AgentPress: Building Blocks for AI Agents

AgentPress is not a agent framework - it's a collection of lightweight, modular utilities that serve as building blocks for creating AI agents. Think of it as "shadcn/ui for AI agents" - a set of utils to copy, paste, and customize in order to quickly bootstrap your AI App / Agent.

AgentPress provides Messages[] API on Steroids called "Threads", a ThreadManager with automatic Tool Execution and a simple StateManager.

Installation & Setup

1. Install the package:

pip install agentpress

2. Initialize AgentPress in your project:

agentpress init

This will create a agentpress directory with the core utilities you can customize.

Key Components

• Threads: Simple message thread handling utilities
• Automatic Tool: Flexible tool definition and automatic execution
• State Management: Basic JSON-based state persistence
• LLM Integration: Provider-agnostic LLM calls via LiteLLM

Quick Start

1. Set up your environment variables (API keys, etc.) in a .env file.

2. Create a tool - copy this code directly into your project:

from agentpress.tool import Tool, ToolResult, tool_schema

class CalculatorTool(Tool):
    @tool_schema({
        "name": "add",
        "description": "Add two numbers",
        "parameters": {
            "type": "object",
            "properties": {
                "a": {"type": "number"},
                "b": {"type": "number"}
            },
            "required": ["a", "b"]
        }
    })
    async def add(self, a: float, b: float) -> ToolResult:
        return self.success_response(f"The sum is {a + b}")

3. Use the Thread Manager - customize as needed:

import asyncio
from agentpress.thread_manager import ThreadManager

async def main():
    manager = ThreadManager()
    manager.add_tool(CalculatorTool)
    thread_id = await manager.create_thread()
    
    # Add your custom logic here
    await manager.add_message(thread_id, {
        "role": "user", 
        "content": "What's 2 + 2?"
    })
    
    response = await manager.run_thread(
        thread_id=thread_id,
        system_message={
            "role": "system", 
            "content": "You are a helpful assistant with calculation abilities."
        },
        model_name="gpt-4",
        use_tools=True,
        execute_model_tool_calls=True
    )
    print("Response:", response)

asyncio.run(main())

Building Your Own Agent

Example of a customized autonomous agent:

import asyncio
from agentpress.thread_manager import ThreadManager
from your_custom_tools import CustomTool

async def run_agent(max_iterations=5):
    # Create your own manager instance
    manager = ThreadManager()
    thread_id = await manager.create_thread()
    
    # Add your custom tools
    manager.add_tool(CustomTool)
    
    # Define your agent's behavior
    system_message = {
        "role": "system",
        "content": "Your custom system message here"
    }
    
    # Implement your control loop
    for iteration in range(max_iterations):
        response = await manager.run_thread(
            thread_id=thread_id,
            system_message=system_message,
            model_name="your-preferred-model",
            # Customize parameters as needed
        )
        
        # Add your custom logic here
        process_response(response)

if __name__ == "__main__":
    asyncio.run(run_agent())

Development

1. Clone for reference:

git clone https://github.com/kortix-ai/agentpress
cd agentpress

2. Install dependencies:

pip install poetry
poetry install

Philosophy

• Modular: Pick and choose what you need. Each component is designed to work independently.
• Agnostic: Built on LiteLLM, supporting any LLM provider. Minimal opinions, maximum flexibility.
• Simplicity: Clean, readable code that's easy to understand and modify.
• Plug & Play: Start with our defaults, then customize to your needs.
• No Lock-in: Take full ownership of the code. Copy what you need directly into your codebase.

Contributing

We welcome contributions! Feel free to:

• Submit issues for bugs or suggestions
• Fork the repository and send pull requests
• Share how you've used AgentPress in your projects

License

MIT License

Built with ❤️ by Kortix AI Corp