github.com/owner/repo",
+                "file_path": "test/file.txt",
+                "content": "Updated content",
+                "branch": "main",
+                "commit_message": "Update test file",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("url", "https://github.com/owner/repo/blob/main/test/file.txt"),
+                ("sha", "def456"),
+            ],
+            test_mock={
+                "update_file": lambda *args, **kwargs: (
+                    "https://github.com/owner/repo/blob/main/test/file.txt",
+                    "def456",
+                )
+            },
+        )
+
+    @staticmethod
+    async def update_file(
+        credentials: GithubCredentials,
+        repo_url: str,
+        file_path: str,
+        content: str,
+        branch: str,
+        commit_message: str,
+    ) -> tuple[str, str]:
+        api = get_api(credentials)
+        contents_url = repo_url + f"/contents/{quote(file_path, safe='/')}"
+        params = {"ref": branch}
+        response = await api.get(contents_url, params=params)
+        data = response.json()
+
+        # Convert new content to base64
+        content_base64 = base64.b64encode(content.encode()).decode()
+        data = {
+            "message": commit_message,
+            "content": content_base64,
+            "sha": data["sha"],
+            "branch": branch,
+        }
+        response = await api.put(contents_url, json=data)
+        data = response.json()
+        return data["content"]["html_url"], data["commit"]["sha"]
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            url, sha = await self.update_file(
+                credentials,
+                input_data.repo_url,
+                input_data.file_path,
+                input_data.content,
+                input_data.branch,
+                input_data.commit_message,
+            )
+            yield "url", url
+            yield "sha", sha
+        except Exception as e:
+            yield "error", str(e)
+
+
+class GithubSearchCodeBlock(Block):
+    class Input(BlockSchemaInput):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        query: str = SchemaField(
+            description="Search query (GitHub code search syntax)",
+            placeholder="className language:python",
+        )
+        repo: str = SchemaField(
+            description="Restrict search to a repository (owner/repo format, optional)",
+            default="",
+            placeholder="owner/repo",
+        )
+        per_page: int = SchemaField(
+            description="Number of results to return (max 100)",
+            default=30,
+            ge=1,
+            le=100,
+        )
+
+    class Output(BlockSchemaOutput):
+        class SearchResult(TypedDict):
+            name: str
+            path: str
+            repository: str
+            url: str
+            score: float
+
+        result: SearchResult = SchemaField(
+            title="Result", description="A code search result"
+        )
+        results: list[SearchResult] = SchemaField(
+            description="List of code search results"
+        )
+        total_count: int = SchemaField(description="Total number of matching results")
+        error: str = SchemaField(description="Error message if search failed")
+
+    def __init__(self):
+        super().__init__(
+            id="47f94891-a2b1-4f1c-b5f2-573c043f721e",
+            description="This block searches for code in GitHub repositories.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubSearchCodeBlock.Input,
+            output_schema=GithubSearchCodeBlock.Output,
+            test_input={
+                "query": "addClass",
+                "repo": "owner/repo",
+                "per_page": 30,
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("total_count", 1),
+                (
+                    "results",
+                    [
+                        {
+                            "name": "file.py",
+                            "path": "src/file.py",
+                            "repository": "owner/repo",
+                            "url": "https://github.com/owner/repo/blob/main/src/file.py",
+                            "score": 1.0,
+                        }
+                    ],
+                ),
+                (
+                    "result",
+                    {
+                        "name": "file.py",
+                        "path": "src/file.py",
+                        "repository": "owner/repo",
+                        "url": "https://github.com/owner/repo/blob/main/src/file.py",
+                        "score": 1.0,
+                    },
+                ),
+            ],
+            test_mock={
+                "search_code": lambda *args, **kwargs: (
+                    1,
+                    [
+                        {
+                            "name": "file.py",
+                            "path": "src/file.py",
+                            "repository": "owner/repo",
+                            "url": "https://github.com/owner/repo/blob/main/src/file.py",
+                            "score": 1.0,
+                        }
+                    ],
+                )
+            },
+        )
+
+    @staticmethod
+    async def search_code(
+        credentials: GithubCredentials,
+        query: str,
+        repo: str,
+        per_page: int,
+    ) -> tuple[int, list[Output.SearchResult]]:
+        api = get_api(credentials, convert_urls=False)
+        full_query = f"{query} repo:{repo}" if repo else query
+        params = {"q": full_query, "per_page": str(per_page)}
+        response = await api.get("https://api.github.com/search/code", params=params)
+        data = response.json()
+        results: list[GithubSearchCodeBlock.Output.SearchResult] = [
+            GithubSearchCodeBlock.Output.SearchResult(
+                name=item["name"],
+                path=item["path"],
+                repository=item["repository"]["full_name"],
+                url=item["html_url"],
+                score=item["score"],
+            )
+            for item in data["items"]
+        ]
+        return data["total_count"], results
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            total_count, results = await self.search_code(
+                credentials,
+                input_data.query,
+                input_data.repo,
+                input_data.per_page,
+            )
+            yield "total_count", total_count
+            yield "results", results
+            for result in results:
+                yield "result", result
+        except Exception as e:
+            yield "error", str(e)
+
+
+class GithubGetRepositoryTreeBlock(Block):
+    class Input(BlockSchemaInput):
+        credentials: GithubCredentialsInput = GithubCredentialsField("repo")
+        repo_url: str = SchemaField(
+            description="URL of the GitHub repository",
+            placeholder="https://github.com/owner/repo",
+        )
+        branch: str = SchemaField(
+            description="Branch name to get the tree from",
+            default="main",
+        )
+        recursive: bool = SchemaField(
+            description="Whether to recursively list the entire tree",
+            default=True,
+        )
+
+    class Output(BlockSchemaOutput):
+        class TreeEntry(TypedDict):
+            path: str
+            type: str
+            size: int
+            sha: str
+
+        entry: TreeEntry = SchemaField(
+            title="Tree Entry", description="A file or directory in the tree"
+        )
+        entries: list[TreeEntry] = SchemaField(
+            description="List of all files and directories in the tree"
+        )
+        truncated: bool = SchemaField(
+            description="Whether the tree was truncated due to size"
+        )
+        error: str = SchemaField(description="Error message if getting tree failed")
+
+    def __init__(self):
+        super().__init__(
+            id="89c5c0ec-172e-4001-a32c-bdfe4d0c9e81",
+            description="This block lists the entire file tree of a GitHub repository recursively.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=GithubGetRepositoryTreeBlock.Input,
+            output_schema=GithubGetRepositoryTreeBlock.Output,
+            test_input={
+                "repo_url": "https://github.com/owner/repo",
+                "branch": "main",
+                "recursive": True,
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("truncated", False),
+                (
+                    "entries",
+                    [
+                        {
+                            "path": "src/main.py",
+                            "type": "blob",
+                            "size": 1234,
+                            "sha": "abc123",
+                        }
+                    ],
+                ),
+                (
+                    "entry",
+                    {
+                        "path": "src/main.py",
+                        "type": "blob",
+                        "size": 1234,
+                        "sha": "abc123",
+                    },
+                ),
+            ],
+            test_mock={
+                "get_tree": lambda *args, **kwargs: (
+                    False,
+                    [
+                        {
+                            "path": "src/main.py",
+                            "type": "blob",
+                            "size": 1234,
+                            "sha": "abc123",
+                        }
+                    ],
+                )
+            },
+        )
+
+    @staticmethod
+    async def get_tree(
+        credentials: GithubCredentials,
+        repo_url: str,
+        branch: str,
+        recursive: bool,
+    ) -> tuple[bool, list[Output.TreeEntry]]:
+        api = get_api(credentials)
+        tree_url = repo_url + f"/git/trees/{quote(branch, safe='')}"
+        params = {"recursive": "1"} if recursive else {}
+        response = await api.get(tree_url, params=params)
+        data = response.json()
+        entries: list[GithubGetRepositoryTreeBlock.Output.TreeEntry] = [
+            GithubGetRepositoryTreeBlock.Output.TreeEntry(
+                path=item["path"],
+                type=item["type"],
+                size=item.get("size", 0),
+                sha=item["sha"],
+            )
+            for item in data["tree"]
+        ]
+        return data.get("truncated", False), entries
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: GithubCredentials,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            truncated, entries = await self.get_tree(
+                credentials,
+                input_data.repo_url,
+                input_data.branch,
+                input_data.recursive,
+            )
+            yield "truncated", truncated
+            yield "entries", entries
+            for entry in entries:
+                yield "entry", entry
+        except Exception as e:
+            yield "error", str(e)

autogpt_platform/backend/backend/blocks/github/test_github_blocks.py

@@ -0,0 +1,125 @@
+import inspect
+
+import pytest
+
+from backend.blocks.github._auth import TEST_CREDENTIALS, TEST_CREDENTIALS_INPUT
+from backend.blocks.github.commits import FileOperation, GithubMultiFileCommitBlock
+from backend.blocks.github.pull_requests import (
+    GithubMergePullRequestBlock,
+    prepare_pr_api_url,
+)
+from backend.data.execution import ExecutionContext
+from backend.util.exceptions import BlockExecutionError
+
+# ── prepare_pr_api_url tests ──
+
+
+class TestPreparePrApiUrl:
+    def test_https_scheme_preserved(self):
+        result = prepare_pr_api_url("https://github.com/owner/repo/pull/42", "merge")
+        assert result == "https://github.com/owner/repo/pulls/42/merge"
+
+    def test_http_scheme_preserved(self):
+        result = prepare_pr_api_url("http://github.com/owner/repo/pull/1", "files")
+        assert result == "http://github.com/owner/repo/pulls/1/files"
+
+    def test_no_scheme_defaults_to_https(self):
+        result = prepare_pr_api_url("github.com/owner/repo/pull/5", "merge")
+        assert result == "https://github.com/owner/repo/pulls/5/merge"
+
+    def test_reviewers_path(self):
+        result = prepare_pr_api_url(
+            "https://github.com/owner/repo/pull/99", "requested_reviewers"
+        )
+        assert result == "https://github.com/owner/repo/pulls/99/requested_reviewers"
+
+    def test_invalid_url_returned_as_is(self):
+        url = "https://example.com/not-a-pr"
+        assert prepare_pr_api_url(url, "merge") == url
+
+    def test_empty_string(self):
+        assert prepare_pr_api_url("", "merge") == ""
+
+
+# ── Error-path block tests ──
+# When a block's run() yields ("error", msg), _execute() converts it to a
+# BlockExecutionError. We call block.execute() directly (not execute_block_test,
+# which returns early on empty test_output).
+
+
+def _mock_block(block, mocks: dict):
+    """Apply mocks to a block's static methods, wrapping sync mocks as async."""
+    for name, mock_fn in mocks.items():
+        original = getattr(block, name)
+        if inspect.iscoroutinefunction(original):
+
+            async def async_mock(*args, _fn=mock_fn, **kwargs):
+                return _fn(*args, **kwargs)
+
+            setattr(block, name, async_mock)
+        else:
+            setattr(block, name, mock_fn)
+
+
+def _raise(exc: Exception):
+    """Helper that returns a callable which raises the given exception."""
+
+    def _raiser(*args, **kwargs):
+        raise exc
+
+    return _raiser
+
+
+@pytest.mark.asyncio
+async def test_merge_pr_error_path():
+    block = GithubMergePullRequestBlock()
+    _mock_block(block, {"merge_pr": _raise(RuntimeError("PR not mergeable"))})
+    input_data = {
+        "pr_url": "https://github.com/owner/repo/pull/1",
+        "merge_method": "squash",
+        "commit_title": "",
+        "commit_message": "",
+        "credentials": TEST_CREDENTIALS_INPUT,
+    }
+    with pytest.raises(BlockExecutionError, match="PR not mergeable"):
+        async for _ in block.execute(input_data, credentials=TEST_CREDENTIALS):
+            pass
+
+
+@pytest.mark.asyncio
+async def test_multi_file_commit_error_path():
+    block = GithubMultiFileCommitBlock()
+    _mock_block(block, {"multi_file_commit": _raise(RuntimeError("ref update failed"))})
+    input_data = {
+        "repo_url": "https://github.com/owner/repo",
+        "branch": "feature",
+        "commit_message": "test",
+        "files": [{"path": "a.py", "content": "x", "operation": "upsert"}],
+        "credentials": TEST_CREDENTIALS_INPUT,
+    }
+    with pytest.raises(BlockExecutionError, match="ref update failed"):
+        async for _ in block.execute(
+            input_data,
+            credentials=TEST_CREDENTIALS,
+            execution_context=ExecutionContext(),
+        ):
+            pass
+
+
+# ── FileOperation enum tests ──
+
+
+class TestFileOperation:
+    def test_upsert_value(self):
+        assert FileOperation.UPSERT == "upsert"
+
+    def test_delete_value(self):
+        assert FileOperation.DELETE == "delete"
+
+    def test_invalid_value_raises(self):
+        with pytest.raises(ValueError):
+            FileOperation("create")
+
+    def test_invalid_value_raises_typo(self):
+        with pytest.raises(ValueError):
+            FileOperation("upser")

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

@@ -241,8 +241,8 @@ class GmailBase(Block, ABC):
                     h.ignore_links = False
                     h.ignore_images = True
                     return h.handle(html_content)
-                except ImportError:
-                    # Fallback: return raw HTML if html2text is not available
+                except Exception:
+                    # Keep extraction resilient if html2text is unavailable or fails.
                     return html_content
 
         # Handle content stored as attachment

autogpt_platform/backend/backend/blocks/helpers/review.py

@@ -67,6 +67,7 @@ class HITLReviewHelper:
         graph_version: int,
         block_name: str = "Block",
         editable: bool = False,
+        is_graph_execution: bool = True,
     ) -> Optional[ReviewResult]:
         """
         Handle a review request for a block that requires human review.
@@ -143,10 +144,11 @@ class HITLReviewHelper:
             logger.info(
                 f"Block {block_name} pausing execution for node {node_exec_id} - awaiting human review"
             )
-            await HITLReviewHelper.update_node_execution_status(
-                exec_id=node_exec_id,
-                status=ExecutionStatus.REVIEW,
-            )
+            if is_graph_execution:
+                await HITLReviewHelper.update_node_execution_status(
+                    exec_id=node_exec_id,
+                    status=ExecutionStatus.REVIEW,
+                )
             return None  # Signal that execution should pause
 
         # Mark review as processed if not already done
@@ -168,6 +170,7 @@ class HITLReviewHelper:
         graph_version: int,
         block_name: str = "Block",
         editable: bool = False,
+        is_graph_execution: bool = True,
     ) -> Optional[ReviewDecision]:
         """
         Handle a review request and return the decision in a single call.
@@ -197,6 +200,7 @@ class HITLReviewHelper:
             graph_version=graph_version,
             block_name=block_name,
             editable=editable,
+            is_graph_execution=is_graph_execution,
         )
 
         if review_result is None:

autogpt_platform/backend/backend/blocks/io.py

@@ -211,7 +211,7 @@ class AgentOutputBlock(Block):
         if input_data.format:
             try:
                 formatter = TextFormatter(autoescape=input_data.escape_html)
-                yield "output", formatter.format_string(
+                yield "output", await formatter.format_string(
                     input_data.format, {input_data.name: input_data.value}
                 )
             except Exception as e:

autogpt_platform/backend/backend/blocks/jina/search.py

@@ -17,7 +17,7 @@ from backend.blocks.jina._auth import (
 from backend.blocks.search import GetRequest
 from backend.data.model import SchemaField
 from backend.util.exceptions import BlockExecutionError
-from backend.util.request import HTTPClientError, HTTPServerError, validate_url
+from backend.util.request import HTTPClientError, HTTPServerError, validate_url_host
 
 
 class SearchTheWebBlock(Block, GetRequest):
@@ -112,7 +112,7 @@ class ExtractWebsiteContentBlock(Block, GetRequest):
     ) -> BlockOutput:
         if input_data.raw_content:
             try:
-                parsed_url, _, _ = await validate_url(input_data.url, [])
+                parsed_url, _, _ = await validate_url_host(input_data.url)
                 url = parsed_url.geturl()
             except ValueError as e:
                 yield "error", f"Invalid URL: {e}"

autogpt_platform/backend/backend/blocks/llm.py

@@ -31,10 +31,21 @@ from backend.data.model import (
 )
 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
 from backend.util.text import TextFormatter
 
+settings = Settings()
 logger = TruncatedLogger(logging.getLogger(__name__), "[LLM-Block]")
 fmt = TextFormatter(autoescape=False)
 
@@ -107,7 +118,6 @@ 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"
@@ -116,6 +126,7 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"
     CLAUDE_4_5_HAIKU = "claude-haiku-4-5-20251001"
     CLAUDE_4_6_OPUS = "claude-opus-4-6"
+    CLAUDE_4_6_SONNET = "claude-sonnet-4-6"
     CLAUDE_3_HAIKU = "claude-3-haiku-20240307"
     # AI/ML API models
     AIML_API_QWEN2_5_72B = "Qwen/Qwen2.5-72B-Instruct-Turbo"
@@ -135,19 +146,31 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     # OpenRouter models
     OPENAI_GPT_OSS_120B = "openai/gpt-oss-120b"
     OPENAI_GPT_OSS_20B = "openai/gpt-oss-20b"
-    GEMINI_2_5_PRO = "google/gemini-2.5-pro-preview-03-25"
-    GEMINI_3_PRO_PREVIEW = "google/gemini-3-pro-preview"
+    GEMINI_2_5_PRO_PREVIEW = "google/gemini-2.5-pro-preview-03-25"
+    GEMINI_2_5_PRO = "google/gemini-2.5-pro"
+    GEMINI_3_1_PRO_PREVIEW = "google/gemini-3.1-pro-preview"
+    GEMINI_3_FLASH_PREVIEW = "google/gemini-3-flash-preview"
     GEMINI_2_5_FLASH = "google/gemini-2.5-flash"
     GEMINI_2_0_FLASH = "google/gemini-2.0-flash-001"
+    GEMINI_3_1_FLASH_LITE_PREVIEW = "google/gemini-3.1-flash-lite-preview"
     GEMINI_2_5_FLASH_LITE_PREVIEW = "google/gemini-2.5-flash-lite-preview-06-17"
     GEMINI_2_0_FLASH_LITE = "google/gemini-2.0-flash-lite-001"
     MISTRAL_NEMO = "mistralai/mistral-nemo"
+    MISTRAL_LARGE_3 = "mistralai/mistral-large-2512"
+    MISTRAL_MEDIUM_3_1 = "mistralai/mistral-medium-3.1"
+    MISTRAL_SMALL_3_2 = "mistralai/mistral-small-3.2-24b-instruct"
+    CODESTRAL = "mistralai/codestral-2508"
     COHERE_COMMAND_R_08_2024 = "cohere/command-r-08-2024"
     COHERE_COMMAND_R_PLUS_08_2024 = "cohere/command-r-plus-08-2024"
+    COHERE_COMMAND_A_03_2025 = "cohere/command-a-03-2025"
+    COHERE_COMMAND_A_TRANSLATE_08_2025 = "cohere/command-a-translate-08-2025"
+    COHERE_COMMAND_A_REASONING_08_2025 = "cohere/command-a-reasoning-08-2025"
+    COHERE_COMMAND_A_VISION_07_2025 = "cohere/command-a-vision-07-2025"
     DEEPSEEK_CHAT = "deepseek/deepseek-chat"  # Actually: DeepSeek V3
     DEEPSEEK_R1_0528 = "deepseek/deepseek-r1-0528"
     PERPLEXITY_SONAR = "perplexity/sonar"
     PERPLEXITY_SONAR_PRO = "perplexity/sonar-pro"
+    PERPLEXITY_SONAR_REASONING_PRO = "perplexity/sonar-reasoning-pro"
     PERPLEXITY_SONAR_DEEP_RESEARCH = "perplexity/sonar-deep-research"
     NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B = "nousresearch/hermes-3-llama-3.1-405b"
     NOUSRESEARCH_HERMES_3_LLAMA_3_1_70B = "nousresearch/hermes-3-llama-3.1-70b"
@@ -155,9 +178,11 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     AMAZON_NOVA_MICRO_V1 = "amazon/nova-micro-v1"
     AMAZON_NOVA_PRO_V1 = "amazon/nova-pro-v1"
     MICROSOFT_WIZARDLM_2_8X22B = "microsoft/wizardlm-2-8x22b"
+    MICROSOFT_PHI_4 = "microsoft/phi-4"
     GRYPHE_MYTHOMAX_L2_13B = "gryphe/mythomax-l2-13b"
     META_LLAMA_4_SCOUT = "meta-llama/llama-4-scout"
     META_LLAMA_4_MAVERICK = "meta-llama/llama-4-maverick"
+    GROK_3 = "x-ai/grok-3"
     GROK_4 = "x-ai/grok-4"
     GROK_4_FAST = "x-ai/grok-4-fast"
     GROK_4_1_FAST = "x-ai/grok-4.1-fast"
@@ -258,9 +283,6 @@ 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
@@ -274,6 +296,9 @@ MODEL_METADATA = {
     LlmModel.CLAUDE_4_6_OPUS: ModelMetadata(
         "anthropic", 200000, 128000, "Claude Opus 4.6", "Anthropic", "Anthropic", 3
     ),  # claude-opus-4-6
+    LlmModel.CLAUDE_4_6_SONNET: ModelMetadata(
+        "anthropic", 200000, 64000, "Claude Sonnet 4.6", "Anthropic", "Anthropic", 3
+    ),  # claude-sonnet-4-6
     LlmModel.CLAUDE_4_5_OPUS: ModelMetadata(
         "anthropic", 200000, 64000, "Claude Opus 4.5", "Anthropic", "Anthropic", 3
     ),  # claude-opus-4-5-20251101
@@ -332,17 +357,41 @@ MODEL_METADATA = {
         "ollama", 32768, None, "Dolphin Mistral Latest", "Ollama", "Mistral AI", 1
     ),
     # https://openrouter.ai/models
-    LlmModel.GEMINI_2_5_PRO: ModelMetadata(
+    LlmModel.GEMINI_2_5_PRO_PREVIEW: ModelMetadata(
         "open_router",
-        1050000,
-        8192,
+        1048576,
+        65536,
         "Gemini 2.5 Pro Preview 03.25",
         "OpenRouter",
         "Google",
         2,
     ),
-    LlmModel.GEMINI_3_PRO_PREVIEW: ModelMetadata(
-        "open_router", 1048576, 65535, "Gemini 3 Pro Preview", "OpenRouter", "Google", 2
+    LlmModel.GEMINI_2_5_PRO: ModelMetadata(
+        "open_router",
+        1048576,
+        65536,
+        "Gemini 2.5 Pro",
+        "OpenRouter",
+        "Google",
+        2,
+    ),
+    LlmModel.GEMINI_3_1_PRO_PREVIEW: ModelMetadata(
+        "open_router",
+        1048576,
+        65536,
+        "Gemini 3.1 Pro Preview",
+        "OpenRouter",
+        "Google",
+        2,
+    ),
+    LlmModel.GEMINI_3_FLASH_PREVIEW: ModelMetadata(
+        "open_router",
+        1048576,
+        65536,
+        "Gemini 3 Flash Preview",
+        "OpenRouter",
+        "Google",
+        1,
     ),
     LlmModel.GEMINI_2_5_FLASH: ModelMetadata(
         "open_router", 1048576, 65535, "Gemini 2.5 Flash", "OpenRouter", "Google", 1
@@ -350,6 +399,15 @@ MODEL_METADATA = {
     LlmModel.GEMINI_2_0_FLASH: ModelMetadata(
         "open_router", 1048576, 8192, "Gemini 2.0 Flash 001", "OpenRouter", "Google", 1
     ),
+    LlmModel.GEMINI_3_1_FLASH_LITE_PREVIEW: ModelMetadata(
+        "open_router",
+        1048576,
+        65536,
+        "Gemini 3.1 Flash Lite Preview",
+        "OpenRouter",
+        "Google",
+        1,
+    ),
     LlmModel.GEMINI_2_5_FLASH_LITE_PREVIEW: ModelMetadata(
         "open_router",
         1048576,
@@ -371,12 +429,78 @@ MODEL_METADATA = {
     LlmModel.MISTRAL_NEMO: ModelMetadata(
         "open_router", 128000, 4096, "Mistral Nemo", "OpenRouter", "Mistral AI", 1
     ),
+    LlmModel.MISTRAL_LARGE_3: ModelMetadata(
+        "open_router",
+        262144,
+        None,
+        "Mistral Large 3 2512",
+        "OpenRouter",
+        "Mistral AI",
+        2,
+    ),
+    LlmModel.MISTRAL_MEDIUM_3_1: ModelMetadata(
+        "open_router",
+        131072,
+        None,
+        "Mistral Medium 3.1",
+        "OpenRouter",
+        "Mistral AI",
+        2,
+    ),
+    LlmModel.MISTRAL_SMALL_3_2: ModelMetadata(
+        "open_router",
+        131072,
+        131072,
+        "Mistral Small 3.2 24B",
+        "OpenRouter",
+        "Mistral AI",
+        1,
+    ),
+    LlmModel.CODESTRAL: ModelMetadata(
+        "open_router",
+        256000,
+        None,
+        "Codestral 2508",
+        "OpenRouter",
+        "Mistral AI",
+        1,
+    ),
     LlmModel.COHERE_COMMAND_R_08_2024: ModelMetadata(
         "open_router", 128000, 4096, "Command R 08.2024", "OpenRouter", "Cohere", 1
     ),
     LlmModel.COHERE_COMMAND_R_PLUS_08_2024: ModelMetadata(
         "open_router", 128000, 4096, "Command R Plus 08.2024", "OpenRouter", "Cohere", 2
     ),
+    LlmModel.COHERE_COMMAND_A_03_2025: ModelMetadata(
+        "open_router", 256000, 8192, "Command A 03.2025", "OpenRouter", "Cohere", 2
+    ),
+    LlmModel.COHERE_COMMAND_A_TRANSLATE_08_2025: ModelMetadata(
+        "open_router",
+        128000,
+        8192,
+        "Command A Translate 08.2025",
+        "OpenRouter",
+        "Cohere",
+        2,
+    ),
+    LlmModel.COHERE_COMMAND_A_REASONING_08_2025: ModelMetadata(
+        "open_router",
+        256000,
+        32768,
+        "Command A Reasoning 08.2025",
+        "OpenRouter",
+        "Cohere",
+        3,
+    ),
+    LlmModel.COHERE_COMMAND_A_VISION_07_2025: ModelMetadata(
+        "open_router",
+        128000,
+        8192,
+        "Command A Vision 07.2025",
+        "OpenRouter",
+        "Cohere",
+        2,
+    ),
     LlmModel.DEEPSEEK_CHAT: ModelMetadata(
         "open_router", 64000, 2048, "DeepSeek Chat", "OpenRouter", "DeepSeek", 1
     ),
@@ -389,6 +513,15 @@ MODEL_METADATA = {
     LlmModel.PERPLEXITY_SONAR_PRO: ModelMetadata(
         "open_router", 200000, 8000, "Sonar Pro", "OpenRouter", "Perplexity", 2
     ),
+    LlmModel.PERPLEXITY_SONAR_REASONING_PRO: ModelMetadata(
+        "open_router",
+        128000,
+        8000,
+        "Sonar Reasoning Pro",
+        "OpenRouter",
+        "Perplexity",
+        2,
+    ),
     LlmModel.PERPLEXITY_SONAR_DEEP_RESEARCH: ModelMetadata(
         "open_router",
         128000,
@@ -434,6 +567,9 @@ MODEL_METADATA = {
     LlmModel.MICROSOFT_WIZARDLM_2_8X22B: ModelMetadata(
         "open_router", 65536, 4096, "WizardLM 2 8x22B", "OpenRouter", "Microsoft", 1
     ),
+    LlmModel.MICROSOFT_PHI_4: ModelMetadata(
+        "open_router", 16384, 16384, "Phi-4", "OpenRouter", "Microsoft", 1
+    ),
     LlmModel.GRYPHE_MYTHOMAX_L2_13B: ModelMetadata(
         "open_router", 4096, 4096, "MythoMax L2 13B", "OpenRouter", "Gryphe", 1
     ),
@@ -443,6 +579,15 @@ MODEL_METADATA = {
     LlmModel.META_LLAMA_4_MAVERICK: ModelMetadata(
         "open_router", 1048576, 1000000, "Llama 4 Maverick", "OpenRouter", "Meta", 1
     ),
+    LlmModel.GROK_3: ModelMetadata(
+        "open_router",
+        131072,
+        131072,
+        "Grok 3",
+        "OpenRouter",
+        "xAI",
+        2,
+    ),
     LlmModel.GROK_4: ModelMetadata(
         "open_router", 256000, 256000, "Grok 4", "OpenRouter", "xAI", 3
     ),
@@ -659,36 +804,53 @@ 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
 
-        parallel_tool_calls = get_parallel_tool_calls_param(
-            llm_model, parallel_tool_calls
-        )
+        tools_param = convert_tools_to_responses_format(tools) if tools else openai.omit
 
+        text_config = openai.omit
         if force_json_output:
-            response_format = {"type": "json_object"}
+            text_config = {"format": {"type": "json_object"}}  # type: ignore
 
-        response = await oai_client.chat.completions.create(
+        response = await oai_client.responses.create(
             model=llm_model.value,
-            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,
+            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,
         )
 
-        tool_calls = extract_openai_tool_calls(response)
-        reasoning = extract_openai_reasoning(response)
+        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)
 
         return LLMResponse(
-            raw_response=response.choices[0].message,
+            raw_response=response,
             prompt=prompt,
-            response=response.choices[0].message.content or "",
+            response=content,
             tool_calls=tool_calls,
-            prompt_tokens=response.usage.prompt_tokens if response.usage else 0,
-            completion_tokens=response.usage.completion_tokens if response.usage else 0,
+            prompt_tokens=prompt_tokens,
+            completion_tokens=completion_tokens,
             reasoning=reasoning,
         )
     elif provider == "anthropic":
@@ -800,6 +962,11 @@ async def llm_call(
         if tools:
             raise ValueError("Ollama does not support tools.")
 
+        # Validate user-provided Ollama host to prevent SSRF etc.
+        await validate_url_host(
+            ollama_host, trusted_hostnames=[settings.config.ollama_host]
+        )
+
         client = ollama.AsyncClient(host=ollama_host)
         sys_messages = [p["content"] for p in prompt if p["role"] == "system"]
         usr_messages = [p["content"] for p in prompt if p["role"] != "system"]
@@ -821,7 +988,7 @@ async def llm_call(
     elif provider == "open_router":
         tools_param = tools if tools else openai.NOT_GIVEN
         client = openai.AsyncOpenAI(
-            base_url="https://openrouter.ai/api/v1",
+            base_url=OPENROUTER_BASE_URL,
             api_key=credentials.api_key.get_secret_value(),
         )
 
@@ -1129,8 +1296,10 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
 
         values = input_data.prompt_values
         if values:
-            input_data.prompt = fmt.format_string(input_data.prompt, values)
-            input_data.sys_prompt = fmt.format_string(input_data.sys_prompt, values)
+            input_data.prompt = await fmt.format_string(input_data.prompt, values)
+            input_data.sys_prompt = await fmt.format_string(
+                input_data.sys_prompt, values
+            )
 
         if input_data.sys_prompt:
             prompt.append({"role": "system", "content": input_data.sys_prompt})

autogpt_platform/backend/backend/blocks/perplexity.py

@@ -4,7 +4,7 @@ from enum import Enum
 from typing import Any, Literal
 
 import openai
-from pydantic import SecretStr
+from pydantic import SecretStr, field_validator
 
 from backend.blocks._base import (
     Block,
@@ -13,6 +13,7 @@ from backend.blocks._base import (
     BlockSchemaInput,
     BlockSchemaOutput,
 )
+from backend.data.block import BlockInput
 from backend.data.model import (
     APIKeyCredentials,
     CredentialsField,
@@ -21,6 +22,7 @@ from backend.data.model import (
     SchemaField,
 )
 from backend.integrations.providers import ProviderName
+from backend.util.clients import OPENROUTER_BASE_URL
 from backend.util.logging import TruncatedLogger
 
 logger = TruncatedLogger(logging.getLogger(__name__), "[Perplexity-Block]")
@@ -34,6 +36,20 @@ class PerplexityModel(str, Enum):
     SONAR_DEEP_RESEARCH = "perplexity/sonar-deep-research"
 
 
+def _sanitize_perplexity_model(value: Any) -> PerplexityModel:
+    """Return a valid PerplexityModel, falling back to SONAR for invalid values."""
+    if isinstance(value, PerplexityModel):
+        return value
+    try:
+        return PerplexityModel(value)
+    except ValueError:
+        logger.warning(
+            f"Invalid PerplexityModel '{value}', "
+            f"falling back to {PerplexityModel.SONAR.value}"
+        )
+        return PerplexityModel.SONAR
+
+
 PerplexityCredentials = CredentialsMetaInput[
     Literal[ProviderName.OPEN_ROUTER], Literal["api_key"]
 ]
@@ -72,6 +88,25 @@ class PerplexityBlock(Block):
             advanced=False,
         )
         credentials: PerplexityCredentials = PerplexityCredentialsField()
+
+        @field_validator("model", mode="before")
+        @classmethod
+        def fallback_invalid_model(cls, v: Any) -> PerplexityModel:
+            """Fall back to SONAR if the model value is not a valid
+            PerplexityModel (e.g. an OpenAI model ID set by the agent
+            generator)."""
+            return _sanitize_perplexity_model(v)
+
+        @classmethod
+        def validate_data(cls, data: BlockInput) -> str | None:
+            """Sanitize the model field before JSON schema validation so that
+            invalid values are replaced with the default instead of raising a
+            BlockInputError."""
+            model_value = data.get("model")
+            if model_value is not None:
+                data["model"] = _sanitize_perplexity_model(model_value).value
+            return super().validate_data(data)
+
         system_prompt: str = SchemaField(
             title="System Prompt",
             default="",
@@ -136,7 +171,7 @@ class PerplexityBlock(Block):
     ) -> dict[str, Any]:
         """Call Perplexity via OpenRouter and extract annotations."""
         client = openai.AsyncOpenAI(
-            base_url="https://openrouter.ai/api/v1",
+            base_url=OPENROUTER_BASE_URL,
             api_key=credentials.api_key.get_secret_value(),
         )
 

autogpt_platform/backend/backend/blocks/reddit.py

@@ -2232,6 +2232,7 @@ class DeleteRedditPostBlock(Block):
                 ("post_id", "abc123"),
             ],
             test_mock={"delete_post": lambda creds, post_id: True},
+            is_sensitive_action=True,
         )
 
     @staticmethod
@@ -2290,6 +2291,7 @@ class DeleteRedditCommentBlock(Block):
                 ("comment_id", "xyz789"),
             ],
             test_mock={"delete_comment": lambda creds, comment_id: True},
+            is_sensitive_action=True,
         )
 
     @staticmethod

autogpt_platform/backend/backend/blocks/slant3d/order.py

@@ -72,6 +72,7 @@ class Slant3DCreateOrderBlock(Slant3DBlockBase):
                 "_make_request": lambda *args, **kwargs: {"orderId": "314144241"},
                 "_convert_to_color": lambda *args, **kwargs: "black",
             },
+            is_sensitive_action=True,
         )
 
     async def run(

autogpt_platform/backend/backend/blocks/smart_decision_maker.py

@@ -61,20 +61,27 @@ 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 both OpenAI and Anthropics formats.
+    Supports OpenAI Chat Completions, Responses API, and Anthropic 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: check for tool_calls in the entry.
+    # OpenAI Chat Completions: 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)
 
-    # Anthropics: check content items for tool_use type.
+    # Anthropic: check content items for tool_use type.
     content = entry.get("content")
     if isinstance(content, list):
         for item in content:
@@ -89,16 +96,22 @@ 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 both OpenAI and Anthropics formats.
+    Supports OpenAI Chat Completions, Responses API, and Anthropic formats.
     """
     tool_call_ids: list[str] = []
 
-    # OpenAI: a tool response message with role "tool" and key "tool_call_id".
+    # 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".
     if entry.get("role") == "tool":
         if tool_call_id := entry.get("tool_call_id"):
             tool_call_ids.append(str(tool_call_id))
 
-    # Anthropics: check content items for tool_result type.
+    # Anthropic: check content items for tool_result type.
     if entry.get("role") == "user":
         content = entry.get("content")
         if isinstance(content, list):
@@ -111,14 +124,16 @@ def _get_tool_responses(entry: dict[str, Any]) -> list[str]:
     return tool_call_ids
 
 
-def _create_tool_response(call_id: str, output: Any) -> dict[str, Any]:
+def _create_tool_response(
+    call_id: str, output: Any, *, responses_api: bool = False
+) -> dict[str, Any]:
     """
-    Create a tool response message for either OpenAI or Anthropics,
-    based on the tool_id format.
+    Create a tool response message for OpenAI, Anthropic, or OpenAI Responses API,
+    based on the tool_id format and the responses_api flag.
     """
     content = output if isinstance(output, str) else json.dumps(output)
 
-    # Anthropics format: tool IDs typically start with "toolu_"
+    # Anthropic format: tool IDs typically start with "toolu_"
     if call_id.startswith("toolu_"):
         return {
             "role": "user",
@@ -128,8 +143,11 @@ def _create_tool_response(call_id: str, output: Any) -> dict[str, Any]:
             ],
         }
 
-    # OpenAI format: tool IDs typically start with "call_".
-    # Or default fallback (if the tool_id doesn't match any known prefix)
+    # OpenAI Responses API format
+    if responses_api:
+        return {"type": "function_call_output", "call_id": call_id, "output": content}
+
+    # OpenAI Chat Completions format (default fallback)
     return {"role": "tool", "tool_call_id": call_id, "content": content}
 
 
@@ -177,10 +195,19 @@ 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]:
+def _convert_raw_response_to_dict(
+    raw_response: Any,
+) -> dict[str, Any] | list[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
@@ -188,11 +215,28 @@ def _convert_raw_response_to_dict(raw_response: Any) -> dict[str, Any]:
     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:
-        # OpenAI/Anthropic return objects, convert with json.to_dict
+        # Chat Completions / Anthropic return message objects
         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.
@@ -754,19 +798,34 @@ class SmartDecisionMakerBlock(Block):
         self, prompt: list[dict], response, tool_outputs: list | None = None
     ):
         """Update conversation history with response and tool outputs."""
-        # 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", [])
-        )
+        converted = _convert_raw_response_to_dict(response.raw_response)
 
-        if response.reasoning and not has_tool_calls:
-            prompt.append(
-                {"role": "assistant", "content": f"[Reasoning]: {response.reasoning}"}
+        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
             )
-
-        prompt.append(assistant_message)
+            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)
 
         if tool_outputs:
             prompt.extend(tool_outputs)
@@ -776,6 +835,8 @@ 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
@@ -868,13 +929,17 @@ class SmartDecisionMakerBlock(Block):
                 if node_outputs
                 else "Tool executed successfully"
             )
-            return _create_tool_response(tool_call.id, tool_response_content)
+            return _create_tool_response(
+                tool_call.id, tool_response_content, responses_api=responses_api
+            )
 
         except Exception as 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)}"
+                tool_call.id,
+                f"Tool execution failed: {str(e)}",
+                responses_api=responses_api,
             )
 
     async def _execute_tools_agent_mode(
@@ -895,6 +960,7 @@ 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(
@@ -951,14 +1017,19 @@ 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
+                        tool_info,
+                        execution_params,
+                        execution_processor,
+                        responses_api=use_responses_api,
                     )
                     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)}"
+                        tool_info.tool_call.id,
+                        f"Error: {str(e)}",
+                        responses_api=use_responses_api,
                     )
                     tool_outputs.append(error_response)
 
@@ -1020,11 +1091,17 @@ 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)
+                _create_tool_response(
+                    first_call_id,
+                    input_data.last_tool_output,
+                    responses_api=use_responses_api,
+                )
             )
 
             prompt.extend(tool_output)
@@ -1050,11 +1127,15 @@ class SmartDecisionMakerBlock(Block):
 
         values = input_data.prompt_values
         if values:
-            input_data.prompt = llm.fmt.format_string(input_data.prompt, values)
-            input_data.sys_prompt = llm.fmt.format_string(input_data.sys_prompt, values)
+            input_data.prompt = await llm.fmt.format_string(input_data.prompt, values)
+            input_data.sys_prompt = await llm.fmt.format_string(
+                input_data.sys_prompt, values
+            )
 
         if input_data.sys_prompt and not any(
-            p["role"] == "system" and p["content"].startswith(MAIN_OBJECTIVE_PREFIX)
+            p.get("role") == "system"
+            and isinstance(p.get("content"), str)
+            and p["content"].startswith(MAIN_OBJECTIVE_PREFIX)
             for p in prompt
         ):
             prompt.append(
@@ -1065,7 +1146,9 @@ class SmartDecisionMakerBlock(Block):
             )
 
         if input_data.prompt and not any(
-            p["role"] == "user" and p["content"].startswith(MAIN_OBJECTIVE_PREFIX)
+            p.get("role") == "user"
+            and isinstance(p.get("content"), str)
+            and p["content"].startswith(MAIN_OBJECTIVE_PREFIX)
             for p in prompt
         ):
             prompt.append(
@@ -1173,11 +1256,26 @@ class SmartDecisionMakerBlock(Block):
                 )
                 yield emit_key, arg_value
 
-        if response.reasoning:
+        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:
             prompt.append(
                 {"role": "assistant", "content": f"[Reasoning]: {response.reasoning}"}
             )
 
-        prompt.append(_convert_raw_response_to_dict(response.raw_response))
+        if isinstance(converted, list):
+            prompt.extend(converted)
+        else:
+            prompt.append(converted)
 
         yield "conversations", prompt

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

@@ -83,7 +83,8 @@ class StagehandRecommendedLlmModel(str, Enum):
     GPT41_MINI = "gpt-4.1-mini-2025-04-14"
 
     # Anthropic
-    CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"
+    CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"  # Keep for backwards compat
+    CLAUDE_4_6_SONNET = "claude-sonnet-4-6"
 
     @property
     def provider_name(self) -> str:
@@ -137,7 +138,7 @@ class StagehandObserveBlock(Block):
         model: StagehandRecommendedLlmModel = SchemaField(
             title="LLM Model",
             description="LLM to use for Stagehand (provider is inferred)",
-            default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
+            default=StagehandRecommendedLlmModel.CLAUDE_4_6_SONNET,
             advanced=False,
         )
         model_credentials: AICredentials = AICredentialsField()
@@ -227,7 +228,7 @@ class StagehandActBlock(Block):
         model: StagehandRecommendedLlmModel = SchemaField(
             title="LLM Model",
             description="LLM to use for Stagehand (provider is inferred)",
-            default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
+            default=StagehandRecommendedLlmModel.CLAUDE_4_6_SONNET,
             advanced=False,
         )
         model_credentials: AICredentials = AICredentialsField()
@@ -324,7 +325,7 @@ class StagehandExtractBlock(Block):
         model: StagehandRecommendedLlmModel = SchemaField(
             title="LLM Model",
             description="LLM to use for Stagehand (provider is inferred)",
-            default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
+            default=StagehandRecommendedLlmModel.CLAUDE_4_6_SONNET,
             advanced=False,
         )
         model_credentials: AICredentials = AICredentialsField()

autogpt_platform/backend/backend/blocks/system/store_operations.py

@@ -1,8 +1,8 @@
 import logging
-from typing import Literal
 
 from pydantic import BaseModel
 
+from backend.api.features.store.db import StoreAgentsSortOptions
 from backend.blocks._base import (
     Block,
     BlockCategory,
@@ -176,8 +176,8 @@ class SearchStoreAgentsBlock(Block):
         category: str | None = SchemaField(
             description="Filter by category", default=None
         )
-        sort_by: Literal["rating", "runs", "name", "updated_at"] = SchemaField(
-            description="How to sort the results", default="rating"
+        sort_by: StoreAgentsSortOptions = SchemaField(
+            description="How to sort the results", default=StoreAgentsSortOptions.RATING
         )
         limit: int = SchemaField(
             description="Maximum number of results to return", default=10, ge=1, le=100
@@ -278,7 +278,7 @@ class SearchStoreAgentsBlock(Block):
         self,
         query: str | None = None,
         category: str | None = None,
-        sort_by: Literal["rating", "runs", "name", "updated_at"] = "rating",
+        sort_by: StoreAgentsSortOptions = StoreAgentsSortOptions.RATING,
         limit: int = 10,
     ) -> SearchAgentsResponse:
         """

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

@@ -0,0 +1,223 @@
+"""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

@@ -13,18 +13,17 @@ class TestLLMStatsTracking:
         """Test that llm_call returns proper token counts in LLMResponse."""
         import backend.blocks.llm as llm
 
-        # Mock the OpenAI client
+        # Mock the OpenAI Responses API response
         mock_response = MagicMock()
-        mock_response.choices = [
-            MagicMock(message=MagicMock(content="Test response", tool_calls=None))
-        ]
-        mock_response.usage = MagicMock(prompt_tokens=10, completion_tokens=20)
+        mock_response.output_text = "Test response"
+        mock_response.output = []
+        mock_response.usage = MagicMock(input_tokens=10, output_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.chat.completions.create = AsyncMock(return_value=mock_response)
+            mock_client.responses.create = AsyncMock(return_value=mock_response)
 
             response = await llm.llm_call(
                 credentials=llm.TEST_CREDENTIALS,
@@ -271,30 +270,17 @@ class TestLLMStatsTracking:
             mock_response = MagicMock()
             # Return different responses for chunk summary vs final summary
             if call_count == 1:
-                mock_response.choices = [
-                    MagicMock(
-                        message=MagicMock(
-                            content='<json_output id="test123456">{"summary": "Test chunk summary"}</json_output>',
-                            tool_calls=None,
-                        )
-                    )
-                ]
+                mock_response.output_text = '<json_output id="test123456">{"summary": "Test chunk summary"}</json_output>'
             else:
-                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)
+                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)
             return mock_response
 
         with patch("openai.AsyncOpenAI") as mock_openai:
             mock_client = AsyncMock()
             mock_openai.return_value = mock_client
-            mock_client.chat.completions.create = mock_create
+            mock_client.responses.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/blocks/test/test_perplexity.py

@@ -0,0 +1,81 @@
+"""Unit tests for PerplexityBlock model fallback behavior."""
+
+import pytest
+
+from backend.blocks.perplexity import (
+    TEST_CREDENTIALS_INPUT,
+    PerplexityBlock,
+    PerplexityModel,
+)
+
+
+def _make_input(**overrides) -> dict:
+    defaults = {
+        "prompt": "test query",
+        "credentials": TEST_CREDENTIALS_INPUT,
+    }
+    defaults.update(overrides)
+    return defaults
+
+
+class TestPerplexityModelFallback:
+    """Tests for fallback_invalid_model field_validator."""
+
+    def test_invalid_model_falls_back_to_sonar(self):
+        inp = PerplexityBlock.Input(**_make_input(model="gpt-5.2-2025-12-11"))
+        assert inp.model == PerplexityModel.SONAR
+
+    def test_another_invalid_model_falls_back_to_sonar(self):
+        inp = PerplexityBlock.Input(**_make_input(model="gpt-4o"))
+        assert inp.model == PerplexityModel.SONAR
+
+    def test_valid_model_string_is_kept(self):
+        inp = PerplexityBlock.Input(**_make_input(model="perplexity/sonar-pro"))
+        assert inp.model == PerplexityModel.SONAR_PRO
+
+    def test_valid_enum_value_is_kept(self):
+        inp = PerplexityBlock.Input(
+            **_make_input(model=PerplexityModel.SONAR_DEEP_RESEARCH)
+        )
+        assert inp.model == PerplexityModel.SONAR_DEEP_RESEARCH
+
+    def test_default_model_when_omitted(self):
+        inp = PerplexityBlock.Input(**_make_input())
+        assert inp.model == PerplexityModel.SONAR
+
+    @pytest.mark.parametrize(
+        "model_value",
+        [
+            "perplexity/sonar",
+            "perplexity/sonar-pro",
+            "perplexity/sonar-deep-research",
+        ],
+    )
+    def test_all_valid_models_accepted(self, model_value: str):
+        inp = PerplexityBlock.Input(**_make_input(model=model_value))
+        assert inp.model.value == model_value
+
+
+class TestPerplexityValidateData:
+    """Tests for validate_data which runs during block execution (before
+    Pydantic instantiation). Invalid models must be sanitized here so
+    JSON schema validation does not reject them."""
+
+    def test_invalid_model_sanitized_before_schema_validation(self):
+        data = _make_input(model="gpt-5.2-2025-12-11")
+        error = PerplexityBlock.Input.validate_data(data)
+        assert error is None
+        assert data["model"] == PerplexityModel.SONAR.value
+
+    def test_valid_model_unchanged_by_validate_data(self):
+        data = _make_input(model="perplexity/sonar-pro")
+        error = PerplexityBlock.Input.validate_data(data)
+        assert error is None
+        assert data["model"] == "perplexity/sonar-pro"
+
+    def test_missing_model_uses_default(self):
+        data = _make_input()  # no model key
+        error = PerplexityBlock.Input.validate_data(data)
+        assert error is None
+        inp = PerplexityBlock.Input(**data)
+        assert inp.model == PerplexityModel.SONAR

autogpt_platform/backend/backend/blocks/test/test_store_operations.py

@@ -2,6 +2,7 @@ from unittest.mock import MagicMock
 
 import pytest
 
+from backend.api.features.store.db import StoreAgentsSortOptions
 from backend.blocks.system.library_operations import (
     AddToLibraryFromStoreBlock,
     LibraryAgent,
@@ -121,7 +122,10 @@ async def test_search_store_agents_block(mocker):
     )
 
     input_data = block.Input(
-        query="test", category="productivity", sort_by="rating", limit=10
+        query="test",
+        category="productivity",
+        sort_by=StoreAgentsSortOptions.RATING,  # type: ignore[reportArgumentType]
+        limit=10,
     )
 
     outputs = {}

autogpt_platform/backend/backend/blocks/text.py

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

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

@@ -22,6 +22,7 @@ from backend.copilot.model import (
     update_session_title,
     upsert_chat_session,
 )
+from backend.copilot.prompting import get_baseline_supplement
 from backend.copilot.response_model import (
     StreamBaseResponse,
     StreamError,
@@ -35,13 +36,15 @@ from backend.copilot.response_model import (
     StreamToolInputAvailable,
     StreamToolInputStart,
     StreamToolOutputAvailable,
+    StreamUsage,
 )
 from backend.copilot.service import (
     _build_system_prompt,
     _generate_session_title,
-    client,
+    _get_openai_client,
     config,
 )
+from backend.copilot.token_tracking import persist_and_record_usage
 from backend.copilot.tools import execute_tool, get_available_tools
 from backend.copilot.tracking import track_user_message
 from backend.util.exceptions import NotFoundError
@@ -62,8 +65,8 @@ async def _update_title_async(
     """Generate and persist a session title in the background."""
     try:
         title = await _generate_session_title(message, user_id, session_id)
-        if title:
-            await update_session_title(session_id, title)
+        if title and user_id:
+            await update_session_title(session_id, user_id, title, only_if_empty=True)
     except Exception as e:
         logger.warning("[Baseline] Failed to update session title: %s", e)
 
@@ -88,7 +91,7 @@ async def _compress_session_messages(
         result = await compress_context(
             messages=messages_dict,
             model=config.model,
-            client=client,
+            client=_get_openai_client(),
         )
     except Exception as e:
         logger.warning("[Baseline] Context compression with LLM failed: %s", e)
@@ -176,14 +179,17 @@ async def stream_chat_completion_baseline(
     # changes from concurrent chats updating business understanding.
     is_first_turn = len(session.messages) <= 1
     if is_first_turn:
-        system_prompt, _ = await _build_system_prompt(
+        base_system_prompt, _ = await _build_system_prompt(
             user_id, has_conversation_history=False
         )
     else:
-        system_prompt, _ = await _build_system_prompt(
+        base_system_prompt, _ = await _build_system_prompt(
             user_id=None, has_conversation_history=True
         )
 
+    # Append tool documentation and technical notes
+    system_prompt = base_system_prompt + get_baseline_supplement()
+
     # Compress context if approaching the model's token limit
     messages_for_context = await _compress_session_messages(session.messages)
 
@@ -217,6 +223,10 @@ async def stream_chat_completion_baseline(
     text_block_id = str(uuid.uuid4())
     text_started = False
     step_open = False
+    # Token usage accumulators — populated from streaming chunks
+    turn_prompt_tokens = 0
+    turn_completion_tokens = 0
+    _stream_error = False  # Track whether an error occurred during streaming
     try:
         for _round in range(_MAX_TOOL_ROUNDS):
             # Open a new step for each LLM round
@@ -228,16 +238,31 @@ async def stream_chat_completion_baseline(
                 model=config.model,
                 messages=openai_messages,
                 stream=True,
+                stream_options={"include_usage": True},
             )
             if tools:
                 create_kwargs["tools"] = tools
-            response = await client.chat.completions.create(**create_kwargs)  # type: ignore[arg-type]  # dynamic kwargs
+            response = await _get_openai_client().chat.completions.create(**create_kwargs)  # type: ignore[arg-type]  # dynamic kwargs
 
             # Accumulate streamed response (text + tool calls)
             round_text = ""
             tool_calls_by_index: dict[int, dict[str, str]] = {}
 
             async for chunk in response:
+                # Capture token usage from the streaming chunk.
+                # OpenRouter normalises all providers into OpenAI format
+                # where prompt_tokens already includes cached tokens
+                # (unlike Anthropic's native API). Use += to sum all
+                # tool-call rounds since each API call is independent.
+                # NOTE: stream_options={"include_usage": True} is not
+                # universally supported — some providers (Mistral, Llama
+                # via OpenRouter) always return chunk.usage=None. When
+                # that happens, tokens stay 0 and the tiktoken fallback
+                # below activates. Fail-open: one round is estimated.
+                if chunk.usage:
+                    turn_prompt_tokens += chunk.usage.prompt_tokens or 0
+                    turn_completion_tokens += chunk.usage.completion_tokens or 0
+
                 delta = chunk.choices[0].delta if chunk.choices else None
                 if not delta:
                     continue
@@ -390,6 +415,7 @@ async def stream_chat_completion_baseline(
             )
 
     except Exception as e:
+        _stream_error = True
         error_msg = str(e) or type(e).__name__
         logger.error("[Baseline] Streaming error: %s", error_msg, exc_info=True)
         # Close any open text/step before emitting error
@@ -407,6 +433,49 @@ async def stream_chat_completion_baseline(
             except Exception:
                 logger.warning("[Baseline] Langfuse trace context teardown failed")
 
+        # Fallback: estimate tokens via tiktoken when the provider does
+        # not honour stream_options={"include_usage": True}.
+        # Count the full message list (system + history + turn) since
+        # each API call sends the complete context window.
+        # NOTE: This estimates one round's prompt tokens. Multi-round tool-calling
+        # turns consume prompt tokens on each API call, so the total is underestimated.
+        # Skip fallback when an error occurred and no output was produced —
+        # charging rate-limit tokens for completely failed requests is unfair.
+        if (
+            turn_prompt_tokens == 0
+            and turn_completion_tokens == 0
+            and not (_stream_error and not assistant_text)
+        ):
+            from backend.util.prompt import (
+                estimate_token_count,
+                estimate_token_count_str,
+            )
+
+            turn_prompt_tokens = max(
+                estimate_token_count(openai_messages, model=config.model), 1
+            )
+            turn_completion_tokens = estimate_token_count_str(
+                assistant_text, model=config.model
+            )
+            logger.info(
+                "[Baseline] No streaming usage reported; estimated tokens: "
+                "prompt=%d, completion=%d",
+                turn_prompt_tokens,
+                turn_completion_tokens,
+            )
+
+        # Persist token usage to session and record for rate limiting.
+        # NOTE: OpenRouter folds cached tokens into prompt_tokens, so we
+        # cannot break out cache_read/cache_creation weights. Users on the
+        # baseline path may be slightly over-counted vs the SDK path.
+        await persist_and_record_usage(
+            session=session,
+            user_id=user_id,
+            prompt_tokens=turn_prompt_tokens,
+            completion_tokens=turn_completion_tokens,
+            log_prefix="[Baseline]",
+        )
+
         # Persist assistant response
         if assistant_text:
             session.messages.append(
@@ -417,4 +486,16 @@ async def stream_chat_completion_baseline(
         except Exception as persist_err:
             logger.error("[Baseline] Failed to persist session: %s", persist_err)
 
+    # Yield usage and finish AFTER try/finally (not inside finally).
+    # PEP 525 prohibits yielding from finally in async generators during
+    # aclose() — doing so raises RuntimeError on client disconnect.
+    # On GeneratorExit the client is already gone, so unreachable yields
+    # are harmless; on normal completion they reach the SSE stream.
+    if turn_prompt_tokens > 0 or turn_completion_tokens > 0:
+        yield StreamUsage(
+            prompt_tokens=turn_prompt_tokens,
+            completion_tokens=turn_completion_tokens,
+            total_tokens=turn_prompt_tokens + turn_completion_tokens,
+        )
+
     yield StreamFinish()

autogpt_platform/backend/backend/copilot/config.py

@@ -1,10 +1,13 @@
 """Configuration management for chat system."""
 
 import os
+from typing import Literal
 
 from pydantic import Field, field_validator
 from pydantic_settings import BaseSettings
 
+from backend.util.clients import OPENROUTER_BASE_URL
+
 
 class ChatConfig(BaseSettings):
     """Configuration for the chat system."""
@@ -19,7 +22,7 @@ class ChatConfig(BaseSettings):
     )
     api_key: str | None = Field(default=None, description="OpenAI API key")
     base_url: str | None = Field(
-        default="https://openrouter.ai/api/v1",
+        default=OPENROUTER_BASE_URL,
         description="Base URL for API (e.g., for OpenRouter)",
     )
 
@@ -67,6 +70,27 @@ class ChatConfig(BaseSettings):
         description="Cache TTL in seconds for Langfuse prompt (0 to disable caching)",
     )
 
+    # Rate limiting — token-based limits per day and per week.
+    # Per-turn token cost varies with context size: ~10-15K for early turns,
+    # ~30-50K mid-session, up to ~100K pre-compaction. Average across a
+    # session with compaction cycles is ~25-35K tokens/turn, so 2.5M daily
+    # allows ~70-100 turns/day.
+    # Checked at the HTTP layer (routes.py) before each turn.
+    #
+    # TODO: These are deploy-time constants applied identically to every user.
+    #  If per-user or per-plan limits are needed (e.g., free tier vs paid), these
+    #  must move to the database (e.g., a UserPlan table) and get_usage_status /
+    #  check_rate_limit would look up each user's specific limits instead of
+    #  reading config.daily_token_limit / config.weekly_token_limit.
+    daily_token_limit: int = Field(
+        default=2_500_000,
+        description="Max tokens per day, resets at midnight UTC (0 = unlimited)",
+    )
+    weekly_token_limit: int = Field(
+        default=12_500_000,
+        description="Max tokens per week, resets Monday 00:00 UTC (0 = unlimited)",
+    )
+
     # Claude Agent SDK Configuration
     use_claude_agent_sdk: bool = Field(
         default=True,
@@ -91,10 +115,22 @@ class ChatConfig(BaseSettings):
         description="Use --resume for multi-turn conversations instead of "
         "history compression. Falls back to compression when unavailable.",
     )
+    use_openrouter: bool = Field(
+        default=True,
+        description="Enable routing API calls through the OpenRouter proxy. "
+        "The actual decision also requires ``api_key`` and ``base_url`` — "
+        "use the ``openrouter_active`` property for the final answer.",
+    )
     use_claude_code_subscription: bool = Field(
         default=False,
         description="For personal/dev use: use Claude Code CLI subscription auth instead of API keys. Requires `claude login` on the host. Only works with SDK mode.",
     )
+    test_mode: bool = Field(
+        default=False,
+        description="Use dummy service instead of real LLM calls. "
+        "Send __test_transient_error__, __test_fatal_error__, or "
+        "__test_slow_response__ to trigger specific scenarios.",
+    )
 
     # E2B Sandbox Configuration
     use_e2b_sandbox: bool = Field(
@@ -112,18 +148,52 @@ class ChatConfig(BaseSettings):
         description="E2B sandbox template to use for copilot sessions.",
     )
     e2b_sandbox_timeout: int = Field(
-        default=43200,  # 12 hours — same as session_ttl
-        description="E2B sandbox keepalive timeout in seconds.",
+        default=420,  # 7 min safety net — allows headroom for compaction retries
+        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.",
+    )
+    e2b_sandbox_on_timeout: Literal["kill", "pause"] = Field(
+        default="pause",
+        description="E2B lifecycle action on timeout: 'pause' (default, free) or 'kill'.",
     )
 
-    @field_validator("use_e2b_sandbox", mode="before")
-    @classmethod
-    def get_use_e2b_sandbox(cls, v):
-        """Get use_e2b_sandbox from environment if not provided."""
-        env_val = os.getenv("CHAT_USE_E2B_SANDBOX", "").lower()
-        if env_val:
-            return env_val in ("true", "1", "yes", "on")
-        return True if v is None else v
+    @property
+    def openrouter_active(self) -> bool:
+        """True when OpenRouter is enabled AND credentials are usable.
+
+        Single source of truth for "will the SDK route through OpenRouter?".
+        Checks the flag *and* that ``api_key`` + a valid ``base_url`` are
+        present — mirrors the fallback logic in ``_build_sdk_env``.
+        """
+        if not self.use_openrouter:
+            return False
+        base = (self.base_url or "").rstrip("/")
+        if base.endswith("/v1"):
+            base = base[:-3]
+        return bool(self.api_key and base and base.startswith("http"))
+
+    @property
+    def e2b_active(self) -> bool:
+        """True when E2B is enabled and the API key is present.
+
+        Single source of truth for "should we use E2B right now?".
+        Prefer this over combining ``use_e2b_sandbox`` and ``e2b_api_key``
+        separately at call sites.
+        """
+        return self.use_e2b_sandbox and bool(self.e2b_api_key)
+
+    @property
+    def active_e2b_api_key(self) -> str | None:
+        """Return the E2B API key when E2B is enabled and configured, else None.
+
+        Combines the ``use_e2b_sandbox`` flag check and key presence into one.
+        Use in callers::
+
+            if api_key := config.active_e2b_api_key:
+                # E2B is active; api_key is narrowed to str
+        """
+        return self.e2b_api_key if self.e2b_active else None
 
     @field_validator("e2b_api_key", mode="before")
     @classmethod
@@ -164,29 +234,9 @@ class ChatConfig(BaseSettings):
             if not v:
                 v = os.getenv("OPENAI_BASE_URL")
             if not v:
-                v = "https://openrouter.ai/api/v1"
+                v = OPENROUTER_BASE_URL
         return v
 
-    @field_validator("use_claude_agent_sdk", mode="before")
-    @classmethod
-    def get_use_claude_agent_sdk(cls, v):
-        """Get use_claude_agent_sdk from environment if not provided."""
-        # Check environment variable - default to True if not set
-        env_val = os.getenv("CHAT_USE_CLAUDE_AGENT_SDK", "").lower()
-        if env_val:
-            return env_val in ("true", "1", "yes", "on")
-        # Default to True (SDK enabled by default)
-        return True if v is None else v
-
-    @field_validator("use_claude_code_subscription", mode="before")
-    @classmethod
-    def get_use_claude_code_subscription(cls, v):
-        """Get use_claude_code_subscription from environment if not provided."""
-        env_val = os.getenv("CHAT_USE_CLAUDE_CODE_SUBSCRIPTION", "").lower()
-        if env_val:
-            return env_val in ("true", "1", "yes", "on")
-        return False if v is None else v
-
     # Prompt paths for different contexts
     PROMPT_PATHS: dict[str, str] = {
         "default": "prompts/chat_system.md",
@@ -196,6 +246,7 @@ class ChatConfig(BaseSettings):
     class Config:
         """Pydantic config."""
 
+        env_prefix = "CHAT_"
         env_file = ".env"
         env_file_encoding = "utf-8"
         extra = "ignore"  # Ignore extra environment variables

autogpt_platform/backend/backend/copilot/config_test.py

@@ -0,0 +1,89 @@
+"""Unit tests for ChatConfig."""
+
+import pytest
+
+from .config import ChatConfig
+
+# Env vars that the ChatConfig validators read — must be cleared so they don't
+# override the explicit constructor values we pass in each test.
+_ENV_VARS_TO_CLEAR = (
+    "CHAT_USE_E2B_SANDBOX",
+    "CHAT_E2B_API_KEY",
+    "E2B_API_KEY",
+    "CHAT_USE_OPENROUTER",
+    "CHAT_API_KEY",
+    "OPEN_ROUTER_API_KEY",
+    "OPENAI_API_KEY",
+    "CHAT_BASE_URL",
+    "OPENROUTER_BASE_URL",
+    "OPENAI_BASE_URL",
+)
+
+
+@pytest.fixture(autouse=True)
+def _clean_env(monkeypatch: pytest.MonkeyPatch) -> None:
+    for var in _ENV_VARS_TO_CLEAR:
+        monkeypatch.delenv(var, raising=False)
+
+
+class TestOpenrouterActive:
+    """Tests for the openrouter_active property."""
+
+    def test_enabled_with_credentials_returns_true(self):
+        cfg = ChatConfig(
+            use_openrouter=True,
+            api_key="or-key",
+            base_url="https://openrouter.ai/api/v1",
+        )
+        assert cfg.openrouter_active is True
+
+    def test_enabled_but_missing_api_key_returns_false(self):
+        cfg = ChatConfig(
+            use_openrouter=True,
+            api_key=None,
+            base_url="https://openrouter.ai/api/v1",
+        )
+        assert cfg.openrouter_active is False
+
+    def test_disabled_returns_false_despite_credentials(self):
+        cfg = ChatConfig(
+            use_openrouter=False,
+            api_key="or-key",
+            base_url="https://openrouter.ai/api/v1",
+        )
+        assert cfg.openrouter_active is False
+
+    def test_strips_v1_suffix_and_still_valid(self):
+        cfg = ChatConfig(
+            use_openrouter=True,
+            api_key="or-key",
+            base_url="https://openrouter.ai/api/v1",
+        )
+        assert cfg.openrouter_active is True
+
+    def test_invalid_base_url_returns_false(self):
+        cfg = ChatConfig(
+            use_openrouter=True,
+            api_key="or-key",
+            base_url="not-a-url",
+        )
+        assert cfg.openrouter_active is False
+
+
+class TestE2BActive:
+    """Tests for the e2b_active property — single source of truth for E2B usage."""
+
+    def test_both_enabled_and_key_present_returns_true(self):
+        """e2b_active is True when use_e2b_sandbox=True and e2b_api_key is set."""
+        cfg = ChatConfig(use_e2b_sandbox=True, e2b_api_key="test-key")
+        assert cfg.e2b_active is True
+
+    def test_enabled_but_missing_key_returns_false(self):
+        """e2b_active is False when use_e2b_sandbox=True but e2b_api_key is absent."""
+        cfg = ChatConfig(use_e2b_sandbox=True, e2b_api_key=None)
+        assert cfg.e2b_active is False
+
+    def test_disabled_returns_false(self):
+        """e2b_active is False when use_e2b_sandbox=False regardless of key."""
+        cfg = ChatConfig(use_e2b_sandbox=False, e2b_api_key="test-key")
+        assert cfg.e2b_active is False