Files
AutoGPT/autogpt_platform
Nicholas Tindle 6bb6a081a2 feat(backend): add support for v0 by Vercel models and credentials (#10641)
## Summary
This PR adds support for v0 by Vercel's Model API to the AutoGPT
platform, enabling users to leverage v0's framework-aware AI models
optimized for React and Next.js code generation.

v0 provides OpenAI-compatible endpoints with models specifically trained
for frontend development, making them ideal for generating UI components
and web applications.

### Changes 🏗️

#### Backend Changes
- **Added v0 Provider**: Added `V0 = "v0"` to `ProviderName` enum in
`/backend/backend/integrations/providers.py`
- **Added v0 Models**: Added three v0 models to `LlmModel` enum in
`/backend/backend/blocks/llm.py`:
- `V0_1_5_MD = "v0-1.5-md"` - Everyday tasks and UI generation (128K
context, 64K output)
- `V0_1_5_LG = "v0-1.5-lg"` - Advanced reasoning (512K context, 64K
output)
  - `V0_1_0_MD = "v0-1.0-md"` - Legacy model (128K context, 64K output)
- **Implemented v0 Provider**: Added v0 support in `llm_call()` function
using OpenAI-compatible client with base URL `https://api.v0.dev/v1`
- **Added Credentials Support**: Created `v0_credentials` in
`/backend/backend/integrations/credentials_store.py` with UUID
`c4e6d1a0-3b5f-4789-a8e2-9b123456789f`
- **Cost Configuration**: Added model costs in
`/backend/backend/data/block_cost_config.py`:
  - v0-1.5-md: 1 credit
  - v0-1.5-lg: 2 credits
  - v0-1.0-md: 1 credit

#### Configuration Changes
- **Settings**: Added `v0_api_key` field to `Secrets` class in
`/backend/backend/util/settings.py`
- **Environment Variables**: Added `V0_API_KEY=` to
`/backend/.env.default`

### Features
-  Full OpenAI-compatible API support
-  Tool/function calling support
-  JSON response format support
-  Framework-aware completions optimized for React/Next.js
-  Large context windows (up to 512K tokens)
-  Integrated with platform credit system

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  <!-- Put your test plan here: -->
- [x] Run existing block tests to ensure no regressions: `poetry run
pytest backend/blocks/test/test_block.py`
  - [x] Verify AITextGeneratorBlock works with v0 models
  - [x] Confirm all model metadata is correctly configured
  - [x] Validate cost configuration is properly set up
  - [x] Check that v0_credentials has a valid UUID4

#### For configuration changes:
- [x] `.env.example` is updated or already compatible with my changes
  - Added `V0_API_KEY=` to `/backend/.env.default`
- [x] `docker-compose.yml` is updated or already compatible with my
changes
  - No changes needed - uses existing environment variable patterns
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**)

### Configuration Requirements
Users need to:
1. Obtain a v0 API key from [v0.app](https://v0.app) (requires Premium
or Team plan)
2. Add `V0_API_KEY=your-api-key` to their `.env` file

### API Documentation
- v0 API Docs: https://v0.app/docs/api
- Model API Docs: https://v0.app/docs/api/model

### Testing
All existing tests pass with the new v0 integration:
```bash
poetry run pytest backend/blocks/test/test_block.py::test_available_blocks -k "AITextGeneratorBlock" -xvs
# Result: PASSED
```
2025-08-15 05:59:43 +00:00
..

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:

  1. Clone this repository to your local machine and navigate to the autogpt_platform directory within the repository:

    git clone <https://github.com/Significant-Gravitas/AutoGPT.git | git@github.com:Significant-Gravitas/AutoGPT.git>
    cd AutoGPT/autogpt_platform
    
  2. Run the following command:

    cp .env.default .env
    

    This command will copy the .env.default file to .env. You can modify the .env file to add your own environment variables.

  3. Run the following command:

    docker compose up -d
    

    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.

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:

  1. Updating and restarting a specific service:

    docker compose build api_srv
    docker compose up -d --no-deps api_srv
    

    This rebuilds the api_srv service and restarts it without affecting other services.

  2. Viewing logs for troubleshooting:

    docker compose logs -f api_srv ws_srv
    

    This shows and follows the logs for both api_srv and ws_srv services.

  3. Scaling a service for increased load:

    docker compose up -d --scale executor=3
    

    This scales the executor service to 3 instances to handle increased load.

  4. Stopping the entire system for maintenance:

    docker compose stop
    docker compose rm -f
    docker compose pull
    docker compose up -d
    

    This stops all services, removes containers, pulls the latest images, and restarts the system.

  5. Developing with live updates:

    docker compose watch
    

    This watches for changes in your code and automatically updates the relevant services.

  6. Checking the status of services:

    docker compose ps
    

    This 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:

  1. Open the docker-compose.yml file in a text editor.

  2. 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:
    
  3. Save the file and run docker compose up -d to 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 Orval
  • 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-all
    

This will fetch the latest OpenAPI specification and regenerate the TypeScript client code.