agentaxis 0.1.0

A production-ready, extensible multi-LLM AI Agent Framework with LiteLLM support

🤖 AI Agent Framework

A production-ready, extensible AI Agent Framework for Python. Built with Clean Architecture, it supports multi-provider LLM orchestration (via LiteLLM), memory management, and tool usage.

🚀 Features

• Multi-Provider Support: Switch between OpenAI, Anthropic, Gemini, and local models seamlessly using LiteLLM.
• Intelligent Routing: Architecture designed for dynamic model selection.
• Tooling System: Register Python functions as tools with automatic JSON schema generation + MCP Support.
• Memory Management: Pluggable memory backends (In-Memory provided, Extensible to Redis/Postgres).
• Vector Store / RAG: Built-in adapter for ChromaDB.
• Clean Architecture: strictly decoupled core logic from infrastructure.

📦 Installation

pip install agentaxis

⚡ Quick Start

1. Basic Agent

from agentaxis import AgentService, AgentEntity, InMemoryMemory, LiteLLMAdapter
from agentaxis.adapters.tools import ToolRegistry
import asyncio

async def main():
    # 1. Setup Wrapper
    llm = LiteLLMAdapter(model="gpt-4o", api_key="sk-...")
    memory = InMemoryMemory()
    registry = ToolRegistry()
    
    # 2. Register Tools
    @registry.register
    def get_time(timezone: str) -> str:
        """Returns current time in timezone."""
        return "12:00 PM"

    # 3. Create Agent
    entity = AgentEntity(id="bot-1", name="Helper", role_description="Assistant")
    agent = AgentService(agent_entity=entity, llm=llm, memory=memory, tool_registry=registry)

    # 4. Chat
    response = await agent.chat("What time is it in NY?")
    print(response)

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

🏗️ Architecture

The framework follows Hexagonal Architecture:

• Core/Domain: Pure business entities (Agent, Message).
• Core/Ports: Interfaces for external dependencies (BaseLLM, MemoryPort).
• Adapters: Concrete implementations (LiteLLMAdapter, ChromaAdapter).

🛠️ Development

1. Clone the repository.
2. Install dependencies: pip install -e .[dev]
3. Run tests: pytest

🤝 Contribution

Contributions are welcome! Please follow the Clean Architecture patterns.