chore(deps): bump docker/build-push-action from 6 to 7

Bumps [docker/build-push-action](https://github.com/docker/build-push-action) from 6 to 7.
- [Release notes](https://github.com/docker/build-push-action/releases)
- [Commits](https://github.com/docker/build-push-action/compare/v6...v7)

---
updated-dependencies:
- dependency-name: docker/build-push-action
  dependency-version: '7'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

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

.claude/skills/backend-check/SKILL.md

@@ -0,0 +1,17 @@
+---
+name: backend-check
+description: Run the full backend formatting, linting, and test suite. Ensures code quality before commits and PRs. TRIGGER when backend Python code has been modified and needs validation.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# Backend Check
+
+## Steps
+
+1. **Format**: `poetry run format` — runs formatting AND linting. NEVER run ruff/black/isort individually
+2. **Fix** any remaining errors manually, re-run until clean
+3. **Test**: `poetry run test` (runs DB setup + pytest). For specific files: `poetry run pytest -s -vvv <test_files>`
+4. **Snapshots** (if needed): `poetry run pytest path/to/test.py --snapshot-update` — review with `git diff`

.claude/skills/code-style/SKILL.md

@@ -0,0 +1,35 @@
+---
+name: code-style
+description: Python code style preferences for the AutoGPT backend. Apply when writing or reviewing Python code. TRIGGER when writing new Python code, reviewing PRs, or refactoring backend code.
+user-invocable: false
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# Code Style
+
+## Imports
+
+- **Top-level only** — no local/inner imports. Move all imports to the top of the file.
+
+## Typing
+
+- **No duck typing** — avoid `hasattr`, `getattr`, `isinstance` for type dispatch. Use proper typed interfaces, unions, or protocols.
+- **Pydantic models** over dataclass, namedtuple, or raw dict for structured data.
+- **No linter suppressors** — avoid `# type: ignore`, `# noqa`, `# pyright: ignore` etc. 99% of the time the right fix is fixing the type/code, not silencing the tool.
+
+## Code Structure
+
+- **List comprehensions** over manual loop-and-append.
+- **Early return** — guard clauses first, avoid deep nesting.
+- **Flatten inline** — prefer short, concise expressions. Reduce `if/else` chains with direct returns or ternaries when readable.
+- **Modular functions** — break complex logic into small, focused functions rather than long blocks with nested conditionals.
+
+## Review Checklist
+
+Before finishing, always ask:
+- Can any function be split into smaller pieces?
+- Is there unnecessary nesting that an early return would eliminate?
+- Can any loop be a comprehension?
+- Is there a simpler way to express this logic?

.claude/skills/frontend-check/SKILL.md

@@ -0,0 +1,16 @@
+---
+name: frontend-check
+description: Run the full frontend formatting, linting, and type checking suite. Ensures code quality before commits and PRs. TRIGGER when frontend TypeScript/React code has been modified and needs validation.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# Frontend Check
+
+## Steps (in order)
+
+1. **Format**: `pnpm format` — NEVER run individual formatters
+2. **Lint**: `pnpm lint` — fix errors, re-run until clean
+3. **Types**: `pnpm types` — if it keeps failing after multiple attempts, stop and ask the user

.claude/skills/new-block/SKILL.md

@@ -0,0 +1,29 @@
+---
+name: new-block
+description: Create a new backend block following the Block SDK Guide. Guides through provider configuration, schema definition, authentication, and testing. TRIGGER when user asks to create a new block, add a new integration, or build a new node for the graph editor.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# New Block Creation
+
+Read `docs/platform/block-sdk-guide.md` first for the full guide.
+
+## Steps
+
+1. **Provider config** (if external service): create `_config.py` with `ProviderBuilder`
+2. **Block file** in `backend/blocks/` (from `autogpt_platform/backend/`):
+   - Generate a UUID once with `uuid.uuid4()`, then **hard-code that string** as `id` (IDs must be stable across imports)
+   - `Input(BlockSchema)` and `Output(BlockSchema)` classes
+   - `async def run` that `yield`s output fields
+3. **Files**: use `store_media_file()` with `"for_block_output"` for outputs
+4. **Test**: `poetry run pytest 'backend/blocks/test/test_block.py::test_available_blocks[MyBlock]' -xvs`
+5. **Format**: `poetry run format`
+
+## Rules
+
+- Analyze interfaces: do inputs/outputs connect well with other blocks in a graph?
+- Use top-level imports, avoid duck typing
+- Always use `for_block_output` for block outputs

.claude/skills/openapi-regen/SKILL.md

@@ -0,0 +1,28 @@
+---
+name: openapi-regen
+description: Regenerate the OpenAPI spec and frontend API client. Starts the backend REST server, fetches the spec, and regenerates the typed frontend hooks. TRIGGER when API routes change, new endpoints are added, or frontend API types are stale.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# OpenAPI Spec Regeneration
+
+## Steps
+
+1. **Run end-to-end** in a single shell block (so `REST_PID` persists):
+   ```bash
+   cd autogpt_platform/backend && poetry run rest &
+   REST_PID=$!
+   WAIT=0; until curl -sf http://localhost:8006/health > /dev/null 2>&1; do sleep 1; WAIT=$((WAIT+1)); [ $WAIT -ge 60 ] && echo "Timed out" && kill $REST_PID && exit 1; done
+   cd ../frontend && pnpm generate:api:force
+   kill $REST_PID
+   pnpm types && pnpm lint && pnpm format
+   ```
+
+## Rules
+
+- Always use `pnpm generate:api:force` (not `pnpm generate:api`)
+- Don't manually edit files in `src/app/api/__generated__/`
+- Generated hooks follow: `use{Method}{Version}{OperationName}`

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

@@ -0,0 +1,31 @@
+---
+name: pr-create
+description: Create a pull request for the current branch. TRIGGER when user asks to create a PR, open a pull request, push changes for review, or submit work for merging.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# Create Pull Request
+
+## Steps
+
+1. **Check for existing PR**: `gh pr view --json url -q .url 2>/dev/null` — if a PR already exists, output its URL and stop
+2. **Understand changes**: `git status`, `git diff dev...HEAD`, `git log dev..HEAD --oneline`
+3. **Read PR template**: `.github/PULL_REQUEST_TEMPLATE.md`
+4. **Draft PR title**: Use conventional commits format (see CLAUDE.md for types and scopes)
+5. **Fill out PR template** as the body — be thorough in the Changes section
+6. **Format first** (if relevant changes exist):
+   - Backend: `cd autogpt_platform/backend && poetry run format`
+   - Frontend: `cd autogpt_platform/frontend && pnpm format`
+   - Fix any lint errors, then commit formatting changes before pushing
+7. **Push**: `git push -u origin HEAD`
+8. **Create PR**: `gh pr create --base dev`
+9. **Output** the PR URL
+
+## Rules
+
+- Always target `dev` branch
+- Do NOT run tests — CI will handle that
+- Use the PR template from `.github/PULL_REQUEST_TEMPLATE.md`

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

@@ -0,0 +1,51 @@
+---
+name: pr-review
+description: Address all open PR review comments systematically. Fetches comments, addresses each one, reacts +1/-1, and replies when clarification is needed. Keeps iterating until all comments are addressed and CI is green. TRIGGER when user shares a PR URL, asks to address review comments, fix PR feedback, or respond to reviewer comments.
+user-invocable: true
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# PR Review Comment Workflow
+
+## Steps
+
+1. **Find PR**: `gh pr list --head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT`
+2. **Fetch comments** (all three sources):
+   - `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews` (top-level reviews)
+   - `gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments` (inline review comments)
+   - `gh api repos/Significant-Gravitas/AutoGPT/issues/{N}/comments` (PR conversation comments)
+3. **Skip** comments already reacted to by PR author
+4. **For each unreacted comment**:
+   - Read referenced code, make the fix (or reply if you disagree/need info)
+   - **Inline review comments** (`pulls/{N}/comments`):
+     - React: `gh api repos/.../pulls/comments/{ID}/reactions -f content="+1"` (or `-1`)
+     - Reply: `gh api repos/.../pulls/{N}/comments/{ID}/replies -f body="..."`
+   - **PR conversation comments** (`issues/{N}/comments`):
+     - React: `gh api repos/.../issues/comments/{ID}/reactions -f content="+1"` (or `-1`)
+     - No threaded replies — post a new issue comment if needed
+   - **Top-level reviews**: no reaction API — address in code, reply via issue comment if needed
+5. **Include autogpt-reviewer bot fixes** too
+6. **Format**: `cd autogpt_platform/backend && poetry run format`, `cd autogpt_platform/frontend && pnpm format`
+7. **Commit & push**
+8. **Re-fetch comments** immediately — address any new unreacted ones before waiting on CI
+9. **Stay productive while CI runs** — don't idle. In priority order:
+   - Run any pending local tests (`poetry run pytest`, e2e, etc.) and fix failures
+   - Address any remaining comments
+   - Only poll `gh pr checks {N}` as the last resort when there's truly nothing left to do
+10. **If CI fails** — fix, go back to step 6
+11. **Re-fetch comments again** after CI is green — address anything that appeared while CI was running
+12. **Done** only when: all comments reacted AND CI is green.
+
+## CRITICAL: Do Not Stop
+
+**Loop is: address → format → commit → push → re-check comments → run local tests → wait CI → re-check comments → repeat.**
+
+Never idle. If CI is running and you have nothing to address, run local tests. Waiting on CI is the last resort.
+
+## Rules
+
+- One todo per comment
+- For inline review comments: reply on existing threads. For PR conversation comments: post a new issue comment (API doesn't support threaded replies)
+- React to every comment: +1 addressed, -1 disagreed (with explanation)

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

@@ -0,0 +1,45 @@
+---
+name: worktree-setup
+description: Set up a new git worktree for parallel development. Creates the worktree, copies .env files, installs dependencies, generates Prisma client, and optionally starts the app (with port conflict resolution) or runs tests. 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
+metadata:
+  author: autogpt-team
+  version: "1.0.0"
+---
+
+# Worktree Setup
+
+## Preferred: Use Branchlet
+
+The repo has a `.branchlet.json` config — it handles env file copying, dependency installation, and Prisma generation automatically.
+
+```bash
+npm install -g branchlet                                      # install once
+branchlet create -n <name> -s <source-branch> -b <new-branch>
+branchlet list --json   # list all worktrees
+```
+
+## Manual Fallback
+
+If branchlet isn't available:
+
+1. `git worktree add ../<RepoName><N> <branch-name>`
+2. Copy `.env` files: `backend/.env`, `frontend/.env`, `autogpt_platform/.env`, `db/docker/.env`
+3. Install deps:
+   - `cd autogpt_platform/backend && poetry install && poetry run prisma generate`
+   - `cd autogpt_platform/frontend && pnpm install`
+
+## Running the App
+
+Free ports first — backend uses: 8001, 8002, 8003, 8005, 8006, 8007, 8008.
+
+```bash
+for port in 8001 8002 8003 8005 8006 8007 8008; do
+  lsof -ti :$port | xargs kill -9 2>/dev/null || true
+done
+cd <worktree>/autogpt_platform/backend && poetry run app
+```
+
+## CoPilot Testing Gotcha
+
+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.

.dockerignore

@@ -5,42 +5,13 @@
 !docs/
 
 # Platform - Libs
-!autogpt_platform/autogpt_libs/autogpt_libs/
-!autogpt_platform/autogpt_libs/pyproject.toml
-!autogpt_platform/autogpt_libs/poetry.lock
-!autogpt_platform/autogpt_libs/README.md
+!autogpt_platform/autogpt_libs/
 
 # Platform - Backend
-!autogpt_platform/backend/backend/
-!autogpt_platform/backend/test/e2e_test_data.py
-!autogpt_platform/backend/migrations/
-!autogpt_platform/backend/schema.prisma
-!autogpt_platform/backend/pyproject.toml
-!autogpt_platform/backend/poetry.lock
-!autogpt_platform/backend/README.md
-!autogpt_platform/backend/.env
-!autogpt_platform/backend/gen_prisma_types_stub.py
-
-# Platform - Market
-!autogpt_platform/market/market/
-!autogpt_platform/market/scripts.py
-!autogpt_platform/market/schema.prisma
-!autogpt_platform/market/pyproject.toml
-!autogpt_platform/market/poetry.lock
-!autogpt_platform/market/README.md
+!autogpt_platform/backend/
 
 # Platform - Frontend
-!autogpt_platform/frontend/src/
-!autogpt_platform/frontend/public/
-!autogpt_platform/frontend/scripts/
-!autogpt_platform/frontend/package.json
-!autogpt_platform/frontend/pnpm-lock.yaml
-!autogpt_platform/frontend/tsconfig.json
-!autogpt_platform/frontend/README.md
-## config
-!autogpt_platform/frontend/*.config.*
-!autogpt_platform/frontend/.env.*
-!autogpt_platform/frontend/.env
+!autogpt_platform/frontend/
 
 # Classic - AutoGPT
 !classic/original_autogpt/autogpt/
@@ -64,6 +35,38 @@
 # Classic - Frontend
 !classic/frontend/build/web/
 
-# Explicitly re-ignore some folders
-.*
-**/__pycache__
+# Explicitly re-ignore unwanted files from whitelisted directories
+# Note: These patterns MUST come after the whitelist rules to take effect
+
+# Hidden files and directories (but keep frontend .env files needed for build)
+**/.*
+!autogpt_platform/frontend/.env
+!autogpt_platform/frontend/.env.default
+!autogpt_platform/frontend/.env.production
+
+# Python artifacts
+**/__pycache__/
+**/*.pyc
+**/*.pyo
+**/.venv/
+**/.ruff_cache/
+**/.pytest_cache/
+**/.coverage
+**/htmlcov/
+
+# Node artifacts
+**/node_modules/
+**/.next/
+**/storybook-static/
+**/playwright-report/
+**/test-results/
+
+# Build artifacts
+**/dist/
+**/build/
+!autogpt_platform/frontend/src/**/build/
+**/target/
+
+# Logs and temp files
+**/*.log
+**/*.tmp

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

@@ -23,7 +23,7 @@ jobs:
 
       - id: build
         name: Build image
-        uses: docker/build-push-action@v6
+        uses: docker/build-push-action@v7
         with:
           context: classic/
           file: classic/Dockerfile.autogpt

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

@@ -47,7 +47,7 @@ jobs:
 
       - id: build
         name: Build image
-        uses: docker/build-push-action@v6
+        uses: docker/build-push-action@v7
         with:
           context: classic/
           file: classic/Dockerfile.autogpt
@@ -117,7 +117,7 @@ jobs:
 
       - id: build
         name: Build image
-        uses: docker/build-push-action@v6
+        uses: docker/build-push-action@v7
         with:
           context: classic/
           file: classic/Dockerfile.autogpt

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

@@ -42,7 +42,7 @@ jobs:
 
       - id: build
         name: Build image
-        uses: docker/build-push-action@v6
+        uses: docker/build-push-action@v7
         with:
           context: classic/
           file: Dockerfile.autogpt

.github/workflows/claude-ci-failure-auto-fix.yml

@@ -22,7 +22,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           ref: ${{ github.event.workflow_run.head_branch }}
           fetch-depth: 0
@@ -40,9 +40,51 @@ jobs:
           git checkout -b "$BRANCH_NAME"
           echo "branch_name=$BRANCH_NAME" >> $GITHUB_OUTPUT
 
+      # Backend Python/Poetry setup (so Claude can run linting/tests)
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+
+      - name: Set up Python dependency cache
+        uses: actions/cache@v5
+        with:
+          path: ~/.cache/pypoetry
+          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
+
+      - name: Install Poetry
+        run: |
+          cd autogpt_platform/backend
+          HEAD_POETRY_VERSION=$(python3 ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
+          curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
+          echo "$HOME/.local/bin" >> $GITHUB_PATH
+
+      - name: Install Python dependencies
+        working-directory: autogpt_platform/backend
+        run: poetry install
+
+      - name: Generate Prisma Client
+        working-directory: autogpt_platform/backend
+        run: poetry run prisma generate && poetry run gen-prisma-stub
+
+      # Frontend Node.js/pnpm setup (so Claude can run linting/tests)
+      - name: Enable corepack
+        run: corepack enable
+
+      - name: Set up Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: "22"
+          cache: "pnpm"
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
+
+      - name: Install JavaScript dependencies
+        working-directory: autogpt_platform/frontend
+        run: pnpm install --frozen-lockfile
+
       - name: Get CI failure details
         id: failure_details
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             const run = await github.rest.actions.getWorkflowRun({

.github/workflows/claude-dependabot.yml

@@ -30,7 +30,7 @@ jobs:
       actions: read # Required for CI access
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 1
 
@@ -41,7 +41,7 @@ jobs:
           python-version: "3.11"  # Use standard version matching CI
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -77,27 +77,15 @@ jobs:
         run: poetry run prisma generate && poetry run gen-prisma-stub
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
-      - name: Set up Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version: "22"
-
       - name: Enable corepack
         run: corepack enable
 
-      - name: Set pnpm store directory
-        run: |
-          pnpm config set store-dir ~/.pnpm-store
-          echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
-
-      - name: Cache frontend dependencies
-        uses: actions/cache@v4
+      - name: Set up Node.js
+        uses: actions/setup-node@v6
         with:
-          path: ~/.pnpm-store
-          key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
-          restore-keys: |
-            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
-            ${{ runner.os }}-pnpm-
+          node-version: "22"
+          cache: "pnpm"
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
 
       - name: Install JavaScript dependencies
         working-directory: autogpt_platform/frontend
@@ -124,7 +112,7 @@ jobs:
       # Phase 1: Cache and load Docker images for faster setup
       - name: Set up Docker image cache
         id: docker-cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes

.github/workflows/claude.yml

@@ -40,7 +40,7 @@ jobs:
       actions: read # Required for CI access
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 1
 
@@ -57,7 +57,7 @@ jobs:
           python-version: "3.11"  # Use standard version matching CI
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -93,27 +93,15 @@ jobs:
         run: poetry run prisma generate && poetry run gen-prisma-stub
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
-      - name: Set up Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version: "22"
-
       - name: Enable corepack
         run: corepack enable
 
-      - name: Set pnpm store directory
-        run: |
-          pnpm config set store-dir ~/.pnpm-store
-          echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
-
-      - name: Cache frontend dependencies
-        uses: actions/cache@v4
+      - name: Set up Node.js
+        uses: actions/setup-node@v6
         with:
-          path: ~/.pnpm-store
-          key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
-          restore-keys: |
-            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
-            ${{ runner.os }}-pnpm-
+          node-version: "22"
+          cache: "pnpm"
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
 
       - name: Install JavaScript dependencies
         working-directory: autogpt_platform/frontend
@@ -140,7 +128,7 @@ jobs:
       # Phase 1: Cache and load Docker images for faster setup
       - name: Set up Docker image cache
         id: docker-cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes

.github/workflows/codeql.yml

@@ -58,11 +58,11 @@ jobs:
         # your codebase is analyzed, see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/codeql-code-scanning-for-compiled-languages
     steps:
     - name: Checkout repository
-      uses: actions/checkout@v4
+      uses: actions/checkout@v6
 
     # Initializes the CodeQL tools for scanning.
     - name: Initialize CodeQL
-      uses: github/codeql-action/init@v3
+      uses: github/codeql-action/init@v4
       with:
         languages: ${{ matrix.language }}
         build-mode: ${{ matrix.build-mode }}
@@ -93,6 +93,6 @@ jobs:
         exit 1
 
     - name: Perform CodeQL Analysis
-      uses: github/codeql-action/analyze@v3
+      uses: github/codeql-action/analyze@v4
       with:
         category: "/language:${{matrix.language}}"

.github/workflows/copilot-setup-steps.yml

@@ -27,7 +27,7 @@ jobs:
     # If you do not check out your code, Copilot will do this for you.
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
           submodules: true
@@ -39,7 +39,7 @@ jobs:
           python-version: "3.11"  # Use standard version matching CI
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -76,7 +76,7 @@ jobs:
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22"
 
@@ -89,7 +89,7 @@ jobs:
           echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
 
       - name: Cache frontend dependencies
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -132,7 +132,7 @@ jobs:
       # Phase 1: Cache and load Docker images for faster setup
       - name: Set up Docker image cache
         id: docker-cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes

.github/workflows/docs-block-sync.yml

@@ -23,7 +23,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 1
 
@@ -33,7 +33,7 @@ jobs:
           python-version: "3.11"
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}

.github/workflows/docs-claude-review.yml

@@ -7,6 +7,10 @@ on:
       - "docs/integrations/**"
       - "autogpt_platform/backend/backend/blocks/**"
 
+concurrency:
+  group: claude-docs-review-${{ github.event.pull_request.number }}
+  cancel-in-progress: true
+
 jobs:
   claude-review:
     # Only run for PRs from members/collaborators
@@ -23,7 +27,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
@@ -33,7 +37,7 @@ jobs:
           python-version: "3.11"
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -91,5 +95,35 @@ jobs:
             3. Read corresponding documentation files to verify accuracy
             4. Provide your feedback as a PR comment
 
+            ## IMPORTANT: Comment Marker
+            Start your PR comment with exactly this HTML comment marker on its own line:
+            <!-- CLAUDE_DOCS_REVIEW -->
+
+            This marker is used to identify and replace your comment on subsequent runs.
+
             Be constructive and specific. If everything looks good, say so!
             If there are issues, explain what's wrong and suggest how to fix it.
+
+      - name: Delete old Claude review comments
+        env:
+          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          # Get all comment IDs with our marker, sorted by creation date (oldest first)
+          COMMENT_IDS=$(gh api \
+            repos/${{ github.repository }}/issues/${{ github.event.pull_request.number }}/comments \
+            --jq '[.[] | select(.body | contains("<!-- CLAUDE_DOCS_REVIEW -->"))] | sort_by(.created_at) | .[].id')
+
+          # Count comments
+          COMMENT_COUNT=$(echo "$COMMENT_IDS" | grep -c . || true)
+
+          if [ "$COMMENT_COUNT" -gt 1 ]; then
+            # Delete all but the last (newest) comment
+            echo "$COMMENT_IDS" | head -n -1 | while read -r COMMENT_ID; do
+              if [ -n "$COMMENT_ID" ]; then
+                echo "Deleting old review comment: $COMMENT_ID"
+                gh api -X DELETE repos/${{ github.repository }}/issues/comments/$COMMENT_ID
+              fi
+            done
+          else
+            echo "No old review comments to clean up"
+          fi

.github/workflows/docs-enhance.yml

@@ -28,7 +28,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 1
 
@@ -38,7 +38,7 @@ jobs:
           python-version: "3.11"
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}

.github/workflows/platform-autogpt-deploy-dev.yaml

@@ -25,7 +25,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           ref: ${{ github.event.inputs.git_ref || github.ref_name }}
 
@@ -52,7 +52,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Trigger deploy workflow
-        uses: peter-evans/repository-dispatch@v3
+        uses: peter-evans/repository-dispatch@v4
         with:
           token: ${{ secrets.DEPLOY_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure

.github/workflows/platform-autogpt-deploy-prod.yml

@@ -17,7 +17,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           ref: ${{ github.ref_name || 'master' }}
 
@@ -45,7 +45,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Trigger deploy workflow
-        uses: peter-evans/repository-dispatch@v3
+        uses: peter-evans/repository-dispatch@v4
         with:
           token: ${{ secrets.DEPLOY_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure

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

@@ -41,13 +41,18 @@ jobs:
         ports:
           - 6379:6379
       rabbitmq:
-        image: rabbitmq:3.12-management
+        image: rabbitmq:4.1.4
         ports:
           - 5672:5672
-          - 15672:15672
         env:
           RABBITMQ_DEFAULT_USER: ${{ env.RABBITMQ_DEFAULT_USER }}
           RABBITMQ_DEFAULT_PASS: ${{ env.RABBITMQ_DEFAULT_PASS }}
+        options: >-
+          --health-cmd "rabbitmq-diagnostics -q ping"
+          --health-interval 30s
+          --health-timeout 10s
+          --health-retries 5
+          --health-start-period 10s
       clamav:
         image: clamav/clamav-debian:latest
         ports:
@@ -68,7 +73,7 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
           submodules: true
@@ -88,7 +93,7 @@ jobs:
         run: echo "date=$(date +'%Y-%m-%d')" >> $GITHUB_OUTPUT
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}

.github/workflows/platform-dev-deploy-event-dispatcher.yml

@@ -17,7 +17,7 @@ jobs:
       - name: Check comment permissions and deployment status
         id: check_status
         if: github.event_name == 'issue_comment' && github.event.issue.pull_request
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             const commentBody = context.payload.comment.body.trim();
@@ -55,7 +55,7 @@ jobs:
 
       - name: Post permission denied comment
         if: steps.check_status.outputs.permission_denied == 'true'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             await github.rest.issues.createComment({
@@ -68,7 +68,7 @@ jobs:
       - name: Get PR details for deployment
         id: pr_details
         if: steps.check_status.outputs.should_deploy == 'true' || steps.check_status.outputs.should_undeploy == 'true'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             const pr = await github.rest.pulls.get({
@@ -82,7 +82,7 @@ jobs:
           
       - name: Dispatch Deploy Event
         if: steps.check_status.outputs.should_deploy == 'true'
-        uses: peter-evans/repository-dispatch@v3
+        uses: peter-evans/repository-dispatch@v4
         with:
           token: ${{ secrets.DISPATCH_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
@@ -98,7 +98,7 @@ jobs:
 
       - name: Post deploy success comment
         if: steps.check_status.outputs.should_deploy == 'true'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             await github.rest.issues.createComment({
@@ -110,7 +110,7 @@ jobs:
 
       - name: Dispatch Undeploy Event (from comment)
         if: steps.check_status.outputs.should_undeploy == 'true'
-        uses: peter-evans/repository-dispatch@v3
+        uses: peter-evans/repository-dispatch@v4
         with:
           token: ${{ secrets.DISPATCH_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
@@ -126,7 +126,7 @@ jobs:
 
       - name: Post undeploy success comment
         if: steps.check_status.outputs.should_undeploy == 'true'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             await github.rest.issues.createComment({
@@ -139,7 +139,7 @@ jobs:
       - name: Check deployment status on PR close
         id: check_pr_close
         if: github.event_name == 'pull_request' && github.event.action == 'closed'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             const comments = await github.rest.issues.listComments({
@@ -168,7 +168,7 @@ jobs:
           github.event_name == 'pull_request' &&
           github.event.action == 'closed' &&
           steps.check_pr_close.outputs.should_undeploy == 'true'
-        uses: peter-evans/repository-dispatch@v3
+        uses: peter-evans/repository-dispatch@v4
         with:
           token: ${{ secrets.DISPATCH_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
@@ -187,7 +187,7 @@ jobs:
           github.event_name == 'pull_request' &&
           github.event.action == 'closed' &&
           steps.check_pr_close.outputs.should_undeploy == 'true'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             await github.rest.issues.createComment({

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

@@ -6,10 +6,16 @@ on:
     paths:
       - ".github/workflows/platform-frontend-ci.yml"
       - "autogpt_platform/frontend/**"
+      - "autogpt_platform/backend/Dockerfile"
+      - "autogpt_platform/docker-compose.yml"
+      - "autogpt_platform/docker-compose.platform.yml"
   pull_request:
     paths:
       - ".github/workflows/platform-frontend-ci.yml"
       - "autogpt_platform/frontend/**"
+      - "autogpt_platform/backend/Dockerfile"
+      - "autogpt_platform/docker-compose.yml"
+      - "autogpt_platform/docker-compose.platform.yml"
   merge_group:
   workflow_dispatch:
 
@@ -26,12 +32,11 @@ jobs:
   setup:
     runs-on: ubuntu-latest
     outputs:
-      cache-key: ${{ steps.cache-key.outputs.key }}
       components-changed: ${{ steps.filter.outputs.components }}
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Check for component changes
         uses: dorny/paths-filter@v3
@@ -41,28 +46,17 @@ jobs:
             components:
               - 'autogpt_platform/frontend/src/components/**'
 
-      - name: Set up Node.js
-        uses: actions/setup-node@v4
-        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@v4
+      - 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
 
   lint:
@@ -71,24 +65,17 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
-
-      - name: Set up Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version: "22.18.0"
+        uses: actions/checkout@v6
 
       - name: Enable corepack
         run: corepack enable
 
-      - name: Restore dependencies cache
-        uses: actions/cache@v4
+      - name: Set up Node
+        uses: actions/setup-node@v6
         with:
-          path: ~/.pnpm-store
-          key: ${{ needs.setup.outputs.cache-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
         run: pnpm install --frozen-lockfile
@@ -107,26 +94,19 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
-      - name: Set up Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version: "22.18.0"
-
       - name: Enable corepack
         run: corepack enable
 
-      - name: Restore dependencies cache
-        uses: actions/cache@v4
+      - name: Set up Node
+        uses: actions/setup-node@v6
         with:
-          path: ~/.pnpm-store
-          key: ${{ needs.setup.outputs.cache-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
         run: pnpm install --frozen-lockfile
@@ -141,30 +121,20 @@ jobs:
           exitOnceUploaded: true
 
   e2e_test:
+    name: end-to-end tests
     runs-on: big-boi
-    needs: setup
-    strategy:
-      fail-fast: false
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           submodules: recursive
 
-      - name: Set up Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version: "22.18.0"
-
-      - name: Enable corepack
-        run: corepack enable
-
-      - name: Copy default supabase .env
+      - name: Set up Platform - Copy default supabase .env
         run: |
           cp ../.env.default ../.env
 
-      - name: Copy backend .env and set OpenAI API key
+      - 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
@@ -172,77 +142,125 @@ jobs:
           # Used by E2E test data script to generate embeddings for approved store agents
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
 
-      - name: Set up Docker Buildx
+      - name: Set up Platform - Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
-
-      - name: Cache Docker layers
-        uses: actions/cache@v4
         with:
-          path: /tmp/.buildx-cache
-          key: ${{ runner.os }}-buildx-frontend-test-${{ hashFiles('autogpt_platform/docker-compose.yml', 'autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/pyproject.toml', 'autogpt_platform/backend/poetry.lock') }}
-          restore-keys: |
-            ${{ runner.os }}-buildx-frontend-test-
+          driver: docker-container
+          driver-opts: network=host
 
-      - name: Run docker compose
+      - 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: |
-          NEXT_PUBLIC_PW_TEST=true docker compose -f ../docker-compose.yml up -d
+          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:
-          DOCKER_BUILDKIT: 1
-          BUILDX_CACHE_FROM: type=local,src=/tmp/.buildx-cache
-          BUILDX_CACHE_TO: type=local,dest=/tmp/.buildx-cache-new,mode=max
+          NEXT_PUBLIC_PW_TEST: true
 
-      - name: Move cache
-        run: |
-          rm -rf /tmp/.buildx-cache
-          if [ -d "/tmp/.buildx-cache-new" ]; then
-            mv /tmp/.buildx-cache-new /tmp/.buildx-cache
-          fi
+      - 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: Wait for services to be ready
+      - 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..."
-          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..."
+        env:
+          NEXT_PUBLIC_PW_TEST: true
 
-      - name: Create E2E test data
+      - name: Set up tests - Create E2E test data
+        if: steps.e2e-data-cache.outputs.cache-hit != 'true'
         run: |
           echo "Creating E2E test data..."
-          # First try to run the script from inside the container
-          if docker compose -f ../docker-compose.yml exec -T rest_server test -f /app/autogpt_platform/backend/test/e2e_test_data.py; then
-            echo "✅ Found e2e_test_data.py in container, running it..."
-            docker compose -f ../docker-compose.yml exec -T rest_server sh -c "cd /app/autogpt_platform && python backend/test/e2e_test_data.py" || {
-              echo "❌ E2E test data creation failed!"
-              docker compose -f ../docker-compose.yml logs --tail=50 rest_server
-              exit 1
-            }
-          else
-            echo "⚠️ e2e_test_data.py not found in container, copying and running..."
-            # Copy the script into the container and run it
-            docker cp ../backend/test/e2e_test_data.py $(docker compose -f ../docker-compose.yml ps -q rest_server):/tmp/e2e_test_data.py || {
-              echo "❌ Failed to copy script to container"
-              exit 1
-            }
-            docker compose -f ../docker-compose.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.yml logs --tail=50 rest_server
-              exit 1
-            }
-          fi
+          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
+          }
 
-      - name: Restore dependencies cache
-        uses: actions/cache@v4
+          # 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:
-          path: ~/.pnpm-store
-          key: ${{ needs.setup.outputs.cache-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: Set up tests - Install dependencies
         run: pnpm install --frozen-lockfile
 
-      - name: Install Browser 'chromium'
+      - name: Set up tests - Install browser 'chromium'
         run: pnpm playwright install --with-deps chromium
 
       - name: Run Playwright tests
@@ -269,7 +287,7 @@ jobs:
 
       - name: Print Final Docker Compose logs
         if: always()
-        run: docker compose -f ../docker-compose.yml logs
+        run: docker compose -f ../docker-compose.resolved.yml logs
 
   integration_test:
     runs-on: ubuntu-latest
@@ -277,26 +295,19 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           submodules: recursive
 
-      - name: Set up Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version: "22.18.0"
-
       - name: Enable corepack
         run: corepack enable
 
-      - name: Restore dependencies cache
-        uses: actions/cache@v4
+      - name: Set up Node
+        uses: actions/setup-node@v6
         with:
-          path: ~/.pnpm-store
-          key: ${{ needs.setup.outputs.cache-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
         run: pnpm install --frozen-lockfile

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

@@ -29,10 +29,10 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
 
@@ -44,7 +44,7 @@ jobs:
         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@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ steps.cache-key.outputs.key }}
@@ -56,19 +56,19 @@ jobs:
         run: pnpm install --frozen-lockfile
 
   types:
-    runs-on: ubuntu-latest
+    runs-on: big-boi
     needs: setup
     strategy:
       fail-fast: false
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           submodules: recursive
 
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
 
@@ -85,10 +85,10 @@ jobs:
 
       - name: Run docker compose
         run: |
-          docker compose -f ../docker-compose.yml --profile local --profile deps_backend up -d
+          docker compose -f ../docker-compose.yml --profile local up -d deps_backend
 
       - name: Restore dependencies cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}

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

@@ -0,0 +1,39 @@
+name: PR Overlap Detection
+
+on:
+  pull_request:
+    types: [opened, synchronize, reopened]
+    branches:
+      - dev
+      - master
+
+permissions:
+  contents: read
+  pull-requests: write
+
+jobs:
+  check-overlaps:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0  # Need full history for merge testing
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.11'
+
+      - name: Configure git
+        run: |
+          git config user.email "github-actions[bot]@users.noreply.github.com"
+          git config user.name "github-actions[bot]"
+
+      - name: Run overlap detection
+        env:
+          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        # Always succeed - this check informs contributors, it shouldn't block merging
+        continue-on-error: true
+        run: |
+          python .github/scripts/detect_overlaps.py ${{ github.event.pull_request.number }}

.github/workflows/repo-workflow-checker.yml

@@ -11,7 +11,7 @@ jobs:
     steps:
       # - name: Wait some time for all actions to start
       #   run: sleep 30
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
         # with:
           # fetch-depth: 0
       - name: Set up Python

.github/workflows/scripts/docker-ci-fix-compose-build-cache.py

@@ -0,0 +1,195 @@
+#!/usr/bin/env python3
+"""
+Add cache configuration to a resolved docker-compose file for all services
+that have a build key, and ensure image names match what docker compose expects.
+"""
+
+import argparse
+
+import yaml
+
+
+DEFAULT_BRANCH = "dev"
+CACHE_BUILDS_FOR_COMPONENTS = ["backend", "frontend"]
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Add cache config to a resolved compose file"
+    )
+    parser.add_argument(
+        "--source",
+        required=True,
+        help="Source compose file to read (should be output of `docker compose config`)",
+    )
+    parser.add_argument(
+        "--cache-from",
+        default="type=gha",
+        help="Cache source configuration",
+    )
+    parser.add_argument(
+        "--cache-to",
+        default="type=gha,mode=max",
+        help="Cache destination configuration",
+    )
+    for component in CACHE_BUILDS_FOR_COMPONENTS:
+        parser.add_argument(
+            f"--{component}-hash",
+            default="",
+            help=f"Hash for {component} cache scope (e.g., from hashFiles())",
+        )
+    parser.add_argument(
+        "--git-ref",
+        default="",
+        help="Git ref for branch-based cache scope (e.g., refs/heads/master)",
+    )
+    args = parser.parse_args()
+
+    # Normalize git ref to a safe scope name (e.g., refs/heads/master -> master)
+    git_ref_scope = ""
+    if args.git_ref:
+        git_ref_scope = args.git_ref.replace("refs/heads/", "").replace("/", "-")
+
+    with open(args.source, "r") as f:
+        compose = yaml.safe_load(f)
+
+    # Get project name from compose file or default
+    project_name = compose.get("name", "autogpt_platform")
+
+    def get_image_name(dockerfile: str, target: str) -> str:
+        """Generate image name based on Dockerfile folder and build target."""
+        dockerfile_parts = dockerfile.replace("\\", "/").split("/")
+        if len(dockerfile_parts) >= 2:
+            folder_name = dockerfile_parts[-2]  # e.g., "backend" or "frontend"
+        else:
+            folder_name = "app"
+        return f"{project_name}-{folder_name}:{target}"
+
+    def get_build_key(dockerfile: str, target: str) -> str:
+        """Generate a unique key for a Dockerfile+target combination."""
+        return f"{dockerfile}:{target}"
+
+    def get_component(dockerfile: str) -> str | None:
+        """Get component name (frontend/backend) from dockerfile path."""
+        for component in CACHE_BUILDS_FOR_COMPONENTS:
+            if component in dockerfile:
+                return component
+        return None
+
+    # First pass: collect all services with build configs and identify duplicates
+    # Track which (dockerfile, target) combinations we've seen
+    build_key_to_first_service: dict[str, str] = {}
+    services_to_build: list[str] = []
+    services_to_dedupe: list[str] = []
+
+    for service_name, service_config in compose.get("services", {}).items():
+        if "build" not in service_config:
+            continue
+
+        build_config = service_config["build"]
+        dockerfile = build_config.get("dockerfile", "Dockerfile")
+        target = build_config.get("target", "default")
+        build_key = get_build_key(dockerfile, target)
+
+        if build_key not in build_key_to_first_service:
+            # First service with this build config - it will do the actual build
+            build_key_to_first_service[build_key] = service_name
+            services_to_build.append(service_name)
+        else:
+            # Duplicate - will just use the image from the first service
+            services_to_dedupe.append(service_name)
+
+    # Second pass: configure builds and deduplicate
+    modified_services = []
+    for service_name, service_config in compose.get("services", {}).items():
+        if "build" not in service_config:
+            continue
+
+        build_config = service_config["build"]
+        dockerfile = build_config.get("dockerfile", "Dockerfile")
+        target = build_config.get("target", "latest")
+        image_name = get_image_name(dockerfile, target)
+
+        # Set image name for all services (needed for both builders and deduped)
+        service_config["image"] = image_name
+
+        if service_name in services_to_dedupe:
+            # Remove build config - this service will use the pre-built image
+            del service_config["build"]
+            continue
+
+        # This service will do the actual build - add cache config
+        cache_from_list = []
+        cache_to_list = []
+
+        component = get_component(dockerfile)
+        if not component:
+            # Skip services that don't clearly match frontend/backend
+            continue
+
+        # Get the hash for this component
+        component_hash = getattr(args, f"{component}_hash")
+
+        # Scope format: platform-{component}-{target}-{hash|ref}
+        # Example: platform-backend-server-abc123
+
+        if "type=gha" in args.cache_from:
+            # 1. Primary: exact hash match (most specific)
+            if component_hash:
+                hash_scope = f"platform-{component}-{target}-{component_hash}"
+                cache_from_list.append(f"{args.cache_from},scope={hash_scope}")
+
+            # 2. Fallback: branch-based cache
+            if git_ref_scope:
+                ref_scope = f"platform-{component}-{target}-{git_ref_scope}"
+                cache_from_list.append(f"{args.cache_from},scope={ref_scope}")
+
+            # 3. Fallback: dev branch cache (for PRs/feature branches)
+            if git_ref_scope and git_ref_scope != DEFAULT_BRANCH:
+                master_scope = f"platform-{component}-{target}-{DEFAULT_BRANCH}"
+                cache_from_list.append(f"{args.cache_from},scope={master_scope}")
+
+        if "type=gha" in args.cache_to:
+            # Write to both hash-based and branch-based scopes
+            if component_hash:
+                hash_scope = f"platform-{component}-{target}-{component_hash}"
+                cache_to_list.append(f"{args.cache_to},scope={hash_scope}")
+
+            if git_ref_scope:
+                ref_scope = f"platform-{component}-{target}-{git_ref_scope}"
+                cache_to_list.append(f"{args.cache_to},scope={ref_scope}")
+
+        # Ensure we have at least one cache source/target
+        if not cache_from_list:
+            cache_from_list.append(args.cache_from)
+        if not cache_to_list:
+            cache_to_list.append(args.cache_to)
+
+        build_config["cache_from"] = cache_from_list
+        build_config["cache_to"] = cache_to_list
+        modified_services.append(service_name)
+
+    # Write back to the same file
+    with open(args.source, "w") as f:
+        yaml.dump(compose, f, default_flow_style=False, sort_keys=False)
+
+    print(f"Added cache config to {len(modified_services)} services in {args.source}:")
+    for svc in modified_services:
+        svc_config = compose["services"][svc]
+        build_cfg = svc_config.get("build", {})
+        cache_from_list = build_cfg.get("cache_from", ["none"])
+        cache_to_list = build_cfg.get("cache_to", ["none"])
+        print(f"  - {svc}")
+        print(f"      image: {svc_config.get('image', 'N/A')}")
+        print(f"      cache_from: {cache_from_list}")
+        print(f"      cache_to: {cache_to_list}")
+    if services_to_dedupe:
+        print(
+            f"Deduplicated {len(services_to_dedupe)} services (will use pre-built images):"
+        )
+        for svc in services_to_dedupe:
+            print(f"  - {svc} -> {compose['services'][svc].get('image', 'N/A')}")
+
+
+if __name__ == "__main__":
+    main()

.gitignore

@@ -180,4 +180,6 @@ autogpt_platform/backend/settings.py
 .claude/settings.local.json
 CLAUDE.local.md
 /autogpt_platform/backend/logs
-.next
+.next
+# Implementation plans (generated by AI agents)
+plans/

.nvmrc

@@ -0,0 +1 @@
+22

.pre-commit-config.yaml

@@ -1,3 +1,10 @@
+default_install_hook_types:
+  - pre-commit
+  - pre-push
+  - post-checkout
+
+default_stages: [pre-commit]
+
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
     rev: v4.4.0
@@ -17,6 +24,7 @@ repos:
         name: Detect secrets
         description: Detects high entropy strings that are likely to be passwords.
         files: ^autogpt_platform/
+        exclude: pnpm-lock\.yaml$
         stages: [pre-push]
 
   - repo: local
@@ -26,49 +34,106 @@ repos:
       - id: poetry-install
         name: Check & Install dependencies - AutoGPT Platform - Backend
         alias: poetry-install-platform-backend
-        entry: poetry -C autogpt_platform/backend install
         # include autogpt_libs source (since it's a path dependency)
-        files: ^autogpt_platform/(backend|autogpt_libs)/poetry\.lock$
-        types: [file]
+        entry: >
+          bash -c '
+          if [ -n "$PRE_COMMIT_FROM_REF" ]; then
+            git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
+          else
+            git diff --cached --name-only
+          fi | grep -qE "^autogpt_platform/(backend|autogpt_libs)/poetry\.lock$" || exit 0;
+          poetry -C autogpt_platform/backend install
+          '
+        always_run: true
         language: system
         pass_filenames: false
+        stages: [pre-commit, post-checkout]
 
       - id: poetry-install
         name: Check & Install dependencies - AutoGPT Platform - Libs
         alias: poetry-install-platform-libs
-        entry: poetry -C autogpt_platform/autogpt_libs install
-        files: ^autogpt_platform/autogpt_libs/poetry\.lock$
-        types: [file]
+        entry: >
+          bash -c '
+          if [ -n "$PRE_COMMIT_FROM_REF" ]; then
+            git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
+          else
+            git diff --cached --name-only
+          fi | grep -qE "^autogpt_platform/autogpt_libs/poetry\.lock$" || exit 0;
+          poetry -C autogpt_platform/autogpt_libs install
+          '
+        always_run: true
         language: system
         pass_filenames: false
+        stages: [pre-commit, post-checkout]
+
+      - id: pnpm-install
+        name: Check & Install dependencies - AutoGPT Platform - Frontend
+        alias: pnpm-install-platform-frontend
+        entry: >
+          bash -c '
+          if [ -n "$PRE_COMMIT_FROM_REF" ]; then
+            git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
+          else
+            git diff --cached --name-only
+          fi | grep -qE "^autogpt_platform/frontend/pnpm-lock\.yaml$" || exit 0;
+          pnpm --prefix autogpt_platform/frontend install
+          '
+        always_run: true
+        language: system
+        pass_filenames: false
+        stages: [pre-commit, post-checkout]
 
       - id: poetry-install
         name: Check & Install dependencies - Classic - AutoGPT
         alias: poetry-install-classic-autogpt
-        entry: poetry -C classic/original_autogpt install
+        entry: >
+          bash -c '
+          if [ -n "$PRE_COMMIT_FROM_REF" ]; then
+            git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
+          else
+            git diff --cached --name-only
+          fi | grep -qE "^classic/(original_autogpt|forge)/poetry\.lock$" || exit 0;
+          poetry -C classic/original_autogpt install
+          '
         # include forge source (since it's a path dependency)
-        files: ^classic/(original_autogpt|forge)/poetry\.lock$
-        types: [file]
+        always_run: true
         language: system
         pass_filenames: false
+        stages: [pre-commit, post-checkout]
 
       - id: poetry-install
         name: Check & Install dependencies - Classic - Forge
         alias: poetry-install-classic-forge
-        entry: poetry -C classic/forge install
-        files: ^classic/forge/poetry\.lock$
-        types: [file]
+        entry: >
+          bash -c '
+          if [ -n "$PRE_COMMIT_FROM_REF" ]; then
+            git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
+          else
+            git diff --cached --name-only
+          fi | grep -qE "^classic/forge/poetry\.lock$" || exit 0;
+          poetry -C classic/forge install
+          '
+        always_run: true
         language: system
         pass_filenames: false
+        stages: [pre-commit, post-checkout]
 
       - id: poetry-install
         name: Check & Install dependencies - Classic - Benchmark
         alias: poetry-install-classic-benchmark
-        entry: poetry -C classic/benchmark install
-        files: ^classic/benchmark/poetry\.lock$
-        types: [file]
+        entry: >
+          bash -c '
+          if [ -n "$PRE_COMMIT_FROM_REF" ]; then
+            git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
+          else
+            git diff --cached --name-only
+          fi | grep -qE "^classic/benchmark/poetry\.lock$" || exit 0;
+          poetry -C classic/benchmark install
+          '
+        always_run: true
         language: system
         pass_filenames: false
+        stages: [pre-commit, post-checkout]
 
   - repo: local
     # For proper type checking, Prisma client must be up-to-date.
@@ -76,12 +141,54 @@ repos:
       - id: prisma-generate
         name: Prisma Generate - AutoGPT Platform - Backend
         alias: prisma-generate-platform-backend
-        entry: bash -c 'cd autogpt_platform/backend && poetry run prisma generate'
+        entry: >
+          bash -c '
+          if [ -n "$PRE_COMMIT_FROM_REF" ]; then
+            git diff --name-only "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF"
+          else
+            git diff --cached --name-only
+          fi | grep -qE "^autogpt_platform/((backend|autogpt_libs)/poetry\.lock|backend/schema\.prisma)$" || exit 0;
+          cd autogpt_platform/backend
+          && poetry run prisma generate
+          && poetry run gen-prisma-stub
+          '
         # include everything that triggers poetry install + the prisma schema
-        files: ^autogpt_platform/((backend|autogpt_libs)/poetry\.lock|backend/schema.prisma)$
-        types: [file]
+        always_run: true
         language: system
         pass_filenames: false
+        stages: [pre-commit, post-checkout]
+
+      - id: export-api-schema
+        name: Export API schema - AutoGPT Platform - Backend -> Frontend
+        alias: export-api-schema-platform
+        entry: >
+          bash -c '
+          cd autogpt_platform/backend
+          && poetry run export-api-schema --output ../frontend/src/app/api/openapi.json
+          && cd ../frontend
+          && pnpm prettier --write ./src/app/api/openapi.json
+          '
+        files: ^autogpt_platform/backend/
+        language: system
+        pass_filenames: false
+
+      - id: generate-api-client
+        name: Generate API client - AutoGPT Platform - Frontend
+        alias: generate-api-client-platform-frontend
+        entry: >
+          bash -c '
+          SCHEMA=autogpt_platform/frontend/src/app/api/openapi.json;
+          if [ -n "$PRE_COMMIT_FROM_REF" ]; then
+            git diff --quiet "$PRE_COMMIT_FROM_REF" "$PRE_COMMIT_TO_REF" -- "$SCHEMA" && exit 0
+          else
+            git diff --quiet HEAD -- "$SCHEMA" && exit 0
+          fi;
+          cd autogpt_platform/frontend && pnpm generate:api
+          '
+        always_run: true
+        language: system
+        pass_filenames: false
+        stages: [pre-commit, post-checkout]
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
     rev: v0.7.2

autogpt_platform/.gitignore

@@ -1,2 +1,3 @@
 *.ignore.*
-*.ign.*
+*.ign.*
+.application.logs

autogpt_platform/CLAUDE.md

@@ -45,6 +45,11 @@ AutoGPT Platform is a monorepo containing:
 - Backend/Frontend services use YAML anchors for consistent configuration
 - Supabase services (`db/docker/docker-compose.yml`) follow the same pattern
 
+### Branching Strategy
+
+- **`dev`** is the main development branch. All PRs should target `dev`.
+- **`master`** is the production branch. Only used for production releases.
+
 ### Creating Pull Requests
 
 - Create the PR against the `dev` branch of the repository.

autogpt_platform/autogpt_libs/poetry.lock

@@ -99,84 +99,101 @@ files = [
 
 [[package]]
 name = "cffi"
-version = "1.17.1"
+version = "2.0.0"
 description = "Foreign Function Interface for Python calling C code."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["main"]
 markers = "platform_python_implementation != \"PyPy\""
 files = [
-    {file = "cffi-1.17.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:df8b1c11f177bc2313ec4b2d46baec87a5f3e71fc8b45dab2ee7cae86d9aba14"},
-    {file = "cffi-1.17.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8f2cdc858323644ab277e9bb925ad72ae0e67f69e804f4898c070998d50b1a67"},
-    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:edae79245293e15384b51f88b00613ba9f7198016a5948b5dddf4917d4d26382"},
-    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:45398b671ac6d70e67da8e4224a065cec6a93541bb7aebe1b198a61b58c7b702"},
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 [package.dependencies]
@@ -413,62 +448,75 @@ toml = ["tomli ; python_full_version <= \"3.11.0a6\""]
 
 [[package]]
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 optional = false
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 [package.dependencies]
-cffi = {version = ">=1.14", markers = "platform_python_implementation != \"PyPy\""}
+cffi = {version = ">=2.0.0", markers = "python_full_version >= \"3.9.0\" and platform_python_implementation != \"PyPy\""}
+typing-extensions = {version = ">=4.13.2", markers = "python_full_version < \"3.11.0\""}
 
 [package.extras]
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+docs = ["sphinx (>=5.3.0)", "sphinx-inline-tabs", "sphinx-rtd-theme (>=3.0.0)"]
 docstest = ["pyenchant (>=3)", "readme-renderer (>=30.0)", "sphinxcontrib-spelling (>=7.3.1)"]
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-pep8test = ["check-sdist ; python_full_version >= \"3.8.0\"", "click (>=8.0.1)", "mypy (>=1.4)", "ruff (>=0.3.6)"]
+nox = ["nox[uv] (>=2024.4.15)"]
+pep8test = ["check-sdist", "click (>=8.0.1)", "mypy (>=1.14)", "ruff (>=0.11.11)"]
 sdist = ["build (>=1.0.0)"]
 ssh = ["bcrypt (>=3.1.5)"]
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+test = ["certifi (>=2024)", "cryptography-vectors (==46.0.5)", "pretend (>=0.7)", "pytest (>=7.4.0)", "pytest-benchmark (>=4.0)", "pytest-cov (>=2.10.1)", "pytest-xdist (>=3.5.0)"]
 test-randomorder = ["pytest-randomly"]
 
 [[package]]
@@ -522,24 +570,25 @@ tests = ["coverage", "coveralls", "dill", "mock", "nose"]
 
 [[package]]
 name = "fastapi"
-version = "0.128.0"
+version = "0.128.7"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
 annotated-doc = ">=0.0.2"
 pydantic = ">=2.7.0"
-starlette = ">=0.40.0,<0.51.0"
+starlette = ">=0.40.0,<1.0.0"
 typing-extensions = ">=4.8.0"
+typing-inspection = ">=0.4.2"
 
 [package.extras]
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+all = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.8)", "httpx (>=0.23.0,<1.0.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=3.1.5)", "orjson (>=3.9.3)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "pyyaml (>=5.3.1)", "ujson (>=5.8.0)", "uvicorn[standard] (>=0.12.0)"]
 standard = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.8)", "httpx (>=0.23.0,<1.0.0)", "jinja2 (>=3.1.5)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
 standard-no-fastapi-cloud-cli = ["email-validator (>=2.0.0)", "fastapi-cli[standard-no-fastapi-cloud-cli] (>=0.0.8)", "httpx (>=0.23.0,<1.0.0)", "jinja2 (>=3.1.5)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
 
@@ -1014,14 +1063,14 @@ urllib3 = ">=1.26.0,<3"
 
 [[package]]
 name = "launchdarkly-server-sdk"
-version = "9.14.1"
+version = "9.15.0"
 description = "LaunchDarkly SDK for Python"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
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+    {file = "launchdarkly_server_sdk-9.15.0-py3-none-any.whl", hash = "sha256:c267e29bfa3fb5e2a06a208448ada6ed5557a2924979b8d79c970b45d227c668"},
+    {file = "launchdarkly_server_sdk-9.15.0.tar.gz", hash = "sha256:f31441b74bc1a69c381db57c33116509e407a2612628ad6dff0a7dbb39d5020b"},
 ]
 
 [package.dependencies]
@@ -1430,14 +1479,14 @@ testing = ["coverage", "pytest", "pytest-benchmark"]
 
 [[package]]
 name = "postgrest"
-version = "2.27.2"
+version = "2.28.0"
 description = "PostgREST client for Python. This library provides an ORM interface to PostgREST."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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-    {file = "postgrest-2.27.2.tar.gz", hash = "sha256:55407d530b5af3d64e883a71fec1f345d369958f723ce4a8ab0b7d169e313242"},
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+    {file = "postgrest-2.28.0.tar.gz", hash = "sha256:c36b38646d25ea4255321d3d924ce70f8d20ec7799cb42c1221d6a818d4f6515"},
 ]
 
 [package.dependencies]
@@ -1650,7 +1699,7 @@ description = "C parser in Python"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "platform_python_implementation != \"PyPy\""
+markers = "platform_python_implementation != \"PyPy\" and implementation_name != \"PyPy\""
 files = [
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@@ -1972,14 +2021,14 @@ files = [
 
 [[package]]
 name = "pyright"
-version = "1.1.404"
+version = "1.1.408"
 description = "Command line wrapper for pyright"
 optional = false
 python-versions = ">=3.7"
 groups = ["dev"]
 files = [
-    {file = "pyright-1.1.404-py3-none-any.whl", hash = "sha256:c7b7ff1fdb7219c643079e4c3e7d4125f0dafcc19d253b47e898d130ea426419"},
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+    {file = "pyright-1.1.408-py3-none-any.whl", hash = "sha256:090b32865f4fdb1e0e6cd82bf5618480d48eecd2eb2e70f960982a3d9a4c17c1"},
+    {file = "pyright-1.1.408.tar.gz", hash = "sha256:f28f2321f96852fa50b5829ea492f6adb0e6954568d1caa3f3af3a5f555eb684"},
 ]
 
 [package.dependencies]
@@ -2111,19 +2160,20 @@ dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "requests
 
 [[package]]
 name = "pytest-asyncio"
-version = "1.1.0"
+version = "1.3.0"
 description = "Pytest support for asyncio"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["dev"]
 files = [
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+    {file = "pytest_asyncio-1.3.0.tar.gz", hash = "sha256:d7f52f36d231b80ee124cd216ffb19369aa168fc10095013c6b014a34d3ee9e5"},
 ]
 
 [package.dependencies]
 backports-asyncio-runner = {version = ">=1.1,<2", markers = "python_version < \"3.11\""}
-pytest = ">=8.2,<9"
+pytest = ">=8.2,<10"
+typing-extensions = {version = ">=4.12", markers = "python_version < \"3.13\""}
 
 [package.extras]
 docs = ["sphinx (>=5.3)", "sphinx-rtd-theme (>=1)"]
@@ -2131,34 +2181,34 @@ testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
 
 [[package]]
 name = "pytest-cov"
-version = "6.2.1"
+version = "7.0.0"
 description = "Pytest plugin for measuring coverage."
 optional = false
 python-versions = ">=3.9"
 groups = ["dev"]
 files = [
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+    {file = "pytest_cov-7.0.0.tar.gz", hash = "sha256:33c97eda2e049a0c5298e91f519302a1334c26ac65c1a483d6206fd458361af1"},
 ]
 
 [package.dependencies]
-coverage = {version = ">=7.5", extras = ["toml"]}
+coverage = {version = ">=7.10.6", extras = ["toml"]}
 pluggy = ">=1.2"
-pytest = ">=6.2.5"
+pytest = ">=7"
 
 [package.extras]
-testing = ["fields", "hunter", "process-tests", "pytest-xdist", "virtualenv"]
+testing = ["process-tests", "pytest-xdist", "virtualenv"]
 
 [[package]]
 name = "pytest-mock"
-version = "3.14.1"
+version = "3.15.1"
 description = "Thin-wrapper around the mock package for easier use with pytest"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["dev"]
 files = [
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+    {file = "pytest_mock-3.15.1-py3-none-any.whl", hash = "sha256:0a25e2eb88fe5168d535041d09a4529a188176ae608a6d249ee65abc0949630d"},
+    {file = "pytest_mock-3.15.1.tar.gz", hash = "sha256:1849a238f6f396da19762269de72cb1814ab44416fa73a8686deac10b0d87a0f"},
 ]
 
 [package.dependencies]
@@ -2199,14 +2249,14 @@ cli = ["click (>=5.0)"]
 
 [[package]]
 name = "realtime"
-version = "2.27.2"
+version = "2.28.0"
 description = ""
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "realtime-2.27.2-py3-none-any.whl", hash = "sha256:34a9cbb26a274e707e8fc9e3ee0a66de944beac0fe604dc336d1e985db2c830f"},
-    {file = "realtime-2.27.2.tar.gz", hash = "sha256:b960a90294d2cea1b3f1275ecb89204304728e08fff1c393cc1b3150739556b3"},
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+    {file = "realtime-2.28.0.tar.gz", hash = "sha256:d18cedcebd6a8f22fcd509bc767f639761eb218b7b2b6f14fc4205b6259b50fc"},
 ]
 
 [package.dependencies]
@@ -2292,31 +2342,30 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "ruff"
-version = "0.12.11"
+version = "0.15.0"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 groups = ["dev"]
 files = [
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+    {file = "ruff-0.15.0.tar.gz", hash = "sha256:6bdea47cdbea30d40f8f8d7d69c0854ba7c15420ec75a26f463290949d7f7e9a"},
 ]
 
 [[package]]
@@ -2388,14 +2437,14 @@ full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart
 
 [[package]]
 name = "storage3"
-version = "2.27.2"
+version = "2.28.0"
 description = "Supabase Storage client for Python."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "storage3-2.27.2-py3-none-any.whl", hash = "sha256:e6f16e7a260729e7b1f46e9bf61746805a02e30f5e419ee1291007c432e3ec63"},
-    {file = "storage3-2.27.2.tar.gz", hash = "sha256:cb4807b7f86b4bb1272ac6fdd2f3cfd8ba577297046fa5f88557425200275af5"},
+    {file = "storage3-2.28.0-py3-none-any.whl", hash = "sha256:ecb50efd2ac71dabbdf97e99ad346eafa630c4c627a8e5a138ceb5fbbadae716"},
+    {file = "storage3-2.28.0.tar.gz", hash = "sha256:bc1d008aff67de7a0f2bd867baee7aadbcdb6f78f5a310b4f7a38e8c13c19865"},
 ]
 
 [package.dependencies]
@@ -2439,35 +2488,35 @@ python-dateutil = ">=2.6.0"
 
 [[package]]
 name = "supabase"
-version = "2.27.2"
+version = "2.28.0"
 description = "Supabase client for Python."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase-2.27.2-py3-none-any.whl", hash = "sha256:d4dce00b3a418ee578017ec577c0e5be47a9a636355009c76f20ed2faa15bc54"},
-    {file = "supabase-2.27.2.tar.gz", hash = "sha256:2aed40e4f3454438822442a1e94a47be6694c2c70392e7ae99b51a226d4293f7"},
+    {file = "supabase-2.28.0-py3-none-any.whl", hash = "sha256:42776971c7d0ccca16034df1ab96a31c50228eb1eb19da4249ad2f756fc20272"},
+    {file = "supabase-2.28.0.tar.gz", hash = "sha256:aea299aaab2a2eed3c57e0be7fc035c6807214194cce795a3575add20268ece1"},
 ]
 
 [package.dependencies]
 httpx = ">=0.26,<0.29"
-postgrest = "2.27.2"
-realtime = "2.27.2"
-storage3 = "2.27.2"
-supabase-auth = "2.27.2"
-supabase-functions = "2.27.2"
+postgrest = "2.28.0"
+realtime = "2.28.0"
+storage3 = "2.28.0"
+supabase-auth = "2.28.0"
+supabase-functions = "2.28.0"
 yarl = ">=1.22.0"
 
 [[package]]
 name = "supabase-auth"
-version = "2.27.2"
+version = "2.28.0"
 description = "Python Client Library for Supabase Auth"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase_auth-2.27.2-py3-none-any.whl", hash = "sha256:78ec25b11314d0a9527a7205f3b1c72560dccdc11b38392f80297ef98664ee91"},
-    {file = "supabase_auth-2.27.2.tar.gz", hash = "sha256:0f5bcc79b3677cb42e9d321f3c559070cfa40d6a29a67672cc8382fb7dc2fe97"},
+    {file = "supabase_auth-2.28.0-py3-none-any.whl", hash = "sha256:2ac85026cc285054c7fa6d41924f3a333e9ec298c013e5b5e1754039ba7caec9"},
+    {file = "supabase_auth-2.28.0.tar.gz", hash = "sha256:2bb8f18ff39934e44b28f10918db965659f3735cd6fbfcc022fe0b82dbf8233e"},
 ]
 
 [package.dependencies]
@@ -2477,14 +2526,14 @@ pyjwt = {version = ">=2.10.1", extras = ["crypto"]}
 
 [[package]]
 name = "supabase-functions"
-version = "2.27.2"
+version = "2.28.0"
 description = "Library for Supabase Functions"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase_functions-2.27.2-py3-none-any.whl", hash = "sha256:db480efc669d0bca07605b9b6f167312af43121adcc842a111f79bea416ef754"},
-    {file = "supabase_functions-2.27.2.tar.gz", hash = "sha256:d0c8266207a94371cb3fd35ad3c7f025b78a97cf026861e04ccd35ac1775f80b"},
+    {file = "supabase_functions-2.28.0-py3-none-any.whl", hash = "sha256:30bf2d586f8df285faf0621bb5d5bb3ec3157234fc820553ca156f009475e4ae"},
+    {file = "supabase_functions-2.28.0.tar.gz", hash = "sha256:db3dddfc37aca5858819eb461130968473bd8c75bd284581013958526dac718b"},
 ]
 
 [package.dependencies]
@@ -2863,4 +2912,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<4.0"
-content-hash = "5f15a9c9381c9a374f3d18e087c23b1f1ba8cce192d6f67463a3e3a7a18fee44"
+content-hash = "9619cae908ad38fa2c48016a58bcf4241f6f5793aa0e6cc140276e91c433cbbb"

autogpt_platform/autogpt_libs/pyproject.toml

@@ -9,25 +9,25 @@ packages = [{ include = "autogpt_libs" }]
 [tool.poetry.dependencies]
 python = ">=3.10,<4.0"
 colorama = "^0.4.6"
-cryptography = "^45.0"
+cryptography = "^46.0"
 expiringdict = "^1.2.2"
-fastapi = "^0.128.0"
+fastapi = "^0.128.7"
 google-cloud-logging = "^3.13.0"
-launchdarkly-server-sdk = "^9.14.1"
+launchdarkly-server-sdk = "^9.15.0"
 pydantic = "^2.12.5"
 pydantic-settings = "^2.12.0"
 pyjwt = { version = "^2.11.0", extras = ["crypto"] }
 redis = "^6.2.0"
-supabase = "^2.27.2"
+supabase = "^2.28.0"
 uvicorn = "^0.40.0"
 
 [tool.poetry.group.dev.dependencies]
-pyright = "^1.1.404"
+pyright = "^1.1.408"
 pytest = "^8.4.1"
-pytest-asyncio = "^1.1.0"
-pytest-mock = "^3.14.1"
-pytest-cov = "^6.2.1"
-ruff = "^0.12.11"
+pytest-asyncio = "^1.3.0"
+pytest-mock = "^3.15.1"
+pytest-cov = "^7.0.0"
+ruff = "^0.15.0"
 
 [build-system]
 requires = ["poetry-core"]

autogpt_platform/backend/.env.default

@@ -104,6 +104,12 @@ TWITTER_CLIENT_SECRET=
 # Make a new workspace for your OAuth APP -- trust me
 # https://linear.app/settings/api/applications/new
 # Callback URL: http://localhost:3000/auth/integrations/oauth_callback
+LINEAR_API_KEY=
+# Linear project and team IDs for the feature request tracker.
+# Find these in your Linear workspace URL: linear.app/<workspace>/project/<project-id>
+# and in team settings. Used by the chat copilot to file and search feature requests.
+LINEAR_FEATURE_REQUEST_PROJECT_ID=
+LINEAR_FEATURE_REQUEST_TEAM_ID=
 LINEAR_CLIENT_ID=
 LINEAR_CLIENT_SECRET=
 
@@ -184,5 +190,8 @@ ZEROBOUNCE_API_KEY=
 POSTHOG_API_KEY=
 POSTHOG_HOST=https://eu.i.posthog.com
 
+# Tally Form Integration (pre-populate business understanding on signup)
+TALLY_API_KEY=
+
 # Other Services
 AUTOMOD_API_KEY=

autogpt_platform/backend/Dockerfile

@@ -1,3 +1,5 @@
+# ============================ DEPENDENCY BUILDER ============================ #
+
 FROM debian:13-slim AS builder
 
 # Set environment variables
@@ -51,60 +53,106 @@ COPY autogpt_platform/backend/backend/data/partial_types.py ./backend/data/parti
 COPY autogpt_platform/backend/gen_prisma_types_stub.py ./
 RUN poetry run prisma generate && poetry run gen-prisma-stub
 
-FROM debian:13-slim AS server_dependencies
+# =============================== DB MIGRATOR =============================== #
+
+# Lightweight migrate stage - only needs Prisma CLI, not full Python environment
+FROM debian:13-slim AS migrate
+
+WORKDIR /app/autogpt_platform/backend
+
+ENV DEBIAN_FRONTEND=noninteractive
+
+# Install only what's needed for prisma migrate: Node.js and minimal Python for prisma-python
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    python3.13 \
+    python3-pip \
+    ca-certificates \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy Node.js from builder (needed for Prisma CLI)
+COPY --from=builder /usr/bin/node /usr/bin/node
+COPY --from=builder /usr/lib/node_modules /usr/lib/node_modules
+COPY --from=builder /usr/bin/npm /usr/bin/npm
+
+# Copy Prisma binaries
+COPY --from=builder /root/.cache/prisma-python/binaries /root/.cache/prisma-python/binaries
+
+# Install prisma-client-py directly (much smaller than copying full venv)
+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/migrations ./migrations
+
+# ============================== BACKEND SERVER ============================== #
+
+FROM debian:13-slim AS server
 
 WORKDIR /app
 
-ENV POETRY_HOME=/opt/poetry \
-    POETRY_NO_INTERACTION=1 \
-    POETRY_VIRTUALENVS_CREATE=true \
-    POETRY_VIRTUALENVS_IN_PROJECT=true \
-    DEBIAN_FRONTEND=noninteractive
-ENV PATH=/opt/poetry/bin:$PATH
+ENV DEBIAN_FRONTEND=noninteractive
 
-# Install Python, FFmpeg, and ImageMagick (required for video processing blocks)
-RUN apt-get update && apt-get install -y \
+# Install Python, FFmpeg, ImageMagick, and CLI tools for agent use.
+# bubblewrap provides OS-level sandbox (whitelist-only FS + no network)
+# for the bash_exec MCP tool (fallback when E2B is not configured).
+# Using --no-install-recommends saves ~650MB by skipping unnecessary deps like llvm, mesa, etc.
+RUN apt-get update && apt-get install -y --no-install-recommends \
     python3.13 \
     python3-pip \
     ffmpeg \
     imagemagick \
+    jq \
+    ripgrep \
+    tree \
+    bubblewrap \
     && rm -rf /var/lib/apt/lists/*
 
-# Copy only necessary files from builder
-COPY --from=builder /app /app
+# Copy poetry (build-time only, for `poetry install --only-root` to create entry points)
 COPY --from=builder /usr/local/lib/python3* /usr/local/lib/python3*
 COPY --from=builder /usr/local/bin/poetry /usr/local/bin/poetry
-# Copy Node.js installation for Prisma
+# Copy Node.js installation for Prisma and agent-browser.
+# npm/npx are symlinks in the builder (-> ../lib/node_modules/npm/bin/*-cli.js);
+# COPY resolves them to regular files, breaking require() paths.  Recreate as
+# proper symlinks so npm/npx can find their modules.
 COPY --from=builder /usr/bin/node /usr/bin/node
 COPY --from=builder /usr/lib/node_modules /usr/lib/node_modules
-COPY --from=builder /usr/bin/npm /usr/bin/npm
-COPY --from=builder /usr/bin/npx /usr/bin/npx
+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
 
-ENV PATH="/app/autogpt_platform/backend/.venv/bin:$PATH"
-
-RUN mkdir -p /app/autogpt_platform/autogpt_libs
-RUN mkdir -p /app/autogpt_platform/backend
-
-COPY autogpt_platform/autogpt_libs /app/autogpt_platform/autogpt_libs
-
-COPY autogpt_platform/backend/poetry.lock autogpt_platform/backend/pyproject.toml /app/autogpt_platform/backend/
+# Install agent-browser (Copilot browser tool) + Chromium runtime dependencies.
+# These are the runtime libraries Chromium/Playwright needs on Debian 13 (trixie).
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    libnss3 libnspr4 libatk1.0-0 libatk-bridge2.0-0 libcups2 libdrm2 \
+    libdbus-1-3 libxkbcommon0 libatspi2.0-0t64 libxcomposite1 libxdamage1 \
+    libxfixes3 libxrandr2 libgbm1 libasound2t64 libpango-1.0-0 libcairo2 \
+    libx11-6 libx11-xcb1 libxcb1 libxext6 libglib2.0-0t64 \
+    fonts-liberation libfontconfig1 \
+    && rm -rf /var/lib/apt/lists/* \
+    && npm install -g agent-browser \
+    && agent-browser install \
+    && rm -rf /tmp/* /root/.npm
 
 WORKDIR /app/autogpt_platform/backend
 
-FROM server_dependencies AS migrate
+# Copy only the .venv from builder (not the entire /app directory)
+# The .venv includes the generated Prisma client
+COPY --from=builder /app/autogpt_platform/backend/.venv ./.venv
+ENV PATH="/app/autogpt_platform/backend/.venv/bin:$PATH"
 
-# Migration stage only needs schema and migrations - much lighter than full backend
-COPY autogpt_platform/backend/schema.prisma /app/autogpt_platform/backend/
-COPY autogpt_platform/backend/backend/data/partial_types.py /app/autogpt_platform/backend/backend/data/partial_types.py
-COPY autogpt_platform/backend/migrations /app/autogpt_platform/backend/migrations
+# Copy dependency files + autogpt_libs (path dependency)
+COPY autogpt_platform/autogpt_libs /app/autogpt_platform/autogpt_libs
+COPY autogpt_platform/backend/poetry.lock autogpt_platform/backend/pyproject.toml ./
 
-FROM server_dependencies AS server
-
-COPY autogpt_platform/backend /app/autogpt_platform/backend
+# Copy backend code + docs (for Copilot docs search)
+COPY autogpt_platform/backend ./
 COPY docs /app/docs
-RUN poetry install --no-ansi --only-root
+# Install the project package to create entry point scripts in .venv/bin/
+# (e.g., rest, executor, ws, db, scheduler, notification - see [tool.poetry.scripts])
+RUN POETRY_VIRTUALENVS_CREATE=true POETRY_VIRTUALENVS_IN_PROJECT=true \
+    poetry install --no-ansi --only-root
 
 ENV PORT=8000
 
-CMD ["poetry", "run", "rest"]
+CMD ["rest"]

autogpt_platform/backend/backend/api/conftest.py

@@ -1,4 +1,9 @@
-"""Common test fixtures for server tests."""
+"""Common test fixtures for server tests.
+
+Note: Common fixtures like test_user_id, admin_user_id, target_user_id,
+setup_test_user, and setup_admin_user are defined in the parent conftest.py
+(backend/conftest.py) and are available here automatically.
+"""
 
 import pytest
 from pytest_snapshot.plugin import Snapshot
@@ -11,54 +16,6 @@ def configured_snapshot(snapshot: Snapshot) -> Snapshot:
     return snapshot
 
 
-@pytest.fixture
-def test_user_id() -> str:
-    """Test user ID fixture."""
-    return "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
-
-
-@pytest.fixture
-def admin_user_id() -> str:
-    """Admin user ID fixture."""
-    return "4e53486c-cf57-477e-ba2a-cb02dc828e1b"
-
-
-@pytest.fixture
-def target_user_id() -> str:
-    """Target user ID fixture."""
-    return "5e53486c-cf57-477e-ba2a-cb02dc828e1c"
-
-
-@pytest.fixture
-async def setup_test_user(test_user_id):
-    """Create test user in database before tests."""
-    from backend.data.user import get_or_create_user
-
-    # Create the test user in the database using JWT token format
-    user_data = {
-        "sub": test_user_id,
-        "email": "test@example.com",
-        "user_metadata": {"name": "Test User"},
-    }
-    await get_or_create_user(user_data)
-    return test_user_id
-
-
-@pytest.fixture
-async def setup_admin_user(admin_user_id):
-    """Create admin user in database before tests."""
-    from backend.data.user import get_or_create_user
-
-    # Create the admin user in the database using JWT token format
-    user_data = {
-        "sub": admin_user_id,
-        "email": "test-admin@example.com",
-        "user_metadata": {"name": "Test Admin"},
-    }
-    await get_or_create_user(user_data)
-    return admin_user_id
-
-
 @pytest.fixture
 def mock_jwt_user(test_user_id):
     """Provide mock JWT payload for regular user testing."""

autogpt_platform/backend/backend/api/external/middleware.py

@@ -88,20 +88,23 @@ async def require_auth(
     )
 
 
-def require_permission(permission: APIKeyPermission):
+def require_permission(*permissions: APIKeyPermission):
     """
-    Dependency function for checking specific permissions
+    Dependency function for checking required permissions.
+    All listed permissions must be present.
     (works with API keys and OAuth tokens)
     """
 
-    async def check_permission(
+    async def check_permissions(
         auth: APIAuthorizationInfo = Security(require_auth),
     ) -> APIAuthorizationInfo:
-        if permission not in auth.scopes:
+        missing = [p for p in permissions if p not in auth.scopes]
+        if missing:
             raise HTTPException(
                 status_code=status.HTTP_403_FORBIDDEN,
-                detail=f"Missing required permission: {permission.value}",
+                detail=f"Missing required permission(s): "
+                f"{', '.join(p.value for p in missing)}",
             )
         return auth
 
-    return check_permission
+    return check_permissions

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
@@ -9,15 +9,17 @@ 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.data.block
-from backend.api.external.middleware import require_permission
+import backend.blocks
+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
 from backend.data.auth.base import APIAuthorizationInfo
 from backend.data.block import BlockInput, CompletedBlockOutput
 from backend.executor.utils import add_graph_execution
+from backend.integrations.webhooks.graph_lifecycle_hooks import on_graph_activate
 from backend.util.settings import Settings
 
 from .integrations import integrations_router
@@ -67,7 +69,7 @@ async def get_user_info(
     dependencies=[Security(require_permission(APIKeyPermission.READ_BLOCK))],
 )
 async def get_graph_blocks() -> Sequence[dict[Any, Any]]:
-    blocks = [block() for block in backend.data.block.get_blocks().values()]
+    blocks = [block() for block in backend.blocks.get_blocks().values()]
     return [b.to_dict() for b in blocks if not b.disabled]
 
 
@@ -83,7 +85,7 @@ async def execute_graph_block(
         require_permission(APIKeyPermission.EXECUTE_BLOCK)
     ),
 ) -> CompletedBlockOutput:
-    obj = backend.data.block.get_block(block_id)
+    obj = backend.blocks.get_block(block_id)
     if not obj:
         raise HTTPException(status_code=404, detail=f"Block #{block_id} not found.")
     if obj.disabled:
@@ -95,6 +97,43 @@ async def execute_graph_block(
     return output
 
 
+@v1_router.post(
+    path="/graphs",
+    tags=["graphs"],
+    status_code=201,
+    dependencies=[
+        Security(
+            require_permission(
+                APIKeyPermission.WRITE_GRAPH, APIKeyPermission.WRITE_LIBRARY
+            )
+        )
+    ],
+)
+async def create_graph(
+    graph: graph_db.Graph,
+    auth: APIAuthorizationInfo = Security(
+        require_permission(APIKeyPermission.WRITE_GRAPH, APIKeyPermission.WRITE_LIBRARY)
+    ),
+) -> graph_db.GraphModel:
+    """
+    Create a new agent graph.
+
+    The graph will be validated and assigned a new ID.
+    It is automatically added to the user's library.
+    """
+    from backend.api.features.library import db as library_db
+
+    graph_model = graph_db.make_graph_model(graph, auth.user_id)
+    graph_model.reassign_ids(user_id=auth.user_id, reassign_graph_id=True)
+    graph_model.validate_graph(for_run=False)
+
+    await graph_db.create_graph(graph_model, user_id=auth.user_id)
+    await library_db.create_library_agent(graph_model, auth.user_id)
+    activated_graph = await on_graph_activate(graph_model, user_id=auth.user_id)
+
+    return activated_graph
+
+
 @v1_router.post(
     path="/graphs/{graph_id}/execute/{graph_version}",
     tags=["graphs"],
@@ -192,13 +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,
@@ -240,7 +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(
@@ -268,13 +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:
@@ -310,7 +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/external/v1/tools.py

@@ -15,9 +15,9 @@ from prisma.enums import APIKeyPermission
 from pydantic import BaseModel, Field
 
 from backend.api.external.middleware import require_permission
-from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.tools import find_agent_tool, run_agent_tool
-from backend.api.features.chat.tools.models import ToolResponseBase
+from backend.copilot.model import ChatSession
+from backend.copilot.tools import find_agent_tool, run_agent_tool
+from backend.copilot.tools.models import ToolResponseBase
 from backend.data.auth.base import APIAuthorizationInfo
 
 logger = logging.getLogger(__name__)

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

@@ -1,20 +1,26 @@
 import logging
 from dataclasses import dataclass
-from datetime import datetime, timedelta, timezone
 from difflib import SequenceMatcher
-from typing import Sequence
+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
-import backend.data.block
+from backend.api.features.store.hybrid_search import unified_hybrid_search
 from backend.blocks import load_all_blocks
+from backend.blocks._base import (
+    AnyBlockSchema,
+    BlockCategory,
+    BlockInfo,
+    BlockSchema,
+    BlockType,
+)
 from backend.blocks.llm import LlmModel
-from backend.data.block import AnyBlockSchema, BlockCategory, BlockInfo, BlockSchema
-from backend.data.db import query_raw_with_schema
 from backend.integrations.providers import ProviderName
 from backend.util.cache import cached
 from backend.util.models import Pagination
@@ -22,7 +28,7 @@ from backend.util.models import Pagination
 from .model import (
     BlockCategoryResponse,
     BlockResponse,
-    BlockType,
+    BlockTypeFilter,
     CountResponse,
     FilterType,
     Provider,
@@ -37,6 +43,16 @@ MAX_LIBRARY_AGENT_RESULTS = 100
 MAX_MARKETPLACE_AGENT_RESULTS = 100
 MIN_SCORE_FOR_FILTERED_RESULTS = 10.0
 
+# Boost blocks over marketplace agents in search results
+BLOCK_SCORE_BOOST = 50.0
+
+# Block IDs to exclude from search results
+EXCLUDED_BLOCK_IDS = frozenset(
+    {
+        "e189baac-8c20-45a1-94a7-55177ea42565",  # AgentExecutorBlock
+    }
+)
+
 SearchResultItem = BlockInfo | library_model.LibraryAgent | store_model.StoreAgent
 
 
@@ -59,8 +75,8 @@ def get_block_categories(category_blocks: int = 3) -> list[BlockCategoryResponse
 
     for block_type in load_all_blocks().values():
         block: AnyBlockSchema = block_type()
-        # Skip disabled blocks
-        if block.disabled:
+        # Skip disabled and excluded blocks
+        if block.disabled or block.id in EXCLUDED_BLOCK_IDS:
             continue
         # Skip blocks that don't have categories (all should have at least one)
         if not block.categories:
@@ -88,7 +104,7 @@ def get_block_categories(category_blocks: int = 3) -> list[BlockCategoryResponse
 def get_blocks(
     *,
     category: str | None = None,
-    type: BlockType | None = None,
+    type: BlockTypeFilter | None = None,
     provider: ProviderName | None = None,
     page: int = 1,
     page_size: int = 50,
@@ -111,6 +127,9 @@ def get_blocks(
         # Skip disabled blocks
         if block.disabled:
             continue
+        # Skip excluded blocks
+        if block.id in EXCLUDED_BLOCK_IDS:
+            continue
         # Skip blocks that don't match the category
         if category and category not in {c.name.lower() for c in block.categories}:
             continue
@@ -250,14 +269,25 @@ async def _build_cached_search_results(
         "my_agents": 0,
     }
 
-    block_results, block_total, integration_total = _collect_block_results(
-        normalized_query=normalized_query,
-        include_blocks=include_blocks,
-        include_integrations=include_integrations,
-    )
-    scored_items.extend(block_results)
-    total_items["blocks"] = block_total
-    total_items["integrations"] = integration_total
+    # 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(
+            query=search_query,
+            include_blocks=include_blocks,
+            include_integrations=include_integrations,
+        )
+        scored_items.extend(block_results)
+        total_items["blocks"] = block_total
+        total_items["integrations"] = integration_total
+    elif include_blocks or include_integrations:
+        # No query - list all blocks using in-memory approach
+        block_results, block_total, integration_total = _collect_block_results(
+            include_blocks=include_blocks,
+            include_integrations=include_integrations,
+        )
+        scored_items.extend(block_results)
+        total_items["blocks"] = block_total
+        total_items["integrations"] = integration_total
 
     if include_library_agents:
         library_response = await library_db.list_library_agents(
@@ -302,10 +332,14 @@ async def _build_cached_search_results(
 
 def _collect_block_results(
     *,
-    normalized_query: str,
     include_blocks: bool,
     include_integrations: bool,
 ) -> tuple[list[_ScoredItem], int, int]:
+    """
+    Collect all blocks for listing (no search query).
+
+    All blocks get BLOCK_SCORE_BOOST to prioritize them over marketplace agents.
+    """
     results: list[_ScoredItem] = []
     block_count = 0
     integration_count = 0
@@ -318,6 +352,10 @@ def _collect_block_results(
         if block.disabled:
             continue
 
+        # Skip excluded blocks
+        if block.id in EXCLUDED_BLOCK_IDS:
+            continue
+
         block_info = block.get_info()
         credentials = list(block.input_schema.get_credentials_fields().values())
         is_integration = len(credentials) > 0
@@ -327,10 +365,6 @@ def _collect_block_results(
         if not is_integration and not include_blocks:
             continue
 
-        score = _score_block(block, block_info, normalized_query)
-        if not _should_include_item(score, normalized_query):
-            continue
-
         filter_type: FilterType = "integrations" if is_integration else "blocks"
         if is_integration:
             integration_count += 1
@@ -341,8 +375,122 @@ def _collect_block_results(
             _ScoredItem(
                 item=block_info,
                 filter_type=filter_type,
-                score=score,
-                sort_key=_get_item_name(block_info),
+                score=BLOCK_SCORE_BOOST,
+                sort_key=block_info.name.lower(),
+            )
+        )
+
+    return results, block_count, integration_count
+
+
+async def _hybrid_search_blocks(
+    *,
+    query: str,
+    include_blocks: bool,
+    include_integrations: bool,
+) -> tuple[list[_ScoredItem], int, int]:
+    """
+    Search blocks using hybrid search with builder-specific filtering.
+
+    Uses unified_hybrid_search for semantic + lexical search, then applies
+    post-filtering for block/integration types and scoring adjustments.
+
+    Scoring:
+        - Base: hybrid relevance score (0-1) scaled to 0-100, plus BLOCK_SCORE_BOOST
+          to prioritize blocks over marketplace agents in combined results
+        - +30 for exact name match, +15 for prefix name match
+        - +20 if the block has an LlmModel field and the query matches an LLM model name
+
+    Args:
+        query: The search query string
+        include_blocks: Whether to include regular blocks
+        include_integrations: Whether to include integration blocks
+
+    Returns:
+        Tuple of (scored_items, block_count, integration_count)
+    """
+    results: list[_ScoredItem] = []
+    block_count = 0
+    integration_count = 0
+
+    if not include_blocks and not include_integrations:
+        return results, block_count, integration_count
+
+    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,
+    )
+
+    # Load all blocks for getting BlockInfo
+    all_blocks = load_all_blocks()
+
+    for result in search_results:
+        block_id = result["content_id"]
+
+        # Skip excluded blocks
+        if block_id in EXCLUDED_BLOCK_IDS:
+            continue
+
+        metadata = result.get("metadata", {})
+        hybrid_score = result.get("relevance", 0.0)
+
+        # Get the actual block class
+        if block_id not in all_blocks:
+            continue
+
+        block_cls = all_blocks[block_id]
+        block: AnyBlockSchema = block_cls()
+
+        if block.disabled:
+            continue
+
+        # Check block/integration filter using metadata
+        is_integration = metadata.get("is_integration", False)
+
+        if is_integration and not include_integrations:
+            continue
+        if not is_integration and not include_blocks:
+            continue
+
+        # Get block info
+        block_info = block.get_info()
+
+        # Calculate final score: scale hybrid score and add builder-specific bonuses
+        # Hybrid scores are 0-1, builder scores were 0-200+
+        # Add BLOCK_SCORE_BOOST to prioritize blocks over marketplace agents
+        final_score = hybrid_score * 100 + BLOCK_SCORE_BOOST
+
+        # Add LLM model match bonus
+        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
+
+        # 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,
             )
         )
 
@@ -467,6 +615,8 @@ async def _get_static_counts():
         block: AnyBlockSchema = block_type()
         if block.disabled:
             continue
+        if block.id in EXCLUDED_BLOCK_IDS:
+            continue
 
         all_blocks += 1
 
@@ -493,47 +643,25 @@ async def _get_static_counts():
     }
 
 
+def _contains_type(annotation: Any, target: type) -> bool:
+    """Check if an annotation is or contains the target type (handles Optional/Union/Annotated)."""
+    if annotation is target:
+        return True
+    origin = get_origin(annotation)
+    if origin is None:
+        return False
+    return any(_contains_type(arg, target) for arg in get_args(annotation))
+
+
 def _matches_llm_model(schema_cls: type[BlockSchema], query: str) -> bool:
     for field in schema_cls.model_fields.values():
-        if field.annotation == LlmModel:
+        if _contains_type(field.annotation, LlmModel):
             # Check if query matches any value in llm_models
             if any(query in name for name in llm_models):
                 return True
     return False
 
 
-def _score_block(
-    block: AnyBlockSchema,
-    block_info: BlockInfo,
-    normalized_query: str,
-) -> float:
-    if not normalized_query:
-        return 0.0
-
-    name = block_info.name.lower()
-    description = block_info.description.lower()
-    score = _score_primary_fields(name, description, normalized_query)
-
-    category_text = " ".join(
-        category.get("category", "").lower() for category in block_info.categories
-    )
-    score += _score_additional_field(category_text, normalized_query, 12, 6)
-
-    credentials_info = block.input_schema.get_credentials_fields_info().values()
-    provider_names = [
-        provider.value.lower()
-        for info in credentials_info
-        for provider in info.provider
-    ]
-    provider_text = " ".join(provider_names)
-    score += _score_additional_field(provider_text, normalized_query, 15, 6)
-
-    if _matches_llm_model(block.input_schema, normalized_query):
-        score += 20
-
-    return score
-
-
 def _score_library_agent(
     agent: library_model.LibraryAgent,
     normalized_query: str,
@@ -640,45 +768,32 @@ def _get_all_providers() -> dict[ProviderName, Provider]:
     return providers
 
 
-@cached(ttl_seconds=3600)
+@cached(ttl_seconds=3600, shared_cache=True)
 async def get_suggested_blocks(count: int = 5) -> list[BlockInfo]:
-    suggested_blocks = []
-    # Sum the number of executions for each block type
-    # Prisma cannot group by nested relations, so we do a raw query
-    # Calculate the cutoff timestamp
-    timestamp_threshold = datetime.now(timezone.utc) - timedelta(days=30)
+    """Return the most-executed blocks from the last 14 days.
 
-    results = await query_raw_with_schema(
-        """
-        SELECT
-            agent_node."agentBlockId" AS block_id,
-            COUNT(execution.id) AS execution_count
-        FROM {schema_prefix}"AgentNodeExecution" execution
-        JOIN {schema_prefix}"AgentNode" agent_node ON execution."agentNodeId" = agent_node.id
-        WHERE execution."endedTime" >= $1::timestamp
-        GROUP BY agent_node."agentBlockId"
-        ORDER BY execution_count DESC;
-        """,
-        timestamp_threshold,
-    )
+    Queries the mv_suggested_blocks materialized view (refreshed hourly via pg_cron)
+    and returns the top `count` blocks sorted by execution count, excluding
+    Input/Output/Agent block types and blocks in EXCLUDED_BLOCK_IDS.
+    """
+    results = await mv_suggested_blocks.prisma().find_many()
 
     # Get the top blocks based on execution count
-    # But ignore Input and Output blocks
+    # But ignore Input, Output, Agent, and excluded blocks
     blocks: list[tuple[BlockInfo, int]] = []
+    execution_counts = {row.block_id: row.execution_count for row in results}
 
     for block_type in load_all_blocks().values():
         block: AnyBlockSchema = block_type()
         if block.disabled or block.block_type in (
-            backend.data.block.BlockType.INPUT,
-            backend.data.block.BlockType.OUTPUT,
-            backend.data.block.BlockType.AGENT,
+            BlockType.INPUT,
+            BlockType.OUTPUT,
+            BlockType.AGENT,
         ):
             continue
-        # Find the execution count for this block
-        execution_count = next(
-            (row["execution_count"] for row in results if row["block_id"] == block.id),
-            0,
-        )
+        if block.id in EXCLUDED_BLOCK_IDS:
+            continue
+        execution_count = execution_counts.get(block.id, 0)
         blocks.append((block.get_info(), execution_count))
     # Sort blocks by execution count
     blocks.sort(key=lambda x: x[1], reverse=True)

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

@@ -4,7 +4,7 @@ from pydantic import BaseModel
 
 import backend.api.features.library.model as library_model
 import backend.api.features.store.model as store_model
-from backend.data.block import BlockInfo
+from backend.blocks._base import BlockInfo
 from backend.integrations.providers import ProviderName
 from backend.util.models import Pagination
 
@@ -15,7 +15,7 @@ FilterType = Literal[
     "my_agents",
 ]
 
-BlockType = Literal["all", "input", "action", "output"]
+BlockTypeFilter = Literal["all", "input", "action", "output"]
 
 
 class SearchEntry(BaseModel):
@@ -27,7 +27,6 @@ class SearchEntry(BaseModel):
 
 # Suggestions
 class SuggestionsResponse(BaseModel):
-    otto_suggestions: list[str]
     recent_searches: list[SearchEntry]
     providers: list[ProviderName]
     top_blocks: list[BlockInfo]

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

@@ -1,5 +1,5 @@
 import logging
-from typing import Annotated, Sequence
+from typing import Annotated, Sequence, cast, get_args
 
 import fastapi
 from autogpt_libs.auth.dependencies import get_user_id, requires_user
@@ -10,6 +10,8 @@ from backend.util.models import Pagination
 from . import db as builder_db
 from . import model as builder_model
 
+VALID_FILTER_VALUES = get_args(builder_model.FilterType)
+
 logger = logging.getLogger(__name__)
 
 router = fastapi.APIRouter(
@@ -49,11 +51,6 @@ async def get_suggestions(
     Get all suggestions for the Blocks Menu.
     """
     return builder_model.SuggestionsResponse(
-        otto_suggestions=[
-            "What blocks do I need to get started?",
-            "Help me create a list",
-            "Help me feed my data to Google Maps",
-        ],
         recent_searches=await builder_db.get_recent_searches(user_id),
         providers=[
             ProviderName.TWITTER,
@@ -88,7 +85,7 @@ async def get_block_categories(
 )
 async def get_blocks(
     category: Annotated[str | None, fastapi.Query()] = None,
-    type: Annotated[builder_model.BlockType | None, fastapi.Query()] = None,
+    type: Annotated[builder_model.BlockTypeFilter | None, fastapi.Query()] = None,
     provider: Annotated[ProviderName | None, fastapi.Query()] = None,
     page: Annotated[int, fastapi.Query()] = 1,
     page_size: Annotated[int, fastapi.Query()] = 50,
@@ -151,7 +148,7 @@ async def get_providers(
 async def search(
     user_id: Annotated[str, fastapi.Security(get_user_id)],
     search_query: Annotated[str | None, fastapi.Query()] = None,
-    filter: Annotated[list[builder_model.FilterType] | None, fastapi.Query()] = None,
+    filter: Annotated[str | None, fastapi.Query()] = None,
     search_id: Annotated[str | None, fastapi.Query()] = None,
     by_creator: Annotated[list[str] | None, fastapi.Query()] = None,
     page: Annotated[int, fastapi.Query()] = 1,
@@ -160,9 +157,20 @@ async def search(
     """
     Search for blocks (including integrations), marketplace agents, and user library agents.
     """
-    # If no filters are provided, then we will return all types
-    if not filter:
-        filter = [
+    # Parse and validate filter parameter
+    filters: list[builder_model.FilterType]
+    if filter:
+        filter_values = [f.strip() for f in filter.split(",")]
+        invalid_filters = [f for f in filter_values if f not in VALID_FILTER_VALUES]
+        if invalid_filters:
+            raise fastapi.HTTPException(
+                status_code=400,
+                detail=f"Invalid filter value(s): {', '.join(invalid_filters)}. "
+                f"Valid values are: {', '.join(VALID_FILTER_VALUES)}",
+            )
+        filters = cast(list[builder_model.FilterType], filter_values)
+    else:
+        filters = [
             "blocks",
             "integrations",
             "marketplace_agents",
@@ -174,7 +182,7 @@ async def search(
     cached_results = await builder_db.get_sorted_search_results(
         user_id=user_id,
         search_query=search_query,
-        filters=filter,
+        filters=filters,
         by_creator=by_creator,
     )
 
@@ -196,7 +204,7 @@ async def search(
         user_id,
         builder_model.SearchEntry(
             search_query=search_query,
-            filter=filter,
+            filter=filters,
             by_creator=by_creator,
             search_id=search_id,
         ),

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

@@ -1,368 +0,0 @@
-"""Redis Streams consumer for operation completion messages.
-
-This module provides a consumer (ChatCompletionConsumer) that listens for
-completion notifications (OperationCompleteMessage) from external services
-(like Agent Generator) and triggers the appropriate stream registry and
-chat service updates via process_operation_success/process_operation_failure.
-
-Why Redis Streams instead of RabbitMQ?
---------------------------------------
-While the project typically uses RabbitMQ for async task queues (e.g., execution
-queue), Redis Streams was chosen for chat completion notifications because:
-
-1. **Unified Infrastructure**: The SSE reconnection feature already uses Redis
-   Streams (via stream_registry) for message persistence and replay. Using Redis
-   Streams for completion notifications keeps all chat streaming infrastructure
-   in one system, simplifying operations and reducing cross-system coordination.
-
-2. **Message Replay**: Redis Streams support XREAD with arbitrary message IDs,
-   allowing consumers to replay missed messages after reconnection. This aligns
-   with the SSE reconnection pattern where clients can resume from last_message_id.
-
-3. **Consumer Groups with XAUTOCLAIM**: Redis consumer groups provide automatic
-   load balancing across pods with explicit message claiming (XAUTOCLAIM) for
-   recovering from dead consumers - ideal for the completion callback pattern.
-
-4. **Lower Latency**: For real-time SSE updates, Redis (already in-memory for
-   stream_registry) provides lower latency than an additional RabbitMQ hop.
-
-5. **Atomicity with Task State**: Completion processing often needs to update
-   task metadata stored in Redis. Keeping both in Redis enables simpler
-   transactional semantics without distributed coordination.
-
-The consumer uses Redis Streams with consumer groups for reliable message
-processing across multiple platform pods, with XAUTOCLAIM for reclaiming
-stale pending messages from dead consumers.
-"""
-
-import asyncio
-import logging
-import os
-import uuid
-from typing import Any
-
-import orjson
-from prisma import Prisma
-from pydantic import BaseModel
-from redis.exceptions import ResponseError
-
-from backend.data.redis_client import get_redis_async
-
-from . import stream_registry
-from .completion_handler import process_operation_failure, process_operation_success
-from .config import ChatConfig
-
-logger = logging.getLogger(__name__)
-config = ChatConfig()
-
-
-class OperationCompleteMessage(BaseModel):
-    """Message format for operation completion notifications."""
-
-    operation_id: str
-    task_id: str
-    success: bool
-    result: dict | str | None = None
-    error: str | None = None
-
-
-class ChatCompletionConsumer:
-    """Consumer for chat operation completion messages from Redis Streams.
-
-    This consumer initializes its own Prisma client in start() to ensure
-    database operations work correctly within this async context.
-
-    Uses Redis consumer groups to allow multiple platform pods to consume
-    messages reliably with automatic redelivery on failure.
-    """
-
-    def __init__(self):
-        self._consumer_task: asyncio.Task | None = None
-        self._running = False
-        self._prisma: Prisma | None = None
-        self._consumer_name = f"consumer-{uuid.uuid4().hex[:8]}"
-
-    async def start(self) -> None:
-        """Start the completion consumer."""
-        if self._running:
-            logger.warning("Completion consumer already running")
-            return
-
-        # Create consumer group if it doesn't exist
-        try:
-            redis = await get_redis_async()
-            await redis.xgroup_create(
-                config.stream_completion_name,
-                config.stream_consumer_group,
-                id="0",
-                mkstream=True,
-            )
-            logger.info(
-                f"Created consumer group '{config.stream_consumer_group}' "
-                f"on stream '{config.stream_completion_name}'"
-            )
-        except ResponseError as e:
-            if "BUSYGROUP" in str(e):
-                logger.debug(
-                    f"Consumer group '{config.stream_consumer_group}' already exists"
-                )
-            else:
-                raise
-
-        self._running = True
-        self._consumer_task = asyncio.create_task(self._consume_messages())
-        logger.info(
-            f"Chat completion consumer started (consumer: {self._consumer_name})"
-        )
-
-    async def _ensure_prisma(self) -> Prisma:
-        """Lazily initialize Prisma client on first use."""
-        if self._prisma is None:
-            database_url = os.getenv("DATABASE_URL", "postgresql://localhost:5432")
-            self._prisma = Prisma(datasource={"url": database_url})
-            await self._prisma.connect()
-            logger.info("[COMPLETION] Consumer Prisma client connected (lazy init)")
-        return self._prisma
-
-    async def stop(self) -> None:
-        """Stop the completion consumer."""
-        self._running = False
-
-        if self._consumer_task:
-            self._consumer_task.cancel()
-            try:
-                await self._consumer_task
-            except asyncio.CancelledError:
-                pass
-            self._consumer_task = None
-
-        if self._prisma:
-            await self._prisma.disconnect()
-            self._prisma = None
-            logger.info("[COMPLETION] Consumer Prisma client disconnected")
-
-        logger.info("Chat completion consumer stopped")
-
-    async def _consume_messages(self) -> None:
-        """Main message consumption loop with retry logic."""
-        max_retries = 10
-        retry_delay = 5  # seconds
-        retry_count = 0
-        block_timeout = 5000  # milliseconds
-
-        while self._running and retry_count < max_retries:
-            try:
-                redis = await get_redis_async()
-
-                # Reset retry count on successful connection
-                retry_count = 0
-
-                while self._running:
-                    # First, claim any stale pending messages from dead consumers
-                    # Redis does NOT auto-redeliver pending messages; we must explicitly
-                    # claim them using XAUTOCLAIM
-                    try:
-                        claimed_result = await redis.xautoclaim(
-                            name=config.stream_completion_name,
-                            groupname=config.stream_consumer_group,
-                            consumername=self._consumer_name,
-                            min_idle_time=config.stream_claim_min_idle_ms,
-                            start_id="0-0",
-                            count=10,
-                        )
-                        # xautoclaim returns: (next_start_id, [(id, data), ...], [deleted_ids])
-                        if claimed_result and len(claimed_result) >= 2:
-                            claimed_entries = claimed_result[1]
-                            if claimed_entries:
-                                logger.info(
-                                    f"Claimed {len(claimed_entries)} stale pending messages"
-                                )
-                                for entry_id, data in claimed_entries:
-                                    if not self._running:
-                                        return
-                                    await self._process_entry(redis, entry_id, data)
-                    except Exception as e:
-                        logger.warning(f"XAUTOCLAIM failed (non-fatal): {e}")
-
-                    # Read new messages from the stream
-                    messages = await redis.xreadgroup(
-                        groupname=config.stream_consumer_group,
-                        consumername=self._consumer_name,
-                        streams={config.stream_completion_name: ">"},
-                        block=block_timeout,
-                        count=10,
-                    )
-
-                    if not messages:
-                        continue
-
-                    for stream_name, entries in messages:
-                        for entry_id, data in entries:
-                            if not self._running:
-                                return
-                            await self._process_entry(redis, entry_id, data)
-
-            except asyncio.CancelledError:
-                logger.info("Consumer cancelled")
-                return
-            except Exception as e:
-                retry_count += 1
-                logger.error(
-                    f"Consumer error (retry {retry_count}/{max_retries}): {e}",
-                    exc_info=True,
-                )
-                if self._running and retry_count < max_retries:
-                    await asyncio.sleep(retry_delay)
-                else:
-                    logger.error("Max retries reached, stopping consumer")
-                    return
-
-    async def _process_entry(
-        self, redis: Any, entry_id: str, data: dict[str, Any]
-    ) -> None:
-        """Process a single stream entry and acknowledge it on success.
-
-        Args:
-            redis: Redis client connection
-            entry_id: The stream entry ID
-            data: The entry data dict
-        """
-        try:
-            # Handle the message
-            message_data = data.get("data")
-            if message_data:
-                await self._handle_message(
-                    message_data.encode()
-                    if isinstance(message_data, str)
-                    else message_data
-                )
-
-            # Acknowledge the message after successful processing
-            await redis.xack(
-                config.stream_completion_name,
-                config.stream_consumer_group,
-                entry_id,
-            )
-        except Exception as e:
-            logger.error(
-                f"Error processing completion message {entry_id}: {e}",
-                exc_info=True,
-            )
-            # Message remains in pending state and will be claimed by
-            # XAUTOCLAIM after min_idle_time expires
-
-    async def _handle_message(self, body: bytes) -> None:
-        """Handle a completion message using our own Prisma client."""
-        try:
-            data = orjson.loads(body)
-            message = OperationCompleteMessage(**data)
-        except Exception as e:
-            logger.error(f"Failed to parse completion message: {e}")
-            return
-
-        logger.info(
-            f"[COMPLETION] Received completion for operation {message.operation_id} "
-            f"(task_id={message.task_id}, success={message.success})"
-        )
-
-        # Find task in registry
-        task = await stream_registry.find_task_by_operation_id(message.operation_id)
-        if task is None:
-            task = await stream_registry.get_task(message.task_id)
-
-        if task is None:
-            logger.warning(
-                f"[COMPLETION] Task not found for operation {message.operation_id} "
-                f"(task_id={message.task_id})"
-            )
-            return
-
-        logger.info(
-            f"[COMPLETION] Found task: task_id={task.task_id}, "
-            f"session_id={task.session_id}, tool_call_id={task.tool_call_id}"
-        )
-
-        # Guard against empty task fields
-        if not task.task_id or not task.session_id or not task.tool_call_id:
-            logger.error(
-                f"[COMPLETION] Task has empty critical fields! "
-                f"task_id={task.task_id!r}, session_id={task.session_id!r}, "
-                f"tool_call_id={task.tool_call_id!r}"
-            )
-            return
-
-        if message.success:
-            await self._handle_success(task, message)
-        else:
-            await self._handle_failure(task, message)
-
-    async def _handle_success(
-        self,
-        task: stream_registry.ActiveTask,
-        message: OperationCompleteMessage,
-    ) -> None:
-        """Handle successful operation completion."""
-        prisma = await self._ensure_prisma()
-        await process_operation_success(task, message.result, prisma)
-
-    async def _handle_failure(
-        self,
-        task: stream_registry.ActiveTask,
-        message: OperationCompleteMessage,
-    ) -> None:
-        """Handle failed operation completion."""
-        prisma = await self._ensure_prisma()
-        await process_operation_failure(task, message.error, prisma)
-
-
-# Module-level consumer instance
-_consumer: ChatCompletionConsumer | None = None
-
-
-async def start_completion_consumer() -> None:
-    """Start the global completion consumer."""
-    global _consumer
-    if _consumer is None:
-        _consumer = ChatCompletionConsumer()
-    await _consumer.start()
-
-
-async def stop_completion_consumer() -> None:
-    """Stop the global completion consumer."""
-    global _consumer
-    if _consumer:
-        await _consumer.stop()
-        _consumer = None
-
-
-async def publish_operation_complete(
-    operation_id: str,
-    task_id: str,
-    success: bool,
-    result: dict | str | None = None,
-    error: str | None = None,
-) -> None:
-    """Publish an operation completion message to Redis Streams.
-
-    Args:
-        operation_id: The operation ID that completed.
-        task_id: The task ID associated with the operation.
-        success: Whether the operation succeeded.
-        result: The result data (for success).
-        error: The error message (for failure).
-    """
-    message = OperationCompleteMessage(
-        operation_id=operation_id,
-        task_id=task_id,
-        success=success,
-        result=result,
-        error=error,
-    )
-
-    redis = await get_redis_async()
-    await redis.xadd(
-        config.stream_completion_name,
-        {"data": message.model_dump_json()},
-        maxlen=config.stream_max_length,
-    )
-    logger.info(f"Published completion for operation {operation_id}")

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

@@ -1,344 +0,0 @@
-"""Shared completion handling for operation success and failure.
-
-This module provides common logic for handling operation completion from both:
-- The Redis Streams consumer (completion_consumer.py)
-- The HTTP webhook endpoint (routes.py)
-"""
-
-import logging
-from typing import Any
-
-import orjson
-from prisma import Prisma
-
-from . import service as chat_service
-from . import stream_registry
-from .response_model import StreamError, StreamToolOutputAvailable
-from .tools.models import ErrorResponse
-
-logger = logging.getLogger(__name__)
-
-# Tools that produce agent_json that needs to be saved to library
-AGENT_GENERATION_TOOLS = {"create_agent", "edit_agent"}
-
-# Keys that should be stripped from agent_json when returning in error responses
-SENSITIVE_KEYS = frozenset(
-    {
-        "api_key",
-        "apikey",
-        "api_secret",
-        "password",
-        "secret",
-        "credentials",
-        "credential",
-        "token",
-        "access_token",
-        "refresh_token",
-        "private_key",
-        "privatekey",
-        "auth",
-        "authorization",
-    }
-)
-
-
-def _sanitize_agent_json(obj: Any) -> Any:
-    """Recursively sanitize agent_json by removing sensitive keys.
-
-    Args:
-        obj: The object to sanitize (dict, list, or primitive)
-
-    Returns:
-        Sanitized copy with sensitive keys removed/redacted
-    """
-    if isinstance(obj, dict):
-        return {
-            k: "[REDACTED]" if k.lower() in SENSITIVE_KEYS else _sanitize_agent_json(v)
-            for k, v in obj.items()
-        }
-    elif isinstance(obj, list):
-        return [_sanitize_agent_json(item) for item in obj]
-    else:
-        return obj
-
-
-class ToolMessageUpdateError(Exception):
-    """Raised when updating a tool message in the database fails."""
-
-    pass
-
-
-async def _update_tool_message(
-    session_id: str,
-    tool_call_id: str,
-    content: str,
-    prisma_client: Prisma | None,
-) -> None:
-    """Update tool message in database.
-
-    Args:
-        session_id: The session ID
-        tool_call_id: The tool call ID to update
-        content: The new content for the message
-        prisma_client: Optional Prisma client. If None, uses chat_service.
-
-    Raises:
-        ToolMessageUpdateError: If the database update fails. The caller should
-            handle this to avoid marking the task as completed with inconsistent state.
-    """
-    try:
-        if prisma_client:
-            # Use provided Prisma client (for consumer with its own connection)
-            updated_count = await prisma_client.chatmessage.update_many(
-                where={
-                    "sessionId": session_id,
-                    "toolCallId": tool_call_id,
-                },
-                data={"content": content},
-            )
-            # Check if any rows were updated - 0 means message not found
-            if updated_count == 0:
-                raise ToolMessageUpdateError(
-                    f"No message found with tool_call_id={tool_call_id} in session {session_id}"
-                )
-        else:
-            # Use service function (for webhook endpoint)
-            await chat_service._update_pending_operation(
-                session_id=session_id,
-                tool_call_id=tool_call_id,
-                result=content,
-            )
-    except ToolMessageUpdateError:
-        raise
-    except Exception as e:
-        logger.error(f"[COMPLETION] Failed to update tool message: {e}", exc_info=True)
-        raise ToolMessageUpdateError(
-            f"Failed to update tool message for tool_call_id={tool_call_id}: {e}"
-        ) from e
-
-
-def serialize_result(result: dict | list | str | int | float | bool | None) -> str:
-    """Serialize result to JSON string with sensible defaults.
-
-    Args:
-        result: The result to serialize. Can be a dict, list, string,
-            number, boolean, or None.
-
-    Returns:
-        JSON string representation of the result. Returns '{"status": "completed"}'
-        only when result is explicitly None.
-    """
-    if isinstance(result, str):
-        return result
-    if result is None:
-        return '{"status": "completed"}'
-    return orjson.dumps(result).decode("utf-8")
-
-
-async def _save_agent_from_result(
-    result: dict[str, Any],
-    user_id: str | None,
-    tool_name: str,
-) -> dict[str, Any]:
-    """Save agent to library if result contains agent_json.
-
-    Args:
-        result: The result dict that may contain agent_json
-        user_id: The user ID to save the agent for
-        tool_name: The tool name (create_agent or edit_agent)
-
-    Returns:
-        Updated result dict with saved agent details, or original result if no agent_json
-    """
-    if not user_id:
-        logger.warning("[COMPLETION] Cannot save agent: no user_id in task")
-        return result
-
-    agent_json = result.get("agent_json")
-    if not agent_json:
-        logger.warning(
-            f"[COMPLETION] {tool_name} completed but no agent_json in result"
-        )
-        return result
-
-    try:
-        from .tools.agent_generator import save_agent_to_library
-
-        is_update = tool_name == "edit_agent"
-        created_graph, library_agent = await save_agent_to_library(
-            agent_json, user_id, is_update=is_update
-        )
-
-        logger.info(
-            f"[COMPLETION] Saved agent '{created_graph.name}' to library "
-            f"(graph_id={created_graph.id}, library_agent_id={library_agent.id})"
-        )
-
-        # Return a response similar to AgentSavedResponse
-        return {
-            "type": "agent_saved",
-            "message": f"Agent '{created_graph.name}' has been saved to your library!",
-            "agent_id": created_graph.id,
-            "agent_name": created_graph.name,
-            "library_agent_id": library_agent.id,
-            "library_agent_link": f"/library/agents/{library_agent.id}",
-            "agent_page_link": f"/build?flowID={created_graph.id}",
-        }
-    except Exception as e:
-        logger.error(
-            f"[COMPLETION] Failed to save agent to library: {e}",
-            exc_info=True,
-        )
-        # Return error but don't fail the whole operation
-        # Sanitize agent_json to remove sensitive keys before returning
-        return {
-            "type": "error",
-            "message": f"Agent was generated but failed to save: {str(e)}",
-            "error": str(e),
-            "agent_json": _sanitize_agent_json(agent_json),
-        }
-
-
-async def process_operation_success(
-    task: stream_registry.ActiveTask,
-    result: dict | str | None,
-    prisma_client: Prisma | None = None,
-) -> None:
-    """Handle successful operation completion.
-
-    Publishes the result to the stream registry, updates the database,
-    generates LLM continuation, and marks the task as completed.
-
-    Args:
-        task: The active task that completed
-        result: The result data from the operation
-        prisma_client: Optional Prisma client for database operations.
-            If None, uses chat_service._update_pending_operation instead.
-
-    Raises:
-        ToolMessageUpdateError: If the database update fails. The task will be
-            marked as failed instead of completed to avoid inconsistent state.
-    """
-    # For agent generation tools, save the agent to library
-    if task.tool_name in AGENT_GENERATION_TOOLS and isinstance(result, dict):
-        result = await _save_agent_from_result(result, task.user_id, task.tool_name)
-
-    # Serialize result for output (only substitute default when result is exactly None)
-    result_output = result if result is not None else {"status": "completed"}
-    output_str = (
-        result_output
-        if isinstance(result_output, str)
-        else orjson.dumps(result_output).decode("utf-8")
-    )
-
-    # Publish result to stream registry
-    await stream_registry.publish_chunk(
-        task.task_id,
-        StreamToolOutputAvailable(
-            toolCallId=task.tool_call_id,
-            toolName=task.tool_name,
-            output=output_str,
-            success=True,
-        ),
-    )
-
-    # Update pending operation in database
-    # If this fails, we must not continue to mark the task as completed
-    result_str = serialize_result(result)
-    try:
-        await _update_tool_message(
-            session_id=task.session_id,
-            tool_call_id=task.tool_call_id,
-            content=result_str,
-            prisma_client=prisma_client,
-        )
-    except ToolMessageUpdateError:
-        # DB update failed - mark task as failed to avoid inconsistent state
-        logger.error(
-            f"[COMPLETION] DB update failed for task {task.task_id}, "
-            "marking as failed instead of completed"
-        )
-        await stream_registry.publish_chunk(
-            task.task_id,
-            StreamError(errorText="Failed to save operation result to database"),
-        )
-        await stream_registry.mark_task_completed(task.task_id, status="failed")
-        raise
-
-    # Generate LLM continuation with streaming
-    try:
-        await chat_service._generate_llm_continuation_with_streaming(
-            session_id=task.session_id,
-            user_id=task.user_id,
-            task_id=task.task_id,
-        )
-    except Exception as e:
-        logger.error(
-            f"[COMPLETION] Failed to generate LLM continuation: {e}",
-            exc_info=True,
-        )
-
-    # Mark task as completed and release Redis lock
-    await stream_registry.mark_task_completed(task.task_id, status="completed")
-    try:
-        await chat_service._mark_operation_completed(task.tool_call_id)
-    except Exception as e:
-        logger.error(f"[COMPLETION] Failed to mark operation completed: {e}")
-
-    logger.info(
-        f"[COMPLETION] Successfully processed completion for task {task.task_id}"
-    )
-
-
-async def process_operation_failure(
-    task: stream_registry.ActiveTask,
-    error: str | None,
-    prisma_client: Prisma | None = None,
-) -> None:
-    """Handle failed operation completion.
-
-    Publishes the error to the stream registry, updates the database with
-    the error response, and marks the task as failed.
-
-    Args:
-        task: The active task that failed
-        error: The error message from the operation
-        prisma_client: Optional Prisma client for database operations.
-            If None, uses chat_service._update_pending_operation instead.
-    """
-    error_msg = error or "Operation failed"
-
-    # Publish error to stream registry
-    await stream_registry.publish_chunk(
-        task.task_id,
-        StreamError(errorText=error_msg),
-    )
-
-    # Update pending operation with error
-    # If this fails, we still continue to mark the task as failed
-    error_response = ErrorResponse(
-        message=error_msg,
-        error=error,
-    )
-    try:
-        await _update_tool_message(
-            session_id=task.session_id,
-            tool_call_id=task.tool_call_id,
-            content=error_response.model_dump_json(),
-            prisma_client=prisma_client,
-        )
-    except ToolMessageUpdateError:
-        # DB update failed - log but continue with cleanup
-        logger.error(
-            f"[COMPLETION] DB update failed while processing failure for task {task.task_id}, "
-            "continuing with cleanup"
-        )
-
-    # Mark task as failed and release Redis lock
-    await stream_registry.mark_task_completed(task.task_id, status="failed")
-    try:
-        await chat_service._mark_operation_completed(task.tool_call_id)
-    except Exception as e:
-        logger.error(f"[COMPLETION] Failed to mark operation completed: {e}")
-
-    logger.info(f"[COMPLETION] Processed failure for task {task.task_id}: {error_msg}")

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

@@ -1,146 +0,0 @@
-"""Configuration management for chat system."""
-
-import os
-
-from pydantic import Field, field_validator
-from pydantic_settings import BaseSettings
-
-
-class ChatConfig(BaseSettings):
-    """Configuration for the chat system."""
-
-    # OpenAI API Configuration
-    model: str = Field(
-        default="anthropic/claude-opus-4.6", description="Default model to use"
-    )
-    title_model: str = Field(
-        default="openai/gpt-4o-mini",
-        description="Model to use for generating session titles (should be fast/cheap)",
-    )
-    api_key: str | None = Field(default=None, description="OpenAI API key")
-    base_url: str | None = Field(
-        default="https://openrouter.ai/api/v1",
-        description="Base URL for API (e.g., for OpenRouter)",
-    )
-
-    # Session TTL Configuration - 12 hours
-    session_ttl: int = Field(default=43200, description="Session TTL in seconds")
-
-    # Streaming Configuration
-    max_context_messages: int = Field(
-        default=50, ge=1, le=200, description="Maximum context messages"
-    )
-
-    stream_timeout: int = Field(default=300, description="Stream timeout in seconds")
-    max_retries: int = Field(default=3, description="Maximum number of retries")
-    max_agent_runs: int = Field(default=30, description="Maximum number of agent runs")
-    max_agent_schedules: int = Field(
-        default=30, description="Maximum number of agent schedules"
-    )
-
-    # Long-running operation configuration
-    long_running_operation_ttl: int = Field(
-        default=600,
-        description="TTL in seconds for long-running operation tracking in Redis (safety net if pod dies)",
-    )
-
-    # Stream registry configuration for SSE reconnection
-    stream_ttl: int = Field(
-        default=3600,
-        description="TTL in seconds for stream data in Redis (1 hour)",
-    )
-    stream_max_length: int = Field(
-        default=10000,
-        description="Maximum number of messages to store per stream",
-    )
-
-    # Redis Streams configuration for completion consumer
-    stream_completion_name: str = Field(
-        default="chat:completions",
-        description="Redis Stream name for operation completions",
-    )
-    stream_consumer_group: str = Field(
-        default="chat_consumers",
-        description="Consumer group name for completion stream",
-    )
-    stream_claim_min_idle_ms: int = Field(
-        default=60000,
-        description="Minimum idle time in milliseconds before claiming pending messages from dead consumers",
-    )
-
-    # Redis key prefixes for stream registry
-    task_meta_prefix: str = Field(
-        default="chat:task:meta:",
-        description="Prefix for task metadata hash keys",
-    )
-    task_stream_prefix: str = Field(
-        default="chat:stream:",
-        description="Prefix for task message stream keys",
-    )
-    task_op_prefix: str = Field(
-        default="chat:task:op:",
-        description="Prefix for operation ID to task ID mapping keys",
-    )
-    internal_api_key: str | None = Field(
-        default=None,
-        description="API key for internal webhook callbacks (env: CHAT_INTERNAL_API_KEY)",
-    )
-
-    # Langfuse Prompt Management Configuration
-    # Note: Langfuse credentials are in Settings().secrets (settings.py)
-    langfuse_prompt_name: str = Field(
-        default="CoPilot Prompt",
-        description="Name of the prompt in Langfuse to fetch",
-    )
-
-    @field_validator("api_key", mode="before")
-    @classmethod
-    def get_api_key(cls, v):
-        """Get API key from environment if not provided."""
-        if v is None:
-            # Try to get from environment variables
-            # First check for CHAT_API_KEY (Pydantic prefix)
-            v = os.getenv("CHAT_API_KEY")
-            if not v:
-                # Fall back to OPEN_ROUTER_API_KEY
-                v = os.getenv("OPEN_ROUTER_API_KEY")
-            if not v:
-                # Fall back to OPENAI_API_KEY
-                v = os.getenv("OPENAI_API_KEY")
-        return v
-
-    @field_validator("base_url", mode="before")
-    @classmethod
-    def get_base_url(cls, v):
-        """Get base URL from environment if not provided."""
-        if v is None:
-            # Check for OpenRouter or custom base URL
-            v = os.getenv("CHAT_BASE_URL")
-            if not v:
-                v = os.getenv("OPENROUTER_BASE_URL")
-            if not v:
-                v = os.getenv("OPENAI_BASE_URL")
-            if not v:
-                v = "https://openrouter.ai/api/v1"
-        return v
-
-    @field_validator("internal_api_key", mode="before")
-    @classmethod
-    def get_internal_api_key(cls, v):
-        """Get internal API key from environment if not provided."""
-        if v is None:
-            v = os.getenv("CHAT_INTERNAL_API_KEY")
-        return v
-
-    # Prompt paths for different contexts
-    PROMPT_PATHS: dict[str, str] = {
-        "default": "prompts/chat_system.md",
-        "onboarding": "prompts/onboarding_system.md",
-    }
-
-    class Config:
-        """Pydantic config."""
-
-        env_file = ".env"
-        env_file_encoding = "utf-8"
-        extra = "ignore"  # Ignore extra environment variables

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

@@ -1,291 +0,0 @@
-"""Database operations for chat sessions."""
-
-import asyncio
-import logging
-from datetime import UTC, datetime
-from typing import Any, cast
-
-from prisma.models import ChatMessage as PrismaChatMessage
-from prisma.models import ChatSession as PrismaChatSession
-from prisma.types import (
-    ChatMessageCreateInput,
-    ChatSessionCreateInput,
-    ChatSessionUpdateInput,
-    ChatSessionWhereInput,
-)
-
-from backend.data.db import transaction
-from backend.util.json import SafeJson
-
-logger = logging.getLogger(__name__)
-
-
-async def get_chat_session(session_id: str) -> PrismaChatSession | None:
-    """Get a chat session by ID from the database."""
-    session = await PrismaChatSession.prisma().find_unique(
-        where={"id": session_id},
-        include={"Messages": True},
-    )
-    if session and session.Messages:
-        # Sort messages by sequence in Python - Prisma Python client doesn't support
-        # order_by in include clauses (unlike Prisma JS), so we sort after fetching
-        session.Messages.sort(key=lambda m: m.sequence)
-    return session
-
-
-async def create_chat_session(
-    session_id: str,
-    user_id: str,
-) -> PrismaChatSession:
-    """Create a new chat session in the database."""
-    data = ChatSessionCreateInput(
-        id=session_id,
-        userId=user_id,
-        credentials=SafeJson({}),
-        successfulAgentRuns=SafeJson({}),
-        successfulAgentSchedules=SafeJson({}),
-    )
-    return await PrismaChatSession.prisma().create(
-        data=data,
-        include={"Messages": True},
-    )
-
-
-async def update_chat_session(
-    session_id: str,
-    credentials: dict[str, Any] | None = None,
-    successful_agent_runs: dict[str, Any] | None = None,
-    successful_agent_schedules: dict[str, Any] | None = None,
-    total_prompt_tokens: int | None = None,
-    total_completion_tokens: int | None = None,
-    title: str | None = None,
-) -> PrismaChatSession | None:
-    """Update a chat session's metadata."""
-    data: ChatSessionUpdateInput = {"updatedAt": datetime.now(UTC)}
-
-    if credentials is not None:
-        data["credentials"] = SafeJson(credentials)
-    if successful_agent_runs is not None:
-        data["successfulAgentRuns"] = SafeJson(successful_agent_runs)
-    if successful_agent_schedules is not None:
-        data["successfulAgentSchedules"] = SafeJson(successful_agent_schedules)
-    if total_prompt_tokens is not None:
-        data["totalPromptTokens"] = total_prompt_tokens
-    if total_completion_tokens is not None:
-        data["totalCompletionTokens"] = total_completion_tokens
-    if title is not None:
-        data["title"] = title
-
-    session = await PrismaChatSession.prisma().update(
-        where={"id": session_id},
-        data=data,
-        include={"Messages": True},
-    )
-    if session and session.Messages:
-        # Sort in Python - Prisma Python doesn't support order_by in include clauses
-        session.Messages.sort(key=lambda m: m.sequence)
-    return session
-
-
-async def add_chat_message(
-    session_id: str,
-    role: str,
-    sequence: int,
-    content: str | None = None,
-    name: str | None = None,
-    tool_call_id: str | None = None,
-    refusal: str | None = None,
-    tool_calls: list[dict[str, Any]] | None = None,
-    function_call: dict[str, Any] | None = None,
-) -> PrismaChatMessage:
-    """Add a message to a chat session."""
-    # Build input dict dynamically rather than using ChatMessageCreateInput directly
-    # because Prisma's TypedDict validation rejects optional fields set to None.
-    # We only include fields that have values, then cast at the end.
-    data: dict[str, Any] = {
-        "Session": {"connect": {"id": session_id}},
-        "role": role,
-        "sequence": sequence,
-    }
-
-    # Add optional string fields
-    if content is not None:
-        data["content"] = content
-    if name is not None:
-        data["name"] = name
-    if tool_call_id is not None:
-        data["toolCallId"] = tool_call_id
-    if refusal is not None:
-        data["refusal"] = refusal
-
-    # Add optional JSON fields only when they have values
-    if tool_calls is not None:
-        data["toolCalls"] = SafeJson(tool_calls)
-    if function_call is not None:
-        data["functionCall"] = SafeJson(function_call)
-
-    # Run message create and session timestamp update in parallel for lower latency
-    _, message = await asyncio.gather(
-        PrismaChatSession.prisma().update(
-            where={"id": session_id},
-            data={"updatedAt": datetime.now(UTC)},
-        ),
-        PrismaChatMessage.prisma().create(data=cast(ChatMessageCreateInput, data)),
-    )
-    return message
-
-
-async def add_chat_messages_batch(
-    session_id: str,
-    messages: list[dict[str, Any]],
-    start_sequence: int,
-) -> list[PrismaChatMessage]:
-    """Add multiple messages to a chat session in a batch.
-
-    Uses a transaction for atomicity - if any message creation fails,
-    the entire batch is rolled back.
-    """
-    if not messages:
-        return []
-
-    created_messages = []
-
-    async with transaction() as tx:
-        for i, msg in enumerate(messages):
-            # Build input dict dynamically rather than using ChatMessageCreateInput
-            # directly because Prisma's TypedDict validation rejects optional fields
-            # set to None. We only include fields that have values, then cast.
-            data: dict[str, Any] = {
-                "Session": {"connect": {"id": session_id}},
-                "role": msg["role"],
-                "sequence": start_sequence + i,
-            }
-
-            # Add optional string fields
-            if msg.get("content") is not None:
-                data["content"] = msg["content"]
-            if msg.get("name") is not None:
-                data["name"] = msg["name"]
-            if msg.get("tool_call_id") is not None:
-                data["toolCallId"] = msg["tool_call_id"]
-            if msg.get("refusal") is not None:
-                data["refusal"] = msg["refusal"]
-
-            # Add optional JSON fields only when they have values
-            if msg.get("tool_calls") is not None:
-                data["toolCalls"] = SafeJson(msg["tool_calls"])
-            if msg.get("function_call") is not None:
-                data["functionCall"] = SafeJson(msg["function_call"])
-
-            created = await PrismaChatMessage.prisma(tx).create(
-                data=cast(ChatMessageCreateInput, data)
-            )
-            created_messages.append(created)
-
-        # Update session's updatedAt timestamp within the same transaction.
-        # Note: Token usage (total_prompt_tokens, total_completion_tokens) is updated
-        # separately via update_chat_session() after streaming completes.
-        await PrismaChatSession.prisma(tx).update(
-            where={"id": session_id},
-            data={"updatedAt": datetime.now(UTC)},
-        )
-
-    return created_messages
-
-
-async def get_user_chat_sessions(
-    user_id: str,
-    limit: int = 50,
-    offset: int = 0,
-) -> list[PrismaChatSession]:
-    """Get chat sessions for a user, ordered by most recent."""
-    return await PrismaChatSession.prisma().find_many(
-        where={"userId": user_id},
-        order={"updatedAt": "desc"},
-        take=limit,
-        skip=offset,
-    )
-
-
-async def get_user_session_count(user_id: str) -> int:
-    """Get the total number of chat sessions for a user."""
-    return await PrismaChatSession.prisma().count(where={"userId": user_id})
-
-
-async def delete_chat_session(session_id: str, user_id: str | None = None) -> bool:
-    """Delete a chat session and all its messages.
-
-    Args:
-        session_id: The session ID to delete.
-        user_id: If provided, validates that the session belongs to this user
-            before deletion. This prevents unauthorized deletion of other
-            users' sessions.
-
-    Returns:
-        True if deleted successfully, False otherwise.
-    """
-    try:
-        # Build typed where clause with optional user_id validation
-        where_clause: ChatSessionWhereInput = {"id": session_id}
-        if user_id is not None:
-            where_clause["userId"] = user_id
-
-        result = await PrismaChatSession.prisma().delete_many(where=where_clause)
-        if result == 0:
-            logger.warning(
-                f"No session deleted for {session_id} "
-                f"(user_id validation: {user_id is not None})"
-            )
-            return False
-        return True
-    except Exception as e:
-        logger.error(f"Failed to delete chat session {session_id}: {e}")
-        return False
-
-
-async def get_chat_session_message_count(session_id: str) -> int:
-    """Get the number of messages in a chat session."""
-    count = await PrismaChatMessage.prisma().count(where={"sessionId": session_id})
-    return count
-
-
-async def update_tool_message_content(
-    session_id: str,
-    tool_call_id: str,
-    new_content: str,
-) -> bool:
-    """Update the content of a tool message in chat history.
-
-    Used by background tasks to update pending operation messages with final results.
-
-    Args:
-        session_id: The chat session ID.
-        tool_call_id: The tool call ID to find the message.
-        new_content: The new content to set.
-
-    Returns:
-        True if a message was updated, False otherwise.
-    """
-    try:
-        result = await PrismaChatMessage.prisma().update_many(
-            where={
-                "sessionId": session_id,
-                "toolCallId": tool_call_id,
-            },
-            data={
-                "content": new_content,
-            },
-        )
-        if result == 0:
-            logger.warning(
-                f"No message found to update for session {session_id}, "
-                f"tool_call_id {tool_call_id}"
-            )
-            return False
-        return True
-    except Exception as e:
-        logger.error(
-            f"Failed to update tool message for session {session_id}, "
-            f"tool_call_id {tool_call_id}: {e}"
-        )
-        return False

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

@@ -1,119 +0,0 @@
-import pytest
-
-from .model import (
-    ChatMessage,
-    ChatSession,
-    Usage,
-    get_chat_session,
-    upsert_chat_session,
-)
-
-messages = [
-    ChatMessage(content="Hello, how are you?", role="user"),
-    ChatMessage(
-        content="I'm fine, thank you!",
-        role="assistant",
-        tool_calls=[
-            {
-                "id": "t123",
-                "type": "function",
-                "function": {
-                    "name": "get_weather",
-                    "arguments": '{"city": "New York"}',
-                },
-            }
-        ],
-    ),
-    ChatMessage(
-        content="I'm using the tool to get the weather",
-        role="tool",
-        tool_call_id="t123",
-    ),
-]
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_chatsession_serialization_deserialization():
-    s = ChatSession.new(user_id="abc123")
-    s.messages = messages
-    s.usage = [Usage(prompt_tokens=100, completion_tokens=200, total_tokens=300)]
-    serialized = s.model_dump_json()
-    s2 = ChatSession.model_validate_json(serialized)
-    assert s2.model_dump() == s.model_dump()
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_chatsession_redis_storage(setup_test_user, test_user_id):
-
-    s = ChatSession.new(user_id=test_user_id)
-    s.messages = messages
-
-    s = await upsert_chat_session(s)
-
-    s2 = await get_chat_session(
-        session_id=s.session_id,
-        user_id=s.user_id,
-    )
-
-    assert s2 == s
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_chatsession_redis_storage_user_id_mismatch(
-    setup_test_user, test_user_id
-):
-
-    s = ChatSession.new(user_id=test_user_id)
-    s.messages = messages
-    s = await upsert_chat_session(s)
-
-    s2 = await get_chat_session(s.session_id, "different_user_id")
-
-    assert s2 is None
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_chatsession_db_storage(setup_test_user, test_user_id):
-    """Test that messages are correctly saved to and loaded from DB (not cache)."""
-    from backend.data.redis_client import get_redis_async
-
-    # Create session with messages including assistant message
-    s = ChatSession.new(user_id=test_user_id)
-    s.messages = messages  # Contains user, assistant, and tool messages
-    assert s.session_id is not None, "Session id is not set"
-    # Upsert to save to both cache and DB
-    s = await upsert_chat_session(s)
-
-    # Clear the Redis cache to force DB load
-    redis_key = f"chat:session:{s.session_id}"
-    async_redis = await get_redis_async()
-    await async_redis.delete(redis_key)
-
-    # Load from DB (cache was cleared)
-    s2 = await get_chat_session(
-        session_id=s.session_id,
-        user_id=s.user_id,
-    )
-
-    assert s2 is not None, "Session not found after loading from DB"
-    assert len(s2.messages) == len(
-        s.messages
-    ), f"Message count mismatch: expected {len(s.messages)}, got {len(s2.messages)}"
-
-    # Verify all roles are present
-    roles = [m.role for m in s2.messages]
-    assert "user" in roles, f"User message missing. Roles found: {roles}"
-    assert "assistant" in roles, f"Assistant message missing. Roles found: {roles}"
-    assert "tool" in roles, f"Tool message missing. Roles found: {roles}"
-
-    # Verify message content
-    for orig, loaded in zip(s.messages, s2.messages):
-        assert orig.role == loaded.role, f"Role mismatch: {orig.role} != {loaded.role}"
-        assert (
-            orig.content == loaded.content
-        ), f"Content mismatch for {orig.role}: {orig.content} != {loaded.content}"
-        if orig.tool_calls:
-            assert (
-                loaded.tool_calls is not None
-            ), f"Tool calls missing for {orig.role} message"
-            assert len(orig.tool_calls) == len(loaded.tool_calls)

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

@@ -0,0 +1,251 @@
+"""Tests for chat API routes: session title update and file attachment validation."""
+
+from unittest.mock import AsyncMock
+
+import fastapi
+import fastapi.testclient
+import pytest
+import pytest_mock
+
+from backend.api.features.chat import routes as chat_routes
+
+app = fastapi.FastAPI()
+app.include_router(chat_routes.router)
+
+client = fastapi.testclient.TestClient(app)
+
+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"]
+    yield
+    app.dependency_overrides.clear()
+
+
+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():
+    """More than 20 file_ids should be rejected by Pydantic validation (422)."""
+    response = client.post(
+        "/sessions/sess-1/stream",
+        json={
+            "message": "hello",
+            "file_ids": [f"00000000-0000-0000-0000-{i:012d}" for i in range(21)],
+        },
+    )
+    assert response.status_code == 422
+
+
+def _mock_stream_internals(mocker: pytest_mock.MockFixture):
+    """Mock the async internals of stream_chat_post so tests can exercise
+    validation and enrichment logic without needing Redis/RabbitMQ."""
+    mocker.patch(
+        "backend.api.features.chat.routes._validate_and_get_session",
+        return_value=None,
+    )
+    mocker.patch(
+        "backend.api.features.chat.routes.append_and_save_message",
+        return_value=None,
+    )
+    mock_registry = mocker.MagicMock()
+    mock_registry.create_session = mocker.AsyncMock(return_value=None)
+    mocker.patch(
+        "backend.api.features.chat.routes.stream_registry",
+        mock_registry,
+    )
+    mocker.patch(
+        "backend.api.features.chat.routes.enqueue_copilot_turn",
+        return_value=None,
+    )
+    mocker.patch(
+        "backend.api.features.chat.routes.track_user_message",
+        return_value=None,
+    )
+
+
+def test_stream_chat_accepts_20_file_ids(mocker: pytest_mock.MockFixture):
+    """Exactly 20 file_ids should be accepted (not rejected by validation)."""
+    _mock_stream_internals(mocker)
+    # Patch workspace lookup as imported by the routes module
+    mocker.patch(
+        "backend.api.features.chat.routes.get_or_create_workspace",
+        return_value=type("W", (), {"id": "ws-1"})(),
+    )
+    mock_prisma = mocker.MagicMock()
+    mock_prisma.find_many = mocker.AsyncMock(return_value=[])
+    mocker.patch(
+        "prisma.models.UserWorkspaceFile.prisma",
+        return_value=mock_prisma,
+    )
+
+    response = client.post(
+        "/sessions/sess-1/stream",
+        json={
+            "message": "hello",
+            "file_ids": [f"00000000-0000-0000-0000-{i:012d}" for i in range(20)],
+        },
+    )
+    # Should get past validation — 200 streaming response expected
+    assert response.status_code == 200
+
+
+# ─── UUID format filtering ─────────────────────────────────────────────
+
+
+def test_file_ids_filters_invalid_uuids(mocker: pytest_mock.MockFixture):
+    """Non-UUID strings in file_ids should be silently filtered out
+    and NOT passed to the database query."""
+    _mock_stream_internals(mocker)
+    mocker.patch(
+        "backend.api.features.chat.routes.get_or_create_workspace",
+        return_value=type("W", (), {"id": "ws-1"})(),
+    )
+
+    mock_prisma = mocker.MagicMock()
+    mock_prisma.find_many = mocker.AsyncMock(return_value=[])
+    mocker.patch(
+        "prisma.models.UserWorkspaceFile.prisma",
+        return_value=mock_prisma,
+    )
+
+    valid_id = "aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee"
+    client.post(
+        "/sessions/sess-1/stream",
+        json={
+            "message": "hello",
+            "file_ids": [
+                valid_id,
+                "not-a-uuid",
+                "../../../etc/passwd",
+                "",
+            ],
+        },
+    )
+
+    # The find_many call should only receive the one valid UUID
+    mock_prisma.find_many.assert_called_once()
+    call_kwargs = mock_prisma.find_many.call_args[1]
+    assert call_kwargs["where"]["id"]["in"] == [valid_id]
+
+
+# ─── Cross-workspace file_ids ─────────────────────────────────────────
+
+
+def test_file_ids_scoped_to_workspace(mocker: pytest_mock.MockFixture):
+    """The batch query should scope to the user's workspace."""
+    _mock_stream_internals(mocker)
+    mocker.patch(
+        "backend.api.features.chat.routes.get_or_create_workspace",
+        return_value=type("W", (), {"id": "my-workspace-id"})(),
+    )
+
+    mock_prisma = mocker.MagicMock()
+    mock_prisma.find_many = mocker.AsyncMock(return_value=[])
+    mocker.patch(
+        "prisma.models.UserWorkspaceFile.prisma",
+        return_value=mock_prisma,
+    )
+
+    fid = "aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee"
+    client.post(
+        "/sessions/sess-1/stream",
+        json={"message": "hi", "file_ids": [fid]},
+    )
+
+    call_kwargs = mock_prisma.find_many.call_args[1]
+    assert call_kwargs["where"]["workspaceId"] == "my-workspace-id"
+    assert call_kwargs["where"]["isDeleted"] is False

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

@@ -1,82 +0,0 @@
-import logging
-from os import getenv
-
-import pytest
-
-from . import service as chat_service
-from .model import create_chat_session, get_chat_session, upsert_chat_session
-from .response_model import (
-    StreamError,
-    StreamFinish,
-    StreamTextDelta,
-    StreamToolOutputAvailable,
-)
-
-logger = logging.getLogger(__name__)
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_stream_chat_completion(setup_test_user, test_user_id):
-    """
-    Test the stream_chat_completion function.
-    """
-    api_key: str | None = getenv("OPEN_ROUTER_API_KEY")
-    if not api_key:
-        return pytest.skip("OPEN_ROUTER_API_KEY is not set, skipping test")
-
-    session = await create_chat_session(test_user_id)
-
-    has_errors = False
-    has_ended = False
-    assistant_message = ""
-    async for chunk in chat_service.stream_chat_completion(
-        session.session_id, "Hello, how are you?", user_id=session.user_id
-    ):
-        logger.info(chunk)
-        if isinstance(chunk, StreamError):
-            has_errors = True
-        if isinstance(chunk, StreamTextDelta):
-            assistant_message += chunk.delta
-        if isinstance(chunk, StreamFinish):
-            has_ended = True
-
-    assert has_ended, "Chat completion did not end"
-    assert not has_errors, "Error occurred while streaming chat completion"
-    assert assistant_message, "Assistant message is empty"
-
-
-@pytest.mark.asyncio(loop_scope="session")
-async def test_stream_chat_completion_with_tool_calls(setup_test_user, test_user_id):
-    """
-    Test the stream_chat_completion function.
-    """
-    api_key: str | None = getenv("OPEN_ROUTER_API_KEY")
-    if not api_key:
-        return pytest.skip("OPEN_ROUTER_API_KEY is not set, skipping test")
-
-    session = await create_chat_session(test_user_id)
-    session = await upsert_chat_session(session)
-
-    has_errors = False
-    has_ended = False
-    had_tool_calls = False
-    async for chunk in chat_service.stream_chat_completion(
-        session.session_id,
-        "Please find me an agent that can help me with my business. Use the query 'moneny printing agent'",
-        user_id=session.user_id,
-    ):
-        logger.info(chunk)
-        if isinstance(chunk, StreamError):
-            has_errors = True
-
-        if isinstance(chunk, StreamFinish):
-            has_ended = True
-        if isinstance(chunk, StreamToolOutputAvailable):
-            had_tool_calls = True
-
-    assert has_ended, "Chat completion did not end"
-    assert not has_errors, "Error occurred while streaming chat completion"
-    assert had_tool_calls, "Tool calls did not occur"
-    session = await get_chat_session(session.session_id)
-    assert session, "Session not found"
-    assert session.usage, "Usage is empty"

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

@@ -1,704 +0,0 @@
-"""Stream registry for managing reconnectable SSE streams.
-
-This module provides a registry for tracking active streaming tasks and their
-messages. It uses Redis for all state management (no in-memory state), making
-pods stateless and horizontally scalable.
-
-Architecture:
-- Redis Stream: Persists all messages for replay and real-time delivery
-- Redis Hash: Task metadata (status, session_id, etc.)
-
-Subscribers:
-1. Replay missed messages from Redis Stream (XREAD)
-2. Listen for live updates via blocking XREAD
-3. No in-memory state required on the subscribing pod
-"""
-
-import asyncio
-import logging
-from dataclasses import dataclass, field
-from datetime import datetime, timezone
-from typing import Any, Literal
-
-import orjson
-
-from backend.data.redis_client import get_redis_async
-
-from .config import ChatConfig
-from .response_model import StreamBaseResponse, StreamError, StreamFinish
-
-logger = logging.getLogger(__name__)
-config = ChatConfig()
-
-# Track background tasks for this pod (just the asyncio.Task reference, not subscribers)
-_local_tasks: dict[str, asyncio.Task] = {}
-
-# Track listener tasks per subscriber queue for cleanup
-# Maps queue id() to (task_id, asyncio.Task) for proper cleanup on unsubscribe
-_listener_tasks: dict[int, tuple[str, asyncio.Task]] = {}
-
-# Timeout for putting chunks into subscriber queues (seconds)
-# If the queue is full and doesn't drain within this time, send an overflow error
-QUEUE_PUT_TIMEOUT = 5.0
-
-# Lua script for atomic compare-and-swap status update (idempotent completion)
-# Returns 1 if status was updated, 0 if already completed/failed
-COMPLETE_TASK_SCRIPT = """
-local current = redis.call("HGET", KEYS[1], "status")
-if current == "running" then
-    redis.call("HSET", KEYS[1], "status", ARGV[1])
-    return 1
-end
-return 0
-"""
-
-
-@dataclass
-class ActiveTask:
-    """Represents an active streaming task (metadata only, no in-memory queues)."""
-
-    task_id: str
-    session_id: str
-    user_id: str | None
-    tool_call_id: str
-    tool_name: str
-    operation_id: str
-    status: Literal["running", "completed", "failed"] = "running"
-    created_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
-    asyncio_task: asyncio.Task | None = None
-
-
-def _get_task_meta_key(task_id: str) -> str:
-    """Get Redis key for task metadata."""
-    return f"{config.task_meta_prefix}{task_id}"
-
-
-def _get_task_stream_key(task_id: str) -> str:
-    """Get Redis key for task message stream."""
-    return f"{config.task_stream_prefix}{task_id}"
-
-
-def _get_operation_mapping_key(operation_id: str) -> str:
-    """Get Redis key for operation_id to task_id mapping."""
-    return f"{config.task_op_prefix}{operation_id}"
-
-
-async def create_task(
-    task_id: str,
-    session_id: str,
-    user_id: str | None,
-    tool_call_id: str,
-    tool_name: str,
-    operation_id: str,
-) -> ActiveTask:
-    """Create a new streaming task in Redis.
-
-    Args:
-        task_id: Unique identifier for the task
-        session_id: Chat session ID
-        user_id: User ID (may be None for anonymous)
-        tool_call_id: Tool call ID from the LLM
-        tool_name: Name of the tool being executed
-        operation_id: Operation ID for webhook callbacks
-
-    Returns:
-        The created ActiveTask instance (metadata only)
-    """
-    task = ActiveTask(
-        task_id=task_id,
-        session_id=session_id,
-        user_id=user_id,
-        tool_call_id=tool_call_id,
-        tool_name=tool_name,
-        operation_id=operation_id,
-    )
-
-    # Store metadata in Redis
-    redis = await get_redis_async()
-    meta_key = _get_task_meta_key(task_id)
-    op_key = _get_operation_mapping_key(operation_id)
-
-    await redis.hset(  # type: ignore[misc]
-        meta_key,
-        mapping={
-            "task_id": task_id,
-            "session_id": session_id,
-            "user_id": user_id or "",
-            "tool_call_id": tool_call_id,
-            "tool_name": tool_name,
-            "operation_id": operation_id,
-            "status": task.status,
-            "created_at": task.created_at.isoformat(),
-        },
-    )
-    await redis.expire(meta_key, config.stream_ttl)
-
-    # Create operation_id -> task_id mapping for webhook lookups
-    await redis.set(op_key, task_id, ex=config.stream_ttl)
-
-    logger.debug(f"Created task {task_id} for session {session_id}")
-
-    return task
-
-
-async def publish_chunk(
-    task_id: str,
-    chunk: StreamBaseResponse,
-) -> str:
-    """Publish a chunk to Redis Stream.
-
-    All delivery is via Redis Streams - no in-memory state.
-
-    Args:
-        task_id: Task ID to publish to
-        chunk: The stream response chunk to publish
-
-    Returns:
-        The Redis Stream message ID
-    """
-    chunk_json = chunk.model_dump_json()
-    message_id = "0-0"
-
-    try:
-        redis = await get_redis_async()
-        stream_key = _get_task_stream_key(task_id)
-
-        # Write to Redis Stream for persistence and real-time delivery
-        raw_id = await redis.xadd(
-            stream_key,
-            {"data": chunk_json},
-            maxlen=config.stream_max_length,
-        )
-        message_id = raw_id if isinstance(raw_id, str) else raw_id.decode()
-
-        # Set TTL on stream to match task metadata TTL
-        await redis.expire(stream_key, config.stream_ttl)
-    except Exception as e:
-        logger.error(
-            f"Failed to publish chunk for task {task_id}: {e}",
-            exc_info=True,
-        )
-
-    return message_id
-
-
-async def subscribe_to_task(
-    task_id: str,
-    user_id: str | None,
-    last_message_id: str = "0-0",
-) -> asyncio.Queue[StreamBaseResponse] | None:
-    """Subscribe to a task's stream with replay of missed messages.
-
-    This is fully stateless - uses Redis Stream for replay and pub/sub for live updates.
-
-    Args:
-        task_id: Task ID to subscribe to
-        user_id: User ID for ownership validation
-        last_message_id: Last Redis Stream message ID received ("0-0" for full replay)
-
-    Returns:
-        An asyncio Queue that will receive stream chunks, or None if task not found
-        or user doesn't have access
-    """
-    redis = await get_redis_async()
-    meta_key = _get_task_meta_key(task_id)
-    meta: dict[Any, Any] = await redis.hgetall(meta_key)  # type: ignore[misc]
-
-    if not meta:
-        logger.debug(f"Task {task_id} not found in Redis")
-        return None
-
-    # Note: Redis client uses decode_responses=True, so keys are strings
-    task_status = meta.get("status", "")
-    task_user_id = meta.get("user_id", "") or None
-
-    # Validate ownership - if task has an owner, requester must match
-    if task_user_id:
-        if user_id != task_user_id:
-            logger.warning(
-                f"User {user_id} denied access to task {task_id} "
-                f"owned by {task_user_id}"
-            )
-            return None
-
-    subscriber_queue: asyncio.Queue[StreamBaseResponse] = asyncio.Queue()
-    stream_key = _get_task_stream_key(task_id)
-
-    # Step 1: Replay messages from Redis Stream
-    messages = await redis.xread({stream_key: last_message_id}, block=0, count=1000)
-
-    replayed_count = 0
-    replay_last_id = last_message_id
-    if messages:
-        for _stream_name, stream_messages in messages:
-            for msg_id, msg_data in stream_messages:
-                replay_last_id = msg_id if isinstance(msg_id, str) else msg_id.decode()
-                # Note: Redis client uses decode_responses=True, so keys are strings
-                if "data" in msg_data:
-                    try:
-                        chunk_data = orjson.loads(msg_data["data"])
-                        chunk = _reconstruct_chunk(chunk_data)
-                        if chunk:
-                            await subscriber_queue.put(chunk)
-                            replayed_count += 1
-                    except Exception as e:
-                        logger.warning(f"Failed to replay message: {e}")
-
-    logger.debug(f"Task {task_id}: replayed {replayed_count} messages")
-
-    # Step 2: If task is still running, start stream listener for live updates
-    if task_status == "running":
-        listener_task = asyncio.create_task(
-            _stream_listener(task_id, subscriber_queue, replay_last_id)
-        )
-        # Track listener task for cleanup on unsubscribe
-        _listener_tasks[id(subscriber_queue)] = (task_id, listener_task)
-    else:
-        # Task is completed/failed - add finish marker
-        await subscriber_queue.put(StreamFinish())
-
-    return subscriber_queue
-
-
-async def _stream_listener(
-    task_id: str,
-    subscriber_queue: asyncio.Queue[StreamBaseResponse],
-    last_replayed_id: str,
-) -> None:
-    """Listen to Redis Stream for new messages using blocking XREAD.
-
-    This approach avoids the duplicate message issue that can occur with pub/sub
-    when messages are published during the gap between replay and subscription.
-
-    Args:
-        task_id: Task ID to listen for
-        subscriber_queue: Queue to deliver messages to
-        last_replayed_id: Last message ID from replay (continue from here)
-    """
-    queue_id = id(subscriber_queue)
-    # Track the last successfully delivered message ID for recovery hints
-    last_delivered_id = last_replayed_id
-
-    try:
-        redis = await get_redis_async()
-        stream_key = _get_task_stream_key(task_id)
-        current_id = last_replayed_id
-
-        while True:
-            # Block for up to 30 seconds waiting for new messages
-            # This allows periodic checking if task is still running
-            messages = await redis.xread(
-                {stream_key: current_id}, block=30000, count=100
-            )
-
-            if not messages:
-                # Timeout - check if task is still running
-                meta_key = _get_task_meta_key(task_id)
-                status = await redis.hget(meta_key, "status")  # type: ignore[misc]
-                if status and status != "running":
-                    try:
-                        await asyncio.wait_for(
-                            subscriber_queue.put(StreamFinish()),
-                            timeout=QUEUE_PUT_TIMEOUT,
-                        )
-                    except asyncio.TimeoutError:
-                        logger.warning(
-                            f"Timeout delivering finish event for task {task_id}"
-                        )
-                    break
-                continue
-
-            for _stream_name, stream_messages in messages:
-                for msg_id, msg_data in stream_messages:
-                    current_id = msg_id if isinstance(msg_id, str) else msg_id.decode()
-
-                    if "data" not in msg_data:
-                        continue
-
-                    try:
-                        chunk_data = orjson.loads(msg_data["data"])
-                        chunk = _reconstruct_chunk(chunk_data)
-                        if chunk:
-                            try:
-                                await asyncio.wait_for(
-                                    subscriber_queue.put(chunk),
-                                    timeout=QUEUE_PUT_TIMEOUT,
-                                )
-                                # Update last delivered ID on successful delivery
-                                last_delivered_id = current_id
-                            except asyncio.TimeoutError:
-                                logger.warning(
-                                    f"Subscriber queue full for task {task_id}, "
-                                    f"message delivery timed out after {QUEUE_PUT_TIMEOUT}s"
-                                )
-                                # Send overflow error with recovery info
-                                try:
-                                    overflow_error = StreamError(
-                                        errorText="Message delivery timeout - some messages may have been missed",
-                                        code="QUEUE_OVERFLOW",
-                                        details={
-                                            "last_delivered_id": last_delivered_id,
-                                            "recovery_hint": f"Reconnect with last_message_id={last_delivered_id}",
-                                        },
-                                    )
-                                    subscriber_queue.put_nowait(overflow_error)
-                                except asyncio.QueueFull:
-                                    # Queue is completely stuck, nothing more we can do
-                                    logger.error(
-                                        f"Cannot deliver overflow error for task {task_id}, "
-                                        "queue completely blocked"
-                                    )
-
-                            # Stop listening on finish
-                            if isinstance(chunk, StreamFinish):
-                                return
-                    except Exception as e:
-                        logger.warning(f"Error processing stream message: {e}")
-
-    except asyncio.CancelledError:
-        logger.debug(f"Stream listener cancelled for task {task_id}")
-        raise  # Re-raise to propagate cancellation
-    except Exception as e:
-        logger.error(f"Stream listener error for task {task_id}: {e}")
-        # On error, send finish to unblock subscriber
-        try:
-            await asyncio.wait_for(
-                subscriber_queue.put(StreamFinish()),
-                timeout=QUEUE_PUT_TIMEOUT,
-            )
-        except (asyncio.TimeoutError, asyncio.QueueFull):
-            logger.warning(
-                f"Could not deliver finish event for task {task_id} after error"
-            )
-    finally:
-        # Clean up listener task mapping on exit
-        _listener_tasks.pop(queue_id, None)
-
-
-async def mark_task_completed(
-    task_id: str,
-    status: Literal["completed", "failed"] = "completed",
-) -> bool:
-    """Mark a task as completed and publish finish event.
-
-    This is idempotent - calling multiple times with the same task_id is safe.
-    Uses atomic compare-and-swap via Lua script to prevent race conditions.
-    Status is updated first (source of truth), then finish event is published (best-effort).
-
-    Args:
-        task_id: Task ID to mark as completed
-        status: Final status ("completed" or "failed")
-
-    Returns:
-        True if task was newly marked completed, False if already completed/failed
-    """
-    redis = await get_redis_async()
-    meta_key = _get_task_meta_key(task_id)
-
-    # Atomic compare-and-swap: only update if status is "running"
-    # This prevents race conditions when multiple callers try to complete simultaneously
-    result = await redis.eval(COMPLETE_TASK_SCRIPT, 1, meta_key, status)  # type: ignore[misc]
-
-    if result == 0:
-        logger.debug(f"Task {task_id} already completed/failed, skipping")
-        return False
-
-    # THEN publish finish event (best-effort - listeners can detect via status polling)
-    try:
-        await publish_chunk(task_id, StreamFinish())
-    except Exception as e:
-        logger.error(
-            f"Failed to publish finish event for task {task_id}: {e}. "
-            "Listeners will detect completion via status polling."
-        )
-
-    # Clean up local task reference if exists
-    _local_tasks.pop(task_id, None)
-    return True
-
-
-async def find_task_by_operation_id(operation_id: str) -> ActiveTask | None:
-    """Find a task by its operation ID.
-
-    Used by webhook callbacks to locate the task to update.
-
-    Args:
-        operation_id: Operation ID to search for
-
-    Returns:
-        ActiveTask if found, None otherwise
-    """
-    redis = await get_redis_async()
-    op_key = _get_operation_mapping_key(operation_id)
-    task_id = await redis.get(op_key)
-
-    if not task_id:
-        return None
-
-    task_id_str = task_id.decode() if isinstance(task_id, bytes) else task_id
-    return await get_task(task_id_str)
-
-
-async def get_task(task_id: str) -> ActiveTask | None:
-    """Get a task by its ID from Redis.
-
-    Args:
-        task_id: Task ID to look up
-
-    Returns:
-        ActiveTask if found, None otherwise
-    """
-    redis = await get_redis_async()
-    meta_key = _get_task_meta_key(task_id)
-    meta: dict[Any, Any] = await redis.hgetall(meta_key)  # type: ignore[misc]
-
-    if not meta:
-        return None
-
-    # Note: Redis client uses decode_responses=True, so keys/values are strings
-    return ActiveTask(
-        task_id=meta.get("task_id", ""),
-        session_id=meta.get("session_id", ""),
-        user_id=meta.get("user_id", "") or None,
-        tool_call_id=meta.get("tool_call_id", ""),
-        tool_name=meta.get("tool_name", ""),
-        operation_id=meta.get("operation_id", ""),
-        status=meta.get("status", "running"),  # type: ignore[arg-type]
-    )
-
-
-async def get_task_with_expiry_info(
-    task_id: str,
-) -> tuple[ActiveTask | None, str | None]:
-    """Get a task by its ID with expiration detection.
-
-    Returns (task, error_code) where error_code is:
-    - None if task found
-    - "TASK_EXPIRED" if stream exists but metadata is gone (TTL expired)
-    - "TASK_NOT_FOUND" if neither exists
-
-    Args:
-        task_id: Task ID to look up
-
-    Returns:
-        Tuple of (ActiveTask or None, error_code or None)
-    """
-    redis = await get_redis_async()
-    meta_key = _get_task_meta_key(task_id)
-    stream_key = _get_task_stream_key(task_id)
-
-    meta: dict[Any, Any] = await redis.hgetall(meta_key)  # type: ignore[misc]
-
-    if not meta:
-        # Check if stream still has data (metadata expired but stream hasn't)
-        stream_len = await redis.xlen(stream_key)
-        if stream_len > 0:
-            return None, "TASK_EXPIRED"
-        return None, "TASK_NOT_FOUND"
-
-    # Note: Redis client uses decode_responses=True, so keys/values are strings
-    return (
-        ActiveTask(
-            task_id=meta.get("task_id", ""),
-            session_id=meta.get("session_id", ""),
-            user_id=meta.get("user_id", "") or None,
-            tool_call_id=meta.get("tool_call_id", ""),
-            tool_name=meta.get("tool_name", ""),
-            operation_id=meta.get("operation_id", ""),
-            status=meta.get("status", "running"),  # type: ignore[arg-type]
-        ),
-        None,
-    )
-
-
-async def get_active_task_for_session(
-    session_id: str,
-    user_id: str | None = None,
-) -> tuple[ActiveTask | None, str]:
-    """Get the active (running) task for a session, if any.
-
-    Scans Redis for tasks matching the session_id with status="running".
-
-    Args:
-        session_id: Session ID to look up
-        user_id: User ID for ownership validation (optional)
-
-    Returns:
-        Tuple of (ActiveTask if found and running, last_message_id from Redis Stream)
-    """
-
-    redis = await get_redis_async()
-
-    # Scan Redis for task metadata keys
-    cursor = 0
-    tasks_checked = 0
-
-    while True:
-        cursor, keys = await redis.scan(
-            cursor, match=f"{config.task_meta_prefix}*", count=100
-        )
-
-        for key in keys:
-            tasks_checked += 1
-            meta: dict[Any, Any] = await redis.hgetall(key)  # type: ignore[misc]
-            if not meta:
-                continue
-
-            # Note: Redis client uses decode_responses=True, so keys/values are strings
-            task_session_id = meta.get("session_id", "")
-            task_status = meta.get("status", "")
-            task_user_id = meta.get("user_id", "") or None
-            task_id = meta.get("task_id", "")
-
-            if task_session_id == session_id and task_status == "running":
-                # Validate ownership - if task has an owner, requester must match
-                if task_user_id and user_id != task_user_id:
-                    continue
-
-                # Get the last message ID from Redis Stream
-                stream_key = _get_task_stream_key(task_id)
-                last_id = "0-0"
-                try:
-                    messages = await redis.xrevrange(stream_key, count=1)
-                    if messages:
-                        msg_id = messages[0][0]
-                        last_id = msg_id if isinstance(msg_id, str) else msg_id.decode()
-                except Exception as e:
-                    logger.warning(f"Failed to get last message ID: {e}")
-
-                return (
-                    ActiveTask(
-                        task_id=task_id,
-                        session_id=task_session_id,
-                        user_id=task_user_id,
-                        tool_call_id=meta.get("tool_call_id", ""),
-                        tool_name=meta.get("tool_name", ""),
-                        operation_id=meta.get("operation_id", ""),
-                        status="running",
-                    ),
-                    last_id,
-                )
-
-        if cursor == 0:
-            break
-
-    return None, "0-0"
-
-
-def _reconstruct_chunk(chunk_data: dict) -> StreamBaseResponse | None:
-    """Reconstruct a StreamBaseResponse from JSON data.
-
-    Args:
-        chunk_data: Parsed JSON data from Redis
-
-    Returns:
-        Reconstructed response object, or None if unknown type
-    """
-    from .response_model import (
-        ResponseType,
-        StreamError,
-        StreamFinish,
-        StreamHeartbeat,
-        StreamStart,
-        StreamTextDelta,
-        StreamTextEnd,
-        StreamTextStart,
-        StreamToolInputAvailable,
-        StreamToolInputStart,
-        StreamToolOutputAvailable,
-        StreamUsage,
-    )
-
-    # Map response types to their corresponding classes
-    type_to_class: dict[str, type[StreamBaseResponse]] = {
-        ResponseType.START.value: StreamStart,
-        ResponseType.FINISH.value: StreamFinish,
-        ResponseType.TEXT_START.value: StreamTextStart,
-        ResponseType.TEXT_DELTA.value: StreamTextDelta,
-        ResponseType.TEXT_END.value: StreamTextEnd,
-        ResponseType.TOOL_INPUT_START.value: StreamToolInputStart,
-        ResponseType.TOOL_INPUT_AVAILABLE.value: StreamToolInputAvailable,
-        ResponseType.TOOL_OUTPUT_AVAILABLE.value: StreamToolOutputAvailable,
-        ResponseType.ERROR.value: StreamError,
-        ResponseType.USAGE.value: StreamUsage,
-        ResponseType.HEARTBEAT.value: StreamHeartbeat,
-    }
-
-    chunk_type = chunk_data.get("type")
-    chunk_class = type_to_class.get(chunk_type)  # type: ignore[arg-type]
-
-    if chunk_class is None:
-        logger.warning(f"Unknown chunk type: {chunk_type}")
-        return None
-
-    try:
-        return chunk_class(**chunk_data)
-    except Exception as e:
-        logger.warning(f"Failed to reconstruct chunk of type {chunk_type}: {e}")
-        return None
-
-
-async def set_task_asyncio_task(task_id: str, asyncio_task: asyncio.Task) -> None:
-    """Track the asyncio.Task for a task (local reference only).
-
-    This is just for cleanup purposes - the task state is in Redis.
-
-    Args:
-        task_id: Task ID
-        asyncio_task: The asyncio Task to track
-    """
-    _local_tasks[task_id] = asyncio_task
-
-
-async def unsubscribe_from_task(
-    task_id: str,
-    subscriber_queue: asyncio.Queue[StreamBaseResponse],
-) -> None:
-    """Clean up when a subscriber disconnects.
-
-    Cancels the XREAD-based listener task associated with this subscriber queue
-    to prevent resource leaks.
-
-    Args:
-        task_id: Task ID
-        subscriber_queue: The subscriber's queue used to look up the listener task
-    """
-    queue_id = id(subscriber_queue)
-    listener_entry = _listener_tasks.pop(queue_id, None)
-
-    if listener_entry is None:
-        logger.debug(
-            f"No listener task found for task {task_id} queue {queue_id} "
-            "(may have already completed)"
-        )
-        return
-
-    stored_task_id, listener_task = listener_entry
-
-    if stored_task_id != task_id:
-        logger.warning(
-            f"Task ID mismatch in unsubscribe: expected {task_id}, "
-            f"found {stored_task_id}"
-        )
-
-    if listener_task.done():
-        logger.debug(f"Listener task for task {task_id} already completed")
-        return
-
-    # Cancel the listener task
-    listener_task.cancel()
-
-    try:
-        # Wait for the task to be cancelled with a timeout
-        await asyncio.wait_for(listener_task, timeout=5.0)
-    except asyncio.CancelledError:
-        # Expected - the task was successfully cancelled
-        pass
-    except asyncio.TimeoutError:
-        logger.warning(
-            f"Timeout waiting for listener task cancellation for task {task_id}"
-        )
-    except Exception as e:
-        logger.error(f"Error during listener task cancellation for task {task_id}: {e}")
-
-    logger.debug(f"Successfully unsubscribed from task {task_id}")

autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/service.py

@@ -1,498 +0,0 @@
-"""External Agent Generator service client.
-
-This module provides a client for communicating with the external Agent Generator
-microservice. When AGENTGENERATOR_HOST is configured, the agent generation functions
-will delegate to the external service instead of using the built-in LLM-based implementation.
-"""
-
-import logging
-from typing import Any
-
-import httpx
-
-from backend.util.settings import Settings
-
-logger = logging.getLogger(__name__)
-
-
-def _create_error_response(
-    error_message: str,
-    error_type: str = "unknown",
-    details: dict[str, Any] | None = None,
-) -> dict[str, Any]:
-    """Create a standardized error response dict.
-
-    Args:
-        error_message: Human-readable error message
-        error_type: Machine-readable error type
-        details: Optional additional error details
-
-    Returns:
-        Error dict with type="error" and error details
-    """
-    response: dict[str, Any] = {
-        "type": "error",
-        "error": error_message,
-        "error_type": error_type,
-    }
-    if details:
-        response["details"] = details
-    return response
-
-
-def _classify_http_error(e: httpx.HTTPStatusError) -> tuple[str, str]:
-    """Classify an HTTP error into error_type and message.
-
-    Args:
-        e: The HTTP status error
-
-    Returns:
-        Tuple of (error_type, error_message)
-    """
-    status = e.response.status_code
-    if status == 429:
-        return "rate_limit", f"Agent Generator rate limited: {e}"
-    elif status == 503:
-        return "service_unavailable", f"Agent Generator unavailable: {e}"
-    elif status == 504 or status == 408:
-        return "timeout", f"Agent Generator timed out: {e}"
-    else:
-        return "http_error", f"HTTP error calling Agent Generator: {e}"
-
-
-def _classify_request_error(e: httpx.RequestError) -> tuple[str, str]:
-    """Classify a request error into error_type and message.
-
-    Args:
-        e: The request error
-
-    Returns:
-        Tuple of (error_type, error_message)
-    """
-    error_str = str(e).lower()
-    if "timeout" in error_str or "timed out" in error_str:
-        return "timeout", f"Agent Generator request timed out: {e}"
-    elif "connect" in error_str:
-        return "connection_error", f"Could not connect to Agent Generator: {e}"
-    else:
-        return "request_error", f"Request error calling Agent Generator: {e}"
-
-
-_client: httpx.AsyncClient | None = None
-_settings: Settings | None = None
-
-
-def _get_settings() -> Settings:
-    """Get or create settings singleton."""
-    global _settings
-    if _settings is None:
-        _settings = Settings()
-    return _settings
-
-
-def is_external_service_configured() -> bool:
-    """Check if external Agent Generator service is configured."""
-    settings = _get_settings()
-    return bool(settings.config.agentgenerator_host)
-
-
-def _get_base_url() -> str:
-    """Get the base URL for the external service."""
-    settings = _get_settings()
-    host = settings.config.agentgenerator_host
-    port = settings.config.agentgenerator_port
-    return f"http://{host}:{port}"
-
-
-def _get_client() -> httpx.AsyncClient:
-    """Get or create the HTTP client for the external service."""
-    global _client
-    if _client is None:
-        settings = _get_settings()
-        _client = httpx.AsyncClient(
-            base_url=_get_base_url(),
-            timeout=httpx.Timeout(settings.config.agentgenerator_timeout),
-        )
-    return _client
-
-
-async def decompose_goal_external(
-    description: str,
-    context: str = "",
-    library_agents: list[dict[str, Any]] | None = None,
-) -> dict[str, Any] | None:
-    """Call the external service to decompose a goal.
-
-    Args:
-        description: Natural language goal description
-        context: Additional context (e.g., answers to previous questions)
-        library_agents: User's library agents available for sub-agent composition
-
-    Returns:
-        Dict with either:
-        - {"type": "clarifying_questions", "questions": [...]}
-        - {"type": "instructions", "steps": [...]}
-        - {"type": "unachievable_goal", ...}
-        - {"type": "vague_goal", ...}
-        - {"type": "error", "error": "...", "error_type": "..."} on error
-        Or None on unexpected error
-    """
-    client = _get_client()
-
-    if context:
-        description = f"{description}\n\nAdditional context from user:\n{context}"
-
-    payload: dict[str, Any] = {"description": description}
-    if library_agents:
-        payload["library_agents"] = library_agents
-
-    try:
-        response = await client.post("/api/decompose-description", json=payload)
-        response.raise_for_status()
-        data = response.json()
-
-        if not data.get("success"):
-            error_msg = data.get("error", "Unknown error from Agent Generator")
-            error_type = data.get("error_type", "unknown")
-            logger.error(
-                f"Agent Generator decomposition failed: {error_msg} "
-                f"(type: {error_type})"
-            )
-            return _create_error_response(error_msg, error_type)
-
-        # Map the response to the expected format
-        response_type = data.get("type")
-        if response_type == "instructions":
-            return {"type": "instructions", "steps": data.get("steps", [])}
-        elif response_type == "clarifying_questions":
-            return {
-                "type": "clarifying_questions",
-                "questions": data.get("questions", []),
-            }
-        elif response_type == "unachievable_goal":
-            return {
-                "type": "unachievable_goal",
-                "reason": data.get("reason"),
-                "suggested_goal": data.get("suggested_goal"),
-            }
-        elif response_type == "vague_goal":
-            return {
-                "type": "vague_goal",
-                "suggested_goal": data.get("suggested_goal"),
-            }
-        elif response_type == "error":
-            # Pass through error from the service
-            return _create_error_response(
-                data.get("error", "Unknown error"),
-                data.get("error_type", "unknown"),
-            )
-        else:
-            logger.error(
-                f"Unknown response type from external service: {response_type}"
-            )
-            return _create_error_response(
-                f"Unknown response type from Agent Generator: {response_type}",
-                "invalid_response",
-            )
-
-    except httpx.HTTPStatusError as e:
-        error_type, error_msg = _classify_http_error(e)
-        logger.error(error_msg)
-        return _create_error_response(error_msg, error_type)
-    except httpx.RequestError as e:
-        error_type, error_msg = _classify_request_error(e)
-        logger.error(error_msg)
-        return _create_error_response(error_msg, error_type)
-    except Exception as e:
-        error_msg = f"Unexpected error calling Agent Generator: {e}"
-        logger.error(error_msg)
-        return _create_error_response(error_msg, "unexpected_error")
-
-
-async def generate_agent_external(
-    instructions: dict[str, Any],
-    library_agents: list[dict[str, Any]] | None = None,
-    operation_id: str | None = None,
-    task_id: str | None = None,
-) -> dict[str, Any] | None:
-    """Call the external service to generate an agent from instructions.
-
-    Args:
-        instructions: Structured instructions from decompose_goal
-        library_agents: User's library agents available for sub-agent composition
-        operation_id: Operation ID for async processing (enables Redis Streams callback)
-        task_id: Task ID for async processing (enables Redis Streams callback)
-
-    Returns:
-        Agent JSON dict, {"status": "accepted"} for async, or error dict {"type": "error", ...} on error
-    """
-    client = _get_client()
-
-    # Build request payload
-    payload: dict[str, Any] = {"instructions": instructions}
-    if library_agents:
-        payload["library_agents"] = library_agents
-    if operation_id and task_id:
-        payload["operation_id"] = operation_id
-        payload["task_id"] = task_id
-
-    try:
-        response = await client.post("/api/generate-agent", json=payload)
-
-        # Handle 202 Accepted for async processing
-        if response.status_code == 202:
-            logger.info(
-                f"Agent Generator accepted async request "
-                f"(operation_id={operation_id}, task_id={task_id})"
-            )
-            return {
-                "status": "accepted",
-                "operation_id": operation_id,
-                "task_id": task_id,
-            }
-
-        response.raise_for_status()
-        data = response.json()
-
-        if not data.get("success"):
-            error_msg = data.get("error", "Unknown error from Agent Generator")
-            error_type = data.get("error_type", "unknown")
-            logger.error(
-                f"Agent Generator generation failed: {error_msg} (type: {error_type})"
-            )
-            return _create_error_response(error_msg, error_type)
-
-        return data.get("agent_json")
-
-    except httpx.HTTPStatusError as e:
-        error_type, error_msg = _classify_http_error(e)
-        logger.error(error_msg)
-        return _create_error_response(error_msg, error_type)
-    except httpx.RequestError as e:
-        error_type, error_msg = _classify_request_error(e)
-        logger.error(error_msg)
-        return _create_error_response(error_msg, error_type)
-    except Exception as e:
-        error_msg = f"Unexpected error calling Agent Generator: {e}"
-        logger.error(error_msg)
-        return _create_error_response(error_msg, "unexpected_error")
-
-
-async def generate_agent_patch_external(
-    update_request: str,
-    current_agent: dict[str, Any],
-    library_agents: list[dict[str, Any]] | None = None,
-    operation_id: str | None = None,
-    task_id: str | None = None,
-) -> dict[str, Any] | None:
-    """Call the external service to generate a patch for an existing agent.
-
-    Args:
-        update_request: Natural language description of changes
-        current_agent: Current agent JSON
-        library_agents: User's library agents available for sub-agent composition
-        operation_id: Operation ID for async processing (enables Redis Streams callback)
-        task_id: Task ID for async processing (enables Redis Streams callback)
-
-    Returns:
-        Updated agent JSON, clarifying questions dict, {"status": "accepted"} for async, or error dict on error
-    """
-    client = _get_client()
-
-    # Build request payload
-    payload: dict[str, Any] = {
-        "update_request": update_request,
-        "current_agent_json": current_agent,
-    }
-    if library_agents:
-        payload["library_agents"] = library_agents
-    if operation_id and task_id:
-        payload["operation_id"] = operation_id
-        payload["task_id"] = task_id
-
-    try:
-        response = await client.post("/api/update-agent", json=payload)
-
-        # Handle 202 Accepted for async processing
-        if response.status_code == 202:
-            logger.info(
-                f"Agent Generator accepted async update request "
-                f"(operation_id={operation_id}, task_id={task_id})"
-            )
-            return {
-                "status": "accepted",
-                "operation_id": operation_id,
-                "task_id": task_id,
-            }
-
-        response.raise_for_status()
-        data = response.json()
-
-        if not data.get("success"):
-            error_msg = data.get("error", "Unknown error from Agent Generator")
-            error_type = data.get("error_type", "unknown")
-            logger.error(
-                f"Agent Generator patch generation failed: {error_msg} "
-                f"(type: {error_type})"
-            )
-            return _create_error_response(error_msg, error_type)
-
-        # Check if it's clarifying questions
-        if data.get("type") == "clarifying_questions":
-            return {
-                "type": "clarifying_questions",
-                "questions": data.get("questions", []),
-            }
-
-        # Check if it's an error passed through
-        if data.get("type") == "error":
-            return _create_error_response(
-                data.get("error", "Unknown error"),
-                data.get("error_type", "unknown"),
-            )
-
-        # Otherwise return the updated agent JSON
-        return data.get("agent_json")
-
-    except httpx.HTTPStatusError as e:
-        error_type, error_msg = _classify_http_error(e)
-        logger.error(error_msg)
-        return _create_error_response(error_msg, error_type)
-    except httpx.RequestError as e:
-        error_type, error_msg = _classify_request_error(e)
-        logger.error(error_msg)
-        return _create_error_response(error_msg, error_type)
-    except Exception as e:
-        error_msg = f"Unexpected error calling Agent Generator: {e}"
-        logger.error(error_msg)
-        return _create_error_response(error_msg, "unexpected_error")
-
-
-async def customize_template_external(
-    template_agent: dict[str, Any],
-    modification_request: str,
-    context: str = "",
-) -> dict[str, Any] | None:
-    """Call the external service to customize a template/marketplace agent.
-
-    Args:
-        template_agent: The template agent JSON to customize
-        modification_request: Natural language description of customizations
-        context: Additional context (e.g., answers to previous questions)
-
-    Returns:
-        Customized agent JSON, clarifying questions dict, or error dict on error
-    """
-    client = _get_client()
-
-    request = modification_request
-    if context:
-        request = f"{modification_request}\n\nAdditional context from user:\n{context}"
-
-    payload: dict[str, Any] = {
-        "template_agent_json": template_agent,
-        "modification_request": request,
-    }
-
-    try:
-        response = await client.post("/api/template-modification", json=payload)
-        response.raise_for_status()
-        data = response.json()
-
-        if not data.get("success"):
-            error_msg = data.get("error", "Unknown error from Agent Generator")
-            error_type = data.get("error_type", "unknown")
-            logger.error(
-                f"Agent Generator template customization failed: {error_msg} "
-                f"(type: {error_type})"
-            )
-            return _create_error_response(error_msg, error_type)
-
-        # Check if it's clarifying questions
-        if data.get("type") == "clarifying_questions":
-            return {
-                "type": "clarifying_questions",
-                "questions": data.get("questions", []),
-            }
-
-        # Check if it's an error passed through
-        if data.get("type") == "error":
-            return _create_error_response(
-                data.get("error", "Unknown error"),
-                data.get("error_type", "unknown"),
-            )
-
-        # Otherwise return the customized agent JSON
-        return data.get("agent_json")
-
-    except httpx.HTTPStatusError as e:
-        error_type, error_msg = _classify_http_error(e)
-        logger.error(error_msg)
-        return _create_error_response(error_msg, error_type)
-    except httpx.RequestError as e:
-        error_type, error_msg = _classify_request_error(e)
-        logger.error(error_msg)
-        return _create_error_response(error_msg, error_type)
-    except Exception as e:
-        error_msg = f"Unexpected error calling Agent Generator: {e}"
-        logger.error(error_msg)
-        return _create_error_response(error_msg, "unexpected_error")
-
-
-async def get_blocks_external() -> list[dict[str, Any]] | None:
-    """Get available blocks from the external service.
-
-    Returns:
-        List of block info dicts or None on error
-    """
-    client = _get_client()
-
-    try:
-        response = await client.get("/api/blocks")
-        response.raise_for_status()
-        data = response.json()
-
-        if not data.get("success"):
-            logger.error("External service returned error getting blocks")
-            return None
-
-        return data.get("blocks", [])
-
-    except httpx.HTTPStatusError as e:
-        logger.error(f"HTTP error getting blocks from external service: {e}")
-        return None
-    except httpx.RequestError as e:
-        logger.error(f"Request error getting blocks from external service: {e}")
-        return None
-    except Exception as e:
-        logger.error(f"Unexpected error getting blocks from external service: {e}")
-        return None
-
-
-async def health_check() -> bool:
-    """Check if the external service is healthy.
-
-    Returns:
-        True if healthy, False otherwise
-    """
-    if not is_external_service_configured():
-        return False
-
-    client = _get_client()
-
-    try:
-        response = await client.get("/health")
-        response.raise_for_status()
-        data = response.json()
-        return data.get("status") == "healthy" and data.get("blocks_loaded", False)
-    except Exception as e:
-        logger.warning(f"External agent generator health check failed: {e}")
-        return False
-
-
-async def close_client() -> None:
-    """Close the HTTP client."""
-    global _client
-    if _client is not None:
-        await _client.aclose()
-        _client = None

autogpt_platform/backend/backend/api/features/chat/tools/base.py

@@ -1,129 +0,0 @@
-"""Base classes and shared utilities for chat tools."""
-
-import logging
-from typing import Any
-
-from openai.types.chat import ChatCompletionToolParam
-
-from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.response_model import StreamToolOutputAvailable
-
-from .models import ErrorResponse, NeedLoginResponse, ToolResponseBase
-
-logger = logging.getLogger(__name__)
-
-
-class BaseTool:
-    """Base class for all chat tools."""
-
-    @property
-    def name(self) -> str:
-        """Tool name for OpenAI function calling."""
-        raise NotImplementedError
-
-    @property
-    def description(self) -> str:
-        """Tool description for OpenAI."""
-        raise NotImplementedError
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        """Tool parameters schema for OpenAI."""
-        raise NotImplementedError
-
-    @property
-    def requires_auth(self) -> bool:
-        """Whether this tool requires authentication."""
-        return False
-
-    @property
-    def is_long_running(self) -> bool:
-        """Whether this tool is long-running and should execute in background.
-
-        Long-running tools (like agent generation) are executed via background
-        tasks to survive SSE disconnections. The result is persisted to chat
-        history and visible when the user refreshes.
-        """
-        return False
-
-    def as_openai_tool(self) -> ChatCompletionToolParam:
-        """Convert to OpenAI tool format."""
-        return ChatCompletionToolParam(
-            type="function",
-            function={
-                "name": self.name,
-                "description": self.description,
-                "parameters": self.parameters,
-            },
-        )
-
-    async def execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        tool_call_id: str,
-        **kwargs,
-    ) -> StreamToolOutputAvailable:
-        """Execute the tool with authentication check.
-
-        Args:
-            user_id: User ID (may be anonymous like "anon_123")
-            session_id: Chat session ID
-            **kwargs: Tool-specific parameters
-
-        Returns:
-            Pydantic response object
-
-        """
-        if self.requires_auth and not user_id:
-            logger.error(
-                f"Attempted tool call for {self.name} but user not authenticated"
-            )
-            return StreamToolOutputAvailable(
-                toolCallId=tool_call_id,
-                toolName=self.name,
-                output=NeedLoginResponse(
-                    message=f"Please sign in to use {self.name}",
-                    session_id=session.session_id,
-                ).model_dump_json(),
-                success=False,
-            )
-
-        try:
-            result = await self._execute(user_id, session, **kwargs)
-            return StreamToolOutputAvailable(
-                toolCallId=tool_call_id,
-                toolName=self.name,
-                output=result.model_dump_json(),
-            )
-        except Exception as e:
-            logger.error(f"Error in {self.name}: {e}", exc_info=True)
-            return StreamToolOutputAvailable(
-                toolCallId=tool_call_id,
-                toolName=self.name,
-                output=ErrorResponse(
-                    message=f"An error occurred while executing {self.name}",
-                    error=str(e),
-                    session_id=session.session_id,
-                ).model_dump_json(),
-                success=False,
-            )
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        """Internal execution logic to be implemented by subclasses.
-
-        Args:
-            user_id: User ID (authenticated or anonymous)
-            session_id: Chat session ID
-            **kwargs: Tool-specific parameters
-
-        Returns:
-            Pydantic response object
-
-        """
-        raise NotImplementedError

autogpt_platform/backend/backend/api/features/chat/tools/create_agent.py

@@ -1,335 +0,0 @@
-"""CreateAgentTool - Creates agents from natural language descriptions."""
-
-import logging
-from typing import Any
-
-from backend.api.features.chat.model import ChatSession
-
-from .agent_generator import (
-    AgentGeneratorNotConfiguredError,
-    decompose_goal,
-    enrich_library_agents_from_steps,
-    generate_agent,
-    get_all_relevant_agents_for_generation,
-    get_user_message_for_error,
-    save_agent_to_library,
-)
-from .base import BaseTool
-from .models import (
-    AgentPreviewResponse,
-    AgentSavedResponse,
-    AsyncProcessingResponse,
-    ClarificationNeededResponse,
-    ClarifyingQuestion,
-    ErrorResponse,
-    ToolResponseBase,
-)
-
-logger = logging.getLogger(__name__)
-
-
-class CreateAgentTool(BaseTool):
-    """Tool for creating agents from natural language descriptions."""
-
-    @property
-    def name(self) -> str:
-        return "create_agent"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Create a new agent workflow from a natural language description. "
-            "First generates a preview, then saves to library if save=true."
-        )
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    @property
-    def is_long_running(self) -> bool:
-        return True
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "description": {
-                    "type": "string",
-                    "description": (
-                        "Natural language description of what the agent should do. "
-                        "Be specific about inputs, outputs, and the workflow steps."
-                    ),
-                },
-                "context": {
-                    "type": "string",
-                    "description": (
-                        "Additional context or answers to previous clarifying questions. "
-                        "Include any preferences or constraints mentioned by the user."
-                    ),
-                },
-                "save": {
-                    "type": "boolean",
-                    "description": (
-                        "Whether to save the agent to the user's library. "
-                        "Default is true. Set to false for preview only."
-                    ),
-                    "default": True,
-                },
-            },
-            "required": ["description"],
-        }
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        """Execute the create_agent tool.
-
-        Flow:
-        1. Decompose the description into steps (may return clarifying questions)
-        2. Generate agent JSON (external service handles fixing and validation)
-        3. Preview or save based on the save parameter
-        """
-        description = kwargs.get("description", "").strip()
-        context = kwargs.get("context", "")
-        save = kwargs.get("save", True)
-        session_id = session.session_id if session else None
-
-        # Extract async processing params (passed by long-running tool handler)
-        operation_id = kwargs.get("_operation_id")
-        task_id = kwargs.get("_task_id")
-
-        if not description:
-            return ErrorResponse(
-                message="Please provide a description of what the agent should do.",
-                error="Missing description parameter",
-                session_id=session_id,
-            )
-
-        library_agents = None
-        if user_id:
-            try:
-                library_agents = await get_all_relevant_agents_for_generation(
-                    user_id=user_id,
-                    search_query=description,
-                    include_marketplace=True,
-                )
-                logger.debug(
-                    f"Found {len(library_agents)} relevant agents for sub-agent composition"
-                )
-            except Exception as e:
-                logger.warning(f"Failed to fetch library agents: {e}")
-
-        try:
-            decomposition_result = await decompose_goal(
-                description, context, library_agents
-            )
-        except AgentGeneratorNotConfiguredError:
-            return ErrorResponse(
-                message=(
-                    "Agent generation is not available. "
-                    "The Agent Generator service is not configured."
-                ),
-                error="service_not_configured",
-                session_id=session_id,
-            )
-
-        if decomposition_result is None:
-            return ErrorResponse(
-                message="Failed to analyze the goal. The agent generation service may be unavailable. Please try again.",
-                error="decomposition_failed",
-                details={"description": description[:100]},
-                session_id=session_id,
-            )
-
-        if decomposition_result.get("type") == "error":
-            error_msg = decomposition_result.get("error", "Unknown error")
-            error_type = decomposition_result.get("error_type", "unknown")
-            user_message = get_user_message_for_error(
-                error_type,
-                operation="analyze the goal",
-                llm_parse_message="The AI had trouble understanding this request. Please try rephrasing your goal.",
-            )
-            return ErrorResponse(
-                message=user_message,
-                error=f"decomposition_failed:{error_type}",
-                details={
-                    "description": description[:100],
-                    "service_error": error_msg,
-                    "error_type": error_type,
-                },
-                session_id=session_id,
-            )
-
-        if decomposition_result.get("type") == "clarifying_questions":
-            questions = decomposition_result.get("questions", [])
-            return ClarificationNeededResponse(
-                message=(
-                    "I need some more information to create this agent. "
-                    "Please answer the following questions:"
-                ),
-                questions=[
-                    ClarifyingQuestion(
-                        question=q.get("question", ""),
-                        keyword=q.get("keyword", ""),
-                        example=q.get("example"),
-                    )
-                    for q in questions
-                ],
-                session_id=session_id,
-            )
-
-        if decomposition_result.get("type") == "unachievable_goal":
-            suggested = decomposition_result.get("suggested_goal", "")
-            reason = decomposition_result.get("reason", "")
-            return ErrorResponse(
-                message=(
-                    f"This goal cannot be accomplished with the available blocks. "
-                    f"{reason} "
-                    f"Suggestion: {suggested}"
-                ),
-                error="unachievable_goal",
-                details={"suggested_goal": suggested, "reason": reason},
-                session_id=session_id,
-            )
-
-        if decomposition_result.get("type") == "vague_goal":
-            suggested = decomposition_result.get("suggested_goal", "")
-            return ErrorResponse(
-                message=(
-                    f"The goal is too vague to create a specific workflow. "
-                    f"Suggestion: {suggested}"
-                ),
-                error="vague_goal",
-                details={"suggested_goal": suggested},
-                session_id=session_id,
-            )
-
-        if user_id and library_agents is not None:
-            try:
-                library_agents = await enrich_library_agents_from_steps(
-                    user_id=user_id,
-                    decomposition_result=decomposition_result,
-                    existing_agents=library_agents,
-                    include_marketplace=True,
-                )
-                logger.debug(
-                    f"After enrichment: {len(library_agents)} total agents for sub-agent composition"
-                )
-            except Exception as e:
-                logger.warning(f"Failed to enrich library agents from steps: {e}")
-
-        try:
-            agent_json = await generate_agent(
-                decomposition_result,
-                library_agents,
-                operation_id=operation_id,
-                task_id=task_id,
-            )
-        except AgentGeneratorNotConfiguredError:
-            return ErrorResponse(
-                message=(
-                    "Agent generation is not available. "
-                    "The Agent Generator service is not configured."
-                ),
-                error="service_not_configured",
-                session_id=session_id,
-            )
-
-        if agent_json is None:
-            return ErrorResponse(
-                message="Failed to generate the agent. The agent generation service may be unavailable. Please try again.",
-                error="generation_failed",
-                details={"description": description[:100]},
-                session_id=session_id,
-            )
-
-        if isinstance(agent_json, dict) and agent_json.get("type") == "error":
-            error_msg = agent_json.get("error", "Unknown error")
-            error_type = agent_json.get("error_type", "unknown")
-            user_message = get_user_message_for_error(
-                error_type,
-                operation="generate the agent",
-                llm_parse_message="The AI had trouble generating the agent. Please try again or simplify your goal.",
-                validation_message=(
-                    "I wasn't able to create a valid agent for this request. "
-                    "The generated workflow had some structural issues. "
-                    "Please try simplifying your goal or breaking it into smaller steps."
-                ),
-                error_details=error_msg,
-            )
-            return ErrorResponse(
-                message=user_message,
-                error=f"generation_failed:{error_type}",
-                details={
-                    "description": description[:100],
-                    "service_error": error_msg,
-                    "error_type": error_type,
-                },
-                session_id=session_id,
-            )
-
-        # Check if Agent Generator accepted for async processing
-        if agent_json.get("status") == "accepted":
-            logger.info(
-                f"Agent generation delegated to async processing "
-                f"(operation_id={operation_id}, task_id={task_id})"
-            )
-            return AsyncProcessingResponse(
-                message="Agent generation started. You'll be notified when it's complete.",
-                operation_id=operation_id,
-                task_id=task_id,
-                session_id=session_id,
-            )
-
-        agent_name = agent_json.get("name", "Generated Agent")
-        agent_description = agent_json.get("description", "")
-        node_count = len(agent_json.get("nodes", []))
-        link_count = len(agent_json.get("links", []))
-
-        if not save:
-            return AgentPreviewResponse(
-                message=(
-                    f"I've generated an agent called '{agent_name}' with {node_count} blocks. "
-                    f"Review it and call create_agent with save=true to save it to your library."
-                ),
-                agent_json=agent_json,
-                agent_name=agent_name,
-                description=agent_description,
-                node_count=node_count,
-                link_count=link_count,
-                session_id=session_id,
-            )
-
-        if not user_id:
-            return ErrorResponse(
-                message="You must be logged in to save agents.",
-                error="auth_required",
-                session_id=session_id,
-            )
-
-        try:
-            created_graph, library_agent = await save_agent_to_library(
-                agent_json, user_id
-            )
-
-            return AgentSavedResponse(
-                message=f"Agent '{created_graph.name}' has been saved to your library!",
-                agent_id=created_graph.id,
-                agent_name=created_graph.name,
-                library_agent_id=library_agent.id,
-                library_agent_link=f"/library/agents/{library_agent.id}",
-                agent_page_link=f"/build?flowID={created_graph.id}",
-                session_id=session_id,
-            )
-        except Exception as e:
-            return ErrorResponse(
-                message=f"Failed to save the agent: {str(e)}",
-                error="save_failed",
-                details={"exception": str(e)},
-                session_id=session_id,
-            )

autogpt_platform/backend/backend/api/features/chat/tools/customize_agent.py

@@ -1,337 +0,0 @@
-"""CustomizeAgentTool - Customizes marketplace/template agents using natural language."""
-
-import logging
-from typing import Any
-
-from backend.api.features.chat.model import ChatSession
-from backend.api.features.store import db as store_db
-from backend.api.features.store.exceptions import AgentNotFoundError
-
-from .agent_generator import (
-    AgentGeneratorNotConfiguredError,
-    customize_template,
-    get_user_message_for_error,
-    graph_to_json,
-    save_agent_to_library,
-)
-from .base import BaseTool
-from .models import (
-    AgentPreviewResponse,
-    AgentSavedResponse,
-    ClarificationNeededResponse,
-    ClarifyingQuestion,
-    ErrorResponse,
-    ToolResponseBase,
-)
-
-logger = logging.getLogger(__name__)
-
-
-class CustomizeAgentTool(BaseTool):
-    """Tool for customizing marketplace/template agents using natural language."""
-
-    @property
-    def name(self) -> str:
-        return "customize_agent"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Customize a marketplace or template agent using natural language. "
-            "Takes an existing agent from the marketplace and modifies it based on "
-            "the user's requirements before adding to their library."
-        )
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    @property
-    def is_long_running(self) -> bool:
-        return True
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "agent_id": {
-                    "type": "string",
-                    "description": (
-                        "The marketplace agent ID in format 'creator/slug' "
-                        "(e.g., 'autogpt/newsletter-writer'). "
-                        "Get this from find_agent results."
-                    ),
-                },
-                "modifications": {
-                    "type": "string",
-                    "description": (
-                        "Natural language description of how to customize the agent. "
-                        "Be specific about what changes you want to make."
-                    ),
-                },
-                "context": {
-                    "type": "string",
-                    "description": (
-                        "Additional context or answers to previous clarifying questions."
-                    ),
-                },
-                "save": {
-                    "type": "boolean",
-                    "description": (
-                        "Whether to save the customized agent to the user's library. "
-                        "Default is true. Set to false for preview only."
-                    ),
-                    "default": True,
-                },
-            },
-            "required": ["agent_id", "modifications"],
-        }
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        """Execute the customize_agent tool.
-
-        Flow:
-        1. Parse the agent ID to get creator/slug
-        2. Fetch the template agent from the marketplace
-        3. Call customize_template with the modification request
-        4. Preview or save based on the save parameter
-        """
-        agent_id = kwargs.get("agent_id", "").strip()
-        modifications = kwargs.get("modifications", "").strip()
-        context = kwargs.get("context", "")
-        save = kwargs.get("save", True)
-        session_id = session.session_id if session else None
-
-        if not agent_id:
-            return ErrorResponse(
-                message="Please provide the marketplace agent ID (e.g., 'creator/agent-name').",
-                error="missing_agent_id",
-                session_id=session_id,
-            )
-
-        if not modifications:
-            return ErrorResponse(
-                message="Please describe how you want to customize this agent.",
-                error="missing_modifications",
-                session_id=session_id,
-            )
-
-        # Parse agent_id in format "creator/slug"
-        parts = [p.strip() for p in agent_id.split("/")]
-        if len(parts) != 2 or not parts[0] or not parts[1]:
-            return ErrorResponse(
-                message=(
-                    f"Invalid agent ID format: '{agent_id}'. "
-                    "Expected format is 'creator/agent-name' "
-                    "(e.g., 'autogpt/newsletter-writer')."
-                ),
-                error="invalid_agent_id_format",
-                session_id=session_id,
-            )
-
-        creator_username, agent_slug = parts
-
-        # Fetch the marketplace agent details
-        try:
-            agent_details = await store_db.get_store_agent_details(
-                username=creator_username, agent_name=agent_slug
-            )
-        except AgentNotFoundError:
-            return ErrorResponse(
-                message=(
-                    f"Could not find marketplace agent '{agent_id}'. "
-                    "Please check the agent ID and try again."
-                ),
-                error="agent_not_found",
-                session_id=session_id,
-            )
-        except Exception as e:
-            logger.error(f"Error fetching marketplace agent {agent_id}: {e}")
-            return ErrorResponse(
-                message="Failed to fetch the marketplace agent. Please try again.",
-                error="fetch_error",
-                session_id=session_id,
-            )
-
-        if not agent_details.store_listing_version_id:
-            return ErrorResponse(
-                message=(
-                    f"The agent '{agent_id}' does not have an available version. "
-                    "Please try a different agent."
-                ),
-                error="no_version_available",
-                session_id=session_id,
-            )
-
-        # Get the full agent graph
-        try:
-            graph = await store_db.get_agent(agent_details.store_listing_version_id)
-            template_agent = graph_to_json(graph)
-        except Exception as e:
-            logger.error(f"Error fetching agent graph for {agent_id}: {e}")
-            return ErrorResponse(
-                message="Failed to fetch the agent configuration. Please try again.",
-                error="graph_fetch_error",
-                session_id=session_id,
-            )
-
-        # Call customize_template
-        try:
-            result = await customize_template(
-                template_agent=template_agent,
-                modification_request=modifications,
-                context=context,
-            )
-        except AgentGeneratorNotConfiguredError:
-            return ErrorResponse(
-                message=(
-                    "Agent customization is not available. "
-                    "The Agent Generator service is not configured."
-                ),
-                error="service_not_configured",
-                session_id=session_id,
-            )
-        except Exception as e:
-            logger.error(f"Error calling customize_template for {agent_id}: {e}")
-            return ErrorResponse(
-                message=(
-                    "Failed to customize the agent due to a service error. "
-                    "Please try again."
-                ),
-                error="customization_service_error",
-                session_id=session_id,
-            )
-
-        if result is None:
-            return ErrorResponse(
-                message=(
-                    "Failed to customize the agent. "
-                    "The agent generation service may be unavailable or timed out. "
-                    "Please try again."
-                ),
-                error="customization_failed",
-                session_id=session_id,
-            )
-
-        # Handle error response
-        if isinstance(result, dict) and result.get("type") == "error":
-            error_msg = result.get("error", "Unknown error")
-            error_type = result.get("error_type", "unknown")
-            user_message = get_user_message_for_error(
-                error_type,
-                operation="customize the agent",
-                llm_parse_message=(
-                    "The AI had trouble customizing the agent. "
-                    "Please try again or simplify your request."
-                ),
-                validation_message=(
-                    "The customized agent failed validation. "
-                    "Please try rephrasing your request."
-                ),
-                error_details=error_msg,
-            )
-            return ErrorResponse(
-                message=user_message,
-                error=f"customization_failed:{error_type}",
-                session_id=session_id,
-            )
-
-        # Handle clarifying questions
-        if isinstance(result, dict) and result.get("type") == "clarifying_questions":
-            questions = result.get("questions") or []
-            if not isinstance(questions, list):
-                logger.error(
-                    f"Unexpected clarifying questions format: {type(questions)}"
-                )
-                questions = []
-            return ClarificationNeededResponse(
-                message=(
-                    "I need some more information to customize this agent. "
-                    "Please answer the following questions:"
-                ),
-                questions=[
-                    ClarifyingQuestion(
-                        question=q.get("question", ""),
-                        keyword=q.get("keyword", ""),
-                        example=q.get("example"),
-                    )
-                    for q in questions
-                    if isinstance(q, dict)
-                ],
-                session_id=session_id,
-            )
-
-        # Result should be the customized agent JSON
-        if not isinstance(result, dict):
-            logger.error(f"Unexpected customize_template response type: {type(result)}")
-            return ErrorResponse(
-                message="Failed to customize the agent due to an unexpected response.",
-                error="unexpected_response_type",
-                session_id=session_id,
-            )
-
-        customized_agent = result
-
-        agent_name = customized_agent.get(
-            "name", f"Customized {agent_details.agent_name}"
-        )
-        agent_description = customized_agent.get("description", "")
-        nodes = customized_agent.get("nodes")
-        links = customized_agent.get("links")
-        node_count = len(nodes) if isinstance(nodes, list) else 0
-        link_count = len(links) if isinstance(links, list) else 0
-
-        if not save:
-            return AgentPreviewResponse(
-                message=(
-                    f"I've customized the agent '{agent_details.agent_name}'. "
-                    f"The customized agent has {node_count} blocks. "
-                    f"Review it and call customize_agent with save=true to save it."
-                ),
-                agent_json=customized_agent,
-                agent_name=agent_name,
-                description=agent_description,
-                node_count=node_count,
-                link_count=link_count,
-                session_id=session_id,
-            )
-
-        if not user_id:
-            return ErrorResponse(
-                message="You must be logged in to save agents.",
-                error="auth_required",
-                session_id=session_id,
-            )
-
-        # Save to user's library
-        try:
-            created_graph, library_agent = await save_agent_to_library(
-                customized_agent, user_id, is_update=False
-            )
-
-            return AgentSavedResponse(
-                message=(
-                    f"Customized agent '{created_graph.name}' "
-                    f"(based on '{agent_details.agent_name}') "
-                    f"has been saved to your library!"
-                ),
-                agent_id=created_graph.id,
-                agent_name=created_graph.name,
-                library_agent_id=library_agent.id,
-                library_agent_link=f"/library/agents/{library_agent.id}",
-                agent_page_link=f"/build?flowID={created_graph.id}",
-                session_id=session_id,
-            )
-        except Exception as e:
-            logger.error(f"Error saving customized agent: {e}")
-            return ErrorResponse(
-                message="Failed to save the customized agent. Please try again.",
-                error="save_failed",
-                session_id=session_id,
-            )

autogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py

@@ -1,284 +0,0 @@
-"""EditAgentTool - Edits existing agents using natural language."""
-
-import logging
-from typing import Any
-
-from backend.api.features.chat.model import ChatSession
-
-from .agent_generator import (
-    AgentGeneratorNotConfiguredError,
-    generate_agent_patch,
-    get_agent_as_json,
-    get_all_relevant_agents_for_generation,
-    get_user_message_for_error,
-    save_agent_to_library,
-)
-from .base import BaseTool
-from .models import (
-    AgentPreviewResponse,
-    AgentSavedResponse,
-    AsyncProcessingResponse,
-    ClarificationNeededResponse,
-    ClarifyingQuestion,
-    ErrorResponse,
-    ToolResponseBase,
-)
-
-logger = logging.getLogger(__name__)
-
-
-class EditAgentTool(BaseTool):
-    """Tool for editing existing agents using natural language."""
-
-    @property
-    def name(self) -> str:
-        return "edit_agent"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Edit an existing agent from the user's library using natural language. "
-            "Generates updates to the agent while preserving unchanged parts."
-        )
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    @property
-    def is_long_running(self) -> bool:
-        return True
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "agent_id": {
-                    "type": "string",
-                    "description": (
-                        "The ID of the agent to edit. "
-                        "Can be a graph ID or library agent ID."
-                    ),
-                },
-                "changes": {
-                    "type": "string",
-                    "description": (
-                        "Natural language description of what changes to make. "
-                        "Be specific about what to add, remove, or modify."
-                    ),
-                },
-                "context": {
-                    "type": "string",
-                    "description": (
-                        "Additional context or answers to previous clarifying questions."
-                    ),
-                },
-                "save": {
-                    "type": "boolean",
-                    "description": (
-                        "Whether to save the changes. "
-                        "Default is true. Set to false for preview only."
-                    ),
-                    "default": True,
-                },
-            },
-            "required": ["agent_id", "changes"],
-        }
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        """Execute the edit_agent tool.
-
-        Flow:
-        1. Fetch the current agent
-        2. Generate updated agent (external service handles fixing and validation)
-        3. Preview or save based on the save parameter
-        """
-        agent_id = kwargs.get("agent_id", "").strip()
-        changes = kwargs.get("changes", "").strip()
-        context = kwargs.get("context", "")
-        save = kwargs.get("save", True)
-        session_id = session.session_id if session else None
-
-        # Extract async processing params (passed by long-running tool handler)
-        operation_id = kwargs.get("_operation_id")
-        task_id = kwargs.get("_task_id")
-
-        if not agent_id:
-            return ErrorResponse(
-                message="Please provide the agent ID to edit.",
-                error="Missing agent_id parameter",
-                session_id=session_id,
-            )
-
-        if not changes:
-            return ErrorResponse(
-                message="Please describe what changes you want to make.",
-                error="Missing changes parameter",
-                session_id=session_id,
-            )
-
-        current_agent = await get_agent_as_json(agent_id, user_id)
-
-        if current_agent is None:
-            return ErrorResponse(
-                message=f"Could not find agent with ID '{agent_id}' in your library.",
-                error="agent_not_found",
-                session_id=session_id,
-            )
-
-        library_agents = None
-        if user_id:
-            try:
-                graph_id = current_agent.get("id")
-                library_agents = await get_all_relevant_agents_for_generation(
-                    user_id=user_id,
-                    search_query=changes,
-                    exclude_graph_id=graph_id,
-                    include_marketplace=True,
-                )
-                logger.debug(
-                    f"Found {len(library_agents)} relevant agents for sub-agent composition"
-                )
-            except Exception as e:
-                logger.warning(f"Failed to fetch library agents: {e}")
-
-        update_request = changes
-        if context:
-            update_request = f"{changes}\n\nAdditional context:\n{context}"
-
-        try:
-            result = await generate_agent_patch(
-                update_request,
-                current_agent,
-                library_agents,
-                operation_id=operation_id,
-                task_id=task_id,
-            )
-        except AgentGeneratorNotConfiguredError:
-            return ErrorResponse(
-                message=(
-                    "Agent editing is not available. "
-                    "The Agent Generator service is not configured."
-                ),
-                error="service_not_configured",
-                session_id=session_id,
-            )
-
-        if result is None:
-            return ErrorResponse(
-                message="Failed to generate changes. The agent generation service may be unavailable or timed out. Please try again.",
-                error="update_generation_failed",
-                details={"agent_id": agent_id, "changes": changes[:100]},
-                session_id=session_id,
-            )
-
-        # Check if Agent Generator accepted for async processing
-        if result.get("status") == "accepted":
-            logger.info(
-                f"Agent edit delegated to async processing "
-                f"(operation_id={operation_id}, task_id={task_id})"
-            )
-            return AsyncProcessingResponse(
-                message="Agent edit started. You'll be notified when it's complete.",
-                operation_id=operation_id,
-                task_id=task_id,
-                session_id=session_id,
-            )
-
-        # Check if the result is an error from the external service
-        if isinstance(result, dict) and result.get("type") == "error":
-            error_msg = result.get("error", "Unknown error")
-            error_type = result.get("error_type", "unknown")
-            user_message = get_user_message_for_error(
-                error_type,
-                operation="generate the changes",
-                llm_parse_message="The AI had trouble generating the changes. Please try again or simplify your request.",
-                validation_message="The generated changes failed validation. Please try rephrasing your request.",
-                error_details=error_msg,
-            )
-            return ErrorResponse(
-                message=user_message,
-                error=f"update_generation_failed:{error_type}",
-                details={
-                    "agent_id": agent_id,
-                    "changes": changes[:100],
-                    "service_error": error_msg,
-                    "error_type": error_type,
-                },
-                session_id=session_id,
-            )
-
-        if result.get("type") == "clarifying_questions":
-            questions = result.get("questions", [])
-            return ClarificationNeededResponse(
-                message=(
-                    "I need some more information about the changes. "
-                    "Please answer the following questions:"
-                ),
-                questions=[
-                    ClarifyingQuestion(
-                        question=q.get("question", ""),
-                        keyword=q.get("keyword", ""),
-                        example=q.get("example"),
-                    )
-                    for q in questions
-                ],
-                session_id=session_id,
-            )
-
-        updated_agent = result
-
-        agent_name = updated_agent.get("name", "Updated Agent")
-        agent_description = updated_agent.get("description", "")
-        node_count = len(updated_agent.get("nodes", []))
-        link_count = len(updated_agent.get("links", []))
-
-        if not save:
-            return AgentPreviewResponse(
-                message=(
-                    f"I've updated the agent. "
-                    f"The agent now has {node_count} blocks. "
-                    f"Review it and call edit_agent with save=true to save the changes."
-                ),
-                agent_json=updated_agent,
-                agent_name=agent_name,
-                description=agent_description,
-                node_count=node_count,
-                link_count=link_count,
-                session_id=session_id,
-            )
-
-        if not user_id:
-            return ErrorResponse(
-                message="You must be logged in to save agents.",
-                error="auth_required",
-                session_id=session_id,
-            )
-
-        try:
-            created_graph, library_agent = await save_agent_to_library(
-                updated_agent, user_id, is_update=True
-            )
-
-            return AgentSavedResponse(
-                message=f"Updated agent '{created_graph.name}' has been saved to your library!",
-                agent_id=created_graph.id,
-                agent_name=created_graph.name,
-                library_agent_id=library_agent.id,
-                library_agent_link=f"/library/agents/{library_agent.id}",
-                agent_page_link=f"/build?flowID={created_graph.id}",
-                session_id=session_id,
-            )
-        except Exception as e:
-            return ErrorResponse(
-                message=f"Failed to save the updated agent: {str(e)}",
-                error="save_failed",
-                details={"exception": str(e)},
-                session_id=session_id,
-            )

autogpt_platform/backend/backend/api/features/chat/tools/find_block.py

@@ -1,193 +0,0 @@
-import logging
-from typing import Any
-
-from prisma.enums import ContentType
-
-from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.tools.base import BaseTool, ToolResponseBase
-from backend.api.features.chat.tools.models import (
-    BlockInfoSummary,
-    BlockInputFieldInfo,
-    BlockListResponse,
-    ErrorResponse,
-    NoResultsResponse,
-)
-from backend.api.features.store.hybrid_search import unified_hybrid_search
-from backend.data.block import get_block
-
-logger = logging.getLogger(__name__)
-
-
-class FindBlockTool(BaseTool):
-    """Tool for searching available blocks."""
-
-    @property
-    def name(self) -> str:
-        return "find_block"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Search for available blocks by name or description. "
-            "Blocks are reusable components that perform specific tasks like "
-            "sending emails, making API calls, processing text, etc. "
-            "IMPORTANT: Use this tool FIRST to get the block's 'id' before calling run_block. "
-            "The response includes each block's id, required_inputs, and input_schema."
-        )
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "query": {
-                    "type": "string",
-                    "description": (
-                        "Search query to find blocks by name or description. "
-                        "Use keywords like 'email', 'http', 'text', 'ai', etc."
-                    ),
-                },
-            },
-            "required": ["query"],
-        }
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        """Search for blocks matching the query.
-
-        Args:
-            user_id: User ID (required)
-            session: Chat session
-            query: Search query
-
-        Returns:
-            BlockListResponse: List of matching blocks
-            NoResultsResponse: No blocks found
-            ErrorResponse: Error message
-        """
-        query = kwargs.get("query", "").strip()
-        session_id = session.session_id
-
-        if not query:
-            return ErrorResponse(
-                message="Please provide a search query",
-                session_id=session_id,
-            )
-
-        try:
-            # Search for blocks using hybrid search
-            results, total = await unified_hybrid_search(
-                query=query,
-                content_types=[ContentType.BLOCK],
-                page=1,
-                page_size=10,
-            )
-
-            if not results:
-                return NoResultsResponse(
-                    message=f"No blocks found for '{query}'",
-                    suggestions=[
-                        "Try broader keywords like 'email', 'http', 'text', 'ai'",
-                        "Check spelling of technical terms",
-                    ],
-                    session_id=session_id,
-                )
-
-            # Enrich results with full block information
-            blocks: list[BlockInfoSummary] = []
-            for result in results:
-                block_id = result["content_id"]
-                block = get_block(block_id)
-
-                # Skip disabled blocks
-                if block and not block.disabled:
-                    # Get input/output schemas
-                    input_schema = {}
-                    output_schema = {}
-                    try:
-                        input_schema = block.input_schema.jsonschema()
-                    except Exception:
-                        pass
-                    try:
-                        output_schema = block.output_schema.jsonschema()
-                    except Exception:
-                        pass
-
-                    # Get categories from block instance
-                    categories = []
-                    if hasattr(block, "categories") and block.categories:
-                        categories = [cat.value for cat in block.categories]
-
-                    # Extract required inputs for easier use
-                    required_inputs: list[BlockInputFieldInfo] = []
-                    if input_schema:
-                        properties = input_schema.get("properties", {})
-                        required_fields = set(input_schema.get("required", []))
-                        # Get credential field names to exclude from required inputs
-                        credentials_fields = set(
-                            block.input_schema.get_credentials_fields().keys()
-                        )
-
-                        for field_name, field_schema in properties.items():
-                            # Skip credential fields - they're handled separately
-                            if field_name in credentials_fields:
-                                continue
-
-                            required_inputs.append(
-                                BlockInputFieldInfo(
-                                    name=field_name,
-                                    type=field_schema.get("type", "string"),
-                                    description=field_schema.get("description", ""),
-                                    required=field_name in required_fields,
-                                    default=field_schema.get("default"),
-                                )
-                            )
-
-                    blocks.append(
-                        BlockInfoSummary(
-                            id=block_id,
-                            name=block.name,
-                            description=block.description or "",
-                            categories=categories,
-                            input_schema=input_schema,
-                            output_schema=output_schema,
-                            required_inputs=required_inputs,
-                        )
-                    )
-
-            if not blocks:
-                return NoResultsResponse(
-                    message=f"No blocks found for '{query}'",
-                    suggestions=[
-                        "Try broader keywords like 'email', 'http', 'text', 'ai'",
-                    ],
-                    session_id=session_id,
-                )
-
-            return BlockListResponse(
-                message=(
-                    f"Found {len(blocks)} block(s) matching '{query}'. "
-                    "To execute a block, use run_block with the block's 'id' field "
-                    "and provide 'input_data' matching the block's input_schema."
-                ),
-                blocks=blocks,
-                count=len(blocks),
-                query=query,
-                session_id=session_id,
-            )
-
-        except Exception as e:
-            logger.error(f"Error searching blocks: {e}", exc_info=True)
-            return ErrorResponse(
-                message="Failed to search blocks",
-                error=str(e),
-                session_id=session_id,
-            )

autogpt_platform/backend/backend/api/features/chat/tools/workspace_files.py

@@ -1,620 +0,0 @@
-"""CoPilot tools for workspace file operations."""
-
-import base64
-import logging
-from typing import Any, Optional
-
-from pydantic import BaseModel
-
-from backend.api.features.chat.model import ChatSession
-from backend.data.workspace import get_or_create_workspace
-from backend.util.settings import Config
-from backend.util.virus_scanner import scan_content_safe
-from backend.util.workspace import WorkspaceManager
-
-from .base import BaseTool
-from .models import ErrorResponse, ResponseType, ToolResponseBase
-
-logger = logging.getLogger(__name__)
-
-
-class WorkspaceFileInfoData(BaseModel):
-    """Data model for workspace file information (not a response itself)."""
-
-    file_id: str
-    name: str
-    path: str
-    mime_type: str
-    size_bytes: int
-
-
-class WorkspaceFileListResponse(ToolResponseBase):
-    """Response containing list of workspace files."""
-
-    type: ResponseType = ResponseType.WORKSPACE_FILE_LIST
-    files: list[WorkspaceFileInfoData]
-    total_count: int
-
-
-class WorkspaceFileContentResponse(ToolResponseBase):
-    """Response containing workspace file content (legacy, for small text files)."""
-
-    type: ResponseType = ResponseType.WORKSPACE_FILE_CONTENT
-    file_id: str
-    name: str
-    path: str
-    mime_type: str
-    content_base64: str
-
-
-class WorkspaceFileMetadataResponse(ToolResponseBase):
-    """Response containing workspace file metadata and download URL (prevents context bloat)."""
-
-    type: ResponseType = ResponseType.WORKSPACE_FILE_METADATA
-    file_id: str
-    name: str
-    path: str
-    mime_type: str
-    size_bytes: int
-    download_url: str
-    preview: str | None = None  # First 500 chars for text files
-
-
-class WorkspaceWriteResponse(ToolResponseBase):
-    """Response after writing a file to workspace."""
-
-    type: ResponseType = ResponseType.WORKSPACE_FILE_WRITTEN
-    file_id: str
-    name: str
-    path: str
-    size_bytes: int
-
-
-class WorkspaceDeleteResponse(ToolResponseBase):
-    """Response after deleting a file from workspace."""
-
-    type: ResponseType = ResponseType.WORKSPACE_FILE_DELETED
-    file_id: str
-    success: bool
-
-
-class ListWorkspaceFilesTool(BaseTool):
-    """Tool for listing files in user's workspace."""
-
-    @property
-    def name(self) -> str:
-        return "list_workspace_files"
-
-    @property
-    def description(self) -> str:
-        return (
-            "List files in the user's workspace. "
-            "Returns file names, paths, sizes, and metadata. "
-            "Optionally filter by path prefix."
-        )
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "path_prefix": {
-                    "type": "string",
-                    "description": (
-                        "Optional path prefix to filter files "
-                        "(e.g., '/documents/' to list only files in documents folder). "
-                        "By default, only files from the current session are listed."
-                    ),
-                },
-                "limit": {
-                    "type": "integer",
-                    "description": "Maximum number of files to return (default 50, max 100)",
-                    "minimum": 1,
-                    "maximum": 100,
-                },
-                "include_all_sessions": {
-                    "type": "boolean",
-                    "description": (
-                        "If true, list files from all sessions. "
-                        "Default is false (only current session's files)."
-                    ),
-                },
-            },
-            "required": [],
-        }
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        session_id = session.session_id
-
-        if not user_id:
-            return ErrorResponse(
-                message="Authentication required",
-                session_id=session_id,
-            )
-
-        path_prefix: Optional[str] = kwargs.get("path_prefix")
-        limit = min(kwargs.get("limit", 50), 100)
-        include_all_sessions: bool = kwargs.get("include_all_sessions", False)
-
-        try:
-            workspace = await get_or_create_workspace(user_id)
-            # Pass session_id for session-scoped file access
-            manager = WorkspaceManager(user_id, workspace.id, session_id)
-
-            files = await manager.list_files(
-                path=path_prefix,
-                limit=limit,
-                include_all_sessions=include_all_sessions,
-            )
-            total = await manager.get_file_count(
-                path=path_prefix,
-                include_all_sessions=include_all_sessions,
-            )
-
-            file_infos = [
-                WorkspaceFileInfoData(
-                    file_id=f.id,
-                    name=f.name,
-                    path=f.path,
-                    mime_type=f.mimeType,
-                    size_bytes=f.sizeBytes,
-                )
-                for f in files
-            ]
-
-            scope_msg = "all sessions" if include_all_sessions else "current session"
-            return WorkspaceFileListResponse(
-                files=file_infos,
-                total_count=total,
-                message=f"Found {len(files)} files in workspace ({scope_msg})",
-                session_id=session_id,
-            )
-
-        except Exception as e:
-            logger.error(f"Error listing workspace files: {e}", exc_info=True)
-            return ErrorResponse(
-                message=f"Failed to list workspace files: {str(e)}",
-                error=str(e),
-                session_id=session_id,
-            )
-
-
-class ReadWorkspaceFileTool(BaseTool):
-    """Tool for reading file content from workspace."""
-
-    # Size threshold for returning full content vs metadata+URL
-    # Files larger than this return metadata with download URL to prevent context bloat
-    MAX_INLINE_SIZE_BYTES = 32 * 1024  # 32KB
-    # Preview size for text files
-    PREVIEW_SIZE = 500
-
-    @property
-    def name(self) -> str:
-        return "read_workspace_file"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Read a file from the user's workspace. "
-            "Specify either file_id or path to identify the file. "
-            "For small text files, returns content directly. "
-            "For large or binary files, returns metadata and a download URL. "
-            "Paths are scoped to the current session by default. "
-            "Use /sessions/<session_id>/... for cross-session access."
-        )
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "file_id": {
-                    "type": "string",
-                    "description": "The file's unique ID (from list_workspace_files)",
-                },
-                "path": {
-                    "type": "string",
-                    "description": (
-                        "The virtual file path (e.g., '/documents/report.pdf'). "
-                        "Scoped to current session by default."
-                    ),
-                },
-                "force_download_url": {
-                    "type": "boolean",
-                    "description": (
-                        "If true, always return metadata+URL instead of inline content. "
-                        "Default is false (auto-selects based on file size/type)."
-                    ),
-                },
-            },
-            "required": [],  # At least one must be provided
-        }
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    def _is_text_mime_type(self, mime_type: str) -> bool:
-        """Check if the MIME type is a text-based type."""
-        text_types = [
-            "text/",
-            "application/json",
-            "application/xml",
-            "application/javascript",
-            "application/x-python",
-            "application/x-sh",
-        ]
-        return any(mime_type.startswith(t) for t in text_types)
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        session_id = session.session_id
-
-        if not user_id:
-            return ErrorResponse(
-                message="Authentication required",
-                session_id=session_id,
-            )
-
-        file_id: Optional[str] = kwargs.get("file_id")
-        path: Optional[str] = kwargs.get("path")
-        force_download_url: bool = kwargs.get("force_download_url", False)
-
-        if not file_id and not path:
-            return ErrorResponse(
-                message="Please provide either file_id or path",
-                session_id=session_id,
-            )
-
-        try:
-            workspace = await get_or_create_workspace(user_id)
-            # Pass session_id for session-scoped file access
-            manager = WorkspaceManager(user_id, workspace.id, session_id)
-
-            # Get file info
-            if file_id:
-                file_info = await manager.get_file_info(file_id)
-                if file_info is None:
-                    return ErrorResponse(
-                        message=f"File not found: {file_id}",
-                        session_id=session_id,
-                    )
-                target_file_id = file_id
-            else:
-                # path is guaranteed to be non-None here due to the check above
-                assert path is not None
-                file_info = await manager.get_file_info_by_path(path)
-                if file_info is None:
-                    return ErrorResponse(
-                        message=f"File not found at path: {path}",
-                        session_id=session_id,
-                    )
-                target_file_id = file_info.id
-
-            # Decide whether to return inline content or metadata+URL
-            is_small_file = file_info.sizeBytes <= self.MAX_INLINE_SIZE_BYTES
-            is_text_file = self._is_text_mime_type(file_info.mimeType)
-
-            # Return inline content for small text files (unless force_download_url)
-            if is_small_file and is_text_file and not force_download_url:
-                content = await manager.read_file_by_id(target_file_id)
-                content_b64 = base64.b64encode(content).decode("utf-8")
-
-                return WorkspaceFileContentResponse(
-                    file_id=file_info.id,
-                    name=file_info.name,
-                    path=file_info.path,
-                    mime_type=file_info.mimeType,
-                    content_base64=content_b64,
-                    message=f"Successfully read file: {file_info.name}",
-                    session_id=session_id,
-                )
-
-            # Return metadata + workspace:// reference for large or binary files
-            # This prevents context bloat (100KB file = ~133KB as base64)
-            # Use workspace:// format so frontend urlTransform can add proxy prefix
-            download_url = f"workspace://{target_file_id}"
-
-            # Generate preview for text files
-            preview: str | None = None
-            if is_text_file:
-                try:
-                    content = await manager.read_file_by_id(target_file_id)
-                    preview_text = content[: self.PREVIEW_SIZE].decode(
-                        "utf-8", errors="replace"
-                    )
-                    if len(content) > self.PREVIEW_SIZE:
-                        preview_text += "..."
-                    preview = preview_text
-                except Exception:
-                    pass  # Preview is optional
-
-            return WorkspaceFileMetadataResponse(
-                file_id=file_info.id,
-                name=file_info.name,
-                path=file_info.path,
-                mime_type=file_info.mimeType,
-                size_bytes=file_info.sizeBytes,
-                download_url=download_url,
-                preview=preview,
-                message=f"File: {file_info.name} ({file_info.sizeBytes} bytes). Use download_url to retrieve content.",
-                session_id=session_id,
-            )
-
-        except FileNotFoundError as e:
-            return ErrorResponse(
-                message=str(e),
-                session_id=session_id,
-            )
-        except Exception as e:
-            logger.error(f"Error reading workspace file: {e}", exc_info=True)
-            return ErrorResponse(
-                message=f"Failed to read workspace file: {str(e)}",
-                error=str(e),
-                session_id=session_id,
-            )
-
-
-class WriteWorkspaceFileTool(BaseTool):
-    """Tool for writing files to workspace."""
-
-    @property
-    def name(self) -> str:
-        return "write_workspace_file"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Write or create a file in the user's workspace. "
-            "Provide the content as a base64-encoded string. "
-            f"Maximum file size is {Config().max_file_size_mb}MB. "
-            "Files are saved to the current session's folder by default. "
-            "Use /sessions/<session_id>/... for cross-session access."
-        )
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "filename": {
-                    "type": "string",
-                    "description": "Name for the file (e.g., 'report.pdf')",
-                },
-                "content_base64": {
-                    "type": "string",
-                    "description": "Base64-encoded file content",
-                },
-                "path": {
-                    "type": "string",
-                    "description": (
-                        "Optional virtual path where to save the file "
-                        "(e.g., '/documents/report.pdf'). "
-                        "Defaults to '/{filename}'. Scoped to current session."
-                    ),
-                },
-                "mime_type": {
-                    "type": "string",
-                    "description": (
-                        "Optional MIME type of the file. "
-                        "Auto-detected from filename if not provided."
-                    ),
-                },
-                "overwrite": {
-                    "type": "boolean",
-                    "description": "Whether to overwrite if file exists at path (default: false)",
-                },
-            },
-            "required": ["filename", "content_base64"],
-        }
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        session_id = session.session_id
-
-        if not user_id:
-            return ErrorResponse(
-                message="Authentication required",
-                session_id=session_id,
-            )
-
-        filename: str = kwargs.get("filename", "")
-        content_b64: str = kwargs.get("content_base64", "")
-        path: Optional[str] = kwargs.get("path")
-        mime_type: Optional[str] = kwargs.get("mime_type")
-        overwrite: bool = kwargs.get("overwrite", False)
-
-        if not filename:
-            return ErrorResponse(
-                message="Please provide a filename",
-                session_id=session_id,
-            )
-
-        if not content_b64:
-            return ErrorResponse(
-                message="Please provide content_base64",
-                session_id=session_id,
-            )
-
-        # Decode content
-        try:
-            content = base64.b64decode(content_b64)
-        except Exception:
-            return ErrorResponse(
-                message="Invalid base64-encoded content",
-                session_id=session_id,
-            )
-
-        # Check size
-        max_file_size = Config().max_file_size_mb * 1024 * 1024
-        if len(content) > max_file_size:
-            return ErrorResponse(
-                message=f"File too large. Maximum size is {Config().max_file_size_mb}MB",
-                session_id=session_id,
-            )
-
-        try:
-            # Virus scan
-            await scan_content_safe(content, filename=filename)
-
-            workspace = await get_or_create_workspace(user_id)
-            # Pass session_id for session-scoped file access
-            manager = WorkspaceManager(user_id, workspace.id, session_id)
-
-            file_record = await manager.write_file(
-                content=content,
-                filename=filename,
-                path=path,
-                mime_type=mime_type,
-                overwrite=overwrite,
-            )
-
-            return WorkspaceWriteResponse(
-                file_id=file_record.id,
-                name=file_record.name,
-                path=file_record.path,
-                size_bytes=file_record.sizeBytes,
-                message=f"Successfully wrote file: {file_record.name}",
-                session_id=session_id,
-            )
-
-        except ValueError as e:
-            return ErrorResponse(
-                message=str(e),
-                session_id=session_id,
-            )
-        except Exception as e:
-            logger.error(f"Error writing workspace file: {e}", exc_info=True)
-            return ErrorResponse(
-                message=f"Failed to write workspace file: {str(e)}",
-                error=str(e),
-                session_id=session_id,
-            )
-
-
-class DeleteWorkspaceFileTool(BaseTool):
-    """Tool for deleting files from workspace."""
-
-    @property
-    def name(self) -> str:
-        return "delete_workspace_file"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Delete a file from the user's workspace. "
-            "Specify either file_id or path to identify the file. "
-            "Paths are scoped to the current session by default. "
-            "Use /sessions/<session_id>/... for cross-session access."
-        )
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "file_id": {
-                    "type": "string",
-                    "description": "The file's unique ID (from list_workspace_files)",
-                },
-                "path": {
-                    "type": "string",
-                    "description": (
-                        "The virtual file path (e.g., '/documents/report.pdf'). "
-                        "Scoped to current session by default."
-                    ),
-                },
-            },
-            "required": [],  # At least one must be provided
-        }
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        session_id = session.session_id
-
-        if not user_id:
-            return ErrorResponse(
-                message="Authentication required",
-                session_id=session_id,
-            )
-
-        file_id: Optional[str] = kwargs.get("file_id")
-        path: Optional[str] = kwargs.get("path")
-
-        if not file_id and not path:
-            return ErrorResponse(
-                message="Please provide either file_id or path",
-                session_id=session_id,
-            )
-
-        try:
-            workspace = await get_or_create_workspace(user_id)
-            # Pass session_id for session-scoped file access
-            manager = WorkspaceManager(user_id, workspace.id, session_id)
-
-            # Determine the file_id to delete
-            target_file_id: str
-            if file_id:
-                target_file_id = file_id
-            else:
-                # path is guaranteed to be non-None here due to the check above
-                assert path is not None
-                file_info = await manager.get_file_info_by_path(path)
-                if file_info is None:
-                    return ErrorResponse(
-                        message=f"File not found at path: {path}",
-                        session_id=session_id,
-                    )
-                target_file_id = file_info.id
-
-            success = await manager.delete_file(target_file_id)
-
-            if not success:
-                return ErrorResponse(
-                    message=f"File not found: {target_file_id}",
-                    session_id=session_id,
-                )
-
-            return WorkspaceDeleteResponse(
-                file_id=target_file_id,
-                success=True,
-                message="File deleted successfully",
-                session_id=session_id,
-            )
-
-        except Exception as e:
-            logger.error(f"Error deleting workspace file: {e}", exc_info=True)
-            return ErrorResponse(
-                message=f"Failed to delete workspace file: {str(e)}",
-                error=str(e),
-                session_id=session_id,
-            )

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

@@ -22,6 +22,7 @@ from backend.data.human_review import (
 )
 from backend.data.model import USER_TIMEZONE_NOT_SET
 from backend.data.user import get_user_by_id
+from backend.data.workspace import get_or_create_workspace
 from backend.executor.utils import add_graph_execution
 
 from .model import PendingHumanReviewModel, ReviewRequest, ReviewResponse
@@ -321,10 +322,13 @@ async def process_review_action(
                     user.timezone if user.timezone != USER_TIMEZONE_NOT_SET else "UTC"
                 )
 
+                workspace = await get_or_create_workspace(user_id)
+
                 execution_context = ExecutionContext(
                     human_in_the_loop_safe_mode=settings.human_in_the_loop_safe_mode,
                     sensitive_action_safe_mode=settings.sensitive_action_safe_mode,
                     user_timezone=user_timezone,
+                    workspace_id=workspace.id,
                 )
 
                 await add_graph_execution(

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

@@ -1,7 +1,7 @@
 import asyncio
 import logging
 from datetime import datetime, timedelta, timezone
-from typing import TYPE_CHECKING, Annotated, List, Literal
+from typing import TYPE_CHECKING, Annotated, Any, List, Literal
 
 from autogpt_libs.auth import get_user_id
 from fastapi import (
@@ -14,7 +14,7 @@ from fastapi import (
     Security,
     status,
 )
-from pydantic import BaseModel, Field, SecretStr
+from pydantic import BaseModel, Field, SecretStr, model_validator
 from starlette.status import HTTP_500_INTERNAL_SERVER_ERROR, HTTP_502_BAD_GATEWAY
 
 from backend.api.features.library.db import set_preset_webhook, update_preset
@@ -39,7 +39,11 @@ from backend.data.onboarding import OnboardingStep, complete_onboarding_step
 from backend.data.user import get_user_integrations
 from backend.executor.utils import add_graph_execution
 from backend.integrations.ayrshare import AyrshareClient, SocialPlatform
-from backend.integrations.creds_manager import IntegrationCredentialsManager
+from backend.integrations.credentials_store import provider_matches
+from backend.integrations.creds_manager import (
+    IntegrationCredentialsManager,
+    create_mcp_oauth_handler,
+)
 from backend.integrations.oauth import CREDENTIALS_BY_PROVIDER, HANDLERS_BY_NAME
 from backend.integrations.providers import ProviderName
 from backend.integrations.webhooks import get_webhook_manager
@@ -102,9 +106,37 @@ class CredentialsMetaResponse(BaseModel):
     scopes: list[str] | None
     username: str | None
     host: str | None = Field(
-        default=None, description="Host pattern for host-scoped credentials"
+        default=None,
+        description="Host pattern for host-scoped or MCP server URL for MCP credentials",
     )
 
+    @model_validator(mode="before")
+    @classmethod
+    def _normalize_provider(cls, data: Any) -> Any:
+        """Fix ``ProviderName.X`` format from Python 3.13 ``str(Enum)`` bug."""
+        if isinstance(data, dict):
+            prov = data.get("provider", "")
+            if isinstance(prov, str) and prov.startswith("ProviderName."):
+                member = prov.removeprefix("ProviderName.")
+                try:
+                    data = {**data, "provider": ProviderName[member].value}
+                except KeyError:
+                    pass
+        return data
+
+    @staticmethod
+    def get_host(cred: Credentials) -> str | None:
+        """Extract host from credential: HostScoped host or MCP server URL."""
+        if isinstance(cred, HostScopedCredentials):
+            return cred.host
+        if isinstance(cred, OAuth2Credentials) and cred.provider in (
+            ProviderName.MCP,
+            ProviderName.MCP.value,
+            "ProviderName.MCP",
+        ):
+            return (cred.metadata or {}).get("mcp_server_url")
+        return None
+
 
 @router.post("/{provider}/callback", summary="Exchange OAuth code for tokens")
 async def callback(
@@ -179,9 +211,7 @@ async def callback(
         title=credentials.title,
         scopes=credentials.scopes,
         username=credentials.username,
-        host=(
-            credentials.host if isinstance(credentials, HostScopedCredentials) else None
-        ),
+        host=(CredentialsMetaResponse.get_host(credentials)),
     )
 
 
@@ -199,7 +229,7 @@ async def list_credentials(
             title=cred.title,
             scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
             username=cred.username if isinstance(cred, OAuth2Credentials) else None,
-            host=cred.host if isinstance(cred, HostScopedCredentials) else None,
+            host=CredentialsMetaResponse.get_host(cred),
         )
         for cred in credentials
     ]
@@ -222,7 +252,7 @@ async def list_credentials_by_provider(
             title=cred.title,
             scopes=cred.scopes if isinstance(cred, OAuth2Credentials) else None,
             username=cred.username if isinstance(cred, OAuth2Credentials) else None,
-            host=cred.host if isinstance(cred, HostScopedCredentials) else None,
+            host=CredentialsMetaResponse.get_host(cred),
         )
         for cred in credentials
     ]
@@ -322,7 +352,11 @@ async def delete_credentials(
 
     tokens_revoked = None
     if isinstance(creds, OAuth2Credentials):
-        handler = _get_provider_oauth_handler(request, provider)
+        if provider_matches(provider.value, ProviderName.MCP.value):
+            # MCP uses dynamic per-server OAuth — create handler from metadata
+            handler = create_mcp_oauth_handler(creds)
+        else:
+            handler = _get_provider_oauth_handler(request, provider)
         tokens_revoked = await handler.revoke_tokens(creds)
 
     return CredentialsDeletionResponse(revoked=tokens_revoked)

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
 
@@ -144,6 +143,7 @@ async def test_add_agent_to_library(mocker):
     )
 
     mock_library_agent = mocker.patch("prisma.models.LibraryAgent.prisma")
+    mock_library_agent.return_value.find_first = mocker.AsyncMock(return_value=None)
     mock_library_agent.return_value.find_unique = mocker.AsyncMock(return_value=None)
     mock_library_agent.return_value.create = mocker.AsyncMock(
         return_value=mock_library_agent_data
@@ -178,7 +178,6 @@ async def test_add_agent_to_library(mocker):
                 "agentGraphVersion": 1,
             }
         },
-        include={"AgentGraph": True},
     )
     # Check that create was called with the expected data including settings
     create_call_args = mock_library_agent.return_value.create.call_args
@@ -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/exceptions.py

@@ -0,0 +1,10 @@
+class FolderValidationError(Exception):
+    """Raised when folder operations fail validation."""
+
+    pass
+
+
+class FolderAlreadyExistsError(FolderValidationError):
+    """Raised when a folder with the same name already exists in the location."""
+
+    pass

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

@@ -6,9 +6,12 @@ import prisma.enums
 import prisma.models
 import pydantic
 
-from backend.data.block import BlockInput
 from backend.data.graph import GraphModel, GraphSettings, GraphTriggerInfo
-from backend.data.model import CredentialsMetaInput, is_credentials_field_name
+from backend.data.model import (
+    CredentialsMetaInput,
+    GraphInput,
+    is_credentials_field_name,
+)
 from backend.util.json import loads as json_loads
 from backend.util.models import Pagination
 
@@ -23,6 +26,95 @@ class LibraryAgentStatus(str, Enum):
     ERROR = "ERROR"
 
 
+# === Folder Models ===
+
+
+class LibraryFolder(pydantic.BaseModel):
+    """Represents a folder for organizing library agents."""
+
+    id: str
+    user_id: str
+    name: str
+    icon: str | None = None
+    color: str | None = None
+    parent_id: str | None = None
+    created_at: datetime.datetime
+    updated_at: datetime.datetime
+    agent_count: int = 0  # Direct agents in folder
+    subfolder_count: int = 0  # Direct child folders
+
+    @staticmethod
+    def from_db(
+        folder: prisma.models.LibraryFolder,
+        agent_count: int = 0,
+        subfolder_count: int = 0,
+    ) -> "LibraryFolder":
+        """Factory method that constructs a LibraryFolder from a Prisma model."""
+        return LibraryFolder(
+            id=folder.id,
+            user_id=folder.userId,
+            name=folder.name,
+            icon=folder.icon,
+            color=folder.color,
+            parent_id=folder.parentId,
+            created_at=folder.createdAt,
+            updated_at=folder.updatedAt,
+            agent_count=agent_count,
+            subfolder_count=subfolder_count,
+        )
+
+
+class LibraryFolderTree(LibraryFolder):
+    """Folder with nested children for tree view."""
+
+    children: list["LibraryFolderTree"] = []
+
+
+class FolderCreateRequest(pydantic.BaseModel):
+    """Request model for creating a folder."""
+
+    name: str = pydantic.Field(..., min_length=1, max_length=100)
+    icon: str | None = None
+    color: str | None = pydantic.Field(
+        None, pattern=r"^#[0-9A-Fa-f]{6}$", description="Hex color code (#RRGGBB)"
+    )
+    parent_id: str | None = None
+
+
+class FolderUpdateRequest(pydantic.BaseModel):
+    """Request model for updating a folder."""
+
+    name: str | None = pydantic.Field(None, min_length=1, max_length=100)
+    icon: str | None = None
+    color: str | None = None
+
+
+class FolderMoveRequest(pydantic.BaseModel):
+    """Request model for moving a folder to a new parent."""
+
+    target_parent_id: str | None = None  # None = move to root
+
+
+class BulkMoveAgentsRequest(pydantic.BaseModel):
+    """Request model for moving multiple agents to a folder."""
+
+    agent_ids: list[str]
+    folder_id: str | None = None  # None = move to root
+
+
+class FolderListResponse(pydantic.BaseModel):
+    """Response schema for a list of folders."""
+
+    folders: list[LibraryFolder]
+    pagination: Pagination
+
+
+class FolderTreeResponse(pydantic.BaseModel):
+    """Response schema for folder tree structure."""
+
+    tree: list[LibraryFolderTree]
+
+
 class MarketplaceListingCreator(pydantic.BaseModel):
     """Creator information for a marketplace listing."""
 
@@ -117,6 +209,9 @@ class LibraryAgent(pydantic.BaseModel):
     can_access_graph: bool
     is_latest_version: bool
     is_favorite: bool
+    folder_id: str | None = None
+    folder_name: str | None = None  # Denormalized for display
+
     recommended_schedule_cron: str | None = None
     settings: GraphSettings = pydantic.Field(default_factory=GraphSettings)
     marketplace_listing: Optional["MarketplaceListing"] = None
@@ -256,6 +351,8 @@ class LibraryAgent(pydantic.BaseModel):
             can_access_graph=can_access_graph,
             is_latest_version=is_latest_version,
             is_favorite=agent.isFavorite,
+            folder_id=agent.folderId,
+            folder_name=agent.Folder.name if agent.Folder else None,
             recommended_schedule_cron=agent.AgentGraph.recommendedScheduleCron,
             settings=_parse_settings(agent.settings),
             marketplace_listing=marketplace_listing_data,
@@ -323,7 +420,7 @@ class LibraryAgentPresetCreatable(pydantic.BaseModel):
     graph_id: str
     graph_version: int
 
-    inputs: BlockInput
+    inputs: GraphInput
     credentials: dict[str, CredentialsMetaInput]
 
     name: str
@@ -352,7 +449,7 @@ class LibraryAgentPresetUpdatable(pydantic.BaseModel):
     Request model used when updating a preset for a library agent.
     """
 
-    inputs: Optional[BlockInput] = None
+    inputs: Optional[GraphInput] = None
     credentials: Optional[dict[str, CredentialsMetaInput]] = None
 
     name: Optional[str] = None
@@ -395,7 +492,7 @@ class LibraryAgentPreset(LibraryAgentPresetCreatable):
                 "Webhook must be included in AgentPreset query when webhookId is set"
             )
 
-        input_data: BlockInput = {}
+        input_data: GraphInput = {}
         input_credentials: dict[str, CredentialsMetaInput] = {}
 
         for preset_input in preset.InputPresets:
@@ -467,3 +564,7 @@ class LibraryAgentUpdateRequest(pydantic.BaseModel):
     settings: Optional[GraphSettings] = pydantic.Field(
         default=None, description="User-specific settings for this library agent"
     )
+    folder_id: Optional[str] = pydantic.Field(
+        default=None,
+        description="Folder ID to move agent to (None to move to root)",
+    )

autogpt_platform/backend/backend/api/features/library/routes/__init__.py

@@ -1,9 +1,11 @@
 import fastapi
 
 from .agents import router as agents_router
+from .folders import router as folders_router
 from .presets import router as presets_router
 
 router = fastapi.APIRouter()
 
 router.include_router(presets_router)
+router.include_router(folders_router)
 router.include_router(agents_router)

autogpt_platform/backend/backend/api/features/library/routes/agents.py

@@ -41,6 +41,14 @@ async def list_library_agents(
         ge=1,
         description="Number of agents per page (must be >= 1)",
     ),
+    folder_id: Optional[str] = Query(
+        None,
+        description="Filter by folder ID",
+    ),
+    include_root_only: bool = Query(
+        False,
+        description="Only return agents without a folder (root-level agents)",
+    ),
 ) -> library_model.LibraryAgentResponse:
     """
     Get all agents in the user's library (both created and saved).
@@ -51,6 +59,8 @@ async def list_library_agents(
         sort_by=sort_by,
         page=page,
         page_size=page_size,
+        folder_id=folder_id,
+        include_root_only=include_root_only,
     )
 
 
@@ -168,6 +178,7 @@ async def update_library_agent(
         is_favorite=payload.is_favorite,
         is_archived=payload.is_archived,
         settings=payload.settings,
+        folder_id=payload.folder_id,
     )
 
 

autogpt_platform/backend/backend/api/features/library/routes/folders.py

@@ -0,0 +1,287 @@
+from typing import Optional
+
+import autogpt_libs.auth as autogpt_auth_lib
+from fastapi import APIRouter, Query, Security, status
+from fastapi.responses import Response
+
+from .. import db as library_db
+from .. import model as library_model
+
+router = APIRouter(
+    prefix="/folders",
+    tags=["library", "folders", "private"],
+    dependencies=[Security(autogpt_auth_lib.requires_user)],
+)
+
+
+@router.get(
+    "",
+    summary="List Library Folders",
+    response_model=library_model.FolderListResponse,
+    responses={
+        200: {"description": "List of folders"},
+        500: {"description": "Server error"},
+    },
+)
+async def list_folders(
+    user_id: str = Security(autogpt_auth_lib.get_user_id),
+    parent_id: Optional[str] = Query(
+        None,
+        description="Filter by parent folder ID. If not provided, returns root-level folders.",
+    ),
+    include_relations: bool = Query(
+        True,
+        description="Include agent and subfolder relations (for counts)",
+    ),
+) -> library_model.FolderListResponse:
+    """
+    List folders for the authenticated user.
+
+    Args:
+        user_id: ID of the authenticated user.
+        parent_id: Optional parent folder ID to filter by.
+        include_relations: Whether to include agent and subfolder relations for counts.
+
+    Returns:
+        A FolderListResponse containing folders.
+    """
+    folders = await library_db.list_folders(
+        user_id=user_id,
+        parent_id=parent_id,
+        include_relations=include_relations,
+    )
+    return library_model.FolderListResponse(
+        folders=folders,
+        pagination=library_model.Pagination(
+            total_items=len(folders),
+            total_pages=1,
+            current_page=1,
+            page_size=len(folders),
+        ),
+    )
+
+
+@router.get(
+    "/tree",
+    summary="Get Folder Tree",
+    response_model=library_model.FolderTreeResponse,
+    responses={
+        200: {"description": "Folder tree structure"},
+        500: {"description": "Server error"},
+    },
+)
+async def get_folder_tree(
+    user_id: str = Security(autogpt_auth_lib.get_user_id),
+) -> library_model.FolderTreeResponse:
+    """
+    Get the full folder tree for the authenticated user.
+
+    Args:
+        user_id: ID of the authenticated user.
+
+    Returns:
+        A FolderTreeResponse containing the nested folder structure.
+    """
+    tree = await library_db.get_folder_tree(user_id=user_id)
+    return library_model.FolderTreeResponse(tree=tree)
+
+
+@router.get(
+    "/{folder_id}",
+    summary="Get Folder",
+    response_model=library_model.LibraryFolder,
+    responses={
+        200: {"description": "Folder details"},
+        404: {"description": "Folder not found"},
+        500: {"description": "Server error"},
+    },
+)
+async def get_folder(
+    folder_id: str,
+    user_id: str = Security(autogpt_auth_lib.get_user_id),
+) -> library_model.LibraryFolder:
+    """
+    Get a specific folder.
+
+    Args:
+        folder_id: ID of the folder to retrieve.
+        user_id: ID of the authenticated user.
+
+    Returns:
+        The requested LibraryFolder.
+    """
+    return await library_db.get_folder(folder_id=folder_id, user_id=user_id)
+
+
+@router.post(
+    "",
+    summary="Create Folder",
+    status_code=status.HTTP_201_CREATED,
+    response_model=library_model.LibraryFolder,
+    responses={
+        201: {"description": "Folder created successfully"},
+        400: {"description": "Validation error"},
+        404: {"description": "Parent folder not found"},
+        409: {"description": "Folder name conflict"},
+        500: {"description": "Server error"},
+    },
+)
+async def create_folder(
+    payload: library_model.FolderCreateRequest,
+    user_id: str = Security(autogpt_auth_lib.get_user_id),
+) -> library_model.LibraryFolder:
+    """
+    Create a new folder.
+
+    Args:
+        payload: The folder creation request.
+        user_id: ID of the authenticated user.
+
+    Returns:
+        The created LibraryFolder.
+    """
+    return await library_db.create_folder(
+        user_id=user_id,
+        name=payload.name,
+        parent_id=payload.parent_id,
+        icon=payload.icon,
+        color=payload.color,
+    )
+
+
+@router.patch(
+    "/{folder_id}",
+    summary="Update Folder",
+    response_model=library_model.LibraryFolder,
+    responses={
+        200: {"description": "Folder updated successfully"},
+        400: {"description": "Validation error"},
+        404: {"description": "Folder not found"},
+        409: {"description": "Folder name conflict"},
+        500: {"description": "Server error"},
+    },
+)
+async def update_folder(
+    folder_id: str,
+    payload: library_model.FolderUpdateRequest,
+    user_id: str = Security(autogpt_auth_lib.get_user_id),
+) -> library_model.LibraryFolder:
+    """
+    Update a folder's properties.
+
+    Args:
+        folder_id: ID of the folder to update.
+        payload: The folder update request.
+        user_id: ID of the authenticated user.
+
+    Returns:
+        The updated LibraryFolder.
+    """
+    return await library_db.update_folder(
+        folder_id=folder_id,
+        user_id=user_id,
+        name=payload.name,
+        icon=payload.icon,
+        color=payload.color,
+    )
+
+
+@router.post(
+    "/{folder_id}/move",
+    summary="Move Folder",
+    response_model=library_model.LibraryFolder,
+    responses={
+        200: {"description": "Folder moved successfully"},
+        400: {"description": "Validation error (circular reference)"},
+        404: {"description": "Folder or target parent not found"},
+        409: {"description": "Folder name conflict in target location"},
+        500: {"description": "Server error"},
+    },
+)
+async def move_folder(
+    folder_id: str,
+    payload: library_model.FolderMoveRequest,
+    user_id: str = Security(autogpt_auth_lib.get_user_id),
+) -> library_model.LibraryFolder:
+    """
+    Move a folder to a new parent.
+
+    Args:
+        folder_id: ID of the folder to move.
+        payload: The move request with target parent.
+        user_id: ID of the authenticated user.
+
+    Returns:
+        The moved LibraryFolder.
+    """
+    return await library_db.move_folder(
+        folder_id=folder_id,
+        user_id=user_id,
+        target_parent_id=payload.target_parent_id,
+    )
+
+
+@router.delete(
+    "/{folder_id}",
+    summary="Delete Folder",
+    status_code=status.HTTP_204_NO_CONTENT,
+    responses={
+        204: {"description": "Folder deleted successfully"},
+        404: {"description": "Folder not found"},
+        500: {"description": "Server error"},
+    },
+)
+async def delete_folder(
+    folder_id: str,
+    user_id: str = Security(autogpt_auth_lib.get_user_id),
+) -> Response:
+    """
+    Soft-delete a folder and all its contents.
+
+    Args:
+        folder_id: ID of the folder to delete.
+        user_id: ID of the authenticated user.
+
+    Returns:
+        204 No Content if successful.
+    """
+    await library_db.delete_folder(
+        folder_id=folder_id,
+        user_id=user_id,
+        soft_delete=True,
+    )
+    return Response(status_code=status.HTTP_204_NO_CONTENT)
+
+
+# === Bulk Agent Operations ===
+
+
+@router.post(
+    "/agents/bulk-move",
+    summary="Bulk Move Agents",
+    response_model=list[library_model.LibraryAgent],
+    responses={
+        200: {"description": "Agents moved successfully"},
+        404: {"description": "Folder not found"},
+        500: {"description": "Server error"},
+    },
+)
+async def bulk_move_agents(
+    payload: library_model.BulkMoveAgentsRequest,
+    user_id: str = Security(autogpt_auth_lib.get_user_id),
+) -> list[library_model.LibraryAgent]:
+    """
+    Move multiple agents to a folder.
+
+    Args:
+        payload: The bulk move request with agent IDs and target folder.
+        user_id: ID of the authenticated user.
+
+    Returns:
+        The updated LibraryAgents.
+    """
+    return await library_db.bulk_move_agents_to_folder(
+        agent_ids=payload.agent_ids,
+        folder_id=payload.folder_id,
+        user_id=user_id,
+    )

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

@@ -115,6 +115,8 @@ async def test_get_library_agents_success(
         sort_by=library_model.LibraryAgentSort.UPDATED_AT,
         page=1,
         page_size=15,
+        folder_id=None,
+        include_root_only=False,
     )
 
 

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

@@ -0,0 +1,511 @@
+"""
+MCP (Model Context Protocol) API routes.
+
+Provides endpoints for MCP tool discovery and OAuth authentication so the
+frontend can list available tools on an MCP server before placing a block.
+"""
+
+import logging
+from typing import Annotated, Any
+
+import fastapi
+from autogpt_libs.auth import get_user_id
+from fastapi import Security
+from pydantic import BaseModel, Field, SecretStr
+
+from backend.api.features.integrations.router import CredentialsMetaResponse
+from backend.blocks.mcp.client import MCPClient, MCPClientError
+from backend.blocks.mcp.helpers import (
+    auto_lookup_mcp_credential,
+    normalize_mcp_url,
+    server_host,
+)
+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.settings import Settings
+
+logger = logging.getLogger(__name__)
+
+settings = Settings()
+router = fastapi.APIRouter(tags=["mcp"])
+creds_manager = IntegrationCredentialsManager()
+
+
+# ====================== Tool Discovery ====================== #
+
+
+class DiscoverToolsRequest(BaseModel):
+    """Request to discover tools on an MCP server."""
+
+    server_url: str = Field(description="URL of the MCP server")
+    auth_token: str | None = Field(
+        default=None,
+        description="Optional Bearer token for authenticated MCP servers",
+    )
+
+
+class MCPToolResponse(BaseModel):
+    """A single MCP tool returned by discovery."""
+
+    name: str
+    description: str
+    input_schema: dict[str, Any]
+
+
+class DiscoverToolsResponse(BaseModel):
+    """Response containing the list of tools available on an MCP server."""
+
+    tools: list[MCPToolResponse]
+    server_name: str | None = None
+    protocol_version: str | None = None
+
+
+@router.post(
+    "/discover-tools",
+    summary="Discover available tools on an MCP server",
+    response_model=DiscoverToolsResponse,
+)
+async def discover_tools(
+    request: DiscoverToolsRequest,
+    user_id: Annotated[str, Security(get_user_id)],
+) -> DiscoverToolsResponse:
+    """
+    Connect to an MCP server and return its available tools.
+
+    If the user has a stored MCP credential for this server URL, it will be
+    used automatically — no need to pass an explicit auth token.
+    """
+    # Validate URL to prevent SSRF — blocks loopback and private IP ranges.
+    try:
+        await validate_url(request.server_url, trusted_origins=[])
+    except ValueError as e:
+        raise fastapi.HTTPException(status_code=400, detail=f"Invalid server URL: {e}")
+
+    auth_token = request.auth_token
+
+    # Auto-use stored MCP credential when no explicit token is provided.
+    if not auth_token:
+        best_cred = await auto_lookup_mcp_credential(
+            user_id, normalize_mcp_url(request.server_url)
+        )
+        if best_cred:
+            auth_token = best_cred.access_token.get_secret_value()
+
+    client = MCPClient(request.server_url, auth_token=auth_token)
+
+    try:
+        init_result = await client.initialize()
+        tools = await client.list_tools()
+    except HTTPClientError as e:
+        if e.status_code in (401, 403):
+            raise fastapi.HTTPException(
+                status_code=401,
+                detail="This MCP server requires authentication. "
+                "Please provide a valid auth token.",
+            )
+        raise fastapi.HTTPException(status_code=502, detail=str(e))
+    except MCPClientError as e:
+        raise fastapi.HTTPException(status_code=502, detail=str(e))
+    except Exception as e:
+        raise fastapi.HTTPException(
+            status_code=502,
+            detail=f"Failed to connect to MCP server: {e}",
+        )
+
+    return DiscoverToolsResponse(
+        tools=[
+            MCPToolResponse(
+                name=t.name,
+                description=t.description,
+                input_schema=t.input_schema,
+            )
+            for t in tools
+        ],
+        server_name=(
+            init_result.get("serverInfo", {}).get("name")
+            or server_host(request.server_url)
+            or "MCP"
+        ),
+        protocol_version=init_result.get("protocolVersion"),
+    )
+
+
+# ======================== OAuth Flow ======================== #
+
+
+class MCPOAuthLoginRequest(BaseModel):
+    """Request to start an OAuth flow for an MCP server."""
+
+    server_url: str = Field(description="URL of the MCP server that requires OAuth")
+
+
+class MCPOAuthLoginResponse(BaseModel):
+    """Response with the OAuth login URL for the user to authenticate."""
+
+    login_url: str
+    state_token: str
+
+
+@router.post(
+    "/oauth/login",
+    summary="Initiate OAuth login for an MCP server",
+)
+async def mcp_oauth_login(
+    request: MCPOAuthLoginRequest,
+    user_id: Annotated[str, Security(get_user_id)],
+) -> MCPOAuthLoginResponse:
+    """
+    Discover OAuth metadata from the MCP server and return a login URL.
+
+    1. Discovers the protected-resource metadata (RFC 9728)
+    2. Fetches the authorization server metadata (RFC 8414)
+    3. Performs Dynamic Client Registration (RFC 7591) if available
+    4. Returns the authorization URL for the frontend to open in a popup
+    """
+    # Validate URL to prevent SSRF — blocks loopback and private IP ranges.
+    try:
+        await validate_url(request.server_url, trusted_origins=[])
+    except ValueError as e:
+        raise fastapi.HTTPException(status_code=400, detail=f"Invalid server URL: {e}")
+
+    # Normalize the URL so that credentials stored here are matched consistently
+    # by auto_lookup_mcp_credential (which also uses normalized URLs).
+    server_url = normalize_mcp_url(request.server_url)
+    client = MCPClient(server_url)
+
+    # Step 1: Discover protected-resource metadata (RFC 9728)
+    protected_resource = await client.discover_auth()
+
+    metadata: dict[str, Any] | None = None
+
+    if protected_resource and protected_resource.get("authorization_servers"):
+        auth_server_url = protected_resource["authorization_servers"][0]
+        resource_url = protected_resource.get("resource", server_url)
+
+        # Validate the auth server URL from metadata to prevent SSRF.
+        try:
+            await validate_url(auth_server_url, trusted_origins=[])
+        except ValueError as e:
+            raise fastapi.HTTPException(
+                status_code=400,
+                detail=f"Invalid authorization server URL in metadata: {e}",
+            )
+
+        # Step 2a: Discover auth-server metadata (RFC 8414)
+        metadata = await client.discover_auth_server_metadata(auth_server_url)
+    else:
+        # Fallback: Some MCP servers (e.g. Linear) are their own auth server
+        # and serve OAuth metadata directly without protected-resource metadata.
+        # Don't assume a resource_url — omitting it lets the auth server choose
+        # the correct audience for the token (RFC 8707 resource is optional).
+        resource_url = None
+        metadata = await client.discover_auth_server_metadata(server_url)
+
+    if (
+        not metadata
+        or "authorization_endpoint" not in metadata
+        or "token_endpoint" not in metadata
+    ):
+        raise fastapi.HTTPException(
+            status_code=400,
+            detail="This MCP server does not advertise OAuth support. "
+            "You may need to provide an auth token manually.",
+        )
+
+    authorize_url = metadata["authorization_endpoint"]
+    token_url = metadata["token_endpoint"]
+    registration_endpoint = metadata.get("registration_endpoint")
+    revoke_url = metadata.get("revocation_endpoint")
+
+    # Step 3: Dynamic Client Registration (RFC 7591) if available
+    frontend_base_url = settings.config.frontend_base_url
+    if not frontend_base_url:
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Frontend base URL is not configured.",
+        )
+    redirect_uri = f"{frontend_base_url}/auth/integrations/mcp_callback"
+
+    client_id = ""
+    client_secret = ""
+    if registration_endpoint:
+        # Validate the registration endpoint to prevent SSRF via metadata.
+        try:
+            await validate_url(registration_endpoint, trusted_origins=[])
+        except ValueError:
+            pass  # Skip registration, fall back to default client_id
+        else:
+            reg_result = await _register_mcp_client(
+                registration_endpoint, redirect_uri, server_url
+            )
+            if reg_result:
+                client_id = reg_result.get("client_id", "")
+                client_secret = reg_result.get("client_secret", "")
+
+    if not client_id:
+        client_id = "autogpt-platform"
+
+    # Step 4: Store state token with OAuth metadata for the callback
+    scopes = (protected_resource or {}).get("scopes_supported") or metadata.get(
+        "scopes_supported", []
+    )
+    state_token, code_challenge = await creds_manager.store.store_state_token(
+        user_id,
+        ProviderName.MCP.value,
+        scopes,
+        state_metadata={
+            "authorize_url": authorize_url,
+            "token_url": token_url,
+            "revoke_url": revoke_url,
+            "resource_url": resource_url,
+            "server_url": server_url,
+            "client_id": client_id,
+            "client_secret": client_secret,
+        },
+    )
+
+    # Step 5: Build and return the login URL
+    handler = MCPOAuthHandler(
+        client_id=client_id,
+        client_secret=client_secret,
+        redirect_uri=redirect_uri,
+        authorize_url=authorize_url,
+        token_url=token_url,
+        resource_url=resource_url,
+    )
+    login_url = handler.get_login_url(
+        scopes, state_token, code_challenge=code_challenge
+    )
+
+    return MCPOAuthLoginResponse(login_url=login_url, state_token=state_token)
+
+
+class MCPOAuthCallbackRequest(BaseModel):
+    """Request to exchange an OAuth code for tokens."""
+
+    code: str = Field(description="Authorization code from OAuth callback")
+    state_token: str = Field(description="State token for CSRF verification")
+
+
+class MCPOAuthCallbackResponse(BaseModel):
+    """Response after successfully storing OAuth credentials."""
+
+    credential_id: str
+
+
+@router.post(
+    "/oauth/callback",
+    summary="Exchange OAuth code for MCP tokens",
+)
+async def mcp_oauth_callback(
+    request: MCPOAuthCallbackRequest,
+    user_id: Annotated[str, Security(get_user_id)],
+) -> CredentialsMetaResponse:
+    """
+    Exchange the authorization code for tokens and store the credential.
+
+    The frontend calls this after receiving the OAuth code from the popup.
+    On success, subsequent ``/discover-tools`` calls for the same server URL
+    will automatically use the stored credential.
+    """
+    valid_state = await creds_manager.store.verify_state_token(
+        user_id, request.state_token, ProviderName.MCP.value
+    )
+    if not valid_state:
+        raise fastapi.HTTPException(
+            status_code=400,
+            detail="Invalid or expired state token.",
+        )
+
+    meta = valid_state.state_metadata
+    frontend_base_url = settings.config.frontend_base_url
+    if not frontend_base_url:
+        raise fastapi.HTTPException(
+            status_code=500,
+            detail="Frontend base URL is not configured.",
+        )
+    redirect_uri = f"{frontend_base_url}/auth/integrations/mcp_callback"
+
+    handler = MCPOAuthHandler(
+        client_id=meta["client_id"],
+        client_secret=meta.get("client_secret", ""),
+        redirect_uri=redirect_uri,
+        authorize_url=meta["authorize_url"],
+        token_url=meta["token_url"],
+        revoke_url=meta.get("revoke_url"),
+        resource_url=meta.get("resource_url"),
+    )
+
+    try:
+        credentials = await handler.exchange_code_for_tokens(
+            request.code, valid_state.scopes, valid_state.code_verifier
+        )
+    except Exception as e:
+        raise fastapi.HTTPException(
+            status_code=400,
+            detail=f"OAuth token exchange failed: {e}",
+        )
+
+    # Enrich credential metadata for future lookup and token refresh
+    if credentials.metadata is None:
+        credentials.metadata = {}
+    credentials.metadata["mcp_server_url"] = meta["server_url"]
+    credentials.metadata["mcp_client_id"] = meta["client_id"]
+    credentials.metadata["mcp_client_secret"] = meta.get("client_secret", "")
+    credentials.metadata["mcp_token_url"] = meta["token_url"]
+    credentials.metadata["mcp_resource_url"] = meta.get("resource_url", "")
+
+    hostname = server_host(meta["server_url"])
+    credentials.title = f"MCP: {hostname}"
+
+    # Remove old MCP credentials for the same server to prevent stale token buildup.
+    try:
+        old_creds = await creds_manager.store.get_creds_by_provider(
+            user_id, ProviderName.MCP.value
+        )
+        for old in old_creds:
+            if (
+                isinstance(old, OAuth2Credentials)
+                and (old.metadata or {}).get("mcp_server_url") == meta["server_url"]
+            ):
+                await creds_manager.store.delete_creds_by_id(user_id, old.id)
+                logger.info(
+                    "Removed old MCP credential %s for %s",
+                    old.id,
+                    server_host(meta["server_url"]),
+                )
+    except Exception:
+        logger.debug("Could not clean up old MCP credentials", exc_info=True)
+
+    await creds_manager.create(user_id, credentials)
+
+    return CredentialsMetaResponse(
+        id=credentials.id,
+        provider=credentials.provider,
+        type=credentials.type,
+        title=credentials.title,
+        scopes=credentials.scopes,
+        username=credentials.username,
+        host=credentials.metadata.get("mcp_server_url"),
+    )
+
+
+# ======================== Bearer Token ======================== #
+
+
+class MCPStoreTokenRequest(BaseModel):
+    """Request to store a bearer token for an MCP server that doesn't support OAuth."""
+
+    server_url: str = Field(
+        description="MCP server URL the token authenticates against"
+    )
+    token: SecretStr = Field(
+        min_length=1, description="Bearer token / API key for the MCP server"
+    )
+
+
+@router.post(
+    "/token",
+    summary="Store a bearer token for an MCP server",
+)
+async def mcp_store_token(
+    request: MCPStoreTokenRequest,
+    user_id: Annotated[str, Security(get_user_id)],
+) -> CredentialsMetaResponse:
+    """
+    Store a manually provided bearer token as an MCP credential.
+
+    Used by the Copilot MCPSetupCard when the server doesn't support the MCP
+    OAuth discovery flow (returns 400 from /oauth/login).  Subsequent
+    ``run_mcp_tool`` calls will automatically pick up the token via
+    ``_auto_lookup_credential``.
+    """
+    token = request.token.get_secret_value().strip()
+    if not token:
+        raise fastapi.HTTPException(status_code=422, detail="Token must not be blank.")
+
+    # Validate URL to prevent SSRF — blocks loopback and private IP ranges.
+    try:
+        await validate_url(request.server_url, trusted_origins=[])
+    except ValueError as e:
+        raise fastapi.HTTPException(status_code=400, detail=f"Invalid server URL: {e}")
+
+    # Normalize URL so trailing-slash variants match existing credentials.
+    server_url = normalize_mcp_url(request.server_url)
+    hostname = server_host(server_url)
+
+    # Collect IDs of old credentials to clean up after successful create.
+    old_cred_ids: list[str] = []
+    try:
+        old_creds = await creds_manager.store.get_creds_by_provider(
+            user_id, ProviderName.MCP.value
+        )
+        old_cred_ids = [
+            old.id
+            for old in old_creds
+            if isinstance(old, OAuth2Credentials)
+            and normalize_mcp_url((old.metadata or {}).get("mcp_server_url", ""))
+            == server_url
+        ]
+    except Exception:
+        logger.debug("Could not query old MCP token credentials", exc_info=True)
+
+    credentials = OAuth2Credentials(
+        provider=ProviderName.MCP.value,
+        title=f"MCP: {hostname}",
+        access_token=SecretStr(token),
+        scopes=[],
+        metadata={"mcp_server_url": server_url},
+    )
+    await creds_manager.create(user_id, credentials)
+
+    # Only delete old credentials after the new one is safely stored.
+    for old_id in old_cred_ids:
+        try:
+            await creds_manager.store.delete_creds_by_id(user_id, old_id)
+        except Exception:
+            logger.debug("Could not clean up old MCP token credential", exc_info=True)
+
+    return CredentialsMetaResponse(
+        id=credentials.id,
+        provider=credentials.provider,
+        type=credentials.type,
+        title=credentials.title,
+        scopes=credentials.scopes,
+        username=credentials.username,
+        host=hostname,
+    )
+
+
+# ======================== Helpers ======================== #
+
+
+async def _register_mcp_client(
+    registration_endpoint: str,
+    redirect_uri: str,
+    server_url: str,
+) -> dict[str, Any] | None:
+    """Attempt Dynamic Client Registration (RFC 7591) with an MCP auth server."""
+    try:
+        response = await Requests(raise_for_status=True).post(
+            registration_endpoint,
+            json={
+                "client_name": "AutoGPT Platform",
+                "redirect_uris": [redirect_uri],
+                "grant_types": ["authorization_code"],
+                "response_types": ["code"],
+                "token_endpoint_auth_method": "client_secret_post",
+            },
+        )
+        data = response.json()
+        if isinstance(data, dict) and "client_id" in data:
+            return data
+        return None
+    except Exception as e:
+        logger.warning(
+            "Dynamic client registration failed for %s: %s", server_host(server_url), e
+        )
+        return None

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

@@ -0,0 +1,572 @@
+"""Tests for MCP API routes.
+
+Uses httpx.AsyncClient with ASGITransport instead of fastapi.testclient.TestClient
+to avoid creating blocking portals that can corrupt pytest-asyncio's session event loop.
+"""
+
+from unittest.mock import AsyncMock, patch
+
+import fastapi
+import httpx
+import pytest
+import pytest_asyncio
+from autogpt_libs.auth import get_user_id
+from pydantic import SecretStr
+
+from backend.api.features.mcp.routes import router
+from backend.blocks.mcp.client import MCPClientError, MCPTool
+from backend.data.model import OAuth2Credentials
+from backend.util.request import HTTPClientError
+
+app = fastapi.FastAPI()
+app.include_router(router)
+app.dependency_overrides[get_user_id] = lambda: "test-user-id"
+
+
+@pytest_asyncio.fixture(scope="module")
+async def client():
+    transport = httpx.ASGITransport(app=app)
+    async with httpx.AsyncClient(transport=transport, base_url="http://test") as c:
+        yield c
+
+
+@pytest.fixture(autouse=True)
+def _bypass_ssrf_validation():
+    """Bypass validate_url in all route tests (test URLs don't resolve)."""
+    with patch(
+        "backend.api.features.mcp.routes.validate_url",
+        new_callable=AsyncMock,
+    ):
+        yield
+
+
+class TestDiscoverTools:
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_success(self, client):
+        mock_tools = [
+            MCPTool(
+                name="get_weather",
+                description="Get weather for a city",
+                input_schema={
+                    "type": "object",
+                    "properties": {"city": {"type": "string"}},
+                    "required": ["city"],
+                },
+            ),
+            MCPTool(
+                name="add_numbers",
+                description="Add two numbers",
+                input_schema={
+                    "type": "object",
+                    "properties": {
+                        "a": {"type": "number"},
+                        "b": {"type": "number"},
+                    },
+                },
+            ),
+        ]
+
+        with (
+            patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
+            patch(
+                "backend.api.features.mcp.routes.auto_lookup_mcp_credential",
+                new_callable=AsyncMock,
+                return_value=None,
+            ),
+        ):
+            instance = MockClient.return_value
+            instance.initialize = AsyncMock(
+                return_value={
+                    "protocolVersion": "2025-03-26",
+                    "serverInfo": {"name": "test-server"},
+                }
+            )
+            instance.list_tools = AsyncMock(return_value=mock_tools)
+
+            response = await client.post(
+                "/discover-tools",
+                json={"server_url": "https://mcp.example.com/mcp"},
+            )
+
+        assert response.status_code == 200
+        data = response.json()
+        assert len(data["tools"]) == 2
+        assert data["tools"][0]["name"] == "get_weather"
+        assert data["tools"][1]["name"] == "add_numbers"
+        assert data["server_name"] == "test-server"
+        assert data["protocol_version"] == "2025-03-26"
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_with_auth_token(self, client):
+        with patch("backend.api.features.mcp.routes.MCPClient") as MockClient:
+            instance = MockClient.return_value
+            instance.initialize = AsyncMock(
+                return_value={"serverInfo": {}, "protocolVersion": "2025-03-26"}
+            )
+            instance.list_tools = AsyncMock(return_value=[])
+
+            response = await client.post(
+                "/discover-tools",
+                json={
+                    "server_url": "https://mcp.example.com/mcp",
+                    "auth_token": "my-secret-token",
+                },
+            )
+
+        assert response.status_code == 200
+        MockClient.assert_called_once_with(
+            "https://mcp.example.com/mcp",
+            auth_token="my-secret-token",
+        )
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_auto_uses_stored_credential(self, client):
+        """When no explicit token is given, stored MCP credentials are used."""
+        stored_cred = OAuth2Credentials(
+            provider="mcp",
+            title="MCP: example.com",
+            access_token=SecretStr("stored-token-123"),
+            refresh_token=None,
+            access_token_expires_at=None,
+            refresh_token_expires_at=None,
+            scopes=[],
+            metadata={"mcp_server_url": "https://mcp.example.com/mcp"},
+        )
+
+        with (
+            patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
+            patch(
+                "backend.api.features.mcp.routes.auto_lookup_mcp_credential",
+                new_callable=AsyncMock,
+                return_value=stored_cred,
+            ),
+        ):
+            instance = MockClient.return_value
+            instance.initialize = AsyncMock(
+                return_value={"serverInfo": {}, "protocolVersion": "2025-03-26"}
+            )
+            instance.list_tools = AsyncMock(return_value=[])
+
+            response = await client.post(
+                "/discover-tools",
+                json={"server_url": "https://mcp.example.com/mcp"},
+            )
+
+        assert response.status_code == 200
+        MockClient.assert_called_once_with(
+            "https://mcp.example.com/mcp",
+            auth_token="stored-token-123",
+        )
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_mcp_error(self, client):
+        with (
+            patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
+            patch(
+                "backend.api.features.mcp.routes.auto_lookup_mcp_credential",
+                new_callable=AsyncMock,
+                return_value=None,
+            ),
+        ):
+            instance = MockClient.return_value
+            instance.initialize = AsyncMock(
+                side_effect=MCPClientError("Connection refused")
+            )
+
+            response = await client.post(
+                "/discover-tools",
+                json={"server_url": "https://bad-server.example.com/mcp"},
+            )
+
+        assert response.status_code == 502
+        assert "Connection refused" in response.json()["detail"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_generic_error(self, client):
+        with (
+            patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
+            patch(
+                "backend.api.features.mcp.routes.auto_lookup_mcp_credential",
+                new_callable=AsyncMock,
+                return_value=None,
+            ),
+        ):
+            instance = MockClient.return_value
+            instance.initialize = AsyncMock(side_effect=Exception("Network timeout"))
+
+            response = await client.post(
+                "/discover-tools",
+                json={"server_url": "https://timeout.example.com/mcp"},
+            )
+
+        assert response.status_code == 502
+        assert "Failed to connect" in response.json()["detail"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_auth_required(self, client):
+        with (
+            patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
+            patch(
+                "backend.api.features.mcp.routes.auto_lookup_mcp_credential",
+                new_callable=AsyncMock,
+                return_value=None,
+            ),
+        ):
+            instance = MockClient.return_value
+            instance.initialize = AsyncMock(
+                side_effect=HTTPClientError("HTTP 401 Error: Unauthorized", 401)
+            )
+
+            response = await client.post(
+                "/discover-tools",
+                json={"server_url": "https://auth-server.example.com/mcp"},
+            )
+
+        assert response.status_code == 401
+        assert "requires authentication" in response.json()["detail"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_forbidden(self, client):
+        with (
+            patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
+            patch(
+                "backend.api.features.mcp.routes.auto_lookup_mcp_credential",
+                new_callable=AsyncMock,
+                return_value=None,
+            ),
+        ):
+            instance = MockClient.return_value
+            instance.initialize = AsyncMock(
+                side_effect=HTTPClientError("HTTP 403 Error: Forbidden", 403)
+            )
+
+            response = await client.post(
+                "/discover-tools",
+                json={"server_url": "https://auth-server.example.com/mcp"},
+            )
+
+        assert response.status_code == 401
+        assert "requires authentication" in response.json()["detail"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_discover_tools_missing_url(self, client):
+        response = await client.post("/discover-tools", json={})
+        assert response.status_code == 422
+
+
+class TestOAuthLogin:
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_oauth_login_success(self, client):
+        with (
+            patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
+            patch("backend.api.features.mcp.routes.creds_manager") as mock_cm,
+            patch("backend.api.features.mcp.routes.settings") as mock_settings,
+            patch(
+                "backend.api.features.mcp.routes._register_mcp_client"
+            ) as mock_register,
+        ):
+            instance = MockClient.return_value
+            instance.discover_auth = AsyncMock(
+                return_value={
+                    "authorization_servers": ["https://auth.sentry.io"],
+                    "resource": "https://mcp.sentry.dev/mcp",
+                    "scopes_supported": ["openid"],
+                }
+            )
+            instance.discover_auth_server_metadata = AsyncMock(
+                return_value={
+                    "authorization_endpoint": "https://auth.sentry.io/authorize",
+                    "token_endpoint": "https://auth.sentry.io/token",
+                    "registration_endpoint": "https://auth.sentry.io/register",
+                }
+            )
+            mock_register.return_value = {
+                "client_id": "registered-client-id",
+                "client_secret": "registered-secret",
+            }
+            mock_cm.store.store_state_token = AsyncMock(
+                return_value=("state-token-123", "code-challenge-abc")
+            )
+            mock_settings.config.frontend_base_url = "http://localhost:3000"
+
+            response = await client.post(
+                "/oauth/login",
+                json={"server_url": "https://mcp.sentry.dev/mcp"},
+            )
+
+        assert response.status_code == 200
+        data = response.json()
+        assert "login_url" in data
+        assert data["state_token"] == "state-token-123"
+        assert "auth.sentry.io/authorize" in data["login_url"]
+        assert "registered-client-id" in data["login_url"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_oauth_login_no_oauth_support(self, client):
+        with patch("backend.api.features.mcp.routes.MCPClient") as MockClient:
+            instance = MockClient.return_value
+            instance.discover_auth = AsyncMock(return_value=None)
+            instance.discover_auth_server_metadata = AsyncMock(return_value=None)
+
+            response = await client.post(
+                "/oauth/login",
+                json={"server_url": "https://simple-server.example.com/mcp"},
+            )
+
+        assert response.status_code == 400
+        assert "does not advertise OAuth" in response.json()["detail"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_oauth_login_fallback_to_public_client(self, client):
+        """When DCR is unavailable, falls back to default public client ID."""
+        with (
+            patch("backend.api.features.mcp.routes.MCPClient") as MockClient,
+            patch("backend.api.features.mcp.routes.creds_manager") as mock_cm,
+            patch("backend.api.features.mcp.routes.settings") as mock_settings,
+        ):
+            instance = MockClient.return_value
+            instance.discover_auth = AsyncMock(
+                return_value={
+                    "authorization_servers": ["https://auth.example.com"],
+                    "resource": "https://mcp.example.com/mcp",
+                }
+            )
+            instance.discover_auth_server_metadata = AsyncMock(
+                return_value={
+                    "authorization_endpoint": "https://auth.example.com/authorize",
+                    "token_endpoint": "https://auth.example.com/token",
+                    # No registration_endpoint
+                }
+            )
+            mock_cm.store.store_state_token = AsyncMock(
+                return_value=("state-abc", "challenge-xyz")
+            )
+            mock_settings.config.frontend_base_url = "http://localhost:3000"
+
+            response = await client.post(
+                "/oauth/login",
+                json={"server_url": "https://mcp.example.com/mcp"},
+            )
+
+        assert response.status_code == 200
+        data = response.json()
+        assert "autogpt-platform" in data["login_url"]
+
+
+class TestOAuthCallback:
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_oauth_callback_success(self, client):
+        mock_creds = OAuth2Credentials(
+            provider="mcp",
+            title=None,
+            access_token=SecretStr("access-token-xyz"),
+            refresh_token=None,
+            access_token_expires_at=None,
+            refresh_token_expires_at=None,
+            scopes=[],
+            metadata={
+                "mcp_token_url": "https://auth.sentry.io/token",
+                "mcp_resource_url": "https://mcp.sentry.dev/mcp",
+            },
+        )
+
+        with (
+            patch("backend.api.features.mcp.routes.creds_manager") as mock_cm,
+            patch("backend.api.features.mcp.routes.settings") as mock_settings,
+            patch("backend.api.features.mcp.routes.MCPOAuthHandler") as MockHandler,
+        ):
+            mock_settings.config.frontend_base_url = "http://localhost:3000"
+
+            # Mock state verification
+            mock_state = AsyncMock()
+            mock_state.state_metadata = {
+                "authorize_url": "https://auth.sentry.io/authorize",
+                "token_url": "https://auth.sentry.io/token",
+                "client_id": "test-client-id",
+                "client_secret": "test-secret",
+                "server_url": "https://mcp.sentry.dev/mcp",
+            }
+            mock_state.scopes = ["openid"]
+            mock_state.code_verifier = "verifier-123"
+            mock_cm.store.verify_state_token = AsyncMock(return_value=mock_state)
+            mock_cm.create = AsyncMock()
+
+            handler_instance = MockHandler.return_value
+            handler_instance.exchange_code_for_tokens = AsyncMock(
+                return_value=mock_creds
+            )
+
+            # Mock old credential cleanup
+            mock_cm.store.get_creds_by_provider = AsyncMock(return_value=[])
+
+            response = await client.post(
+                "/oauth/callback",
+                json={"code": "auth-code-abc", "state_token": "state-token-123"},
+            )
+
+        assert response.status_code == 200
+        data = response.json()
+        assert "id" in data
+        assert data["provider"] == "mcp"
+        assert data["type"] == "oauth2"
+        mock_cm.create.assert_called_once()
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_oauth_callback_invalid_state(self, client):
+        with patch("backend.api.features.mcp.routes.creds_manager") as mock_cm:
+            mock_cm.store.verify_state_token = AsyncMock(return_value=None)
+
+            response = await client.post(
+                "/oauth/callback",
+                json={"code": "auth-code", "state_token": "bad-state"},
+            )
+
+        assert response.status_code == 400
+        assert "Invalid or expired" in response.json()["detail"]
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_oauth_callback_token_exchange_fails(self, client):
+        with (
+            patch("backend.api.features.mcp.routes.creds_manager") as mock_cm,
+            patch("backend.api.features.mcp.routes.settings") as mock_settings,
+            patch("backend.api.features.mcp.routes.MCPOAuthHandler") as MockHandler,
+        ):
+            mock_settings.config.frontend_base_url = "http://localhost:3000"
+            mock_state = AsyncMock()
+            mock_state.state_metadata = {
+                "authorize_url": "https://auth.example.com/authorize",
+                "token_url": "https://auth.example.com/token",
+                "client_id": "cid",
+                "server_url": "https://mcp.example.com/mcp",
+            }
+            mock_state.scopes = []
+            mock_state.code_verifier = "v"
+            mock_cm.store.verify_state_token = AsyncMock(return_value=mock_state)
+
+            handler_instance = MockHandler.return_value
+            handler_instance.exchange_code_for_tokens = AsyncMock(
+                side_effect=RuntimeError("Token exchange failed")
+            )
+
+            response = await client.post(
+                "/oauth/callback",
+                json={"code": "bad-code", "state_token": "state"},
+            )
+
+        assert response.status_code == 400
+        assert "token exchange failed" in response.json()["detail"].lower()
+
+
+class TestStoreToken:
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_store_token_success(self, client):
+        with patch("backend.api.features.mcp.routes.creds_manager") as mock_cm:
+            mock_cm.store.get_creds_by_provider = AsyncMock(return_value=[])
+            mock_cm.create = AsyncMock()
+
+            response = await client.post(
+                "/token",
+                json={
+                    "server_url": "https://mcp.example.com/mcp",
+                    "token": "my-api-key-123",
+                },
+            )
+
+        assert response.status_code == 200
+        data = response.json()
+        assert data["provider"] == "mcp"
+        assert data["type"] == "oauth2"
+        assert data["host"] == "mcp.example.com"
+        mock_cm.create.assert_called_once()
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_store_token_blank_rejected(self, client):
+        """Blank token string (after stripping) should return 422."""
+        response = await client.post(
+            "/token",
+            json={
+                "server_url": "https://mcp.example.com/mcp",
+                "token": "   ",
+            },
+        )
+        # Pydantic min_length=1 catches the whitespace-only token
+        assert response.status_code == 422
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_store_token_replaces_old_credential(self, client):
+        old_cred = OAuth2Credentials(
+            provider="mcp",
+            title="MCP: mcp.example.com",
+            access_token=SecretStr("old-token"),
+            scopes=[],
+            metadata={"mcp_server_url": "https://mcp.example.com/mcp"},
+        )
+        with patch("backend.api.features.mcp.routes.creds_manager") as mock_cm:
+            mock_cm.store.get_creds_by_provider = AsyncMock(return_value=[old_cred])
+            mock_cm.create = AsyncMock()
+            mock_cm.store.delete_creds_by_id = AsyncMock()
+
+            response = await client.post(
+                "/token",
+                json={
+                    "server_url": "https://mcp.example.com/mcp",
+                    "token": "new-token",
+                },
+            )
+
+        assert response.status_code == 200
+        mock_cm.store.delete_creds_by_id.assert_called_once_with(
+            "test-user-id", old_cred.id
+        )
+
+
+class TestSSRFValidation:
+    """Verify that validate_url 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",
+            new_callable=AsyncMock,
+            side_effect=ValueError("blocked loopback"),
+        ):
+            response = await client.post(
+                "/discover-tools",
+                json={"server_url": "http://localhost/mcp"},
+            )
+
+        assert response.status_code == 400
+        assert "blocked loopback" in response.json()["detail"].lower()
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_oauth_login_ssrf_blocked(self, client):
+        with patch(
+            "backend.api.features.mcp.routes.validate_url",
+            new_callable=AsyncMock,
+            side_effect=ValueError("blocked private IP"),
+        ):
+            response = await client.post(
+                "/oauth/login",
+                json={"server_url": "http://10.0.0.1/mcp"},
+            )
+
+        assert response.status_code == 400
+        assert "blocked private ip" in response.json()["detail"].lower()
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_store_token_ssrf_blocked(self, client):
+        with patch(
+            "backend.api.features.mcp.routes.validate_url",
+            new_callable=AsyncMock,
+            side_effect=ValueError("blocked loopback"),
+        ):
+            response = await client.post(
+                "/token",
+                json={
+                    "server_url": "http://127.0.0.1/mcp",
+                    "token": "some-token",
+                },
+            )
+
+        assert response.status_code == 400
+        assert "blocked loopback" in response.json()["detail"].lower()

autogpt_platform/backend/backend/api/features/otto/service.py

@@ -5,8 +5,8 @@ from typing import Optional
 import aiohttp
 from fastapi import HTTPException
 
+from backend.blocks import get_block
 from backend.data import graph as graph_db
-from backend.data.block import get_block
 from backend.util.settings import Settings
 
 from .models import ApiResponse, ChatRequest, GraphData

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

@@ -9,15 +9,26 @@ import logging
 from abc import ABC, abstractmethod
 from dataclasses import dataclass
 from pathlib import Path
-from typing import Any
+from typing import Any, get_args, get_origin
 
 from prisma.enums import ContentType
 
+from backend.blocks.llm import LlmModel
 from backend.data.db import query_raw_with_schema
 
 logger = logging.getLogger(__name__)
 
 
+def _contains_type(annotation: Any, target: type) -> bool:
+    """Check if an annotation is or contains the target type (handles Optional/Union/Annotated)."""
+    if annotation is target:
+        return True
+    origin = get_origin(annotation)
+    if origin is None:
+        return False
+    return any(_contains_type(arg, target) for arg in get_args(annotation))
+
+
 @dataclass
 class ContentItem:
     """Represents a piece of content to be embedded."""
@@ -152,7 +163,7 @@ class BlockHandler(ContentHandler):
 
     async def get_missing_items(self, batch_size: int) -> list[ContentItem]:
         """Fetch blocks without embeddings."""
-        from backend.data.block import get_blocks
+        from backend.blocks import get_blocks
 
         # Get all available blocks
         all_blocks = get_blocks()
@@ -188,45 +199,51 @@ class BlockHandler(ContentHandler):
             try:
                 block_instance = block_cls()
 
-                # Skip disabled blocks - they shouldn't be indexed
                 if block_instance.disabled:
                     continue
 
                 # Build searchable text from block metadata
                 parts = []
-                if hasattr(block_instance, "name") and block_instance.name:
+                if block_instance.name:
                     parts.append(block_instance.name)
-                if (
-                    hasattr(block_instance, "description")
-                    and block_instance.description
-                ):
+                if block_instance.description:
                     parts.append(block_instance.description)
-                if hasattr(block_instance, "categories") and block_instance.categories:
-                    # Convert BlockCategory enum to strings
+                if block_instance.categories:
                     parts.append(
                         " ".join(str(cat.value) for cat in block_instance.categories)
                     )
 
-                # Add input/output schema info
-                if hasattr(block_instance, "input_schema"):
-                    schema = block_instance.input_schema
-                    if hasattr(schema, "model_json_schema"):
-                        schema_dict = schema.model_json_schema()
-                        if "properties" in schema_dict:
-                            for prop_name, prop_info in schema_dict[
-                                "properties"
-                            ].items():
-                                if "description" in prop_info:
-                                    parts.append(
-                                        f"{prop_name}: {prop_info['description']}"
-                                    )
+                # 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()
+                    if field_info.description
+                ]
 
                 searchable_text = " ".join(parts)
 
-                # Convert categories set of enums to list of strings for JSON serialization
-                categories = getattr(block_instance, "categories", set())
                 categories_list = (
-                    [cat.value for cat in categories] if categories else []
+                    [cat.value for cat in block_instance.categories]
+                    if block_instance.categories
+                    else []
+                )
+
+                # Extract provider names from credentials fields
+                credentials_info = (
+                    block_instance.input_schema.get_credentials_fields_info()
+                )
+                is_integration = len(credentials_info) > 0
+                provider_names = [
+                    provider.value.lower()
+                    for info in credentials_info.values()
+                    for provider in info.provider
+                ]
+
+                # 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()
                 )
 
                 items.append(
@@ -235,8 +252,11 @@ class BlockHandler(ContentHandler):
                         content_type=ContentType.BLOCK,
                         searchable_text=searchable_text,
                         metadata={
-                            "name": getattr(block_instance, "name", ""),
+                            "name": block_instance.name,
                             "categories": categories_list,
+                            "providers": provider_names,
+                            "has_llm_model_field": has_llm_model_field,
+                            "is_integration": is_integration,
                         },
                         user_id=None,  # Blocks are public
                     )
@@ -249,7 +269,7 @@ class BlockHandler(ContentHandler):
 
     async def get_stats(self) -> dict[str, int]:
         """Get statistics about block embedding coverage."""
-        from backend.data.block import get_blocks
+        from backend.blocks import get_blocks
 
         all_blocks = get_blocks()
 

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

@@ -82,9 +82,10 @@ async def test_block_handler_get_missing_items(mocker):
     mock_block_instance.description = "Performs calculations"
     mock_block_instance.categories = [MagicMock(value="MATH")]
     mock_block_instance.disabled = False
-    mock_block_instance.input_schema.model_json_schema.return_value = {
-        "properties": {"expression": {"description": "Math expression to evaluate"}}
-    }
+    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}
@@ -93,7 +94,7 @@ async def test_block_handler_get_missing_items(mocker):
     mock_existing = []
 
     with patch(
-        "backend.data.block.get_blocks",
+        "backend.blocks.get_blocks",
         return_value=mock_blocks,
     ):
         with patch(
@@ -135,7 +136,7 @@ async def test_block_handler_get_stats(mocker):
     mock_embedded = [{"count": 2}]
 
     with patch(
-        "backend.data.block.get_blocks",
+        "backend.blocks.get_blocks",
         return_value=mock_blocks,
     ):
         with patch(
@@ -309,25 +310,25 @@ async def test_content_handlers_registry():
 
 
 @pytest.mark.asyncio(loop_scope="session")
-async def test_block_handler_handles_missing_attributes():
-    """Test BlockHandler gracefully handles blocks with missing attributes."""
+async def test_block_handler_handles_empty_attributes():
+    """Test BlockHandler handles blocks with empty/falsy attribute values."""
     handler = BlockHandler()
 
-    # Mock block with minimal attributes
+    # 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
-    # No description, categories, or schema
-    del mock_block_instance.description
-    del mock_block_instance.categories
-    del mock_block_instance.input_schema
+    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.data.block.get_blocks",
+        "backend.blocks.get_blocks",
         return_value=mock_blocks,
     ):
         with patch(
@@ -352,6 +353,8 @@ async def test_block_handler_skips_failed_blocks():
     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()
@@ -360,7 +363,7 @@ async def test_block_handler_skips_failed_blocks():
     mock_blocks = {"good-block": good_block, "bad-block": bad_block}
 
     with patch(
-        "backend.data.block.get_blocks",
+        "backend.blocks.get_blocks",
         return_value=mock_blocks,
     ):
         with patch(

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

@@ -662,7 +662,7 @@ async def cleanup_orphaned_embeddings() -> dict[str, Any]:
                 )
                 current_ids = {row["id"] for row in valid_agents}
             elif content_type == ContentType.BLOCK:
-                from backend.data.block import get_blocks
+                from backend.blocks import get_blocks
 
                 current_ids = set(get_blocks().keys())
             elif content_type == ContentType.DOCUMENTATION:

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

@@ -8,6 +8,7 @@ Includes BM25 reranking for improved lexical relevance.
 
 import logging
 import re
+import time
 from dataclasses import dataclass
 from typing import Any, Literal
 
@@ -362,7 +363,11 @@ async def unified_hybrid_search(
         LIMIT {limit_param} OFFSET {offset_param}
     """
 
-    results = await query_raw_with_schema(sql_query, *params)
+    try:
+        results = await query_raw_with_schema(sql_query, *params)
+    except Exception as e:
+        await _log_vector_error_diagnostics(e)
+        raise
 
     total = results[0]["total_count"] if results else 0
     # Apply BM25 reranking
@@ -563,7 +568,7 @@ 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})
@@ -577,7 +582,7 @@ 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}
@@ -600,7 +605,7 @@ 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
@@ -622,9 +627,9 @@ 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 (
@@ -660,7 +665,7 @@ async def hybrid_search(
                 featured,
                 is_available,
                 updated_at,
-                "agentGraphId",
+                graph_id,
                 searchable_text,
                 semantic_score,
                 lexical_score,
@@ -686,7 +691,11 @@ async def hybrid_search(
         LIMIT {limit_param} OFFSET {offset_param}
     """
 
-    results = await query_raw_with_schema(sql_query, *params)
+    try:
+        results = await query_raw_with_schema(sql_query, *params)
+    except Exception as e:
+        await _log_vector_error_diagnostics(e)
+        raise
 
     total = results[0]["total_count"] if results else 0
 
@@ -718,6 +727,87 @@ async def hybrid_search_simple(
     return await hybrid_search(query=query, page=page, page_size=page_size)
 
 
+# ============================================================================
+# Diagnostics
+# ============================================================================
+
+# Rate limit: only log vector error diagnostics once per this interval
+_VECTOR_DIAG_INTERVAL_SECONDS = 60
+_last_vector_diag_time: float = 0
+
+
+async def _log_vector_error_diagnostics(error: Exception) -> None:
+    """Log diagnostic info when 'type vector does not exist' error occurs.
+
+    Note: Diagnostic queries use query_raw_with_schema which may run on a different
+    pooled connection than the one that failed. Session-level search_path can differ,
+    so these diagnostics show cluster-wide state, not necessarily the failed session.
+
+    Includes rate limiting to avoid log spam - only logs once per minute.
+    Caller should re-raise the error after calling this function.
+    """
+    global _last_vector_diag_time
+
+    # Check if this is the vector type error
+    error_str = str(error).lower()
+    if not (
+        "type" in error_str and "vector" in error_str and "does not exist" in error_str
+    ):
+        return
+
+    # Rate limit: only log once per interval
+    now = time.time()
+    if now - _last_vector_diag_time < _VECTOR_DIAG_INTERVAL_SECONDS:
+        return
+    _last_vector_diag_time = now
+
+    try:
+        diagnostics: dict[str, object] = {}
+
+        try:
+            search_path_result = await query_raw_with_schema("SHOW search_path")
+            diagnostics["search_path"] = search_path_result
+        except Exception as e:
+            diagnostics["search_path"] = f"Error: {e}"
+
+        try:
+            schema_result = await query_raw_with_schema("SELECT current_schema()")
+            diagnostics["current_schema"] = schema_result
+        except Exception as e:
+            diagnostics["current_schema"] = f"Error: {e}"
+
+        try:
+            user_result = await query_raw_with_schema(
+                "SELECT current_user, session_user, current_database()"
+            )
+            diagnostics["user_info"] = user_result
+        except Exception as e:
+            diagnostics["user_info"] = f"Error: {e}"
+
+        try:
+            # Check pgvector extension installation (cluster-wide, stable info)
+            ext_result = await query_raw_with_schema(
+                "SELECT extname, extversion, nspname as schema "
+                "FROM pg_extension e "
+                "JOIN pg_namespace n ON e.extnamespace = n.oid "
+                "WHERE extname = 'vector'"
+            )
+            diagnostics["pgvector_extension"] = ext_result
+        except Exception as e:
+            diagnostics["pgvector_extension"] = f"Error: {e}"
+
+        logger.error(
+            f"Vector type error diagnostics:\n"
+            f"  Error: {error}\n"
+            f"  search_path: {diagnostics.get('search_path')}\n"
+            f"  current_schema: {diagnostics.get('current_schema')}\n"
+            f"  user_info: {diagnostics.get('user_info')}\n"
+            f"  pgvector_extension: {diagnostics.get('pgvector_extension')}"
+        )
+    except Exception as diag_error:
+        logger.error(f"Failed to collect vector error diagnostics: {diag_error}")
+
+
 # Backward compatibility alias - HybridSearchWeights maps to StoreAgentSearchWeights
 # for existing code that expects the popularity parameter
 HybridSearchWeights = StoreAgentSearchWeights

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

@@ -7,15 +7,6 @@ from replicate.client import Client as ReplicateClient
 from replicate.exceptions import ReplicateError
 from replicate.helpers import FileOutput
 
-from backend.blocks.ideogram import (
-    AspectRatio,
-    ColorPalettePreset,
-    IdeogramModelBlock,
-    IdeogramModelName,
-    MagicPromptOption,
-    StyleType,
-    UpscaleOption,
-)
 from backend.data.graph import GraphBaseMeta
 from backend.data.model import CredentialsMetaInput, ProviderName
 from backend.integrations.credentials_store import ideogram_credentials
@@ -50,6 +41,16 @@ async def generate_agent_image_v2(graph: GraphBaseMeta | AgentGraph) -> io.Bytes
     if not ideogram_credentials.api_key:
         raise ValueError("Missing Ideogram API key")
 
+    from backend.blocks.ideogram import (
+        AspectRatio,
+        ColorPalettePreset,
+        IdeogramModelBlock,
+        IdeogramModelName,
+        MagicPromptOption,
+        StyleType,
+        UpscaleOption,
+    )
+
     name = graph.name
     description = f"{name} ({graph.description})" if graph.description else name
 

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 +1,17 @@
 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 +35,15 @@ 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 +51,17 @@ 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 +71,30 @@ 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 +128,69 @@ 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 +200,82 @@ 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.FileResponse:
+    """Download agent graph file for a specific marketplace listing version"""
+    graph_data = await store_db.get_agent(store_listing_version_id)
+    file_name = f"agent_{graph_data.id}_v{graph_data.version or 'latest'}.json"
+
+    # 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"
+        )
+
+
 ##############################################
 ############# Creator Endpoints #############
 ##############################################
@@ -349,37 +285,19 @@ 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 +309,12 @@ 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 +326,17 @@ 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 +345,17 @@ 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 +363,14 @@ 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 +383,17 @@ 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 +406,6 @@ 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 +413,14 @@ 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 +435,6 @@ async def edit_submission(
         changes_summary=submission_request.changes_summary,
         recommended_schedule_cron=submission_request.recommended_schedule_cron,
     )
-
     return result
 
 
@@ -596,115 +442,61 @@ 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/v1.py

@@ -40,10 +40,11 @@ from backend.api.model import (
     UpdateTimezoneRequest,
     UploadFileResponse,
 )
+from backend.blocks import get_block, get_blocks
 from backend.data import execution as execution_db
 from backend.data import graph as graph_db
 from backend.data.auth import api_key as api_key_db
-from backend.data.block import BlockInput, CompletedBlockOutput, get_block, get_blocks
+from backend.data.block import BlockInput, CompletedBlockOutput
 from backend.data.credit import (
     AutoTopUpConfig,
     RefundRequest,
@@ -125,6 +126,9 @@ v1_router = APIRouter()
 ########################################################
 
 
+_tally_background_tasks: set[asyncio.Task] = set()
+
+
 @v1_router.post(
     "/auth/user",
     summary="Get or create user",
@@ -133,6 +137,24 @@ v1_router = APIRouter()
 )
 async def get_or_create_user_route(user_data: dict = Security(get_jwt_payload)):
     user = await get_or_create_user(user_data)
+
+    # Fire-and-forget: populate business understanding from Tally form.
+    # We use created_at proximity instead of an is_new flag because
+    # get_or_create_user is cached — a separate is_new return value would be
+    # unreliable on repeated calls within the cache TTL.
+    age_seconds = (datetime.now(timezone.utc) - user.created_at).total_seconds()
+    if age_seconds < 30:
+        try:
+            from backend.data.tally import populate_understanding_from_tally
+
+            task = asyncio.create_task(
+                populate_understanding_from_tally(user.id, user.email)
+            )
+            _tally_background_tasks.add(task)
+            task.add_done_callback(_tally_background_tasks.discard)
+        except Exception:
+            logger.debug("Failed to start Tally population task", exc_info=True)
+
     return user.model_dump()
 
 
@@ -427,7 +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:
     """
@@ -490,7 +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

@@ -1,5 +1,5 @@
 import json
-from datetime import datetime
+from datetime import datetime, timezone
 from io import BytesIO
 from unittest.mock import AsyncMock, Mock, patch
 
@@ -43,6 +43,7 @@ def test_get_or_create_user_route(
 ) -> None:
     """Test get or create user endpoint"""
     mock_user = Mock()
+    mock_user.created_at = datetime.now(timezone.utc)
     mock_user.model_dump.return_value = {
         "id": test_user_id,
         "email": "test@example.com",
@@ -514,7 +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,
         )
 
@@ -532,7 +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/features/workspace/routes.py

@@ -3,15 +3,29 @@ Workspace API routes for managing user file storage.
 """
 
 import logging
+import os
 import re
 from typing import Annotated
 from urllib.parse import quote
 
 import fastapi
 from autogpt_libs.auth.dependencies import get_user_id, requires_user
+from fastapi import Query, UploadFile
 from fastapi.responses import Response
+from pydantic import BaseModel
 
-from backend.data.workspace import get_workspace, get_workspace_file
+from backend.data.workspace import (
+    WorkspaceFile,
+    count_workspace_files,
+    get_or_create_workspace,
+    get_workspace,
+    get_workspace_file,
+    get_workspace_total_size,
+    soft_delete_workspace_file,
+)
+from backend.util.settings import Config
+from backend.util.virus_scanner import scan_content_safe
+from backend.util.workspace import WorkspaceManager
 from backend.util.workspace_storage import get_workspace_storage
 
 
@@ -44,11 +58,11 @@ router = fastapi.APIRouter(
 )
 
 
-def _create_streaming_response(content: bytes, file) -> Response:
+def _create_streaming_response(content: bytes, file: WorkspaceFile) -> Response:
     """Create a streaming response for file content."""
     return Response(
         content=content,
-        media_type=file.mimeType,
+        media_type=file.mime_type,
         headers={
             "Content-Disposition": _sanitize_filename_for_header(file.name),
             "Content-Length": str(len(content)),
@@ -56,7 +70,7 @@ def _create_streaming_response(content: bytes, file) -> Response:
     )
 
 
-async def _create_file_download_response(file) -> Response:
+async def _create_file_download_response(file: WorkspaceFile) -> Response:
     """
     Create a download response for a workspace file.
 
@@ -66,38 +80,57 @@ async def _create_file_download_response(file) -> Response:
     storage = await get_workspace_storage()
 
     # For local storage, stream the file directly
-    if file.storagePath.startswith("local://"):
-        content = await storage.retrieve(file.storagePath)
+    if file.storage_path.startswith("local://"):
+        content = await storage.retrieve(file.storage_path)
         return _create_streaming_response(content, file)
 
     # For GCS, try to redirect to signed URL, fall back to streaming
     try:
-        url = await storage.get_download_url(file.storagePath, expires_in=300)
+        url = await storage.get_download_url(file.storage_path, expires_in=300)
         # If we got back an API path (fallback), stream directly instead
         if url.startswith("/api/"):
-            content = await storage.retrieve(file.storagePath)
+            content = await storage.retrieve(file.storage_path)
             return _create_streaming_response(content, file)
         return fastapi.responses.RedirectResponse(url=url, status_code=302)
     except Exception as e:
         # Log the signed URL failure with context
         logger.error(
             f"Failed to get signed URL for file {file.id} "
-            f"(storagePath={file.storagePath}): {e}",
+            f"(storagePath={file.storage_path}): {e}",
             exc_info=True,
         )
         # Fall back to streaming directly from GCS
         try:
-            content = await storage.retrieve(file.storagePath)
+            content = await storage.retrieve(file.storage_path)
             return _create_streaming_response(content, file)
         except Exception as fallback_error:
             logger.error(
                 f"Fallback streaming also failed for file {file.id} "
-                f"(storagePath={file.storagePath}): {fallback_error}",
+                f"(storagePath={file.storage_path}): {fallback_error}",
                 exc_info=True,
             )
             raise
 
 
+class UploadFileResponse(BaseModel):
+    file_id: str
+    name: str
+    path: str
+    mime_type: str
+    size_bytes: int
+
+
+class DeleteFileResponse(BaseModel):
+    deleted: bool
+
+
+class StorageUsageResponse(BaseModel):
+    used_bytes: int
+    limit_bytes: int
+    used_percent: float
+    file_count: int
+
+
 @router.get(
     "/files/{file_id}/download",
     summary="Download file by ID",
@@ -120,3 +153,148 @@ async def download_file(
         raise fastapi.HTTPException(status_code=404, detail="File not found")
 
     return await _create_file_download_response(file)
+
+
+@router.delete(
+    "/files/{file_id}",
+    summary="Delete a workspace file",
+)
+async def delete_workspace_file(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+    file_id: str,
+) -> DeleteFileResponse:
+    """
+    Soft-delete a workspace file and attempt to remove it from storage.
+
+    Used when a user clears a file input in the builder.
+    """
+    workspace = await get_workspace(user_id)
+    if workspace is None:
+        raise fastapi.HTTPException(status_code=404, detail="Workspace not found")
+
+    manager = WorkspaceManager(user_id, workspace.id)
+    deleted = await manager.delete_file(file_id)
+    if not deleted:
+        raise fastapi.HTTPException(status_code=404, detail="File not found")
+
+    return DeleteFileResponse(deleted=True)
+
+
+@router.post(
+    "/files/upload",
+    summary="Upload file to workspace",
+)
+async def upload_file(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+    file: UploadFile,
+    session_id: str | None = Query(default=None),
+) -> UploadFileResponse:
+    """
+    Upload a file to the user's workspace.
+
+    Files are stored in session-scoped paths when session_id is provided,
+    so the agent's session-scoped tools can discover them automatically.
+    """
+    config = Config()
+
+    # Sanitize filename — strip any directory components
+    filename = os.path.basename(file.filename or "upload") or "upload"
+
+    # Read file content with early abort on size limit
+    max_file_bytes = config.max_file_size_mb * 1024 * 1024
+    chunks: list[bytes] = []
+    total_size = 0
+    while chunk := await file.read(64 * 1024):  # 64KB chunks
+        total_size += len(chunk)
+        if total_size > max_file_bytes:
+            raise fastapi.HTTPException(
+                status_code=413,
+                detail=f"File exceeds maximum size of {config.max_file_size_mb} MB",
+            )
+        chunks.append(chunk)
+    content = b"".join(chunks)
+
+    # Get or create workspace
+    workspace = await get_or_create_workspace(user_id)
+
+    # Pre-write storage cap check (soft check — final enforcement is post-write)
+    storage_limit_bytes = config.max_workspace_storage_mb * 1024 * 1024
+    current_usage = await get_workspace_total_size(workspace.id)
+    if storage_limit_bytes and current_usage + len(content) > storage_limit_bytes:
+        used_percent = (current_usage / storage_limit_bytes) * 100
+        raise fastapi.HTTPException(
+            status_code=413,
+            detail={
+                "message": "Storage limit exceeded",
+                "used_bytes": current_usage,
+                "limit_bytes": storage_limit_bytes,
+                "used_percent": round(used_percent, 1),
+            },
+        )
+
+    # Warn at 80% usage
+    if (
+        storage_limit_bytes
+        and (usage_ratio := (current_usage + len(content)) / storage_limit_bytes) >= 0.8
+    ):
+        logger.warning(
+            f"User {user_id} workspace storage at {usage_ratio * 100:.1f}% "
+            f"({current_usage + len(content)} / {storage_limit_bytes} bytes)"
+        )
+
+    # Virus scan
+    await scan_content_safe(content, filename=filename)
+
+    # Write file via WorkspaceManager
+    manager = WorkspaceManager(user_id, workspace.id, session_id)
+    try:
+        workspace_file = await manager.write_file(content, filename)
+    except ValueError as e:
+        raise fastapi.HTTPException(status_code=409, detail=str(e)) from e
+
+    # Post-write storage check — eliminates TOCTOU race on the quota.
+    # If a concurrent upload pushed us over the limit, undo this write.
+    new_total = await get_workspace_total_size(workspace.id)
+    if storage_limit_bytes and new_total > storage_limit_bytes:
+        await soft_delete_workspace_file(workspace_file.id, workspace.id)
+        raise fastapi.HTTPException(
+            status_code=413,
+            detail={
+                "message": "Storage limit exceeded (concurrent upload)",
+                "used_bytes": new_total,
+                "limit_bytes": storage_limit_bytes,
+            },
+        )
+
+    return UploadFileResponse(
+        file_id=workspace_file.id,
+        name=workspace_file.name,
+        path=workspace_file.path,
+        mime_type=workspace_file.mime_type,
+        size_bytes=workspace_file.size_bytes,
+    )
+
+
+@router.get(
+    "/storage/usage",
+    summary="Get workspace storage usage",
+)
+async def get_storage_usage(
+    user_id: Annotated[str, fastapi.Security(get_user_id)],
+) -> StorageUsageResponse:
+    """
+    Get storage usage information for the user's workspace.
+    """
+    config = Config()
+    workspace = await get_or_create_workspace(user_id)
+
+    used_bytes = await get_workspace_total_size(workspace.id)
+    file_count = await count_workspace_files(workspace.id)
+    limit_bytes = config.max_workspace_storage_mb * 1024 * 1024
+
+    return StorageUsageResponse(
+        used_bytes=used_bytes,
+        limit_bytes=limit_bytes,
+        used_percent=round((used_bytes / limit_bytes) * 100, 1) if limit_bytes else 0,
+        file_count=file_count,
+    )

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

@@ -0,0 +1,359 @@
+"""Tests for workspace file upload and download routes."""
+
+import io
+from datetime import datetime, timezone
+
+import fastapi
+import fastapi.testclient
+import pytest
+import pytest_mock
+
+from backend.api.features.workspace import routes as workspace_routes
+from backend.data.workspace import WorkspaceFile
+
+app = fastapi.FastAPI()
+app.include_router(workspace_routes.router)
+
+
+@app.exception_handler(ValueError)
+async def _value_error_handler(
+    request: fastapi.Request, exc: ValueError
+) -> fastapi.responses.JSONResponse:
+    """Mirror the production ValueError → 400 mapping from rest_api.py."""
+    return fastapi.responses.JSONResponse(status_code=400, content={"detail": str(exc)})
+
+
+client = fastapi.testclient.TestClient(app)
+
+TEST_USER_ID = "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
+
+MOCK_WORKSPACE = type("W", (), {"id": "ws-1"})()
+
+_NOW = datetime(2023, 1, 1, tzinfo=timezone.utc)
+
+MOCK_FILE = WorkspaceFile(
+    id="file-aaa-bbb",
+    workspace_id="ws-1",
+    created_at=_NOW,
+    updated_at=_NOW,
+    name="hello.txt",
+    path="/session/hello.txt",
+    mime_type="text/plain",
+    size_bytes=13,
+    storage_path="local://hello.txt",
+)
+
+
+@pytest.fixture(autouse=True)
+def setup_app_auth(mock_jwt_user):
+    from autogpt_libs.auth.jwt_utils import get_jwt_payload
+
+    app.dependency_overrides[get_jwt_payload] = mock_jwt_user["get_jwt_payload"]
+    yield
+    app.dependency_overrides.clear()
+
+
+def _upload(
+    filename: str = "hello.txt",
+    content: bytes = b"Hello, world!",
+    content_type: str = "text/plain",
+):
+    """Helper to POST a file upload."""
+    return client.post(
+        "/files/upload?session_id=sess-1",
+        files={"file": (filename, io.BytesIO(content), content_type)},
+    )
+
+
+# ---- Happy path ----
+
+
+def test_upload_happy_path(mocker: pytest_mock.MockFixture):
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_or_create_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace_total_size",
+        return_value=0,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.scan_content_safe",
+        return_value=None,
+    )
+    mock_manager = mocker.MagicMock()
+    mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
+    mocker.patch(
+        "backend.api.features.workspace.routes.WorkspaceManager",
+        return_value=mock_manager,
+    )
+
+    response = _upload()
+    assert response.status_code == 200
+    data = response.json()
+    assert data["file_id"] == "file-aaa-bbb"
+    assert data["name"] == "hello.txt"
+    assert data["size_bytes"] == 13
+
+
+# ---- Per-file size limit ----
+
+
+def test_upload_exceeds_max_file_size(mocker: pytest_mock.MockFixture):
+    """Files larger than max_file_size_mb should be rejected with 413."""
+    cfg = mocker.patch("backend.api.features.workspace.routes.Config")
+    cfg.return_value.max_file_size_mb = 0  # 0 MB → any content is too big
+    cfg.return_value.max_workspace_storage_mb = 500
+
+    response = _upload(content=b"x" * 1024)
+    assert response.status_code == 413
+
+
+# ---- Storage quota exceeded ----
+
+
+def test_upload_storage_quota_exceeded(mocker: pytest_mock.MockFixture):
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_or_create_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    # Current usage already at limit
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace_total_size",
+        return_value=500 * 1024 * 1024,
+    )
+
+    response = _upload()
+    assert response.status_code == 413
+    assert "Storage limit exceeded" in response.text
+
+
+# ---- Post-write quota race (B2) ----
+
+
+def test_upload_post_write_quota_race(mocker: pytest_mock.MockFixture):
+    """If a concurrent upload tips the total over the limit after write,
+    the file should be soft-deleted and 413 returned."""
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_or_create_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    # Pre-write check passes (under limit), but post-write check fails
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace_total_size",
+        side_effect=[0, 600 * 1024 * 1024],  # first call OK, second over limit
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.scan_content_safe",
+        return_value=None,
+    )
+    mock_manager = mocker.MagicMock()
+    mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
+    mocker.patch(
+        "backend.api.features.workspace.routes.WorkspaceManager",
+        return_value=mock_manager,
+    )
+    mock_delete = mocker.patch(
+        "backend.api.features.workspace.routes.soft_delete_workspace_file",
+        return_value=None,
+    )
+
+    response = _upload()
+    assert response.status_code == 413
+    mock_delete.assert_called_once_with("file-aaa-bbb", "ws-1")
+
+
+# ---- Any extension accepted (no allowlist) ----
+
+
+def test_upload_any_extension(mocker: pytest_mock.MockFixture):
+    """Any file extension should be accepted — ClamAV is the security layer."""
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_or_create_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace_total_size",
+        return_value=0,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.scan_content_safe",
+        return_value=None,
+    )
+    mock_manager = mocker.MagicMock()
+    mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
+    mocker.patch(
+        "backend.api.features.workspace.routes.WorkspaceManager",
+        return_value=mock_manager,
+    )
+
+    response = _upload(filename="data.xyz", content=b"arbitrary")
+    assert response.status_code == 200
+
+
+# ---- Virus scan rejection ----
+
+
+def test_upload_blocked_by_virus_scan(mocker: pytest_mock.MockFixture):
+    """Files flagged by ClamAV should be rejected and never written to storage."""
+    from backend.api.features.store.exceptions import VirusDetectedError
+
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_or_create_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace_total_size",
+        return_value=0,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.scan_content_safe",
+        side_effect=VirusDetectedError("Eicar-Test-Signature"),
+    )
+    mock_manager = mocker.MagicMock()
+    mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
+    mocker.patch(
+        "backend.api.features.workspace.routes.WorkspaceManager",
+        return_value=mock_manager,
+    )
+
+    response = _upload(filename="evil.exe", content=b"X5O!P%@AP...")
+    assert response.status_code == 400
+    assert "Virus detected" in response.text
+    mock_manager.write_file.assert_not_called()
+
+
+# ---- No file extension ----
+
+
+def test_upload_file_without_extension(mocker: pytest_mock.MockFixture):
+    """Files without an extension should be accepted and stored as-is."""
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_or_create_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace_total_size",
+        return_value=0,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.scan_content_safe",
+        return_value=None,
+    )
+    mock_manager = mocker.MagicMock()
+    mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
+    mocker.patch(
+        "backend.api.features.workspace.routes.WorkspaceManager",
+        return_value=mock_manager,
+    )
+
+    response = _upload(
+        filename="Makefile",
+        content=b"all:\n\techo hello",
+        content_type="application/octet-stream",
+    )
+    assert response.status_code == 200
+    mock_manager.write_file.assert_called_once()
+    assert mock_manager.write_file.call_args[0][1] == "Makefile"
+
+
+# ---- Filename sanitization (SF5) ----
+
+
+def test_upload_strips_path_components(mocker: pytest_mock.MockFixture):
+    """Path-traversal filenames should be reduced to their basename."""
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_or_create_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace_total_size",
+        return_value=0,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.scan_content_safe",
+        return_value=None,
+    )
+    mock_manager = mocker.MagicMock()
+    mock_manager.write_file = mocker.AsyncMock(return_value=MOCK_FILE)
+    mocker.patch(
+        "backend.api.features.workspace.routes.WorkspaceManager",
+        return_value=mock_manager,
+    )
+
+    # Filename with traversal
+    _upload(filename="../../etc/passwd.txt")
+
+    # write_file should have been called with just the basename
+    mock_manager.write_file.assert_called_once()
+    call_args = mock_manager.write_file.call_args
+    assert call_args[0][1] == "passwd.txt"
+
+
+# ---- Download ----
+
+
+def test_download_file_not_found(mocker: pytest_mock.MockFixture):
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace_file",
+        return_value=None,
+    )
+
+    response = client.get("/files/some-file-id/download")
+    assert response.status_code == 404
+
+
+# ---- Delete ----
+
+
+def test_delete_file_success(mocker: pytest_mock.MockFixture):
+    """Deleting an existing file should return {"deleted": true}."""
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    mock_manager = mocker.MagicMock()
+    mock_manager.delete_file = mocker.AsyncMock(return_value=True)
+    mocker.patch(
+        "backend.api.features.workspace.routes.WorkspaceManager",
+        return_value=mock_manager,
+    )
+
+    response = client.delete("/files/file-aaa-bbb")
+    assert response.status_code == 200
+    assert response.json() == {"deleted": True}
+    mock_manager.delete_file.assert_called_once_with("file-aaa-bbb")
+
+
+def test_delete_file_not_found(mocker: pytest_mock.MockFixture):
+    """Deleting a non-existent file should return 404."""
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace",
+        return_value=MOCK_WORKSPACE,
+    )
+    mock_manager = mocker.MagicMock()
+    mock_manager.delete_file = mocker.AsyncMock(return_value=False)
+    mocker.patch(
+        "backend.api.features.workspace.routes.WorkspaceManager",
+        return_value=mock_manager,
+    )
+
+    response = client.delete("/files/nonexistent-id")
+    assert response.status_code == 404
+    assert "File not found" in response.text
+
+
+def test_delete_file_no_workspace(mocker: pytest_mock.MockFixture):
+    """Deleting when user has no workspace should return 404."""
+    mocker.patch(
+        "backend.api.features.workspace.routes.get_workspace",
+        return_value=None,
+    )
+
+    response = client.delete("/files/file-aaa-bbb")
+    assert response.status_code == 404
+    assert "Workspace not found" in response.text

autogpt_platform/backend/backend/api/rest_api.py

@@ -26,6 +26,7 @@ import backend.api.features.executions.review.routes
 import backend.api.features.library.db
 import backend.api.features.library.model
 import backend.api.features.library.routes
+import backend.api.features.mcp.routes as mcp_routes
 import backend.api.features.oauth
 import backend.api.features.otto.routes
 import backend.api.features.postmark.postmark
@@ -40,9 +41,9 @@ import backend.data.user
 import backend.integrations.webhooks.utils
 import backend.util.service
 import backend.util.settings
-from backend.api.features.chat.completion_consumer import (
-    start_completion_consumer,
-    stop_completion_consumer,
+from backend.api.features.library.exceptions import (
+    FolderAlreadyExistsError,
+    FolderValidationError,
 )
 from backend.blocks.llm import DEFAULT_LLM_MODEL
 from backend.data.model import Credentials
@@ -54,6 +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
@@ -122,21 +124,9 @@ async def lifespan_context(app: fastapi.FastAPI):
     await backend.data.graph.migrate_llm_models(DEFAULT_LLM_MODEL)
     await backend.integrations.webhooks.utils.migrate_legacy_triggered_graphs()
 
-    # Start chat completion consumer for Redis Streams notifications
-    try:
-        await start_completion_consumer()
-    except Exception as e:
-        logger.warning(f"Could not start chat completion consumer: {e}")
-
     with launch_darkly_context():
         yield
 
-    # Stop chat completion consumer
-    try:
-        await stop_completion_consumer()
-    except Exception as e:
-        logger.warning(f"Error stopping chat completion consumer: {e}")
-
     try:
         await shutdown_cloud_storage_handler()
     except Exception as e:
@@ -276,12 +266,17 @@ async def validation_error_handler(
 
 
 app.add_exception_handler(PrismaError, handle_internal_http_error(500))
+app.add_exception_handler(
+    FolderAlreadyExistsError, handle_internal_http_error(409, False)
+)
+app.add_exception_handler(FolderValidationError, handle_internal_http_error(400, False))
 app.add_exception_handler(NotFoundError, handle_internal_http_error(404, False))
 app.add_exception_handler(NotAuthorizedError, handle_internal_http_error(403, False))
 app.add_exception_handler(RequestValidationError, validation_error_handler)
 app.add_exception_handler(pydantic.ValidationError, validation_error_handler)
 app.add_exception_handler(MissingConfigError, handle_internal_http_error(503))
 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")
@@ -343,6 +338,11 @@ app.include_router(
     tags=["workspace"],
     prefix="/api/workspace",
 )
+app.include_router(
+    mcp_routes.router,
+    tags=["v2", "mcp"],
+    prefix="/api/mcp",
+)
 app.include_router(
     backend.api.features.oauth.router,
     tags=["oauth"],

autogpt_platform/backend/backend/app.py

@@ -24,7 +24,7 @@ def run_processes(*processes: "AppProcess", **kwargs):
         # Run the last process in the foreground.
         processes[-1].start(background=False, **kwargs)
     finally:
-        for process in processes:
+        for process in reversed(processes):
             try:
                 process.stop()
             except Exception as e:
@@ -38,7 +38,9 @@ def main(**kwargs):
 
     from backend.api.rest_api import AgentServer
     from backend.api.ws_api import WebsocketServer
-    from backend.executor import DatabaseManager, ExecutionManager, Scheduler
+    from backend.copilot.executor.manager import CoPilotExecutor
+    from backend.data.db_manager import DatabaseManager
+    from backend.executor import ExecutionManager, Scheduler
     from backend.notifications import NotificationManager
 
     run_processes(
@@ -48,6 +50,7 @@ def main(**kwargs):
         WebsocketServer(),
         AgentServer(),
         ExecutionManager(),
+        CoPilotExecutor(),
         **kwargs,
     )
 

autogpt_platform/backend/backend/blocks/__init__.py

@@ -3,22 +3,19 @@ import logging
 import os
 import re
 from pathlib import Path
-from typing import TYPE_CHECKING, TypeVar
+from typing import Sequence, Type, TypeVar
 
+from backend.blocks._base import AnyBlockSchema, BlockType
 from backend.util.cache import cached
 
 logger = logging.getLogger(__name__)
 
-
-if TYPE_CHECKING:
-    from backend.data.block import Block
-
 T = TypeVar("T")
 
 
 @cached(ttl_seconds=3600)
-def load_all_blocks() -> dict[str, type["Block"]]:
-    from backend.data.block import Block
+def load_all_blocks() -> dict[str, type["AnyBlockSchema"]]:
+    from backend.blocks._base import Block
     from backend.util.settings import Config
 
     # Check if example blocks should be loaded from settings
@@ -50,8 +47,8 @@ def load_all_blocks() -> dict[str, type["Block"]]:
         importlib.import_module(f".{module}", package=__name__)
 
     # Load all Block instances from the available modules
-    available_blocks: dict[str, type["Block"]] = {}
-    for block_cls in all_subclasses(Block):
+    available_blocks: dict[str, type["AnyBlockSchema"]] = {}
+    for block_cls in _all_subclasses(Block):
         class_name = block_cls.__name__
 
         if class_name.endswith("Base"):
@@ -64,7 +61,7 @@ def load_all_blocks() -> dict[str, type["Block"]]:
                 "please name the class with 'Base' at the end"
             )
 
-        block = block_cls.create()
+        block = block_cls()  # pyright: ignore[reportAbstractUsage]
 
         if not isinstance(block.id, str) or len(block.id) != 36:
             raise ValueError(
@@ -105,7 +102,7 @@ def load_all_blocks() -> dict[str, type["Block"]]:
         available_blocks[block.id] = block_cls
 
     # Filter out blocks with incomplete auth configs, e.g. missing OAuth server secrets
-    from backend.data.block import is_block_auth_configured
+    from ._utils import is_block_auth_configured
 
     filtered_blocks = {}
     for block_id, block_cls in available_blocks.items():
@@ -115,11 +112,48 @@ def load_all_blocks() -> dict[str, type["Block"]]:
     return filtered_blocks
 
 
-__all__ = ["load_all_blocks"]
-
-
-def all_subclasses(cls: type[T]) -> list[type[T]]:
+def _all_subclasses(cls: type[T]) -> list[type[T]]:
     subclasses = cls.__subclasses__()
     for subclass in subclasses:
-        subclasses += all_subclasses(subclass)
+        subclasses += _all_subclasses(subclass)
     return subclasses
+
+
+# ============== Block access helper functions ============== #
+
+
+def get_blocks() -> dict[str, Type["AnyBlockSchema"]]:
+    return load_all_blocks()
+
+
+# Note on the return type annotation: https://github.com/microsoft/pyright/issues/10281
+def get_block(block_id: str) -> "AnyBlockSchema | None":
+    cls = get_blocks().get(block_id)
+    return cls() if cls else None
+
+
+@cached(ttl_seconds=3600)
+def get_webhook_block_ids() -> Sequence[str]:
+    return [
+        id
+        for id, B in get_blocks().items()
+        if B().block_type in (BlockType.WEBHOOK, BlockType.WEBHOOK_MANUAL)
+    ]
+
+
+@cached(ttl_seconds=3600)
+def get_io_block_ids() -> Sequence[str]:
+    return [
+        id
+        for id, B in get_blocks().items()
+        if B().block_type in (BlockType.INPUT, BlockType.OUTPUT)
+    ]
+
+
+@cached(ttl_seconds=3600)
+def get_human_in_the_loop_block_ids() -> Sequence[str]:
+    return [
+        id
+        for id, B in get_blocks().items()
+        if B().block_type == BlockType.HUMAN_IN_THE_LOOP
+    ]

autogpt_platform/backend/backend/blocks/_base.py

@@ -0,0 +1,744 @@
+import inspect
+import logging
+from abc import ABC, abstractmethod
+from enum import Enum
+from typing import (
+    TYPE_CHECKING,
+    Any,
+    Callable,
+    ClassVar,
+    Generic,
+    Optional,
+    Type,
+    TypeAlias,
+    TypeVar,
+    cast,
+    get_origin,
+)
+
+import jsonref
+import jsonschema
+from pydantic import BaseModel
+
+from backend.data.block import BlockInput, BlockOutput, BlockOutputEntry
+from backend.data.model import (
+    Credentials,
+    CredentialsFieldInfo,
+    CredentialsMetaInput,
+    SchemaField,
+    is_credentials_field_name,
+)
+from backend.integrations.providers import ProviderName
+from backend.util import json
+from backend.util.exceptions import (
+    BlockError,
+    BlockExecutionError,
+    BlockInputError,
+    BlockOutputError,
+    BlockUnknownError,
+)
+from backend.util.settings import Config
+
+logger = logging.getLogger(__name__)
+
+if TYPE_CHECKING:
+    from backend.data.execution import ExecutionContext
+    from backend.data.model import ContributorDetails, NodeExecutionStats
+
+    from ..data.graph import Link
+
+app_config = Config()
+
+
+BlockTestOutput = BlockOutputEntry | tuple[str, Callable[[Any], bool]]
+
+
+class BlockType(Enum):
+    STANDARD = "Standard"
+    INPUT = "Input"
+    OUTPUT = "Output"
+    NOTE = "Note"
+    WEBHOOK = "Webhook"
+    WEBHOOK_MANUAL = "Webhook (manual)"
+    AGENT = "Agent"
+    AI = "AI"
+    AYRSHARE = "Ayrshare"
+    HUMAN_IN_THE_LOOP = "Human In The Loop"
+    MCP_TOOL = "MCP Tool"
+
+
+class BlockCategory(Enum):
+    AI = "Block that leverages AI to perform a task."
+    SOCIAL = "Block that interacts with social media platforms."
+    TEXT = "Block that processes text data."
+    SEARCH = "Block that searches or extracts information from the internet."
+    BASIC = "Block that performs basic operations."
+    INPUT = "Block that interacts with input of the graph."
+    OUTPUT = "Block that interacts with output of the graph."
+    LOGIC = "Programming logic to control the flow of your agent"
+    COMMUNICATION = "Block that interacts with communication platforms."
+    DEVELOPER_TOOLS = "Developer tools such as GitHub blocks."
+    DATA = "Block that interacts with structured data."
+    HARDWARE = "Block that interacts with hardware."
+    AGENT = "Block that interacts with other agents."
+    CRM = "Block that interacts with CRM services."
+    SAFETY = (
+        "Block that provides AI safety mechanisms such as detecting harmful content"
+    )
+    PRODUCTIVITY = "Block that helps with productivity"
+    ISSUE_TRACKING = "Block that helps with issue tracking"
+    MULTIMEDIA = "Block that interacts with multimedia content"
+    MARKETING = "Block that helps with marketing"
+
+    def dict(self) -> dict[str, str]:
+        return {"category": self.name, "description": self.value}
+
+
+class BlockCostType(str, Enum):
+    RUN = "run"  # cost X credits per run
+    BYTE = "byte"  # cost X credits per byte
+    SECOND = "second"  # cost X credits per second
+
+
+class BlockCost(BaseModel):
+    cost_amount: int
+    cost_filter: BlockInput
+    cost_type: BlockCostType
+
+    def __init__(
+        self,
+        cost_amount: int,
+        cost_type: BlockCostType = BlockCostType.RUN,
+        cost_filter: Optional[BlockInput] = None,
+        **data: Any,
+    ) -> None:
+        super().__init__(
+            cost_amount=cost_amount,
+            cost_filter=cost_filter or {},
+            cost_type=cost_type,
+            **data,
+        )
+
+
+class BlockInfo(BaseModel):
+    id: str
+    name: str
+    inputSchema: dict[str, Any]
+    outputSchema: dict[str, Any]
+    costs: list[BlockCost]
+    description: str
+    categories: list[dict[str, str]]
+    contributors: list[dict[str, Any]]
+    staticOutput: bool
+    uiType: str
+
+
+class BlockSchema(BaseModel):
+    cached_jsonschema: ClassVar[dict[str, Any]]
+
+    @classmethod
+    def jsonschema(cls) -> dict[str, Any]:
+        if cls.cached_jsonschema:
+            return cls.cached_jsonschema
+
+        model = jsonref.replace_refs(cls.model_json_schema(), merge_props=True)
+
+        def ref_to_dict(obj):
+            if isinstance(obj, dict):
+                # OpenAPI <3.1 does not support sibling fields that has a $ref key
+                # So sometimes, the schema has an "allOf"/"anyOf"/"oneOf" with 1 item.
+                keys = {"allOf", "anyOf", "oneOf"}
+                one_key = next((k for k in keys if k in obj and len(obj[k]) == 1), None)
+                if one_key:
+                    obj.update(obj[one_key][0])
+
+                return {
+                    key: ref_to_dict(value)
+                    for key, value in obj.items()
+                    if not key.startswith("$") and key != one_key
+                }
+            elif isinstance(obj, list):
+                return [ref_to_dict(item) for item in obj]
+
+            return obj
+
+        cls.cached_jsonschema = cast(dict[str, Any], ref_to_dict(model))
+
+        return cls.cached_jsonschema
+
+    @classmethod
+    def validate_data(cls, data: BlockInput) -> str | None:
+        return json.validate_with_jsonschema(
+            schema=cls.jsonschema(),
+            data={k: v for k, v in data.items() if v is not None},
+        )
+
+    @classmethod
+    def get_mismatch_error(cls, data: BlockInput) -> str | None:
+        return cls.validate_data(data)
+
+    @classmethod
+    def get_field_schema(cls, field_name: str) -> dict[str, Any]:
+        model_schema = cls.jsonschema().get("properties", {})
+        if not model_schema:
+            raise ValueError(f"Invalid model schema {cls}")
+
+        property_schema = model_schema.get(field_name)
+        if not property_schema:
+            raise ValueError(f"Invalid property name {field_name}")
+
+        return property_schema
+
+    @classmethod
+    def validate_field(cls, field_name: str, data: BlockInput) -> str | None:
+        """
+        Validate the data against a specific property (one of the input/output name).
+        Returns the validation error message if the data does not match the schema.
+        """
+        try:
+            property_schema = cls.get_field_schema(field_name)
+            jsonschema.validate(json.to_dict(data), property_schema)
+            return None
+        except jsonschema.ValidationError as e:
+            return str(e)
+
+    @classmethod
+    def get_fields(cls) -> set[str]:
+        return set(cls.model_fields.keys())
+
+    @classmethod
+    def get_required_fields(cls) -> set[str]:
+        return {
+            field
+            for field, field_info in cls.model_fields.items()
+            if field_info.is_required()
+        }
+
+    @classmethod
+    def __pydantic_init_subclass__(cls, **kwargs):
+        """Validates the schema definition. Rules:
+        - Fields with annotation `CredentialsMetaInput` MUST be
+          named `credentials` or `*_credentials`
+        - Fields named `credentials` or `*_credentials` MUST be
+          of type `CredentialsMetaInput`
+        """
+        super().__pydantic_init_subclass__(**kwargs)
+
+        # Reset cached JSON schema to prevent inheriting it from parent class
+        cls.cached_jsonschema = {}
+
+        credentials_fields = cls.get_credentials_fields()
+
+        for field_name in cls.get_fields():
+            if is_credentials_field_name(field_name):
+                if field_name not in credentials_fields:
+                    raise TypeError(
+                        f"Credentials field '{field_name}' on {cls.__qualname__} "
+                        f"is not of type {CredentialsMetaInput.__name__}"
+                    )
+
+                CredentialsMetaInput.validate_credentials_field_schema(
+                    cls.get_field_schema(field_name), field_name
+                )
+
+            elif field_name in credentials_fields:
+                raise KeyError(
+                    f"Credentials field '{field_name}' on {cls.__qualname__} "
+                    "has invalid name: must be 'credentials' or *_credentials"
+                )
+
+    @classmethod
+    def get_credentials_fields(cls) -> dict[str, type[CredentialsMetaInput]]:
+        return {
+            field_name: info.annotation
+            for field_name, info in cls.model_fields.items()
+            if (
+                inspect.isclass(info.annotation)
+                and issubclass(
+                    get_origin(info.annotation) or info.annotation,
+                    CredentialsMetaInput,
+                )
+            )
+        }
+
+    @classmethod
+    def get_auto_credentials_fields(cls) -> dict[str, dict[str, Any]]:
+        """
+        Get fields that have auto_credentials metadata (e.g., GoogleDriveFileInput).
+
+        Returns a dict mapping kwarg_name -> {field_name, auto_credentials_config}
+
+        Raises:
+            ValueError: If multiple fields have the same kwarg_name, as this would
+                cause silent overwriting and only the last field would be processed.
+        """
+        result: dict[str, dict[str, Any]] = {}
+        schema = cls.jsonschema()
+        properties = schema.get("properties", {})
+
+        for field_name, field_schema in properties.items():
+            auto_creds = field_schema.get("auto_credentials")
+            if auto_creds:
+                kwarg_name = auto_creds.get("kwarg_name", "credentials")
+                if kwarg_name in result:
+                    raise ValueError(
+                        f"Duplicate auto_credentials kwarg_name '{kwarg_name}' "
+                        f"in fields '{result[kwarg_name]['field_name']}' and "
+                        f"'{field_name}' on {cls.__qualname__}"
+                    )
+                result[kwarg_name] = {
+                    "field_name": field_name,
+                    "config": auto_creds,
+                }
+        return result
+
+    @classmethod
+    def get_credentials_fields_info(cls) -> dict[str, CredentialsFieldInfo]:
+        result = {}
+
+        # Regular credentials fields
+        for field_name in cls.get_credentials_fields().keys():
+            result[field_name] = CredentialsFieldInfo.model_validate(
+                cls.get_field_schema(field_name), by_alias=True
+            )
+
+        # Auto-generated credentials fields (from GoogleDriveFileInput etc.)
+        for kwarg_name, info in cls.get_auto_credentials_fields().items():
+            config = info["config"]
+            # Build a schema-like dict that CredentialsFieldInfo can parse
+            auto_schema = {
+                "credentials_provider": [config.get("provider", "google")],
+                "credentials_types": [config.get("type", "oauth2")],
+                "credentials_scopes": config.get("scopes"),
+            }
+            result[kwarg_name] = CredentialsFieldInfo.model_validate(
+                auto_schema, by_alias=True
+            )
+
+        return result
+
+    @classmethod
+    def get_input_defaults(cls, data: BlockInput) -> BlockInput:
+        return data  # Return as is, by default.
+
+    @classmethod
+    def get_missing_links(cls, data: BlockInput, links: list["Link"]) -> set[str]:
+        input_fields_from_nodes = {link.sink_name for link in links}
+        return input_fields_from_nodes - set(data)
+
+    @classmethod
+    def get_missing_input(cls, data: BlockInput) -> set[str]:
+        return cls.get_required_fields() - set(data)
+
+
+class BlockSchemaInput(BlockSchema):
+    """
+    Base schema class for block inputs.
+    All block input schemas should extend this class for consistency.
+    """
+
+    pass
+
+
+class BlockSchemaOutput(BlockSchema):
+    """
+    Base schema class for block outputs that includes a standard error field.
+    All block output schemas should extend this class to ensure consistent error handling.
+    """
+
+    error: str = SchemaField(
+        description="Error message if the operation failed", default=""
+    )
+
+
+BlockSchemaInputType = TypeVar("BlockSchemaInputType", bound=BlockSchemaInput)
+BlockSchemaOutputType = TypeVar("BlockSchemaOutputType", bound=BlockSchemaOutput)
+
+
+class EmptyInputSchema(BlockSchemaInput):
+    pass
+
+
+class EmptyOutputSchema(BlockSchemaOutput):
+    pass
+
+
+# For backward compatibility - will be deprecated
+EmptySchema = EmptyOutputSchema
+
+
+# --8<-- [start:BlockWebhookConfig]
+class BlockManualWebhookConfig(BaseModel):
+    """
+    Configuration model for webhook-triggered blocks on which
+    the user has to manually set up the webhook at the provider.
+    """
+
+    provider: ProviderName
+    """The service provider that the webhook connects to"""
+
+    webhook_type: str
+    """
+    Identifier for the webhook type. E.g. GitHub has repo and organization level hooks.
+
+    Only for use in the corresponding `WebhooksManager`.
+    """
+
+    event_filter_input: str = ""
+    """
+    Name of the block's event filter input.
+    Leave empty if the corresponding webhook doesn't have distinct event/payload types.
+    """
+
+    event_format: str = "{event}"
+    """
+    Template string for the event(s) that a block instance subscribes to.
+    Applied individually to each event selected in the event filter input.
+
+    Example: `"pull_request.{event}"` -> `"pull_request.opened"`
+    """
+
+
+class BlockWebhookConfig(BlockManualWebhookConfig):
+    """
+    Configuration model for webhook-triggered blocks for which
+    the webhook can be automatically set up through the provider's API.
+    """
+
+    resource_format: str
+    """
+    Template string for the resource that a block instance subscribes to.
+    Fields will be filled from the block's inputs (except `payload`).
+
+    Example: `f"{repo}/pull_requests"` (note: not how it's actually implemented)
+
+    Only for use in the corresponding `WebhooksManager`.
+    """
+    # --8<-- [end:BlockWebhookConfig]
+
+
+class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
+    _optimized_description: ClassVar[str | None] = None
+
+    def __init__(
+        self,
+        id: str = "",
+        description: str = "",
+        contributors: list["ContributorDetails"] = [],
+        categories: set[BlockCategory] | None = None,
+        input_schema: Type[BlockSchemaInputType] = EmptyInputSchema,
+        output_schema: Type[BlockSchemaOutputType] = EmptyOutputSchema,
+        test_input: BlockInput | list[BlockInput] | None = None,
+        test_output: BlockTestOutput | list[BlockTestOutput] | None = None,
+        test_mock: dict[str, Any] | None = None,
+        test_credentials: Optional[Credentials | dict[str, Credentials]] = None,
+        disabled: bool = False,
+        static_output: bool = False,
+        block_type: BlockType = BlockType.STANDARD,
+        webhook_config: Optional[BlockWebhookConfig | BlockManualWebhookConfig] = None,
+        is_sensitive_action: bool = False,
+    ):
+        """
+        Initialize the block with the given schema.
+
+        Args:
+            id: The unique identifier for the block, this value will be persisted in the
+                DB. So it should be a unique and constant across the application run.
+                Use the UUID format for the ID.
+            description: The description of the block, explaining what the block does.
+            contributors: The list of contributors who contributed to the block.
+            input_schema: The schema, defined as a Pydantic model, for the input data.
+            output_schema: The schema, defined as a Pydantic model, for the output data.
+            test_input: The list or single sample input data for the block, for testing.
+            test_output: The list or single expected output if the test_input is run.
+            test_mock: function names on the block implementation to mock on test run.
+            disabled: If the block is disabled, it will not be available for execution.
+            static_output: Whether the output links of the block are static by default.
+        """
+        from backend.data.model import NodeExecutionStats
+
+        self.id = id
+        self.input_schema = input_schema
+        self.output_schema = output_schema
+        self.test_input = test_input
+        self.test_output = test_output
+        self.test_mock = test_mock
+        self.test_credentials = test_credentials
+        self.description = description
+        self.categories = categories or set()
+        self.contributors = contributors or set()
+        self.disabled = disabled
+        self.static_output = static_output
+        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:
+            if isinstance(self.webhook_config, BlockWebhookConfig):
+                # Enforce presence of credentials field on auto-setup webhook blocks
+                if not (cred_fields := self.input_schema.get_credentials_fields()):
+                    raise TypeError(
+                        "credentials field is required on auto-setup webhook blocks"
+                    )
+                # Disallow multiple credentials inputs on webhook blocks
+                elif len(cred_fields) > 1:
+                    raise ValueError(
+                        "Multiple credentials inputs not supported on webhook blocks"
+                    )
+
+                self.block_type = BlockType.WEBHOOK
+            else:
+                self.block_type = BlockType.WEBHOOK_MANUAL
+
+            # Enforce shape of webhook event filter, if present
+            if self.webhook_config.event_filter_input:
+                event_filter_field = self.input_schema.model_fields[
+                    self.webhook_config.event_filter_input
+                ]
+                if not (
+                    isinstance(event_filter_field.annotation, type)
+                    and issubclass(event_filter_field.annotation, BaseModel)
+                    and all(
+                        field.annotation is bool
+                        for field in event_filter_field.annotation.model_fields.values()
+                    )
+                ):
+                    raise NotImplementedError(
+                        f"{self.name} has an invalid webhook event selector: "
+                        "field must be a BaseModel and all its fields must be boolean"
+                    )
+
+            # Enforce presence of 'payload' input
+            if "payload" not in self.input_schema.model_fields:
+                raise TypeError(
+                    f"{self.name} is webhook-triggered but has no 'payload' input"
+                )
+
+            # Disable webhook-triggered block if webhook functionality not available
+            if not app_config.platform_base_url:
+                self.disabled = True
+
+    @abstractmethod
+    async def run(self, input_data: BlockSchemaInputType, **kwargs) -> BlockOutput:
+        """
+        Run the block with the given input data.
+        Args:
+            input_data: The input data with the structure of input_schema.
+
+        Kwargs: Currently 14/02/2025 these include
+            graph_id: The ID of the graph.
+            node_id: The ID of the node.
+            graph_exec_id: The ID of the graph execution.
+            node_exec_id: The ID of the node execution.
+            user_id: The ID of the user.
+
+        Returns:
+            A Generator that yields (output_name, output_data).
+            output_name: One of the output name defined in Block's output_schema.
+            output_data: The data for the output_name, matching the defined schema.
+        """
+        # --- satisfy the type checker, never executed -------------
+        if False:  # noqa: SIM115
+            yield "name", "value"  # pyright: ignore[reportMissingYield]
+        raise NotImplementedError(f"{self.name} does not implement the run method.")
+
+    async def run_once(
+        self, input_data: BlockSchemaInputType, output: str, **kwargs
+    ) -> Any:
+        async for item in self.run(input_data, **kwargs):
+            name, data = item
+            if name == output:
+                return data
+        raise ValueError(f"{self.name} did not produce any output for {output}")
+
+    def merge_stats(self, stats: "NodeExecutionStats") -> "NodeExecutionStats":
+        self.execution_stats += stats
+        return self.execution_stats
+
+    @property
+    def name(self):
+        return self.__class__.__name__
+
+    def to_dict(self):
+        return {
+            "id": self.id,
+            "name": self.name,
+            "inputSchema": self.input_schema.jsonschema(),
+            "outputSchema": self.output_schema.jsonschema(),
+            "description": self.description,
+            "categories": [category.dict() for category in self.categories],
+            "contributors": [
+                contributor.model_dump() for contributor in self.contributors
+            ],
+            "staticOutput": self.static_output,
+            "uiType": self.block_type.value,
+        }
+
+    def get_info(self) -> BlockInfo:
+        from backend.data.credit import get_block_cost
+
+        return BlockInfo(
+            id=self.id,
+            name=self.name,
+            inputSchema=self.input_schema.jsonschema(),
+            outputSchema=self.output_schema.jsonschema(),
+            costs=get_block_cost(self),
+            description=self.description,
+            categories=[category.dict() for category in self.categories],
+            contributors=[
+                contributor.model_dump() for contributor in self.contributors
+            ],
+            staticOutput=self.static_output,
+            uiType=self.block_type.value,
+        )
+
+    async def execute(self, input_data: BlockInput, **kwargs) -> BlockOutput:
+        try:
+            async for output_name, output_data in self._execute(input_data, **kwargs):
+                yield output_name, output_data
+        except Exception as ex:
+            if isinstance(ex, BlockError):
+                raise ex
+            else:
+                raise (
+                    BlockExecutionError
+                    if isinstance(ex, ValueError)
+                    else BlockUnknownError
+                )(
+                    message=str(ex),
+                    block_name=self.name,
+                    block_id=self.id,
+                ) from ex
+
+    async def is_block_exec_need_review(
+        self,
+        input_data: BlockInput,
+        *,
+        user_id: str,
+        node_id: str,
+        node_exec_id: str,
+        graph_exec_id: str,
+        graph_id: str,
+        graph_version: int,
+        execution_context: "ExecutionContext",
+        **kwargs,
+    ) -> tuple[bool, BlockInput]:
+        """
+        Check if this block execution needs human review and handle the review process.
+
+        Returns:
+            Tuple of (should_pause, input_data_to_use)
+            - should_pause: True if execution should be paused for review
+            - input_data_to_use: The input data to use (may be modified by reviewer)
+        """
+        if not (
+            self.is_sensitive_action and execution_context.sensitive_action_safe_mode
+        ):
+            return False, input_data
+
+        from backend.blocks.helpers.review import HITLReviewHelper
+
+        # Handle the review request and get decision
+        decision = await HITLReviewHelper.handle_review_decision(
+            input_data=input_data,
+            user_id=user_id,
+            node_id=node_id,
+            node_exec_id=node_exec_id,
+            graph_exec_id=graph_exec_id,
+            graph_id=graph_id,
+            graph_version=graph_version,
+            block_name=self.name,
+            editable=True,
+        )
+
+        if decision is None:
+            # We're awaiting review - pause execution
+            return True, input_data
+
+        if not decision.should_proceed:
+            # Review was rejected, raise an error to stop execution
+            raise BlockExecutionError(
+                message=f"Block execution rejected by reviewer: {decision.message}",
+                block_name=self.name,
+                block_id=self.id,
+            )
+
+        # Review was approved - use the potentially modified data
+        # ReviewResult.data must be a dict for block inputs
+        reviewed_data = decision.review_result.data
+        if not isinstance(reviewed_data, dict):
+            raise BlockExecutionError(
+                message=f"Review data must be a dict for block input, got {type(reviewed_data).__name__}",
+                block_name=self.name,
+                block_id=self.id,
+            )
+        return False, reviewed_data
+
+    async def _execute(self, input_data: BlockInput, **kwargs) -> BlockOutput:
+        # Check for review requirement only if running within a graph execution context
+        # Direct block execution (e.g., from chat) skips the review process
+        has_graph_context = all(
+            key in kwargs
+            for key in (
+                "node_exec_id",
+                "graph_exec_id",
+                "graph_id",
+                "execution_context",
+            )
+        )
+        if has_graph_context:
+            should_pause, input_data = await self.is_block_exec_need_review(
+                input_data, **kwargs
+            )
+            if should_pause:
+                return
+
+        # Validate the input data (original or reviewer-modified) once
+        if error := self.input_schema.validate_data(input_data):
+            raise BlockInputError(
+                message=f"Unable to execute block with invalid input data: {error}",
+                block_name=self.name,
+                block_id=self.id,
+            )
+
+        # Use the validated input data
+        async for output_name, output_data in self.run(
+            self.input_schema(**{k: v for k, v in input_data.items() if v is not None}),
+            **kwargs,
+        ):
+            if output_name == "error":
+                raise BlockExecutionError(
+                    message=output_data, block_name=self.name, block_id=self.id
+                )
+            if self.block_type == BlockType.STANDARD and (
+                error := self.output_schema.validate_field(output_name, output_data)
+            ):
+                raise BlockOutputError(
+                    message=f"Block produced an invalid output data: {error}",
+                    block_name=self.name,
+                    block_id=self.id,
+                )
+            yield output_name, output_data
+
+    def is_triggered_by_event_type(
+        self, trigger_config: dict[str, Any], event_type: str
+    ) -> bool:
+        if not self.webhook_config:
+            raise TypeError("This method can't be used on non-trigger blocks")
+        if not self.webhook_config.event_filter_input:
+            return True
+        event_filter = trigger_config.get(self.webhook_config.event_filter_input)
+        if not event_filter:
+            raise ValueError("Event filter is not configured on trigger")
+        return event_type in [
+            self.webhook_config.event_format.format(event=k)
+            for k in event_filter
+            if event_filter[k] is True
+        ]
+
+
+# Type alias for any block with standard input/output schemas
+AnyBlockSchema: TypeAlias = Block[BlockSchemaInput, BlockSchemaOutput]