📊 Chat with Your CSV Data

🚀 Demo

Talk-To-Your-Data.mp4

✨ A live version of the application is hosted on Streamlit! Try it out yourself using the link below:
🌐 Chat with Your CSV on Streamlit

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🧐 Overview

Chat with Your CSV Data is a web application built with Streamlit that enables users to interact with their CSV datasets through natural language queries. By leveraging the power of Large Language Models (LLMs), users can extract insights, visualizations, and analyses from their data without needing to write code!

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🎯 Objective

The main goal of this app is to provide an intuitive and interactive way for users to analyze and visualize their data using conversational AI. It demonstrates how AI can simplify data science and help everyone, regardless of their technical skills, explore data effectively.

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🛠️ Tech Stack

• Streamlit: 🌐 For building the easy-to-use web interface.
• Unify AI: 🤖 Powers the backend LLMs that respond to your queries in real-time.
• Pandas: 🐼 For manipulating and analyzing CSV data.

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⚙️ Application Flow

1. 🔑 Initialization: Enter your Unify AI API key and select a model for interaction.
2. 📂 Data Upload: Upload a CSV file and preview it in the app.
3. 💬 Query Interaction:
   • Ask questions about your data.
   • The LLM responds with insights

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🎨 Motivation

This app showcases how AI can enhance data analysis by making it simple and fun. It empowers users to engage with their data conversationally, making data science more accessible and approachable for everyone.

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🧠 Key Concepts

• Natural Language Processing: Enables the LLMs to understand and respond naturally to your questions.

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📂 Repository and Deployment

🔍 Access the Source Code

The source code for Chat with Your CSV Data is available here.

🌐 Live Application

Access the live app here: Chat with Your CSV on Streamlit

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💻 Running Locally

To run the app locally, follow these steps:

1. 📥 Clone the Repository:

   git clone https://github.com/your-github-repo-link
   cd your-repository-folder

📦 Install Dependencies:

pip install -r requirements.txt

🚀 Launch the Application:

streamlit run app.py

This command will start the Streamlit server, and you’ll see a URL (usually http://localhost:8501) where you can access the app in your browser.

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👥 Contributors

Name	GitHub Profile
Syed Muzakkir Hussain	muzakkirhussain011