🛰️ Live AI Assistant

A real-time AI assistant that searches the web live and answers your questions instantly — powered by Groq, Tavily, and LangChain.

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🚀 Demo

Ask anything — get real-time answers with sources!

url:https://6rzdockyzxnsctkevcaejp.streamlit.app/

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🧠 How It Works

User Question
     ↓
Tavily searches the web live
     ↓
Results passed to Groq LLM as context
     ↓
Answer returned with sources

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🛠️ Tech Stack

Tool	Purpose
LangChain	Chain building
Groq (LLaMA 3.3)	LLM - super fast inference
Tavily	Live web search API
Streamlit	UI
Python	Backend

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📁 Project Structure

live-ai-assistant/
│
├── assistant.py     → Core logic (LangChain + Groq + Tavily)
├── app.py           → Streamlit UI
├── requirements.txt → Dependencies
├── .gitignore       → Ignores .env file
└── README.md

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⚙️ Setup Locally

1. Clone the repo

git clone https://github.com/vivek41-glitch/live-ai-assistant.git
cd live-ai-assistant

2. Install dependencies

pip install -r requirements.txt

3. Create .env file

GROQ_API_KEY=your_groq_key_here
TAVILY_API_KEY=your_tavily_key_here

Get keys from:

• Groq → https://console.groq.com
• Tavily → https://app.tavily.com

4. Run the app

streamlit run app.py

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🔑 API Keys Required

• Groq — Free at https://console.groq.com
• Tavily — Free tier (1000 calls/month) at https://app.tavily.com

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💡 This vs RAG

My RAG Project	This Project
PDF → chunks → Vector DB	Web search → live results
Static data	Real-time data
Retriever fetches chunks	Tavily fetches live pages
LLM answers from docs	LLM answers from web

Same LangChain chain concept — different data source!

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👨‍💻 Built By

Vivek — 2nd year CS student passionate about AI/ML

• GitHub: @vivek41-glitch