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---
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) |