🎓 Student RAG Chatbot (LangGraph + Groq)

This project is an AI-powered student performance assistant built using LangGraph, LangChain, and Groq’s LLaMA-3 model. It integrates a Retrieval-Augmented Generation (RAG) system to answer queries about student performance, assignments, marks, and attendance.

🚀 Features

🔍 Student RAG Helper – retrieves academic data from a structured dataset.

🧠 LLM-Powered Chatbot – uses Groq’s LLaMA-3 (llama3-8b-8192) for intelligent responses.

⚡ LangGraph Workflow – tool-augmented conversation flow with conditional routing.

🛠️ Custom Tool Integration – structured RAG tool (student_progress_lookup) for academic queries.

💬 Interactive CLI Chat – ask natural language questions like:

"What is my overall progress in Data Structures?"

"How many assignments are pending for Ganesh?"

"Who are the top 3 students in AI?"

🗂️ Project Structure ├── helpers.py # Contains StudentRAGHelper class (retrieval logic) ├── main.py # Chatbot implementation (LangGraph + Groq + Tools) ├── .env # Store your GROQ_API_KEY ├── requirements.txt # Python dependencies └── README.md # Project documentation

🔑 Prerequisites

Python 3.9+

A valid Groq API key

⚙️ Installation

Clone the repo

git clone https://github.com/your-username/student-rag-chatbot.git cd student-rag-chatbot

Create a virtual environment

python -m venv venv source venv/bin/activate # (Linux/Mac) venv\Scripts\activate # (Windows)

Install dependencies

pip install -r requirements.txt

Set up environment variables Create a .env file in the root directory and add:

GROQ_API_KEY=your_groq_api_key_here

▶️ Usage

Run the chatbot:

python main.py

Example conversation:

💬 Student RAG Chatbot (LangGraph + Groq) Type 'exit' to quit.

Examples:

• What is my overall progress in Data Structures?
• How many assignments are pending for Ganesh?
• Who are the top 3 students in AI?

You: How many assignments are pending for Ganesh? Bot: Ganesh has 2 pending assignments in Machine Learning.

🛠️ Tech Stack

LangChain – LLM orchestration

LangGraph – stateful graph-based agent framework

Groq – fast LLM inference (LLaMA-3 model)

Pandas – dataset handling

dotenv – environment variable management

📌 Next Steps

✅ Add support for multiple datasets (marks, attendance, assignments).

✅ Extend RAG retrieval to include semantic search on notes.

🚀 Deploy chatbot as a web app (Streamlit/Flask/FastAPI).

🔒 Add authentication for multi-user access.

🤝 Contributing

Contributions are welcome! Feel free to fork this repo, create a feature branch, and submit a PR.