README_HF.md

metadata

title: Multi-Agent RAG System
emoji: 🤖
colorFrom: blue
colorTo: purple
sdk: docker
app_port: 8000
pinned: false
license: mit

Multi-Agent RAG System

A production-grade Retrieval-Augmented Generation system using multiple specialized AI agents.

Features

• Router Agent: Classifies queries and routes to appropriate agents
• Retriever Agent: Semantic search using FAISS vector store
• Reasoning Agent: Generates grounded responses from context
• Action Agent: Executes actions like creating tickets

API Endpoints

• POST /api/v1/query - Submit a question
• POST /api/v1/ingest - Ingest documents
• GET /api/v1/health - Health check
• GET /docs - Swagger UI

Usage

import requests

response = requests.post(
    "https://your-space.hf.space/api/v1/query",
    json={"query": "How do I reset my password?"}
)
print(response.json()["answer"])

Architecture

User Query → Router Agent → Retriever Agent → Reasoning Agent → Response
                                    ↓
                              FAISS Vector Store

Built with LangChain, FastAPI, and HuggingFace models.