README.md

metadata

title: Agentic RAG System
emoji: ⚡
colorFrom: blue
colorTo: indigo
sdk: gradio
sdk_version: 5.43.1
app_file: app.py
pinned: false
license: mit
short_description: Agentic RAG application with enhanced web search.

⚡ Agentic RAG System

An Agentic Retrieval-Augmented Generation (RAG) system that combines local vector search with live web retrieval to provide grounded, cited answers.

Features

• 🔍 Semantic retrieval with FAISS
• 🌐 Live web search fallback via Tavily
• 💬 Multi-turn conversations with contextual memory
• 📚 Automatic source citations
• ⚡ Powered by Qwen2.5-7B-Instruct

Tech Stack

• Framework: LangGraph
• LLM: Qwen2.5-7B-Instruct
• Vector Store: FAISS
• Web Search: Tavily

Usage

1. Ask a question.
2. The system first searches its local knowledge base.
3. If relevant information isn't available, it retrieves information from the web.
4. Responses include references to the retrieved sources.

Configuration

This Space requires the following secret:

Secret	Description
TAVILY_API_KEY	Tavily Search API key

The Space is configured to run on ZeroGPU hardware.

Source Code

The complete implementation and project documentation are available on GitHub.