CodeRabbit flagged that _flush_orphan_tool_uses_to_session (called from _InterruptedAttempt.finalize) used state.adapter._flush_unresolved_tool_calls with a # noqa: SLF001 suppressor. The private call mutates resolved_tool_calls and flips has_unresolved_tool_calls to False, which caused the downstream error-cleanup block at lines 4185-4200 to skip its own flush — UI spinners on the client stayed open until page refresh because no cleanup events were yielded after the early flush swallowed the unresolved state. Changes: - Rename _flush_unresolved_tool_calls → flush_unresolved_tool_calls (public) in response_adapter.py; update 3 internal call sites + 2 service.py sites. Drops the # noqa: SLF001 suppressor (no longer a private-access violation). - _flush_orphan_tool_uses_to_session and _InterruptedAttempt.finalize now return the list[StreamBaseResponse] produced by the flush so the caller yields them to the client instead of re-flushing. - Replace the three scattered post-loop error blocks (partial restore + redundant flush + stream_err yield + handled_error yield) with one consolidated block that: (a) calls _classify_final_failure → _FinalFailure, (b) yields finalize()'s events + _end_text_if_open, (c) yields one StreamError (unless handled_error.already_yielded=True). Fixes the double-flush skip-cleanup bug and eliminates duplicated error-text/code strings between history marker and SSE yield. - _classify_final_failure now returns _FinalFailure(display_msg, code, retryable) instead of a (msg, retryable) tuple — single source of truth for in-history marker + SSE event so they can't drift. Tests: +5 _classify_final_failure contract tests, +2 return-value assertions on finalize/orphan-flush. All 1022 SDK tests pass (was 1012).
AutoGPT Platform
Welcome to the AutoGPT Platform - a powerful system for creating and running AI agents to solve business problems. This platform enables you to harness the power of artificial intelligence to automate tasks, analyze data, and generate insights for your organization.
Getting Started
Prerequisites
- Docker
- Docker Compose V2 (comes with Docker Desktop, or can be installed separately)
Running the System
To run the AutoGPT Platform, follow these steps:
-
Clone this repository to your local machine and navigate to the
autogpt_platformdirectory within the repository:git clone <https://github.com/Significant-Gravitas/AutoGPT.git | git@github.com:Significant-Gravitas/AutoGPT.git> cd AutoGPT/autogpt_platform -
Run the following command:
cp .env.default .envThis command will copy the
.env.defaultfile to.env. You can modify the.envfile to add your own environment variables. -
Run the following command:
docker compose up -dThis command will start all the necessary backend services defined in the
docker-compose.ymlfile in detached mode. -
After all the services are in ready state, open your browser and navigate to
http://localhost:3000to access the AutoGPT Platform frontend.
Running Just Core services
You can now run the following to enable just the core services.
# For help
make help
# Run just Supabase + Redis + RabbitMQ
make start-core
# Stop core services
make stop-core
# View logs from core services
make logs-core
# Run formatting and linting for backend and frontend
make format
# Run migrations for backend database
make migrate
# Run backend server
make run-backend
# Run frontend development server
make run-frontend
Docker Compose Commands
Here are some useful Docker Compose commands for managing your AutoGPT Platform:
docker compose up -d: Start the services in detached mode.docker compose stop: Stop the running services without removing them.docker compose rm: Remove stopped service containers.docker compose build: Build or rebuild services.docker compose down: Stop and remove containers, networks, and volumes.docker compose watch: Watch for changes in your services and automatically update them.
Sample Scenarios
Here are some common scenarios where you might use multiple Docker Compose commands:
-
Updating and restarting a specific service:
docker compose build api_srv docker compose up -d --no-deps api_srvThis rebuilds the
api_srvservice and restarts it without affecting other services. -
Viewing logs for troubleshooting:
docker compose logs -f api_srv ws_srvThis shows and follows the logs for both
api_srvandws_srvservices. -
Scaling a service for increased load:
docker compose up -d --scale executor=3This scales the
executorservice to 3 instances to handle increased load. -
Stopping the entire system for maintenance:
docker compose stop docker compose rm -f docker compose pull docker compose up -dThis stops all services, removes containers, pulls the latest images, and restarts the system.
-
Developing with live updates:
docker compose watchThis watches for changes in your code and automatically updates the relevant services.
-
Checking the status of services:
docker compose psThis shows the current status of all services defined in your docker-compose.yml file.
These scenarios demonstrate how to use Docker Compose commands in combination to manage your AutoGPT Platform effectively.
Persisting Data
To persist data for PostgreSQL and Redis, you can modify the docker-compose.yml file to add volumes. Here's how:
-
Open the
docker-compose.ymlfile in a text editor. -
Add volume configurations for PostgreSQL and Redis services:
services: postgres: # ... other configurations ... volumes: - postgres_data:/var/lib/postgresql/data redis: # ... other configurations ... volumes: - redis_data:/data volumes: postgres_data: redis_data: -
Save the file and run
docker compose up -dto apply the changes.
This configuration will create named volumes for PostgreSQL and Redis, ensuring that your data persists across container restarts.
API Client Generation
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 Orvalpnpm generate:api: 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:
-
Ensure the backend services are running:
docker compose up -d -
Generate the updated API client:
pnpm generate:api
This will fetch the latest OpenAPI specification and regenerate the TypeScript client code.