Smart PDF Chatbot (RAG + Ollama)

A Retrieval-Augmented Generation (RAG) based AI chatbot that allows users to upload any PDF and interact with it in a conversational way.
Built using Streamlit, LangChain, FAISS, HuggingFace embeddings, and Ollama (local LLM).

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Features

• Upload any PDF document
• AI understands document content using embeddings
• Chat with your PDF like a personal assistant
• Context-aware answers using FAISS retrieval
• Supports follow-up questions (memory enabled)
• Runs locally using Ollama (no API cost)

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Tech Stack

• Streamlit (Frontend UI)
• LangChain (RAG pipeline)
• FAISS (Vector database)
• HuggingFace Transformers (Embeddings)
• SentenceTransformers (all-MiniLM-L6-v2)
• Ollama (Local LLM - Mistral)
• PyPDF (PDF parsing)

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System Architecture

The following diagram explains the end-to-end workflow of the Smart PDF Chatbot using RAG and Ollama.

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Setup Guide

1️ Clone the repository

git clone https://github.com/ya-sonia/RAG-based-PDF-chatbot.git
cd RAG-based-PDF-chatbot

2. Create and activate virtual environment

For Windows :
python -m venv venv
venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

4. Install Ollama (IMPORTANT)

Download Ollama: https://ollama.com

Then pull the model:

ollama pull mistral

Run Ollama (keep it running in background):

ollama run mistral

5. Run the Application

streamlit run app.py