LangGraph AI Chatbot

LangGraph AI Chatbot is a powerful chatbot application built using FastAPI, LangGraph, and LangChain. It leverages large language models (LLMs) like Llama3 and Mixtral, integrated with the Tavily search tool, to provide intelligent responses. The frontend is designed with Streamlit for an interactive and sleek user experience.

🚀 Features

• FastAPI Backend: Efficient API for handling chat requests.
• LangGraph & LangChain: Enables intelligent conversation processing.
• Multiple LLM Models: Supports llama3-70b-8192 and mixtral-8x7b-32768.
• Tavily Search Integration: Fetches relevant search results.
• Streamlit UI: Interactive, customizable, and responsive frontend.
• Docker Support: Easily deploy the application with Docker.
• Custom Themes: Light & Dark mode for enhanced user experience.

🛠️ Installation & Setup

1️⃣ Clone the Repository

https://github.com/ToufiqQureshi/ai-agent-with-langraph.git

2️⃣ Create a Virtual Environment & Install Dependencies

python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`
pip install -r requirements.txt

3️⃣ Set Environment Variables

Create a .env file and add your API keys:

GROQ_API_KEY=your_groq_api_key
TAVILY_API_KEY=your_tavily_api_key

Alternatively, set them in your terminal:

export GROQ_API_KEY=your_groq_api_key
export TAVILY_API_KEY=your_tavily_api_key

4️⃣ Run the Application

Start FastAPI Backend

uvicorn main:app --host 0.0.0.0 --port 8000 --reload

Start Streamlit Frontend

streamlit run ui.py

🐳 Deploy with Docker

1️⃣ Build the Docker Image

docker build -t langgraph-chatbot .

2️⃣ Run the Docker Container

docker run -p 8000:8000 -p 8501:8501 langgraph-chatbot

🔧 API Usage

Chat Endpoint

URL: http://127.0.0.1:8000/chat

Request Body:

{
  "system_prompt": "Define your AI agent",
  "model_name": "llama3-70b-8192",
  "messages": ["Hello, how can you help me?"]
}

Response:

{
  "messages": [
    { "type": "ai", "content": "Hello! How can I assist you today?" }
  ]
}

🖥️ UI Features

• Send Messages: Chat with AI.
• Select Model: Choose from llama3-70b-8192 or mixtral-8x7b-32768.
• Define AI Behavior: Custom system prompts.
• Dark & Light Themes: Switch between modes for a better experience.

📜 Project Structure

langgraph-chatbot/
│── main.py          # FastAPI backend
│── ui.py            # Streamlit frontend
│── requirements.txt # Dependencies
│── Dockerfile       # Docker setup
│── .env             # Environment variables (ignored in Git)

📜 License

This project is licensed under the MIT License.

📩 Contact

For support or inquiries, contact: toufiqqureshi651@gmail.com

Enjoy using LangGraph AI Chatbot! 🎉