Breakout_LLM_assesement

Project Overview

This Flask-based web application enables intelligent data filtering using natural language prompts. By leveraging AI (Groq API), users can easily analyze CSV files through intuitive, conversational filtering.

Features

• CSV file upload
• AI-powered natural language data filtering
• Interactive column selection
• Real-time data visualization
• CSV download functionality

Prerequisites

• Python 3.8+
• Groq API Key

Installation Steps

1. Clone the Repository

git clone https://github.com/nikhilyadav09/Breakout_LLM_assesement.git
cd your-project-directory

2. Create Virtual Environment

python3 -m venv venv
source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

3. Install Dependencies

pip install -r requirements.txt

4. Set Up Groq API Key

1. Create a .env file in project root
2. Add your Groq API key:

GROQ_API_KEY=your_groq_api_key_here

5. Run the Application

python app.py

Usage Guide

1. Upload a CSV file
2. Select a column
3. Enter a natural language prompt like:
   • "Show rows where price is greater than 100"
   • "Find entries with rating less than 3"
4. View filtered results
5. Download filtered data as CSV

Example Prompts

• "Show me rows where time_spent is more than 20"
• "Filter data with rating equal to 4"
• "Select entries where price is less than 50"

Error Handling

• Supports various comparison operators
• Provides clear error messages
• Handles type conversion automatically

Technology Stack

• Flask
• Pandas
• Groq AI
• Python

Troubleshooting

• Ensure CSV has numeric columns
• Use clear, simple language in prompts
• Check internet connection for AI processing

This is the video Link attached for my AI submission

https://drive.google.com/file/d/1A8i8pF5Vwgss7yCCoIZJl6HJ30ALQkOx/view?usp=sharing