GPT-4 Fine-Tuner

Introduction

This application allows users to create and save fine-tuning data for GPT-4 by providing system prompts alongside user and assistant inputs. It supports a "multi-prompt mode" that allows users to provide multiple sets of user and assistant inputs with optional weights.

Features

Generate fine-tuning data for GPT-4 models.
Multi-prompt mode for advanced fine-tuning scenarios.
Dark mode toggle for improved user experience.

Technologies Used

Python
Flask
HTML
CSS
JavaScript

Prerequisites

Python 3.x
pip (Python package installer)

Installation

Clone the repository:

git clone https://github.com/alextobias78/Fine-Tuner.git
cd Fine-Tuner

Install the required packages:
```
pip install flask
```

Running the Application

Start the Flask server:
```
python app.py
```
Open your browser and navigate to:
```
http://127.0.0.1:5000/
```

Usage

Home Page

Enter the System Prompt in the provided text area.
Add user and assistant inputs by clicking the "Add Prompt" button.
To enable multi-prompt mode, check the Multi-Prompt Mode checkbox.
- When multi-prompt mode is enabled, you can provide weights for each set of inputs.
Click the Submit button to save the entries.

Toggle Dark Mode

Click the moon/sun icon at the top to toggle between light and dark themes.

File Structure

app.py:
- The main Flask application file.
- Routes and logic for handling data submission and rendering the HTML template.
templates/index.html:
- The HTML template for the main interface.
- Contains a form for entering system prompts, user inputs, assistant inputs, and a response area for displaying results.
static/script.js:
- Handles the front-end logic for the form submission.
- Manages the dynamic addition and removal of prompt sets.
- Toggles multi-prompt mode and dark mode.
static/styles.css:
- Contains styling for the application, including form elements and dark mode.

Author

Alex Tobias

License

This project is licensed under the MIT License.

LuciferMornens/Fine-Tuner