README.md

metadata

title: DDaT RAG Chatbot
emoji: 🧠
colorFrom: green
colorTo: purple
sdk: gradio
sdk_version: 4.26.0
app_file: app.py
pinned: false

RAG Chatbot for DDaT Knowledge Base (Gradio + Hugging Face)

This chatbot answers questions using Retrieval-Augmented Generation (RAG) powered by LangChain + OpenAI, loading multiple PDFs from a folder.

📁 How It Works

• Upload documents to knowledge_base/ (PDF format)
• They are indexed and embedded into a vector DB (FAISS)
• Queries are answered using OpenAI with document grounding

📦 Files

• app.py – main Gradio chatbot app
• requirements.txt – dependencies
• README.md – Hugging Face setup info
• knowledge_base/ – folder to store your PDFs

🚀 How to Deploy

1. Go to https://huggingface.co/spaces

2. Create a Gradio Space

3. Upload:

   • app.py
   • requirements.txt
   • README.md
   • knowledge_base/ folder with your PDFs

4. Go to Settings → Secrets, add:

   OPENAI_API_KEY = sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
   

5. ✅ Your chatbot will be live and answer questions from your full document base!

🧠 Built With

• LangChain
• OpenAI
• FAISS
• Gradio