🚀 Automate repetitive browser tasks!

Try it yourself:

curl -X POST http://localhost:3000/runs \ -H "Content-Type: application/json" \ -d '{ "task": "Go to https://webagent.cloud and explain what the platform does." }' 

The universal connector for web agents :

• 🔗 Integrate into any app with our API
• 🌐 Multiple LLM compatibility
• 🔎 Supports multiple Browsers providers
• 🔒 Host on your infrastructure
• 💽 Store and retrieve results in database
• 🪝 Get notified of results with webhooks
• 🗄️ Structure results with JSON Schema

1. Make sure you have Python 3.12+ installed.
2. Install the dependencies:

pip install -r requirements.txt

3. Configure your .env file with the necessary environment variables (API keys, etc.) Add your API keys for the provider you want to use to your .env file.

OPENAI_API_KEY= ANTHROPIC_API_KEY= AZURE_ENDPOINT= AZURE_OPENAI_API_KEY= GEMINI_API_KEY= DEEPSEEK_API_KEY= GROK_API_KEY= NOVITA_API_KEY= 

4. Run the server

python server.py

1. Build the Docker image:

docker build -t webagent .

2. Run the container:

docker run -p 8080:8080 --env-file .env webagent

The Docker image includes all necessary dependencies, including Playwright for browser automation.

1. Configure your environment variables in the docker-compose.yml file or in a .env file.

2. Start the service:

docker-compose up

python server.py

# Using Docker docker run -p 8080:8080 --env-file .env webagent # Using Docker Compose docker-compose up

The server will start at http://localhost:8080

Once the server is started, you can access the interactive API documentation at:

• http://localhost:8080/docs (Swagger UI)
• http://localhost:8080/redoc (ReDoc)

Endpoint: POST /runs

Request body:

{ "task": "go to this site https://example.com and retrieve the page title", "provider": "openai", "model": "o3" }

Response:

{ "history": [ { "is_done": true, "success": true, "extracted_content": "Example Domain", "error": null, "include_in_memory": false } ], "result": "Example Domain", "is_done": true, "is_successful": true, "status": "success" }

# Execute a task curl -X 'POST' \ 'http://localhost:8080/run' \ -H 'Content-Type: application/json' \ -d '{  "task": "go to this site https://example.com and retrieve the page title",  "model": "o3",  "provider": "openai" }'

import requests # Base URL of the API base_url = "http://localhost:8080" # Execute a task response = requests.post( f"{base_url}/run", json={ "task": "go to this site https://example.com and retrieve the page title", "model": "o3", "provider": "openai" } ) # Print the response print(f"Response: {response.json()}")