Agentify 🤖

Agentify is an intelligent orchestration platform designed to manage and coordinate multiple AI agents. It leverages OpenAI's GPT model to facilitate seamless interaction between agents and their tools, offering a dynamic environment for complex task execution.

Table of Contents

• Features
• Installation
• Backend Structure
• Agent & Tool Format
• Configuration
• Usage
• Contributing
• License

Features ✨

• Agent Creation: Dynamically create AI agents with specific contexts and toolsets.
• Orchestration: Execute complex workflows by delegating tasks to various agents.
• Tool Integration: Easily extend agent capabilities with custom tools.
• Visualization: Visualize agent networks and interactions in real-time.

Installation 🚀

To get started with Agentify, follow these steps:

git clone https://github.com/corzed/agentify.git
cd agentify
pip install -r requirements.txt
cp .env.example .env

Ensure you set up your .env file with the appropriate environment variables, including your OpenAI API key.

Backend Structure 📂

Organized as follows:

backend/
│
├── agents/             # Folder for storing agent configuration files
│   ├── agent1.json
│   └── agent2.json
│
├── tools/              # Folder for storing tool scripts
│   ├── tool1.py
│   └── tool2.py
│
├── app.py              # Main Flask application
├── requirements.txt    # Python dependencies
└── .env.example        # Example environment variables

Agent & Tool Format 🛠️

Agent Configuration Files

Each agent is represented by a JSON file stored in the agents/ directory. The file defines the agent's name, context, and associated tools.

Example: agents/agent1.json

{
    "name": "Agent1",
    "context": "This is the context for Agent1.",
    "tools": ["tool1", "tool2"]
}

• name: The agent's name.
• context: The initial context or background information for the agent.
• tools: A list of tools available to the agent.

Tool Scripts

Tools are Python scripts located in the tools/ directory. Each tool should define a tool dictionary with at least a description and a function key.

Example: tools/tool1.py

tool = {
    "description": "This tool processes data and returns results.",
    "function": lambda data: f"Processed {data}"
}

• description: A brief description of what the tool does.
• function: A callable that performs the tool's operation.

Configuration ⚙️

The main configurations are handled through the .env file:

• OPENAI_API_KEY: Your OpenAI API key.
• GPT_MODEL: The GPT model to be used (e.g., gpt-4o-mini).

Usage 💻

Running the Application

To start the Agentify server, run:

python app.py

This will start the Flask server with SocketIO enabled for real-time communication.

Managing Agents and Tools

Agents can be added in real time on the website, or added/modified by updating the respective JSON files in the agents/ directory and Python scripts in the tools/ directory. The server will not automatically recognize these changes and will require a restart though.

Visualizing the Network

Once the agents are created and active, you can visualize the network of agents, orchestrators, and tools in real-time.

Contributing 🤝

Contributions are welcome! Please follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes.
4. Commit your changes (git commit -m 'Add some feature').
5. Push to the branch (git push origin feature-branch).
6. Open a pull request.

License 📄

This project is licensed under the MIT License. See the LICENSE file for more details.