README.md

metadata

title: openai_swarm_firecrawl
app_file: user_interface.py
sdk: gradio
sdk_version: 4.44.1

Swarm Firecrawl Marketing Agent

A multi-agent system using OpenAI's Swarm for AI-powered content analysis and generation, integrated with Firecrawl for web scraping. This project features a Gradio-based user interface for easy interaction and configuration of the agent swarm.

Features

• Web scraping using Firecrawl API
• Configurable multi-agent system for content analysis and generation
• Interactive Gradio-based graphical user interface
• Real-time updates on scraping and agent progress
• Ability to modify agent configurations on-the-fly

Requirements

• Python 3.7+
• Firecrawl API key
• OpenAI API key

Setup

1. Clone the repository:

   git clone https://github.com/your-username/swarm-firecrawl-marketing-agent.git
   cd swarm-firecrawl-marketing-agent
   

2. Install the required packages:

   pip install -r requirements.txt
   

3. Set up your environment variables in a .env file:

   OPENAI_API_KEY=your_openai_api_key
   FIRECRAWL_API_KEY=your_firecrawl_api_key
   

Usage

User Interface

To use the Gradio-based user interface:

1. Run the user interface:

   python user_interface.py
   

2. In the Gradio interface:

   • The URL is pre-filled with https://www.okgo.app/, but you can change it if needed.
   • Click "Scrape Website" to fetch the content.
   • Modify agent configurations in the respective tabs if desired.
   • Click "Run Workflow" to process the scraped content through the SwarmEditor.

Configuration

The system uses a configuration file to define the agents in the swarm. You can modify the swarm_config.json file to change the number of agents, their names, and instructions.

Example configuration:

{
  "agents": [
    {
      "name": "Agent 1",
      "instructions": "Process the input data and provide initial insights."
    },
    {
      "name": "Agent 2",
      "instructions": "Analyze the insights from Agent 1 and generate recommendations."
    },
    {
      "name": "Agent 3",
      "instructions": "Create a final report based on the recommendations from Agent 2."
    }
  ]
}

Integration Test

To run the integration test:

python integration_test.py

This will use Firecrawl to scrape https://www.okgo.app/, then pass the scraped content through the SwarmEditor workflow, and finally output the result to stdout.

Project Structure

• swarm_editor.py: Contains the SwarmEditor class for managing the agent swarm.
• user_interface.py: Implements the Gradio-based user interface.
• integration_test.py: Provides an end-to-end test of the system.
• swarm_config.json: Configuration file for defining the agent swarm.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.