suna/backend

Suna Backend

Running the backend

Within the backend directory, run the following command to stop and start the backend:

docker compose down && docker compose up --build

Running Individual Services

You can run individual services from the docker-compose file. This is particularly useful during development:

Running only Redis and RabbitMQ

docker compose up redis rabbitmq

Running only the API and Worker

docker compose up api worker

Development Setup

For local development, you might only need to run Redis and RabbitMQ, while working on the API locally. This is useful when:

• You're making changes to the API code and want to test them directly
• You want to avoid rebuilding the API container on every change
• You're running the API service directly on your machine

To run just Redis and RabbitMQ for development:```bash docker compose up redis rabbitmq

Then you can run your API service locally with the following commands

# On one terminal
cd backend
uv run api.py

# On another terminal
cd backend
uv run dramatiq --processes 4 --threads 4 run_agent_background

Environment Configuration

When running services individually, make sure to:

1. Check your .env file and adjust any necessary environment variables
2. Ensure Redis connection settings match your local setup (default: localhost:6379)
3. Ensure RabbitMQ connection settings match your local setup (default: localhost:5672)
4. Update any service-specific environment variables if needed

Important: Redis Host Configuration

When running the API locally with Redis in Docker, you need to set the correct Redis host in your .env file:

• For Docker-to-Docker communication (when running both services in Docker): use REDIS_HOST=redis
• For local-to-Docker communication (when running API locally): use REDIS_HOST=localhost

Important: RabbitMQ Host Configuration

When running the API locally with Redis in Docker, you need to set the correct RabbitMQ host in your .env file:

• For Docker-to-Docker communication (when running both services in Docker): use RABBITMQ_HOST=rabbitmq
• For local-to-Docker communication (when running API locally): use RABBITMQ_HOST=localhost

Example .env configuration for local development:

REDIS_HOST=localhost (instead of 'redis')
REDIS_PORT=6379
REDIS_PASSWORD=

RABBITMQ_HOST=localhost (instead of 'rabbitmq')
RABBITMQ_PORT=5672

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Feature Flags

The backend includes a Redis-backed feature flag system that allows you to control feature availability without code deployments.

Setup

The feature flag system uses the existing Redis service and is automatically available when Redis is running.

CLI Management

Use the CLI tool to manage feature flags:

cd backend/flags
python setup.py <command> [arguments]

Available Commands

Enable a feature flag:

python setup.py enable test_flag "Test decsription"

Disable a feature flag:

python setup.py disable test_flag

List all feature flags:

python setup.py list

API Endpoints

Feature flags are accessible via REST API:

Get all feature flags:

GET /feature-flags

Get specific feature flag:

GET /feature-flags/{flag_name}

Example response:

{
  "test_flag": {
    "enabled": true,
    "description": "Test flag",
    "updated_at": "2024-01-15T10:30:00Z"
  }
}

Backend Integration

Use feature flags in your Python code:

from flags.flags import is_enabled

# Check if a feature is enabled
if await is_enabled('test_flag'):
    # Feature-specific logic
    pass

# With fallback value
enabled = await is_enabled('new_feature', default=False)

Current Feature Flags

The system currently supports these feature flags:

• custom_agents: Controls custom agent creation and management
• agent_marketplace: Controls agent marketplace functionality

Error Handling

The feature flag system includes robust error handling:

• If Redis is unavailable, flags default to False
• API endpoints return empty objects on Redis errors
• CLI operations show clear error messages

Caching

• Backend operations are direct Redis calls (no caching)
• Frontend includes 5-minute caching for performance
• Use clearCache() in frontend to force refresh

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Production Setup

For production deployments, use the following command to set resource limits

docker compose -f docker-compose.yml -f docker-compose.prod.yml up -d