AutoGPT/autogpt_platform/CLAUDE.md

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

Essential Commands

Backend Development

# Install dependencies
cd backend && poetry install

# Run database migrations
poetry run prisma migrate dev

# Start all services (database, redis, rabbitmq)
docker compose up -d

# Run the backend server
poetry run serve

# Run tests
poetry run test

# Run specific test
poetry run pytest path/to/test_file.py::test_function_name

# Lint and format
poetry run format  # Black + isort
poetry run lint    # ruff

More details can be found in TESTING.md

Creating/Updating Snapshots

When you first write a test or when the expected output changes:

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

# Install dependencies
cd frontend && npm install

# Start development server
npm run dev

# Run E2E tests
npm run test

# Run Storybook for component development
npm run storybook

# Build production
npm run build

# Type checking
npm run type-check

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
• Execution Engine: Separate executor service processes agent workflows
• Authentication: JWT-based with Supabase integration

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
• UI Components: Radix UI primitives with Tailwind CSS styling
• 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
4. Store: Marketplace for sharing agent templates

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
• AgentNode: Individual nodes in a workflow
• StoreListing: Marketplace listings for sharing agents

Environment Configuration

• 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:

1. Create new file in /backend/backend/blocks/
2. Inherit from Block base class
3. Define input/output schemas
4. Implement run method
5. Register in block registry

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
4. Test with Playwright if user-facing