---
title: Multi-Source RAG Assistant
emoji: 📚
colorFrom: indigo
colorTo: blue
sdk: streamlit
sdk_version: 1.45.0
app_file: app.py
pinned: false
---

# 📚 Multi-Source RAG Assistant

This app lets users interact with:
- 🧾 PDF documents
- 📊 CSV datasets (with automatic EDA)
- 🌐 Any website (scraped and embedded into a vector database)

💡 Powered by:
- Google Gemini API
- FAISS vector search
- LangChain framework

## 🔧 How It Works

1. Select input type from sidebar: **PDF**, **CSV**, or **Website URL**.
2. Upload or input accordingly.
3. Ask questions — the assistant answers using context-aware RAG via Gemini.

## 🚀 Getting Started

Before using the app:
- Enter your **Gemini API Key** in the sidebar.

## 🧠 Tech Stack

- `Streamlit` for UI
- `LangChain` for RAG logic
- `FAISS` for vector storage
- `SentenceTransformers` for embeddings
- `Google Generative AI (Gemini)` for LLM-powered answers

---

### 🛠 Developed by Abhijeet Singh

Hosted with ❤️ on [Hugging Face Spaces](https://huggingface.co/spaces)