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https://github.com/prem07a/automl

A Streamlit app for automated data cleaning, feature selection, and model training. Easily manage machine learning tasks with a user-friendly interface.
https://github.com/prem07a/automl

automation llm machine-learning openai

Last synced: 23 days ago
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A Streamlit app for automated data cleaning, feature selection, and model training. Easily manage machine learning tasks with a user-friendly interface.

Host: GitHub
URL: https://github.com/prem07a/automl
Owner: Prem07a
License: mit
Created: 2024-07-27T02:18:27.000Z (5 months ago)
Default Branch: main
Last Pushed: 2024-07-27T13:56:28.000Z (5 months ago)
Last Synced: 2024-07-28T15:08:11.672Z (5 months ago)
Topics: automation, llm, machine-learning, openai
Language: Python
Homepage:
Size: 1.16 MB
Stars: 0
Watchers: 2
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

## 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:

```env
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:

```txt
# 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:

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

#### **2. Create and Activate a Virtual Environment**

For macOS and Linux:

```bash
python3 -m venv venv
source venv/bin/activate
```

For Windows:

```bash
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`:

```bash
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:

```bash
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](images/HomePage.png)

#### **Home Page 2**

![Home Page 2](images/HomePage2.png)

#### **AutoML Page**

![AutoML](images/Automl.png)

#### **Transform Page**

![Transform](images/transform.png)

#### **Explore Page**

![Explore](images/explore.png)

#### **Open Project Page**

![Open Project](images/openProject.png)

## License

This project is licensed under the MIT License - see the [LICENSE](./LICENSE) file for details.