Project Documentation

1. Folder Structure

src/
│
├── images/
│   ├── favicon.ico
│   ├── logo.png
│   ├── HomePage.png
│   ├── HomePage2.png
│   ├── Automl.png
│   ├── transform.png
│   ├── explore.png
│   └── openProject.png
│
├── project/
│   └── [Project Name]/
│           ├── data/
│           ├── models/
│           ├── report/
│           └── code/
│
├── src/
│   ├── app.py
│   ├── automl.py
│   ├── explore.py
│   ├── transform.py
│   └── prompt.py
│
├── .env
├── requirements.txt
├── LICENSE
└── README.md

2. .env File

The .env file should be placed in the root of your project directory (src) and contain environment variables used by your application. For example:

OPENAI_API_KEY=your_openai_api_key_here

Replace your_openai_api_key_here with your actual OpenAI API key.

3. requirements.txt

The requirements.txt file lists all Python packages your project depends on. Here’s an example based on your provided code:

# Application
streamlit
llama-index-llms-openai
python-dotenv
pandasai

# Data manipulation
pandas
numpy

# Machine learning
scikit-learn
xgboost
lightgbm
catboost

# Statistics
scipy

# Plotting
matplotlib
seaborn

# For running the code
joblib

4. Running Steps

1. Clone the Git Repository

Start by cloning your Git repository to your local machine:

git clone https://github.com/Prem07a/AutoML.git
cd AutoML

2. Create and Activate a Virtual Environment

For macOS and Linux:

python3 -m venv venv
source venv/bin/activate

For Windows:

python -m venv venv
venv\Scripts\activate

This step creates a virtual environment and activates it to ensure that dependencies are installed in an isolated environment.

3. Install the Required Packages

With the virtual environment activated, install the necessary Python packages listed in requirements.txt:

pip install -r requirements.txt

This command installs all the dependencies required for your project.

Note: If you encounter issues installing pandasai, try using Python 3.11.9

4. Run Your Streamlit App

After setting up the environment and installing dependencies, you can start your Streamlit app. Navigate to the src directory and run:

streamlit run app.py

This command launches the Streamlit server and opens your app in the default web browser.

5. Project Screenshots

Here are some screenshots of the different pages in the application:

Home Page

Home Page 2

AutoML Page

Transform Page

Explore Page

Open Project Page

License

This project is licensed under the MIT License - see the LICENSE file for details.

Copyright (c) 2024 Prem Gaikwad