🤖 LangGraph AI Chatbot

An intelligent AI chatbot built using LangGraph Agents, FastAPI, Streamlit, and Groq LLMs, enhanced with Tavily Web Search functionality.
A clean frontend + powerful backend = seamless chatbot experience!

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📸 Screenshot

🛠️ Tech Stack

• Python 3.10
• LangGraph (AI Agent Framework)
• FastAPI (Backend API)
• Streamlit (Frontend UI)
• Groq LLMs (llama3 models)
• Tavily (Web Search API)
• Pydantic (Request Validation)
• dotenv (Environment Variables)

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🚀 How It Works

1. Frontend (Streamlit) collects user query, model selection, system prompt, etc.
2. Backend (FastAPI) handles request, initializes the AI Agent dynamically based on input.
3. LangGraph Agent communicates with Groq models and optionally uses Tavily Search for real-time information.
4. Result is returned back to the frontend and displayed beautifully along with avatars and download options.

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📂 Project Structure

• ├── AI_Agent.py # LangGraph agent setup
• ├── Backend.py # FastAPI backend server
• ├── Frontend.py # Streamlit frontend UI
• ├── app.py # Entry point to run the app
• ├── requirements.txt # List of required Python packages
• ├── .env # Environment variables (API keys)
• ├── venv/ # Virtual environment (not pushed)
• ├── README.md # Project Documentation

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Create and activate a virtual environment

• python -m venv venv
• source venv/bin/activate # MacOS/Linux
• venv\Scripts\activate # Windows

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Add your .env file

• GROQ_API_KEY = your_groq_api_key_here
• TAVILY_API_KEY = your_tavily_api_key_here

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🧠 Supported LLM Models

• llama3-70b-8192
• llama-3.3-70b-versatile

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📢 Features

• Dynamic model selection (Groq)
• Custom system prompts
• Real-time web search (Tavily integration)
• Beautiful chat history with avatars
• Download AI responses easily
• Lightweight and beginner-friendly

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🌐 Web App Links

• Backend API (FastAPI) Live
• Frontend UI (Streamlit):
• • On Streamlit cloud
  • On Hugging Face

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🙏 Acknowledgements

• A heartfelt thank you to AI with Hassan on YouTube Channel — this project wouldn’t have come to life without his insightful tutorials and guidance.
• His content makes complex LangChain & multi-agent systems feel simple and achievable. If you're diving into AI agents, his videos are a must-watch!
• I made a few customizations to better fit my learning goals — for example, I currently use only one model provider (Groq) instead of combining Groq and OpenAI as demonstrated in his tutorials.

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👨‍💻 Author

• Made with ❤️ by Uzma Khatun
• Connect on LinkedIn