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----
-title: AI-Powered EDA Feature Engineering Assistant
-emoji: 📊
-colorFrom: blue
-colorTo: purple
-sdk: streamlit
-sdk_version: "1.30.0"
-app_file: main.py
-pinned: false
----
-
-
-# AI-Powered EDA & Feature Engineering Assistant
-
-![App Banner](https://raw.githubusercontent.com/vashu2425/AI-Powered-EDA-Feature-Engineering-Assistant/main/assets/banner.png)
-
-An interactive application that uses AI to analyze datasets and provide comprehensive exploratory data analysis (EDA) insights and feature engineering recommendations.
-
-## 🌟 Features
-
-- **🤖 AI-Powered Analysis**: Receive detailed EDA insights generated by Mistral-7B
-- **📊 Automated Visualizations**: Generate key visualizations with a single click
-- **🔧 Feature Engineering Recommendations**: Get AI suggestions for improving your data
-- **⚠️ Data Quality Assessment**: Identify issues in your dataset and receive fixing advice 
-- **💬 Chat Interface**: Ask questions about your dataset and get AI-powered answers
-- **🌙 Dark Mode UI**: Sleek, modern dark interface for comfortable analysis
-
-## 📋 Demo
-
-Here's a quick look at what you can do:
-
-1. Upload a CSV dataset
-2. Get automatic visualizations and statistics
-3. Generate AI-powered insights for:
-   - Exploratory Data Analysis
-   - Feature Engineering Recommendations
-   - Data Quality Assessment
-4. Chat with your data to ask specific questions
-
-## 🛠️ Tech Stack
-
-- **Frontend**: Streamlit
-- **Data Processing**: Pandas, NumPy, Matplotlib, Seaborn
-- **AI Integration**: LangChain + Groq API
-- **LLM Model**: Llama3-8b-8192
-
-## 📦 Installation
-
-### Prerequisites
-- Python 3.8+
-- Anaconda or Miniconda (recommended)
-- Groq API key
-
-### Setup
-
-1. Clone the repository:
-```bash
-git clone https://github.com/vashu2425/AI-Powered-EDA-Feature-Engineering-Assistant.git
-cd AI-Powered-EDA-Feature-Engineering-Assistant
-```
-
-2. Create and activate a conda environment:
-```bash
-conda create -n ai_eda_env python=3.10
-conda activate ai_eda_env
-```
-
-3. Install the required packages:
-```bash
-pip install -r requirements.txt
-```
-
-4. Create a `.env` file with your Groq API key:
-```
-GROQ_API_KEY=your_groq_api_key_here
-```
-
-### ⚠️ Compatibility Note
-
-This application requires specific versions of NumPy (1.24.3) and pandas (1.5.3) to avoid binary compatibility issues. The requirements.txt file has been updated with these specific versions to ensure a smooth installation experience.
-
-### 🔧 Troubleshooting
-
-If you encounter the following error:
-```
-ValueError: numpy.dtype size changed, may indicate binary incompatibility. Expected 96 from C header, got 88 from PyObject
-```
-
-Try the following solutions:
-
-1. Make sure you're using the exact versions specified in requirements.txt:
-```bash
-pip install numpy==1.24.3 pandas==1.5.3
-```
-
-2. If you're using Streamlit version older than 1.11.0, you might need to update the code to replace `st.experimental_rerun()` with `st.rerun()`.
-
-3. If you're still having issues, try creating a fresh conda environment with Python 3.10:
-```bash
-conda create -n fresh_ai_eda_env python=3.10
-conda activate fresh_ai_eda_env
-pip install -r requirements.txt
-```
-
-## 🚀 Usage
-
-1. Activate the conda environment:
-```bash
-conda activate ai_eda_env
-```
-
-2. Run the application:
-```bash
-streamlit run main.py
-```
-
-3. Open your web browser and navigate to `http://localhost:8501`
-
-4. Upload a CSV dataset and start exploring!
-
-## 📊 Example Analysis
-
-Here are some examples of insights you can get:
-
-- Comprehensive EDA insights about your dataset variables and distributions
-- Feature engineering ideas specific to your data
-- Data quality improvement recommendations
-- Visualizations including correlation heatmaps, distribution plots, and more
-
-## 🤝 Contributing
-
-Contributions are welcome! Please feel free to submit a Pull Request.
-
-## 📝 License
-
-This project is licensed under the MIT License - see the LICENSE file for details.
-
-## 📬 Contact
-
-For any questions or feedback, please reach out to the repository owner.
-
----
-
-### 🌟 Star this repository if you find it useful!