Compare commits

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4 Commits

Author SHA1 Message Date
Swifty
894e3600fb add other specs 2025-08-01 14:21:57 +02:00
Swifty
9de4b09f20 mv to sub dir 2025-08-01 13:19:42 +02:00
Swifty
62e41d409a websocket server running well now 2025-08-01 13:17:45 +02:00
Swifty
9f03e3af47 added websocket service 2025-08-01 11:19:29 +02:00
1076 changed files with 41628 additions and 53498 deletions

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@@ -15,7 +15,6 @@
!autogpt_platform/backend/pyproject.toml
!autogpt_platform/backend/poetry.lock
!autogpt_platform/backend/README.md
!autogpt_platform/backend/.env
# Platform - Market
!autogpt_platform/market/market/
@@ -28,7 +27,6 @@
# 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
@@ -36,7 +34,6 @@
## config
!autogpt_platform/frontend/*.config.*
!autogpt_platform/frontend/.env.*
!autogpt_platform/frontend/.env
# Classic - AutoGPT
!classic/original_autogpt/autogpt/

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@@ -24,8 +24,7 @@
</details>
#### For configuration changes:
- [ ] `.env.default` is updated or already compatible with my changes
- [ ] `.env.example` is updated or already compatible with my changes
- [ ] `docker-compose.yml` is updated or already compatible with my changes
- [ ] I have included a list of my configuration changes in the PR description (under **Changes**)

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@@ -1,244 +0,0 @@
# GitHub Copilot Instructions for AutoGPT
This file provides comprehensive onboarding information for GitHub Copilot coding agent to work efficiently with the AutoGPT repository.
## Repository Overview
**AutoGPT** is a powerful platform for creating, deploying, and managing continuous AI agents that automate complex workflows. This is a large monorepo (~150MB) containing multiple components:
- **AutoGPT Platform** (`autogpt_platform/`) - Main focus: Modern AI agent platform (Polyform Shield License)
- **Classic AutoGPT** (`classic/`) - Legacy agent system (MIT License)
- **Documentation** (`docs/`) - MkDocs-based documentation site
- **Infrastructure** - Docker configurations, CI/CD, and development tools
**Primary Languages & Frameworks:**
- **Backend**: Python 3.10-3.13, FastAPI, Prisma ORM, PostgreSQL, RabbitMQ
- **Frontend**: TypeScript, Next.js 15, React, Tailwind CSS, Radix UI
- **Development**: Docker, Poetry, pnpm, Playwright, Storybook
## Build and Validation Instructions
### Essential Setup Commands
**Always run these commands in the correct directory and in this order:**
1. **Initial Setup** (required once):
```bash
# Clone and enter repository
git clone <repo> && cd AutoGPT
# Start all services (database, redis, rabbitmq, clamav)
cd autogpt_platform && docker compose --profile local up deps --build --detach
```
2. **Backend Setup** (always run before backend development):
```bash
cd autogpt_platform/backend
poetry install # Install dependencies
poetry run prisma migrate dev # Run database migrations
poetry run prisma generate # Generate Prisma client
```
3. **Frontend Setup** (always run before frontend development):
```bash
cd autogpt_platform/frontend
pnpm install # Install dependencies
```
### Runtime Requirements
**Critical:** Always ensure Docker services are running before starting development:
```bash
cd autogpt_platform && docker compose --profile local up deps --build --detach
```
**Python Version:** Use Python 3.11 (required; managed by Poetry via pyproject.toml)
**Node.js Version:** Use Node.js 21+ with pnpm package manager
### Development Commands
**Backend Development:**
```bash
cd autogpt_platform/backend
poetry run serve # Start development server (port 8000)
poetry run test # Run all tests (requires ~5 minutes)
poetry run pytest path/to/test.py # Run specific test
poetry run format # Format code (Black + isort) - always run first
poetry run lint # Lint code (ruff) - run after format
```
**Frontend Development:**
```bash
cd autogpt_platform/frontend
pnpm dev # Start development server (port 3000) - use for active development
pnpm build # Build for production (only needed for E2E tests or deployment)
pnpm test # Run Playwright E2E tests (requires build first)
pnpm test-ui # Run tests with UI
pnpm format # Format and lint code
pnpm storybook # Start component development server
```
### Testing Strategy
**Backend Tests:**
- **Block Tests**: `poetry run pytest backend/blocks/test/test_block.py -xvs` (validates all blocks)
- **Specific Block**: `poetry run pytest 'backend/blocks/test/test_block.py::test_available_blocks[BlockName]' -xvs`
- **Snapshot Tests**: Use `--snapshot-update` when output changes, always review with `git diff`
**Frontend Tests:**
- **E2E Tests**: Always run `pnpm dev` before `pnpm test` (Playwright requires running instance)
- **Component Tests**: Use Storybook for isolated component development
### Critical Validation Steps
**Before committing changes:**
1. Run `poetry run format` (backend) and `pnpm format` (frontend)
2. Ensure all tests pass in modified areas
3. Verify Docker services are still running
4. Check that database migrations apply cleanly
**Common Issues & Workarounds:**
- **Prisma issues**: Run `poetry run prisma generate` after schema changes
- **Permission errors**: Ensure Docker has proper permissions
- **Port conflicts**: Check the `docker-compose.yml` file for the current list of exposed ports. You can list all mapped ports with:
- **Test timeouts**: Backend tests can take 5+ minutes, use `-x` flag to stop on first failure
## Project Layout & Architecture
### Core Architecture
**AutoGPT Platform** (`autogpt_platform/`):
- `backend/` - FastAPI server with async support
- `backend/backend/` - Core API logic
- `backend/blocks/` - Agent execution blocks
- `backend/data/` - Database models and schemas
- `schema.prisma` - Database schema definition
- `frontend/` - Next.js application
- `src/app/` - App Router pages and layouts
- `src/components/` - Reusable React components
- `src/lib/` - Utilities and configurations
- `autogpt_libs/` - Shared Python utilities
- `docker-compose.yml` - Development stack orchestration
**Key Configuration Files:**
- `pyproject.toml` - Python dependencies and tooling
- `package.json` - Node.js dependencies and scripts
- `schema.prisma` - Database schema and migrations
- `next.config.mjs` - Next.js configuration
- `tailwind.config.ts` - Styling configuration
### Security & Middleware
**Cache Protection**: Backend includes middleware preventing sensitive data caching in browsers/proxies
**Authentication**: JWT-based with Supabase integration
**User ID Validation**: All data access requires user ID checks - verify this for any `data/*.py` changes
### Development Workflow
**GitHub Actions**: Multiple CI/CD workflows in `.github/workflows/`
- `platform-backend-ci.yml` - Backend testing and validation
- `platform-frontend-ci.yml` - Frontend testing and validation
- `platform-fullstack-ci.yml` - End-to-end integration tests
**Pre-commit Hooks**: Run linting and formatting checks
**Conventional Commits**: Use format `type(scope): description` (e.g., `feat(backend): add API`)
### Key Source Files
**Backend Entry Points:**
- `backend/backend/server/server.py` - FastAPI application setup
- `backend/backend/data/` - Database models and user management
- `backend/blocks/` - Agent execution blocks and logic
**Frontend Entry Points:**
- `frontend/src/app/layout.tsx` - Root application layout
- `frontend/src/app/page.tsx` - Home page
- `frontend/src/lib/supabase/` - Authentication and database client
**Protected Routes**: Update `frontend/lib/supabase/middleware.ts` when adding protected routes
### Agent Block System
Agents are built using a visual block-based system where each block performs a single action. Blocks are defined in `backend/blocks/` and must include:
- Block definition with input/output schemas
- Execution logic with proper error handling
- Tests validating functionality
### Database & ORM
**Prisma ORM** with PostgreSQL backend including pgvector for embeddings:
- Schema in `schema.prisma`
- Migrations in `backend/migrations/`
- Always run `prisma migrate dev` and `prisma generate` after schema changes
## Environment Configuration
### Configuration Files Priority Order
1. **Backend**: `/backend/.env.default` → `/backend/.env` (user overrides)
2. **Frontend**: `/frontend/.env.default` → `/frontend/.env` (user overrides)
3. **Platform**: `/.env.default` (Supabase/shared) → `/.env` (user overrides)
4. Docker Compose `environment:` sections override file-based config
5. Shell environment variables have highest precedence
### Docker Environment Setup
- All services use hardcoded defaults (no `${VARIABLE}` substitutions)
- The `env_file` directive loads variables INTO containers at runtime
- Backend/Frontend services use YAML anchors for consistent configuration
- Copy `.env.default` files to `.env` for local development customization
## Advanced Development Patterns
### Adding New Blocks
1. Create file in `/backend/backend/blocks/`
2. Inherit from `Block` base class with input/output schemas
3. Implement `run` method with proper error handling
4. Generate block UUID using `uuid.uuid4()`
5. Register in block registry
6. Write tests alongside block implementation
7. Consider how inputs/outputs connect with other blocks in graph editor
### API Development
1. Update routes in `/backend/backend/server/routers/`
2. Add/update Pydantic models in same directory
3. Write tests alongside route files
4. For `data/*.py` changes, validate user ID checks
5. Run `poetry run test` to verify changes
### Frontend Development
1. Components in `/frontend/src/components/`
2. Use existing UI components from `/frontend/src/components/ui/`
3. Add Storybook stories for component development
4. Test user-facing features with Playwright E2E tests
5. Update protected routes in middleware when needed
### Security Guidelines
**Cache Protection Middleware** (`/backend/backend/server/middleware/security.py`):
- Default: Disables caching for ALL endpoints with `Cache-Control: no-store, no-cache, must-revalidate, private`
- Uses allow list approach for cacheable paths (static assets, health checks, public pages)
- Prevents sensitive data caching in browsers/proxies
- Add new cacheable endpoints to `CACHEABLE_PATHS`
### CI/CD Alignment
The repository has comprehensive CI workflows that test:
- **Backend**: Python 3.11-3.13, services (Redis/RabbitMQ/ClamAV), Prisma migrations, Poetry lock validation
- **Frontend**: Node.js 21, pnpm, Playwright with Docker Compose stack, API schema validation
- **Integration**: Full-stack type checking and E2E testing
Match these patterns when developing locally - the copilot setup environment mirrors these CI configurations.
## Collaboration with Other AI Assistants
This repository is actively developed with assistance from Claude (via CLAUDE.md files). When working on this codebase:
- Check for existing CLAUDE.md files that provide additional context
- Follow established patterns and conventions already in the codebase
- Maintain consistency with existing code style and architecture
- Consider that changes may be reviewed and extended by both human developers and AI assistants
## Trust These Instructions
These instructions are comprehensive and tested. Only perform additional searches if:
1. Information here is incomplete for your specific task
2. You encounter errors not covered by the workarounds
3. You need to understand implementation details not covered above
For detailed platform development patterns, refer to `autogpt_platform/CLAUDE.md` and `AGENTS.md` in the repository root.

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@@ -1,97 +0,0 @@
name: Auto Fix CI Failures
on:
workflow_run:
workflows: ["CI"]
types:
- completed
permissions:
contents: write
pull-requests: write
actions: read
issues: write
id-token: write # Required for OIDC token exchange
jobs:
auto-fix:
if: |
github.event.workflow_run.conclusion == 'failure' &&
github.event.workflow_run.pull_requests[0] &&
!startsWith(github.event.workflow_run.head_branch, 'claude-auto-fix-ci-')
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
ref: ${{ github.event.workflow_run.head_branch }}
fetch-depth: 0
token: ${{ secrets.GITHUB_TOKEN }}
- name: Setup git identity
run: |
git config --global user.email "claude[bot]@users.noreply.github.com"
git config --global user.name "claude[bot]"
- name: Create fix branch
id: branch
run: |
BRANCH_NAME="claude-auto-fix-ci-${{ github.event.workflow_run.head_branch }}-${{ github.run_id }}"
git checkout -b "$BRANCH_NAME"
echo "branch_name=$BRANCH_NAME" >> $GITHUB_OUTPUT
- name: Get CI failure details
id: failure_details
uses: actions/github-script@v7
with:
script: |
const run = await github.rest.actions.getWorkflowRun({
owner: context.repo.owner,
repo: context.repo.repo,
run_id: ${{ github.event.workflow_run.id }}
});
const jobs = await github.rest.actions.listJobsForWorkflowRun({
owner: context.repo.owner,
repo: context.repo.repo,
run_id: ${{ github.event.workflow_run.id }}
});
const failedJobs = jobs.data.jobs.filter(job => job.conclusion === 'failure');
let errorLogs = [];
for (const job of failedJobs) {
const logs = await github.rest.actions.downloadJobLogsForWorkflowRun({
owner: context.repo.owner,
repo: context.repo.repo,
job_id: job.id
});
errorLogs.push({
jobName: job.name,
logs: logs.data
});
}
return {
runUrl: run.data.html_url,
failedJobs: failedJobs.map(j => j.name),
errorLogs: errorLogs
};
- name: Fix CI failures with Claude
id: claude
uses: anthropics/claude-code-action@v1
with:
prompt: |
/fix-ci
Failed CI Run: ${{ fromJSON(steps.failure_details.outputs.result).runUrl }}
Failed Jobs: ${{ join(fromJSON(steps.failure_details.outputs.result).failedJobs, ', ') }}
PR Number: ${{ github.event.workflow_run.pull_requests[0].number }}
Branch Name: ${{ steps.branch.outputs.branch_name }}
Base Branch: ${{ github.event.workflow_run.head_branch }}
Repository: ${{ github.repository }}
Error logs:
${{ toJSON(fromJSON(steps.failure_details.outputs.result).errorLogs) }}
anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
claude_args: "--allowedTools 'Edit,MultiEdit,Write,Read,Glob,Grep,LS,Bash(git:*),Bash(bun:*),Bash(npm:*),Bash(npx:*),Bash(gh:*)'"

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@@ -1,379 +0,0 @@
# Claude Dependabot PR Review Workflow
#
# This workflow automatically runs Claude analysis on Dependabot PRs to:
# - Identify dependency changes and their versions
# - Look up changelogs for updated packages
# - Assess breaking changes and security impacts
# - Provide actionable recommendations for the development team
#
# Triggered on: Dependabot PRs (opened, synchronize)
# Requirements: ANTHROPIC_API_KEY secret must be configured
name: Claude Dependabot PR Review
on:
pull_request:
types: [opened, synchronize]
jobs:
dependabot-review:
# Only run on Dependabot PRs
if: github.actor == 'dependabot[bot]'
runs-on: ubuntu-latest
timeout-minutes: 30
permissions:
contents: write
pull-requests: read
issues: read
id-token: write
actions: read # Required for CI access
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 1
# Backend Python/Poetry setup (mirrors platform-backend-ci.yml)
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11" # Use standard version matching CI
- name: Set up Python dependency cache
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
- name: Install Poetry
run: |
# Extract Poetry version from backend/poetry.lock (matches CI)
cd autogpt_platform/backend
HEAD_POETRY_VERSION=$(python3 ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
echo "Found Poetry version ${HEAD_POETRY_VERSION} in backend/poetry.lock"
# Install Poetry
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
# Add Poetry to PATH
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Check poetry.lock
working-directory: autogpt_platform/backend
run: |
poetry lock
if ! git diff --quiet --ignore-matching-lines="^# " poetry.lock; then
echo "Warning: poetry.lock not up to date, but continuing for setup"
git checkout poetry.lock # Reset for clean setup
fi
- name: Install Python dependencies
working-directory: autogpt_platform/backend
run: poetry install
- name: Generate Prisma Client
working-directory: autogpt_platform/backend
run: poetry run prisma generate
# Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
- name: Set up Node.js
uses: actions/setup-node@v4
with:
node-version: "21"
- name: Enable corepack
run: corepack enable
- name: Set pnpm store directory
run: |
pnpm config set store-dir ~/.pnpm-store
echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
- name: Cache frontend dependencies
uses: actions/cache@v4
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') }}
${{ runner.os }}-pnpm-
- name: Install JavaScript dependencies
working-directory: autogpt_platform/frontend
run: pnpm install --frozen-lockfile
# Install Playwright browsers for frontend testing
# NOTE: Disabled to save ~1 minute of setup time. Re-enable if Copilot needs browser automation (e.g., for MCP)
# - name: Install Playwright browsers
# working-directory: autogpt_platform/frontend
# run: pnpm playwright install --with-deps chromium
# Docker setup for development environment
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Copy default environment files
working-directory: autogpt_platform
run: |
# Copy default environment files for development
cp .env.default .env
cp backend/.env.default backend/.env
cp frontend/.env.default frontend/.env
# Phase 1: Cache and load Docker images for faster setup
- name: Set up Docker image cache
id: docker-cache
uses: actions/cache@v4
with:
path: ~/docker-cache
# Use a versioned key for cache invalidation when image list changes
key: docker-images-v2-${{ runner.os }}-${{ hashFiles('.github/workflows/copilot-setup-steps.yml') }}
restore-keys: |
docker-images-v2-${{ runner.os }}-
docker-images-v1-${{ runner.os }}-
- name: Load or pull Docker images
working-directory: autogpt_platform
run: |
mkdir -p ~/docker-cache
# Define image list for easy maintenance
IMAGES=(
"redis:latest"
"rabbitmq:management"
"clamav/clamav-debian:latest"
"busybox:latest"
"kong:2.8.1"
"supabase/gotrue:v2.170.0"
"supabase/postgres:15.8.1.049"
"supabase/postgres-meta:v0.86.1"
"supabase/studio:20250224-d10db0f"
)
# Check if any cached tar files exist (more reliable than cache-hit)
if ls ~/docker-cache/*.tar 1> /dev/null 2>&1; then
echo "Docker cache found, loading images in parallel..."
for image in "${IMAGES[@]}"; do
# Convert image name to filename (replace : and / with -)
filename=$(echo "$image" | tr ':/' '--')
if [ -f ~/docker-cache/${filename}.tar ]; then
echo "Loading $image..."
docker load -i ~/docker-cache/${filename}.tar || echo "Warning: Failed to load $image from cache" &
fi
done
wait
echo "All cached images loaded"
else
echo "No Docker cache found, pulling images in parallel..."
# Pull all images in parallel
for image in "${IMAGES[@]}"; do
docker pull "$image" &
done
wait
# Only save cache on main branches (not PRs) to avoid cache pollution
if [[ "${{ github.ref }}" == "refs/heads/master" ]] || [[ "${{ github.ref }}" == "refs/heads/dev" ]]; then
echo "Saving Docker images to cache in parallel..."
for image in "${IMAGES[@]}"; do
# Convert image name to filename (replace : and / with -)
filename=$(echo "$image" | tr ':/' '--')
echo "Saving $image..."
docker save -o ~/docker-cache/${filename}.tar "$image" || echo "Warning: Failed to save $image" &
done
wait
echo "Docker image cache saved"
else
echo "Skipping cache save for PR/feature branch"
fi
fi
echo "Docker images ready for use"
# Phase 2: Build migrate service with GitHub Actions cache
- name: Build migrate Docker image with cache
working-directory: autogpt_platform
run: |
# Build the migrate image with buildx for GHA caching
docker buildx build \
--cache-from type=gha \
--cache-to type=gha,mode=max \
--target migrate \
--tag autogpt_platform-migrate:latest \
--load \
-f backend/Dockerfile \
..
# Start services using pre-built images
- name: Start Docker services for development
working-directory: autogpt_platform
run: |
# Start essential services (migrate image already built with correct tag)
docker compose --profile local up deps --no-build --detach
echo "Waiting for services to be ready..."
# Wait for database to be ready
echo "Checking database readiness..."
timeout 30 sh -c 'until docker compose exec -T db pg_isready -U postgres 2>/dev/null; do
echo " Waiting for database..."
sleep 2
done' && echo "✅ Database is ready" || echo "⚠️ Database ready check timeout after 30s, continuing..."
# Check migrate service status
echo "Checking migration status..."
docker compose ps migrate || echo " Migrate service not visible in ps output"
# Wait for migrate service to complete
echo "Waiting for migrations to complete..."
timeout 30 bash -c '
ATTEMPTS=0
while [ $ATTEMPTS -lt 15 ]; do
ATTEMPTS=$((ATTEMPTS + 1))
# Check using docker directly (more reliable than docker compose ps)
CONTAINER_STATUS=$(docker ps -a --filter "label=com.docker.compose.service=migrate" --format "{{.Status}}" | head -1)
if [ -z "$CONTAINER_STATUS" ]; then
echo " Attempt $ATTEMPTS: Migrate container not found yet..."
elif echo "$CONTAINER_STATUS" | grep -q "Exited (0)"; then
echo "✅ Migrations completed successfully"
docker compose logs migrate --tail=5 2>/dev/null || true
exit 0
elif echo "$CONTAINER_STATUS" | grep -q "Exited ([1-9]"; then
EXIT_CODE=$(echo "$CONTAINER_STATUS" | grep -oE "Exited \([0-9]+\)" | grep -oE "[0-9]+")
echo "❌ Migrations failed with exit code: $EXIT_CODE"
echo "Migration logs:"
docker compose logs migrate --tail=20 2>/dev/null || true
exit 1
elif echo "$CONTAINER_STATUS" | grep -q "Up"; then
echo " Attempt $ATTEMPTS: Migrate container is running... ($CONTAINER_STATUS)"
else
echo " Attempt $ATTEMPTS: Migrate container status: $CONTAINER_STATUS"
fi
sleep 2
done
echo "⚠️ Timeout: Could not determine migration status after 30 seconds"
echo "Final container check:"
docker ps -a --filter "label=com.docker.compose.service=migrate" || true
echo "Migration logs (if available):"
docker compose logs migrate --tail=10 2>/dev/null || echo " No logs available"
' || echo "⚠️ Migration check completed with warnings, continuing..."
# Brief wait for other services to stabilize
echo "Waiting 5 seconds for other services to stabilize..."
sleep 5
# Verify installations and provide environment info
- name: Verify setup and show environment info
run: |
echo "=== Python Setup ==="
python --version
poetry --version
echo "=== Node.js Setup ==="
node --version
pnpm --version
echo "=== Additional Tools ==="
docker --version
docker compose version
gh --version || true
echo "=== Services Status ==="
cd autogpt_platform
docker compose ps || true
echo "=== Backend Dependencies ==="
cd backend
poetry show | head -10 || true
echo "=== Frontend Dependencies ==="
cd ../frontend
pnpm list --depth=0 | head -10 || true
echo "=== Environment Files ==="
ls -la ../.env* || true
ls -la .env* || true
ls -la ../backend/.env* || true
echo "✅ AutoGPT Platform development environment setup complete!"
echo "🚀 Ready for development with Docker services running"
echo "📝 Backend server: poetry run serve (port 8000)"
echo "🌐 Frontend server: pnpm dev (port 3000)"
- name: Run Claude Dependabot Analysis
id: claude_review
uses: anthropics/claude-code-action@v1
with:
anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
claude_args: |
--allowedTools "Bash(npm:*),Bash(pnpm:*),Bash(poetry:*),Bash(git:*),Edit,Replace,NotebookEditCell,mcp__github_inline_comment__create_inline_comment,Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*)"
prompt: |
You are Claude, an AI assistant specialized in reviewing Dependabot dependency update PRs.
Your primary tasks are:
1. **Analyze the dependency changes** in this Dependabot PR
2. **Look up changelogs** for all updated dependencies to understand what changed
3. **Identify breaking changes** and assess potential impact on the AutoGPT codebase
4. **Provide actionable recommendations** for the development team
## Analysis Process:
1. **Identify Changed Dependencies**:
- Use git diff to see what dependencies were updated
- Parse package.json, poetry.lock, requirements files, etc.
- List all package versions: old → new
2. **Changelog Research**:
- For each updated dependency, look up its changelog/release notes
- Use WebFetch to access GitHub releases, NPM package pages, PyPI project pages. The pr should also have some details
- Focus on versions between the old and new versions
- Identify: breaking changes, deprecations, security fixes, new features
3. **Breaking Change Assessment**:
- Categorize changes: BREAKING, MAJOR, MINOR, PATCH, SECURITY
- Assess impact on AutoGPT's usage patterns
- Check if AutoGPT uses affected APIs/features
- Look for migration guides or upgrade instructions
4. **Codebase Impact Analysis**:
- Search the AutoGPT codebase for usage of changed APIs
- Identify files that might be affected by breaking changes
- Check test files for deprecated usage patterns
- Look for configuration changes needed
## Output Format:
Provide a comprehensive review comment with:
### 🔍 Dependency Analysis Summary
- List of updated packages with version changes
- Overall risk assessment (LOW/MEDIUM/HIGH)
### 📋 Detailed Changelog Review
For each updated dependency:
- **Package**: name (old_version → new_version)
- **Changes**: Summary of key changes
- **Breaking Changes**: List any breaking changes
- **Security Fixes**: Note security improvements
- **Migration Notes**: Any upgrade steps needed
### ⚠️ Impact Assessment
- **Breaking Changes Found**: Yes/No with details
- **Affected Files**: List AutoGPT files that may need updates
- **Test Impact**: Any tests that may need updating
- **Configuration Changes**: Required config updates
### 🛠️ Recommendations
- **Action Required**: What the team should do
- **Testing Focus**: Areas to test thoroughly
- **Follow-up Tasks**: Any additional work needed
- **Merge Recommendation**: APPROVE/REVIEW_NEEDED/HOLD
### 📚 Useful Links
- Links to relevant changelogs, migration guides, documentation
Be thorough but concise. Focus on actionable insights that help the development team make informed decisions about the dependency updates.

View File

@@ -30,296 +30,18 @@ jobs:
github.event.issue.author_association == 'COLLABORATOR'
)
runs-on: ubuntu-latest
timeout-minutes: 45
permissions:
contents: write
contents: read
pull-requests: read
issues: read
id-token: write
actions: read # Required for CI access
steps:
- name: Checkout code
- name: Checkout repository
uses: actions/checkout@v4
with:
fetch-depth: 1
# Backend Python/Poetry setup (mirrors platform-backend-ci.yml)
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11" # Use standard version matching CI
- name: Set up Python dependency cache
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
- name: Install Poetry
run: |
# Extract Poetry version from backend/poetry.lock (matches CI)
cd autogpt_platform/backend
HEAD_POETRY_VERSION=$(python3 ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
echo "Found Poetry version ${HEAD_POETRY_VERSION} in backend/poetry.lock"
# Install Poetry
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
# Add Poetry to PATH
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Check poetry.lock
working-directory: autogpt_platform/backend
run: |
poetry lock
if ! git diff --quiet --ignore-matching-lines="^# " poetry.lock; then
echo "Warning: poetry.lock not up to date, but continuing for setup"
git checkout poetry.lock # Reset for clean setup
fi
- name: Install Python dependencies
working-directory: autogpt_platform/backend
run: poetry install
- name: Generate Prisma Client
working-directory: autogpt_platform/backend
run: poetry run prisma generate
# Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
- name: Set up Node.js
uses: actions/setup-node@v4
with:
node-version: "21"
- name: Enable corepack
run: corepack enable
- name: Set pnpm store directory
run: |
pnpm config set store-dir ~/.pnpm-store
echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
- name: Cache frontend dependencies
uses: actions/cache@v4
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') }}
${{ runner.os }}-pnpm-
- name: Install JavaScript dependencies
working-directory: autogpt_platform/frontend
run: pnpm install --frozen-lockfile
# Install Playwright browsers for frontend testing
# NOTE: Disabled to save ~1 minute of setup time. Re-enable if Copilot needs browser automation (e.g., for MCP)
# - name: Install Playwright browsers
# working-directory: autogpt_platform/frontend
# run: pnpm playwright install --with-deps chromium
# Docker setup for development environment
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Copy default environment files
working-directory: autogpt_platform
run: |
# Copy default environment files for development
cp .env.default .env
cp backend/.env.default backend/.env
cp frontend/.env.default frontend/.env
# Phase 1: Cache and load Docker images for faster setup
- name: Set up Docker image cache
id: docker-cache
uses: actions/cache@v4
with:
path: ~/docker-cache
# Use a versioned key for cache invalidation when image list changes
key: docker-images-v2-${{ runner.os }}-${{ hashFiles('.github/workflows/copilot-setup-steps.yml') }}
restore-keys: |
docker-images-v2-${{ runner.os }}-
docker-images-v1-${{ runner.os }}-
- name: Load or pull Docker images
working-directory: autogpt_platform
run: |
mkdir -p ~/docker-cache
# Define image list for easy maintenance
IMAGES=(
"redis:latest"
"rabbitmq:management"
"clamav/clamav-debian:latest"
"busybox:latest"
"kong:2.8.1"
"supabase/gotrue:v2.170.0"
"supabase/postgres:15.8.1.049"
"supabase/postgres-meta:v0.86.1"
"supabase/studio:20250224-d10db0f"
)
# Check if any cached tar files exist (more reliable than cache-hit)
if ls ~/docker-cache/*.tar 1> /dev/null 2>&1; then
echo "Docker cache found, loading images in parallel..."
for image in "${IMAGES[@]}"; do
# Convert image name to filename (replace : and / with -)
filename=$(echo "$image" | tr ':/' '--')
if [ -f ~/docker-cache/${filename}.tar ]; then
echo "Loading $image..."
docker load -i ~/docker-cache/${filename}.tar || echo "Warning: Failed to load $image from cache" &
fi
done
wait
echo "All cached images loaded"
else
echo "No Docker cache found, pulling images in parallel..."
# Pull all images in parallel
for image in "${IMAGES[@]}"; do
docker pull "$image" &
done
wait
# Only save cache on main branches (not PRs) to avoid cache pollution
if [[ "${{ github.ref }}" == "refs/heads/master" ]] || [[ "${{ github.ref }}" == "refs/heads/dev" ]]; then
echo "Saving Docker images to cache in parallel..."
for image in "${IMAGES[@]}"; do
# Convert image name to filename (replace : and / with -)
filename=$(echo "$image" | tr ':/' '--')
echo "Saving $image..."
docker save -o ~/docker-cache/${filename}.tar "$image" || echo "Warning: Failed to save $image" &
done
wait
echo "Docker image cache saved"
else
echo "Skipping cache save for PR/feature branch"
fi
fi
echo "Docker images ready for use"
# Phase 2: Build migrate service with GitHub Actions cache
- name: Build migrate Docker image with cache
working-directory: autogpt_platform
run: |
# Build the migrate image with buildx for GHA caching
docker buildx build \
--cache-from type=gha \
--cache-to type=gha,mode=max \
--target migrate \
--tag autogpt_platform-migrate:latest \
--load \
-f backend/Dockerfile \
..
# Start services using pre-built images
- name: Start Docker services for development
working-directory: autogpt_platform
run: |
# Start essential services (migrate image already built with correct tag)
docker compose --profile local up deps --no-build --detach
echo "Waiting for services to be ready..."
# Wait for database to be ready
echo "Checking database readiness..."
timeout 30 sh -c 'until docker compose exec -T db pg_isready -U postgres 2>/dev/null; do
echo " Waiting for database..."
sleep 2
done' && echo "✅ Database is ready" || echo "⚠️ Database ready check timeout after 30s, continuing..."
# Check migrate service status
echo "Checking migration status..."
docker compose ps migrate || echo " Migrate service not visible in ps output"
# Wait for migrate service to complete
echo "Waiting for migrations to complete..."
timeout 30 bash -c '
ATTEMPTS=0
while [ $ATTEMPTS -lt 15 ]; do
ATTEMPTS=$((ATTEMPTS + 1))
# Check using docker directly (more reliable than docker compose ps)
CONTAINER_STATUS=$(docker ps -a --filter "label=com.docker.compose.service=migrate" --format "{{.Status}}" | head -1)
if [ -z "$CONTAINER_STATUS" ]; then
echo " Attempt $ATTEMPTS: Migrate container not found yet..."
elif echo "$CONTAINER_STATUS" | grep -q "Exited (0)"; then
echo "✅ Migrations completed successfully"
docker compose logs migrate --tail=5 2>/dev/null || true
exit 0
elif echo "$CONTAINER_STATUS" | grep -q "Exited ([1-9]"; then
EXIT_CODE=$(echo "$CONTAINER_STATUS" | grep -oE "Exited \([0-9]+\)" | grep -oE "[0-9]+")
echo "❌ Migrations failed with exit code: $EXIT_CODE"
echo "Migration logs:"
docker compose logs migrate --tail=20 2>/dev/null || true
exit 1
elif echo "$CONTAINER_STATUS" | grep -q "Up"; then
echo " Attempt $ATTEMPTS: Migrate container is running... ($CONTAINER_STATUS)"
else
echo " Attempt $ATTEMPTS: Migrate container status: $CONTAINER_STATUS"
fi
sleep 2
done
echo "⚠️ Timeout: Could not determine migration status after 30 seconds"
echo "Final container check:"
docker ps -a --filter "label=com.docker.compose.service=migrate" || true
echo "Migration logs (if available):"
docker compose logs migrate --tail=10 2>/dev/null || echo " No logs available"
' || echo "⚠️ Migration check completed with warnings, continuing..."
# Brief wait for other services to stabilize
echo "Waiting 5 seconds for other services to stabilize..."
sleep 5
# Verify installations and provide environment info
- name: Verify setup and show environment info
run: |
echo "=== Python Setup ==="
python --version
poetry --version
echo "=== Node.js Setup ==="
node --version
pnpm --version
echo "=== Additional Tools ==="
docker --version
docker compose version
gh --version || true
echo "=== Services Status ==="
cd autogpt_platform
docker compose ps || true
echo "=== Backend Dependencies ==="
cd backend
poetry show | head -10 || true
echo "=== Frontend Dependencies ==="
cd ../frontend
pnpm list --depth=0 | head -10 || true
echo "=== Environment Files ==="
ls -la ../.env* || true
ls -la .env* || true
ls -la ../backend/.env* || true
echo "✅ AutoGPT Platform development environment setup complete!"
echo "🚀 Ready for development with Docker services running"
echo "📝 Backend server: poetry run serve (port 8000)"
echo "🌐 Frontend server: pnpm dev (port 3000)"
- name: Run Claude Code
id: claude
uses: anthropics/claude-code-action@v1
uses: anthropics/claude-code-action@beta
with:
anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
claude_args: |
--allowedTools "Bash(npm:*),Bash(pnpm:*),Bash(poetry:*),Bash(git:*),Edit,Replace,NotebookEditCell,mcp__github_inline_comment__create_inline_comment,Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*), Bash(gh pr edit:*)"
--model opus
additional_permissions: |
actions: read

View File

@@ -1,302 +0,0 @@
name: "Copilot Setup Steps"
# Automatically run the setup steps when they are changed to allow for easy validation, and
# allow manual testing through the repository's "Actions" tab
on:
workflow_dispatch:
push:
paths:
- .github/workflows/copilot-setup-steps.yml
pull_request:
paths:
- .github/workflows/copilot-setup-steps.yml
jobs:
# The job MUST be called `copilot-setup-steps` or it will not be picked up by Copilot.
copilot-setup-steps:
runs-on: ubuntu-latest
timeout-minutes: 45
# Set the permissions to the lowest permissions possible needed for your steps.
# Copilot will be given its own token for its operations.
permissions:
# If you want to clone the repository as part of your setup steps, for example to install dependencies, you'll need the `contents: read` permission. If you don't clone the repository in your setup steps, Copilot will do this for you automatically after the steps complete.
contents: read
# You can define any steps you want, and they will run before the agent starts.
# If you do not check out your code, Copilot will do this for you.
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0
submodules: true
# Backend Python/Poetry setup (mirrors platform-backend-ci.yml)
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: "3.11" # Use standard version matching CI
- name: Set up Python dependency cache
uses: actions/cache@v4
with:
path: ~/.cache/pypoetry
key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
- name: Install Poetry
run: |
# Extract Poetry version from backend/poetry.lock (matches CI)
cd autogpt_platform/backend
HEAD_POETRY_VERSION=$(python3 ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
echo "Found Poetry version ${HEAD_POETRY_VERSION} in backend/poetry.lock"
# Install Poetry
curl -sSL https://install.python-poetry.org | POETRY_VERSION=$HEAD_POETRY_VERSION python3 -
# Add Poetry to PATH
echo "$HOME/.local/bin" >> $GITHUB_PATH
- name: Check poetry.lock
working-directory: autogpt_platform/backend
run: |
poetry lock
if ! git diff --quiet --ignore-matching-lines="^# " poetry.lock; then
echo "Warning: poetry.lock not up to date, but continuing for setup"
git checkout poetry.lock # Reset for clean setup
fi
- name: Install Python dependencies
working-directory: autogpt_platform/backend
run: poetry install
- name: Generate Prisma Client
working-directory: autogpt_platform/backend
run: poetry run prisma generate
# Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
- name: Set up Node.js
uses: actions/setup-node@v4
with:
node-version: "21"
- name: Enable corepack
run: corepack enable
- name: Set pnpm store directory
run: |
pnpm config set store-dir ~/.pnpm-store
echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
- name: Cache frontend dependencies
uses: actions/cache@v4
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') }}
${{ runner.os }}-pnpm-
- name: Install JavaScript dependencies
working-directory: autogpt_platform/frontend
run: pnpm install --frozen-lockfile
# Install Playwright browsers for frontend testing
# NOTE: Disabled to save ~1 minute of setup time. Re-enable if Copilot needs browser automation (e.g., for MCP)
# - name: Install Playwright browsers
# working-directory: autogpt_platform/frontend
# run: pnpm playwright install --with-deps chromium
# Docker setup for development environment
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Copy default environment files
working-directory: autogpt_platform
run: |
# Copy default environment files for development
cp .env.default .env
cp backend/.env.default backend/.env
cp frontend/.env.default frontend/.env
# Phase 1: Cache and load Docker images for faster setup
- name: Set up Docker image cache
id: docker-cache
uses: actions/cache@v4
with:
path: ~/docker-cache
# Use a versioned key for cache invalidation when image list changes
key: docker-images-v2-${{ runner.os }}-${{ hashFiles('.github/workflows/copilot-setup-steps.yml') }}
restore-keys: |
docker-images-v2-${{ runner.os }}-
docker-images-v1-${{ runner.os }}-
- name: Load or pull Docker images
working-directory: autogpt_platform
run: |
mkdir -p ~/docker-cache
# Define image list for easy maintenance
IMAGES=(
"redis:latest"
"rabbitmq:management"
"clamav/clamav-debian:latest"
"busybox:latest"
"kong:2.8.1"
"supabase/gotrue:v2.170.0"
"supabase/postgres:15.8.1.049"
"supabase/postgres-meta:v0.86.1"
"supabase/studio:20250224-d10db0f"
)
# Check if any cached tar files exist (more reliable than cache-hit)
if ls ~/docker-cache/*.tar 1> /dev/null 2>&1; then
echo "Docker cache found, loading images in parallel..."
for image in "${IMAGES[@]}"; do
# Convert image name to filename (replace : and / with -)
filename=$(echo "$image" | tr ':/' '--')
if [ -f ~/docker-cache/${filename}.tar ]; then
echo "Loading $image..."
docker load -i ~/docker-cache/${filename}.tar || echo "Warning: Failed to load $image from cache" &
fi
done
wait
echo "All cached images loaded"
else
echo "No Docker cache found, pulling images in parallel..."
# Pull all images in parallel
for image in "${IMAGES[@]}"; do
docker pull "$image" &
done
wait
# Only save cache on main branches (not PRs) to avoid cache pollution
if [[ "${{ github.ref }}" == "refs/heads/master" ]] || [[ "${{ github.ref }}" == "refs/heads/dev" ]]; then
echo "Saving Docker images to cache in parallel..."
for image in "${IMAGES[@]}"; do
# Convert image name to filename (replace : and / with -)
filename=$(echo "$image" | tr ':/' '--')
echo "Saving $image..."
docker save -o ~/docker-cache/${filename}.tar "$image" || echo "Warning: Failed to save $image" &
done
wait
echo "Docker image cache saved"
else
echo "Skipping cache save for PR/feature branch"
fi
fi
echo "Docker images ready for use"
# Phase 2: Build migrate service with GitHub Actions cache
- name: Build migrate Docker image with cache
working-directory: autogpt_platform
run: |
# Build the migrate image with buildx for GHA caching
docker buildx build \
--cache-from type=gha \
--cache-to type=gha,mode=max \
--target migrate \
--tag autogpt_platform-migrate:latest \
--load \
-f backend/Dockerfile \
..
# Start services using pre-built images
- name: Start Docker services for development
working-directory: autogpt_platform
run: |
# Start essential services (migrate image already built with correct tag)
docker compose --profile local up deps --no-build --detach
echo "Waiting for services to be ready..."
# Wait for database to be ready
echo "Checking database readiness..."
timeout 30 sh -c 'until docker compose exec -T db pg_isready -U postgres 2>/dev/null; do
echo " Waiting for database..."
sleep 2
done' && echo "✅ Database is ready" || echo "⚠️ Database ready check timeout after 30s, continuing..."
# Check migrate service status
echo "Checking migration status..."
docker compose ps migrate || echo " Migrate service not visible in ps output"
# Wait for migrate service to complete
echo "Waiting for migrations to complete..."
timeout 30 bash -c '
ATTEMPTS=0
while [ $ATTEMPTS -lt 15 ]; do
ATTEMPTS=$((ATTEMPTS + 1))
# Check using docker directly (more reliable than docker compose ps)
CONTAINER_STATUS=$(docker ps -a --filter "label=com.docker.compose.service=migrate" --format "{{.Status}}" | head -1)
if [ -z "$CONTAINER_STATUS" ]; then
echo " Attempt $ATTEMPTS: Migrate container not found yet..."
elif echo "$CONTAINER_STATUS" | grep -q "Exited (0)"; then
echo "✅ Migrations completed successfully"
docker compose logs migrate --tail=5 2>/dev/null || true
exit 0
elif echo "$CONTAINER_STATUS" | grep -q "Exited ([1-9]"; then
EXIT_CODE=$(echo "$CONTAINER_STATUS" | grep -oE "Exited \([0-9]+\)" | grep -oE "[0-9]+")
echo "❌ Migrations failed with exit code: $EXIT_CODE"
echo "Migration logs:"
docker compose logs migrate --tail=20 2>/dev/null || true
exit 1
elif echo "$CONTAINER_STATUS" | grep -q "Up"; then
echo " Attempt $ATTEMPTS: Migrate container is running... ($CONTAINER_STATUS)"
else
echo " Attempt $ATTEMPTS: Migrate container status: $CONTAINER_STATUS"
fi
sleep 2
done
echo "⚠️ Timeout: Could not determine migration status after 30 seconds"
echo "Final container check:"
docker ps -a --filter "label=com.docker.compose.service=migrate" || true
echo "Migration logs (if available):"
docker compose logs migrate --tail=10 2>/dev/null || echo " No logs available"
' || echo "⚠️ Migration check completed with warnings, continuing..."
# Brief wait for other services to stabilize
echo "Waiting 5 seconds for other services to stabilize..."
sleep 5
# Verify installations and provide environment info
- name: Verify setup and show environment info
run: |
echo "=== Python Setup ==="
python --version
poetry --version
echo "=== Node.js Setup ==="
node --version
pnpm --version
echo "=== Additional Tools ==="
docker --version
docker compose version
gh --version || true
echo "=== Services Status ==="
cd autogpt_platform
docker compose ps || true
echo "=== Backend Dependencies ==="
cd backend
poetry show | head -10 || true
echo "=== Frontend Dependencies ==="
cd ../frontend
pnpm list --depth=0 | head -10 || true
echo "=== Environment Files ==="
ls -la ../.env* || true
ls -la .env* || true
ls -la ../backend/.env* || true
echo "✅ AutoGPT Platform development environment setup complete!"
echo "🚀 Ready for development with Docker services running"
echo "📝 Backend server: poetry run serve (port 8000)"
echo "🌐 Frontend server: pnpm dev (port 3000)"

View File

@@ -32,7 +32,7 @@ jobs:
strategy:
fail-fast: false
matrix:
python-version: ["3.11", "3.12", "3.13"]
python-version: ["3.11"]
runs-on: ubuntu-latest
services:
@@ -201,7 +201,7 @@ jobs:
DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}
SUPABASE_URL: ${{ steps.supabase.outputs.API_URL }}
SUPABASE_SERVICE_ROLE_KEY: ${{ steps.supabase.outputs.SERVICE_ROLE_KEY }}
JWT_VERIFY_KEY: ${{ steps.supabase.outputs.JWT_SECRET }}
SUPABASE_JWT_SECRET: ${{ steps.supabase.outputs.JWT_SECRET }}
REDIS_HOST: "localhost"
REDIS_PORT: "6379"
REDIS_PASSWORD: "testpassword"

View File

@@ -82,6 +82,37 @@ jobs:
- name: Run lint
run: pnpm lint
type-check:
runs-on: ubuntu-latest
needs: setup
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Set up Node.js
uses: actions/setup-node@v4
with:
node-version: "21"
- name: Enable corepack
run: corepack enable
- name: Restore dependencies cache
uses: actions/cache@v4
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-
- name: Install dependencies
run: pnpm install --frozen-lockfile
- name: Run tsc check
run: pnpm type-check
chromatic:
runs-on: ubuntu-latest
needs: setup
@@ -145,7 +176,11 @@ jobs:
- name: Copy default supabase .env
run: |
cp ../.env.default ../.env
cp ../.env.example ../.env
- name: Copy backend .env
run: |
cp ../backend/.env.example ../backend/.env
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
@@ -160,7 +195,7 @@ jobs:
- name: Run docker compose
run: |
NEXT_PUBLIC_PW_TEST=true docker compose -f ../docker-compose.yml up -d
docker compose -f ../docker-compose.yml up -d
env:
DOCKER_BUILDKIT: 1
BUILDX_CACHE_FROM: type=local,src=/tmp/.buildx-cache
@@ -217,6 +252,15 @@ jobs:
- name: Install dependencies
run: pnpm install --frozen-lockfile
- name: Setup .env
run: cp .env.example .env
- name: Build frontend
run: pnpm build --turbo
# uses Turbopack, much faster and safe enough for a test pipeline
env:
NEXT_PUBLIC_PW_TEST: true
- name: Install Browser 'chromium'
run: pnpm playwright install --with-deps chromium

View File

@@ -1,132 +0,0 @@
name: AutoGPT Platform - Frontend CI
on:
push:
branches: [master, dev]
paths:
- ".github/workflows/platform-fullstack-ci.yml"
- "autogpt_platform/**"
pull_request:
paths:
- ".github/workflows/platform-fullstack-ci.yml"
- "autogpt_platform/**"
merge_group:
defaults:
run:
shell: bash
working-directory: autogpt_platform/frontend
jobs:
setup:
runs-on: ubuntu-latest
outputs:
cache-key: ${{ steps.cache-key.outputs.key }}
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Set up Node.js
uses: actions/setup-node@v4
with:
node-version: "21"
- name: Enable corepack
run: corepack enable
- name: Generate cache key
id: cache-key
run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}" >> $GITHUB_OUTPUT
- name: Cache dependencies
uses: actions/cache@v4
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-
- name: Install dependencies
run: pnpm install --frozen-lockfile
types:
runs-on: ubuntu-latest
needs: setup
strategy:
fail-fast: false
steps:
- name: Checkout repository
uses: actions/checkout@v4
with:
submodules: recursive
- name: Set up Node.js
uses: actions/setup-node@v4
with:
node-version: "21"
- name: Enable corepack
run: corepack enable
- name: Copy default supabase .env
run: |
cp ../.env.default ../.env
- name: Copy backend .env
run: |
cp ../backend/.env.default ../backend/.env
- name: Run docker compose
run: |
docker compose -f ../docker-compose.yml --profile local --profile deps_backend up -d
- name: Restore dependencies cache
uses: actions/cache@v4
with:
path: ~/.pnpm-store
key: ${{ needs.setup.outputs.cache-key }}
restore-keys: |
${{ runner.os }}-pnpm-
- name: Install dependencies
run: pnpm install --frozen-lockfile
- name: Setup .env
run: cp .env.default .env
- name: Wait for services to be ready
run: |
echo "Waiting for rest_server to be ready..."
timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
echo "Waiting for database to be ready..."
timeout 60 sh -c 'until docker compose -f ../docker-compose.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done' || echo "Database ready check timeout, continuing..."
- name: Generate API queries
run: pnpm generate:api:force
- name: Check for API schema changes
run: |
if ! git diff --exit-code src/app/api/openapi.json; then
echo "❌ API schema changes detected in src/app/api/openapi.json"
echo ""
echo "The openapi.json file has been modified after running 'pnpm generate:api-all'."
echo "This usually means changes have been made in the BE endpoints without updating the Frontend."
echo "The API schema is now out of sync with the Front-end queries."
echo ""
echo "To fix this:"
echo "1. Pull the backend 'docker compose pull && docker compose up -d --build --force-recreate'"
echo "2. Run 'pnpm generate:api' locally"
echo "3. Run 'pnpm types' locally"
echo "4. Fix any TypeScript errors that may have been introduced"
echo "5. Commit and push your changes"
echo ""
exit 1
else
echo "✅ No API schema changes detected"
fi
- name: Run Typescript checks
run: pnpm types

3
.gitignore vendored
View File

@@ -5,8 +5,6 @@ classic/original_autogpt/*.json
auto_gpt_workspace/*
*.mpeg
.env
# Root .env files
/.env
azure.yaml
.vscode
.idea/*
@@ -123,6 +121,7 @@ celerybeat.pid
# Environments
.direnv/
.env
.venv
env/
venv*/

View File

@@ -235,7 +235,7 @@ repos:
hooks:
- id: tsc
name: Typecheck - AutoGPT Platform - Frontend
entry: bash -c 'cd autogpt_platform/frontend && pnpm types'
entry: bash -c 'cd autogpt_platform/frontend && pnpm type-check'
files: ^autogpt_platform/frontend/
types: [file]
language: system

View File

@@ -3,16 +3,6 @@
[![Discord Follow](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fdiscord.com%2Fapi%2Finvites%2Fautogpt%3Fwith_counts%3Dtrue&query=%24.approximate_member_count&label=total%20members&logo=discord&logoColor=white&color=7289da)](https://discord.gg/autogpt) &ensp;
[![Twitter Follow](https://img.shields.io/twitter/follow/Auto_GPT?style=social)](https://twitter.com/Auto_GPT) &ensp;
<!-- Keep these links. Translations will automatically update with the README. -->
[Deutsch](https://zdoc.app/de/Significant-Gravitas/AutoGPT) |
[Español](https://zdoc.app/es/Significant-Gravitas/AutoGPT) |
[français](https://zdoc.app/fr/Significant-Gravitas/AutoGPT) |
[日本語](https://zdoc.app/ja/Significant-Gravitas/AutoGPT) |
[한국어](https://zdoc.app/ko/Significant-Gravitas/AutoGPT) |
[Português](https://zdoc.app/pt/Significant-Gravitas/AutoGPT) |
[Русский](https://zdoc.app/ru/Significant-Gravitas/AutoGPT) |
[中文](https://zdoc.app/zh/Significant-Gravitas/AutoGPT)
**AutoGPT** is a powerful platform that allows you to create, deploy, and manage continuous AI agents that automate complex workflows.
## Hosting Options

View File

@@ -1,11 +1,9 @@
# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## Repository Overview
AutoGPT Platform is a monorepo containing:
- **Backend** (`/backend`): Python FastAPI server with async support
- **Frontend** (`/frontend`): Next.js React application
- **Shared Libraries** (`/autogpt_libs`): Common Python utilities
@@ -13,7 +11,6 @@ AutoGPT Platform is a monorepo containing:
## Essential Commands
### Backend Development
```bash
# Install dependencies
cd backend && poetry install
@@ -33,18 +30,11 @@ poetry run test
# Run specific test
poetry run pytest path/to/test_file.py::test_function_name
# Run block tests (tests that validate all blocks work correctly)
poetry run pytest backend/blocks/test/test_block.py -xvs
# Run tests for a specific block (e.g., GetCurrentTimeBlock)
poetry run pytest 'backend/blocks/test/test_block.py::test_available_blocks[GetCurrentTimeBlock]' -xvs
# Lint and format
# prefer format if you want to just "fix" it and only get the errors that can't be autofixed
poetry run format # Black + isort
poetry run lint # ruff
```
More details can be found in TESTING.md
#### Creating/Updating Snapshots
@@ -57,35 +47,31 @@ poetry run pytest path/to/test.py --snapshot-update
⚠️ **Important**: Always review snapshot changes before committing! Use `git diff` to verify the changes are expected.
### Frontend Development
### Frontend Development
```bash
# Install dependencies
cd frontend && pnpm i
cd frontend && npm install
# Start development server
pnpm dev
npm run dev
# Run E2E tests
pnpm test
npm run test
# Run Storybook for component development
pnpm storybook
npm run storybook
# Build production
pnpm build
npm run build
# Type checking
pnpm types
npm run type-check
```
We have a components library in autogpt_platform/frontend/src/components/atoms that should be used when adding new pages and components.
## Architecture Overview
### Backend Architecture
- **API Layer**: FastAPI with REST and WebSocket endpoints
- **Database**: PostgreSQL with Prisma ORM, includes pgvector for embeddings
- **Queue System**: RabbitMQ for async task processing
@@ -94,7 +80,6 @@ We have a components library in autogpt_platform/frontend/src/components/atoms t
- **Security**: Cache protection middleware prevents sensitive data caching in browsers/proxies
### Frontend Architecture
- **Framework**: Next.js App Router with React Server Components
- **State Management**: React hooks + Supabase client for real-time updates
- **Workflow Builder**: Visual graph editor using @xyflow/react
@@ -102,7 +87,6 @@ We have a components library in autogpt_platform/frontend/src/components/atoms t
- **Feature Flags**: LaunchDarkly integration
### Key Concepts
1. **Agent Graphs**: Workflow definitions stored as JSON, executed by the backend
2. **Blocks**: Reusable components in `/backend/blocks/` that perform specific tasks
3. **Integrations**: OAuth and API connections stored per user
@@ -110,16 +94,13 @@ We have a components library in autogpt_platform/frontend/src/components/atoms t
5. **Virus Scanning**: ClamAV integration for file upload security
### Testing Approach
- Backend uses pytest with snapshot testing for API responses
- Test files are colocated with source files (`*_test.py`)
- Frontend uses Playwright for E2E tests
- Component testing via Storybook
### Database Schema
Key models (defined in `/backend/schema.prisma`):
- `User`: Authentication and profile data
- `AgentGraph`: Workflow definitions with version control
- `AgentGraphExecution`: Execution history and results
@@ -127,59 +108,27 @@ Key models (defined in `/backend/schema.prisma`):
- `StoreListing`: Marketplace listings for sharing agents
### Environment Configuration
#### Configuration Files
- **Backend**: `/backend/.env.default` (defaults) → `/backend/.env` (user overrides)
- **Frontend**: `/frontend/.env.default` (defaults) → `/frontend/.env` (user overrides)
- **Platform**: `/.env.default` (Supabase/shared defaults) → `/.env` (user overrides)
#### Docker Environment Loading Order
1. `.env.default` files provide base configuration (tracked in git)
2. `.env` files provide user-specific overrides (gitignored)
3. Docker Compose `environment:` sections provide service-specific overrides
4. Shell environment variables have highest precedence
#### Key Points
- All services use hardcoded defaults in docker-compose files (no `${VARIABLE}` substitutions)
- The `env_file` directive loads variables INTO containers at runtime
- Backend/Frontend services use YAML anchors for consistent configuration
- Supabase services (`db/docker/docker-compose.yml`) follow the same pattern
- Backend: `.env` file in `/backend`
- Frontend: `.env.local` file in `/frontend`
- Both require Supabase credentials and API keys for various services
### Common Development Tasks
**Adding a new block:**
Follow the comprehensive [Block SDK Guide](../../../docs/content/platform/block-sdk-guide.md) which covers:
- Provider configuration with `ProviderBuilder`
- Block schema definition
- Authentication (API keys, OAuth, webhooks)
- Testing and validation
- File organization
Quick steps:
1. Create new file in `/backend/backend/blocks/`
2. Configure provider using `ProviderBuilder` in `_config.py`
3. Inherit from `Block` base class
4. Define input/output schemas using `BlockSchema`
5. Implement async `run` method
6. Generate unique block ID using `uuid.uuid4()`
7. Test with `poetry run pytest backend/blocks/test/test_block.py`
Note: when making many new blocks analyze the interfaces for each of these blocks and picture if they would go well together in a graph based editor or would they struggle to connect productively?
ex: do the inputs and outputs tie well together?
2. Inherit from `Block` base class
3. Define input/output schemas
4. Implement `run` method
5. Register in block registry
6. Generate the block uuid using `uuid.uuid4()`
**Modifying the API:**
1. Update route in `/backend/backend/server/routers/`
2. Add/update Pydantic models in same directory
3. Write tests alongside the route file
4. Run `poetry run test` to verify
**Frontend feature development:**
1. Components go in `/frontend/src/components/`
2. Use existing UI components from `/frontend/src/components/ui/`
3. Add Storybook stories for new components
@@ -188,7 +137,6 @@ ex: do the inputs and outputs tie well together?
### Security Implementation
**Cache Protection Middleware:**
- Located in `/backend/backend/server/middleware/security.py`
- Default behavior: Disables caching for ALL endpoints with `Cache-Control: no-store, no-cache, must-revalidate, private`
- Uses an allow list approach - only explicitly permitted paths can be cached
@@ -196,47 +144,3 @@ ex: do the inputs and outputs tie well together?
- Prevents sensitive data (auth tokens, API keys, user data) from being cached by browsers/proxies
- To allow caching for a new endpoint, add it to `CACHEABLE_PATHS` in the middleware
- Applied to both main API server and external API applications
### Creating Pull Requests
- Create the PR aginst the `dev` branch of the repository.
- Ensure the branch name is descriptive (e.g., `feature/add-new-block`)/
- Use conventional commit messages (see below)/
- Fill out the .github/PULL_REQUEST_TEMPLATE.md template as the PR description/
- Run the github pre-commit hooks to ensure code quality.
### Reviewing/Revising Pull Requests
- When the user runs /pr-comments or tries to fetch them, also run gh api /repos/Significant-Gravitas/AutoGPT/pulls/[issuenum]/reviews to get the reviews
- Use gh api /repos/Significant-Gravitas/AutoGPT/pulls/[issuenum]/reviews/[review_id]/comments to get the review contents
- Use gh api /repos/Significant-Gravitas/AutoGPT/issues/9924/comments to get the pr specific comments
### Conventional Commits
Use this format for commit messages and Pull Request titles:
**Conventional Commit Types:**
- `feat`: Introduces a new feature to the codebase
- `fix`: Patches a bug in the codebase
- `refactor`: Code change that neither fixes a bug nor adds a feature; also applies to removing features
- `ci`: Changes to CI configuration
- `docs`: Documentation-only changes
- `dx`: Improvements to the developer experience
**Recommended Base Scopes:**
- `platform`: Changes affecting both frontend and backend
- `frontend`
- `backend`
- `infra`
- `blocks`: Modifications/additions of individual blocks
**Subscope Examples:**
- `backend/executor`
- `backend/db`
- `frontend/builder` (includes changes to the block UI component)
- `infra/prod`
Use these scopes and subscopes for clarity and consistency in commit messages.

View File

@@ -8,6 +8,7 @@ Welcome to the AutoGPT Platform - a powerful system for creating and running AI
- Docker
- Docker Compose V2 (comes with Docker Desktop, or can be installed separately)
- Node.js & NPM (for running the frontend application)
### Running the System
@@ -23,10 +24,10 @@ To run the AutoGPT Platform, follow these steps:
2. Run the following command:
```
cp .env.default .env
cp .env.example .env
```
This command will copy the `.env.default` file to `.env`. You can modify the `.env` file to add your own environment variables.
This command will copy the `.env.example` file to `.env`. You can modify the `.env` file to add your own environment variables.
3. Run the following command:
@@ -36,7 +37,44 @@ To run the AutoGPT Platform, follow these steps:
This command will start all the necessary backend services defined in the `docker-compose.yml` file in detached mode.
4. After all the services are in ready state, open your browser and navigate to `http://localhost:3000` to access the AutoGPT Platform frontend.
4. Navigate to `frontend` within the `autogpt_platform` directory:
```
cd frontend
```
You will need to run your frontend application separately on your local machine.
5. Run the following command:
```
cp .env.example .env.local
```
This command will copy the `.env.example` file to `.env.local` in the `frontend` directory. You can modify the `.env.local` within this folder to add your own environment variables for the frontend application.
6. Run the following command:
Enable corepack and install dependencies by running:
```
corepack enable
pnpm i
```
Generate the API client (this step is required before running the frontend):
```
pnpm generate:api-client
```
Then start the frontend application in development mode:
```
pnpm dev
```
7. Open your browser and navigate to `http://localhost:3000` to access the AutoGPT Platform frontend.
### Docker Compose Commands
@@ -139,21 +177,20 @@ The platform includes scripts for generating and managing the API client:
- `pnpm fetch:openapi`: Fetches the OpenAPI specification from the backend service (requires backend to be running on port 8006)
- `pnpm generate:api-client`: Generates the TypeScript API client from the OpenAPI specification using Orval
- `pnpm generate:api`: Runs both fetch and generate commands in sequence
- `pnpm generate:api-all`: Runs both fetch and generate commands in sequence
#### Manual API Client Updates
If you need to update the API client after making changes to the backend API:
1. Ensure the backend services are running:
```
docker compose up -d
```
2. Generate the updated API client:
```
pnpm generate:api
pnpm generate:api-all
```
This will fetch the latest OpenAPI specification and regenerate the TypeScript client code.

View File

@@ -0,0 +1,802 @@
# DatabaseManager Technical Specification
## Executive Summary
This document provides a complete technical specification for implementing a drop-in replacement for the AutoGPT Platform's DatabaseManager service. The replacement must maintain 100% API compatibility while preserving all functional behaviors, security requirements, and performance characteristics.
## 1. System Overview
### 1.1 Purpose
The DatabaseManager is a centralized service that provides database access for the AutoGPT Platform's executor system. It encapsulates all database operations behind a service interface, enabling distributed execution while maintaining data consistency and security.
### 1.2 Architecture Pattern
- **Service Type**: HTTP-based microservice using FastAPI
- **Communication**: RPC-style over HTTP with JSON serialization
- **Base Class**: Inherits from `AppService` (backend.util.service)
- **Client Classes**: `DatabaseManagerClient` (sync) and `DatabaseManagerAsyncClient` (async)
- **Port**: Configurable via `config.database_api_port`
### 1.3 Critical Requirements
1. **API Compatibility**: All 40+ exposed methods must maintain exact signatures
2. **Type Safety**: Full type preservation across service boundaries
3. **User Isolation**: All operations must respect user_id boundaries
4. **Transaction Support**: Maintain ACID properties for critical operations
5. **Event Publishing**: Maintain Redis event bus integration for real-time updates
## 2. Service Implementation Requirements
### 2.1 Base Service Class
```python
from backend.util.service import AppService, expose
from backend.util.settings import Config
from backend.data import db
import logging
class DatabaseManager(AppService):
"""
REQUIRED: Inherit from AppService to get:
- Automatic endpoint generation via @expose decorator
- Built-in health checks at /health
- Request/response serialization
- Error handling and logging
"""
def run_service(self) -> None:
"""REQUIRED: Initialize database connection before starting service"""
logger.info(f"[{self.service_name}] ⏳ Connecting to Database...")
self.run_and_wait(db.connect()) # CRITICAL: Must connect to database
super().run_service() # Start HTTP server
def cleanup(self):
"""REQUIRED: Clean disconnect on shutdown"""
super().cleanup()
logger.info(f"[{self.service_name}] ⏳ Disconnecting Database...")
self.run_and_wait(db.disconnect()) # CRITICAL: Must disconnect cleanly
@classmethod
def get_port(cls) -> int:
"""REQUIRED: Return configured port"""
return config.database_api_port
```
### 2.2 Method Exposure Pattern
```python
@staticmethod
def _(f: Callable[P, R], name: str | None = None) -> Callable[Concatenate[object, P], R]:
"""
REQUIRED: Helper to expose methods with proper signatures
- Preserves function name for endpoint generation
- Maintains type information
- Adds 'self' parameter for instance binding
"""
if name is not None:
f.__name__ = name
return cast(Callable[Concatenate[object, P], R], expose(f))
```
### 2.3 Database Connection Management
**REQUIRED: Use Prisma ORM with these exact configurations:**
```python
from prisma import Prisma
prisma = Prisma(
auto_register=True,
http={"timeout": HTTP_TIMEOUT}, # Default: 120 seconds
datasource={"url": DATABASE_URL}
)
# Connection lifecycle
async def connect():
await prisma.connect()
async def disconnect():
await prisma.disconnect()
```
### 2.4 Transaction Support
**REQUIRED: Implement both regular and locked transactions:**
```python
async def transaction(timeout: float | None = None):
"""Regular database transaction"""
async with prisma.tx(timeout=timeout) as tx:
yield tx
async def locked_transaction(key: str, timeout: float | None = None):
"""Transaction with PostgreSQL advisory lock"""
lock_key = zlib.crc32(key.encode("utf-8"))
async with transaction(timeout=timeout) as tx:
await tx.execute_raw("SELECT pg_advisory_xact_lock($1)", lock_key)
yield tx
```
## 3. Complete API Specification
### 3.1 Execution Management APIs
#### get_graph_execution
```python
async def get_graph_execution(
user_id: str,
execution_id: str,
*,
include_node_executions: bool = False
) -> GraphExecution | GraphExecutionWithNodes | None
```
**Behavior**:
- Returns execution only if user_id matches
- Optionally includes all node executions
- Returns None if not found or unauthorized
#### get_graph_executions
```python
async def get_graph_executions(
user_id: str,
graph_id: str | None = None,
*,
limit: int = 50,
graph_version: int | None = None,
cursor: str | None = None,
preset_id: str | None = None
) -> tuple[list[GraphExecution], str | None]
```
**Behavior**:
- Paginated results with cursor
- Filter by graph_id, version, or preset_id
- Returns (executions, next_cursor)
#### create_graph_execution
```python
async def create_graph_execution(
graph_id: str,
graph_version: int,
starting_nodes_input: dict[str, dict[str, Any]],
user_id: str,
preset_id: str | None = None
) -> GraphExecutionWithNodes
```
**Behavior**:
- Creates execution with status "QUEUED"
- Initializes all nodes with "PENDING" status
- Publishes creation event to Redis
- Uses locked transaction on graph_id
#### update_graph_execution_start_time
```python
async def update_graph_execution_start_time(
graph_exec_id: str
) -> None
```
**Behavior**:
- Sets start_time to current timestamp
- Only updates if currently NULL
#### update_graph_execution_stats
```python
async def update_graph_execution_stats(
graph_exec_id: str,
status: AgentExecutionStatus | None = None,
stats: dict[str, Any] | None = None
) -> GraphExecution | None
```
**Behavior**:
- Updates status and/or stats atomically
- Sets end_time if status is terminal (COMPLETED/FAILED)
- Publishes update event to Redis
- Returns updated execution
#### get_node_execution
```python
async def get_node_execution(
node_exec_id: str
) -> NodeExecutionResult | None
```
**Behavior**:
- No user_id check (relies on graph execution security)
- Includes all input/output data
#### get_node_executions
```python
async def get_node_executions(
graph_exec_id: str
) -> list[NodeExecutionResult]
```
**Behavior**:
- Returns all node executions for graph
- Ordered by creation time
#### get_latest_node_execution
```python
async def get_latest_node_execution(
graph_exec_id: str,
node_id: str
) -> NodeExecutionResult | None
```
**Behavior**:
- Returns most recent execution of specific node
- Used for retry/rerun scenarios
#### update_node_execution_status
```python
async def update_node_execution_status(
node_exec_id: str,
status: AgentExecutionStatus,
execution_data: dict[str, Any] | None = None,
stats: dict[str, Any] | None = None
) -> NodeExecutionResult
```
**Behavior**:
- Updates status atomically
- Sets end_time for terminal states
- Optionally updates stats/data
- Publishes event to Redis
- Returns updated execution
#### update_node_execution_status_batch
```python
async def update_node_execution_status_batch(
execution_updates: list[NodeExecutionUpdate]
) -> list[NodeExecutionResult]
```
**Behavior**:
- Batch update multiple nodes in single transaction
- Each update can have different status/stats
- Publishes events for all updates
- Returns all updated executions
#### update_node_execution_stats
```python
async def update_node_execution_stats(
node_exec_id: str,
stats: dict[str, Any]
) -> NodeExecutionResult
```
**Behavior**:
- Updates only stats field
- Merges with existing stats
- Does not affect status
#### upsert_execution_input
```python
async def upsert_execution_input(
node_id: str,
graph_exec_id: str,
input_name: str,
input_data: Any,
node_exec_id: str | None = None
) -> tuple[str, BlockInput]
```
**Behavior**:
- Creates or updates input data
- If node_exec_id not provided, creates node execution
- Serializes input_data to JSON
- Returns (node_exec_id, input_object)
#### upsert_execution_output
```python
async def upsert_execution_output(
node_exec_id: str,
output_name: str,
output_data: Any
) -> None
```
**Behavior**:
- Creates or updates output data
- Serializes output_data to JSON
- No return value
#### get_execution_kv_data
```python
async def get_execution_kv_data(
user_id: str,
key: str
) -> Any | None
```
**Behavior**:
- User-scoped key-value storage
- Returns deserialized JSON data
- Returns None if key not found
#### set_execution_kv_data
```python
async def set_execution_kv_data(
user_id: str,
node_exec_id: str,
key: str,
data: Any
) -> Any | None
```
**Behavior**:
- Sets user-scoped key-value data
- Associates with node execution
- Serializes data to JSON
- Returns previous value or None
#### get_block_error_stats
```python
async def get_block_error_stats() -> list[BlockErrorStats]
```
**Behavior**:
- Aggregates error counts by block_id
- Last 7 days of data
- Groups by error type
### 3.2 Graph Management APIs
#### get_node
```python
async def get_node(
node_id: str
) -> AgentNode | None
```
**Behavior**:
- Returns node with block data
- No user_id check (public blocks)
#### get_graph
```python
async def get_graph(
graph_id: str,
version: int | None = None,
user_id: str | None = None,
for_export: bool = False,
include_subgraphs: bool = False
) -> GraphModel | None
```
**Behavior**:
- Returns latest version if version=None
- Checks user_id for private graphs
- for_export=True excludes internal fields
- include_subgraphs=True loads nested graphs
#### get_connected_output_nodes
```python
async def get_connected_output_nodes(
node_id: str,
output_name: str
) -> list[tuple[AgentNode, AgentNodeLink]]
```
**Behavior**:
- Returns downstream nodes connected to output
- Includes link metadata
- Used for execution flow
#### get_graph_metadata
```python
async def get_graph_metadata(
graph_id: str,
user_id: str
) -> GraphMetadata | None
```
**Behavior**:
- Returns graph metadata without full definition
- User must own or have access to graph
### 3.3 Credit System APIs
#### get_credits
```python
async def get_credits(
user_id: str
) -> int
```
**Behavior**:
- Returns current credit balance
- Always non-negative
#### spend_credits
```python
async def spend_credits(
user_id: str,
cost: int,
metadata: UsageTransactionMetadata
) -> int
```
**Behavior**:
- Deducts credits atomically
- Creates transaction record
- Throws InsufficientCredits if balance too low
- Returns new balance
- metadata includes: block_id, node_exec_id, context
### 3.4 User Management APIs
#### get_user_metadata
```python
async def get_user_metadata(
user_id: str
) -> UserMetadata
```
**Behavior**:
- Returns user preferences and settings
- Creates default if not exists
#### update_user_metadata
```python
async def update_user_metadata(
user_id: str,
data: UserMetadataDTO
) -> UserMetadata
```
**Behavior**:
- Partial update of metadata
- Validates against schema
- Returns updated metadata
#### get_user_integrations
```python
async def get_user_integrations(
user_id: str
) -> UserIntegrations
```
**Behavior**:
- Returns OAuth credentials
- Decrypts sensitive data
- Creates empty if not exists
#### update_user_integrations
```python
async def update_user_integrations(
user_id: str,
data: UserIntegrations
) -> None
```
**Behavior**:
- Updates integration credentials
- Encrypts sensitive data
- No return value
### 3.5 User Communication APIs
#### get_active_user_ids_in_timerange
```python
async def get_active_user_ids_in_timerange(
start_time: datetime,
end_time: datetime
) -> list[str]
```
**Behavior**:
- Returns users with graph executions in range
- Used for analytics/notifications
#### get_user_email_by_id
```python
async def get_user_email_by_id(
user_id: str
) -> str | None
```
**Behavior**:
- Returns user's email address
- None if user not found
#### get_user_email_verification
```python
async def get_user_email_verification(
user_id: str
) -> UserEmailVerification
```
**Behavior**:
- Returns email and verification status
- Used for notification filtering
#### get_user_notification_preference
```python
async def get_user_notification_preference(
user_id: str
) -> NotificationPreference
```
**Behavior**:
- Returns notification settings
- Creates default if not exists
### 3.6 Notification APIs
#### create_or_add_to_user_notification_batch
```python
async def create_or_add_to_user_notification_batch(
user_id: str,
notification_type: NotificationType,
notification_data: NotificationEvent
) -> UserNotificationBatchDTO
```
**Behavior**:
- Adds to existing batch or creates new
- Batches by type for efficiency
- Returns updated batch
#### empty_user_notification_batch
```python
async def empty_user_notification_batch(
user_id: str,
notification_type: NotificationType
) -> None
```
**Behavior**:
- Clears all notifications of type
- Used after sending batch
#### get_all_batches_by_type
```python
async def get_all_batches_by_type(
notification_type: NotificationType
) -> list[UserNotificationBatchDTO]
```
**Behavior**:
- Returns all user batches of type
- Used by notification service
#### get_user_notification_batch
```python
async def get_user_notification_batch(
user_id: str,
notification_type: NotificationType
) -> UserNotificationBatchDTO | None
```
**Behavior**:
- Returns user's batch for type
- None if no batch exists
#### get_user_notification_oldest_message_in_batch
```python
async def get_user_notification_oldest_message_in_batch(
user_id: str,
notification_type: NotificationType
) -> NotificationEvent | None
```
**Behavior**:
- Returns oldest notification in batch
- Used for batch timing decisions
## 4. Client Implementation Requirements
### 4.1 Synchronous Client
```python
class DatabaseManagerClient(AppServiceClient):
"""
REQUIRED: Synchronous client that:
- Converts async methods to sync using endpoint_to_sync
- Maintains exact method signatures
- Handles connection pooling
- Implements retry logic
"""
@classmethod
def get_service_type(cls):
return DatabaseManager
# Example method mapping
get_graph_execution = endpoint_to_sync(DatabaseManager.get_graph_execution)
```
### 4.2 Asynchronous Client
```python
class DatabaseManagerAsyncClient(AppServiceClient):
"""
REQUIRED: Async client that:
- Directly references async methods
- No conversion needed
- Shares connection pool
"""
@classmethod
def get_service_type(cls):
return DatabaseManager
# Direct method reference
get_graph_execution = DatabaseManager.get_graph_execution
```
## 5. Data Models
### 5.1 Core Enums
```python
class AgentExecutionStatus(str, Enum):
PENDING = "PENDING"
QUEUED = "QUEUED"
RUNNING = "RUNNING"
COMPLETED = "COMPLETED"
FAILED = "FAILED"
CANCELED = "CANCELED"
class NotificationType(str, Enum):
SYSTEM = "SYSTEM"
REVIEW = "REVIEW"
EXECUTION = "EXECUTION"
MARKETING = "MARKETING"
```
### 5.2 Key Data Models
All models must exactly match the Prisma schema definitions. Key models include:
- `GraphExecution`: Execution metadata with stats
- `GraphExecutionWithNodes`: Includes all node executions
- `NodeExecutionResult`: Node execution with I/O data
- `GraphModel`: Complete graph definition
- `UserIntegrations`: OAuth credentials
- `UsageTransactionMetadata`: Credit usage context
- `NotificationEvent`: Individual notification data
## 6. Security Requirements
### 6.1 User Isolation
- **CRITICAL**: All user-scoped operations MUST filter by user_id
- Never expose data across user boundaries
- Use database-level row security where possible
### 6.2 Authentication
- Service assumes authentication handled by API gateway
- user_id parameter is trusted after authentication
- No additional auth checks within service
### 6.3 Data Protection
- Encrypt sensitive integration credentials
- Use HMAC for unsubscribe tokens
- Never log sensitive data
## 7. Performance Requirements
### 7.1 Connection Management
- Maintain persistent database connection
- Use connection pooling (default: 10 connections)
- Implement exponential backoff for retries
### 7.2 Query Optimization
- Use indexes for all WHERE clauses
- Batch operations where possible
- Limit default result sets (50 items)
### 7.3 Event Publishing
- Publish events asynchronously
- Don't block on event delivery
- Use fire-and-forget pattern
## 8. Error Handling
### 8.1 Standard Exceptions
```python
class InsufficientCredits(Exception):
"""Raised when user lacks credits"""
class NotFoundError(Exception):
"""Raised when entity not found"""
class AuthorizationError(Exception):
"""Raised when user lacks access"""
```
### 8.2 Error Response Format
```json
{
"error": "error_type",
"message": "Human readable message",
"details": {} // Optional additional context
}
```
## 9. Testing Requirements
### 9.1 Unit Tests
- Test each method in isolation
- Mock database calls
- Verify user_id filtering
### 9.2 Integration Tests
- Test with real database
- Verify transaction boundaries
- Test concurrent operations
### 9.3 Service Tests
- Test HTTP endpoint generation
- Verify serialization/deserialization
- Test error handling
## 10. Implementation Checklist
### Phase 1: Core Service Setup
- [ ] Create DatabaseManager class inheriting from AppService
- [ ] Implement run_service() with database connection
- [ ] Implement cleanup() with proper disconnect
- [ ] Configure port from settings
- [ ] Set up method exposure helper
### Phase 2: Execution APIs (15 methods)
- [ ] get_graph_execution
- [ ] get_graph_executions
- [ ] get_graph_execution_meta
- [ ] create_graph_execution
- [ ] update_graph_execution_start_time
- [ ] update_graph_execution_stats
- [ ] get_node_execution
- [ ] get_node_executions
- [ ] get_latest_node_execution
- [ ] update_node_execution_status
- [ ] update_node_execution_status_batch
- [ ] update_node_execution_stats
- [ ] upsert_execution_input
- [ ] upsert_execution_output
- [ ] get_execution_kv_data
- [ ] set_execution_kv_data
- [ ] get_block_error_stats
### Phase 3: Graph APIs (4 methods)
- [ ] get_node
- [ ] get_graph
- [ ] get_connected_output_nodes
- [ ] get_graph_metadata
### Phase 4: Credit APIs (2 methods)
- [ ] get_credits
- [ ] spend_credits
### Phase 5: User APIs (4 methods)
- [ ] get_user_metadata
- [ ] update_user_metadata
- [ ] get_user_integrations
- [ ] update_user_integrations
### Phase 6: Communication APIs (4 methods)
- [ ] get_active_user_ids_in_timerange
- [ ] get_user_email_by_id
- [ ] get_user_email_verification
- [ ] get_user_notification_preference
### Phase 7: Notification APIs (5 methods)
- [ ] create_or_add_to_user_notification_batch
- [ ] empty_user_notification_batch
- [ ] get_all_batches_by_type
- [ ] get_user_notification_batch
- [ ] get_user_notification_oldest_message_in_batch
### Phase 8: Client Implementation
- [ ] Create DatabaseManagerClient with sync methods
- [ ] Create DatabaseManagerAsyncClient with async methods
- [ ] Test client method generation
- [ ] Verify type preservation
### Phase 9: Integration Testing
- [ ] Test all methods with real database
- [ ] Verify user isolation
- [ ] Test error scenarios
- [ ] Performance testing
- [ ] Event publishing verification
### Phase 10: Deployment Validation
- [ ] Deploy to test environment
- [ ] Run integration test suite
- [ ] Verify backward compatibility
- [ ] Performance benchmarking
- [ ] Production deployment
## 11. Success Criteria
The implementation is successful when:
1. **All 40+ methods** produce identical outputs to the original
2. **Performance** is within 10% of original implementation
3. **All tests** pass without modification
4. **No breaking changes** to any client code
5. **Security boundaries** are maintained
6. **Event publishing** works identically
7. **Error handling** matches original behavior
## 12. Critical Implementation Notes
1. **DO NOT** modify any function signatures
2. **DO NOT** change any return types
3. **DO NOT** add new required parameters
4. **DO NOT** remove any functionality
5. **ALWAYS** maintain user_id isolation
6. **ALWAYS** publish events for state changes
7. **ALWAYS** use transactions for multi-step operations
8. **ALWAYS** handle errors exactly as original
This specification, when implemented correctly, will produce a drop-in replacement for the DatabaseManager that maintains 100% compatibility with the existing system.

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# Notification Service Technical Specification
## Overview
The AutoGPT Platform Notification Service is a RabbitMQ-based asynchronous notification system that handles various types of user notifications including real-time alerts, batched notifications, and scheduled summaries. The service supports email delivery via Postmark and system alerts via Discord.
## Architecture Overview
### Core Components
1. **NotificationManager Service** (`notifications.py`)
- AppService implementation with RabbitMQ integration
- Processes notification queues asynchronously
- Manages batching strategies and delivery timing
- Handles email templating and sending
2. **RabbitMQ Message Broker**
- Multiple queues for different notification strategies
- Dead letter exchange for failed messages
- Topic-based routing for message distribution
3. **Email Sender** (`email.py`)
- Postmark integration for email delivery
- Jinja2 template rendering
- HTML email composition with unsubscribe headers
4. **Database Storage**
- Notification batching tables
- User preference storage
- Email verification tracking
## Service Exposure Mechanism
### AppService Framework
The NotificationManager extends `AppService` which automatically exposes methods decorated with `@expose` as HTTP endpoints:
```python
class NotificationManager(AppService):
@expose
def queue_weekly_summary(self):
# Implementation
@expose
def process_existing_batches(self, notification_types: list[NotificationType]):
# Implementation
@expose
async def discord_system_alert(self, content: str):
# Implementation
```
### Automatic HTTP Endpoint Creation
When the service starts, the AppService base class:
1. Scans for methods with `@expose` decorator
2. Creates FastAPI routes for each exposed method:
- Route path: `/{method_name}`
- HTTP method: POST
- Endpoint handler: Generated via `_create_fastapi_endpoint()`
### Service Client Access
#### NotificationManagerClient
```python
class NotificationManagerClient(AppServiceClient):
@classmethod
def get_service_type(cls):
return NotificationManager
# Direct method references (sync)
process_existing_batches = NotificationManager.process_existing_batches
queue_weekly_summary = NotificationManager.queue_weekly_summary
# Async-to-sync conversion
discord_system_alert = endpoint_to_sync(NotificationManager.discord_system_alert)
```
#### Client Usage Pattern
```python
# Get client instance
client = get_service_client(NotificationManagerClient)
# Call exposed methods via HTTP
client.process_existing_batches([NotificationType.AGENT_RUN])
client.queue_weekly_summary()
client.discord_system_alert("System alert message")
```
### HTTP Communication Details
1. **Service URL**: `http://{host}:{notification_service_port}`
- Default port: 8007
- Host: Configurable via settings
2. **Request Format**:
- Method: POST
- Path: `/{method_name}`
- Body: JSON with method parameters
3. **Client Implementation**:
- Uses `httpx` for HTTP requests
- Automatic retry on connection failures
- Configurable timeout (default from api_call_timeout)
### Direct Function Calls
The service also exposes two functions that can be called directly without going through the service client:
```python
# Sync version - used by ExecutionManager
def queue_notification(event: NotificationEventModel) -> NotificationResult
# Async version - used by credit system
async def queue_notification_async(event: NotificationEventModel) -> NotificationResult
```
These functions:
- Connect directly to RabbitMQ
- Publish messages to appropriate queues
- Return success/failure status
- Are NOT exposed via HTTP
## Message Queuing Architecture
### RabbitMQ Configuration
#### Exchanges
```python
NOTIFICATION_EXCHANGE = Exchange(name="notifications", type=ExchangeType.TOPIC)
DEAD_LETTER_EXCHANGE = Exchange(name="dead_letter", type=ExchangeType.TOPIC)
```
#### Queues
1. **immediate_notifications**
- Routing Key: `notification.immediate.#`
- Dead Letter: `failed.immediate`
- For: Critical alerts, errors
2. **admin_notifications**
- Routing Key: `notification.admin.#`
- Dead Letter: `failed.admin`
- For: Refund requests, system alerts
3. **summary_notifications**
- Routing Key: `notification.summary.#`
- Dead Letter: `failed.summary`
- For: Daily/weekly summaries
4. **batch_notifications**
- Routing Key: `notification.batch.#`
- Dead Letter: `failed.batch`
- For: Agent runs, batched events
5. **failed_notifications**
- Routing Key: `failed.#`
- For: All failed messages
### Queue Strategies (QueueType enum)
1. **IMMEDIATE**: Send right away (errors, critical notifications)
2. **BATCH**: Batch for configured delay (agent runs)
3. **SUMMARY**: Scheduled digest (daily/weekly summaries)
4. **BACKOFF**: Exponential backoff strategy (defined but not fully implemented)
5. **ADMIN**: Admin-only notifications
## Notification Types
### Enum Values (NotificationType)
```python
AGENT_RUN # Batch strategy, 1 day delay
ZERO_BALANCE # Backoff strategy, 60 min delay
LOW_BALANCE # Immediate strategy
BLOCK_EXECUTION_FAILED # Backoff strategy, 60 min delay
CONTINUOUS_AGENT_ERROR # Backoff strategy, 60 min delay
DAILY_SUMMARY # Summary strategy
WEEKLY_SUMMARY # Summary strategy
MONTHLY_SUMMARY # Summary strategy
REFUND_REQUEST # Admin strategy
REFUND_PROCESSED # Admin strategy
```
## Integration Points
### 1. Scheduler Integration
The scheduler service (`backend.executor.scheduler`) imports monitoring functions that call the NotificationManagerClient:
```python
from backend.monitoring import (
process_existing_batches,
process_weekly_summary,
)
# These are scheduled as cron jobs
```
### 2. Execution Manager Integration
The ExecutionManager directly calls `queue_notification()` for:
- Agent run completions
- Low balance alerts
```python
from backend.notifications.notifications import queue_notification
# Called after graph execution completes
queue_notification(NotificationEventModel(
user_id=graph_exec.user_id,
type=NotificationType.AGENT_RUN,
data=AgentRunData(...)
))
```
### 3. Credit System Integration
The credit system uses `queue_notification_async()` for:
- Refund requests
- Refund processed notifications
```python
from backend.notifications.notifications import queue_notification_async
await queue_notification_async(NotificationEventModel(
user_id=user_id,
type=NotificationType.REFUND_REQUEST,
data=RefundRequestData(...)
))
```
### 4. Monitoring Module Wrappers
The monitoring module provides wrapper functions that are used by the scheduler:
```python
# backend/monitoring/notification_monitor.py
def process_existing_batches(**kwargs):
args = NotificationJobArgs(**kwargs)
get_notification_manager_client().process_existing_batches(
args.notification_types
)
def process_weekly_summary(**kwargs):
get_notification_manager_client().queue_weekly_summary()
```
## Data Models
### Base Event Model
```typescript
interface BaseEventModel {
type: NotificationType;
user_id: string;
created_at: string; // ISO datetime with timezone
}
```
### Notification Event Model
```typescript
interface NotificationEventModel<T> extends BaseEventModel {
data: T;
}
```
### Notification Data Types
#### AgentRunData
```typescript
interface AgentRunData {
agent_name: string;
credits_used: number;
execution_time: number;
node_count: number;
graph_id: string;
outputs: Array<Record<string, any>>;
}
```
#### ZeroBalanceData
```typescript
interface ZeroBalanceData {
last_transaction: number;
last_transaction_time: string; // ISO datetime with timezone
top_up_link: string;
}
```
#### LowBalanceData
```typescript
interface LowBalanceData {
agent_name: string;
current_balance: number; // credits (100 = $1)
billing_page_link: string;
shortfall: number;
}
```
#### BlockExecutionFailedData
```typescript
interface BlockExecutionFailedData {
block_name: string;
block_id: string;
error_message: string;
graph_id: string;
node_id: string;
execution_id: string;
}
```
#### ContinuousAgentErrorData
```typescript
interface ContinuousAgentErrorData {
agent_name: string;
error_message: string;
graph_id: string;
execution_id: string;
start_time: string; // ISO datetime with timezone
error_time: string; // ISO datetime with timezone
attempts: number;
}
```
#### Summary Data Types
```typescript
interface BaseSummaryData {
total_credits_used: number;
total_executions: number;
most_used_agent: string;
total_execution_time: number;
successful_runs: number;
failed_runs: number;
average_execution_time: number;
cost_breakdown: Record<string, number>;
}
interface DailySummaryData extends BaseSummaryData {
date: string; // ISO datetime with timezone
}
interface WeeklySummaryData extends BaseSummaryData {
start_date: string; // ISO datetime with timezone
end_date: string; // ISO datetime with timezone
}
```
#### RefundRequestData
```typescript
interface RefundRequestData {
user_id: string;
user_name: string;
user_email: string;
transaction_id: string;
refund_request_id: string;
reason: string;
amount: number;
balance: number;
}
```
### Summary Parameters
```typescript
interface BaseSummaryParams {
start_date: string; // ISO datetime with timezone
end_date: string; // ISO datetime with timezone
}
interface DailySummaryParams extends BaseSummaryParams {
date: string; // ISO datetime with timezone
}
interface WeeklySummaryParams extends BaseSummaryParams {
start_date: string; // ISO datetime with timezone
end_date: string; // ISO datetime with timezone
}
```
## Database Schema
### NotificationEvent Table
```sql
model NotificationEvent {
id String @id @default(uuid())
createdAt DateTime @default(now())
updatedAt DateTime @default(now()) @updatedAt
UserNotificationBatch UserNotificationBatch? @relation
userNotificationBatchId String?
type NotificationType
data Json
@@index([userNotificationBatchId])
}
```
### UserNotificationBatch Table
```sql
model UserNotificationBatch {
id String @id @default(uuid())
createdAt DateTime @default(now())
updatedAt DateTime @default(now()) @updatedAt
userId String
User User @relation
type NotificationType
Notifications NotificationEvent[]
@@unique([userId, type])
}
```
## API Methods
### Exposed Service Methods (via HTTP)
#### queue_weekly_summary()
- **HTTP Endpoint**: `POST /queue_weekly_summary`
- **Purpose**: Triggers weekly summary generation for all active users
- **Process**:
1. Runs in background executor
2. Queries users active in last 7 days
3. Queues summary notification for each user
- **Used by**: Scheduler service (via cron)
#### process_existing_batches(notification_types: list[NotificationType])
- **HTTP Endpoint**: `POST /process_existing_batches`
- **Purpose**: Processes aged-out batches for specified notification types
- **Process**:
1. Runs in background executor
2. Retrieves all batches for given types
3. Checks if oldest message exceeds max delay
4. Sends batched email if aged out
5. Clears processed batches
- **Used by**: Scheduler service (via cron)
#### discord_system_alert(content: str)
- **HTTP Endpoint**: `POST /discord_system_alert`
- **Purpose**: Sends system alerts to Discord channel
- **Async**: Yes (converted to sync by client)
- **Used by**: Monitoring services
### Direct Queue Functions (not via HTTP)
#### queue_notification(event: NotificationEventModel) -> NotificationResult
- **Purpose**: Queue a notification (sync version)
- **Used by**: ExecutionManager (same process)
- **Direct RabbitMQ**: Yes
#### queue_notification_async(event: NotificationEventModel) -> NotificationResult
- **Purpose**: Queue a notification (async version)
- **Used by**: Credit system (async context)
- **Direct RabbitMQ**: Yes
## Message Processing Flow
### 1. Message Routing
```python
def get_routing_key(event_type: NotificationType) -> str:
strategy = NotificationTypeOverride(event_type).strategy
if strategy == QueueType.IMMEDIATE:
return f"notification.immediate.{event_type.value}"
elif strategy == QueueType.BATCH:
return f"notification.batch.{event_type.value}"
# ... etc
```
### 2. Queue Processing Methods
#### _process_immediate(message: str) -> bool
1. Parse message to NotificationEventModel
2. Retrieve user email
3. Check user preferences and email verification
4. Send email immediately via EmailSender
5. Return True if successful
#### _process_batch(message: str) -> bool
1. Parse message to NotificationEventModel
2. Add to user's notification batch
3. Check if batch is old enough (based on delay)
4. If aged out:
- Retrieve all batch messages
- Send combined email
- Clear batch
5. Return True if processed or batched
#### _process_summary(message: str) -> bool
1. Parse message to SummaryParamsEventModel
2. Gather summary data (credits, executions, etc.)
- **Note**: Currently returns hardcoded placeholder data
3. Format and send summary email
4. Return True if successful
#### _process_admin_message(message: str) -> bool
1. Parse message
2. Send to configured admin email
3. No user preference checks
4. Return True if successful
## Email Delivery
### EmailSender Class
#### Template Loading
- Base template: `templates/base.html.jinja2`
- Notification templates: `templates/{notification_type}.html.jinja2`
- Subject templates from NotificationTypeOverride
- **Note**: Templates use `.html.jinja2` extension, not just `.html`
#### Email Composition
```python
def send_templated(
notification: NotificationType,
user_email: str,
data: NotificationEventModel | list[NotificationEventModel],
user_unsub_link: str | None = None
)
```
#### Postmark Integration
- API Token: `settings.secrets.postmark_server_api_token`
- Sender Email: `settings.config.postmark_sender_email`
- Headers:
- `List-Unsubscribe-Post: List-Unsubscribe=One-Click`
- `List-Unsubscribe: <{unsubscribe_link}>`
## User Preferences and Permissions
### Email Verification Check
```python
validated_email = get_db().get_user_email_verification(user_id)
```
### Notification Preferences
```python
preferences = get_db().get_user_notification_preference(user_id).preferences
# Returns dict[NotificationType, bool]
```
### Preference Fields in User Model
- `notifyOnAgentRun`
- `notifyOnZeroBalance`
- `notifyOnLowBalance`
- `notifyOnBlockExecutionFailed`
- `notifyOnContinuousAgentError`
- `notifyOnDailySummary`
- `notifyOnWeeklySummary`
- `notifyOnMonthlySummary`
### Unsubscribe Link Generation
```python
def generate_unsubscribe_link(user_id: str) -> str:
# HMAC-SHA256 signed token
# Format: base64(user_id:signature_hex)
# URL: {platform_base_url}/api/email/unsubscribe?token={token}
```
## Batching Logic
### Batch Delays (get_batch_delay)
**Note**: The delay configuration exists for multiple notification types, but only notifications with `QueueType.BATCH` strategy actually use batching. Others use different strategies:
- `AGENT_RUN`: 1 day (Strategy: BATCH - actually uses batching)
- `ZERO_BALANCE`: 60 minutes configured (Strategy: BACKOFF - not batched)
- `LOW_BALANCE`: 60 minutes configured (Strategy: IMMEDIATE - sent immediately)
- `BLOCK_EXECUTION_FAILED`: 60 minutes configured (Strategy: BACKOFF - not batched)
- `CONTINUOUS_AGENT_ERROR`: 60 minutes configured (Strategy: BACKOFF - not batched)
### Batch Processing
1. Messages added to UserNotificationBatch
2. Oldest message timestamp tracked
3. When `oldest_timestamp + delay < now()`:
- Batch is processed
- All messages sent in single email
- Batch cleared
## Service Lifecycle
### Startup
1. Initialize FastAPI app with exposed endpoints
2. Start HTTP server on port 8007
3. Initialize RabbitMQ connection
4. Create/verify exchanges and queues
5. Set up queue consumers
6. Start processing loop
### Main Loop
```python
while self.running:
await self._run_queue(immediate_queue, self._process_immediate, ...)
await self._run_queue(admin_queue, self._process_admin_message, ...)
await self._run_queue(batch_queue, self._process_batch, ...)
await self._run_queue(summary_queue, self._process_summary, ...)
await asyncio.sleep(0.1)
```
### Shutdown
1. Set `running = False`
2. Disconnect RabbitMQ
3. Cleanup resources
## Configuration
### Environment Variables
```python
# Service Configuration
notification_service_port: int = 8007
# Email Configuration
postmark_sender_email: str = "invalid@invalid.com"
refund_notification_email: str = "refund@agpt.co"
# Security
unsubscribe_secret_key: str = ""
# Secrets
postmark_server_api_token: str = ""
postmark_webhook_token: str = ""
discord_bot_token: str = ""
# Platform URLs
platform_base_url: str
frontend_base_url: str
```
## Error Handling
### Message Processing Errors
- Failed messages sent to dead letter queue
- Validation errors logged but don't crash service
- Connection errors trigger retry with `@continuous_retry()`
### RabbitMQ ACK/NACK Protocol
- Success: `message.ack()`
- Failure: `message.reject(requeue=False)`
- Timeout/Queue empty: Continue loop
### HTTP Endpoint Errors
- Wrapped in RemoteCallError for client
- Automatic retry available via client configuration
- Connection failures tracked and logged
## System Integrations
### DatabaseManagerClient
- User email retrieval
- Email verification status
- Notification preferences
- Batch management
- Active user queries
### Discord Integration
- Uses SendDiscordMessageBlock
- Configured via discord_bot_token
- For system alerts only
## Implementation Checklist
1. **Core Service**
- [ ] AppService implementation with @expose decorators
- [ ] FastAPI endpoint generation
- [ ] RabbitMQ connection management
- [ ] Queue consumer setup
- [ ] Message routing logic
2. **Service Client**
- [ ] NotificationManagerClient implementation
- [ ] HTTP client configuration
- [ ] Method mapping to service endpoints
- [ ] Async-to-sync conversions
3. **Message Processing**
- [ ] Parse and validate all notification types
- [ ] Implement all queue strategies
- [ ] Batch management with delays
- [ ] Summary data gathering
4. **Email Delivery**
- [ ] Postmark integration
- [ ] Template loading and rendering
- [ ] Unsubscribe header support
- [ ] HTML email composition
5. **User Management**
- [ ] Preference checking
- [ ] Email verification
- [ ] Unsubscribe link generation
- [ ] Daily limit tracking
6. **Batching System**
- [ ] Database batch operations
- [ ] Age-out checking
- [ ] Batch clearing after send
- [ ] Oldest message tracking
7. **Error Handling**
- [ ] Dead letter queue routing
- [ ] Message rejection on failure
- [ ] Continuous retry wrapper
- [ ] Validation error logging
8. **Scheduled Operations**
- [ ] Weekly summary generation
- [ ] Batch processing triggers
- [ ] Background executor usage
## Security Considerations
1. **Service-to-Service Communication**:
- HTTP endpoints only accessible internally
- No authentication on service endpoints (internal network only)
- Service discovery via host/port configuration
2. **User Security**:
- Email verification required for all user notifications
- Unsubscribe tokens HMAC-signed
- User preferences enforced
3. **Admin Notifications**:
- Separate queue, no user preference checks
- Fixed admin email configuration
## Testing Considerations
1. **Unit Tests**
- Message parsing and validation
- Routing key generation
- Batch delay calculations
- Template rendering
2. **Integration Tests**
- HTTP endpoint accessibility
- Service client method calls
- RabbitMQ message flow
- Database batch operations
- Email sending (mock Postmark)
3. **Load Tests**
- High volume message processing
- Concurrent HTTP requests
- Batch accumulation limits
- Memory usage under load
## Implementation Status Notes
1. **Backoff Strategy**: While `QueueType.BACKOFF` is defined and used by several notification types (ZERO_BALANCE, BLOCK_EXECUTION_FAILED, CONTINUOUS_AGENT_ERROR), the actual exponential backoff processing logic is not implemented. These messages are routed to immediate queue.
2. **Summary Data**: The `_gather_summary_data()` method currently returns hardcoded placeholder values rather than querying actual execution data from the database.
3. **Batch Processing**: Only `AGENT_RUN` notifications actually use batch processing. Other notification types with configured delays use different strategies (IMMEDIATE or BACKOFF).
## Future Enhancements
1. **Additional Channels**
- SMS notifications (not implemented)
- Webhook notifications (not implemented)
- In-app notifications
2. **Advanced Batching**
- Dynamic batch sizes
- Priority-based processing
- Custom delay configurations
3. **Analytics**
- Delivery tracking
- Open/click rates
- Notification effectiveness metrics
4. **Service Improvements**
- Authentication for HTTP endpoints
- Rate limiting per user
- Circuit breaker patterns
- Implement actual backoff processing for BACKOFF strategy
- Implement real summary data gathering

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# AutoGPT Platform Scheduler Technical Specification
## Executive Summary
This document provides a comprehensive technical specification for the AutoGPT Platform Scheduler service. The scheduler is responsible for managing scheduled graph executions, system monitoring tasks, and periodic maintenance operations. This specification is designed to enable a complete reimplementation that maintains 100% compatibility with the existing system.
## Table of Contents
1. [System Architecture](#system-architecture)
2. [Service Implementation](#service-implementation)
3. [Data Models](#data-models)
4. [API Endpoints](#api-endpoints)
5. [Database Schema](#database-schema)
6. [External Dependencies](#external-dependencies)
7. [Authentication & Authorization](#authentication--authorization)
8. [Process Management](#process-management)
9. [Error Handling](#error-handling)
10. [Configuration](#configuration)
11. [Testing Strategy](#testing-strategy)
## System Architecture
### Overview
The scheduler operates as an independent microservice within the AutoGPT platform, implementing the `AppService` base class pattern. It runs on a dedicated port (default: 8003) and exposes HTTP/JSON-RPC endpoints for communication with other services.
### Core Components
1. **Scheduler Service** (`backend/executor/scheduler.py:156`)
- Extends `AppService` base class
- Manages APScheduler instance with multiple jobstores
- Handles lifecycle management and graceful shutdown
2. **Scheduler Client** (`backend/executor/scheduler.py:354`)
- Extends `AppServiceClient` base class
- Provides async/sync method wrappers for RPC calls
- Implements automatic retry and connection pooling
3. **Entry Points**
- Main executable: `backend/scheduler.py`
- Service launcher: `backend/app.py`
## Service Implementation
### Base Service Pattern
```python
class Scheduler(AppService):
scheduler: BlockingScheduler
def __init__(self, register_system_tasks: bool = True):
self.register_system_tasks = register_system_tasks
@classmethod
def get_port(cls) -> int:
return config.execution_scheduler_port # Default: 8003
@classmethod
def db_pool_size(cls) -> int:
return config.scheduler_db_pool_size # Default: 3
def run_service(self):
# Initialize scheduler with jobstores
# Register system tasks if enabled
# Start scheduler blocking loop
def cleanup(self):
# Graceful shutdown of scheduler
# Wait=False for immediate termination
```
### Jobstore Configuration
The scheduler uses three distinct jobstores:
1. **EXECUTION** (`Jobstores.EXECUTION.value`)
- Type: SQLAlchemyJobStore
- Table: `apscheduler_jobs`
- Purpose: Graph execution schedules
- Persistence: Required
2. **BATCHED_NOTIFICATIONS** (`Jobstores.BATCHED_NOTIFICATIONS.value`)
- Type: SQLAlchemyJobStore
- Table: `apscheduler_jobs_batched_notifications`
- Purpose: Batched notification processing
- Persistence: Required
3. **WEEKLY_NOTIFICATIONS** (`Jobstores.WEEKLY_NOTIFICATIONS.value`)
- Type: MemoryJobStore
- Purpose: Weekly summary notifications
- Persistence: Not required
### System Tasks
When `register_system_tasks=True`, the following monitoring tasks are registered:
1. **Weekly Summary Processing**
- Job ID: `process_weekly_summary`
- Schedule: `0 * * * *` (hourly)
- Function: `monitoring.process_weekly_summary`
- Jobstore: WEEKLY_NOTIFICATIONS
2. **Late Execution Monitoring**
- Job ID: `report_late_executions`
- Schedule: Interval (config.execution_late_notification_threshold_secs)
- Function: `monitoring.report_late_executions`
- Jobstore: EXECUTION
3. **Block Error Rate Monitoring**
- Job ID: `report_block_error_rates`
- Schedule: Interval (config.block_error_rate_check_interval_secs)
- Function: `monitoring.report_block_error_rates`
- Jobstore: EXECUTION
4. **Cloud Storage Cleanup**
- Job ID: `cleanup_expired_files`
- Schedule: Interval (config.cloud_storage_cleanup_interval_hours * 3600)
- Function: `cleanup_expired_files`
- Jobstore: EXECUTION
## Data Models
### GraphExecutionJobArgs
```python
class GraphExecutionJobArgs(BaseModel):
user_id: str
graph_id: str
graph_version: int
cron: str
input_data: BlockInput
input_credentials: dict[str, CredentialsMetaInput] = Field(default_factory=dict)
```
### GraphExecutionJobInfo
```python
class GraphExecutionJobInfo(GraphExecutionJobArgs):
id: str
name: str
next_run_time: str
@staticmethod
def from_db(job_args: GraphExecutionJobArgs, job_obj: JobObj) -> "GraphExecutionJobInfo":
return GraphExecutionJobInfo(
id=job_obj.id,
name=job_obj.name,
next_run_time=job_obj.next_run_time.isoformat(),
**job_args.model_dump(),
)
```
### NotificationJobArgs
```python
class NotificationJobArgs(BaseModel):
notification_types: list[NotificationType]
cron: str
```
### CredentialsMetaInput
```python
class CredentialsMetaInput(BaseModel, Generic[CP, CT]):
id: str
title: Optional[str] = None
provider: CP
type: CT
```
## API Endpoints
All endpoints are exposed via the `@expose` decorator and follow HTTP POST JSON-RPC pattern.
### 1. Add Graph Execution Schedule
**Endpoint**: `/add_graph_execution_schedule`
**Request Body**:
```json
{
"user_id": "string",
"graph_id": "string",
"graph_version": "integer",
"cron": "string (crontab format)",
"input_data": {},
"input_credentials": {},
"name": "string (optional)"
}
```
**Response**: `GraphExecutionJobInfo`
**Behavior**:
- Creates APScheduler job with CronTrigger
- Uses job kwargs to store GraphExecutionJobArgs
- Sets `replace_existing=True` to allow updates
- Returns job info with generated ID and next run time
### 2. Delete Graph Execution Schedule
**Endpoint**: `/delete_graph_execution_schedule`
**Request Body**:
```json
{
"schedule_id": "string",
"user_id": "string"
}
```
**Response**: `GraphExecutionJobInfo`
**Behavior**:
- Validates schedule exists in EXECUTION jobstore
- Verifies user_id matches job's user_id
- Removes job from scheduler
- Returns deleted job info
**Errors**:
- `NotFoundError`: If job doesn't exist
- `NotAuthorizedError`: If user_id doesn't match
### 3. Get Graph Execution Schedules
**Endpoint**: `/get_graph_execution_schedules`
**Request Body**:
```json
{
"graph_id": "string (optional)",
"user_id": "string (optional)"
}
```
**Response**: `list[GraphExecutionJobInfo]`
**Behavior**:
- Retrieves all jobs from EXECUTION jobstore
- Filters by graph_id and/or user_id if provided
- Validates job kwargs as GraphExecutionJobArgs
- Skips invalid jobs (ValidationError)
- Only returns jobs with next_run_time set
### 4. System Task Endpoints
- `/execute_process_existing_batches` - Trigger batch processing
- `/execute_process_weekly_summary` - Trigger weekly summary
- `/execute_report_late_executions` - Trigger late execution report
- `/execute_report_block_error_rates` - Trigger error rate report
- `/execute_cleanup_expired_files` - Trigger file cleanup
### 5. Health Check
**Endpoints**: `/health_check`, `/health_check_async`
**Methods**: POST, GET
**Response**: "OK"
## Database Schema
### APScheduler Tables
The scheduler relies on APScheduler's SQLAlchemy jobstore schema:
1. **apscheduler_jobs**
- id: VARCHAR (PRIMARY KEY)
- next_run_time: FLOAT
- job_state: BLOB/BYTEA (pickled job data)
2. **apscheduler_jobs_batched_notifications**
- Same schema as above
- Separate table for notification jobs
### Database Configuration
- URL extraction from `DIRECT_URL` environment variable
- Schema extraction from URL query parameter
- Connection pooling: `pool_size=db_pool_size()`, `max_overflow=0`
- Metadata schema binding for multi-schema support
## External Dependencies
### Required Services
1. **PostgreSQL Database**
- Connection via `DIRECT_URL` environment variable
- Schema support via URL parameter
- APScheduler job persistence
2. **ExecutionManager** (via execution_utils)
- Function: `add_graph_execution`
- Called by: `execute_graph` job function
- Purpose: Create graph execution entries
3. **NotificationManager** (via monitoring module)
- Functions: `process_existing_batches`, `queue_weekly_summary`
- Purpose: Notification processing
4. **Cloud Storage** (via util.cloud_storage)
- Function: `cleanup_expired_files_async`
- Purpose: File expiration management
### Python Dependencies
```
apscheduler>=3.10.0
sqlalchemy
pydantic>=2.0
httpx
uvicorn
fastapi
python-dotenv
tenacity
```
## Authentication & Authorization
### Service-Level Authentication
- No authentication required between internal services
- Services communicate via trusted internal network
- Host/port configuration via environment variables
### User-Level Authorization
- Authorization check in `delete_graph_execution_schedule`:
- Validates `user_id` matches job's `user_id`
- Raises `NotAuthorizedError` on mismatch
- No authorization for read operations (security consideration)
## Process Management
### Startup Sequence
1. Load environment variables via `dotenv.load_dotenv()`
2. Extract database URL and schema
3. Initialize BlockingScheduler with configured jobstores
4. Register system tasks (if enabled)
5. Add job execution listener
6. Start scheduler (blocking)
### Shutdown Sequence
1. Receive SIGTERM/SIGINT signal
2. Call `cleanup()` method
3. Shutdown scheduler with `wait=False`
4. Terminate process
### Multi-Process Architecture
- Runs as independent process via `AppProcess`
- Started by `run_processes()` in app.py
- Can run in foreground or background mode
- Automatic signal handling for graceful shutdown
## Error Handling
### Job Execution Errors
- Listener on `EVENT_JOB_ERROR` logs failures
- Errors in job functions are caught and logged
- Jobs continue to run on schedule despite failures
### RPC Communication Errors
- Automatic retry via `@conn_retry` decorator
- Configurable retry count and timeout
- Connection pooling with self-healing
### Database Connection Errors
- APScheduler handles reconnection automatically
- Pool exhaustion prevented by `max_overflow=0`
- Connection errors logged but don't crash service
## Configuration
### Environment Variables
- `DIRECT_URL`: PostgreSQL connection string (required)
- `{SERVICE_NAME}_HOST`: Override service host
- Standard logging configuration
### Config Settings (via Config class)
```python
execution_scheduler_port: int = 8003
scheduler_db_pool_size: int = 3
execution_late_notification_threshold_secs: int
block_error_rate_check_interval_secs: int
cloud_storage_cleanup_interval_hours: int
pyro_host: str = "localhost"
pyro_client_comm_timeout: float = 15
pyro_client_comm_retry: int = 3
rpc_client_call_timeout: int = 300
```
## Testing Strategy
### Unit Tests
1. Mock APScheduler for job management tests
2. Mock database connections
3. Test each RPC endpoint independently
4. Verify job serialization/deserialization
### Integration Tests
1. Test with real PostgreSQL instance
2. Verify job persistence across restarts
3. Test concurrent job execution
4. Validate cron expression parsing
### Critical Test Cases
1. **Job Persistence**: Jobs survive scheduler restart
2. **User Isolation**: Users can only delete their own jobs
3. **Concurrent Access**: Multiple clients can add/remove jobs
4. **Error Recovery**: Service recovers from database outages
5. **Resource Cleanup**: No memory/connection leaks
## Implementation Notes
### Key Design Decisions
1. **BlockingScheduler vs AsyncIOScheduler**: Uses BlockingScheduler for simplicity and compatibility with multiprocessing architecture
2. **Job Storage**: All job arguments stored in kwargs, not in job name/id
3. **Separate Jobstores**: Isolation between execution and notification jobs
4. **No Authentication**: Relies on network isolation for security
### Migration Considerations
1. APScheduler job format must be preserved exactly
2. Database schema cannot change without migration
3. RPC protocol must maintain compatibility
4. Environment variables must match existing deployment
### Performance Considerations
1. Database pool size limited to prevent exhaustion
2. No job result storage (fire-and-forget pattern)
3. Minimal logging in hot paths
4. Connection reuse via pooling
## Appendix: Critical Implementation Details
### Event Loop Management
```python
@thread_cached
def get_event_loop():
return asyncio.new_event_loop()
def execute_graph(**kwargs):
get_event_loop().run_until_complete(_execute_graph(**kwargs))
```
### Job Function Execution Context
- Jobs run in scheduler's process space
- Each job gets fresh event loop
- No shared state between job executions
- Exceptions logged but don't affect scheduler
### Cron Expression Format
- Uses standard crontab format via `CronTrigger.from_crontab()`
- Supports: minute hour day month day_of_week
- Special strings: @yearly, @monthly, @weekly, @daily, @hourly
This specification provides all necessary details to reimplement the scheduler service while maintaining 100% compatibility with the existing system. Any deviation from these specifications may result in system incompatibility.

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name: CI
on:
push:
branches: [ main, master ]
pull_request:
branches: [ main, master ]
env:
CARGO_TERM_COLOR: always
RUSTFLAGS: "-D warnings"
jobs:
test:
name: Test
runs-on: ubuntu-latest
services:
redis:
image: redis:7
options: >-
--health-cmd "redis-cli ping"
--health-interval 10s
--health-timeout 5s
--health-retries 5
ports:
- 6379:6379
steps:
- uses: actions/checkout@v3
- uses: dtolnay/rust-toolchain@stable
- uses: Swatinem/rust-cache@v2
- name: Run tests
run: cargo test
env:
REDIS_URL: redis://localhost:6379
clippy:
name: Clippy
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: dtolnay/rust-toolchain@stable
with:
components: clippy
- uses: Swatinem/rust-cache@v2
- name: Run clippy
run: |
cargo clippy -- \
-D warnings \
-D clippy::unwrap_used \
-D clippy::panic \
-D clippy::unimplemented \
-D clippy::todo
fmt:
name: Format
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: dtolnay/rust-toolchain@stable
with:
components: rustfmt
- name: Check formatting
run: cargo fmt -- --check
bench:
name: Benchmarks
runs-on: ubuntu-latest
services:
redis:
image: redis:7
options: >-
--health-cmd "redis-cli ping"
--health-interval 10s
--health-timeout 5s
--health-retries 5
ports:
- 6379:6379
steps:
- uses: actions/checkout@v3
- uses: dtolnay/rust-toolchain@stable
- uses: Swatinem/rust-cache@v2
- name: Build benchmarks
run: cargo bench --no-run
env:
REDIS_URL: redis://localhost:6379

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[package]
name = "websocket"
authors = ["AutoGPT Team"]
description = "WebSocket server for AutoGPT Platform"
version = "0.1.0"
edition = "2021"
[lib]
name = "websocket"
path = "src/lib.rs"
[[bin]]
name = "websocket"
path = "src/main.rs"
[dependencies]
axum = { version = "0.7.5", features = ["ws"] }
jsonwebtoken = "9.3.0"
redis = { version = "0.25.4", features = ["aio", "tokio-comp"] }
serde = { version = "1.0.204", features = ["derive"] }
serde_json = "1.0.120"
tokio = { version = "1.38.1", features = ["rt-multi-thread", "macros", "net", "sync", "time", "io-util"] }
tower-http = { version = "0.5.2", features = ["cors"] }
tracing = "0.1"
tracing-subscriber = { version = "0.3", features = ["env-filter"] }
futures = "0.3"
dotenvy = "0.15"
clap = { version = "4.5.4", features = ["derive"] }
toml = "0.8"
[dev-dependencies]
# Load testing and profiling
tokio-console = "0.1"
criterion = { version = "0.5", features = ["async_tokio"] }
pprof = { version = "0.13", features = ["flamegraph", "criterion"] }
# Dependencies for benchmarks
tokio-tungstenite = "0.24"
futures-util = "0.3"
chrono = "0.4"
[[bench]]
name = "websocket_bench"
harness = false
[[example]]
name = "ws_client_example"
required-features = []
[profile.release]
opt-level = 3 # Maximum optimization
lto = true # Enable link-time optimization
codegen-units = 1 # Reduce parallel code generation units to increase optimization
panic = "abort" # Remove panic unwinding to reduce binary size
strip = true # Strip symbols from binary
[profile.bench]
opt-level = 3 # Maximum optimization
lto = true # Enable link-time optimization
codegen-units = 1 # Reduce parallel code generation units to increase optimization
debug = true # Keep debug symbols for profiling

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@@ -0,0 +1,412 @@
# WebSocket API Technical Specification
## Overview
This document provides a complete technical specification for the AutoGPT Platform WebSocket API (`ws_api.py`). The WebSocket API provides real-time updates for graph and node execution events, enabling clients to monitor workflow execution progress.
## Architecture Overview
### Core Components
1. **WebSocket Server** (`ws_api.py`)
- FastAPI application with WebSocket endpoint
- Handles client connections and message routing
- Authenticates clients via JWT tokens
- Manages subscriptions to execution events
2. **Connection Manager** (`conn_manager.py`)
- Maintains active WebSocket connections
- Manages channel subscriptions
- Routes execution events to subscribed clients
- Handles connection lifecycle
3. **Event Broadcasting System**
- Redis Pub/Sub based event bus
- Asynchronous event broadcaster
- Execution event propagation from backend services
## API Endpoint
### WebSocket Endpoint
- **URL**: `/ws`
- **Protocol**: WebSocket (ws:// or wss://)
- **Query Parameters**:
- `token` (required when auth enabled): JWT authentication token
## Authentication
### JWT Token Authentication
- **When Required**: When `settings.config.enable_auth` is `True`
- **Token Location**: Query parameter `?token=<JWT_TOKEN>`
- **Token Validation**:
```python
payload = parse_jwt_token(token)
user_id = payload.get("sub")
```
- **JWT Requirements**:
- Algorithm: Configured via `settings.JWT_ALGORITHM`
- Secret Key: Configured via `settings.JWT_SECRET_KEY`
- Audience: Must be "authenticated"
- Claims: Must contain `sub` (user ID)
### Authentication Failures
- **4001**: Missing authentication token
- **4002**: Invalid token (missing user ID)
- **4003**: Invalid token (parsing error or expired)
### No-Auth Mode
- When `settings.config.enable_auth` is `False`
- Uses `DEFAULT_USER_ID` from `backend.data.user`
## Message Protocol
### Message Format
All messages use JSON format with the following structure:
```typescript
interface WSMessage {
method: WSMethod;
data?: Record<string, any> | any[] | string;
success?: boolean;
channel?: string;
error?: string;
}
```
### Message Methods (WSMethod enum)
1. **Client-to-Server Methods**:
- `SUBSCRIBE_GRAPH_EXEC`: Subscribe to specific graph execution
- `SUBSCRIBE_GRAPH_EXECS`: Subscribe to all executions of a graph
- `UNSUBSCRIBE`: Unsubscribe from a channel
- `HEARTBEAT`: Keep-alive ping
2. **Server-to-Client Methods**:
- `GRAPH_EXECUTION_EVENT`: Graph execution status update
- `NODE_EXECUTION_EVENT`: Node execution status update
- `ERROR`: Error message
- `HEARTBEAT`: Keep-alive pong
## Subscription Models
### Subscribe to Specific Graph Execution
```typescript
interface WSSubscribeGraphExecutionRequest {
graph_exec_id: string;
}
```
**Channel Key Format**: `{user_id}|graph_exec#{graph_exec_id}`
### Subscribe to All Graph Executions
```typescript
interface WSSubscribeGraphExecutionsRequest {
graph_id: string;
}
```
**Channel Key Format**: `{user_id}|graph#{graph_id}|executions`
## Event Models
### Graph Execution Event
```typescript
interface GraphExecutionEvent {
event_type: "graph_execution_update";
id: string; // graph_exec_id
user_id: string;
graph_id: string;
graph_version: number;
preset_id?: string;
status: ExecutionStatus;
started_at: string; // ISO datetime
ended_at: string; // ISO datetime
inputs: Record<string, any>;
outputs: Record<string, any>;
stats?: {
cost: number; // cents
duration: number; // seconds
duration_cpu_only: number;
node_exec_time: number;
node_exec_time_cpu_only: number;
node_exec_count: number;
node_error_count: number;
error?: string;
};
}
```
### Node Execution Event
```typescript
interface NodeExecutionEvent {
event_type: "node_execution_update";
user_id: string;
graph_id: string;
graph_version: number;
graph_exec_id: string;
node_exec_id: string;
node_id: string;
block_id: string;
status: ExecutionStatus;
input_data: Record<string, any>;
output_data: Record<string, any>;
add_time: string; // ISO datetime
queue_time?: string; // ISO datetime
start_time?: string; // ISO datetime
end_time?: string; // ISO datetime
}
```
### Execution Status Enum
```typescript
enum ExecutionStatus {
INCOMPLETE = "INCOMPLETE",
QUEUED = "QUEUED",
RUNNING = "RUNNING",
COMPLETED = "COMPLETED",
FAILED = "FAILED"
}
```
## Message Flow Examples
### 1. Subscribe to Graph Execution
```json
// Client → Server
{
"method": "subscribe_graph_execution",
"data": {
"graph_exec_id": "exec-123"
}
}
// Server → Client (Success)
{
"method": "subscribe_graph_execution",
"success": true,
"channel": "user-456|graph_exec#exec-123"
}
```
### 2. Receive Execution Updates
```json
// Server → Client (Graph Update)
{
"method": "graph_execution_event",
"channel": "user-456|graph_exec#exec-123",
"data": {
"event_type": "graph_execution_update",
"id": "exec-123",
"user_id": "user-456",
"graph_id": "graph-789",
"status": "RUNNING",
// ... other fields
}
}
// Server → Client (Node Update)
{
"method": "node_execution_event",
"channel": "user-456|graph_exec#exec-123",
"data": {
"event_type": "node_execution_update",
"node_exec_id": "node-exec-111",
"status": "COMPLETED",
// ... other fields
}
}
```
### 3. Heartbeat
```json
// Client → Server
{
"method": "heartbeat",
"data": "ping"
}
// Server → Client
{
"method": "heartbeat",
"data": "pong",
"success": true
}
```
### 4. Error Handling
```json
// Server → Client (Invalid Message)
{
"method": "error",
"success": false,
"error": "Invalid message format. Review the schema and retry"
}
```
## Event Broadcasting Architecture
### Redis Pub/Sub Integration
1. **Event Bus Name**: Configured via `config.execution_event_bus_name`
2. **Channel Pattern**: `{event_bus_name}/{channel_key}`
3. **Event Flow**:
- Execution services publish events to Redis
- Event broadcaster listens to Redis pattern `*`
- Events are routed to WebSocket connections based on subscriptions
### Event Broadcaster
- Runs as continuous async task using `@continuous_retry()` decorator
- Listens to all execution events via `AsyncRedisExecutionEventBus`
- Calls `ConnectionManager.send_execution_update()` for each event
## Connection Lifecycle
### Connection Establishment
1. Client connects to `/ws` endpoint
2. Authentication performed (JWT validation)
3. WebSocket accepted via `manager.connect_socket()`
4. Connection added to active connections set
### Message Processing Loop
1. Receive text message from client
2. Parse and validate as `WSMessage`
3. Route to appropriate handler based on `method`
4. Send response or error back to client
### Connection Termination
1. `WebSocketDisconnect` exception caught
2. `manager.disconnect_socket()` called
3. Connection removed from active connections
4. All subscriptions for that connection removed
## Error Handling
### Validation Errors
- **Invalid Message Format**: Returns error with method "error"
- **Invalid Message Data**: Returns error with specific validation message
- **Unknown Message Type**: Returns error indicating unsupported method
### Connection Errors
- WebSocket disconnections handled gracefully
- Failed event parsing logged but doesn't crash connection
- Handler exceptions logged and connection continues
## Configuration
### Environment Variables
```python
# WebSocket Server Configuration
websocket_server_host: str = "0.0.0.0"
websocket_server_port: int = 8001
# Authentication
enable_auth: bool = True
# CORS
backend_cors_allow_origins: List[str] = []
# Redis Event Bus
execution_event_bus_name: str = "autogpt:execution_event_bus"
# Message Size Limits
max_message_size_limit: int = 512000 # 512KB
```
### Security Headers
- CORS middleware applied with configured origins
- Credentials allowed for authenticated requests
- All methods and headers allowed (configurable)
## Deployment Requirements
### Dependencies
1. **FastAPI**: Web framework with WebSocket support
2. **Redis**: For pub/sub event broadcasting
3. **JWT Libraries**: For token validation
4. **Prisma**: Database ORM (for future graph access validation)
### Process Management
- Implements `AppProcess` interface for service lifecycle
- Runs via `uvicorn` ASGI server
- Graceful shutdown handling in `cleanup()` method
### Concurrent Connections
- No hard limit on WebSocket connections
- Memory usage scales with active connections
- Each connection maintains subscription set
## Implementation Checklist
To implement a compatible WebSocket API:
1. **Authentication**
- [ ] JWT token validation from query parameters
- [ ] Support for no-auth mode with default user ID
- [ ] Proper error codes for auth failures
2. **Message Handling**
- [ ] Parse and validate WSMessage format
- [ ] Implement all client-to-server methods
- [ ] Support all server-to-client event types
- [ ] Proper error responses for invalid messages
3. **Subscription Management**
- [ ] Channel key generation matching exact format
- [ ] Support for both execution and graph-level subscriptions
- [ ] Unsubscribe functionality
- [ ] Clean up subscriptions on disconnect
4. **Event Broadcasting**
- [ ] Listen to Redis pub/sub for execution events
- [ ] Route events to correct subscribed connections
- [ ] Handle both graph and node execution events
- [ ] Maintain event order and completeness
5. **Connection Management**
- [ ] Track active WebSocket connections
- [ ] Handle graceful disconnections
- [ ] Implement heartbeat/keepalive
- [ ] Memory-efficient subscription storage
6. **Configuration**
- [ ] Support all environment variables
- [ ] CORS configuration for allowed origins
- [ ] Configurable host/port binding
- [ ] Redis connection configuration
7. **Error Handling**
- [ ] Graceful handling of malformed messages
- [ ] Logging of errors without dropping connections
- [ ] Specific error messages for debugging
- [ ] Recovery from Redis connection issues
## Testing Considerations
1. **Unit Tests**
- Message parsing and validation
- Channel key generation
- Subscription management logic
2. **Integration Tests**
- Full WebSocket connection flow
- Event broadcasting from Redis
- Multi-client subscription scenarios
- Authentication success/failure cases
3. **Load Tests**
- Many concurrent connections
- High-frequency event broadcasting
- Memory usage under load
- Connection/disconnection cycles
## Security Considerations
1. **Authentication**: JWT tokens transmitted via query parameters (consider upgrading to headers)
2. **Authorization**: Currently no graph-level access validation (commented out in code)
3. **Rate Limiting**: No rate limiting implemented
4. **Message Size**: Limited by `max_message_size_limit` configuration
5. **Input Validation**: All inputs validated via Pydantic models
## Future Enhancements (Currently Commented Out)
1. **Graph Access Validation**: Verify user has read access to subscribed graphs
2. **Message Compression**: For large execution payloads
3. **Batch Updates**: Aggregate multiple events in single message
4. **Selective Field Subscription**: Subscribe to specific fields only

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# WebSocket Server Benchmarks
This directory contains performance benchmarks for the AutoGPT WebSocket server.
## Prerequisites
1. Redis must be running locally or set `REDIS_URL` environment variable:
```bash
docker run -d -p 6379:6379 redis:latest
```
2. Build the project in release mode:
```bash
cargo build --release
```
## Running Benchmarks
Run all benchmarks:
```bash
cargo bench
```
Run specific benchmark group:
```bash
cargo bench connection_establishment
cargo bench subscriptions
cargo bench message_throughput
cargo bench concurrent_connections
cargo bench message_parsing
cargo bench redis_event_processing
```
## Benchmark Categories
### Connection Establishment
Tests the performance of establishing WebSocket connections with different authentication scenarios:
- No authentication
- Valid JWT authentication
- Invalid JWT authentication (connection rejection)
### Subscriptions
Measures the performance of subscription operations:
- Subscribing to graph execution events
- Unsubscribing from channels
### Message Throughput
Tests how many messages the server can process per second with varying message counts (10, 100, 1000).
### Concurrent Connections
Benchmarks the server's ability to handle multiple simultaneous connections (10, 50, 100, 500 clients).
### Message Parsing
Tests JSON parsing performance with different message sizes (100B to 100KB).
### Redis Event Processing
Benchmarks the parsing of execution events received from Redis.
## Profiling
To generate flamegraphs for CPU profiling:
1. Install flamegraph tools:
```bash
cargo install flamegraph
```
2. Run benchmarks with profiling:
```bash
cargo bench --bench websocket_bench -- --profile-time=10
```
## Interpreting Results
- **Throughput**: Higher is better (operations/second or elements/second)
- **Time**: Lower is better (nanoseconds per operation)
- **Error margins**: Look for stable results with low standard deviation
## Optimizing Performance
Based on benchmark results, consider:
1. **Connection pooling** for Redis connections
2. **Message batching** for high-throughput scenarios
3. **Async task tuning** for concurrent connection handling
4. **JSON parsing optimization** using simd-json or other fast parsers
5. **Memory allocation** optimization using arena allocators
## Notes
- Benchmarks create actual WebSocket servers on random ports
- Each benchmark iteration properly cleans up resources
- Results may vary based on system resources and Redis performance

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#![allow(clippy::unwrap_used)] // Benchmarks can panic on setup errors
use axum::{routing::get, Router};
use criterion::{criterion_group, criterion_main, BenchmarkId, Criterion, Throughput};
use futures_util::{SinkExt, StreamExt};
use serde_json::json;
use std::sync::Arc;
use std::time::Duration;
use tokio::net::TcpListener;
use tokio::runtime::Runtime;
use tokio_tungstenite::{connect_async, tungstenite::Message};
// Import the actual websocket server components
use websocket::{models, ws_handler, AppState, Config, ConnectionManager, Stats};
// Helper to create a test server
async fn create_test_server(enable_auth: bool) -> (String, tokio::task::JoinHandle<()>) {
// Set environment variables for test config
std::env::set_var("WEBSOCKET_SERVER_HOST", "127.0.0.1");
std::env::set_var("WEBSOCKET_SERVER_PORT", "0");
std::env::set_var("ENABLE_AUTH", enable_auth.to_string());
std::env::set_var("SUPABASE_JWT_SECRET", "test_secret");
std::env::set_var("DEFAULT_USER_ID", "test_user");
if std::env::var("REDIS_URL").is_err() {
std::env::set_var("REDIS_URL", "redis://localhost:6379");
}
let mut config = Config::load(None);
config.port = 0; // Force OS to assign port
let redis_client =
redis::Client::open(config.redis_url.clone()).expect("Failed to connect to Redis");
let stats = Arc::new(Stats::default());
let mgr = Arc::new(ConnectionManager::new(
redis_client,
config.execution_event_bus_name.clone(),
stats.clone(),
));
// Start broadcaster
let mgr_clone = mgr.clone();
tokio::spawn(async move {
mgr_clone.run_broadcaster().await;
});
let state = AppState {
mgr,
config: Arc::new(config),
stats,
};
let app = Router::new()
.route("/ws", get(ws_handler))
.layer(axum::Extension(state));
let listener = TcpListener::bind("127.0.0.1:0").await.unwrap();
let addr = listener.local_addr().unwrap();
let server_url = format!("ws://{addr}");
let server_handle = tokio::spawn(async move {
axum::serve(listener, app.into_make_service())
.await
.unwrap();
});
// Give server time to start
tokio::time::sleep(Duration::from_millis(100)).await;
(server_url, server_handle)
}
// Helper to create a valid JWT token
fn create_jwt_token(user_id: &str) -> String {
use jsonwebtoken::{encode, Algorithm, EncodingKey, Header};
use serde::Serialize;
#[derive(Serialize)]
struct Claims {
sub: String,
aud: Vec<String>,
exp: usize,
}
let claims = Claims {
sub: user_id.to_string(),
aud: vec!["authenticated".to_string()],
exp: (chrono::Utc::now() + chrono::Duration::hours(1)).timestamp() as usize,
};
encode(
&Header::new(Algorithm::HS256),
&claims,
&EncodingKey::from_secret(b"test_secret"),
)
.unwrap()
}
// Benchmark connection establishment
fn benchmark_connection_establishment(c: &mut Criterion) {
let rt = Runtime::new().unwrap();
let mut group = c.benchmark_group("connection_establishment");
group.measurement_time(Duration::from_secs(30));
// Test without auth
group.bench_function("no_auth", |b| {
b.to_async(&rt).iter_with_large_drop(|| async {
let (server_url, server_handle) = create_test_server(false).await;
let url = format!("{server_url}/ws");
let (ws_stream, _) = connect_async(&url).await.unwrap();
drop(ws_stream);
server_handle.abort();
});
});
// Test with valid auth
group.bench_function("valid_auth", |b| {
b.to_async(&rt).iter_with_large_drop(|| async {
let (server_url, server_handle) = create_test_server(true).await;
let token = create_jwt_token("test_user");
let url = format!("{server_url}/ws?token={token}");
let (ws_stream, _) = connect_async(&url).await.unwrap();
drop(ws_stream);
server_handle.abort();
});
});
// Test with invalid auth
group.bench_function("invalid_auth", |b| {
b.to_async(&rt).iter_with_large_drop(|| async {
let (server_url, server_handle) = create_test_server(true).await;
let url = format!("{server_url}/ws?token=invalid");
let result = connect_async(&url).await;
assert!(
result.is_err() || {
if let Ok((mut ws_stream, _)) = result {
// Should receive close frame
matches!(ws_stream.next().await, Some(Ok(Message::Close(_))))
} else {
false
}
}
);
server_handle.abort();
});
});
group.finish();
}
// Benchmark subscription operations
fn benchmark_subscriptions(c: &mut Criterion) {
let rt = Runtime::new().unwrap();
let mut group = c.benchmark_group("subscriptions");
group.measurement_time(Duration::from_secs(20));
group.bench_function("subscribe_graph_execution", |b| {
b.to_async(&rt).iter_with_large_drop(|| async {
let (server_url, server_handle) = create_test_server(false).await;
let url = format!("{server_url}/ws");
let (mut ws_stream, _) = connect_async(&url).await.unwrap();
let msg = json!({
"method": "subscribe_graph_execution",
"data": {
"graph_exec_id": "test_exec_123"
}
});
ws_stream
.send(Message::Text(msg.to_string()))
.await
.unwrap();
// Wait for response
if let Some(Ok(Message::Text(response))) = ws_stream.next().await {
let resp: serde_json::Value = serde_json::from_str(&response).unwrap();
assert_eq!(resp["success"], true);
}
server_handle.abort();
});
});
group.bench_function("unsubscribe", |b| {
b.to_async(&rt).iter_with_large_drop(|| async {
let (server_url, server_handle) = create_test_server(false).await;
let url = format!("{server_url}/ws");
let (mut ws_stream, _) = connect_async(&url).await.unwrap();
// First subscribe
let msg = json!({
"method": "subscribe_graph_execution",
"data": {
"graph_exec_id": "test_exec_123"
}
});
ws_stream
.send(Message::Text(msg.to_string()))
.await
.unwrap();
ws_stream.next().await; // Consume response
let msg = json!({
"method": "unsubscribe",
"data": {
"channel": "test_user|graph_exec#test_exec_123"
}
});
ws_stream
.send(Message::Text(msg.to_string()))
.await
.unwrap();
// Wait for response
if let Some(Ok(Message::Text(response))) = ws_stream.next().await {
let resp: serde_json::Value = serde_json::from_str(&response).unwrap();
assert_eq!(resp["success"], true);
}
server_handle.abort();
});
});
group.finish();
}
// Benchmark message throughput
fn benchmark_message_throughput(c: &mut Criterion) {
let rt = Runtime::new().unwrap();
let mut group = c.benchmark_group("message_throughput");
group.measurement_time(Duration::from_secs(30));
for msg_count in [10, 100, 1000].iter() {
group.throughput(Throughput::Elements(*msg_count as u64));
group.bench_with_input(
BenchmarkId::from_parameter(msg_count),
msg_count,
|b, &msg_count| {
b.to_async(&rt).iter_with_large_drop(|| async {
let (server_url, server_handle) = create_test_server(false).await;
let url = format!("{server_url}/ws");
let (mut ws_stream, _) = connect_async(&url).await.unwrap();
// Send multiple heartbeat messages
for _ in 0..msg_count {
let msg = json!({
"method": "heartbeat",
"data": "ping"
});
ws_stream
.send(Message::Text(msg.to_string()))
.await
.unwrap();
}
// Receive all responses
for _ in 0..msg_count {
ws_stream.next().await;
}
server_handle.abort();
});
},
);
}
group.finish();
}
// Benchmark concurrent connections
fn benchmark_concurrent_connections(c: &mut Criterion) {
let rt = Runtime::new().unwrap();
let mut group = c.benchmark_group("concurrent_connections");
group.measurement_time(Duration::from_secs(60));
group.sample_size(10);
for num_clients in [100, 500, 1000].iter() {
group.throughput(Throughput::Elements(*num_clients as u64));
group.bench_with_input(
BenchmarkId::from_parameter(num_clients),
num_clients,
|b, &num_clients| {
b.to_async(&rt).iter_with_large_drop(|| async {
let (server_url, server_handle) = create_test_server(false).await;
let url = format!("{server_url}/ws");
// Create multiple concurrent connections
let mut handles = vec![];
for i in 0..num_clients {
let url = url.clone();
let handle = tokio::spawn(async move {
let (mut ws_stream, _) = connect_async(&url).await.unwrap();
// Subscribe to a unique channel
let msg = json!({
"method": "subscribe_graph_execution",
"data": {
"graph_exec_id": format!("exec_{}", i)
}
});
ws_stream
.send(Message::Text(msg.to_string()))
.await
.unwrap();
ws_stream.next().await; // Wait for response
// Send a heartbeat
let msg = json!({
"method": "heartbeat",
"data": "ping"
});
ws_stream
.send(Message::Text(msg.to_string()))
.await
.unwrap();
ws_stream.next().await; // Wait for response
ws_stream
});
handles.push(handle);
}
// Wait for all connections to complete
for handle in handles {
let _ = handle.await;
}
server_handle.abort();
});
},
);
}
group.finish();
}
// Benchmark message parsing
fn benchmark_message_parsing(c: &mut Criterion) {
let mut group = c.benchmark_group("message_parsing");
// Test different message sizes
for msg_size in [100, 1000, 10000].iter() {
group.throughput(Throughput::Bytes(*msg_size as u64));
group.bench_with_input(
BenchmarkId::new("parse_json", msg_size),
msg_size,
|b, &msg_size| {
let data_str = "x".repeat(msg_size);
let json_msg = json!({
"method": "subscribe_graph_execution",
"data": {
"graph_exec_id": data_str
}
});
let json_str = json_msg.to_string();
b.iter(|| {
let _: models::WSMessage = serde_json::from_str(&json_str).unwrap();
});
},
);
}
group.finish();
}
// Benchmark Redis event processing
fn benchmark_redis_event_processing(c: &mut Criterion) {
let mut group = c.benchmark_group("redis_event_processing");
group.bench_function("parse_execution_event", |b| {
let event = json!({
"payload": {
"event_type": "graph_execution_update",
"id": "exec_123",
"graph_id": "graph_456",
"graph_version": 1,
"user_id": "user_789",
"status": "RUNNING",
"started_at": "2024-01-01T00:00:00Z",
"inputs": {"test": "data"},
"outputs": {}
}
});
let event_str = event.to_string();
b.iter(|| {
let _: models::RedisEventWrapper = serde_json::from_str(&event_str).unwrap();
});
});
group.finish();
}
criterion_group!(
benches,
benchmark_connection_establishment,
benchmark_subscriptions,
benchmark_message_throughput,
benchmark_concurrent_connections,
benchmark_message_parsing,
benchmark_redis_event_processing
);
criterion_main!(benches);

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# Clippy configuration for robust error handling
# Set the maximum cognitive complexity allowed
cognitive-complexity-threshold = 30
# Warn on TODO/FIXME comments
allow-dbg-in-tests = false
# Enforce documentation
missing-docs-in-crate-items = true

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# WebSocket API Configuration
# Server settings
host = "0.0.0.0"
port = 8001
# Authentication
enable_auth = true
jwt_secret = "your-super-secret-jwt-token-with-at-least-32-characters-long"
jwt_algorithm = "HS256"
default_user_id = "default"
# Redis configuration
redis_url = "redis://:password@localhost:6379/"
# Event bus
execution_event_bus_name = "execution_event"
# Message size limit (in bytes)
max_message_size_limit = 512000
# CORS allowed origins
backend_cors_allow_origins = ["http://localhost:3000", "https://559f69c159ef.ngrok.app"]

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use futures_util::{SinkExt, StreamExt};
use serde_json::json;
use tokio_tungstenite::{connect_async, tungstenite::Message};
#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
let url = "ws://localhost:8001/ws";
println!("Connecting to {url}");
let (mut ws_stream, _) = connect_async(url).await?;
println!("Connected!");
// Subscribe to a graph execution
let subscribe_msg = json!({
"method": "subscribe_graph_execution",
"data": {
"graph_exec_id": "test_exec_123"
}
});
println!("Sending subscription request...");
ws_stream
.send(Message::Text(subscribe_msg.to_string()))
.await?;
// Wait for response
if let Some(msg) = ws_stream.next().await {
if let Message::Text(text) = msg? {
println!("Received: {text}");
}
}
// Send heartbeat
let heartbeat_msg = json!({
"method": "heartbeat",
"data": "ping"
});
println!("Sending heartbeat...");
ws_stream
.send(Message::Text(heartbeat_msg.to_string()))
.await?;
// Wait for pong
if let Some(msg) = ws_stream.next().await {
if let Message::Text(text) = msg? {
println!("Received: {text}");
}
}
// Unsubscribe
let unsubscribe_msg = json!({
"method": "unsubscribe",
"data": {
"channel": "default|graph_exec#test_exec_123"
}
});
println!("Sending unsubscribe request...");
ws_stream
.send(Message::Text(unsubscribe_msg.to_string()))
.await?;
// Wait for response
if let Some(msg) = ws_stream.next().await {
if let Message::Text(text) = msg? {
println!("Received: {text}");
}
}
println!("Closing connection...");
ws_stream.close(None).await?;
Ok(())
}

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use jsonwebtoken::Algorithm;
use serde::Deserialize;
use std::env;
use std::fs;
use std::path::Path;
use std::str::FromStr;
#[derive(Clone, Debug, Deserialize)]
pub struct Config {
pub host: String,
pub port: u16,
pub enable_auth: bool,
pub jwt_secret: String,
pub jwt_algorithm: Algorithm,
pub execution_event_bus_name: String,
pub redis_url: String,
pub default_user_id: String,
pub max_message_size_limit: usize,
pub backend_cors_allow_origins: Vec<String>,
}
impl Config {
pub fn load(config_path: Option<&Path>) -> Self {
let path = config_path.unwrap_or(Path::new("config.toml"));
let toml_result = fs::read_to_string(path)
.ok()
.and_then(|s| toml::from_str::<Config>(&s).ok());
let mut config = match toml_result {
Some(config) => config,
None => Config {
host: env::var("WEBSOCKET_SERVER_HOST").unwrap_or_else(|_| "0.0.0.0".to_string()),
port: env::var("WEBSOCKET_SERVER_PORT")
.ok()
.and_then(|s| s.parse().ok())
.unwrap_or(8001),
enable_auth: env::var("ENABLE_AUTH")
.ok()
.and_then(|s| s.parse().ok())
.unwrap_or(true),
jwt_secret: env::var("SUPABASE_JWT_SECRET")
.unwrap_or_else(|_| "dummy_secret_for_no_auth".to_string()),
jwt_algorithm: Algorithm::HS256,
execution_event_bus_name: env::var("EXECUTION_EVENT_BUS_NAME")
.unwrap_or_else(|_| "execution_event".to_string()),
redis_url: env::var("REDIS_URL")
.unwrap_or_else(|_| "redis://localhost/".to_string()),
default_user_id: "default".to_string(),
max_message_size_limit: env::var("MAX_MESSAGE_SIZE_LIMIT")
.ok()
.and_then(|s| s.parse().ok())
.unwrap_or(512000),
backend_cors_allow_origins: env::var("BACKEND_CORS_ALLOW_ORIGINS")
.unwrap_or_default()
.split(',')
.map(|s| s.trim().to_string())
.filter(|s| !s.is_empty())
.collect(),
},
};
if let Ok(v) = env::var("WEBSOCKET_SERVER_HOST") {
config.host = v;
}
if let Ok(v) = env::var("WEBSOCKET_SERVER_PORT") {
config.port = v.parse().unwrap_or(8001);
}
if let Ok(v) = env::var("ENABLE_AUTH") {
config.enable_auth = v.parse().unwrap_or(true);
}
if let Ok(v) = env::var("SUPABASE_JWT_SECRET") {
config.jwt_secret = v;
}
if let Ok(v) = env::var("JWT_ALGORITHM") {
config.jwt_algorithm = Algorithm::from_str(&v).unwrap_or(Algorithm::HS256);
}
if let Ok(v) = env::var("EXECUTION_EVENT_BUS_NAME") {
config.execution_event_bus_name = v;
}
if let Ok(v) = env::var("REDIS_URL") {
config.redis_url = v;
}
if let Ok(v) = env::var("DEFAULT_USER_ID") {
config.default_user_id = v;
}
if let Ok(v) = env::var("MAX_MESSAGE_SIZE_LIMIT") {
config.max_message_size_limit = v.parse().unwrap_or(512000);
}
if let Ok(v) = env::var("BACKEND_CORS_ALLOW_ORIGINS") {
config.backend_cors_allow_origins = v
.split(',')
.map(|s| s.trim().to_string())
.filter(|s| !s.is_empty())
.collect();
}
config
}
}

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use futures::StreamExt;
use redis::Client as RedisClient;
use std::collections::{HashMap, HashSet};
use std::sync::atomic::AtomicU64;
use std::sync::Arc;
use tokio::sync::{mpsc, RwLock};
use tracing::{debug, error, info, warn};
use crate::models::{ExecutionEvent, RedisEventWrapper, WSMessage};
use crate::stats::Stats;
pub struct ConnectionManager {
pub subscribers: RwLock<HashMap<String, HashSet<u64>>>,
pub clients: RwLock<HashMap<u64, (String, mpsc::Sender<String>)>>,
pub client_channels: RwLock<HashMap<u64, HashSet<String>>>,
pub next_id: AtomicU64,
pub redis_client: RedisClient,
pub bus_name: String,
pub stats: Arc<Stats>,
}
impl ConnectionManager {
pub fn new(redis_client: RedisClient, bus_name: String, stats: Arc<Stats>) -> Self {
Self {
subscribers: RwLock::new(HashMap::new()),
clients: RwLock::new(HashMap::new()),
client_channels: RwLock::new(HashMap::new()),
next_id: AtomicU64::new(0),
redis_client,
bus_name,
stats,
}
}
pub async fn run_broadcaster(self: Arc<Self>) {
info!("🚀 Starting Redis event broadcaster");
loop {
match self.run_broadcaster_inner().await {
Ok(_) => {
warn!("⚠️ Event broadcaster stopped unexpectedly, restarting in 5 seconds");
tokio::time::sleep(tokio::time::Duration::from_secs(5)).await;
}
Err(e) => {
error!("❌ Event broadcaster error: {}, restarting in 5 seconds", e);
tokio::time::sleep(tokio::time::Duration::from_secs(5)).await;
}
}
}
}
async fn run_broadcaster_inner(
self: &Arc<Self>,
) -> Result<(), Box<dyn std::error::Error + Send + Sync>> {
let mut pubsub = self.redis_client.get_async_pubsub().await?;
pubsub.psubscribe("*").await?;
info!(
"📡 Listening to all Redis events, filtering for bus: {}",
self.bus_name
);
let mut pubsub_stream = pubsub.on_message();
loop {
let msg = pubsub_stream.next().await;
match msg {
Some(msg) => {
let channel: String = msg.get_channel_name().to_string();
debug!("📨 Received message on Redis channel: {}", channel);
self.stats
.redis_messages_received
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
let payload: String = match msg.get_payload() {
Ok(p) => p,
Err(e) => {
warn!("⚠️ Failed to get payload from Redis message: {}", e);
self.stats
.errors_total
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
continue;
}
};
// Parse the channel format: execution_event/{user_id}/{graph_id}/{graph_exec_id}
let parts: Vec<&str> = channel.split('/').collect();
// Check if this is an execution event channel
if parts.len() != 4 || parts[0] != self.bus_name {
debug!(
"🚫 Ignoring non-execution event channel: {} (parts: {:?}, bus_name: {})",
channel, parts, self.bus_name
);
self.stats
.redis_messages_ignored
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
continue;
}
let user_id = parts[1];
let graph_id = parts[2];
let graph_exec_id = parts[3];
debug!(
"📥 Received event - user: {}, graph: {}, exec: {}",
user_id, graph_id, graph_exec_id
);
// Parse the wrapped event
let wrapped_event = match RedisEventWrapper::parse(&payload) {
Ok(e) => e,
Err(e) => {
warn!("⚠️ Failed to parse event JSON: {}, payload: {}", e, payload);
self.stats
.errors_json_parse
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
self.stats
.errors_total
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
continue;
}
};
let event = wrapped_event.payload;
debug!("📦 Event received: {:?}", event);
let (method, event_json) = match &event {
ExecutionEvent::GraphExecutionUpdate(graph_event) => {
self.stats
.graph_execution_events
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
self.stats
.events_received_total
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
(
"graph_execution_event",
match serde_json::to_value(graph_event) {
Ok(v) => v,
Err(e) => {
error!("❌ Failed to serialize graph event: {}", e);
continue;
}
},
)
}
ExecutionEvent::NodeExecutionUpdate(node_event) => {
self.stats
.node_execution_events
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
self.stats
.events_received_total
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
(
"node_execution_event",
match serde_json::to_value(node_event) {
Ok(v) => v,
Err(e) => {
error!("❌ Failed to serialize node event: {}", e);
continue;
}
},
)
}
};
// Create the channel keys in the format expected by WebSocket clients
let mut channels_to_notify = Vec::new();
// For both event types, notify the specific execution channel
let exec_channel = format!("{user_id}|graph_exec#{graph_exec_id}");
channels_to_notify.push(exec_channel.clone());
// For graph execution events, also notify the graph executions channel
if matches!(&event, ExecutionEvent::GraphExecutionUpdate(_)) {
let graph_channel = format!("{user_id}|graph#{graph_id}|executions");
channels_to_notify.push(graph_channel);
}
debug!(
"📢 Broadcasting {} event to channels: {:?}",
method, channels_to_notify
);
let subs = self.subscribers.read().await;
// Log current subscriber state
debug!("📊 Current subscribers count: {}", subs.len());
for channel_key in channels_to_notify {
let ws_msg = WSMessage {
method: method.to_string(),
channel: Some(channel_key.clone()),
data: Some(event_json.clone()),
..Default::default()
};
let json_msg = match serde_json::to_string(&ws_msg) {
Ok(j) => {
debug!("📤 Sending WebSocket message: {}", j);
j
}
Err(e) => {
error!("❌ Failed to serialize WebSocket message: {}", e);
continue;
}
};
if let Some(client_ids) = subs.get(&channel_key) {
let clients = self.clients.read().await;
let client_count = client_ids.len();
debug!(
"📣 Broadcasting to {} clients on channel: {}",
client_count, channel_key
);
for &cid in client_ids {
if let Some((user_id, tx)) = clients.get(&cid) {
match tx.try_send(json_msg.clone()) {
Ok(_) => {
debug!(
"✅ Message sent immediately to client {} (user: {})",
cid, user_id
);
self.stats
.messages_sent_total
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
}
Err(mpsc::error::TrySendError::Full(_)) => {
// Channel is full, try with a small timeout
let tx_clone = tx.clone();
let msg_clone = json_msg.clone();
let stats_clone = self.stats.clone();
tokio::spawn(async move {
match tokio::time::timeout(
std::time::Duration::from_millis(100),
tx_clone.send(msg_clone),
)
.await {
Ok(Ok(_)) => {
stats_clone
.messages_sent_total
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
}
_ => {
stats_clone
.messages_failed_total
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
}
}
});
warn!("⚠️ Channel full for client {} (user: {}), sending async", cid, user_id);
}
Err(mpsc::error::TrySendError::Closed(_)) => {
warn!(
"⚠️ Channel closed for client {} (user: {})",
cid, user_id
);
self.stats
.messages_failed_total
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
}
}
} else {
warn!("⚠️ Client {} not found in clients map", cid);
}
}
} else {
info!("📭 No subscribers for channel: {}", channel_key);
}
}
}
None => {
return Err("❌ Redis pubsub stream ended".into());
}
}
}
}
}

View File

@@ -0,0 +1,442 @@
use axum::extract::ws::{CloseFrame, Message, WebSocket};
use axum::{
extract::{Query, WebSocketUpgrade},
http::HeaderMap,
response::IntoResponse,
Extension,
};
use jsonwebtoken::{decode, DecodingKey, Validation};
use serde_json::{json, Value};
use std::collections::HashMap;
use tokio::sync::mpsc;
use tracing::{debug, error, info, warn};
use crate::connection_manager::ConnectionManager;
use crate::models::{Claims, WSMessage};
use crate::AppState;
// Helper function to safely serialize messages
fn serialize_message(msg: &WSMessage) -> String {
serde_json::to_string(msg).unwrap_or_else(|e| {
error!("❌ Failed to serialize WebSocket message: {}", e);
json!({"method": "error", "success": false, "error": "Internal serialization error"})
.to_string()
})
}
pub async fn ws_handler(
ws: WebSocketUpgrade,
query: Query<HashMap<String, String>>,
_headers: HeaderMap,
Extension(state): Extension<AppState>,
) -> impl IntoResponse {
let token = query.0.get("token").cloned();
let mut user_id = state.config.default_user_id.clone();
let mut auth_error_code: Option<u16> = None;
if state.config.enable_auth {
match token {
Some(token_str) => {
debug!("🔐 Authenticating WebSocket connection");
let mut validation = Validation::new(state.config.jwt_algorithm);
validation.set_audience(&["authenticated"]);
let key = DecodingKey::from_secret(state.config.jwt_secret.as_bytes());
match decode::<Claims>(&token_str, &key, &validation) {
Ok(token_data) => {
user_id = token_data.claims.sub.clone();
debug!("✅ WebSocket authenticated for user: {}", user_id);
}
Err(e) => {
warn!("⚠️ JWT validation failed: {}", e);
auth_error_code = Some(4003);
}
}
}
None => {
warn!("⚠️ Missing authentication token in WebSocket connection");
auth_error_code = Some(4001);
}
}
} else {
debug!("🔓 WebSocket connection without auth (auth disabled)");
}
if let Some(code) = auth_error_code {
error!("❌ WebSocket authentication failed with code: {}", code);
state
.mgr
.stats
.connections_failed_auth
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
state
.mgr
.stats
.connections_total
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
return ws
.on_upgrade(move |mut socket: WebSocket| async move {
let close_frame = Some(CloseFrame {
code,
reason: "Authentication failed".into(),
});
let _ = socket.send(Message::Close(close_frame)).await;
let _ = socket.close().await;
})
.into_response();
}
debug!("✅ WebSocket connection established for user: {}", user_id);
ws.on_upgrade(move |socket| {
handle_socket(
socket,
user_id,
state.mgr.clone(),
state.config.max_message_size_limit,
)
})
}
async fn update_subscription_stats(mgr: &ConnectionManager, channel: &str, add: bool) {
if add {
mgr.stats
.subscriptions_total
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
mgr.stats
.subscriptions_active
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
let mut channel_stats = mgr.stats.channels_active.write().await;
let count = channel_stats.entry(channel.to_string()).or_insert(0);
*count += 1;
} else {
mgr.stats
.unsubscriptions_total
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
mgr.stats
.subscriptions_active
.fetch_sub(1, std::sync::atomic::Ordering::Relaxed);
let mut channel_stats = mgr.stats.channels_active.write().await;
if let Some(count) = channel_stats.get_mut(channel) {
*count = count.saturating_sub(1);
if *count == 0 {
channel_stats.remove(channel);
}
}
}
}
pub async fn handle_socket(
mut socket: WebSocket,
user_id: String,
mgr: std::sync::Arc<ConnectionManager>,
max_size: usize,
) {
let client_id = mgr
.next_id
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
let (tx, mut rx) = mpsc::channel::<String>(10);
info!("👋 New WebSocket client {} for user: {}", client_id, user_id);
// Update connection stats
mgr.stats
.connections_total
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
mgr.stats
.connections_active
.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
// Update active users
{
let mut active_users = mgr.stats.active_users.write().await;
let count = active_users.entry(user_id.clone()).or_insert(0);
*count += 1;
}
{
let mut clients = mgr.clients.write().await;
clients.insert(client_id, (user_id.clone(), tx));
}
{
let mut client_channels = mgr.client_channels.write().await;
client_channels.insert(client_id, std::collections::HashSet::new());
}
loop {
tokio::select! {
msg = rx.recv() => {
if let Some(msg) = msg {
if socket.send(Message::Text(msg)).await.is_err() {
break;
}
} else {
break;
}
}
incoming = socket.recv() => {
let msg = match incoming {
Some(Ok(msg)) => msg,
_ => break,
};
match msg {
Message::Text(text) => {
if text.len() > max_size {
warn!("⚠️ Message from client {} exceeds size limit: {} > {}", client_id, text.len(), max_size);
let err_resp = serialize_message(&WSMessage {
method: "error".to_string(),
success: Some(false),
error: Some("Message exceeds size limit".to_string()),
..Default::default()
});
if socket.send(Message::Text(err_resp)).await.is_err() {
break;
}
continue;
}
mgr.stats.messages_received_total.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
let ws_msg: WSMessage = match serde_json::from_str(&text) {
Ok(m) => m,
Err(e) => {
warn!("⚠️ Invalid message format from client {}: {}", client_id, e);
mgr.stats.errors_json_parse.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
mgr.stats.errors_total.fetch_add(1, std::sync::atomic::Ordering::Relaxed);
let err_resp = serialize_message(&WSMessage {
method: "error".to_string(),
success: Some(false),
error: Some("Invalid message format. Review the schema and retry".to_string()),
..Default::default()
});
if socket.send(Message::Text(err_resp)).await.is_err() {
break;
}
continue;
}
};
debug!("📥 Received {} message from client {}", ws_msg.method, client_id);
match ws_msg.method.as_str() {
"subscribe_graph_execution" => {
let graph_exec_id = match &ws_msg.data {
Some(Value::Object(map)) => map.get("graph_exec_id").and_then(|v| v.as_str()),
_ => None,
};
let Some(graph_exec_id) = graph_exec_id else {
warn!("⚠️ Missing graph_exec_id in subscribe_graph_execution from client {}", client_id);
let err_resp = json!({"method": "error", "success": false, "error": "Missing graph_exec_id"});
if socket.send(Message::Text(err_resp.to_string())).await.is_err() {
break;
}
continue;
};
let channel = format!("{user_id}|graph_exec#{graph_exec_id}");
debug!("📌 Client {} subscribing to channel: {}", client_id, channel);
{
let mut subs = mgr.subscribers.write().await;
subs.entry(channel.clone()).or_insert(std::collections::HashSet::new()).insert(client_id);
}
{
let mut chs = mgr.client_channels.write().await;
if let Some(set) = chs.get_mut(&client_id) {
set.insert(channel.clone());
}
}
// Update subscription stats
update_subscription_stats(&mgr, &channel, true).await;
let resp = WSMessage {
method: "subscribe_graph_execution".to_string(),
success: Some(true),
channel: Some(channel),
..Default::default()
};
if socket.send(Message::Text(serialize_message(&resp))).await.is_err() {
break;
}
}
"subscribe_graph_executions" => {
let graph_id = match &ws_msg.data {
Some(Value::Object(map)) => map.get("graph_id").and_then(|v| v.as_str()),
_ => None,
};
let Some(graph_id) = graph_id else {
let err_resp = json!({"method": "error", "success": false, "error": "Missing graph_id"});
if socket.send(Message::Text(err_resp.to_string())).await.is_err() {
break;
}
continue;
};
let channel = format!("{user_id}|graph#{graph_id}|executions");
{
let mut subs = mgr.subscribers.write().await;
subs.entry(channel.clone()).or_insert(std::collections::HashSet::new()).insert(client_id);
}
{
let mut chs = mgr.client_channels.write().await;
if let Some(set) = chs.get_mut(&client_id) {
set.insert(channel.clone());
}
}
debug!("📌 Client {} subscribing to channel: {}", client_id, channel);
// Update subscription stats
update_subscription_stats(&mgr, &channel, true).await;
let resp = WSMessage {
method: "subscribe_graph_executions".to_string(),
success: Some(true),
channel: Some(channel),
..Default::default()
};
if socket.send(Message::Text(serialize_message(&resp))).await.is_err() {
break;
}
}
"unsubscribe" => {
let channel = match &ws_msg.data {
Some(Value::String(s)) => Some(s.as_str()),
Some(Value::Object(map)) => map.get("channel").and_then(|v| v.as_str()),
_ => None,
};
let Some(channel) = channel else {
let err_resp = json!({"method": "error", "success": false, "error": "Missing channel"});
if socket.send(Message::Text(err_resp.to_string())).await.is_err() {
break;
}
continue;
};
let channel = channel.to_string();
if !channel.starts_with(&format!("{user_id}|")) {
let err_resp = json!({"method": "error", "success": false, "error": "Unauthorized channel"});
if socket.send(Message::Text(err_resp.to_string())).await.is_err() {
break;
}
continue;
}
{
let mut subs = mgr.subscribers.write().await;
if let Some(set) = subs.get_mut(&channel) {
set.remove(&client_id);
if set.is_empty() {
subs.remove(&channel);
}
}
}
{
let mut chs = mgr.client_channels.write().await;
if let Some(set) = chs.get_mut(&client_id) {
set.remove(&channel);
}
}
// Update subscription stats
update_subscription_stats(&mgr, &channel, false).await;
let resp = WSMessage {
method: "unsubscribe".to_string(),
success: Some(true),
channel: Some(channel),
..Default::default()
};
if socket.send(Message::Text(serialize_message(&resp))).await.is_err() {
break;
}
}
"heartbeat" => {
if ws_msg.data == Some(Value::String("ping".to_string())) {
let resp = WSMessage {
method: "heartbeat".to_string(),
data: Some(Value::String("pong".to_string())),
success: Some(true),
..Default::default()
};
if socket.send(Message::Text(serialize_message(&resp))).await.is_err() {
break;
}
} else {
let err_resp = json!({"method": "error", "success": false, "error": "Invalid heartbeat"});
if socket.send(Message::Text(err_resp.to_string())).await.is_err() {
break;
}
}
}
_ => {
warn!("❓ Unknown method '{}' from client {}", ws_msg.method, client_id);
let err_resp = json!({"method": "error", "success": false, "error": "Unknown method"});
if socket.send(Message::Text(err_resp.to_string())).await.is_err() {
break;
}
}
}
}
Message::Close(_) => break,
Message::Ping(_) => {
if socket.send(Message::Pong(vec![])).await.is_err() {
break;
}
}
Message::Pong(_) => {}
_ => {}
}
}
else => break,
}
}
// Cleanup
debug!("👋 WebSocket client {} disconnected, cleaning up", client_id);
// Update connection stats
mgr.stats
.connections_active
.fetch_sub(1, std::sync::atomic::Ordering::Relaxed);
// Update active users
{
let mut active_users = mgr.stats.active_users.write().await;
if let Some(count) = active_users.get_mut(&user_id) {
*count = count.saturating_sub(1);
if *count == 0 {
active_users.remove(&user_id);
}
}
}
let channels = {
let mut client_channels = mgr.client_channels.write().await;
client_channels.remove(&client_id).unwrap_or_default()
};
{
let mut subs = mgr.subscribers.write().await;
for channel in &channels {
if let Some(set) = subs.get_mut(channel) {
set.remove(&client_id);
if set.is_empty() {
subs.remove(channel);
}
}
}
}
// Update subscription stats for all channels the client was subscribed to
for channel in &channels {
update_subscription_stats(&mgr, channel, false).await;
}
{
let mut clients = mgr.clients.write().await;
clients.remove(&client_id);
}
debug!("✨ Cleanup completed for client {}", client_id);
}

View File

@@ -0,0 +1,26 @@
#![deny(warnings)]
#![deny(clippy::unwrap_used)]
#![deny(clippy::panic)]
#![deny(clippy::unimplemented)]
#![deny(clippy::todo)]
pub mod config;
pub mod connection_manager;
pub mod handlers;
pub mod models;
pub mod stats;
pub use config::Config;
pub use connection_manager::ConnectionManager;
pub use handlers::ws_handler;
pub use stats::Stats;
use std::sync::Arc;
#[derive(Clone)]
pub struct AppState {
pub mgr: Arc<ConnectionManager>,
pub config: Arc<Config>,
pub stats: Arc<Stats>,
}

View File

@@ -0,0 +1,172 @@
use axum::{
body::Body,
http::{header, StatusCode},
response::Response,
routing::get,
Router,
};
use clap::Parser;
use std::sync::Arc;
use tokio::net::TcpListener;
use tower_http::cors::{Any, CorsLayer};
use tracing::{debug, error, info};
use tracing_subscriber::{layer::SubscriberExt, util::SubscriberInitExt};
use crate::config::Config;
use crate::connection_manager::ConnectionManager;
use crate::handlers::ws_handler;
async fn stats_handler(
axum::Extension(state): axum::Extension<AppState>,
) -> Result<axum::response::Json<stats::StatsSnapshot>, StatusCode> {
let snapshot = state.stats.snapshot().await;
Ok(axum::response::Json(snapshot))
}
async fn prometheus_handler(
axum::Extension(state): axum::Extension<AppState>,
) -> Result<Response, StatusCode> {
let snapshot = state.stats.snapshot().await;
let prometheus_text = state.stats.to_prometheus_format(&snapshot);
Response::builder()
.status(StatusCode::OK)
.header(header::CONTENT_TYPE, "text/plain; version=0.0.4")
.body(Body::from(prometheus_text))
.map_err(|_| StatusCode::INTERNAL_SERVER_ERROR)
}
mod config;
mod connection_manager;
mod handlers;
mod models;
mod stats;
#[derive(Parser, Debug)]
#[command(author, version, about)]
struct Cli {
/// Path to a TOML configuration file
#[arg(short = 'c', long = "config", value_name = "FILE")]
config: Option<std::path::PathBuf>,
}
#[derive(Clone)]
pub struct AppState {
mgr: Arc<ConnectionManager>,
config: Arc<Config>,
stats: Arc<stats::Stats>,
}
#[tokio::main]
async fn main() {
// Initialize tracing
tracing_subscriber::registry()
.with(
tracing_subscriber::EnvFilter::try_from_default_env()
.unwrap_or_else(|_| "websocket=info,tower_http=debug".into()),
)
.with(tracing_subscriber::fmt::layer())
.init();
info!("🚀 Starting WebSocket API server");
let cli = Cli::parse();
let config = Arc::new(Config::load(cli.config.as_deref()));
info!(
"⚙️ Configuration loaded - host: {}, port: {}, auth: {}",
config.host, config.port, config.enable_auth
);
let redis_client = match redis::Client::open(config.redis_url.clone()) {
Ok(client) => {
debug!("✅ Redis client created successfully");
client
}
Err(e) => {
error!(
"❌ Failed to create Redis client: {}. Please check REDIS_URL environment variable",
e
);
std::process::exit(1);
}
};
let stats = Arc::new(stats::Stats::default());
let mgr = Arc::new(ConnectionManager::new(
redis_client,
config.execution_event_bus_name.clone(),
stats.clone(),
));
let mgr_clone = mgr.clone();
tokio::spawn(async move {
debug!("📡 Starting event broadcaster task");
mgr_clone.run_broadcaster().await;
});
let state = AppState {
mgr,
config: config.clone(),
stats,
};
let app = Router::new()
.route("/ws", get(ws_handler))
.route("/stats", get(stats_handler))
.route("/metrics", get(prometheus_handler))
.layer(axum::Extension(state));
let cors = if config.backend_cors_allow_origins.is_empty() {
// If no specific origins configured, allow any origin but without credentials
CorsLayer::new()
.allow_methods(Any)
.allow_headers(Any)
.allow_origin(Any)
} else {
// If specific origins configured, allow credentials
CorsLayer::new()
.allow_methods([
axum::http::Method::GET,
axum::http::Method::POST,
axum::http::Method::PUT,
axum::http::Method::DELETE,
axum::http::Method::OPTIONS,
])
.allow_headers(vec![
axum::http::header::CONTENT_TYPE,
axum::http::header::AUTHORIZATION,
])
.allow_credentials(true)
.allow_origin(
config
.backend_cors_allow_origins
.iter()
.filter_map(|o| o.parse::<axum::http::HeaderValue>().ok())
.collect::<Vec<_>>(),
)
};
let app = app.layer(cors);
let addr = format!("{}:{}", config.host, config.port);
let listener = match TcpListener::bind(&addr).await {
Ok(listener) => {
info!("🎧 WebSocket server listening on: {}", addr);
listener
}
Err(e) => {
error!(
"❌ Failed to bind to {}: {}. Please check if the port is already in use",
addr, e
);
std::process::exit(1);
}
};
info!("✨ WebSocket API server ready to accept connections");
if let Err(e) = axum::serve(listener, app.into_make_service()).await {
error!("💥 Server error: {}", e);
std::process::exit(1);
}
}

View File

@@ -0,0 +1,103 @@
use serde::{Deserialize, Serialize};
use serde_json::Value;
#[derive(Default, Clone, Debug, Serialize, Deserialize)]
pub struct WSMessage {
pub method: String,
#[serde(default, skip_serializing_if = "Option::is_none")]
pub data: Option<Value>,
#[serde(default, skip_serializing_if = "Option::is_none")]
pub success: Option<bool>,
#[serde(default, skip_serializing_if = "Option::is_none")]
pub channel: Option<String>,
#[serde(default, skip_serializing_if = "Option::is_none")]
pub error: Option<String>,
}
#[derive(Deserialize)]
pub struct Claims {
pub sub: String,
}
// Event models moved from events.rs
#[derive(Debug, Clone, Serialize, Deserialize)]
#[serde(tag = "event_type")]
pub enum ExecutionEvent {
#[serde(rename = "graph_execution_update")]
GraphExecutionUpdate(GraphExecutionEvent),
#[serde(rename = "node_execution_update")]
NodeExecutionUpdate(NodeExecutionEvent),
}
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct GraphExecutionEvent {
pub id: String,
pub graph_id: String,
pub graph_version: u32,
pub user_id: String,
pub status: ExecutionStatus,
pub started_at: Option<String>,
pub ended_at: Option<String>,
pub preset_id: Option<String>,
pub stats: Option<ExecutionStats>,
// Keep these as JSON since they vary by graph
pub inputs: Value,
pub outputs: Value,
}
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct NodeExecutionEvent {
pub node_exec_id: String,
pub node_id: String,
pub graph_exec_id: String,
pub graph_id: String,
pub graph_version: u32,
pub user_id: String,
pub block_id: String,
pub status: ExecutionStatus,
pub add_time: String,
pub queue_time: Option<String>,
pub start_time: Option<String>,
pub end_time: Option<String>,
// Keep these as JSON since they vary by node type
pub input_data: Value,
pub output_data: Value,
}
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ExecutionStats {
pub cost: f64,
pub duration: f64,
pub duration_cpu_only: f64,
pub error: Option<String>,
pub node_error_count: u32,
pub node_exec_count: u32,
pub node_exec_time: f64,
pub node_exec_time_cpu_only: f64,
}
#[derive(Debug, Clone, Serialize, Deserialize)]
#[serde(rename_all = "SCREAMING_SNAKE_CASE")]
pub enum ExecutionStatus {
Queued,
Running,
Completed,
Failed,
Incomplete,
Terminated,
}
// Wrapper for the Redis event that includes the payload
#[derive(Debug, Deserialize)]
pub struct RedisEventWrapper {
pub payload: ExecutionEvent,
}
impl RedisEventWrapper {
pub fn parse(json_str: &str) -> Result<Self, serde_json::Error> {
serde_json::from_str(json_str)
}
}

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@@ -0,0 +1,238 @@
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use std::sync::atomic::{AtomicU64, Ordering};
use tokio::sync::RwLock;
#[derive(Default)]
pub struct Stats {
// Connection metrics
pub connections_total: AtomicU64,
pub connections_active: AtomicU64,
pub connections_failed_auth: AtomicU64,
// Message metrics
pub messages_received_total: AtomicU64,
pub messages_sent_total: AtomicU64,
pub messages_failed_total: AtomicU64,
// Subscription metrics
pub subscriptions_total: AtomicU64,
pub subscriptions_active: AtomicU64,
pub unsubscriptions_total: AtomicU64,
// Event metrics by type
pub events_received_total: AtomicU64,
pub graph_execution_events: AtomicU64,
pub node_execution_events: AtomicU64,
// Redis metrics
pub redis_messages_received: AtomicU64,
pub redis_messages_ignored: AtomicU64,
// Channel metrics
pub channels_active: RwLock<HashMap<String, usize>>, // channel -> subscriber count
// User metrics
pub active_users: RwLock<HashMap<String, usize>>, // user_id -> connection count
// Error metrics
pub errors_total: AtomicU64,
pub errors_json_parse: AtomicU64,
pub errors_message_size: AtomicU64,
}
#[derive(Serialize, Deserialize)]
pub struct StatsSnapshot {
// Connection metrics
pub connections_total: u64,
pub connections_active: u64,
pub connections_failed_auth: u64,
// Message metrics
pub messages_received_total: u64,
pub messages_sent_total: u64,
pub messages_failed_total: u64,
// Subscription metrics
pub subscriptions_total: u64,
pub subscriptions_active: u64,
pub unsubscriptions_total: u64,
// Event metrics
pub events_received_total: u64,
pub graph_execution_events: u64,
pub node_execution_events: u64,
// Redis metrics
pub redis_messages_received: u64,
pub redis_messages_ignored: u64,
// Channel metrics
pub channels_active_count: usize,
pub total_subscribers: usize,
// User metrics
pub active_users_count: usize,
// Error metrics
pub errors_total: u64,
pub errors_json_parse: u64,
pub errors_message_size: u64,
}
impl Stats {
pub async fn snapshot(&self) -> StatsSnapshot {
// Take read locks for HashMap data - it's ok if this is slightly stale
let channels = self.channels_active.read().await;
let total_subscribers: usize = channels.values().sum();
let channels_active_count = channels.len();
drop(channels); // Release lock early
let users = self.active_users.read().await;
let active_users_count = users.len();
drop(users); // Release lock early
StatsSnapshot {
connections_total: self.connections_total.load(Ordering::Relaxed),
connections_active: self.connections_active.load(Ordering::Relaxed),
connections_failed_auth: self.connections_failed_auth.load(Ordering::Relaxed),
messages_received_total: self.messages_received_total.load(Ordering::Relaxed),
messages_sent_total: self.messages_sent_total.load(Ordering::Relaxed),
messages_failed_total: self.messages_failed_total.load(Ordering::Relaxed),
subscriptions_total: self.subscriptions_total.load(Ordering::Relaxed),
subscriptions_active: self.subscriptions_active.load(Ordering::Relaxed),
unsubscriptions_total: self.unsubscriptions_total.load(Ordering::Relaxed),
events_received_total: self.events_received_total.load(Ordering::Relaxed),
graph_execution_events: self.graph_execution_events.load(Ordering::Relaxed),
node_execution_events: self.node_execution_events.load(Ordering::Relaxed),
redis_messages_received: self.redis_messages_received.load(Ordering::Relaxed),
redis_messages_ignored: self.redis_messages_ignored.load(Ordering::Relaxed),
channels_active_count,
total_subscribers,
active_users_count,
errors_total: self.errors_total.load(Ordering::Relaxed),
errors_json_parse: self.errors_json_parse.load(Ordering::Relaxed),
errors_message_size: self.errors_message_size.load(Ordering::Relaxed),
}
}
pub fn to_prometheus_format(&self, snapshot: &StatsSnapshot) -> String {
let mut output = String::new();
// Connection metrics
output.push_str("# HELP ws_connections_total Total number of WebSocket connections\n");
output.push_str("# TYPE ws_connections_total counter\n");
output.push_str(&format!(
"ws_connections_total {}\n\n",
snapshot.connections_total
));
output.push_str(
"# HELP ws_connections_active Current number of active WebSocket connections\n",
);
output.push_str("# TYPE ws_connections_active gauge\n");
output.push_str(&format!(
"ws_connections_active {}\n\n",
snapshot.connections_active
));
output
.push_str("# HELP ws_connections_failed_auth Total number of failed authentications\n");
output.push_str("# TYPE ws_connections_failed_auth counter\n");
output.push_str(&format!(
"ws_connections_failed_auth {}\n\n",
snapshot.connections_failed_auth
));
// Message metrics
output.push_str(
"# HELP ws_messages_received_total Total number of messages received from clients\n",
);
output.push_str("# TYPE ws_messages_received_total counter\n");
output.push_str(&format!(
"ws_messages_received_total {}\n\n",
snapshot.messages_received_total
));
output.push_str("# HELP ws_messages_sent_total Total number of messages sent to clients\n");
output.push_str("# TYPE ws_messages_sent_total counter\n");
output.push_str(&format!(
"ws_messages_sent_total {}\n\n",
snapshot.messages_sent_total
));
// Subscription metrics
output.push_str("# HELP ws_subscriptions_active Current number of active subscriptions\n");
output.push_str("# TYPE ws_subscriptions_active gauge\n");
output.push_str(&format!(
"ws_subscriptions_active {}\n\n",
snapshot.subscriptions_active
));
// Event metrics
output.push_str(
"# HELP ws_events_received_total Total number of events received from Redis\n",
);
output.push_str("# TYPE ws_events_received_total counter\n");
output.push_str(&format!(
"ws_events_received_total {}\n\n",
snapshot.events_received_total
));
output.push_str(
"# HELP ws_graph_execution_events_total Total number of graph execution events\n",
);
output.push_str("# TYPE ws_graph_execution_events_total counter\n");
output.push_str(&format!(
"ws_graph_execution_events_total {}\n\n",
snapshot.graph_execution_events
));
output.push_str(
"# HELP ws_node_execution_events_total Total number of node execution events\n",
);
output.push_str("# TYPE ws_node_execution_events_total counter\n");
output.push_str(&format!(
"ws_node_execution_events_total {}\n\n",
snapshot.node_execution_events
));
// Channel metrics
output.push_str("# HELP ws_channels_active Number of active channels\n");
output.push_str("# TYPE ws_channels_active gauge\n");
output.push_str(&format!(
"ws_channels_active {}\n\n",
snapshot.channels_active_count
));
output.push_str(
"# HELP ws_total_subscribers Total number of subscribers across all channels\n",
);
output.push_str("# TYPE ws_total_subscribers gauge\n");
output.push_str(&format!(
"ws_total_subscribers {}\n\n",
snapshot.total_subscribers
));
// User metrics
output.push_str("# HELP ws_active_users Number of unique users with active connections\n");
output.push_str("# TYPE ws_active_users gauge\n");
output.push_str(&format!(
"ws_active_users {}\n\n",
snapshot.active_users_count
));
// Error metrics
output.push_str("# HELP ws_errors_total Total number of errors\n");
output.push_str("# TYPE ws_errors_total counter\n");
output.push_str(&format!("ws_errors_total {}\n", snapshot.errors_total));
output
}
}

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@@ -0,0 +1,35 @@
import hashlib
import secrets
from typing import NamedTuple
class APIKeyContainer(NamedTuple):
"""Container for API key parts."""
raw: str
prefix: str
postfix: str
hash: str
class APIKeyManager:
PREFIX: str = "agpt_"
PREFIX_LENGTH: int = 8
POSTFIX_LENGTH: int = 8
def generate_api_key(self) -> APIKeyContainer:
"""Generate a new API key with all its parts."""
raw_key = f"{self.PREFIX}{secrets.token_urlsafe(32)}"
return APIKeyContainer(
raw=raw_key,
prefix=raw_key[: self.PREFIX_LENGTH],
postfix=raw_key[-self.POSTFIX_LENGTH :],
hash=hashlib.sha256(raw_key.encode()).hexdigest(),
)
def verify_api_key(self, provided_key: str, stored_hash: str) -> bool:
"""Verify if a provided API key matches the stored hash."""
if not provided_key.startswith(self.PREFIX):
return False
provided_hash = hashlib.sha256(provided_key.encode()).hexdigest()
return secrets.compare_digest(provided_hash, stored_hash)

View File

@@ -1,78 +0,0 @@
import hashlib
import secrets
from typing import NamedTuple
from cryptography.hazmat.primitives.kdf.scrypt import Scrypt
class APIKeyContainer(NamedTuple):
"""Container for API key parts."""
key: str
head: str
tail: str
hash: str
salt: str
class APIKeySmith:
PREFIX: str = "agpt_"
HEAD_LENGTH: int = 8
TAIL_LENGTH: int = 8
def generate_key(self) -> APIKeyContainer:
"""Generate a new API key with secure hashing."""
raw_key = f"{self.PREFIX}{secrets.token_urlsafe(32)}"
hash, salt = self.hash_key(raw_key)
return APIKeyContainer(
key=raw_key,
head=raw_key[: self.HEAD_LENGTH],
tail=raw_key[-self.TAIL_LENGTH :],
hash=hash,
salt=salt,
)
def verify_key(
self, provided_key: str, known_hash: str, known_salt: str | None = None
) -> bool:
"""
Verify an API key against a known hash (+ salt).
Supports verifying both legacy SHA256 and secure Scrypt hashes.
"""
if not provided_key.startswith(self.PREFIX):
return False
# Handle legacy SHA256 hashes (migration support)
if known_salt is None:
legacy_hash = hashlib.sha256(provided_key.encode()).hexdigest()
return secrets.compare_digest(legacy_hash, known_hash)
try:
salt_bytes = bytes.fromhex(known_salt)
provided_hash = self._hash_key_with_salt(provided_key, salt_bytes)
return secrets.compare_digest(provided_hash, known_hash)
except (ValueError, TypeError):
return False
def hash_key(self, raw_key: str) -> tuple[str, str]:
"""Migrate a legacy hash to secure hash format."""
salt = self._generate_salt()
hash = self._hash_key_with_salt(raw_key, salt)
return hash, salt.hex()
def _generate_salt(self) -> bytes:
"""Generate a random salt for hashing."""
return secrets.token_bytes(32)
def _hash_key_with_salt(self, raw_key: str, salt: bytes) -> str:
"""Hash API key using Scrypt with salt."""
kdf = Scrypt(
length=32,
salt=salt,
n=2**14, # CPU/memory cost parameter
r=8, # Block size parameter
p=1, # Parallelization parameter
)
key_hash = kdf.derive(raw_key.encode())
return key_hash.hex()

View File

@@ -1,79 +0,0 @@
import hashlib
from autogpt_libs.api_key.keysmith import APIKeySmith
def test_generate_api_key():
keysmith = APIKeySmith()
key = keysmith.generate_key()
assert key.key.startswith(keysmith.PREFIX)
assert key.head == key.key[: keysmith.HEAD_LENGTH]
assert key.tail == key.key[-keysmith.TAIL_LENGTH :]
assert len(key.hash) == 64 # 32 bytes hex encoded
assert len(key.salt) == 64 # 32 bytes hex encoded
def test_verify_new_secure_key():
keysmith = APIKeySmith()
key = keysmith.generate_key()
# Test correct key validates
assert keysmith.verify_key(key.key, key.hash, key.salt) is True
# Test wrong key fails
wrong_key = f"{keysmith.PREFIX}wrongkey123"
assert keysmith.verify_key(wrong_key, key.hash, key.salt) is False
def test_verify_legacy_key():
keysmith = APIKeySmith()
legacy_key = f"{keysmith.PREFIX}legacykey123"
legacy_hash = hashlib.sha256(legacy_key.encode()).hexdigest()
# Test legacy key validates without salt
assert keysmith.verify_key(legacy_key, legacy_hash) is True
# Test wrong legacy key fails
wrong_key = f"{keysmith.PREFIX}wronglegacy"
assert keysmith.verify_key(wrong_key, legacy_hash) is False
def test_rehash_existing_key():
keysmith = APIKeySmith()
legacy_key = f"{keysmith.PREFIX}migratekey123"
# Migrate the legacy key
new_hash, new_salt = keysmith.hash_key(legacy_key)
# Verify migrated key works
assert keysmith.verify_key(legacy_key, new_hash, new_salt) is True
# Verify different key fails with migrated hash
wrong_key = f"{keysmith.PREFIX}wrongkey"
assert keysmith.verify_key(wrong_key, new_hash, new_salt) is False
def test_invalid_key_prefix():
keysmith = APIKeySmith()
key = keysmith.generate_key()
# Test key without proper prefix fails
invalid_key = "invalid_prefix_key"
assert keysmith.verify_key(invalid_key, key.hash, key.salt) is False
def test_secure_hash_requires_salt():
keysmith = APIKeySmith()
key = keysmith.generate_key()
# Secure hash without salt should fail
assert keysmith.verify_key(key.key, key.hash) is False
def test_invalid_salt_format():
keysmith = APIKeySmith()
key = keysmith.generate_key()
# Invalid salt format should fail gracefully
assert keysmith.verify_key(key.key, key.hash, "invalid_hex") is False

View File

@@ -1,13 +1,13 @@
from .config import verify_settings
from .dependencies import get_user_id, requires_admin_user, requires_user
from .helpers import add_auth_responses_to_openapi
from .depends import requires_admin_user, requires_user
from .jwt_utils import parse_jwt_token
from .middleware import APIKeyValidator, auth_middleware
from .models import User
__all__ = [
"verify_settings",
"get_user_id",
"requires_admin_user",
"parse_jwt_token",
"requires_user",
"add_auth_responses_to_openapi",
"requires_admin_user",
"APIKeyValidator",
"auth_middleware",
"User",
]

View File

@@ -1,90 +1,15 @@
import logging
import os
from jwt.algorithms import get_default_algorithms, has_crypto
logger = logging.getLogger(__name__)
class AuthConfigError(ValueError):
"""Raised when authentication configuration is invalid."""
pass
ALGO_RECOMMENDATION = (
"We highly recommend using an asymmetric algorithm such as ES256, "
"because when leaked, a shared secret would allow anyone to "
"forge valid tokens and impersonate users. "
"More info: https://supabase.com/docs/guides/auth/signing-keys#choosing-the-right-signing-algorithm" # noqa
)
class Settings:
def __init__(self):
self.JWT_VERIFY_KEY: str = os.getenv(
"JWT_VERIFY_KEY", os.getenv("SUPABASE_JWT_SECRET", "")
).strip()
self.JWT_ALGORITHM: str = os.getenv("JWT_SIGN_ALGORITHM", "HS256").strip()
self.JWT_SECRET_KEY: str = os.getenv("SUPABASE_JWT_SECRET", "")
self.ENABLE_AUTH: bool = os.getenv("ENABLE_AUTH", "false").lower() == "true"
self.JWT_ALGORITHM: str = "HS256"
self.validate()
def validate(self):
if not self.JWT_VERIFY_KEY:
raise AuthConfigError(
"JWT_VERIFY_KEY must be set. "
"An empty JWT secret would allow anyone to forge valid tokens."
)
if len(self.JWT_VERIFY_KEY) < 32:
logger.warning(
"⚠️ JWT_VERIFY_KEY appears weak (less than 32 characters). "
"Consider using a longer, cryptographically secure secret."
)
supported_algorithms = get_default_algorithms().keys()
if not has_crypto:
logger.warning(
"⚠️ Asymmetric JWT verification is not available "
"because the 'cryptography' package is not installed. "
+ ALGO_RECOMMENDATION
)
if (
self.JWT_ALGORITHM not in supported_algorithms
or self.JWT_ALGORITHM == "none"
):
raise AuthConfigError(
f"Invalid JWT_SIGN_ALGORITHM: '{self.JWT_ALGORITHM}'. "
"Supported algorithms are listed on "
"https://pyjwt.readthedocs.io/en/stable/algorithms.html"
)
if self.JWT_ALGORITHM.startswith("HS"):
logger.warning(
f"⚠️ JWT_SIGN_ALGORITHM is set to '{self.JWT_ALGORITHM}', "
"a symmetric shared-key signature algorithm. " + ALGO_RECOMMENDATION
)
@property
def is_configured(self) -> bool:
return bool(self.JWT_SECRET_KEY)
_settings: Settings = None # type: ignore
def get_settings() -> Settings:
global _settings
if not _settings:
_settings = Settings()
return _settings
def verify_settings() -> None:
global _settings
if not _settings:
_settings = Settings() # calls validation indirectly
return
_settings.validate()
settings = Settings()

View File

@@ -1,306 +0,0 @@
"""
Comprehensive tests for auth configuration to ensure 100% line and branch coverage.
These tests verify critical security checks preventing JWT token forgery.
"""
import logging
import os
import pytest
from pytest_mock import MockerFixture
from autogpt_libs.auth.config import AuthConfigError, Settings
def test_environment_variable_precedence(mocker: MockerFixture):
"""Test that environment variables take precedence over defaults."""
secret = "environment-secret-key-with-proper-length-123456"
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": secret}, clear=True)
settings = Settings()
assert settings.JWT_VERIFY_KEY == secret
def test_environment_variable_backwards_compatible(mocker: MockerFixture):
"""Test that SUPABASE_JWT_SECRET is read if JWT_VERIFY_KEY is not set."""
secret = "environment-secret-key-with-proper-length-123456"
mocker.patch.dict(os.environ, {"SUPABASE_JWT_SECRET": secret}, clear=True)
settings = Settings()
assert settings.JWT_VERIFY_KEY == secret
def test_auth_config_error_inheritance():
"""Test that AuthConfigError is properly defined as an Exception."""
assert issubclass(AuthConfigError, Exception)
error = AuthConfigError("test message")
assert str(error) == "test message"
def test_settings_static_after_creation(mocker: MockerFixture):
"""Test that settings maintain their values after creation."""
secret = "immutable-secret-key-with-proper-length-12345"
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": secret}, clear=True)
settings = Settings()
original_secret = settings.JWT_VERIFY_KEY
# Changing environment after creation shouldn't affect settings
os.environ["JWT_VERIFY_KEY"] = "different-secret"
assert settings.JWT_VERIFY_KEY == original_secret
def test_settings_load_with_valid_secret(mocker: MockerFixture):
"""Test auth enabled with a valid JWT secret."""
valid_secret = "a" * 32 # 32 character secret
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": valid_secret}, clear=True)
settings = Settings()
assert settings.JWT_VERIFY_KEY == valid_secret
def test_settings_load_with_strong_secret(mocker: MockerFixture):
"""Test auth enabled with a cryptographically strong secret."""
strong_secret = "super-secret-jwt-token-with-at-least-32-characters-long"
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": strong_secret}, clear=True)
settings = Settings()
assert settings.JWT_VERIFY_KEY == strong_secret
assert len(settings.JWT_VERIFY_KEY) >= 32
def test_secret_empty_raises_error(mocker: MockerFixture):
"""Test that auth enabled with empty secret raises AuthConfigError."""
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": ""}, clear=True)
with pytest.raises(Exception) as exc_info:
Settings()
assert "JWT_VERIFY_KEY" in str(exc_info.value)
def test_secret_missing_raises_error(mocker: MockerFixture):
"""Test that auth enabled without secret env var raises AuthConfigError."""
mocker.patch.dict(os.environ, {}, clear=True)
with pytest.raises(Exception) as exc_info:
Settings()
assert "JWT_VERIFY_KEY" in str(exc_info.value)
@pytest.mark.parametrize("secret", [" ", " ", "\t", "\n", " \t\n "])
def test_secret_only_whitespace_raises_error(mocker: MockerFixture, secret: str):
"""Test that auth enabled with whitespace-only secret raises error."""
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": secret}, clear=True)
with pytest.raises(ValueError):
Settings()
def test_secret_weak_logs_warning(
mocker: MockerFixture, caplog: pytest.LogCaptureFixture
):
"""Test that weak JWT secret triggers warning log."""
weak_secret = "short" # Less than 32 characters
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": weak_secret}, clear=True)
with caplog.at_level(logging.WARNING):
settings = Settings()
assert settings.JWT_VERIFY_KEY == weak_secret
assert "key appears weak" in caplog.text.lower()
assert "less than 32 characters" in caplog.text
def test_secret_31_char_logs_warning(
mocker: MockerFixture, caplog: pytest.LogCaptureFixture
):
"""Test that 31-character secret triggers warning (boundary test)."""
secret_31 = "a" * 31 # Exactly 31 characters
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": secret_31}, clear=True)
with caplog.at_level(logging.WARNING):
settings = Settings()
assert len(settings.JWT_VERIFY_KEY) == 31
assert "key appears weak" in caplog.text.lower()
def test_secret_32_char_no_warning(
mocker: MockerFixture, caplog: pytest.LogCaptureFixture
):
"""Test that 32-character secret does not trigger warning (boundary test)."""
secret_32 = "a" * 32 # Exactly 32 characters
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": secret_32}, clear=True)
with caplog.at_level(logging.WARNING):
settings = Settings()
assert len(settings.JWT_VERIFY_KEY) == 32
assert "JWT secret appears weak" not in caplog.text
def test_secret_whitespace_stripped(mocker: MockerFixture):
"""Test that JWT secret whitespace is stripped."""
secret = "a" * 32
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": f" {secret} "}, clear=True)
settings = Settings()
assert settings.JWT_VERIFY_KEY == secret
def test_secret_with_special_characters(mocker: MockerFixture):
"""Test JWT secret with special characters."""
special_secret = "!@#$%^&*()_+-=[]{}|;:,.<>?`~" + "a" * 10 # 40 chars total
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": special_secret}, clear=True)
settings = Settings()
assert settings.JWT_VERIFY_KEY == special_secret
def test_secret_with_unicode(mocker: MockerFixture):
"""Test JWT secret with unicode characters."""
unicode_secret = "秘密🔐キー" + "a" * 25 # Ensure >32 bytes
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": unicode_secret}, clear=True)
settings = Settings()
assert settings.JWT_VERIFY_KEY == unicode_secret
def test_secret_very_long(mocker: MockerFixture):
"""Test JWT secret with excessive length."""
long_secret = "a" * 1000 # 1000 character secret
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": long_secret}, clear=True)
settings = Settings()
assert settings.JWT_VERIFY_KEY == long_secret
assert len(settings.JWT_VERIFY_KEY) == 1000
def test_secret_with_newline(mocker: MockerFixture):
"""Test JWT secret containing newlines."""
multiline_secret = "secret\nwith\nnewlines" + "a" * 20
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": multiline_secret}, clear=True)
settings = Settings()
assert settings.JWT_VERIFY_KEY == multiline_secret
def test_secret_base64_encoded(mocker: MockerFixture):
"""Test JWT secret that looks like base64."""
base64_secret = "dGhpc19pc19hX3NlY3JldF9rZXlfd2l0aF9wcm9wZXJfbGVuZ3Ro"
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": base64_secret}, clear=True)
settings = Settings()
assert settings.JWT_VERIFY_KEY == base64_secret
def test_secret_numeric_only(mocker: MockerFixture):
"""Test JWT secret with only numbers."""
numeric_secret = "1234567890" * 4 # 40 character numeric secret
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": numeric_secret}, clear=True)
settings = Settings()
assert settings.JWT_VERIFY_KEY == numeric_secret
def test_algorithm_default_hs256(mocker: MockerFixture):
"""Test that JWT algorithm defaults to HS256."""
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": "a" * 32}, clear=True)
settings = Settings()
assert settings.JWT_ALGORITHM == "HS256"
def test_algorithm_whitespace_stripped(mocker: MockerFixture):
"""Test that JWT algorithm whitespace is stripped."""
secret = "a" * 32
mocker.patch.dict(
os.environ,
{"JWT_VERIFY_KEY": secret, "JWT_SIGN_ALGORITHM": " HS256 "},
clear=True,
)
settings = Settings()
assert settings.JWT_ALGORITHM == "HS256"
def test_no_crypto_warning(mocker: MockerFixture, caplog: pytest.LogCaptureFixture):
"""Test warning when crypto package is not available."""
secret = "a" * 32
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": secret}, clear=True)
# Mock has_crypto to return False
mocker.patch("autogpt_libs.auth.config.has_crypto", False)
with caplog.at_level(logging.WARNING):
Settings()
assert "Asymmetric JWT verification is not available" in caplog.text
assert "cryptography" in caplog.text
def test_algorithm_invalid_raises_error(mocker: MockerFixture):
"""Test that invalid JWT algorithm raises AuthConfigError."""
secret = "a" * 32
mocker.patch.dict(
os.environ,
{"JWT_VERIFY_KEY": secret, "JWT_SIGN_ALGORITHM": "INVALID_ALG"},
clear=True,
)
with pytest.raises(AuthConfigError) as exc_info:
Settings()
assert "Invalid JWT_SIGN_ALGORITHM" in str(exc_info.value)
assert "INVALID_ALG" in str(exc_info.value)
def test_algorithm_none_raises_error(mocker: MockerFixture):
"""Test that 'none' algorithm raises AuthConfigError."""
secret = "a" * 32
mocker.patch.dict(
os.environ,
{"JWT_VERIFY_KEY": secret, "JWT_SIGN_ALGORITHM": "none"},
clear=True,
)
with pytest.raises(AuthConfigError) as exc_info:
Settings()
assert "Invalid JWT_SIGN_ALGORITHM" in str(exc_info.value)
@pytest.mark.parametrize("algorithm", ["HS256", "HS384", "HS512"])
def test_algorithm_symmetric_warning(
mocker: MockerFixture, caplog: pytest.LogCaptureFixture, algorithm: str
):
"""Test warning for symmetric algorithms (HS256, HS384, HS512)."""
secret = "a" * 32
mocker.patch.dict(
os.environ,
{"JWT_VERIFY_KEY": secret, "JWT_SIGN_ALGORITHM": algorithm},
clear=True,
)
with caplog.at_level(logging.WARNING):
settings = Settings()
assert algorithm in caplog.text
assert "symmetric shared-key signature algorithm" in caplog.text
assert settings.JWT_ALGORITHM == algorithm
@pytest.mark.parametrize(
"algorithm",
["ES256", "ES384", "ES512", "RS256", "RS384", "RS512", "PS256", "PS384", "PS512"],
)
def test_algorithm_asymmetric_no_warning(
mocker: MockerFixture, caplog: pytest.LogCaptureFixture, algorithm: str
):
"""Test that asymmetric algorithms do not trigger warning."""
secret = "a" * 32
mocker.patch.dict(
os.environ,
{"JWT_VERIFY_KEY": secret, "JWT_SIGN_ALGORITHM": algorithm},
clear=True,
)
with caplog.at_level(logging.WARNING):
settings = Settings()
# Should not contain the symmetric algorithm warning
assert "symmetric shared-key signature algorithm" not in caplog.text
assert settings.JWT_ALGORITHM == algorithm

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@@ -1,45 +0,0 @@
"""
FastAPI dependency functions for JWT-based authentication and authorization.
These are the high-level dependency functions used in route definitions.
"""
import fastapi
from .jwt_utils import get_jwt_payload, verify_user
from .models import User
def requires_user(jwt_payload: dict = fastapi.Security(get_jwt_payload)) -> User:
"""
FastAPI dependency that requires a valid authenticated user.
Raises:
HTTPException: 401 for authentication failures
"""
return verify_user(jwt_payload, admin_only=False)
def requires_admin_user(jwt_payload: dict = fastapi.Security(get_jwt_payload)) -> User:
"""
FastAPI dependency that requires a valid admin user.
Raises:
HTTPException: 401 for authentication failures, 403 for insufficient permissions
"""
return verify_user(jwt_payload, admin_only=True)
def get_user_id(jwt_payload: dict = fastapi.Security(get_jwt_payload)) -> str:
"""
FastAPI dependency that returns the ID of the authenticated user.
Raises:
HTTPException: 401 for authentication failures or missing user ID
"""
user_id = jwt_payload.get("sub")
if not user_id:
raise fastapi.HTTPException(
status_code=401, detail="User ID not found in token"
)
return user_id

View File

@@ -1,335 +0,0 @@
"""
Comprehensive integration tests for authentication dependencies.
Tests the full authentication flow from HTTP requests to user validation.
"""
import os
import pytest
from fastapi import FastAPI, HTTPException, Security
from fastapi.testclient import TestClient
from pytest_mock import MockerFixture
from autogpt_libs.auth.dependencies import (
get_user_id,
requires_admin_user,
requires_user,
)
from autogpt_libs.auth.models import User
class TestAuthDependencies:
"""Test suite for authentication dependency functions."""
@pytest.fixture
def app(self):
"""Create a test FastAPI application."""
app = FastAPI()
@app.get("/user")
def get_user_endpoint(user: User = Security(requires_user)):
return {"user_id": user.user_id, "role": user.role}
@app.get("/admin")
def get_admin_endpoint(user: User = Security(requires_admin_user)):
return {"user_id": user.user_id, "role": user.role}
@app.get("/user-id")
def get_user_id_endpoint(user_id: str = Security(get_user_id)):
return {"user_id": user_id}
return app
@pytest.fixture
def client(self, app):
"""Create a test client."""
return TestClient(app)
def test_requires_user_with_valid_jwt_payload(self, mocker: MockerFixture):
"""Test requires_user with valid JWT payload."""
jwt_payload = {"sub": "user-123", "role": "user", "email": "user@example.com"}
# Mock get_jwt_payload to return our test payload
mocker.patch(
"autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
)
user = requires_user(jwt_payload)
assert isinstance(user, User)
assert user.user_id == "user-123"
assert user.role == "user"
def test_requires_user_with_admin_jwt_payload(self, mocker: MockerFixture):
"""Test requires_user accepts admin users."""
jwt_payload = {
"sub": "admin-456",
"role": "admin",
"email": "admin@example.com",
}
mocker.patch(
"autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
)
user = requires_user(jwt_payload)
assert user.user_id == "admin-456"
assert user.role == "admin"
def test_requires_user_missing_sub(self):
"""Test requires_user with missing user ID."""
jwt_payload = {"role": "user", "email": "user@example.com"}
with pytest.raises(HTTPException) as exc_info:
requires_user(jwt_payload)
assert exc_info.value.status_code == 401
assert "User ID not found" in exc_info.value.detail
def test_requires_user_empty_sub(self):
"""Test requires_user with empty user ID."""
jwt_payload = {"sub": "", "role": "user"}
with pytest.raises(HTTPException) as exc_info:
requires_user(jwt_payload)
assert exc_info.value.status_code == 401
def test_requires_admin_user_with_admin(self, mocker: MockerFixture):
"""Test requires_admin_user with admin role."""
jwt_payload = {
"sub": "admin-789",
"role": "admin",
"email": "admin@example.com",
}
mocker.patch(
"autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
)
user = requires_admin_user(jwt_payload)
assert user.user_id == "admin-789"
assert user.role == "admin"
def test_requires_admin_user_with_regular_user(self):
"""Test requires_admin_user rejects regular users."""
jwt_payload = {"sub": "user-123", "role": "user", "email": "user@example.com"}
with pytest.raises(HTTPException) as exc_info:
requires_admin_user(jwt_payload)
assert exc_info.value.status_code == 403
assert "Admin access required" in exc_info.value.detail
def test_requires_admin_user_missing_role(self):
"""Test requires_admin_user with missing role."""
jwt_payload = {"sub": "user-123", "email": "user@example.com"}
with pytest.raises(KeyError):
requires_admin_user(jwt_payload)
def test_get_user_id_with_valid_payload(self, mocker: MockerFixture):
"""Test get_user_id extracts user ID correctly."""
jwt_payload = {"sub": "user-id-xyz", "role": "user"}
mocker.patch(
"autogpt_libs.auth.dependencies.get_jwt_payload", return_value=jwt_payload
)
user_id = get_user_id(jwt_payload)
assert user_id == "user-id-xyz"
def test_get_user_id_missing_sub(self):
"""Test get_user_id with missing user ID."""
jwt_payload = {"role": "user"}
with pytest.raises(HTTPException) as exc_info:
get_user_id(jwt_payload)
assert exc_info.value.status_code == 401
assert "User ID not found" in exc_info.value.detail
def test_get_user_id_none_sub(self):
"""Test get_user_id with None user ID."""
jwt_payload = {"sub": None, "role": "user"}
with pytest.raises(HTTPException) as exc_info:
get_user_id(jwt_payload)
assert exc_info.value.status_code == 401
class TestAuthDependenciesIntegration:
"""Integration tests for auth dependencies with FastAPI."""
acceptable_jwt_secret = "test-secret-with-proper-length-123456"
@pytest.fixture
def create_token(self, mocker: MockerFixture):
"""Helper to create JWT tokens."""
import jwt
mocker.patch.dict(
os.environ,
{"JWT_VERIFY_KEY": self.acceptable_jwt_secret},
clear=True,
)
def _create_token(payload, secret=self.acceptable_jwt_secret):
return jwt.encode(payload, secret, algorithm="HS256")
return _create_token
def test_endpoint_auth_enabled_no_token(self):
"""Test endpoints require token when auth is enabled."""
app = FastAPI()
@app.get("/test")
def test_endpoint(user: User = Security(requires_user)):
return {"user_id": user.user_id}
client = TestClient(app)
# Should fail without auth header
response = client.get("/test")
assert response.status_code == 401
def test_endpoint_with_valid_token(self, create_token):
"""Test endpoint with valid JWT token."""
app = FastAPI()
@app.get("/test")
def test_endpoint(user: User = Security(requires_user)):
return {"user_id": user.user_id, "role": user.role}
client = TestClient(app)
token = create_token(
{"sub": "test-user", "role": "user", "aud": "authenticated"},
secret=self.acceptable_jwt_secret,
)
response = client.get("/test", headers={"Authorization": f"Bearer {token}"})
assert response.status_code == 200
assert response.json()["user_id"] == "test-user"
def test_admin_endpoint_requires_admin_role(self, create_token):
"""Test admin endpoint rejects non-admin users."""
app = FastAPI()
@app.get("/admin")
def admin_endpoint(user: User = Security(requires_admin_user)):
return {"user_id": user.user_id}
client = TestClient(app)
# Regular user token
user_token = create_token(
{"sub": "regular-user", "role": "user", "aud": "authenticated"},
secret=self.acceptable_jwt_secret,
)
response = client.get(
"/admin", headers={"Authorization": f"Bearer {user_token}"}
)
assert response.status_code == 403
# Admin token
admin_token = create_token(
{"sub": "admin-user", "role": "admin", "aud": "authenticated"},
secret=self.acceptable_jwt_secret,
)
response = client.get(
"/admin", headers={"Authorization": f"Bearer {admin_token}"}
)
assert response.status_code == 200
assert response.json()["user_id"] == "admin-user"
class TestAuthDependenciesEdgeCases:
"""Edge case tests for authentication dependencies."""
def test_dependency_with_complex_payload(self):
"""Test dependencies handle complex JWT payloads."""
complex_payload = {
"sub": "user-123",
"role": "admin",
"email": "test@example.com",
"app_metadata": {"provider": "email", "providers": ["email"]},
"user_metadata": {
"full_name": "Test User",
"avatar_url": "https://example.com/avatar.jpg",
},
"aud": "authenticated",
"iat": 1234567890,
"exp": 9999999999,
}
user = requires_user(complex_payload)
assert user.user_id == "user-123"
assert user.email == "test@example.com"
admin = requires_admin_user(complex_payload)
assert admin.role == "admin"
def test_dependency_with_unicode_in_payload(self):
"""Test dependencies handle unicode in JWT payloads."""
unicode_payload = {
"sub": "user-😀-123",
"role": "user",
"email": "测试@example.com",
"name": "日本語",
}
user = requires_user(unicode_payload)
assert "😀" in user.user_id
assert user.email == "测试@example.com"
def test_dependency_with_null_values(self):
"""Test dependencies handle null values in payload."""
null_payload = {
"sub": "user-123",
"role": "user",
"email": None,
"phone": None,
"metadata": None,
}
user = requires_user(null_payload)
assert user.user_id == "user-123"
assert user.email is None
def test_concurrent_requests_isolation(self):
"""Test that concurrent requests don't interfere with each other."""
payload1 = {"sub": "user-1", "role": "user"}
payload2 = {"sub": "user-2", "role": "admin"}
# Simulate concurrent processing
user1 = requires_user(payload1)
user2 = requires_admin_user(payload2)
assert user1.user_id == "user-1"
assert user2.user_id == "user-2"
assert user1.role == "user"
assert user2.role == "admin"
@pytest.mark.parametrize(
"payload,expected_error,admin_only",
[
(None, "Authorization header is missing", False),
({}, "User ID not found", False),
({"sub": ""}, "User ID not found", False),
({"role": "user"}, "User ID not found", False),
({"sub": "user", "role": "user"}, "Admin access required", True),
],
)
def test_dependency_error_cases(
self, payload, expected_error: str, admin_only: bool
):
"""Test that errors propagate correctly through dependencies."""
# Import verify_user to test it directly since dependencies use FastAPI Security
from autogpt_libs.auth.jwt_utils import verify_user
with pytest.raises(HTTPException) as exc_info:
verify_user(payload, admin_only=admin_only)
assert expected_error in exc_info.value.detail
def test_dependency_valid_user(self):
"""Test valid user case for dependency."""
# Import verify_user to test it directly since dependencies use FastAPI Security
from autogpt_libs.auth.jwt_utils import verify_user
# Valid case
user = verify_user({"sub": "user", "role": "user"}, admin_only=False)
assert user.user_id == "user"

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@@ -0,0 +1,46 @@
import fastapi
from .config import settings
from .middleware import auth_middleware
from .models import DEFAULT_USER_ID, User
def requires_user(payload: dict = fastapi.Depends(auth_middleware)) -> User:
return verify_user(payload, admin_only=False)
def requires_admin_user(
payload: dict = fastapi.Depends(auth_middleware),
) -> User:
return verify_user(payload, admin_only=True)
def verify_user(payload: dict | None, admin_only: bool) -> User:
if not payload:
if settings.ENABLE_AUTH:
raise fastapi.HTTPException(
status_code=401, detail="Authorization header is missing"
)
# This handles the case when authentication is disabled
payload = {"sub": DEFAULT_USER_ID, "role": "admin"}
user_id = payload.get("sub")
if not user_id:
raise fastapi.HTTPException(
status_code=401, detail="User ID not found in token"
)
if admin_only and payload["role"] != "admin":
raise fastapi.HTTPException(status_code=403, detail="Admin access required")
return User.from_payload(payload)
def get_user_id(payload: dict = fastapi.Depends(auth_middleware)) -> str:
user_id = payload.get("sub")
if not user_id:
raise fastapi.HTTPException(
status_code=401, detail="User ID not found in token"
)
return user_id

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@@ -0,0 +1,68 @@
import pytest
from .depends import requires_admin_user, requires_user, verify_user
def test_verify_user_no_payload():
user = verify_user(None, admin_only=False)
assert user.user_id == "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
assert user.role == "admin"
def test_verify_user_no_user_id():
with pytest.raises(Exception):
verify_user({"role": "admin"}, admin_only=False)
def test_verify_user_not_admin():
with pytest.raises(Exception):
verify_user(
{"sub": "3e53486c-cf57-477e-ba2a-cb02dc828e1a", "role": "user"},
admin_only=True,
)
def test_verify_user_with_admin_role():
user = verify_user(
{"sub": "3e53486c-cf57-477e-ba2a-cb02dc828e1a", "role": "admin"},
admin_only=True,
)
assert user.user_id == "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
assert user.role == "admin"
def test_verify_user_with_user_role():
user = verify_user(
{"sub": "3e53486c-cf57-477e-ba2a-cb02dc828e1a", "role": "user"},
admin_only=False,
)
assert user.user_id == "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
assert user.role == "user"
def test_requires_user():
user = requires_user(
{"sub": "3e53486c-cf57-477e-ba2a-cb02dc828e1a", "role": "user"}
)
assert user.user_id == "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
assert user.role == "user"
def test_requires_user_no_user_id():
with pytest.raises(Exception):
requires_user({"role": "user"})
def test_requires_admin_user():
user = requires_admin_user(
{"sub": "3e53486c-cf57-477e-ba2a-cb02dc828e1a", "role": "admin"}
)
assert user.user_id == "3e53486c-cf57-477e-ba2a-cb02dc828e1a"
assert user.role == "admin"
def test_requires_admin_user_not_admin():
with pytest.raises(Exception):
requires_admin_user(
{"sub": "3e53486c-cf57-477e-ba2a-cb02dc828e1a", "role": "user"}
)

View File

@@ -1,68 +0,0 @@
from fastapi import FastAPI
from fastapi.openapi.utils import get_openapi
from .jwt_utils import bearer_jwt_auth
def add_auth_responses_to_openapi(app: FastAPI) -> None:
"""
Set up custom OpenAPI schema generation that adds 401 responses
to all authenticated endpoints.
This is needed when using HTTPBearer with auto_error=False to get proper
401 responses instead of 403, but FastAPI only automatically adds security
responses when auto_error=True.
"""
def custom_openapi():
if app.openapi_schema:
return app.openapi_schema
openapi_schema = get_openapi(
title=app.title,
version=app.version,
description=app.description,
routes=app.routes,
)
# Add 401 response to all endpoints that have security requirements
for path, methods in openapi_schema["paths"].items():
for method, details in methods.items():
security_schemas = [
schema
for auth_option in details.get("security", [])
for schema in auth_option.keys()
]
if bearer_jwt_auth.scheme_name not in security_schemas:
continue
if "responses" not in details:
details["responses"] = {}
details["responses"]["401"] = {
"$ref": "#/components/responses/HTTP401NotAuthenticatedError"
}
# Ensure #/components/responses exists
if "components" not in openapi_schema:
openapi_schema["components"] = {}
if "responses" not in openapi_schema["components"]:
openapi_schema["components"]["responses"] = {}
# Define 401 response
openapi_schema["components"]["responses"]["HTTP401NotAuthenticatedError"] = {
"description": "Authentication required",
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {"detail": {"type": "string"}},
}
}
},
}
app.openapi_schema = openapi_schema
return app.openapi_schema
app.openapi = custom_openapi

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@@ -1,435 +0,0 @@
"""
Comprehensive tests for auth helpers module to achieve 100% coverage.
Tests OpenAPI schema generation and authentication response handling.
"""
from unittest import mock
from fastapi import FastAPI
from fastapi.openapi.utils import get_openapi
from autogpt_libs.auth.helpers import add_auth_responses_to_openapi
from autogpt_libs.auth.jwt_utils import bearer_jwt_auth
def test_add_auth_responses_to_openapi_basic():
"""Test adding 401 responses to OpenAPI schema."""
app = FastAPI(title="Test App", version="1.0.0")
# Add some test endpoints with authentication
from fastapi import Depends
from autogpt_libs.auth.dependencies import requires_user
@app.get("/protected", dependencies=[Depends(requires_user)])
def protected_endpoint():
return {"message": "Protected"}
@app.get("/public")
def public_endpoint():
return {"message": "Public"}
# Apply the OpenAPI customization
add_auth_responses_to_openapi(app)
# Get the OpenAPI schema
schema = app.openapi()
# Verify basic schema properties
assert schema["info"]["title"] == "Test App"
assert schema["info"]["version"] == "1.0.0"
# Verify 401 response component is added
assert "components" in schema
assert "responses" in schema["components"]
assert "HTTP401NotAuthenticatedError" in schema["components"]["responses"]
# Verify 401 response structure
error_response = schema["components"]["responses"]["HTTP401NotAuthenticatedError"]
assert error_response["description"] == "Authentication required"
assert "application/json" in error_response["content"]
assert "schema" in error_response["content"]["application/json"]
# Verify schema properties
response_schema = error_response["content"]["application/json"]["schema"]
assert response_schema["type"] == "object"
assert "detail" in response_schema["properties"]
assert response_schema["properties"]["detail"]["type"] == "string"
def test_add_auth_responses_to_openapi_with_security():
"""Test that 401 responses are added only to secured endpoints."""
app = FastAPI()
# Mock endpoint with security
from fastapi import Security
from autogpt_libs.auth.dependencies import get_user_id
@app.get("/secured")
def secured_endpoint(user_id: str = Security(get_user_id)):
return {"user_id": user_id}
@app.post("/also-secured")
def another_secured(user_id: str = Security(get_user_id)):
return {"status": "ok"}
@app.get("/unsecured")
def unsecured_endpoint():
return {"public": True}
# Apply OpenAPI customization
add_auth_responses_to_openapi(app)
# Get schema
schema = app.openapi()
# Check that secured endpoints have 401 responses
if "/secured" in schema["paths"]:
if "get" in schema["paths"]["/secured"]:
secured_get = schema["paths"]["/secured"]["get"]
if "responses" in secured_get:
assert "401" in secured_get["responses"]
assert (
secured_get["responses"]["401"]["$ref"]
== "#/components/responses/HTTP401NotAuthenticatedError"
)
if "/also-secured" in schema["paths"]:
if "post" in schema["paths"]["/also-secured"]:
secured_post = schema["paths"]["/also-secured"]["post"]
if "responses" in secured_post:
assert "401" in secured_post["responses"]
# Check that unsecured endpoint does not have 401 response
if "/unsecured" in schema["paths"]:
if "get" in schema["paths"]["/unsecured"]:
unsecured_get = schema["paths"]["/unsecured"]["get"]
if "responses" in unsecured_get:
assert "401" not in unsecured_get.get("responses", {})
def test_add_auth_responses_to_openapi_cached_schema():
"""Test that OpenAPI schema is cached after first generation."""
app = FastAPI()
# Apply customization
add_auth_responses_to_openapi(app)
# Get schema twice
schema1 = app.openapi()
schema2 = app.openapi()
# Should return the same cached object
assert schema1 is schema2
def test_add_auth_responses_to_openapi_existing_responses():
"""Test handling endpoints that already have responses defined."""
app = FastAPI()
from fastapi import Security
from autogpt_libs.auth.jwt_utils import get_jwt_payload
@app.get(
"/with-responses",
responses={
200: {"description": "Success"},
404: {"description": "Not found"},
},
)
def endpoint_with_responses(jwt: dict = Security(get_jwt_payload)):
return {"data": "test"}
# Apply customization
add_auth_responses_to_openapi(app)
schema = app.openapi()
# Check that existing responses are preserved and 401 is added
if "/with-responses" in schema["paths"]:
if "get" in schema["paths"]["/with-responses"]:
responses = schema["paths"]["/with-responses"]["get"].get("responses", {})
# Original responses should be preserved
if "200" in responses:
assert responses["200"]["description"] == "Success"
if "404" in responses:
assert responses["404"]["description"] == "Not found"
# 401 should be added
if "401" in responses:
assert (
responses["401"]["$ref"]
== "#/components/responses/HTTP401NotAuthenticatedError"
)
def test_add_auth_responses_to_openapi_no_security_endpoints():
"""Test with app that has no secured endpoints."""
app = FastAPI()
@app.get("/public1")
def public1():
return {"message": "public1"}
@app.post("/public2")
def public2():
return {"message": "public2"}
# Apply customization
add_auth_responses_to_openapi(app)
schema = app.openapi()
# Component should still be added for consistency
assert "HTTP401NotAuthenticatedError" in schema["components"]["responses"]
# But no endpoints should have 401 responses
for path in schema["paths"].values():
for method in path.values():
if isinstance(method, dict) and "responses" in method:
assert "401" not in method["responses"]
def test_add_auth_responses_to_openapi_multiple_security_schemes():
"""Test endpoints with multiple security requirements."""
app = FastAPI()
from fastapi import Security
from autogpt_libs.auth.dependencies import requires_admin_user, requires_user
from autogpt_libs.auth.models import User
@app.get("/multi-auth")
def multi_auth(
user: User = Security(requires_user),
admin: User = Security(requires_admin_user),
):
return {"status": "super secure"}
# Apply customization
add_auth_responses_to_openapi(app)
schema = app.openapi()
# Should have 401 response
if "/multi-auth" in schema["paths"]:
if "get" in schema["paths"]["/multi-auth"]:
responses = schema["paths"]["/multi-auth"]["get"].get("responses", {})
if "401" in responses:
assert (
responses["401"]["$ref"]
== "#/components/responses/HTTP401NotAuthenticatedError"
)
def test_add_auth_responses_to_openapi_empty_components():
"""Test when OpenAPI schema has no components section initially."""
app = FastAPI()
# Mock get_openapi to return schema without components
original_get_openapi = get_openapi
def mock_get_openapi(*args, **kwargs):
schema = original_get_openapi(*args, **kwargs)
# Remove components if it exists
if "components" in schema:
del schema["components"]
return schema
with mock.patch("autogpt_libs.auth.helpers.get_openapi", mock_get_openapi):
# Apply customization
add_auth_responses_to_openapi(app)
schema = app.openapi()
# Components should be created
assert "components" in schema
assert "responses" in schema["components"]
assert "HTTP401NotAuthenticatedError" in schema["components"]["responses"]
def test_add_auth_responses_to_openapi_all_http_methods():
"""Test that all HTTP methods are handled correctly."""
app = FastAPI()
from fastapi import Security
from autogpt_libs.auth.jwt_utils import get_jwt_payload
@app.get("/resource")
def get_resource(jwt: dict = Security(get_jwt_payload)):
return {"method": "GET"}
@app.post("/resource")
def post_resource(jwt: dict = Security(get_jwt_payload)):
return {"method": "POST"}
@app.put("/resource")
def put_resource(jwt: dict = Security(get_jwt_payload)):
return {"method": "PUT"}
@app.patch("/resource")
def patch_resource(jwt: dict = Security(get_jwt_payload)):
return {"method": "PATCH"}
@app.delete("/resource")
def delete_resource(jwt: dict = Security(get_jwt_payload)):
return {"method": "DELETE"}
# Apply customization
add_auth_responses_to_openapi(app)
schema = app.openapi()
# All methods should have 401 response
if "/resource" in schema["paths"]:
for method in ["get", "post", "put", "patch", "delete"]:
if method in schema["paths"]["/resource"]:
method_spec = schema["paths"]["/resource"][method]
if "responses" in method_spec:
assert "401" in method_spec["responses"]
def test_bearer_jwt_auth_scheme_config():
"""Test that bearer_jwt_auth is configured correctly."""
assert bearer_jwt_auth.scheme_name == "HTTPBearerJWT"
assert bearer_jwt_auth.auto_error is False
def test_add_auth_responses_with_no_routes():
"""Test OpenAPI generation with app that has no routes."""
app = FastAPI(title="Empty App")
# Apply customization to empty app
add_auth_responses_to_openapi(app)
schema = app.openapi()
# Should still have basic structure
assert schema["info"]["title"] == "Empty App"
assert "components" in schema
assert "responses" in schema["components"]
assert "HTTP401NotAuthenticatedError" in schema["components"]["responses"]
def test_custom_openapi_function_replacement():
"""Test that the custom openapi function properly replaces the default."""
app = FastAPI()
# Store original function
original_openapi = app.openapi
# Apply customization
add_auth_responses_to_openapi(app)
# Function should be replaced
assert app.openapi != original_openapi
assert callable(app.openapi)
def test_endpoint_without_responses_section():
"""Test endpoint that has security but no responses section initially."""
app = FastAPI()
from fastapi import Security
from fastapi.openapi.utils import get_openapi as original_get_openapi
from autogpt_libs.auth.jwt_utils import get_jwt_payload
# Create endpoint
@app.get("/no-responses")
def endpoint_without_responses(jwt: dict = Security(get_jwt_payload)):
return {"data": "test"}
# Mock get_openapi to remove responses from the endpoint
def mock_get_openapi(*args, **kwargs):
schema = original_get_openapi(*args, **kwargs)
# Remove responses from our endpoint to trigger line 40
if "/no-responses" in schema.get("paths", {}):
if "get" in schema["paths"]["/no-responses"]:
# Delete responses to force the code to create it
if "responses" in schema["paths"]["/no-responses"]["get"]:
del schema["paths"]["/no-responses"]["get"]["responses"]
return schema
with mock.patch("autogpt_libs.auth.helpers.get_openapi", mock_get_openapi):
# Apply customization
add_auth_responses_to_openapi(app)
# Get schema and verify 401 was added
schema = app.openapi()
# The endpoint should now have 401 response
if "/no-responses" in schema["paths"]:
if "get" in schema["paths"]["/no-responses"]:
responses = schema["paths"]["/no-responses"]["get"].get("responses", {})
assert "401" in responses
assert (
responses["401"]["$ref"]
== "#/components/responses/HTTP401NotAuthenticatedError"
)
def test_components_with_existing_responses():
"""Test when components already has a responses section."""
app = FastAPI()
# Mock get_openapi to return schema with existing components/responses
from fastapi.openapi.utils import get_openapi as original_get_openapi
def mock_get_openapi(*args, **kwargs):
schema = original_get_openapi(*args, **kwargs)
# Add existing components/responses
if "components" not in schema:
schema["components"] = {}
schema["components"]["responses"] = {
"ExistingResponse": {"description": "An existing response"}
}
return schema
with mock.patch("autogpt_libs.auth.helpers.get_openapi", mock_get_openapi):
# Apply customization
add_auth_responses_to_openapi(app)
schema = app.openapi()
# Both responses should exist
assert "ExistingResponse" in schema["components"]["responses"]
assert "HTTP401NotAuthenticatedError" in schema["components"]["responses"]
# Verify our 401 response structure
error_response = schema["components"]["responses"][
"HTTP401NotAuthenticatedError"
]
assert error_response["description"] == "Authentication required"
def test_openapi_schema_persistence():
"""Test that modifications to OpenAPI schema persist correctly."""
app = FastAPI()
from fastapi import Security
from autogpt_libs.auth.jwt_utils import get_jwt_payload
@app.get("/test")
def test_endpoint(jwt: dict = Security(get_jwt_payload)):
return {"test": True}
# Apply customization
add_auth_responses_to_openapi(app)
# Get schema multiple times
schema1 = app.openapi()
# Modify the cached schema (shouldn't affect future calls)
schema1["info"]["title"] = "Modified Title"
# Clear cache and get again
app.openapi_schema = None
schema2 = app.openapi()
# Should regenerate with original title
assert schema2["info"]["title"] == app.title
assert schema2["info"]["title"] != "Modified Title"

View File

@@ -1,48 +1,11 @@
import logging
from typing import Any
from typing import Any, Dict
import jwt
from fastapi import HTTPException, Security
from fastapi.security import HTTPAuthorizationCredentials, HTTPBearer
from .config import get_settings
from .models import User
logger = logging.getLogger(__name__)
# Bearer token authentication scheme
bearer_jwt_auth = HTTPBearer(
bearerFormat="jwt", scheme_name="HTTPBearerJWT", auto_error=False
)
from .config import settings
def get_jwt_payload(
credentials: HTTPAuthorizationCredentials | None = Security(bearer_jwt_auth),
) -> dict[str, Any]:
"""
Extract and validate JWT payload from HTTP Authorization header.
This is the core authentication function that handles:
- Reading the `Authorization` header to obtain the JWT token
- Verifying the JWT token's signature
- Decoding the JWT token's payload
:param credentials: HTTP Authorization credentials from bearer token
:return: JWT payload dictionary
:raises HTTPException: 401 if authentication fails
"""
if not credentials:
raise HTTPException(status_code=401, detail="Authorization header is missing")
try:
payload = parse_jwt_token(credentials.credentials)
logger.debug("Token decoded successfully")
return payload
except ValueError as e:
raise HTTPException(status_code=401, detail=str(e))
def parse_jwt_token(token: str) -> dict[str, Any]:
def parse_jwt_token(token: str) -> Dict[str, Any]:
"""
Parse and validate a JWT token.
@@ -50,11 +13,10 @@ def parse_jwt_token(token: str) -> dict[str, Any]:
:return: The decoded payload
:raises ValueError: If the token is invalid or expired
"""
settings = get_settings()
try:
payload = jwt.decode(
token,
settings.JWT_VERIFY_KEY,
settings.JWT_SECRET_KEY,
algorithms=[settings.JWT_ALGORITHM],
audience="authenticated",
)
@@ -63,18 +25,3 @@ def parse_jwt_token(token: str) -> dict[str, Any]:
raise ValueError("Token has expired")
except jwt.InvalidTokenError as e:
raise ValueError(f"Invalid token: {str(e)}")
def verify_user(jwt_payload: dict | None, admin_only: bool) -> User:
if jwt_payload is None:
raise HTTPException(status_code=401, detail="Authorization header is missing")
user_id = jwt_payload.get("sub")
if not user_id:
raise HTTPException(status_code=401, detail="User ID not found in token")
if admin_only and jwt_payload["role"] != "admin":
raise HTTPException(status_code=403, detail="Admin access required")
return User.from_payload(jwt_payload)

View File

@@ -1,308 +0,0 @@
"""
Comprehensive tests for JWT token parsing and validation.
Ensures 100% line and branch coverage for JWT security functions.
"""
import os
from datetime import datetime, timedelta, timezone
import jwt
import pytest
from fastapi import HTTPException
from fastapi.security import HTTPAuthorizationCredentials
from pytest_mock import MockerFixture
from autogpt_libs.auth import config, jwt_utils
from autogpt_libs.auth.config import Settings
from autogpt_libs.auth.models import User
MOCK_JWT_SECRET = "test-secret-key-with-at-least-32-characters"
TEST_USER_PAYLOAD = {
"sub": "test-user-id",
"role": "user",
"aud": "authenticated",
"email": "test@example.com",
}
TEST_ADMIN_PAYLOAD = {
"sub": "admin-user-id",
"role": "admin",
"aud": "authenticated",
"email": "admin@example.com",
}
@pytest.fixture(autouse=True)
def mock_config(mocker: MockerFixture):
mocker.patch.dict(os.environ, {"JWT_VERIFY_KEY": MOCK_JWT_SECRET}, clear=True)
mocker.patch.object(config, "_settings", Settings())
yield
def create_token(payload, secret=None, algorithm="HS256"):
"""Helper to create JWT tokens."""
if secret is None:
secret = MOCK_JWT_SECRET
return jwt.encode(payload, secret, algorithm=algorithm)
def test_parse_jwt_token_valid():
"""Test parsing a valid JWT token."""
token = create_token(TEST_USER_PAYLOAD)
result = jwt_utils.parse_jwt_token(token)
assert result["sub"] == "test-user-id"
assert result["role"] == "user"
assert result["aud"] == "authenticated"
def test_parse_jwt_token_expired():
"""Test parsing an expired JWT token."""
expired_payload = {
**TEST_USER_PAYLOAD,
"exp": datetime.now(timezone.utc) - timedelta(hours=1),
}
token = create_token(expired_payload)
with pytest.raises(ValueError) as exc_info:
jwt_utils.parse_jwt_token(token)
assert "Token has expired" in str(exc_info.value)
def test_parse_jwt_token_invalid_signature():
"""Test parsing a token with invalid signature."""
# Create token with different secret
token = create_token(TEST_USER_PAYLOAD, secret="wrong-secret")
with pytest.raises(ValueError) as exc_info:
jwt_utils.parse_jwt_token(token)
assert "Invalid token" in str(exc_info.value)
def test_parse_jwt_token_malformed():
"""Test parsing a malformed token."""
malformed_tokens = [
"not.a.token",
"invalid",
"",
# Header only
"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9",
# No signature
"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJzdWIiOiJ0ZXN0In0",
]
for token in malformed_tokens:
with pytest.raises(ValueError) as exc_info:
jwt_utils.parse_jwt_token(token)
assert "Invalid token" in str(exc_info.value)
def test_parse_jwt_token_wrong_audience():
"""Test parsing a token with wrong audience."""
wrong_aud_payload = {**TEST_USER_PAYLOAD, "aud": "wrong-audience"}
token = create_token(wrong_aud_payload)
with pytest.raises(ValueError) as exc_info:
jwt_utils.parse_jwt_token(token)
assert "Invalid token" in str(exc_info.value)
def test_parse_jwt_token_missing_audience():
"""Test parsing a token without audience claim."""
no_aud_payload = {k: v for k, v in TEST_USER_PAYLOAD.items() if k != "aud"}
token = create_token(no_aud_payload)
with pytest.raises(ValueError) as exc_info:
jwt_utils.parse_jwt_token(token)
assert "Invalid token" in str(exc_info.value)
def test_get_jwt_payload_with_valid_token():
"""Test extracting JWT payload with valid bearer token."""
token = create_token(TEST_USER_PAYLOAD)
credentials = HTTPAuthorizationCredentials(scheme="Bearer", credentials=token)
result = jwt_utils.get_jwt_payload(credentials)
assert result["sub"] == "test-user-id"
assert result["role"] == "user"
def test_get_jwt_payload_no_credentials():
"""Test JWT payload when no credentials provided."""
with pytest.raises(HTTPException) as exc_info:
jwt_utils.get_jwt_payload(None)
assert exc_info.value.status_code == 401
assert "Authorization header is missing" in exc_info.value.detail
def test_get_jwt_payload_invalid_token():
"""Test JWT payload extraction with invalid token."""
credentials = HTTPAuthorizationCredentials(
scheme="Bearer", credentials="invalid.token.here"
)
with pytest.raises(HTTPException) as exc_info:
jwt_utils.get_jwt_payload(credentials)
assert exc_info.value.status_code == 401
assert "Invalid token" in exc_info.value.detail
def test_verify_user_with_valid_user():
"""Test verifying a valid user."""
user = jwt_utils.verify_user(TEST_USER_PAYLOAD, admin_only=False)
assert isinstance(user, User)
assert user.user_id == "test-user-id"
assert user.role == "user"
assert user.email == "test@example.com"
def test_verify_user_with_admin():
"""Test verifying an admin user."""
user = jwt_utils.verify_user(TEST_ADMIN_PAYLOAD, admin_only=True)
assert isinstance(user, User)
assert user.user_id == "admin-user-id"
assert user.role == "admin"
def test_verify_user_admin_only_with_regular_user():
"""Test verifying regular user when admin is required."""
with pytest.raises(HTTPException) as exc_info:
jwt_utils.verify_user(TEST_USER_PAYLOAD, admin_only=True)
assert exc_info.value.status_code == 403
assert "Admin access required" in exc_info.value.detail
def test_verify_user_no_payload():
"""Test verifying user with no payload."""
with pytest.raises(HTTPException) as exc_info:
jwt_utils.verify_user(None, admin_only=False)
assert exc_info.value.status_code == 401
assert "Authorization header is missing" in exc_info.value.detail
def test_verify_user_missing_sub():
"""Test verifying user with payload missing 'sub' field."""
invalid_payload = {"role": "user", "email": "test@example.com"}
with pytest.raises(HTTPException) as exc_info:
jwt_utils.verify_user(invalid_payload, admin_only=False)
assert exc_info.value.status_code == 401
assert "User ID not found in token" in exc_info.value.detail
def test_verify_user_empty_sub():
"""Test verifying user with empty 'sub' field."""
invalid_payload = {"sub": "", "role": "user"}
with pytest.raises(HTTPException) as exc_info:
jwt_utils.verify_user(invalid_payload, admin_only=False)
assert exc_info.value.status_code == 401
assert "User ID not found in token" in exc_info.value.detail
def test_verify_user_none_sub():
"""Test verifying user with None 'sub' field."""
invalid_payload = {"sub": None, "role": "user"}
with pytest.raises(HTTPException) as exc_info:
jwt_utils.verify_user(invalid_payload, admin_only=False)
assert exc_info.value.status_code == 401
assert "User ID not found in token" in exc_info.value.detail
def test_verify_user_missing_role_admin_check():
"""Test verifying admin when role field is missing."""
no_role_payload = {"sub": "user-id"}
with pytest.raises(KeyError):
# This will raise KeyError when checking payload["role"]
jwt_utils.verify_user(no_role_payload, admin_only=True)
# ======================== EDGE CASES ======================== #
def test_jwt_with_additional_claims():
"""Test JWT token with additional custom claims."""
extra_claims_payload = {
"sub": "user-id",
"role": "user",
"aud": "authenticated",
"custom_claim": "custom_value",
"permissions": ["read", "write"],
"metadata": {"key": "value"},
}
token = create_token(extra_claims_payload)
result = jwt_utils.parse_jwt_token(token)
assert result["sub"] == "user-id"
assert result["custom_claim"] == "custom_value"
assert result["permissions"] == ["read", "write"]
def test_jwt_with_numeric_sub():
"""Test JWT token with numeric user ID."""
payload = {
"sub": 12345, # Numeric ID
"role": "user",
"aud": "authenticated",
}
# Should convert to string internally
user = jwt_utils.verify_user(payload, admin_only=False)
assert user.user_id == 12345
def test_jwt_with_very_long_sub():
"""Test JWT token with very long user ID."""
long_id = "a" * 1000
payload = {
"sub": long_id,
"role": "user",
"aud": "authenticated",
}
user = jwt_utils.verify_user(payload, admin_only=False)
assert user.user_id == long_id
def test_jwt_with_special_characters_in_claims():
"""Test JWT token with special characters in claims."""
payload = {
"sub": "user@example.com/special-chars!@#$%",
"role": "admin",
"aud": "authenticated",
"email": "test+special@example.com",
}
user = jwt_utils.verify_user(payload, admin_only=True)
assert "special-chars!@#$%" in user.user_id
def test_jwt_with_future_iat():
"""Test JWT token with issued-at time in future."""
future_payload = {
"sub": "user-id",
"role": "user",
"aud": "authenticated",
"iat": datetime.now(timezone.utc) + timedelta(hours=1),
}
token = create_token(future_payload)
# PyJWT validates iat claim and should reject future tokens
with pytest.raises(ValueError, match="not yet valid"):
jwt_utils.parse_jwt_token(token)
def test_jwt_with_different_algorithms():
"""Test that only HS256 algorithm is accepted."""
payload = {
"sub": "user-id",
"role": "user",
"aud": "authenticated",
}
# Try different algorithms
algorithms = ["HS384", "HS512", "none"]
for algo in algorithms:
if algo == "none":
# Special case for 'none' algorithm (security vulnerability if accepted)
token = create_token(payload, "", algorithm="none")
else:
token = create_token(payload, algorithm=algo)
with pytest.raises(ValueError) as exc_info:
jwt_utils.parse_jwt_token(token)
assert "Invalid token" in str(exc_info.value)

View File

@@ -0,0 +1,140 @@
import inspect
import logging
import secrets
from typing import Any, Callable, Optional
from fastapi import HTTPException, Request, Security
from fastapi.security import APIKeyHeader, HTTPBearer
from starlette.status import HTTP_401_UNAUTHORIZED
from .config import settings
from .jwt_utils import parse_jwt_token
security = HTTPBearer()
logger = logging.getLogger(__name__)
async def auth_middleware(request: Request):
if not settings.ENABLE_AUTH:
# If authentication is disabled, allow the request to proceed
logger.warning("Auth disabled")
return {}
security = HTTPBearer()
credentials = await security(request)
if not credentials:
raise HTTPException(status_code=401, detail="Authorization header is missing")
try:
payload = parse_jwt_token(credentials.credentials)
request.state.user = payload
logger.debug("Token decoded successfully")
except ValueError as e:
raise HTTPException(status_code=401, detail=str(e))
return payload
class APIKeyValidator:
"""
Configurable API key validator that supports custom validation functions
for FastAPI applications.
This class provides a flexible way to implement API key authentication with optional
custom validation logic. It can be used for simple token matching
or more complex validation scenarios like database lookups.
Examples:
Simple token validation:
```python
validator = APIKeyValidator(
header_name="X-API-Key",
expected_token="your-secret-token"
)
@app.get("/protected", dependencies=[Depends(validator.get_dependency())])
def protected_endpoint():
return {"message": "Access granted"}
```
Custom validation with database lookup:
```python
async def validate_with_db(api_key: str):
api_key_obj = await db.get_api_key(api_key)
return api_key_obj if api_key_obj and api_key_obj.is_active else None
validator = APIKeyValidator(
header_name="X-API-Key",
validate_fn=validate_with_db
)
```
Args:
header_name (str): The name of the header containing the API key
expected_token (Optional[str]): The expected API key value for simple token matching
validate_fn (Optional[Callable]): Custom validation function that takes an API key
string and returns a boolean or object. Can be async.
error_status (int): HTTP status code to use for validation errors
error_message (str): Error message to return when validation fails
"""
def __init__(
self,
header_name: str,
expected_token: Optional[str] = None,
validate_fn: Optional[Callable[[str], bool]] = None,
error_status: int = HTTP_401_UNAUTHORIZED,
error_message: str = "Invalid API key",
):
# Create the APIKeyHeader as a class property
self.security_scheme = APIKeyHeader(name=header_name)
self.expected_token = expected_token
self.custom_validate_fn = validate_fn
self.error_status = error_status
self.error_message = error_message
async def default_validator(self, api_key: str) -> bool:
if not self.expected_token:
raise ValueError(
"Expected Token Required to be set when uisng API Key Validator default validation"
)
return secrets.compare_digest(api_key, self.expected_token)
async def __call__(
self, request: Request, api_key: str = Security(APIKeyHeader)
) -> Any:
if api_key is None:
raise HTTPException(status_code=self.error_status, detail="Missing API key")
# Use custom validation if provided, otherwise use default equality check
validator = self.custom_validate_fn or self.default_validator
result = (
await validator(api_key)
if inspect.iscoroutinefunction(validator)
else validator(api_key)
)
if not result:
raise HTTPException(
status_code=self.error_status, detail=self.error_message
)
# Store validation result in request state if it's not just a boolean
if result is not True:
request.state.api_key = result
return result
def get_dependency(self):
"""
Returns a callable dependency that FastAPI will recognize as a security scheme
"""
async def validate_api_key(
request: Request, api_key: str = Security(self.security_scheme)
) -> Any:
return await self(request, api_key)
# This helps FastAPI recognize it as a security dependency
validate_api_key.__name__ = f"validate_{self.security_scheme.model.name}"
return validate_api_key

View File

@@ -0,0 +1,166 @@
import asyncio
import contextlib
import logging
from functools import wraps
from typing import Any, Awaitable, Callable, Dict, Optional, TypeVar, Union, cast
import ldclient
from fastapi import HTTPException
from ldclient import Context, LDClient
from ldclient.config import Config
from typing_extensions import ParamSpec
from .config import SETTINGS
logger = logging.getLogger(__name__)
P = ParamSpec("P")
T = TypeVar("T")
def get_client() -> LDClient:
"""Get the LaunchDarkly client singleton."""
return ldclient.get()
def initialize_launchdarkly() -> None:
sdk_key = SETTINGS.launch_darkly_sdk_key
logger.debug(
f"Initializing LaunchDarkly with SDK key: {'present' if sdk_key else 'missing'}"
)
if not sdk_key:
logger.warning("LaunchDarkly SDK key not configured")
return
config = Config(sdk_key)
ldclient.set_config(config)
if ldclient.get().is_initialized():
logger.info("LaunchDarkly client initialized successfully")
else:
logger.error("LaunchDarkly client failed to initialize")
def shutdown_launchdarkly() -> None:
"""Shutdown the LaunchDarkly client."""
if ldclient.get().is_initialized():
ldclient.get().close()
logger.info("LaunchDarkly client closed successfully")
def create_context(
user_id: str, additional_attributes: Optional[Dict[str, Any]] = None
) -> Context:
"""Create LaunchDarkly context with optional additional attributes."""
builder = Context.builder(str(user_id)).kind("user")
if additional_attributes:
for key, value in additional_attributes.items():
builder.set(key, value)
return builder.build()
def feature_flag(
flag_key: str,
default: bool = False,
) -> Callable[
[Callable[P, Union[T, Awaitable[T]]]], Callable[P, Union[T, Awaitable[T]]]
]:
"""
Decorator for feature flag protected endpoints.
"""
def decorator(
func: Callable[P, Union[T, Awaitable[T]]],
) -> Callable[P, Union[T, Awaitable[T]]]:
@wraps(func)
async def async_wrapper(*args: P.args, **kwargs: P.kwargs) -> T:
try:
user_id = kwargs.get("user_id")
if not user_id:
raise ValueError("user_id is required")
if not get_client().is_initialized():
logger.warning(
f"LaunchDarkly not initialized, using default={default}"
)
is_enabled = default
else:
context = create_context(str(user_id))
is_enabled = get_client().variation(flag_key, context, default)
if not is_enabled:
raise HTTPException(status_code=404, detail="Feature not available")
result = func(*args, **kwargs)
if asyncio.iscoroutine(result):
return await result
return cast(T, result)
except Exception as e:
logger.error(f"Error evaluating feature flag {flag_key}: {e}")
raise
@wraps(func)
def sync_wrapper(*args: P.args, **kwargs: P.kwargs) -> T:
try:
user_id = kwargs.get("user_id")
if not user_id:
raise ValueError("user_id is required")
if not get_client().is_initialized():
logger.warning(
f"LaunchDarkly not initialized, using default={default}"
)
is_enabled = default
else:
context = create_context(str(user_id))
is_enabled = get_client().variation(flag_key, context, default)
if not is_enabled:
raise HTTPException(status_code=404, detail="Feature not available")
return cast(T, func(*args, **kwargs))
except Exception as e:
logger.error(f"Error evaluating feature flag {flag_key}: {e}")
raise
return cast(
Callable[P, Union[T, Awaitable[T]]],
async_wrapper if asyncio.iscoroutinefunction(func) else sync_wrapper,
)
return decorator
def percentage_rollout(
flag_key: str,
default: bool = False,
) -> Callable[
[Callable[P, Union[T, Awaitable[T]]]], Callable[P, Union[T, Awaitable[T]]]
]:
"""Decorator for percentage-based rollouts."""
return feature_flag(flag_key, default)
def beta_feature(
flag_key: Optional[str] = None,
unauthorized_response: Any = {"message": "Not available in beta"},
) -> Callable[
[Callable[P, Union[T, Awaitable[T]]]], Callable[P, Union[T, Awaitable[T]]]
]:
"""Decorator for beta features."""
actual_key = f"beta-{flag_key}" if flag_key else "beta"
return feature_flag(actual_key, False)
@contextlib.contextmanager
def mock_flag_variation(flag_key: str, return_value: Any):
"""Context manager for testing feature flags."""
original_variation = get_client().variation
get_client().variation = lambda key, context, default: (
return_value if key == flag_key else original_variation(key, context, default)
)
try:
yield
finally:
get_client().variation = original_variation

View File

@@ -0,0 +1,45 @@
import pytest
from ldclient import LDClient
from autogpt_libs.feature_flag.client import feature_flag, mock_flag_variation
@pytest.fixture
def ld_client(mocker):
client = mocker.Mock(spec=LDClient)
mocker.patch("ldclient.get", return_value=client)
client.is_initialized.return_value = True
return client
@pytest.mark.asyncio
async def test_feature_flag_enabled(ld_client):
ld_client.variation.return_value = True
@feature_flag("test-flag")
async def test_function(user_id: str):
return "success"
result = test_function(user_id="test-user")
assert result == "success"
ld_client.variation.assert_called_once()
@pytest.mark.asyncio
async def test_feature_flag_unauthorized_response(ld_client):
ld_client.variation.return_value = False
@feature_flag("test-flag")
async def test_function(user_id: str):
return "success"
result = test_function(user_id="test-user")
assert result == {"error": "disabled"}
def test_mock_flag_variation(ld_client):
with mock_flag_variation("test-flag", True):
assert ld_client.variation("test-flag", None, False)
with mock_flag_variation("test-flag", False):
assert ld_client.variation("test-flag", None, False)

View File

@@ -0,0 +1,15 @@
from pydantic import Field
from pydantic_settings import BaseSettings, SettingsConfigDict
class Settings(BaseSettings):
launch_darkly_sdk_key: str = Field(
default="",
description="The Launch Darkly SDK key",
validation_alias="LAUNCH_DARKLY_SDK_KEY",
)
model_config = SettingsConfigDict(case_sensitive=True, extra="ignore")
SETTINGS = Settings()

View File

@@ -1,8 +1,6 @@
"""Logging module for Auto-GPT."""
import logging
import os
import socket
import sys
from pathlib import Path
@@ -12,15 +10,6 @@ from pydantic_settings import BaseSettings, SettingsConfigDict
from .filters import BelowLevelFilter
from .formatters import AGPTFormatter
# Configure global socket timeout and gRPC keepalive to prevent deadlocks
# This must be done at import time before any gRPC connections are established
socket.setdefaulttimeout(30) # 30-second socket timeout
# Enable gRPC keepalive to detect dead connections faster
os.environ.setdefault("GRPC_KEEPALIVE_TIME_MS", "30000") # 30 seconds
os.environ.setdefault("GRPC_KEEPALIVE_TIMEOUT_MS", "5000") # 5 seconds
os.environ.setdefault("GRPC_KEEPALIVE_PERMIT_WITHOUT_CALLS", "true")
LOG_DIR = Path(__file__).parent.parent.parent.parent / "logs"
LOG_FILE = "activity.log"
DEBUG_LOG_FILE = "debug.log"
@@ -90,6 +79,7 @@ def configure_logging(force_cloud_logging: bool = False) -> None:
Note: This function is typically called at the start of the application
to set up the logging infrastructure.
"""
config = LoggingConfig()
log_handlers: list[logging.Handler] = []
@@ -115,17 +105,13 @@ def configure_logging(force_cloud_logging: bool = False) -> None:
if config.enable_cloud_logging or force_cloud_logging:
import google.cloud.logging
from google.cloud.logging.handlers import CloudLoggingHandler
from google.cloud.logging_v2.handlers.transports import (
BackgroundThreadTransport,
)
from google.cloud.logging_v2.handlers.transports.sync import SyncTransport
client = google.cloud.logging.Client()
# Use BackgroundThreadTransport to prevent blocking the main thread
# and deadlocks when gRPC calls to Google Cloud Logging hang
cloud_handler = CloudLoggingHandler(
client,
name="autogpt_logs",
transport=BackgroundThreadTransport,
transport=SyncTransport,
)
cloud_handler.setLevel(config.level)
log_handlers.append(cloud_handler)

View File

@@ -1,5 +1,39 @@
import logging
import re
from typing import Any
import uvicorn.config
from colorama import Fore
def remove_color_codes(s: str) -> str:
return re.sub(r"\x1B(?:[@-Z\\-_]|\[[0-?]*[ -/]*[@-~])", "", s)
def fmt_kwargs(kwargs: dict) -> str:
return ", ".join(f"{n}={repr(v)}" for n, v in kwargs.items())
def print_attribute(
title: str, value: Any, title_color: str = Fore.GREEN, value_color: str = ""
) -> None:
logger = logging.getLogger()
logger.info(
str(value),
extra={
"title": f"{title.rstrip(':')}:",
"title_color": title_color,
"color": value_color,
},
)
def generate_uvicorn_config():
"""
Generates a uvicorn logging config that silences uvicorn's default logging and tells it to use the native logging module.
"""
log_config = dict(uvicorn.config.LOGGING_CONFIG)
log_config["loggers"]["uvicorn"] = {"handlers": []}
log_config["loggers"]["uvicorn.error"] = {"handlers": []}
log_config["loggers"]["uvicorn.access"] = {"handlers": []}
return log_config

View File

@@ -1,34 +1,17 @@
import inspect
import logging
import threading
import time
from functools import wraps
from typing import (
Awaitable,
Callable,
ParamSpec,
Protocol,
Tuple,
TypeVar,
cast,
overload,
runtime_checkable,
)
from typing import Awaitable, Callable, ParamSpec, TypeVar, cast, overload
P = ParamSpec("P")
R = TypeVar("R")
logger = logging.getLogger(__name__)
@overload
def thread_cached(func: Callable[P, Awaitable[R]]) -> Callable[P, Awaitable[R]]: ...
@overload
def thread_cached(func: Callable[P, Awaitable[R]]) -> Callable[P, Awaitable[R]]:
pass
@overload
def thread_cached(func: Callable[P, R]) -> Callable[P, R]:
pass
def thread_cached(func: Callable[P, R]) -> Callable[P, R]: ...
def thread_cached(
@@ -74,193 +57,3 @@ def thread_cached(
def clear_thread_cache(func: Callable) -> None:
if clear := getattr(func, "clear_cache", None):
clear()
FuncT = TypeVar("FuncT")
R_co = TypeVar("R_co", covariant=True)
@runtime_checkable
class AsyncCachedFunction(Protocol[P, R_co]):
"""Protocol for async functions with cache management methods."""
def cache_clear(self) -> None:
"""Clear all cached entries."""
return None
def cache_info(self) -> dict[str, int | None]:
"""Get cache statistics."""
return {}
async def __call__(self, *args: P.args, **kwargs: P.kwargs) -> R_co:
"""Call the cached function."""
return None # type: ignore
def async_ttl_cache(
maxsize: int = 128, ttl_seconds: int | None = None
) -> Callable[[Callable[P, Awaitable[R]]], AsyncCachedFunction[P, R]]:
"""
TTL (Time To Live) cache decorator for async functions.
Similar to functools.lru_cache but works with async functions and includes optional TTL.
Args:
maxsize: Maximum number of cached entries
ttl_seconds: Time to live in seconds. If None, entries never expire (like lru_cache)
Returns:
Decorator function
Example:
# With TTL
@async_ttl_cache(maxsize=1000, ttl_seconds=300)
async def api_call(param: str) -> dict:
return {"result": param}
# Without TTL (permanent cache like lru_cache)
@async_ttl_cache(maxsize=1000)
async def expensive_computation(param: str) -> dict:
return {"result": param}
"""
def decorator(
async_func: Callable[P, Awaitable[R]],
) -> AsyncCachedFunction[P, R]:
# Cache storage - use union type to handle both cases
cache_storage: dict[tuple, R | Tuple[R, float]] = {}
@wraps(async_func)
async def wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
# Create cache key from arguments
key = (args, tuple(sorted(kwargs.items())))
current_time = time.time()
# Check if we have a valid cached entry
if key in cache_storage:
if ttl_seconds is None:
# No TTL - return cached result directly
logger.debug(
f"Cache hit for {async_func.__name__} with key: {str(key)[:50]}"
)
return cast(R, cache_storage[key])
else:
# With TTL - check expiration
cached_data = cache_storage[key]
if isinstance(cached_data, tuple):
result, timestamp = cached_data
if current_time - timestamp < ttl_seconds:
logger.debug(
f"Cache hit for {async_func.__name__} with key: {str(key)[:50]}"
)
return cast(R, result)
else:
# Expired entry
del cache_storage[key]
logger.debug(
f"Cache entry expired for {async_func.__name__}"
)
# Cache miss or expired - fetch fresh data
logger.debug(
f"Cache miss for {async_func.__name__} with key: {str(key)[:50]}"
)
result = await async_func(*args, **kwargs)
# Store in cache
if ttl_seconds is None:
cache_storage[key] = result
else:
cache_storage[key] = (result, current_time)
# Simple cleanup when cache gets too large
if len(cache_storage) > maxsize:
# Remove oldest entries (simple FIFO cleanup)
cutoff = maxsize // 2
oldest_keys = list(cache_storage.keys())[:-cutoff] if cutoff > 0 else []
for old_key in oldest_keys:
cache_storage.pop(old_key, None)
logger.debug(
f"Cache cleanup: removed {len(oldest_keys)} entries for {async_func.__name__}"
)
return result
# Add cache management methods (similar to functools.lru_cache)
def cache_clear() -> None:
cache_storage.clear()
def cache_info() -> dict[str, int | None]:
return {
"size": len(cache_storage),
"maxsize": maxsize,
"ttl_seconds": ttl_seconds,
}
# Attach methods to wrapper
setattr(wrapper, "cache_clear", cache_clear)
setattr(wrapper, "cache_info", cache_info)
return cast(AsyncCachedFunction[P, R], wrapper)
return decorator
@overload
def async_cache(
func: Callable[P, Awaitable[R]],
) -> AsyncCachedFunction[P, R]:
pass
@overload
def async_cache(
func: None = None,
*,
maxsize: int = 128,
) -> Callable[[Callable[P, Awaitable[R]]], AsyncCachedFunction[P, R]]:
pass
def async_cache(
func: Callable[P, Awaitable[R]] | None = None,
*,
maxsize: int = 128,
) -> (
AsyncCachedFunction[P, R]
| Callable[[Callable[P, Awaitable[R]]], AsyncCachedFunction[P, R]]
):
"""
Process-level cache decorator for async functions (no TTL).
Similar to functools.lru_cache but works with async functions.
This is a convenience wrapper around async_ttl_cache with ttl_seconds=None.
Args:
func: The async function to cache (when used without parentheses)
maxsize: Maximum number of cached entries
Returns:
Decorated function or decorator
Example:
# Without parentheses (uses default maxsize=128)
@async_cache
async def get_data(param: str) -> dict:
return {"result": param}
# With parentheses and custom maxsize
@async_cache(maxsize=1000)
async def expensive_computation(param: str) -> dict:
# Expensive computation here
return {"result": param}
"""
if func is None:
# Called with parentheses @async_cache() or @async_cache(maxsize=...)
return async_ttl_cache(maxsize=maxsize, ttl_seconds=None)
else:
# Called without parentheses @async_cache
decorator = async_ttl_cache(maxsize=maxsize, ttl_seconds=None)
return decorator(func)

View File

@@ -16,12 +16,7 @@ from unittest.mock import Mock
import pytest
from autogpt_libs.utils.cache import (
async_cache,
async_ttl_cache,
clear_thread_cache,
thread_cached,
)
from autogpt_libs.utils.cache import clear_thread_cache, thread_cached
class TestThreadCached:
@@ -328,378 +323,3 @@ class TestThreadCached:
assert function_using_mock(2) == 42
assert mock.call_count == 2
class TestAsyncTTLCache:
"""Tests for the @async_ttl_cache decorator."""
@pytest.mark.asyncio
async def test_basic_caching(self):
"""Test basic caching functionality."""
call_count = 0
@async_ttl_cache(maxsize=10, ttl_seconds=60)
async def cached_function(x: int, y: int = 0) -> int:
nonlocal call_count
call_count += 1
await asyncio.sleep(0.01) # Simulate async work
return x + y
# First call
result1 = await cached_function(1, 2)
assert result1 == 3
assert call_count == 1
# Second call with same args - should use cache
result2 = await cached_function(1, 2)
assert result2 == 3
assert call_count == 1 # No additional call
# Different args - should call function again
result3 = await cached_function(2, 3)
assert result3 == 5
assert call_count == 2
@pytest.mark.asyncio
async def test_ttl_expiration(self):
"""Test that cache entries expire after TTL."""
call_count = 0
@async_ttl_cache(maxsize=10, ttl_seconds=1) # Short TTL
async def short_lived_cache(x: int) -> int:
nonlocal call_count
call_count += 1
return x * 2
# First call
result1 = await short_lived_cache(5)
assert result1 == 10
assert call_count == 1
# Second call immediately - should use cache
result2 = await short_lived_cache(5)
assert result2 == 10
assert call_count == 1
# Wait for TTL to expire
await asyncio.sleep(1.1)
# Third call after expiration - should call function again
result3 = await short_lived_cache(5)
assert result3 == 10
assert call_count == 2
@pytest.mark.asyncio
async def test_cache_info(self):
"""Test cache info functionality."""
@async_ttl_cache(maxsize=5, ttl_seconds=300)
async def info_test_function(x: int) -> int:
return x * 3
# Check initial cache info
info = info_test_function.cache_info()
assert info["size"] == 0
assert info["maxsize"] == 5
assert info["ttl_seconds"] == 300
# Add an entry
await info_test_function(1)
info = info_test_function.cache_info()
assert info["size"] == 1
@pytest.mark.asyncio
async def test_cache_clear(self):
"""Test cache clearing functionality."""
call_count = 0
@async_ttl_cache(maxsize=10, ttl_seconds=60)
async def clearable_function(x: int) -> int:
nonlocal call_count
call_count += 1
return x * 4
# First call
result1 = await clearable_function(2)
assert result1 == 8
assert call_count == 1
# Second call - should use cache
result2 = await clearable_function(2)
assert result2 == 8
assert call_count == 1
# Clear cache
clearable_function.cache_clear()
# Third call after clear - should call function again
result3 = await clearable_function(2)
assert result3 == 8
assert call_count == 2
@pytest.mark.asyncio
async def test_maxsize_cleanup(self):
"""Test that cache cleans up when maxsize is exceeded."""
call_count = 0
@async_ttl_cache(maxsize=3, ttl_seconds=60)
async def size_limited_function(x: int) -> int:
nonlocal call_count
call_count += 1
return x**2
# Fill cache to maxsize
await size_limited_function(1) # call_count: 1
await size_limited_function(2) # call_count: 2
await size_limited_function(3) # call_count: 3
info = size_limited_function.cache_info()
assert info["size"] == 3
# Add one more entry - should trigger cleanup
await size_limited_function(4) # call_count: 4
# Cache size should be reduced (cleanup removes oldest entries)
info = size_limited_function.cache_info()
assert info["size"] is not None and info["size"] <= 3 # Should be cleaned up
@pytest.mark.asyncio
async def test_argument_variations(self):
"""Test caching with different argument patterns."""
call_count = 0
@async_ttl_cache(maxsize=10, ttl_seconds=60)
async def arg_test_function(a: int, b: str = "default", *, c: int = 100) -> str:
nonlocal call_count
call_count += 1
return f"{a}-{b}-{c}"
# Different ways to call with same logical arguments
result1 = await arg_test_function(1, "test", c=200)
assert call_count == 1
# Same arguments, same order - should use cache
result2 = await arg_test_function(1, "test", c=200)
assert call_count == 1
assert result1 == result2
# Different arguments - should call function
result3 = await arg_test_function(2, "test", c=200)
assert call_count == 2
assert result1 != result3
@pytest.mark.asyncio
async def test_exception_handling(self):
"""Test that exceptions are not cached."""
call_count = 0
@async_ttl_cache(maxsize=10, ttl_seconds=60)
async def exception_function(x: int) -> int:
nonlocal call_count
call_count += 1
if x < 0:
raise ValueError("Negative value not allowed")
return x * 2
# Successful call - should be cached
result1 = await exception_function(5)
assert result1 == 10
assert call_count == 1
# Same successful call - should use cache
result2 = await exception_function(5)
assert result2 == 10
assert call_count == 1
# Exception call - should not be cached
with pytest.raises(ValueError):
await exception_function(-1)
assert call_count == 2
# Same exception call - should call again (not cached)
with pytest.raises(ValueError):
await exception_function(-1)
assert call_count == 3
@pytest.mark.asyncio
async def test_concurrent_calls(self):
"""Test caching behavior with concurrent calls."""
call_count = 0
@async_ttl_cache(maxsize=10, ttl_seconds=60)
async def concurrent_function(x: int) -> int:
nonlocal call_count
call_count += 1
await asyncio.sleep(0.05) # Simulate work
return x * x
# Launch concurrent calls with same arguments
tasks = [concurrent_function(3) for _ in range(5)]
results = await asyncio.gather(*tasks)
# All results should be the same
assert all(result == 9 for result in results)
# Note: Due to race conditions, call_count might be up to 5 for concurrent calls
# This tests that the cache doesn't break under concurrent access
assert 1 <= call_count <= 5
class TestAsyncCache:
"""Tests for the @async_cache decorator (no TTL)."""
@pytest.mark.asyncio
async def test_basic_caching_no_ttl(self):
"""Test basic caching functionality without TTL."""
call_count = 0
@async_cache(maxsize=10)
async def cached_function(x: int, y: int = 0) -> int:
nonlocal call_count
call_count += 1
await asyncio.sleep(0.01) # Simulate async work
return x + y
# First call
result1 = await cached_function(1, 2)
assert result1 == 3
assert call_count == 1
# Second call with same args - should use cache
result2 = await cached_function(1, 2)
assert result2 == 3
assert call_count == 1 # No additional call
# Third call after some time - should still use cache (no TTL)
await asyncio.sleep(0.05)
result3 = await cached_function(1, 2)
assert result3 == 3
assert call_count == 1 # Still no additional call
# Different args - should call function again
result4 = await cached_function(2, 3)
assert result4 == 5
assert call_count == 2
@pytest.mark.asyncio
async def test_no_ttl_vs_ttl_behavior(self):
"""Test the difference between TTL and no-TTL caching."""
ttl_call_count = 0
no_ttl_call_count = 0
@async_ttl_cache(maxsize=10, ttl_seconds=1) # Short TTL
async def ttl_function(x: int) -> int:
nonlocal ttl_call_count
ttl_call_count += 1
return x * 2
@async_cache(maxsize=10) # No TTL
async def no_ttl_function(x: int) -> int:
nonlocal no_ttl_call_count
no_ttl_call_count += 1
return x * 2
# First calls
await ttl_function(5)
await no_ttl_function(5)
assert ttl_call_count == 1
assert no_ttl_call_count == 1
# Wait for TTL to expire
await asyncio.sleep(1.1)
# Second calls after TTL expiry
await ttl_function(5) # Should call function again (TTL expired)
await no_ttl_function(5) # Should use cache (no TTL)
assert ttl_call_count == 2 # TTL function called again
assert no_ttl_call_count == 1 # No-TTL function still cached
@pytest.mark.asyncio
async def test_async_cache_info(self):
"""Test cache info for no-TTL cache."""
@async_cache(maxsize=5)
async def info_test_function(x: int) -> int:
return x * 3
# Check initial cache info
info = info_test_function.cache_info()
assert info["size"] == 0
assert info["maxsize"] == 5
assert info["ttl_seconds"] is None # No TTL
# Add an entry
await info_test_function(1)
info = info_test_function.cache_info()
assert info["size"] == 1
class TestTTLOptional:
"""Tests for optional TTL functionality."""
@pytest.mark.asyncio
async def test_ttl_none_behavior(self):
"""Test that ttl_seconds=None works like no TTL."""
call_count = 0
@async_ttl_cache(maxsize=10, ttl_seconds=None)
async def no_ttl_via_none(x: int) -> int:
nonlocal call_count
call_count += 1
return x**2
# First call
result1 = await no_ttl_via_none(3)
assert result1 == 9
assert call_count == 1
# Wait (would expire if there was TTL)
await asyncio.sleep(0.1)
# Second call - should still use cache
result2 = await no_ttl_via_none(3)
assert result2 == 9
assert call_count == 1 # No additional call
# Check cache info
info = no_ttl_via_none.cache_info()
assert info["ttl_seconds"] is None
@pytest.mark.asyncio
async def test_cache_options_comparison(self):
"""Test different cache options work as expected."""
ttl_calls = 0
no_ttl_calls = 0
@async_ttl_cache(maxsize=10, ttl_seconds=1) # With TTL
async def ttl_function(x: int) -> int:
nonlocal ttl_calls
ttl_calls += 1
return x * 10
@async_cache(maxsize=10) # Process-level cache (no TTL)
async def process_function(x: int) -> int:
nonlocal no_ttl_calls
no_ttl_calls += 1
return x * 10
# Both should cache initially
await ttl_function(3)
await process_function(3)
assert ttl_calls == 1
assert no_ttl_calls == 1
# Immediate second calls - both should use cache
await ttl_function(3)
await process_function(3)
assert ttl_calls == 1
assert no_ttl_calls == 1
# Wait for TTL to expire
await asyncio.sleep(1.1)
# After TTL expiry
await ttl_function(3) # Should call function again
await process_function(3) # Should still use cache
assert ttl_calls == 2 # TTL cache expired, called again
assert no_ttl_calls == 1 # Process cache never expires

View File

@@ -54,7 +54,7 @@ version = "1.2.0"
description = "Backport of asyncio.Runner, a context manager that controls event loop life cycle."
optional = false
python-versions = "<3.11,>=3.8"
groups = ["dev"]
groups = ["main"]
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@@ -289,176 +208,12 @@ version = "0.4.6"
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{file = "ruff-0.12.3-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:023040a3499f6f974ae9091bcdd0385dd9e9eb4942f231c23c57708147b06311"},
{file = "ruff-0.12.3-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:883d844967bffff5ab28bba1a4d246c1a1b2933f48cb9840f3fdc5111c603b07"},
{file = "ruff-0.12.3-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:2120d3aa855ff385e0e562fdee14d564c9675edbe41625c87eeab744a7830d12"},
{file = "ruff-0.12.3-py3-none-musllinux_1_2_i686.whl", hash = "sha256:6b16647cbb470eaf4750d27dddc6ebf7758b918887b56d39e9c22cce2049082b"},
{file = "ruff-0.12.3-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:e1417051edb436230023575b149e8ff843a324557fe0a265863b7602df86722f"},
{file = "ruff-0.12.3-py3-none-win32.whl", hash = "sha256:dfd45e6e926deb6409d0616078a666ebce93e55e07f0fb0228d4b2608b2c248d"},
{file = "ruff-0.12.3-py3-none-win_amd64.whl", hash = "sha256:a946cf1e7ba3209bdef039eb97647f1c77f6f540e5845ec9c114d3af8df873e7"},
{file = "ruff-0.12.3-py3-none-win_arm64.whl", hash = "sha256:5f9c7c9c8f84c2d7f27e93674d27136fbf489720251544c4da7fb3d742e011b1"},
{file = "ruff-0.12.3.tar.gz", hash = "sha256:f1b5a4b6668fd7b7ea3697d8d98857390b40c1320a63a178eee6be0899ea2d77"},
]
[[package]]
@@ -1725,7 +1410,7 @@ version = "2.2.1"
description = "A lil' TOML parser"
optional = false
python-versions = ">=3.8"
groups = ["dev"]
groups = ["main"]
markers = "python_version < \"3.11\""
files = [
{file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"},
@@ -1768,7 +1453,7 @@ version = "4.14.1"
description = "Backported and Experimental Type Hints for Python 3.9+"
optional = false
python-versions = ">=3.9"
groups = ["main", "dev"]
groups = ["main"]
files = [
{file = "typing_extensions-4.14.1-py3-none-any.whl", hash = "sha256:d1e1e3b58374dc93031d6eda2420a48ea44a36c2b4766a4fdeb3710755731d76"},
{file = "typing_extensions-4.14.1.tar.gz", hash = "sha256:38b39f4aeeab64884ce9f74c94263ef78f3c22467c8724005483154c26648d36"},
@@ -1929,4 +1614,4 @@ type = ["pytest-mypy"]
[metadata]
lock-version = "2.1"
python-versions = ">=3.10,<4.0"
content-hash = "0c40b63c3c921846cf05ccfb4e685d4959854b29c2c302245f9832e20aac6954"
content-hash = "f67db13e6f68b1d67a55eee908c1c560bfa44da8509f98f842889a7570a9830f"

View File

@@ -9,25 +9,21 @@ packages = [{ include = "autogpt_libs" }]
[tool.poetry.dependencies]
python = ">=3.10,<4.0"
colorama = "^0.4.6"
cryptography = "^45.0"
expiringdict = "^1.2.2"
fastapi = "^0.116.1"
google-cloud-logging = "^3.12.1"
launchdarkly-server-sdk = "^9.12.0"
pydantic = "^2.11.7"
pydantic-settings = "^2.10.1"
pyjwt = { version = "^2.10.1", extras = ["crypto"] }
pyjwt = "^2.10.1"
pytest-asyncio = "^1.1.0"
pytest-mock = "^3.14.1"
redis = "^6.2.0"
supabase = "^2.16.0"
uvicorn = "^0.35.0"
[tool.poetry.group.dev.dependencies]
pyright = "^1.1.404"
pytest = "^8.4.1"
pytest-asyncio = "^1.1.0"
pytest-mock = "^3.14.1"
pytest-cov = "^6.2.1"
ruff = "^0.12.11"
ruff = "^0.12.3"
[build-system]
requires = ["poetry-core"]

View File

@@ -1,52 +0,0 @@
# Development and testing files
**/__pycache__
**/*.pyc
**/*.pyo
**/*.pyd
**/.Python
**/env/
**/venv/
**/.venv/
**/pip-log.txt
**/.pytest_cache/
**/test-results/
**/snapshots/
**/test/
# IDE and editor files
**/.vscode/
**/.idea/
**/*.swp
**/*.swo
*~
# OS files
.DS_Store
Thumbs.db
# Logs
**/*.log
**/logs/
# Git
.git/
.gitignore
# Documentation
**/*.md
!README.md
# Local development files
.env
.env.local
**/.env.test
# Build artifacts
**/dist/
**/build/
**/target/
# Docker files (avoid recursion)
Dockerfile*
docker-compose*
.dockerignore

View File

@@ -1,9 +1,3 @@
# Backend Configuration
# This file contains environment variables that MUST be set for the AutoGPT platform
# Variables with working defaults in settings.py are not included here
## ===== REQUIRED DATABASE CONFIGURATION ===== ##
# PostgreSQL Database Connection
DB_USER=postgres
DB_PASS=your-super-secret-and-long-postgres-password
DB_NAME=postgres
@@ -17,48 +11,71 @@ DATABASE_URL="postgresql://${DB_USER}:${DB_PASS}@${DB_HOST}:${DB_PORT}/${DB_NAME
DIRECT_URL="postgresql://${DB_USER}:${DB_PASS}@${DB_HOST}:${DB_PORT}/${DB_NAME}?schema=${DB_SCHEMA}&connect_timeout=${DB_CONNECT_TIMEOUT}"
PRISMA_SCHEMA="postgres/schema.prisma"
## ===== REQUIRED SERVICE CREDENTIALS ===== ##
# Redis Configuration
# EXECUTOR
NUM_GRAPH_WORKERS=10
BACKEND_CORS_ALLOW_ORIGINS=["http://localhost:3000"]
# generate using `from cryptography.fernet import Fernet;Fernet.generate_key().decode()`
ENCRYPTION_KEY='dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw='
UNSUBSCRIBE_SECRET_KEY = 'HlP8ivStJjmbf6NKi78m_3FnOogut0t5ckzjsIqeaio='
REDIS_HOST=localhost
REDIS_PORT=6379
REDIS_PASSWORD=password
# RabbitMQ Credentials
ENABLE_CREDIT=false
STRIPE_API_KEY=
STRIPE_WEBHOOK_SECRET=
# What environment things should be logged under: local dev or prod
APP_ENV=local
# What environment to behave as: "local" or "cloud"
BEHAVE_AS=local
PYRO_HOST=localhost
SENTRY_DSN=
# Email For Postmark so we can send emails
POSTMARK_SERVER_API_TOKEN=
POSTMARK_SENDER_EMAIL=invalid@invalid.com
POSTMARK_WEBHOOK_TOKEN=
## User auth with Supabase is required for any of the 3rd party integrations with auth to work.
ENABLE_AUTH=true
SUPABASE_URL=http://localhost:8000
SUPABASE_SERVICE_ROLE_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJzZXJ2aWNlX3JvbGUiLAogICAgImlzcyI6ICJzdXBhYmFzZS1kZW1vIiwKICAgICJpYXQiOiAxNjQxNzY5MjAwLAogICAgImV4cCI6IDE3OTk1MzU2MDAKfQ.DaYlNEoUrrEn2Ig7tqibS-PHK5vgusbcbo7X36XVt4Q
SUPABASE_JWT_SECRET=your-super-secret-jwt-token-with-at-least-32-characters-long
# RabbitMQ credentials -- Used for communication between services
RABBITMQ_HOST=localhost
RABBITMQ_PORT=5672
RABBITMQ_DEFAULT_USER=rabbitmq_user_default
RABBITMQ_DEFAULT_PASS=k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7
# Supabase Authentication
SUPABASE_URL=http://localhost:8000
SUPABASE_SERVICE_ROLE_KEY=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJzZXJ2aWNlX3JvbGUiLAogICAgImlzcyI6ICJzdXBhYmFzZS1kZW1vIiwKICAgICJpYXQiOiAxNjQxNzY5MjAwLAogICAgImV4cCI6IDE3OTk1MzU2MDAKfQ.DaYlNEoUrrEn2Ig7tqibS-PHK5vgusbcbo7X36XVt4Q
JWT_VERIFY_KEY=your-super-secret-jwt-token-with-at-least-32-characters-long
## ===== REQUIRED SECURITY KEYS ===== ##
# Generate using: from cryptography.fernet import Fernet;Fernet.generate_key().decode()
ENCRYPTION_KEY=dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw=
UNSUBSCRIBE_SECRET_KEY=HlP8ivStJjmbf6NKi78m_3FnOogut0t5ckzjsIqeaio=
## ===== IMPORTANT OPTIONAL CONFIGURATION ===== ##
# Platform URLs (set these for webhooks and OAuth to work)
PLATFORM_BASE_URL=http://localhost:8000
FRONTEND_BASE_URL=http://localhost:3000
# Media Storage (required for marketplace and library functionality)
## GCS bucket is required for marketplace and library functionality
MEDIA_GCS_BUCKET_NAME=
## ===== API KEYS AND OAUTH CREDENTIALS ===== ##
# All API keys below are optional - only add what you need
## For local development, you may need to set FRONTEND_BASE_URL for the OAuth flow
## for integrations to work. Defaults to the value of PLATFORM_BASE_URL if not set.
# FRONTEND_BASE_URL=http://localhost:3000
# AI/LLM Services
OPENAI_API_KEY=
ANTHROPIC_API_KEY=
GROQ_API_KEY=
LLAMA_API_KEY=
AIML_API_KEY=
V0_API_KEY=
OPEN_ROUTER_API_KEY=
NVIDIA_API_KEY=
## PLATFORM_BASE_URL must be set to a *publicly accessible* URL pointing to your backend
## to use the platform's webhook-related functionality.
## If you are developing locally, you can use something like ngrok to get a publc URL
## and tunnel it to your locally running backend.
PLATFORM_BASE_URL=http://localhost:3000
## Cloudflare Turnstile (CAPTCHA) Configuration
## Get these from the Cloudflare Turnstile dashboard: https://dash.cloudflare.com/?to=/:account/turnstile
## This is the backend secret key
TURNSTILE_SECRET_KEY=
## This is the verify URL
TURNSTILE_VERIFY_URL=https://challenges.cloudflare.com/turnstile/v0/siteverify
## == INTEGRATION CREDENTIALS == ##
# Each set of server side credentials is required for the corresponding 3rd party
# integration to work.
# OAuth Credentials
# For the OAuth callback URL, use <your_frontend_url>/auth/integrations/oauth_callback,
# e.g. http://localhost:3000/auth/integrations/oauth_callback
@@ -68,6 +85,7 @@ GITHUB_CLIENT_SECRET=
# Google OAuth App server credentials - https://console.cloud.google.com/apis/credentials, and enable gmail api and set scopes
# https://console.cloud.google.com/apis/credentials/consent ?project=<your_project_id>
# You'll need to add/enable the following scopes (minimum):
# https://console.developers.google.com/apis/api/gmail.googleapis.com/overview ?project=<your_project_id>
# https://console.cloud.google.com/apis/library/sheets.googleapis.com/ ?project=<your_project_id>
@@ -103,75 +121,104 @@ LINEAR_CLIENT_SECRET=
TODOIST_CLIENT_ID=
TODOIST_CLIENT_SECRET=
NOTION_CLIENT_ID=
NOTION_CLIENT_SECRET=
## ===== OPTIONAL API KEYS ===== ##
# Discord OAuth App credentials
# 1. Go to https://discord.com/developers/applications
# 2. Create a new application
# 3. Go to OAuth2 section and add redirect URI: http://localhost:3000/auth/integrations/oauth_callback
# 4. Copy Client ID and Client Secret below
DISCORD_CLIENT_ID=
DISCORD_CLIENT_SECRET=
# LLM
OPENAI_API_KEY=
ANTHROPIC_API_KEY=
AIML_API_KEY=
GROQ_API_KEY=
OPEN_ROUTER_API_KEY=
LLAMA_API_KEY=
# Reddit
# Go to https://www.reddit.com/prefs/apps and create a new app
# Choose "script" for the type
# Fill in the redirect uri as <your_frontend_url>/auth/integrations/oauth_callback, e.g. http://localhost:3000/auth/integrations/oauth_callback
REDDIT_CLIENT_ID=
REDDIT_CLIENT_SECRET=
REDDIT_USER_AGENT="AutoGPT:1.0 (by /u/autogpt)"
# Payment Processing
STRIPE_API_KEY=
STRIPE_WEBHOOK_SECRET=
# Email Service (for sending notifications and confirmations)
POSTMARK_SERVER_API_TOKEN=
POSTMARK_SENDER_EMAIL=invalid@invalid.com
POSTMARK_WEBHOOK_TOKEN=
# Error Tracking
SENTRY_DSN=
# Cloudflare Turnstile (CAPTCHA) Configuration
# Get these from the Cloudflare Turnstile dashboard: https://dash.cloudflare.com/?to=/:account/turnstile
# This is the backend secret key
TURNSTILE_SECRET_KEY=
# This is the verify URL
TURNSTILE_VERIFY_URL=https://challenges.cloudflare.com/turnstile/v0/siteverify
# Feature Flags
LAUNCH_DARKLY_SDK_KEY=
# Content Generation & Media
DID_API_KEY=
FAL_API_KEY=
IDEOGRAM_API_KEY=
REPLICATE_API_KEY=
REVID_API_KEY=
SCREENSHOTONE_API_KEY=
UNREAL_SPEECH_API_KEY=
# Data & Search Services
E2B_API_KEY=
EXA_API_KEY=
JINA_API_KEY=
MEM0_API_KEY=
OPENWEATHERMAP_API_KEY=
GOOGLE_MAPS_API_KEY=
# Communication Services
# Discord
DISCORD_BOT_TOKEN=
MEDIUM_API_KEY=
MEDIUM_AUTHOR_ID=
# SMTP/Email
SMTP_SERVER=
SMTP_PORT=
SMTP_USERNAME=
SMTP_PASSWORD=
# Business & Marketing Tools
# D-ID
DID_API_KEY=
# Open Weather Map
OPENWEATHERMAP_API_KEY=
# SMTP
SMTP_SERVER=
SMTP_PORT=
SMTP_USERNAME=
SMTP_PASSWORD=
# Medium
MEDIUM_API_KEY=
MEDIUM_AUTHOR_ID=
# Google Maps
GOOGLE_MAPS_API_KEY=
# Replicate
REPLICATE_API_KEY=
# Ideogram
IDEOGRAM_API_KEY=
# Fal
FAL_API_KEY=
# Exa
EXA_API_KEY=
# E2B
E2B_API_KEY=
# Mem0
MEM0_API_KEY=
# Nvidia
NVIDIA_API_KEY=
# Apollo
APOLLO_API_KEY=
ENRICHLAYER_API_KEY=
AYRSHARE_API_KEY=
AYRSHARE_JWT_KEY=
# SmartLead
SMARTLEAD_API_KEY=
# ZeroBounce
ZEROBOUNCE_API_KEY=
# Other Services
AUTOMOD_API_KEY=
# Ayrshare
AYRSHARE_API_KEY=
AYRSHARE_JWT_KEY=
## ===== OPTIONAL API KEYS END ===== ##
# Block Error Rate Monitoring
BLOCK_ERROR_RATE_THRESHOLD=0.5
BLOCK_ERROR_RATE_CHECK_INTERVAL_SECS=86400
# Logging Configuration
LOG_LEVEL=INFO
ENABLE_CLOUD_LOGGING=false
ENABLE_FILE_LOGGING=false
# Use to manually set the log directory
# LOG_DIR=./logs
# Example Blocks Configuration
# Set to true to enable example blocks in development
# These blocks are disabled by default in production
ENABLE_EXAMPLE_BLOCKS=false
# Cloud Storage Configuration
# Cleanup interval for expired files (hours between cleanup runs, 1-24 hours)
CLOUD_STORAGE_CLEANUP_INTERVAL_HOURS=6

View File

@@ -1,4 +1,3 @@
.env
database.db
database.db-journal
dev.db

View File

@@ -1,34 +1,31 @@
FROM debian:13-slim AS builder
FROM python:3.11.10-slim-bookworm AS builder
# Set environment variables
ENV PYTHONDONTWRITEBYTECODE=1
ENV PYTHONUNBUFFERED=1
ENV DEBIAN_FRONTEND=noninteractive
ENV PYTHONDONTWRITEBYTECODE 1
ENV PYTHONUNBUFFERED 1
WORKDIR /app
RUN echo 'Acquire::http::Pipeline-Depth 0;\nAcquire::http::No-Cache true;\nAcquire::BrokenProxy true;\n' > /etc/apt/apt.conf.d/99fixbadproxy
# Update package list and install Python and build dependencies
RUN apt-get update --allow-releaseinfo-change --fix-missing \
&& apt-get install -y \
python3.13 \
python3.13-dev \
python3.13-venv \
python3-pip \
build-essential \
libpq5 \
libz-dev \
libssl-dev \
postgresql-client
RUN apt-get update --allow-releaseinfo-change --fix-missing
# Install build dependencies
RUN apt-get install -y build-essential
RUN apt-get install -y libpq5
RUN apt-get install -y libz-dev
RUN apt-get install -y libssl-dev
RUN apt-get install -y postgresql-client
ENV POETRY_HOME=/opt/poetry
ENV POETRY_NO_INTERACTION=1
ENV POETRY_VIRTUALENVS_CREATE=true
ENV POETRY_VIRTUALENVS_IN_PROJECT=true
ENV POETRY_VIRTUALENVS_CREATE=false
ENV PATH=/opt/poetry/bin:$PATH
RUN pip3 install poetry --break-system-packages
# Upgrade pip and setuptools to fix security vulnerabilities
RUN pip3 install --upgrade pip setuptools
RUN pip3 install poetry
# Copy and install dependencies
COPY autogpt_platform/autogpt_libs /app/autogpt_platform/autogpt_libs
@@ -40,30 +37,27 @@ RUN poetry install --no-ansi --no-root
COPY autogpt_platform/backend/schema.prisma ./
RUN poetry run prisma generate
FROM debian:13-slim AS server_dependencies
FROM python:3.11.10-slim-bookworm AS server_dependencies
WORKDIR /app
ENV POETRY_HOME=/opt/poetry \
POETRY_NO_INTERACTION=1 \
POETRY_VIRTUALENVS_CREATE=true \
POETRY_VIRTUALENVS_IN_PROJECT=true \
DEBIAN_FRONTEND=noninteractive
POETRY_VIRTUALENVS_CREATE=false
ENV PATH=/opt/poetry/bin:$PATH
# Install Python without upgrading system-managed packages
RUN apt-get update && apt-get install -y \
python3.13 \
python3-pip
# Upgrade pip and setuptools to fix security vulnerabilities
RUN pip3 install --upgrade pip setuptools
# Copy only necessary files from builder
COPY --from=builder /app /app
COPY --from=builder /usr/local/lib/python3* /usr/local/lib/python3*
COPY --from=builder /usr/local/bin/poetry /usr/local/bin/poetry
COPY --from=builder /usr/local/lib/python3.11 /usr/local/lib/python3.11
COPY --from=builder /usr/local/bin /usr/local/bin
# Copy Prisma binaries
COPY --from=builder /root/.cache/prisma-python/binaries /root/.cache/prisma-python/binaries
ENV PATH="/app/autogpt_platform/backend/.venv/bin:$PATH"
ENV PATH="/app/.venv/bin:$PATH"
RUN mkdir -p /app/autogpt_platform/autogpt_libs
RUN mkdir -p /app/autogpt_platform/backend
@@ -74,12 +68,6 @@ COPY autogpt_platform/backend/poetry.lock autogpt_platform/backend/pyproject.tom
WORKDIR /app/autogpt_platform/backend
FROM server_dependencies AS migrate
# 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/migrations /app/autogpt_platform/backend/migrations
FROM server_dependencies AS server
COPY autogpt_platform/backend /app/autogpt_platform/backend

View File

@@ -132,58 +132,17 @@ def test_endpoint_success(snapshot: Snapshot):
### Testing with Authentication
For the main API routes that use JWT authentication, auth is provided by the `autogpt_libs.auth` module. If the test actually uses the `user_id`, the recommended approach for testing is to mock the `get_jwt_payload` function, which underpins all higher-level auth functions used in the API (`requires_user`, `requires_admin_user`, `get_user_id`).
If the test doesn't need the `user_id` specifically, mocking is not necessary as during tests auth is disabled anyway (see `conftest.py`).
#### Using Global Auth Fixtures
Two global auth fixtures are provided by `backend/server/conftest.py`:
- `mock_jwt_user` - Regular user with `test_user_id` ("test-user-id")
- `mock_jwt_admin` - Admin user with `admin_user_id` ("admin-user-id")
These provide the easiest way to set up authentication mocking in test modules:
```python
import fastapi
import fastapi.testclient
import pytest
from backend.server.v2.myroute import router
def override_auth_middleware():
return {"sub": "test-user-id"}
app = fastapi.FastAPI()
app.include_router(router)
client = fastapi.testclient.TestClient(app)
def override_get_user_id():
return "test-user-id"
@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()
app.dependency_overrides[auth_middleware] = override_auth_middleware
app.dependency_overrides[get_user_id] = override_get_user_id
```
For admin-only endpoints, use `mock_jwt_admin` instead:
```python
@pytest.fixture(autouse=True)
def setup_app_auth(mock_jwt_admin):
"""Setup auth overrides for admin tests"""
from autogpt_libs.auth.jwt_utils import get_jwt_payload
app.dependency_overrides[get_jwt_payload] = mock_jwt_admin['get_jwt_payload']
yield
app.dependency_overrides.clear()
```
The IDs are also available separately as fixtures:
- `test_user_id`
- `admin_user_id`
- `target_user_id` (for admin <-> user operations)
### Mocking External Services
```python
@@ -194,10 +153,10 @@ def test_external_api_call(mocker, snapshot):
"backend.services.external_api.call",
return_value=mock_response
)
response = client.post("/api/process")
assert response.status_code == 200
snapshot.snapshot_dir = "snapshots"
snapshot.assert_match(
json.dumps(response.json(), indent=2, sort_keys=True),
@@ -228,17 +187,6 @@ def test_external_api_call(mocker, snapshot):
- Use `async def` with `@pytest.mark.asyncio` for testing async functions directly
### 5. Fixtures
#### Global Fixtures (conftest.py)
Authentication fixtures are available globally from `conftest.py`:
- `mock_jwt_user` - Standard user authentication
- `mock_jwt_admin` - Admin user authentication
- `configured_snapshot` - Pre-configured snapshot fixture
#### Custom Fixtures
Create reusable fixtures for common test data:
```python
@@ -254,18 +202,9 @@ def test_create_user(sample_user, snapshot):
# ... test implementation
```
#### Test Isolation
All tests must use fixtures that ensure proper isolation:
- Authentication overrides are automatically cleaned up after each test
- Database connections are properly managed with cleanup
- Mock objects are reset between tests
## CI/CD Integration
The GitHub Actions workflow automatically runs tests on:
- Pull requests
- Pushes to main branch
@@ -277,19 +216,16 @@ Snapshot tests work in CI by:
## Troubleshooting
### Snapshot Mismatches
- Review the diff carefully
- If changes are expected: `poetry run pytest --snapshot-update`
- If changes are unexpected: Fix the code causing the difference
### Async Test Issues
- Ensure async functions use `@pytest.mark.asyncio`
- Use `AsyncMock` for mocking async functions
- FastAPI TestClient handles async automatically
### Import Errors
- Check that all dependencies are in `pyproject.toml`
- Run `poetry install` to ensure dependencies are installed
- Verify import paths are correct
@@ -298,4 +234,4 @@ Snapshot tests work in CI by:
Snapshot testing provides a powerful way to ensure API responses remain consistent. Combined with traditional assertions, it creates a robust test suite that catches regressions while remaining maintainable.
Remember: Good tests are as important as good code!
Remember: Good tests are as important as good code!

View File

@@ -43,11 +43,11 @@ def main(**kwargs):
run_processes(
DatabaseManager().set_log_level("warning"),
ExecutionManager(),
Scheduler(),
NotificationManager(),
WebsocketServer(),
AgentServer(),
ExecutionManager(),
**kwargs,
)

View File

@@ -1,6 +1,9 @@
import asyncio
import logging
from typing import Any, Optional
from pydantic import JsonValue
from backend.data.block import (
Block,
BlockCategory,
@@ -10,10 +13,9 @@ from backend.data.block import (
BlockType,
get_block,
)
from backend.data.execution import ExecutionStatus, NodesInputMasks
from backend.data.execution import ExecutionStatus
from backend.data.model import NodeExecutionStats, SchemaField
from backend.util.json import validate_with_jsonschema
from backend.util.retry import func_retry
from backend.util import json, retry
_logger = logging.getLogger(__name__)
@@ -23,15 +25,12 @@ class AgentExecutorBlock(Block):
user_id: str = SchemaField(description="User ID")
graph_id: str = SchemaField(description="Graph ID")
graph_version: int = SchemaField(description="Graph Version")
agent_name: Optional[str] = SchemaField(
default=None, description="Name to display in the Builder UI"
)
inputs: BlockInput = SchemaField(description="Input data for the graph")
input_schema: dict = SchemaField(description="Input schema for the graph")
output_schema: dict = SchemaField(description="Output schema for the graph")
nodes_input_masks: Optional[NodesInputMasks] = SchemaField(
nodes_input_masks: Optional[dict[str, dict[str, JsonValue]]] = SchemaField(
default=None, hidden=True
)
@@ -50,7 +49,7 @@ class AgentExecutorBlock(Block):
@classmethod
def get_mismatch_error(cls, data: BlockInput) -> str | None:
return validate_with_jsonschema(cls.get_input_schema(data), data)
return json.validate_with_jsonschema(cls.get_input_schema(data), data)
class Output(BlockSchema):
pass
@@ -96,14 +95,23 @@ class AgentExecutorBlock(Block):
logger=logger,
):
yield name, data
except BaseException as e:
except asyncio.CancelledError:
await self._stop(
graph_exec_id=graph_exec.id,
user_id=input_data.user_id,
logger=logger,
)
logger.warning(
f"Execution of graph {input_data.graph_id}v{input_data.graph_version} failed: {e.__class__.__name__} {str(e)}; execution is stopped."
f"Execution of graph {input_data.graph_id}v{input_data.graph_version} was cancelled."
)
except Exception as e:
await self._stop(
graph_exec_id=graph_exec.id,
user_id=input_data.user_id,
logger=logger,
)
logger.error(
f"Execution of graph {input_data.graph_id}v{input_data.graph_version} failed: {e}, execution is stopped."
)
raise
@@ -123,7 +131,6 @@ class AgentExecutorBlock(Block):
log_id = f"Graph #{graph_id}-V{graph_version}, exec-id: {graph_exec_id}"
logger.info(f"Starting execution of {log_id}")
yielded_node_exec_ids = set()
async for event in event_bus.listen(
user_id=user_id,
@@ -155,14 +162,6 @@ class AgentExecutorBlock(Block):
f"Execution {log_id} produced input {event.input_data} output {event.output_data}"
)
if event.node_exec_id in yielded_node_exec_ids:
logger.warning(
f"{log_id} received duplicate event for node execution {event.node_exec_id}"
)
continue
else:
yielded_node_exec_ids.add(event.node_exec_id)
if not event.block_id:
logger.warning(f"{log_id} received event without block_id {event}")
continue
@@ -182,7 +181,7 @@ class AgentExecutorBlock(Block):
)
yield output_name, output_data
@func_retry
@retry.func_retry
async def _stop(
self,
graph_exec_id: str,
@@ -198,8 +197,7 @@ class AgentExecutorBlock(Block):
await execution_utils.stop_graph_execution(
graph_exec_id=graph_exec_id,
user_id=user_id,
wait_timeout=3600,
)
logger.info(f"Execution {log_id} stopped successfully.")
except TimeoutError as e:
logger.error(f"Execution {log_id} stop timed out: {e}")
except Exception as e:
logger.error(f"Failed to stop execution {log_id}: {e}")

View File

@@ -1,154 +0,0 @@
from enum import Enum
from typing import Literal
from pydantic import SecretStr
from replicate.client import Client as ReplicateClient
from replicate.helpers import FileOutput
from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
from backend.data.model import (
APIKeyCredentials,
CredentialsField,
CredentialsMetaInput,
SchemaField,
)
from backend.integrations.providers import ProviderName
from backend.util.file import MediaFileType
class GeminiImageModel(str, Enum):
NANO_BANANA = "google/nano-banana"
class OutputFormat(str, Enum):
JPG = "jpg"
PNG = "png"
TEST_CREDENTIALS = APIKeyCredentials(
id="01234567-89ab-cdef-0123-456789abcdef",
provider="replicate",
api_key=SecretStr("mock-replicate-api-key"),
title="Mock Replicate API key",
expires_at=None,
)
TEST_CREDENTIALS_INPUT = {
"provider": TEST_CREDENTIALS.provider,
"id": TEST_CREDENTIALS.id,
"type": TEST_CREDENTIALS.type,
"title": TEST_CREDENTIALS.title,
}
class AIImageCustomizerBlock(Block):
class Input(BlockSchema):
credentials: CredentialsMetaInput[
Literal[ProviderName.REPLICATE], Literal["api_key"]
] = CredentialsField(
description="Replicate API key with permissions for Google Gemini image models",
)
prompt: str = SchemaField(
description="A text description of the image you want to generate",
title="Prompt",
)
model: GeminiImageModel = SchemaField(
description="The AI model to use for image generation and editing",
default=GeminiImageModel.NANO_BANANA,
title="Model",
)
images: list[MediaFileType] = SchemaField(
description="Optional list of input images to reference or modify",
default=[],
title="Input Images",
)
output_format: OutputFormat = SchemaField(
description="Format of the output image",
default=OutputFormat.PNG,
title="Output Format",
)
class Output(BlockSchema):
image_url: MediaFileType = SchemaField(description="URL of the generated image")
error: str = SchemaField(description="Error message if generation failed")
def __init__(self):
super().__init__(
id="d76bbe4c-930e-4894-8469-b66775511f71",
description=(
"Generate and edit custom images using Google's Nano-Banana model from Gemini 2.5. "
"Provide a prompt and optional reference images to create or modify images."
),
categories={BlockCategory.AI, BlockCategory.MULTIMEDIA},
input_schema=AIImageCustomizerBlock.Input,
output_schema=AIImageCustomizerBlock.Output,
test_input={
"prompt": "Make the scene more vibrant and colorful",
"model": GeminiImageModel.NANO_BANANA,
"images": [],
"output_format": OutputFormat.JPG,
"credentials": TEST_CREDENTIALS_INPUT,
},
test_output=[
("image_url", "https://replicate.delivery/generated-image.jpg"),
],
test_mock={
"run_model": lambda *args, **kwargs: MediaFileType(
"https://replicate.delivery/generated-image.jpg"
),
},
test_credentials=TEST_CREDENTIALS,
)
async def run(
self,
input_data: Input,
*,
credentials: APIKeyCredentials,
graph_exec_id: str,
user_id: str,
**kwargs,
) -> BlockOutput:
try:
result = await self.run_model(
api_key=credentials.api_key,
model_name=input_data.model.value,
prompt=input_data.prompt,
images=input_data.images,
output_format=input_data.output_format.value,
)
yield "image_url", result
except Exception as e:
yield "error", str(e)
async def run_model(
self,
api_key: SecretStr,
model_name: str,
prompt: str,
images: list[MediaFileType],
output_format: str,
) -> MediaFileType:
client = ReplicateClient(api_token=api_key.get_secret_value())
input_params: dict = {
"prompt": prompt,
"output_format": output_format,
}
# Add images to input if provided (API expects "image_input" parameter)
if images:
input_params["image_input"] = [str(img) for img in images]
output: FileOutput | str = await client.async_run( # type: ignore
model_name,
input=input_params,
wait=False,
)
if isinstance(output, FileOutput):
return MediaFileType(output.url)
if isinstance(output, str):
return MediaFileType(output)
raise ValueError("No output received from the model")

View File

@@ -166,7 +166,7 @@ class AIMusicGeneratorBlock(Block):
output_format=input_data.output_format,
normalization_strategy=input_data.normalization_strategy,
)
if result and isinstance(result, str) and result.startswith("http"):
if result and result != "No output received":
yield "result", result
return
else:

View File

@@ -9,24 +9,6 @@ from backend.sdk import BaseModel, Credentials, Requests
logger = getLogger(__name__)
def _convert_bools(
obj: Any,
) -> Any: # noqa: ANN401 allow Any for deep conversion utility
"""Recursively walk *obj* and coerce string booleans to real booleans."""
if isinstance(obj, str):
lowered = obj.lower()
if lowered == "true":
return True
if lowered == "false":
return False
return obj
if isinstance(obj, list):
return [_convert_bools(item) for item in obj]
if isinstance(obj, dict):
return {k: _convert_bools(v) for k, v in obj.items()}
return obj
class WebhookFilters(BaseModel):
dataTypes: list[str]
changeTypes: list[str] | None = None
@@ -597,7 +579,7 @@ async def update_table(
response = await Requests().patch(
f"https://api.airtable.com/v0/meta/bases/{base_id}/tables/{table_id}",
headers={"Authorization": credentials.auth_header()},
json=_convert_bools(params),
json=params,
)
return response.json()
@@ -627,7 +609,7 @@ async def create_field(
response = await Requests().post(
f"https://api.airtable.com/v0/meta/bases/{base_id}/tables/{table_id}/fields",
headers={"Authorization": credentials.auth_header()},
json=_convert_bools(params),
json=params,
)
return response.json()
@@ -651,7 +633,7 @@ async def update_field(
response = await Requests().patch(
f"https://api.airtable.com/v0/meta/bases/{base_id}/tables/{table_id}/fields/{field_id}",
headers={"Authorization": credentials.auth_header()},
json=_convert_bools(params),
json=params,
)
return response.json()
@@ -661,167 +643,6 @@ async def update_field(
#################################################################
async def get_table_schema(
credentials: Credentials,
base_id: str,
table_id_or_name: str,
) -> dict:
"""
Get the schema for a specific table, including all field definitions.
Args:
credentials: Airtable API credentials
base_id: The base ID
table_id_or_name: The table ID or name
Returns:
Dict containing table schema with fields information
"""
# First get all tables to find the right one
response = await Requests().get(
f"https://api.airtable.com/v0/meta/bases/{base_id}/tables",
headers={"Authorization": credentials.auth_header()},
)
data = response.json()
tables = data.get("tables", [])
# Find the matching table
for table in tables:
if table.get("id") == table_id_or_name or table.get("name") == table_id_or_name:
return table
raise ValueError(f"Table '{table_id_or_name}' not found in base '{base_id}'")
def get_empty_value_for_field(field_type: str) -> Any:
"""
Return the appropriate empty value for a given Airtable field type.
Args:
field_type: The Airtable field type
Returns:
The appropriate empty value for that field type
"""
# Fields that should be false when empty
if field_type == "checkbox":
return False
# Fields that should be empty arrays
if field_type in [
"multipleSelects",
"multipleRecordLinks",
"multipleAttachments",
"multipleLookupValues",
"multipleCollaborators",
]:
return []
# Fields that should be 0 when empty (numeric types)
if field_type in [
"number",
"percent",
"currency",
"rating",
"duration",
"count",
"autoNumber",
]:
return 0
# Fields that should be empty strings
if field_type in [
"singleLineText",
"multilineText",
"email",
"url",
"phoneNumber",
"richText",
"barcode",
]:
return ""
# Everything else gets null (dates, single selects, formulas, etc.)
return None
async def normalize_records(
records: list[dict],
table_schema: dict,
include_field_metadata: bool = False,
) -> dict:
"""
Normalize Airtable records to include all fields with proper empty values.
Args:
records: List of record objects from Airtable API
table_schema: Table schema containing field definitions
include_field_metadata: Whether to include field metadata in response
Returns:
Dict with normalized records and optionally field metadata
"""
fields = table_schema.get("fields", [])
# Normalize each record
normalized_records = []
for record in records:
normalized = {
"id": record.get("id"),
"createdTime": record.get("createdTime"),
"fields": {},
}
# Add existing fields
existing_fields = record.get("fields", {})
# Add all fields from schema, using empty values for missing ones
for field in fields:
field_name = field["name"]
field_type = field["type"]
if field_name in existing_fields:
# Field exists, use its value
normalized["fields"][field_name] = existing_fields[field_name]
else:
# Field is missing, add appropriate empty value
normalized["fields"][field_name] = get_empty_value_for_field(field_type)
normalized_records.append(normalized)
# Build result dictionary
if include_field_metadata:
field_metadata = {}
for field in fields:
metadata = {"type": field["type"], "id": field["id"]}
# Add type-specific metadata
options = field.get("options", {})
if field["type"] == "currency" and "symbol" in options:
metadata["symbol"] = options["symbol"]
metadata["precision"] = options.get("precision", 2)
elif field["type"] == "duration" and "durationFormat" in options:
metadata["format"] = options["durationFormat"]
elif field["type"] == "percent" and "precision" in options:
metadata["precision"] = options["precision"]
elif (
field["type"] in ["singleSelect", "multipleSelects"]
and "choices" in options
):
metadata["choices"] = [choice["name"] for choice in options["choices"]]
elif field["type"] == "rating" and "max" in options:
metadata["max"] = options["max"]
metadata["icon"] = options.get("icon", "star")
metadata["color"] = options.get("color", "yellowBright")
field_metadata[field["name"]] = metadata
return {"records": normalized_records, "field_metadata": field_metadata}
else:
return {"records": normalized_records}
async def list_records(
credentials: Credentials,
base_id: str,
@@ -870,7 +691,7 @@ async def list_records(
response = await Requests().get(
f"https://api.airtable.com/v0/{base_id}/{table_id_or_name}",
headers={"Authorization": credentials.auth_header()},
json=_convert_bools(params),
params=params,
)
return response.json()
@@ -899,22 +720,20 @@ async def update_multiple_records(
typecast: bool | None = None,
) -> dict[str, dict[str, dict[str, str]]]:
params: dict[
str, str | bool | dict[str, list[str]] | list[dict[str, dict[str, str]]]
] = {}
params: dict[str, str | dict[str, list[str]] | list[dict[str, dict[str, str]]]] = {}
if perform_upsert:
params["performUpsert"] = perform_upsert
if return_fields_by_field_id:
params["returnFieldsByFieldId"] = str(return_fields_by_field_id)
if typecast:
params["typecast"] = typecast
params["typecast"] = str(typecast)
params["records"] = [_convert_bools(record) for record in records]
params["records"] = records
response = await Requests().patch(
f"https://api.airtable.com/v0/{base_id}/{table_id_or_name}",
headers={"Authorization": credentials.auth_header()},
json=_convert_bools(params),
json=params,
)
return response.json()
@@ -928,20 +747,18 @@ async def update_record(
typecast: bool | None = None,
fields: dict[str, Any] | None = None,
) -> dict[str, dict[str, dict[str, str]]]:
params: dict[str, str | bool | dict[str, Any] | list[dict[str, dict[str, str]]]] = (
{}
)
params: dict[str, str | dict[str, Any] | list[dict[str, dict[str, str]]]] = {}
if return_fields_by_field_id:
params["returnFieldsByFieldId"] = return_fields_by_field_id
params["returnFieldsByFieldId"] = str(return_fields_by_field_id)
if typecast:
params["typecast"] = typecast
params["typecast"] = str(typecast)
if fields:
params["fields"] = fields
response = await Requests().patch(
f"https://api.airtable.com/v0/{base_id}/{table_id_or_name}/{record_id}",
headers={"Authorization": credentials.auth_header()},
json=_convert_bools(params),
json=params,
)
return response.json()
@@ -962,22 +779,21 @@ async def create_record(
len(records) <= 10
), "Only up to 10 records can be provided when using records"
params: dict[str, str | bool | dict[str, Any] | list[dict[str, Any]]] = {}
params: dict[str, str | dict[str, Any] | list[dict[str, Any]]] = {}
if fields:
params["fields"] = fields
if records:
params["records"] = records
if return_fields_by_field_id:
params["returnFieldsByFieldId"] = return_fields_by_field_id
params["returnFieldsByFieldId"] = str(return_fields_by_field_id)
if typecast:
params["typecast"] = typecast
params["typecast"] = str(typecast)
response = await Requests().post(
f"https://api.airtable.com/v0/{base_id}/{table_id_or_name}",
headers={"Authorization": credentials.auth_header()},
json=_convert_bools(params),
json=params,
)
return response.json()
@@ -1034,7 +850,7 @@ async def create_webhook(
response = await Requests().post(
f"https://api.airtable.com/v0/bases/{base_id}/webhooks",
headers={"Authorization": credentials.auth_header()},
json=_convert_bools(params),
json=params,
)
return response.json()
@@ -1379,7 +1195,7 @@ async def create_base(
"Authorization": credentials.auth_header(),
"Content-Type": "application/json",
},
json=_convert_bools(params),
json=params,
)
return response.json()
@@ -1410,26 +1226,3 @@ async def list_bases(
)
return response.json()
async def get_base_tables(
credentials: Credentials,
base_id: str,
) -> list[dict]:
"""
Get all tables for a specific base.
Args:
credentials: Airtable API credentials
base_id: The ID of the base
Returns:
list[dict]: List of table objects with their schemas
"""
response = await Requests().get(
f"https://api.airtable.com/v0/meta/bases/{base_id}/tables",
headers={"Authorization": credentials.auth_header()},
)
data = response.json()
return data.get("tables", [])

View File

@@ -159,7 +159,6 @@ class AirtableOAuthHandler(BaseOAuthHandler):
logger.info("Successfully refreshed tokens")
new_credentials = OAuth2Credentials(
id=credentials.id,
access_token=SecretStr(response.access_token),
refresh_token=SecretStr(response.refresh_token),
access_token_expires_at=int(time.time()) + response.expires_in,

View File

@@ -14,13 +14,13 @@ from backend.sdk import (
SchemaField,
)
from ._api import create_base, get_base_tables, list_bases
from ._api import create_base, list_bases
from ._config import airtable
class AirtableCreateBaseBlock(Block):
"""
Creates a new base in an Airtable workspace, or returns existing base if one with the same name exists.
Creates a new base in an Airtable workspace.
"""
class Input(BlockSchema):
@@ -31,10 +31,6 @@ class AirtableCreateBaseBlock(Block):
description="The workspace ID where the base will be created"
)
name: str = SchemaField(description="The name of the new base")
find_existing: bool = SchemaField(
description="If true, return existing base with same name instead of creating duplicate",
default=True,
)
tables: list[dict] = SchemaField(
description="At least one table and field must be specified. Array of table objects to create in the base. Each table should have 'name' and 'fields' properties",
default=[
@@ -54,18 +50,14 @@ class AirtableCreateBaseBlock(Block):
)
class Output(BlockSchema):
base_id: str = SchemaField(description="The ID of the created or found base")
base_id: str = SchemaField(description="The ID of the created base")
tables: list[dict] = SchemaField(description="Array of table objects")
table: dict = SchemaField(description="A single table object")
was_created: bool = SchemaField(
description="True if a new base was created, False if existing was found",
default=True,
)
def __init__(self):
super().__init__(
id="f59b88a8-54ce-4676-a508-fd614b4e8dce",
description="Create or find a base in Airtable",
description="Create a new base in Airtable",
categories={BlockCategory.DATA},
input_schema=self.Input,
output_schema=self.Output,
@@ -74,31 +66,6 @@ class AirtableCreateBaseBlock(Block):
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
# If find_existing is true, check if a base with this name already exists
if input_data.find_existing:
# List all bases to check for existing one with same name
# Note: Airtable API doesn't have a direct search, so we need to list and filter
existing_bases = await list_bases(credentials)
for base in existing_bases.get("bases", []):
if base.get("name") == input_data.name:
# Base already exists, return it
base_id = base.get("id")
yield "base_id", base_id
yield "was_created", False
# Get the tables for this base
try:
tables = await get_base_tables(credentials, base_id)
yield "tables", tables
for table in tables:
yield "table", table
except Exception:
# If we can't get tables, return empty list
yield "tables", []
return
# No existing base found or find_existing is false, create new one
data = await create_base(
credentials,
input_data.workspace_id,
@@ -107,7 +74,6 @@ class AirtableCreateBaseBlock(Block):
)
yield "base_id", data.get("id", None)
yield "was_created", True
yield "tables", data.get("tables", [])
for table in data.get("tables", []):
yield "table", table

View File

@@ -2,7 +2,7 @@
Airtable record operation blocks.
"""
from typing import Optional, cast
from typing import Optional
from backend.sdk import (
APIKeyCredentials,
@@ -18,9 +18,7 @@ from ._api import (
create_record,
delete_multiple_records,
get_record,
get_table_schema,
list_records,
normalize_records,
update_multiple_records,
)
from ._config import airtable
@@ -56,24 +54,12 @@ class AirtableListRecordsBlock(Block):
return_fields: list[str] = SchemaField(
description="Specific fields to return (comma-separated)", default=[]
)
normalize_output: bool = SchemaField(
description="Normalize output to include all fields with proper empty values (disable to skip schema fetch and get raw Airtable response)",
default=True,
)
include_field_metadata: bool = SchemaField(
description="Include field type and configuration metadata (requires normalize_output=true)",
default=False,
)
class Output(BlockSchema):
records: list[dict] = SchemaField(description="Array of record objects")
offset: Optional[str] = SchemaField(
description="Offset for next page (null if no more records)", default=None
)
field_metadata: Optional[dict] = SchemaField(
description="Field type and configuration metadata (only when include_field_metadata=true)",
default=None,
)
def __init__(self):
super().__init__(
@@ -87,7 +73,6 @@ class AirtableListRecordsBlock(Block):
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
data = await list_records(
credentials,
input_data.base_id,
@@ -103,33 +88,8 @@ class AirtableListRecordsBlock(Block):
fields=input_data.return_fields if input_data.return_fields else None,
)
records = data.get("records", [])
# Normalize output if requested
if input_data.normalize_output:
# Fetch table schema
table_schema = await get_table_schema(
credentials, input_data.base_id, input_data.table_id_or_name
)
# Normalize the records
normalized_data = await normalize_records(
records,
table_schema,
include_field_metadata=input_data.include_field_metadata,
)
yield "records", normalized_data["records"]
yield "offset", data.get("offset", None)
if (
input_data.include_field_metadata
and "field_metadata" in normalized_data
):
yield "field_metadata", normalized_data["field_metadata"]
else:
yield "records", records
yield "offset", data.get("offset", None)
yield "records", data.get("records", [])
yield "offset", data.get("offset", None)
class AirtableGetRecordBlock(Block):
@@ -144,23 +104,11 @@ class AirtableGetRecordBlock(Block):
base_id: str = SchemaField(description="The Airtable base ID")
table_id_or_name: str = SchemaField(description="Table ID or name")
record_id: str = SchemaField(description="The record ID to retrieve")
normalize_output: bool = SchemaField(
description="Normalize output to include all fields with proper empty values (disable to skip schema fetch and get raw Airtable response)",
default=True,
)
include_field_metadata: bool = SchemaField(
description="Include field type and configuration metadata (requires normalize_output=true)",
default=False,
)
class Output(BlockSchema):
id: str = SchemaField(description="The record ID")
fields: dict = SchemaField(description="The record fields")
created_time: str = SchemaField(description="The record created time")
field_metadata: Optional[dict] = SchemaField(
description="Field type and configuration metadata (only when include_field_metadata=true)",
default=None,
)
def __init__(self):
super().__init__(
@@ -174,7 +122,6 @@ class AirtableGetRecordBlock(Block):
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
record = await get_record(
credentials,
input_data.base_id,
@@ -182,34 +129,9 @@ class AirtableGetRecordBlock(Block):
input_data.record_id,
)
# Normalize output if requested
if input_data.normalize_output:
# Fetch table schema
table_schema = await get_table_schema(
credentials, input_data.base_id, input_data.table_id_or_name
)
# Normalize the single record (wrap in list and unwrap result)
normalized_data = await normalize_records(
[record],
table_schema,
include_field_metadata=input_data.include_field_metadata,
)
normalized_record = normalized_data["records"][0]
yield "id", normalized_record.get("id", None)
yield "fields", normalized_record.get("fields", None)
yield "created_time", normalized_record.get("createdTime", None)
if (
input_data.include_field_metadata
and "field_metadata" in normalized_data
):
yield "field_metadata", normalized_data["field_metadata"]
else:
yield "id", record.get("id", None)
yield "fields", record.get("fields", None)
yield "created_time", record.get("createdTime", None)
yield "id", record.get("id", None)
yield "fields", record.get("fields", None)
yield "created_time", record.get("createdTime", None)
class AirtableCreateRecordsBlock(Block):
@@ -226,10 +148,6 @@ class AirtableCreateRecordsBlock(Block):
records: list[dict] = SchemaField(
description="Array of records to create (each with 'fields' object)"
)
skip_normalization: bool = SchemaField(
description="Skip output normalization to get raw Airtable response (faster but may have missing fields)",
default=False,
)
typecast: bool = SchemaField(
description="Automatically convert string values to appropriate types",
default=False,
@@ -241,6 +159,7 @@ class AirtableCreateRecordsBlock(Block):
class Output(BlockSchema):
records: list[dict] = SchemaField(description="Array of created record objects")
details: dict = SchemaField(description="Details of the created records")
def __init__(self):
super().__init__(
@@ -254,7 +173,7 @@ class AirtableCreateRecordsBlock(Block):
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
# The create_record API expects records in a specific format
data = await create_record(
credentials,
input_data.base_id,
@@ -263,22 +182,11 @@ class AirtableCreateRecordsBlock(Block):
typecast=input_data.typecast if input_data.typecast else None,
return_fields_by_field_id=input_data.return_fields_by_field_id,
)
result_records = cast(list[dict], data.get("records", []))
# Normalize output unless explicitly disabled
if not input_data.skip_normalization and result_records:
# Fetch table schema
table_schema = await get_table_schema(
credentials, input_data.base_id, input_data.table_id_or_name
)
# Normalize the records
normalized_data = await normalize_records(
result_records, table_schema, include_field_metadata=False
)
result_records = normalized_data["records"]
yield "records", result_records
yield "records", data.get("records", [])
details = data.get("details", None)
if details:
yield "details", details
class AirtableUpdateRecordsBlock(Block):

View File

@@ -4,19 +4,11 @@ from typing import Optional
from pydantic import BaseModel, Field
from backend.data.block import BlockSchema
from backend.data.model import SchemaField, UserIntegrations
from backend.data.model import SchemaField
from backend.integrations.ayrshare import AyrshareClient
from backend.util.clients import get_database_manager_async_client
from backend.util.exceptions import MissingConfigError
async def get_profile_key(user_id: str):
user_integrations: UserIntegrations = (
await get_database_manager_async_client().get_user_integrations(user_id)
)
return user_integrations.managed_credentials.ayrshare_profile_key
class BaseAyrshareInput(BlockSchema):
"""Base input model for Ayrshare social media posts with common fields."""

View File

@@ -6,9 +6,10 @@ from backend.sdk import (
BlockSchema,
BlockType,
SchemaField,
SecretStr,
)
from ._util import BaseAyrshareInput, create_ayrshare_client, get_profile_key
from ._util import BaseAyrshareInput, create_ayrshare_client
class PostToBlueskyBlock(Block):
@@ -57,12 +58,10 @@ class PostToBlueskyBlock(Block):
self,
input_data: "PostToBlueskyBlock.Input",
*,
user_id: str,
profile_key: SecretStr,
**kwargs,
) -> BlockOutput:
"""Post to Bluesky with Bluesky-specific options."""
profile_key = await get_profile_key(user_id)
if not profile_key:
yield "error", "Please link a social account via Ayrshare"
return

View File

@@ -6,14 +6,10 @@ from backend.sdk import (
BlockSchema,
BlockType,
SchemaField,
SecretStr,
)
from ._util import (
BaseAyrshareInput,
CarouselItem,
create_ayrshare_client,
get_profile_key,
)
from ._util import BaseAyrshareInput, CarouselItem, create_ayrshare_client
class PostToFacebookBlock(Block):
@@ -120,11 +116,10 @@ class PostToFacebookBlock(Block):
self,
input_data: "PostToFacebookBlock.Input",
*,
user_id: str,
profile_key: SecretStr,
**kwargs,
) -> BlockOutput:
"""Post to Facebook with Facebook-specific options."""
profile_key = await get_profile_key(user_id)
if not profile_key:
yield "error", "Please link a social account via Ayrshare"
return

View File

@@ -6,9 +6,10 @@ from backend.sdk import (
BlockSchema,
BlockType,
SchemaField,
SecretStr,
)
from ._util import BaseAyrshareInput, create_ayrshare_client, get_profile_key
from ._util import BaseAyrshareInput, create_ayrshare_client
class PostToGMBBlock(Block):
@@ -110,10 +111,9 @@ class PostToGMBBlock(Block):
)
async def run(
self, input_data: "PostToGMBBlock.Input", *, user_id: str, **kwargs
self, input_data: "PostToGMBBlock.Input", *, profile_key: SecretStr, **kwargs
) -> BlockOutput:
"""Post to Google My Business with GMB-specific options."""
profile_key = await get_profile_key(user_id)
if not profile_key:
yield "error", "Please link a social account via Ayrshare"
return

View File

@@ -8,14 +8,10 @@ from backend.sdk import (
BlockSchema,
BlockType,
SchemaField,
SecretStr,
)
from ._util import (
BaseAyrshareInput,
InstagramUserTag,
create_ayrshare_client,
get_profile_key,
)
from ._util import BaseAyrshareInput, InstagramUserTag, create_ayrshare_client
class PostToInstagramBlock(Block):
@@ -112,11 +108,10 @@ class PostToInstagramBlock(Block):
self,
input_data: "PostToInstagramBlock.Input",
*,
user_id: str,
profile_key: SecretStr,
**kwargs,
) -> BlockOutput:
"""Post to Instagram with Instagram-specific options."""
profile_key = await get_profile_key(user_id)
if not profile_key:
yield "error", "Please link a social account via Ayrshare"
return

View File

@@ -6,9 +6,10 @@ from backend.sdk import (
BlockSchema,
BlockType,
SchemaField,
SecretStr,
)
from ._util import BaseAyrshareInput, create_ayrshare_client, get_profile_key
from ._util import BaseAyrshareInput, create_ayrshare_client
class PostToLinkedInBlock(Block):
@@ -112,11 +113,10 @@ class PostToLinkedInBlock(Block):
self,
input_data: "PostToLinkedInBlock.Input",
*,
user_id: str,
profile_key: SecretStr,
**kwargs,
) -> BlockOutput:
"""Post to LinkedIn with LinkedIn-specific options."""
profile_key = await get_profile_key(user_id)
if not profile_key:
yield "error", "Please link a social account via Ayrshare"
return

View File

@@ -6,14 +6,10 @@ from backend.sdk import (
BlockSchema,
BlockType,
SchemaField,
SecretStr,
)
from ._util import (
BaseAyrshareInput,
PinterestCarouselOption,
create_ayrshare_client,
get_profile_key,
)
from ._util import BaseAyrshareInput, PinterestCarouselOption, create_ayrshare_client
class PostToPinterestBlock(Block):
@@ -92,11 +88,10 @@ class PostToPinterestBlock(Block):
self,
input_data: "PostToPinterestBlock.Input",
*,
user_id: str,
profile_key: SecretStr,
**kwargs,
) -> BlockOutput:
"""Post to Pinterest with Pinterest-specific options."""
profile_key = await get_profile_key(user_id)
if not profile_key:
yield "error", "Please link a social account via Ayrshare"
return

View File

@@ -6,9 +6,10 @@ from backend.sdk import (
BlockSchema,
BlockType,
SchemaField,
SecretStr,
)
from ._util import BaseAyrshareInput, create_ayrshare_client, get_profile_key
from ._util import BaseAyrshareInput, create_ayrshare_client
class PostToRedditBlock(Block):
@@ -35,9 +36,8 @@ class PostToRedditBlock(Block):
)
async def run(
self, input_data: "PostToRedditBlock.Input", *, user_id: str, **kwargs
self, input_data: "PostToRedditBlock.Input", *, profile_key: SecretStr, **kwargs
) -> BlockOutput:
profile_key = await get_profile_key(user_id)
if not profile_key:
yield "error", "Please link a social account via Ayrshare"
return

View File

@@ -6,9 +6,10 @@ from backend.sdk import (
BlockSchema,
BlockType,
SchemaField,
SecretStr,
)
from ._util import BaseAyrshareInput, create_ayrshare_client, get_profile_key
from ._util import BaseAyrshareInput, create_ayrshare_client
class PostToSnapchatBlock(Block):
@@ -62,11 +63,10 @@ class PostToSnapchatBlock(Block):
self,
input_data: "PostToSnapchatBlock.Input",
*,
user_id: str,
profile_key: SecretStr,
**kwargs,
) -> BlockOutput:
"""Post to Snapchat with Snapchat-specific options."""
profile_key = await get_profile_key(user_id)
if not profile_key:
yield "error", "Please link a social account via Ayrshare"
return

View File

@@ -6,9 +6,10 @@ from backend.sdk import (
BlockSchema,
BlockType,
SchemaField,
SecretStr,
)
from ._util import BaseAyrshareInput, create_ayrshare_client, get_profile_key
from ._util import BaseAyrshareInput, create_ayrshare_client
class PostToTelegramBlock(Block):
@@ -57,11 +58,10 @@ class PostToTelegramBlock(Block):
self,
input_data: "PostToTelegramBlock.Input",
*,
user_id: str,
profile_key: SecretStr,
**kwargs,
) -> BlockOutput:
"""Post to Telegram with Telegram-specific validation."""
profile_key = await get_profile_key(user_id)
if not profile_key:
yield "error", "Please link a social account via Ayrshare"
return

View File

@@ -6,9 +6,10 @@ from backend.sdk import (
BlockSchema,
BlockType,
SchemaField,
SecretStr,
)
from ._util import BaseAyrshareInput, create_ayrshare_client, get_profile_key
from ._util import BaseAyrshareInput, create_ayrshare_client
class PostToThreadsBlock(Block):
@@ -50,11 +51,10 @@ class PostToThreadsBlock(Block):
self,
input_data: "PostToThreadsBlock.Input",
*,
user_id: str,
profile_key: SecretStr,
**kwargs,
) -> BlockOutput:
"""Post to Threads with Threads-specific validation."""
profile_key = await get_profile_key(user_id)
if not profile_key:
yield "error", "Please link a social account via Ayrshare"
return

View File

@@ -1,5 +1,3 @@
from enum import Enum
from backend.integrations.ayrshare import PostIds, PostResponse, SocialPlatform
from backend.sdk import (
Block,
@@ -8,15 +6,10 @@ from backend.sdk import (
BlockSchema,
BlockType,
SchemaField,
SecretStr,
)
from ._util import BaseAyrshareInput, create_ayrshare_client, get_profile_key
class TikTokVisibility(str, Enum):
PUBLIC = "public"
PRIVATE = "private"
FOLLOWERS = "followers"
from ._util import BaseAyrshareInput, create_ayrshare_client
class PostToTikTokBlock(Block):
@@ -28,6 +21,7 @@ class PostToTikTokBlock(Block):
# Override post field to include TikTok-specific information
post: str = SchemaField(
description="The post text (max 2,200 chars, empty string allowed). Use @handle to mention users. Line breaks will be ignored.",
default="",
advanced=False,
)
@@ -40,7 +34,7 @@ class PostToTikTokBlock(Block):
# TikTok-specific options
auto_add_music: bool = SchemaField(
description="Whether to automatically add recommended music to the post. If you set this field to true, you can change the music later in the TikTok app.",
description="Automatically add recommended music to image posts",
default=False,
advanced=True,
)
@@ -60,17 +54,17 @@ class PostToTikTokBlock(Block):
advanced=True,
)
is_ai_generated: bool = SchemaField(
description="If you enable the toggle, your video will be labeled as “Creator labeled as AI-generated” once posted and cant be changed. The “Creator labeled as AI-generated” label indicates that the content was completely AI-generated or significantly edited with AI.",
description="Label content as AI-generated (video only)",
default=False,
advanced=True,
)
is_branded_content: bool = SchemaField(
description="Whether to enable the Branded Content toggle. If this field is set to true, the video will be labeled as Branded Content, indicating you are in a paid partnership with a brand. A “Paid partnership” label will be attached to the video.",
description="Label as branded content (paid partnership)",
default=False,
advanced=True,
)
is_brand_organic: bool = SchemaField(
description="Whether to enable the Brand Organic Content toggle. If this field is set to true, the video will be labeled as Brand Organic Content, indicating you are promoting yourself or your own business. A “Promotional content” label will be attached to the video.",
description="Label as brand organic content (promotional)",
default=False,
advanced=True,
)
@@ -87,9 +81,9 @@ class PostToTikTokBlock(Block):
default=0,
advanced=True,
)
visibility: TikTokVisibility = SchemaField(
visibility: str = SchemaField(
description="Post visibility: 'public', 'private', 'followers', or 'friends'",
default=TikTokVisibility.PUBLIC,
default="public",
advanced=True,
)
draft: bool = SchemaField(
@@ -104,6 +98,7 @@ class PostToTikTokBlock(Block):
def __init__(self):
super().__init__(
disabled=True,
id="7faf4b27-96b0-4f05-bf64-e0de54ae74e1",
description="Post to TikTok using Ayrshare",
categories={BlockCategory.SOCIAL},
@@ -113,10 +108,9 @@ class PostToTikTokBlock(Block):
)
async def run(
self, input_data: "PostToTikTokBlock.Input", *, user_id: str, **kwargs
self, input_data: "PostToTikTokBlock.Input", *, profile_key: SecretStr, **kwargs
) -> BlockOutput:
"""Post to TikTok with TikTok-specific validation and options."""
profile_key = await get_profile_key(user_id)
if not profile_key:
yield "error", "Please link a social account via Ayrshare"
return
@@ -166,6 +160,12 @@ class PostToTikTokBlock(Block):
yield "error", f"Image cover index {input_data.image_cover_index} is out of range (max: {len(input_data.media_urls) - 1})"
return
# Validate visibility option
valid_visibility = ["public", "private", "followers", "friends"]
if input_data.visibility not in valid_visibility:
yield "error", f"TikTok visibility must be one of: {', '.join(valid_visibility)}"
return
# Check for PNG files (not supported)
has_png = any(url.lower().endswith(".png") for url in input_data.media_urls)
if has_png:
@@ -218,8 +218,8 @@ class PostToTikTokBlock(Block):
if input_data.title:
tiktok_options["title"] = input_data.title
if input_data.visibility != TikTokVisibility.PUBLIC:
tiktok_options["visibility"] = input_data.visibility.value
if input_data.visibility != "public":
tiktok_options["visibility"] = input_data.visibility
response = await client.create_post(
post=input_data.post,

View File

@@ -6,9 +6,10 @@ from backend.sdk import (
BlockSchema,
BlockType,
SchemaField,
SecretStr,
)
from ._util import BaseAyrshareInput, create_ayrshare_client, get_profile_key
from ._util import BaseAyrshareInput, create_ayrshare_client
class PostToXBlock(Block):
@@ -115,11 +116,10 @@ class PostToXBlock(Block):
self,
input_data: "PostToXBlock.Input",
*,
user_id: str,
profile_key: SecretStr,
**kwargs,
) -> BlockOutput:
"""Post to X / Twitter with enhanced X-specific options."""
profile_key = await get_profile_key(user_id)
if not profile_key:
yield "error", "Please link a social account via Ayrshare"
return

View File

@@ -9,9 +9,10 @@ from backend.sdk import (
BlockSchema,
BlockType,
SchemaField,
SecretStr,
)
from ._util import BaseAyrshareInput, create_ayrshare_client, get_profile_key
from ._util import BaseAyrshareInput, create_ayrshare_client
class YouTubeVisibility(str, Enum):
@@ -137,12 +138,10 @@ class PostToYouTubeBlock(Block):
self,
input_data: "PostToYouTubeBlock.Input",
*,
user_id: str,
profile_key: SecretStr,
**kwargs,
) -> BlockOutput:
"""Post to YouTube with YouTube-specific validation and options."""
profile_key = await get_profile_key(user_id)
if not profile_key:
yield "error", "Please link a social account via Ayrshare"
return

View File

@@ -1,205 +0,0 @@
"""
Meeting BaaS API client module.
All API calls centralized for consistency and maintainability.
"""
from typing import Any, Dict, List, Optional
from backend.sdk import Requests
class MeetingBaasAPI:
"""Client for Meeting BaaS API endpoints."""
BASE_URL = "https://api.meetingbaas.com"
def __init__(self, api_key: str):
"""Initialize API client with authentication key."""
self.api_key = api_key
self.headers = {"x-meeting-baas-api-key": api_key}
self.requests = Requests()
# Bot Management Endpoints
async def join_meeting(
self,
bot_name: str,
meeting_url: str,
reserved: bool = False,
bot_image: Optional[str] = None,
entry_message: Optional[str] = None,
start_time: Optional[int] = None,
speech_to_text: Optional[Dict[str, Any]] = None,
webhook_url: Optional[str] = None,
automatic_leave: Optional[Dict[str, Any]] = None,
extra: Optional[Dict[str, Any]] = None,
recording_mode: str = "speaker_view",
streaming: Optional[Dict[str, Any]] = None,
deduplication_key: Optional[str] = None,
zoom_sdk_id: Optional[str] = None,
zoom_sdk_pwd: Optional[str] = None,
) -> Dict[str, Any]:
"""
Deploy a bot to join and record a meeting.
POST /bots
"""
body = {
"bot_name": bot_name,
"meeting_url": meeting_url,
"reserved": reserved,
"recording_mode": recording_mode,
}
# Add optional fields if provided
if bot_image is not None:
body["bot_image"] = bot_image
if entry_message is not None:
body["entry_message"] = entry_message
if start_time is not None:
body["start_time"] = start_time
if speech_to_text is not None:
body["speech_to_text"] = speech_to_text
if webhook_url is not None:
body["webhook_url"] = webhook_url
if automatic_leave is not None:
body["automatic_leave"] = automatic_leave
if extra is not None:
body["extra"] = extra
if streaming is not None:
body["streaming"] = streaming
if deduplication_key is not None:
body["deduplication_key"] = deduplication_key
if zoom_sdk_id is not None:
body["zoom_sdk_id"] = zoom_sdk_id
if zoom_sdk_pwd is not None:
body["zoom_sdk_pwd"] = zoom_sdk_pwd
response = await self.requests.post(
f"{self.BASE_URL}/bots",
headers=self.headers,
json=body,
)
return response.json()
async def leave_meeting(self, bot_id: str) -> bool:
"""
Remove a bot from an ongoing meeting.
DELETE /bots/{uuid}
"""
response = await self.requests.delete(
f"{self.BASE_URL}/bots/{bot_id}",
headers=self.headers,
)
return response.status in [200, 204]
async def retranscribe(
self,
bot_uuid: str,
speech_to_text: Optional[Dict[str, Any]] = None,
webhook_url: Optional[str] = None,
) -> Dict[str, Any]:
"""
Re-run transcription on a bot's audio.
POST /bots/retranscribe
"""
body: Dict[str, Any] = {"bot_uuid": bot_uuid}
if speech_to_text is not None:
body["speech_to_text"] = speech_to_text
if webhook_url is not None:
body["webhook_url"] = webhook_url
response = await self.requests.post(
f"{self.BASE_URL}/bots/retranscribe",
headers=self.headers,
json=body,
)
if response.status == 202:
return {"accepted": True}
return response.json()
# Data Retrieval Endpoints
async def get_meeting_data(
self, bot_id: str, include_transcripts: bool = True
) -> Dict[str, Any]:
"""
Retrieve meeting data including recording and transcripts.
GET /bots/meeting_data
"""
params = {
"bot_id": bot_id,
"include_transcripts": str(include_transcripts).lower(),
}
response = await self.requests.get(
f"{self.BASE_URL}/bots/meeting_data",
headers=self.headers,
params=params,
)
return response.json()
async def get_screenshots(self, bot_id: str) -> List[Dict[str, Any]]:
"""
Retrieve screenshots captured during a meeting.
GET /bots/{uuid}/screenshots
"""
response = await self.requests.get(
f"{self.BASE_URL}/bots/{bot_id}/screenshots",
headers=self.headers,
)
result = response.json()
# Ensure we return a list
if isinstance(result, list):
return result
return []
async def delete_data(self, bot_id: str) -> bool:
"""
Delete a bot's recorded data.
POST /bots/{uuid}/delete_data
"""
response = await self.requests.post(
f"{self.BASE_URL}/bots/{bot_id}/delete_data",
headers=self.headers,
)
return response.status == 200
async def list_bots_with_metadata(
self,
limit: Optional[int] = None,
offset: Optional[int] = None,
sort_by: Optional[str] = None,
sort_order: Optional[str] = None,
filter_by: Optional[Dict[str, Any]] = None,
) -> Dict[str, Any]:
"""
List bots with metadata including IDs, names, and meeting details.
GET /bots/bots_with_metadata
"""
params = {}
if limit is not None:
params["limit"] = limit
if offset is not None:
params["offset"] = offset
if sort_by is not None:
params["sort_by"] = sort_by
if sort_order is not None:
params["sort_order"] = sort_order
if filter_by is not None:
params.update(filter_by)
response = await self.requests.get(
f"{self.BASE_URL}/bots/bots_with_metadata",
headers=self.headers,
params=params,
)
return response.json()

View File

@@ -1,13 +0,0 @@
"""
Shared configuration for all Meeting BaaS blocks using the SDK pattern.
"""
from backend.sdk import BlockCostType, ProviderBuilder
# Configure the Meeting BaaS provider with API key authentication
baas = (
ProviderBuilder("baas")
.with_api_key("MEETING_BAAS_API_KEY", "Meeting BaaS API Key")
.with_base_cost(5, BlockCostType.RUN) # Higher cost for meeting recording service
.build()
)

View File

@@ -1,217 +0,0 @@
"""
Meeting BaaS bot (recording) blocks.
"""
from typing import Optional
from backend.sdk import (
APIKeyCredentials,
Block,
BlockCategory,
BlockOutput,
BlockSchema,
CredentialsMetaInput,
SchemaField,
)
from ._api import MeetingBaasAPI
from ._config import baas
class BaasBotJoinMeetingBlock(Block):
"""
Deploy a bot immediately or at a scheduled start_time to join and record a meeting.
"""
class Input(BlockSchema):
credentials: CredentialsMetaInput = baas.credentials_field(
description="Meeting BaaS API credentials"
)
meeting_url: str = SchemaField(
description="The URL of the meeting the bot should join"
)
bot_name: str = SchemaField(
description="Display name for the bot in the meeting"
)
bot_image: str = SchemaField(
description="URL to an image for the bot's avatar (16:9 ratio recommended)",
default="",
)
entry_message: str = SchemaField(
description="Chat message the bot will post upon entry", default=""
)
reserved: bool = SchemaField(
description="Use a reserved bot slot (joins 4 min before meeting)",
default=False,
)
start_time: Optional[int] = SchemaField(
description="Unix timestamp (ms) when bot should join", default=None
)
webhook_url: str | None = SchemaField(
description="URL to receive webhook events for this bot", default=None
)
timeouts: dict = SchemaField(
description="Automatic leave timeouts configuration", default={}
)
extra: dict = SchemaField(
description="Custom metadata to attach to the bot", default={}
)
class Output(BlockSchema):
bot_id: str = SchemaField(description="UUID of the deployed bot")
join_response: dict = SchemaField(
description="Full response from join operation"
)
def __init__(self):
super().__init__(
id="377d1a6a-a99b-46cf-9af3-1d1b12758e04",
description="Deploy a bot to join and record a meeting",
categories={BlockCategory.COMMUNICATION},
input_schema=self.Input,
output_schema=self.Output,
)
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
api_key = credentials.api_key.get_secret_value()
api = MeetingBaasAPI(api_key)
# Call API with all parameters
data = await api.join_meeting(
bot_name=input_data.bot_name,
meeting_url=input_data.meeting_url,
reserved=input_data.reserved,
bot_image=input_data.bot_image if input_data.bot_image else None,
entry_message=(
input_data.entry_message if input_data.entry_message else None
),
start_time=input_data.start_time,
speech_to_text={"provider": "Default"},
webhook_url=input_data.webhook_url if input_data.webhook_url else None,
automatic_leave=input_data.timeouts if input_data.timeouts else None,
extra=input_data.extra if input_data.extra else None,
)
yield "bot_id", data.get("bot_id", "")
yield "join_response", data
class BaasBotLeaveMeetingBlock(Block):
"""
Force the bot to exit the call.
"""
class Input(BlockSchema):
credentials: CredentialsMetaInput = baas.credentials_field(
description="Meeting BaaS API credentials"
)
bot_id: str = SchemaField(description="UUID of the bot to remove from meeting")
class Output(BlockSchema):
left: bool = SchemaField(description="Whether the bot successfully left")
def __init__(self):
super().__init__(
id="bf77d128-8b25-4280-b5c7-2d553ba7e482",
description="Remove a bot from an ongoing meeting",
categories={BlockCategory.COMMUNICATION},
input_schema=self.Input,
output_schema=self.Output,
)
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
api_key = credentials.api_key.get_secret_value()
api = MeetingBaasAPI(api_key)
# Leave meeting
left = await api.leave_meeting(input_data.bot_id)
yield "left", left
class BaasBotFetchMeetingDataBlock(Block):
"""
Pull MP4 URL, transcript & metadata for a completed meeting.
"""
class Input(BlockSchema):
credentials: CredentialsMetaInput = baas.credentials_field(
description="Meeting BaaS API credentials"
)
bot_id: str = SchemaField(description="UUID of the bot whose data to fetch")
include_transcripts: bool = SchemaField(
description="Include transcript data in response", default=True
)
class Output(BlockSchema):
mp4_url: str = SchemaField(
description="URL to download the meeting recording (time-limited)"
)
transcript: list = SchemaField(description="Meeting transcript data")
metadata: dict = SchemaField(description="Meeting metadata and bot information")
def __init__(self):
super().__init__(
id="ea7c1309-303c-4da1-893f-89c0e9d64e78",
description="Retrieve recorded meeting data",
categories={BlockCategory.DATA},
input_schema=self.Input,
output_schema=self.Output,
)
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
api_key = credentials.api_key.get_secret_value()
api = MeetingBaasAPI(api_key)
# Fetch meeting data
data = await api.get_meeting_data(
bot_id=input_data.bot_id,
include_transcripts=input_data.include_transcripts,
)
yield "mp4_url", data.get("mp4", "")
yield "transcript", data.get("bot_data", {}).get("transcripts", [])
yield "metadata", data.get("bot_data", {}).get("bot", {})
class BaasBotDeleteRecordingBlock(Block):
"""
Purge MP4 + transcript data for privacy or storage management.
"""
class Input(BlockSchema):
credentials: CredentialsMetaInput = baas.credentials_field(
description="Meeting BaaS API credentials"
)
bot_id: str = SchemaField(description="UUID of the bot whose data to delete")
class Output(BlockSchema):
deleted: bool = SchemaField(
description="Whether the data was successfully deleted"
)
def __init__(self):
super().__init__(
id="bf8d1aa6-42d8-4944-b6bd-6bac554c0d3b",
description="Permanently delete a meeting's recorded data",
categories={BlockCategory.DATA},
input_schema=self.Input,
output_schema=self.Output,
)
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
api_key = credentials.api_key.get_secret_value()
api = MeetingBaasAPI(api_key)
# Delete recording data
deleted = await api.delete_data(input_data.bot_id)
yield "deleted", deleted

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@@ -1,3 +0,0 @@
from .text_overlay import BannerbearTextOverlayBlock
__all__ = ["BannerbearTextOverlayBlock"]

View File

@@ -1,8 +0,0 @@
from backend.sdk import BlockCostType, ProviderBuilder
bannerbear = (
ProviderBuilder("bannerbear")
.with_api_key("BANNERBEAR_API_KEY", "Bannerbear API Key")
.with_base_cost(1, BlockCostType.RUN)
.build()
)

View File

@@ -1,239 +0,0 @@
import uuid
from typing import TYPE_CHECKING, Any, Dict, List
if TYPE_CHECKING:
pass
from pydantic import SecretStr
from backend.sdk import (
APIKeyCredentials,
Block,
BlockCategory,
BlockOutput,
BlockSchema,
CredentialsMetaInput,
Requests,
SchemaField,
)
from ._config import bannerbear
TEST_CREDENTIALS = APIKeyCredentials(
id="01234567-89ab-cdef-0123-456789abcdef",
provider="bannerbear",
api_key=SecretStr("mock-bannerbear-api-key"),
title="Mock Bannerbear API Key",
)
class TextModification(BlockSchema):
name: str = SchemaField(
description="The name of the layer to modify in the template"
)
text: str = SchemaField(description="The text content to add to this layer")
color: str = SchemaField(
description="Hex color code for the text (e.g., '#FF0000')",
default="",
advanced=True,
)
font_family: str = SchemaField(
description="Font family to use for the text",
default="",
advanced=True,
)
font_size: int = SchemaField(
description="Font size in pixels",
default=0,
advanced=True,
)
font_weight: str = SchemaField(
description="Font weight (e.g., 'bold', 'normal')",
default="",
advanced=True,
)
text_align: str = SchemaField(
description="Text alignment (left, center, right)",
default="",
advanced=True,
)
class BannerbearTextOverlayBlock(Block):
class Input(BlockSchema):
credentials: CredentialsMetaInput = bannerbear.credentials_field(
description="API credentials for Bannerbear"
)
template_id: str = SchemaField(
description="The unique ID of your Bannerbear template"
)
project_id: str = SchemaField(
description="Optional: Project ID (required when using Master API Key)",
default="",
advanced=True,
)
text_modifications: List[TextModification] = SchemaField(
description="List of text layers to modify in the template"
)
image_url: str = SchemaField(
description="Optional: URL of an image to use in the template",
default="",
advanced=True,
)
image_layer_name: str = SchemaField(
description="Optional: Name of the image layer in the template",
default="photo",
advanced=True,
)
webhook_url: str = SchemaField(
description="Optional: URL to receive webhook notification when image is ready",
default="",
advanced=True,
)
metadata: str = SchemaField(
description="Optional: Custom metadata to attach to the image",
default="",
advanced=True,
)
class Output(BlockSchema):
success: bool = SchemaField(
description="Whether the image generation was successfully initiated"
)
image_url: str = SchemaField(
description="URL of the generated image (if synchronous) or placeholder"
)
uid: str = SchemaField(description="Unique identifier for the generated image")
status: str = SchemaField(description="Status of the image generation")
error: str = SchemaField(description="Error message if the operation failed")
def __init__(self):
super().__init__(
id="c7d3a5c2-05fc-450e-8dce-3b0e04626009",
description="Add text overlay to images using Bannerbear templates. Perfect for creating social media graphics, marketing materials, and dynamic image content.",
categories={BlockCategory.PRODUCTIVITY, BlockCategory.AI},
input_schema=self.Input,
output_schema=self.Output,
test_input={
"template_id": "jJWBKNELpQPvbX5R93Gk",
"text_modifications": [
{
"name": "headline",
"text": "Amazing Product Launch!",
"color": "#FF0000",
},
{
"name": "subtitle",
"text": "50% OFF Today Only",
},
],
"credentials": {
"provider": "bannerbear",
"id": str(uuid.uuid4()),
"type": "api_key",
},
},
test_output=[
("success", True),
("image_url", "https://cdn.bannerbear.com/test-image.jpg"),
("uid", "test-uid-123"),
("status", "completed"),
],
test_mock={
"_make_api_request": lambda *args, **kwargs: {
"uid": "test-uid-123",
"status": "completed",
"image_url": "https://cdn.bannerbear.com/test-image.jpg",
}
},
test_credentials=TEST_CREDENTIALS,
)
async def _make_api_request(self, payload: dict, api_key: str) -> dict:
"""Make the actual API request to Bannerbear. This is separated for easy mocking in tests."""
headers = {
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json",
}
response = await Requests().post(
"https://sync.api.bannerbear.com/v2/images",
headers=headers,
json=payload,
)
if response.status in [200, 201, 202]:
return response.json()
else:
error_msg = f"API request failed with status {response.status}"
if response.text:
try:
error_data = response.json()
error_msg = (
f"{error_msg}: {error_data.get('message', response.text)}"
)
except Exception:
error_msg = f"{error_msg}: {response.text}"
raise Exception(error_msg)
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
# Build the modifications array
modifications = []
# Add text modifications
for text_mod in input_data.text_modifications:
mod_data: Dict[str, Any] = {
"name": text_mod.name,
"text": text_mod.text,
}
# Add optional text styling parameters only if they have values
if text_mod.color and text_mod.color.strip():
mod_data["color"] = text_mod.color
if text_mod.font_family and text_mod.font_family.strip():
mod_data["font_family"] = text_mod.font_family
if text_mod.font_size and text_mod.font_size > 0:
mod_data["font_size"] = text_mod.font_size
if text_mod.font_weight and text_mod.font_weight.strip():
mod_data["font_weight"] = text_mod.font_weight
if text_mod.text_align and text_mod.text_align.strip():
mod_data["text_align"] = text_mod.text_align
modifications.append(mod_data)
# Add image modification if provided and not empty
if input_data.image_url and input_data.image_url.strip():
modifications.append(
{
"name": input_data.image_layer_name,
"image_url": input_data.image_url,
}
)
# Build the request payload - only include non-empty optional fields
payload = {
"template": input_data.template_id,
"modifications": modifications,
}
# Add project_id if provided (required for Master API keys)
if input_data.project_id and input_data.project_id.strip():
payload["project_id"] = input_data.project_id
if input_data.webhook_url and input_data.webhook_url.strip():
payload["webhook_url"] = input_data.webhook_url
if input_data.metadata and input_data.metadata.strip():
payload["metadata"] = input_data.metadata
# Make the API request using the private method
data = await self._make_api_request(
payload, credentials.api_key.get_secret_value()
)
# Synchronous request - image should be ready
yield "success", True
yield "image_url", data.get("image_url", "")
yield "uid", data.get("uid", "")
yield "status", data.get("status", "completed")

View File

@@ -1,178 +0,0 @@
"""
DataForSEO API client with async support using the SDK patterns.
"""
import base64
from typing import Any, Dict, List, Optional
from backend.sdk import Requests, UserPasswordCredentials
class DataForSeoClient:
"""Client for the DataForSEO API using async requests."""
API_URL = "https://api.dataforseo.com"
def __init__(self, credentials: UserPasswordCredentials):
self.credentials = credentials
self.requests = Requests(
trusted_origins=["https://api.dataforseo.com"],
raise_for_status=False,
)
def _get_headers(self) -> Dict[str, str]:
"""Generate the authorization header using Basic Auth."""
username = self.credentials.username.get_secret_value()
password = self.credentials.password.get_secret_value()
credentials_str = f"{username}:{password}"
encoded = base64.b64encode(credentials_str.encode("ascii")).decode("ascii")
return {
"Authorization": f"Basic {encoded}",
"Content-Type": "application/json",
}
async def keyword_suggestions(
self,
keyword: str,
location_code: Optional[int] = None,
language_code: Optional[str] = None,
include_seed_keyword: bool = True,
include_serp_info: bool = False,
include_clickstream_data: bool = False,
limit: int = 100,
) -> List[Dict[str, Any]]:
"""
Get keyword suggestions from DataForSEO Labs.
Args:
keyword: Seed keyword
location_code: Location code for targeting
language_code: Language code (e.g., "en")
include_seed_keyword: Include seed keyword in results
include_serp_info: Include SERP data
include_clickstream_data: Include clickstream metrics
limit: Maximum number of results (up to 3000)
Returns:
API response with keyword suggestions
"""
endpoint = f"{self.API_URL}/v3/dataforseo_labs/google/keyword_suggestions/live"
# Build payload only with non-None values to avoid sending null fields
task_data: dict[str, Any] = {
"keyword": keyword,
}
if location_code is not None:
task_data["location_code"] = location_code
if language_code is not None:
task_data["language_code"] = language_code
if include_seed_keyword is not None:
task_data["include_seed_keyword"] = include_seed_keyword
if include_serp_info is not None:
task_data["include_serp_info"] = include_serp_info
if include_clickstream_data is not None:
task_data["include_clickstream_data"] = include_clickstream_data
if limit is not None:
task_data["limit"] = limit
payload = [task_data]
response = await self.requests.post(
endpoint,
headers=self._get_headers(),
json=payload,
)
data = response.json()
# Check for API errors
if response.status != 200:
error_message = data.get("status_message", "Unknown error")
raise Exception(
f"DataForSEO API error ({response.status}): {error_message}"
)
# Extract the results from the response
if data.get("tasks") and len(data["tasks"]) > 0:
task = data["tasks"][0]
if task.get("status_code") == 20000: # Success code
return task.get("result", [])
else:
error_msg = task.get("status_message", "Task failed")
raise Exception(f"DataForSEO task error: {error_msg}")
return []
async def related_keywords(
self,
keyword: str,
location_code: Optional[int] = None,
language_code: Optional[str] = None,
include_seed_keyword: bool = True,
include_serp_info: bool = False,
include_clickstream_data: bool = False,
limit: int = 100,
) -> List[Dict[str, Any]]:
"""
Get related keywords from DataForSEO Labs.
Args:
keyword: Seed keyword
location_code: Location code for targeting
language_code: Language code (e.g., "en")
include_seed_keyword: Include seed keyword in results
include_serp_info: Include SERP data
include_clickstream_data: Include clickstream metrics
limit: Maximum number of results (up to 3000)
Returns:
API response with related keywords
"""
endpoint = f"{self.API_URL}/v3/dataforseo_labs/google/related_keywords/live"
# Build payload only with non-None values to avoid sending null fields
task_data: dict[str, Any] = {
"keyword": keyword,
}
if location_code is not None:
task_data["location_code"] = location_code
if language_code is not None:
task_data["language_code"] = language_code
if include_seed_keyword is not None:
task_data["include_seed_keyword"] = include_seed_keyword
if include_serp_info is not None:
task_data["include_serp_info"] = include_serp_info
if include_clickstream_data is not None:
task_data["include_clickstream_data"] = include_clickstream_data
if limit is not None:
task_data["limit"] = limit
payload = [task_data]
response = await self.requests.post(
endpoint,
headers=self._get_headers(),
json=payload,
)
data = response.json()
# Check for API errors
if response.status != 200:
error_message = data.get("status_message", "Unknown error")
raise Exception(
f"DataForSEO API error ({response.status}): {error_message}"
)
# Extract the results from the response
if data.get("tasks") and len(data["tasks"]) > 0:
task = data["tasks"][0]
if task.get("status_code") == 20000: # Success code
return task.get("result", [])
else:
error_msg = task.get("status_message", "Task failed")
raise Exception(f"DataForSEO task error: {error_msg}")
return []

View File

@@ -1,17 +0,0 @@
"""
Configuration for all DataForSEO blocks using the new SDK pattern.
"""
from backend.sdk import BlockCostType, ProviderBuilder
# Build the DataForSEO provider with username/password authentication
dataforseo = (
ProviderBuilder("dataforseo")
.with_user_password(
username_env_var="DATAFORSEO_USERNAME",
password_env_var="DATAFORSEO_PASSWORD",
title="DataForSEO Credentials",
)
.with_base_cost(1, BlockCostType.RUN)
.build()
)

View File

@@ -1,273 +0,0 @@
"""
DataForSEO Google Keyword Suggestions block.
"""
from typing import Any, Dict, List, Optional
from backend.sdk import (
Block,
BlockCategory,
BlockOutput,
BlockSchema,
CredentialsMetaInput,
SchemaField,
UserPasswordCredentials,
)
from ._api import DataForSeoClient
from ._config import dataforseo
class KeywordSuggestion(BlockSchema):
"""Schema for a keyword suggestion result."""
keyword: str = SchemaField(description="The keyword suggestion")
search_volume: Optional[int] = SchemaField(
description="Monthly search volume", default=None
)
competition: Optional[float] = SchemaField(
description="Competition level (0-1)", default=None
)
cpc: Optional[float] = SchemaField(
description="Cost per click in USD", default=None
)
keyword_difficulty: Optional[int] = SchemaField(
description="Keyword difficulty score", default=None
)
serp_info: Optional[Dict[str, Any]] = SchemaField(
description="data from SERP for each keyword", default=None
)
clickstream_data: Optional[Dict[str, Any]] = SchemaField(
description="Clickstream data metrics", default=None
)
class DataForSeoKeywordSuggestionsBlock(Block):
"""Block for getting keyword suggestions from DataForSEO Labs."""
class Input(BlockSchema):
credentials: CredentialsMetaInput = dataforseo.credentials_field(
description="DataForSEO credentials (username and password)"
)
keyword: str = SchemaField(description="Seed keyword to get suggestions for")
location_code: Optional[int] = SchemaField(
description="Location code for targeting (e.g., 2840 for USA)",
default=2840, # USA
)
language_code: Optional[str] = SchemaField(
description="Language code (e.g., 'en' for English)",
default="en",
)
include_seed_keyword: bool = SchemaField(
description="Include the seed keyword in results",
default=True,
)
include_serp_info: bool = SchemaField(
description="Include SERP information",
default=False,
)
include_clickstream_data: bool = SchemaField(
description="Include clickstream metrics",
default=False,
)
limit: int = SchemaField(
description="Maximum number of results (up to 3000)",
default=100,
ge=1,
le=3000,
)
class Output(BlockSchema):
suggestions: List[KeywordSuggestion] = SchemaField(
description="List of keyword suggestions with metrics"
)
suggestion: KeywordSuggestion = SchemaField(
description="A single keyword suggestion with metrics"
)
total_count: int = SchemaField(
description="Total number of suggestions returned"
)
seed_keyword: str = SchemaField(
description="The seed keyword used for the query"
)
def __init__(self):
super().__init__(
id="73c3e7c4-2b3f-4e9f-9e3e-8f7a5c3e2d45",
description="Get keyword suggestions from DataForSEO Labs Google API",
categories={BlockCategory.SEARCH, BlockCategory.DATA},
input_schema=self.Input,
output_schema=self.Output,
test_input={
"credentials": dataforseo.get_test_credentials().model_dump(),
"keyword": "digital marketing",
"location_code": 2840,
"language_code": "en",
"limit": 1,
},
test_credentials=dataforseo.get_test_credentials(),
test_output=[
(
"suggestion",
lambda x: hasattr(x, "keyword")
and x.keyword == "digital marketing strategy",
),
("suggestions", lambda x: isinstance(x, list) and len(x) == 1),
("total_count", 1),
("seed_keyword", "digital marketing"),
],
test_mock={
"_fetch_keyword_suggestions": lambda *args, **kwargs: [
{
"items": [
{
"keyword": "digital marketing strategy",
"keyword_info": {
"search_volume": 10000,
"competition": 0.5,
"cpc": 2.5,
},
"keyword_properties": {
"keyword_difficulty": 50,
},
}
]
}
]
},
)
async def _fetch_keyword_suggestions(
self,
client: DataForSeoClient,
input_data: Input,
) -> Any:
"""Private method to fetch keyword suggestions - can be mocked for testing."""
return await client.keyword_suggestions(
keyword=input_data.keyword,
location_code=input_data.location_code,
language_code=input_data.language_code,
include_seed_keyword=input_data.include_seed_keyword,
include_serp_info=input_data.include_serp_info,
include_clickstream_data=input_data.include_clickstream_data,
limit=input_data.limit,
)
async def run(
self,
input_data: Input,
*,
credentials: UserPasswordCredentials,
**kwargs,
) -> BlockOutput:
"""Execute the keyword suggestions query."""
client = DataForSeoClient(credentials)
results = await self._fetch_keyword_suggestions(client, input_data)
# Process and format the results
suggestions = []
if results and len(results) > 0:
# results is a list, get the first element
first_result = results[0] if isinstance(results, list) else results
items = (
first_result.get("items", []) if isinstance(first_result, dict) else []
)
for item in items:
# Create the KeywordSuggestion object
suggestion = KeywordSuggestion(
keyword=item.get("keyword", ""),
search_volume=item.get("keyword_info", {}).get("search_volume"),
competition=item.get("keyword_info", {}).get("competition"),
cpc=item.get("keyword_info", {}).get("cpc"),
keyword_difficulty=item.get("keyword_properties", {}).get(
"keyword_difficulty"
),
serp_info=(
item.get("serp_info") if input_data.include_serp_info else None
),
clickstream_data=(
item.get("clickstream_keyword_info")
if input_data.include_clickstream_data
else None
),
)
yield "suggestion", suggestion
suggestions.append(suggestion)
yield "suggestions", suggestions
yield "total_count", len(suggestions)
yield "seed_keyword", input_data.keyword
class KeywordSuggestionExtractorBlock(Block):
"""Extracts individual fields from a KeywordSuggestion object."""
class Input(BlockSchema):
suggestion: KeywordSuggestion = SchemaField(
description="The keyword suggestion object to extract fields from"
)
class Output(BlockSchema):
keyword: str = SchemaField(description="The keyword suggestion")
search_volume: Optional[int] = SchemaField(
description="Monthly search volume", default=None
)
competition: Optional[float] = SchemaField(
description="Competition level (0-1)", default=None
)
cpc: Optional[float] = SchemaField(
description="Cost per click in USD", default=None
)
keyword_difficulty: Optional[int] = SchemaField(
description="Keyword difficulty score", default=None
)
serp_info: Optional[Dict[str, Any]] = SchemaField(
description="data from SERP for each keyword", default=None
)
clickstream_data: Optional[Dict[str, Any]] = SchemaField(
description="Clickstream data metrics", default=None
)
def __init__(self):
super().__init__(
id="4193cb94-677c-48b0-9eec-6ac72fffd0f2",
description="Extract individual fields from a KeywordSuggestion object",
categories={BlockCategory.DATA},
input_schema=self.Input,
output_schema=self.Output,
test_input={
"suggestion": KeywordSuggestion(
keyword="test keyword",
search_volume=1000,
competition=0.5,
cpc=2.5,
keyword_difficulty=60,
).model_dump()
},
test_output=[
("keyword", "test keyword"),
("search_volume", 1000),
("competition", 0.5),
("cpc", 2.5),
("keyword_difficulty", 60),
("serp_info", None),
("clickstream_data", None),
],
)
async def run(
self,
input_data: Input,
**kwargs,
) -> BlockOutput:
"""Extract fields from the KeywordSuggestion object."""
suggestion = input_data.suggestion
yield "keyword", suggestion.keyword
yield "search_volume", suggestion.search_volume
yield "competition", suggestion.competition
yield "cpc", suggestion.cpc
yield "keyword_difficulty", suggestion.keyword_difficulty
yield "serp_info", suggestion.serp_info
yield "clickstream_data", suggestion.clickstream_data

View File

@@ -1,283 +0,0 @@
"""
DataForSEO Google Related Keywords block.
"""
from typing import Any, Dict, List, Optional
from backend.sdk import (
Block,
BlockCategory,
BlockOutput,
BlockSchema,
CredentialsMetaInput,
SchemaField,
UserPasswordCredentials,
)
from ._api import DataForSeoClient
from ._config import dataforseo
class RelatedKeyword(BlockSchema):
"""Schema for a related keyword result."""
keyword: str = SchemaField(description="The related keyword")
search_volume: Optional[int] = SchemaField(
description="Monthly search volume", default=None
)
competition: Optional[float] = SchemaField(
description="Competition level (0-1)", default=None
)
cpc: Optional[float] = SchemaField(
description="Cost per click in USD", default=None
)
keyword_difficulty: Optional[int] = SchemaField(
description="Keyword difficulty score", default=None
)
serp_info: Optional[Dict[str, Any]] = SchemaField(
description="SERP data for the keyword", default=None
)
clickstream_data: Optional[Dict[str, Any]] = SchemaField(
description="Clickstream data metrics", default=None
)
class DataForSeoRelatedKeywordsBlock(Block):
"""Block for getting related keywords from DataForSEO Labs."""
class Input(BlockSchema):
credentials: CredentialsMetaInput = dataforseo.credentials_field(
description="DataForSEO credentials (username and password)"
)
keyword: str = SchemaField(
description="Seed keyword to find related keywords for"
)
location_code: Optional[int] = SchemaField(
description="Location code for targeting (e.g., 2840 for USA)",
default=2840, # USA
)
language_code: Optional[str] = SchemaField(
description="Language code (e.g., 'en' for English)",
default="en",
)
include_seed_keyword: bool = SchemaField(
description="Include the seed keyword in results",
default=True,
)
include_serp_info: bool = SchemaField(
description="Include SERP information",
default=False,
)
include_clickstream_data: bool = SchemaField(
description="Include clickstream metrics",
default=False,
)
limit: int = SchemaField(
description="Maximum number of results (up to 3000)",
default=100,
ge=1,
le=3000,
)
class Output(BlockSchema):
related_keywords: List[RelatedKeyword] = SchemaField(
description="List of related keywords with metrics"
)
related_keyword: RelatedKeyword = SchemaField(
description="A related keyword with metrics"
)
total_count: int = SchemaField(
description="Total number of related keywords returned"
)
seed_keyword: str = SchemaField(
description="The seed keyword used for the query"
)
def __init__(self):
super().__init__(
id="8f2e4d6a-1b3c-4a5e-9d7f-2c8e6a4b3f1d",
description="Get related keywords from DataForSEO Labs Google API",
categories={BlockCategory.SEARCH, BlockCategory.DATA},
input_schema=self.Input,
output_schema=self.Output,
test_input={
"credentials": dataforseo.get_test_credentials().model_dump(),
"keyword": "content marketing",
"location_code": 2840,
"language_code": "en",
"limit": 1,
},
test_credentials=dataforseo.get_test_credentials(),
test_output=[
(
"related_keyword",
lambda x: hasattr(x, "keyword") and x.keyword == "content strategy",
),
("related_keywords", lambda x: isinstance(x, list) and len(x) == 1),
("total_count", 1),
("seed_keyword", "content marketing"),
],
test_mock={
"_fetch_related_keywords": lambda *args, **kwargs: [
{
"items": [
{
"keyword_data": {
"keyword": "content strategy",
"keyword_info": {
"search_volume": 8000,
"competition": 0.4,
"cpc": 3.0,
},
"keyword_properties": {
"keyword_difficulty": 45,
},
}
}
]
}
]
},
)
async def _fetch_related_keywords(
self,
client: DataForSeoClient,
input_data: Input,
) -> Any:
"""Private method to fetch related keywords - can be mocked for testing."""
return await client.related_keywords(
keyword=input_data.keyword,
location_code=input_data.location_code,
language_code=input_data.language_code,
include_seed_keyword=input_data.include_seed_keyword,
include_serp_info=input_data.include_serp_info,
include_clickstream_data=input_data.include_clickstream_data,
limit=input_data.limit,
)
async def run(
self,
input_data: Input,
*,
credentials: UserPasswordCredentials,
**kwargs,
) -> BlockOutput:
"""Execute the related keywords query."""
client = DataForSeoClient(credentials)
results = await self._fetch_related_keywords(client, input_data)
# Process and format the results
related_keywords = []
if results and len(results) > 0:
# results is a list, get the first element
first_result = results[0] if isinstance(results, list) else results
items = (
first_result.get("items", []) if isinstance(first_result, dict) else []
)
for item in items:
# Extract keyword_data from the item
keyword_data = item.get("keyword_data", {})
# Create the RelatedKeyword object
keyword = RelatedKeyword(
keyword=keyword_data.get("keyword", ""),
search_volume=keyword_data.get("keyword_info", {}).get(
"search_volume"
),
competition=keyword_data.get("keyword_info", {}).get("competition"),
cpc=keyword_data.get("keyword_info", {}).get("cpc"),
keyword_difficulty=keyword_data.get("keyword_properties", {}).get(
"keyword_difficulty"
),
serp_info=(
keyword_data.get("serp_info")
if input_data.include_serp_info
else None
),
clickstream_data=(
keyword_data.get("clickstream_keyword_info")
if input_data.include_clickstream_data
else None
),
)
yield "related_keyword", keyword
related_keywords.append(keyword)
yield "related_keywords", related_keywords
yield "total_count", len(related_keywords)
yield "seed_keyword", input_data.keyword
class RelatedKeywordExtractorBlock(Block):
"""Extracts individual fields from a RelatedKeyword object."""
class Input(BlockSchema):
related_keyword: RelatedKeyword = SchemaField(
description="The related keyword object to extract fields from"
)
class Output(BlockSchema):
keyword: str = SchemaField(description="The related keyword")
search_volume: Optional[int] = SchemaField(
description="Monthly search volume", default=None
)
competition: Optional[float] = SchemaField(
description="Competition level (0-1)", default=None
)
cpc: Optional[float] = SchemaField(
description="Cost per click in USD", default=None
)
keyword_difficulty: Optional[int] = SchemaField(
description="Keyword difficulty score", default=None
)
serp_info: Optional[Dict[str, Any]] = SchemaField(
description="SERP data for the keyword", default=None
)
clickstream_data: Optional[Dict[str, Any]] = SchemaField(
description="Clickstream data metrics", default=None
)
def __init__(self):
super().__init__(
id="98342061-09d2-4952-bf77-0761fc8cc9a8",
description="Extract individual fields from a RelatedKeyword object",
categories={BlockCategory.DATA},
input_schema=self.Input,
output_schema=self.Output,
test_input={
"related_keyword": RelatedKeyword(
keyword="test related keyword",
search_volume=800,
competition=0.4,
cpc=3.0,
keyword_difficulty=55,
).model_dump()
},
test_output=[
("keyword", "test related keyword"),
("search_volume", 800),
("competition", 0.4),
("cpc", 3.0),
("keyword_difficulty", 55),
("serp_info", None),
("clickstream_data", None),
],
)
async def run(
self,
input_data: Input,
**kwargs,
) -> BlockOutput:
"""Extract fields from the RelatedKeyword object."""
related_keyword = input_data.related_keyword
yield "keyword", related_keyword.keyword
yield "search_volume", related_keyword.search_volume
yield "competition", related_keyword.competition
yield "cpc", related_keyword.cpc
yield "keyword_difficulty", related_keyword.keyword_difficulty
yield "serp_info", related_keyword.serp_info
yield "clickstream_data", related_keyword.clickstream_data

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@@ -0,0 +1,237 @@
from typing import Literal
import aiohttp
import discord
from pydantic import SecretStr
from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
from backend.data.model import (
APIKeyCredentials,
CredentialsField,
CredentialsMetaInput,
SchemaField,
)
from backend.integrations.providers import ProviderName
DiscordCredentials = CredentialsMetaInput[
Literal[ProviderName.DISCORD], Literal["api_key"]
]
def DiscordCredentialsField() -> DiscordCredentials:
return CredentialsField(description="Discord bot token")
TEST_CREDENTIALS = APIKeyCredentials(
id="01234567-89ab-cdef-0123-456789abcdef",
provider="discord",
api_key=SecretStr("test_api_key"),
title="Mock Discord API key",
expires_at=None,
)
TEST_CREDENTIALS_INPUT = {
"provider": TEST_CREDENTIALS.provider,
"id": TEST_CREDENTIALS.id,
"type": TEST_CREDENTIALS.type,
"title": TEST_CREDENTIALS.type,
}
class ReadDiscordMessagesBlock(Block):
class Input(BlockSchema):
credentials: DiscordCredentials = DiscordCredentialsField()
class Output(BlockSchema):
message_content: str = SchemaField(
description="The content of the message received"
)
channel_name: str = SchemaField(
description="The name of the channel the message was received from"
)
username: str = SchemaField(
description="The username of the user who sent the message"
)
def __init__(self):
super().__init__(
id="df06086a-d5ac-4abb-9996-2ad0acb2eff7",
input_schema=ReadDiscordMessagesBlock.Input, # Assign input schema
output_schema=ReadDiscordMessagesBlock.Output, # Assign output schema
description="Reads messages from a Discord channel using a bot token.",
categories={BlockCategory.SOCIAL},
test_input={
"continuous_read": False,
"credentials": TEST_CREDENTIALS_INPUT,
},
test_credentials=TEST_CREDENTIALS,
test_output=[
(
"message_content",
"Hello!\n\nFile from user: example.txt\nContent: This is the content of the file.",
),
("channel_name", "general"),
("username", "test_user"),
],
test_mock={
"run_bot": lambda token: {
"output_data": "Hello!\n\nFile from user: example.txt\nContent: This is the content of the file.",
"channel_name": "general",
"username": "test_user",
}
},
)
async def run_bot(self, token: SecretStr):
intents = discord.Intents.default()
intents.message_content = True
client = discord.Client(intents=intents)
self.output_data = None
self.channel_name = None
self.username = None
@client.event
async def on_ready():
print(f"Logged in as {client.user}")
@client.event
async def on_message(message):
if message.author == client.user:
return
self.output_data = message.content
self.channel_name = message.channel.name
self.username = message.author.name
if message.attachments:
attachment = message.attachments[0] # Process the first attachment
if attachment.filename.endswith((".txt", ".py")):
async with aiohttp.ClientSession() as session:
async with session.get(attachment.url) as response:
file_content = response.text()
self.output_data += f"\n\nFile from user: {attachment.filename}\nContent: {file_content}"
await client.close()
await client.start(token.get_secret_value())
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
async for output_name, output_value in self.__run(input_data, credentials):
yield output_name, output_value
async def __run(
self, input_data: Input, credentials: APIKeyCredentials
) -> BlockOutput:
try:
result = await self.run_bot(credentials.api_key)
# For testing purposes, use the mocked result
if isinstance(result, dict):
self.output_data = result.get("output_data")
self.channel_name = result.get("channel_name")
self.username = result.get("username")
if (
self.output_data is None
or self.channel_name is None
or self.username is None
):
raise ValueError("No message, channel name, or username received.")
yield "message_content", self.output_data
yield "channel_name", self.channel_name
yield "username", self.username
except discord.errors.LoginFailure as login_err:
raise ValueError(f"Login error occurred: {login_err}")
except Exception as e:
raise ValueError(f"An error occurred: {e}")
class SendDiscordMessageBlock(Block):
class Input(BlockSchema):
credentials: DiscordCredentials = DiscordCredentialsField()
message_content: str = SchemaField(
description="The content of the message received"
)
channel_name: str = SchemaField(
description="The name of the channel the message was received from"
)
class Output(BlockSchema):
status: str = SchemaField(
description="The status of the operation (e.g., 'Message sent', 'Error')"
)
def __init__(self):
super().__init__(
id="d0822ab5-9f8a-44a3-8971-531dd0178b6b",
input_schema=SendDiscordMessageBlock.Input, # Assign input schema
output_schema=SendDiscordMessageBlock.Output, # Assign output schema
description="Sends a message to a Discord channel using a bot token.",
categories={BlockCategory.SOCIAL},
test_input={
"channel_name": "general",
"message_content": "Hello, Discord!",
"credentials": TEST_CREDENTIALS_INPUT,
},
test_output=[("status", "Message sent")],
test_mock={
"send_message": lambda token, channel_name, message_content: "Message sent"
},
test_credentials=TEST_CREDENTIALS,
)
async def send_message(self, token: str, channel_name: str, message_content: str):
intents = discord.Intents.default()
intents.guilds = True # Required for fetching guild/channel information
client = discord.Client(intents=intents)
@client.event
async def on_ready():
print(f"Logged in as {client.user}")
for guild in client.guilds:
for channel in guild.text_channels:
if channel.name == channel_name:
# Split message into chunks if it exceeds 2000 characters
for chunk in self.chunk_message(message_content):
await channel.send(chunk)
self.output_data = "Message sent"
await client.close()
return
self.output_data = "Channel not found"
await client.close()
await client.start(token)
def chunk_message(self, message: str, limit: int = 2000) -> list:
"""Splits a message into chunks not exceeding the Discord limit."""
return [message[i : i + limit] for i in range(0, len(message), limit)]
async def run(
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
try:
result = await self.send_message(
credentials.api_key.get_secret_value(),
input_data.channel_name,
input_data.message_content,
)
# For testing purposes, use the mocked result
if isinstance(result, str):
self.output_data = result
if self.output_data is None:
raise ValueError("No status message received.")
yield "status", self.output_data
except discord.errors.LoginFailure as login_err:
raise ValueError(f"Login error occurred: {login_err}")
except Exception as e:
raise ValueError(f"An error occurred: {e}")

View File

@@ -1,117 +0,0 @@
"""
Discord API helper functions for making authenticated requests.
"""
import logging
from typing import Optional
from pydantic import BaseModel
from backend.data.model import OAuth2Credentials
from backend.util.request import Requests
logger = logging.getLogger(__name__)
class DiscordAPIException(Exception):
"""Exception raised for Discord API errors."""
def __init__(self, message: str, status_code: int):
super().__init__(message)
self.status_code = status_code
class DiscordOAuthUser(BaseModel):
"""Model for Discord OAuth user response."""
user_id: str
username: str
avatar_url: str
banner: Optional[str] = None
accent_color: Optional[int] = None
def get_api(credentials: OAuth2Credentials) -> Requests:
"""
Create a Requests instance configured for Discord API calls with OAuth2 credentials.
Args:
credentials: The OAuth2 credentials containing the access token.
Returns:
A configured Requests instance for Discord API calls.
"""
return Requests(
trusted_origins=[],
extra_headers={
"Authorization": f"Bearer {credentials.access_token.get_secret_value()}",
"Content-Type": "application/json",
},
raise_for_status=False,
)
async def get_current_user(credentials: OAuth2Credentials) -> DiscordOAuthUser:
"""
Fetch the current user's information using Discord OAuth2 API.
Reference: https://discord.com/developers/docs/resources/user#get-current-user
Args:
credentials: The OAuth2 credentials.
Returns:
A model containing user data with avatar URL.
Raises:
DiscordAPIException: If the API request fails.
"""
api = get_api(credentials)
response = await api.get("https://discord.com/api/oauth2/@me")
if not response.ok:
error_text = response.text()
raise DiscordAPIException(
f"Failed to fetch user info: {response.status} - {error_text}",
response.status,
)
data = response.json()
logger.info(f"Discord OAuth2 API Response: {data}")
# The /api/oauth2/@me endpoint returns a user object nested in the response
user_info = data.get("user", {})
logger.info(f"User info extracted: {user_info}")
# Build avatar URL
user_id = user_info.get("id")
avatar_hash = user_info.get("avatar")
if avatar_hash:
# Custom avatar
avatar_ext = "gif" if avatar_hash.startswith("a_") else "png"
avatar_url = (
f"https://cdn.discordapp.com/avatars/{user_id}/{avatar_hash}.{avatar_ext}"
)
else:
# Default avatar based on discriminator or user ID
discriminator = user_info.get("discriminator", "0")
if discriminator == "0":
# New username system - use user ID for default avatar
default_avatar_index = (int(user_id) >> 22) % 6
else:
# Legacy discriminator system
default_avatar_index = int(discriminator) % 5
avatar_url = (
f"https://cdn.discordapp.com/embed/avatars/{default_avatar_index}.png"
)
result = DiscordOAuthUser(
user_id=user_id,
username=user_info.get("username", ""),
avatar_url=avatar_url,
banner=user_info.get("banner"),
accent_color=user_info.get("accent_color"),
)
logger.info(f"Returning user data: {result.model_dump()}")
return result

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