🤖 End-to-End Agentic AI Chatbot This project is a sophisticated, end-to-end Agentic AI Chatbot built with Python. It leverages the power of large language models (LLMs) and advanced frameworks like LangChain and LangGraph to create a conversational agent that can perform complex tasks and interact with users in a natural way. The application is built with a Streamlit interface, making it easy to deploy and share.

🚀 Live Demo You can interact with the chatbot live at: https://agentic-ai-chatbot-1-oujg.onrender.com

✨ Features 💬 Conversational AI: Engage in natural, human-like conversations.

🔧 Tool Usage: The agent can use external tools to fetch information.

⚙️ Task Automation: Capable of understanding multi-step instructions and automating complex workflows.

🖥️ Web Interface: A clean and user-friendly web interface built with Streamlit.

🏗️ Scalable Architecture: Built with LangGraph, allowing for the creation of complex, stateful, and multi-agent workflows.

🛠️ Technologies Used This project utilizes a modern stack for building agentic AI applications:

🐍 Backend: Python

🧠 AI/LLM Frameworks:

LangChain: A framework for developing applications powered by language models.

LangGraph: A library for building stateful, multi-agent applications with LLMs.

☁️ LLM Providers:

Groq: Powers the application with a fast inference engine.

🌐 Web Framework:

Streamlit: An open-source app framework for Machine Learning and Data Science projects.

🔧 Tools:

Tavily Python: A search API optimized for LLMs.

✅ Prerequisites Python 3.8 or higher

An API key from Groq, OpenAI, or another LLM provider.

A Tavily API key for search functionality.