🤖 AI Agent Framework

Autonomous AI agent framework with multi-model orchestration and tool-use

Overview

Production-ready framework for building autonomous AI agents that can reason, plan, and execute complex tasks using multiple LLM providers.

Features

• 🧠 Multi-model orchestration — OpenAI, Anthropic, local models
• 🔧 Tool-use system — extensible tool registry with validation
• 📋 Task planning — automatic task decomposition and execution
• 🔄 Memory management — short-term and long-term agent memory
• 🌐 API server — REST and WebSocket interfaces
• 📊 Observability — tracing, logging, and performance metrics

Quick Start

from ai_agent import Agent, ToolRegistry

agent = Agent(
    model="gpt-4",
    tools=ToolRegistry.default(),
    memory_backend="redis"
)

result = await agent.execute("Analyze the codebase and suggest improvements")

Architecture

Agent Core → Planning → Tool Execution → Memory → Response
     ↓           ↓            ↓             ↓
  LLM API    Task Graph    Registry     Redis/PG

Tech Stack

• Runtime: Python 3.11+
• AI: LangChain, OpenAI, Anthropic
• Infra: Redis, PostgreSQL, Docker
• API: FastAPI, WebSocket

Author

@redoh — Senior Full-Stack Engineer | AI & Machine Learning