Autonomous AI Agent System

This project implements a fully autonomous AI agent capable of task planning, dynamic tool usage, and iterative reasoning using LLMs. It simulates real-world autonomy in agents — from goal breakdown to execution — using modern agentic design principles.

✨ Key Highlights

• ✅ Goal-driven autonomous behavior without human intervention
• 🔁 Multi-step task planning using a ReAct-style framework
• 🧠 Integration of LLMs for dynamic reasoning and decision making
• 🛠️ Tool-use execution with intermediate memory and contextual awareness
• 📦 Modular and extensible for future tools or reasoning layers

🧰 Core Tech Stack

• Python + LangChain
• OpenAI / Local LLMs (pluggable)
• LangChain Agents (ReAct framework)
• Custom Toolkits
• Async task handling

📌 What You’ll See

This project shows how a modern AI system can:

• Interpret complex prompts or objectives
• Create its own sub-tasks
• Select appropriate tools
• Loop until a final result is achieved — all autonomously

🌍 Real-World Use Case Potential

• AI customer support agents
• Automated research agents
• Workflow assistants
• Autonomous taskbots for productivity

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🧑‍💻 Solo Project • No Framework Templates Used • Built From Scratch

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