README.md

metadata

title: Template Final Assignment
emoji: 🕵🏻‍♂️
colorFrom: indigo
colorTo: indigo
sdk: gradio
sdk_version: 5.25.2
app_file: app.py
pinned: false
hf_oauth: true
hf_oauth_expiration_minutes: 480

🧠 AI RAG Agent - Final Project (LangGraph + Supabase)

This project is a Retrieval-Augmented Generation (RAG) agent built using LangGraph, LangChain, and Supabase as a vector store.
It allows users to query a custom knowledge base hosted in their own Supabase instance.

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📋 Features

• 🔎 RAG: Use your Supabase + FAISS for retrieval
• 🤖 LLM-powered: Gemini or other models via LangChain
• 🌐 Optional web search fallback (Tavily or Arxiv)
• 🔒 Keep your API keys secure with private .env

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🚀 How to Use

1. Clone this Space

Click the "Duplicate Space" button at the top-right to create your own copy.

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2. Configure .env Variables

Inside your cloned Space, go to the "Files" tab, create a file named .env, and add the following variables:

SUPABASE_URL=your_supabase_url
SUPABASE_SERVICE_KEY=your_supabase_service_key
GOOGLE_API_KEY=your_google_api_key
TAVILY_API_KEY=your_tavily_api_key  # optional if using Tavily tool


Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference