AI PDF Chatbot (RAG)

An AI-powered chatbot that allows users to upload PDF documents and ask questions about their content.

This project implements a Retrieval-Augmented Generation (RAG) pipeline using vector embeddings and a local language model.

Features

• Upload multiple PDF documents
• Ask questions about the uploaded documents
• Vector search using ChromaDB
• AI-generated answers
• Simple ChatGPT-style web interface

Tech Stack

Python
FastAPI
LangChain
ChromaDB
HuggingFace Transformers
SentenceTransformers

How it Works

1. PDF documents are uploaded
2. Documents are split into smaller text chunks
3. Each chunk is converted into embeddings
4. Embeddings are stored in a vector database
5. User questions retrieve the most relevant chunks
6. A language model generates the final answer

Installation

Clone the repository:

git clone https://github.com/adi232323/rag-pdf-chatbot.git

Install dependencies:

pip install -r requirements.txt

Run the server:

uvicorn api:app --host 0.0.0.0 --port 8000

Open the application:

http://localhost:8000

Project Structure

rag-pdf-chatbot │ ├── api.py ├── rag_pipeline.py ├── index.html ├── requirements.txt └── README.md

Output