🧠 Ask Your PDF: Semantic Search & Chatbot using Qdrant, LangChain, and OpenAI

This project enables you to upload a PDF document and interact with it through a chatbot powered by vector search and OpenAI. It leverages LangChain, SentenceTransformer, Qdrant, and OpenAI GPT-4 to perform document chunking, embedding, similarity search, and conversational responses.

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🚀 Features

• Load any PDF document
• Split and embed using SentenceTransformer
• Store in Qdrant vector database
• Query using natural language
• Retrieve semantic context
• Generate concise answers using OpenAI GPT-4 or GPT-3.5

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🧰 Tech Stack

• Python 3.11+
• LangChain
• SentenceTransformers
• Qdrant
• OpenAI API
• PyPDFLoader

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📦 Installation

1. Clone the Repository

git clone https://github.com/srinivasangr/Rag-chatbot-from-pdf.git
cd Rag-chatbot-from-pdf

2. Create a Virtual Environment

python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

4. Set Environment Variables

Create a .env file in the root directory:

OPENAI_API_KEY=your_openai_api_key

🧪 Run the Application

1. Start Qdrant (via Docker)

docker run -p 6333:6333 -p 6334:6334 qdrant/qdrant

2. Run the Script

python app.py

📁 File Structure

├── app.py ├── mahabharata.pdf ├── .env ├── requirements.txt └── README.md