CSV Data Analyst with Groq AI

A Streamlit web application that allows users to upload CSV files and ask natural language questions about their data using Groq's AI models.

Features

• CSV File Upload: Easy drag-and-drop CSV file uploading
• Data Preview: Automatically displays the first few rows of uploaded data
• Natural Language Queries: Ask questions about your data in plain English
• AI-Powered Analysis: Uses Groq's LLaMA 3 70B model for intelligent data analysis
• Interactive Interface: Clean, user-friendly Streamlit interface

Prerequisites

• Python 3.7 or higher
• Groq API key (sign up at Groq Console)

Installation

1. Clone or download the repository

   git clone <your-repo-url>
   cd csv-data-analyst

2. Install required dependencies

   pip install streamlit pandas langchain-groq python-dotenv

3. Set up environment variables

   Create a .env file in the project root directory:

   GROQ_API_KEY=your_groq_api_key_here
   

   Replace your_groq_api_key_here with your actual Groq API key.

Usage

1. Start the application

   streamlit run app.py

2. Upload your CSV file

   • Click on "Browse files" or drag and drop your CSV file
   • The app will automatically load and display a preview of your data

3. Ask questions about your data

   • Type your question in the text input field
   • Examples of questions you can ask:
     • "What is the average value in the price column?"
     • "How many rows contain missing values?"
     • "What are the top 5 categories by count?"
     • "Show me summary statistics for all numerical columns"
     • "What trends do you see in the data?"

4. View AI-generated insights

   • The AI will analyze your entire dataset and provide detailed answers
   • Results are displayed in an easy-to-read format

Supported File Types

• CSV files (.csv)
• Files should be properly formatted with headers in the first row

Environment Variables

Variable	Description	Required
GROQ_API_KEY	Your Groq API key for accessing the AI model	Yes

Dependencies

• streamlit: Web application framework
• pandas: Data manipulation and analysis
• langchain-groq: Integration with Groq AI models
• python-dotenv: Environment variable management

Model Information

This application uses the LLaMA 3 70B model from Groq, which provides:

• High-quality natural language understanding
• Efficient processing of structured data
• Detailed analytical responses

Limitations

• Large CSV files may take longer to process
• The entire dataset is sent to the AI model for analysis
• API rate limits may apply based on your Groq plan

Troubleshooting

Common Issues

"API key not found" error

• Ensure your .env file is in the correct directory
• Verify your Groq API key is valid and properly formatted

File upload issues

• Check that your file is a valid CSV format
• Ensure the file size is within reasonable limits
• Verify the CSV has proper headers

Slow responses

• Large datasets may take time to process
• Consider using smaller sample datasets for testing

Security Notes

• Never commit your .env file to version control
• Keep your API keys secure and don't share them publicly
• The application sends your data to Groq's servers for processing

Example Questions to Try

Once you've uploaded your CSV, try asking these types of questions:

• Statistical Analysis: "What are the mean, median, and mode of the sales column?"
• Data Quality: "Are there any missing values in the dataset?"
• Trends: "What patterns do you notice in the data over time?"
• Comparisons: "Compare the performance between different categories"
• Summaries: "Give me a summary of the key insights from this data"