AI InfoBot

• 

  Created a smart voice assistant using Groq API, Google APIs, Huggingface, and speech-to-text tools.

• 

  Supported multilingual queries, live weather/news integration, and real-time search execution.

Inspiration

Inspiration While exploring AI chatbots, I noticed most lacked the ability to provide up-to-date or real-world information. This inspired me to create a chatbot that not only understands user queries but also fetches real-time data from the internet using Groq and Google Search APIs. The goal was to build a smarter assistant that blends LLM power with live search capabilities.

What it does

What it does:- AI InfoBot is a web-based chatbot that: Understands natural language questions Uses Groq’s LLM for conversational intelligence Retrieves live search results from Google to provide up-to-date responses Displays responses in a clean, user-friendly interface Supports any general knowledge or factual query

How we built it

How we built it Frontend: Built using HTML, CSS, and Bootstrap for responsive design Backend: Powered by Flask to manage user interactions and API calls Groq API: For fast LLM-generated responses Google Search API: To fetch real-time web data Modular Code: chatbot.py, utils.py, and templates for clean separation of logic and views

Challenges we ran into

Challenges we ran into Dealing with API authentication and rate limits Ensuring real-time results are relevant and well-formatted Handling delays in response time due to live search Maintaining a smooth, natural conversation flow with mixed LLM + web data

Accomplishments that we're proud of

Accomplishments that we're proud of Successfully integrated a live search feature into an AI chatbot Built a full-stack project from scratch using Flask Created a clean, working UI and backend logic within a short development window Learned to balance AI-generated text with factual, up-to-date data

What we learned

What we learned How to work with external APIs (Groq, Google Search) Flask app structure and backend/frontend communication Building production-ready chatbot logic Presenting dynamic data in a user-friendly format

What's next for AI InfoBot

What's next for AI InfoBot Add voice input and speech response features Integrate chat history and user personalization Support for multi-language queries Deploy the bot as a browser extension or mobile app Implement contextual memory for better conversations

Built With

• bootstrap
• css
• flask
• git
• google-search-api
• groq
• html
• jinja
• python
• vscode