OpenAI Flask Starter

This project demonstrates how to create a simple AI chatbot using Python, Flask, and OpenAI's Large Language Model (LLM) API. The chatbot generates human-like responses powered by GPT-4 (or GPT-3.5).

Features

• Chatbot: Conversational AI powered by OpenAI's GPT models.
• Web Interface: Built using Flask to interact with the bot via a browser.
• OpenAI Integration: Utilizes the latest OpenAI API for chat completions.
• Docker Support: Ready for containerization with a Dockerfile and docker-compose setup.
• Easy Setup: Uses Python's built-in virtual environment.

Prerequisites

• Python 3.7+
• OpenAI API key. You can get it here.

Installation

1. Clone the Repository:

   git clone https://github.com/datumbrain/openai-flask-starter.git
   cd openai-flask-starter

2. Set Up Virtual Environment:

   Create a virtual environment and activate it:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install Dependencies:

   Install the required packages using requirements.txt:

   pip install -r requirements.txt

4. Set Up Your OpenAI API Key:

   Add your OpenAI API key in .env.sample and rename the file to .env:

   OPENAI_API_KEY=your-api-key-here
   HTTP_PORT=5899    # change it as you like

5. Run the Flask Application:

   Start the Flask app by running:

   python main.py

   The app will be available at http://127.0.0.1:5899/.

Docker Setup (Optional)

You can run the project in a Docker container using the following steps:

1. Build the Docker Image:

   docker-compose build

2. Run the Application:

   docker-compose up

   The app will be available at http://127.0.0.1:5899/.

Project Structure

.
├── .dockerignore           # Files to ignore in Docker context
├── .env.sample             # Environment variable example file
├── .gitignore              # Files to ignore in git
├── Dockerfile              # Docker image setup
├── LICENSE                 # License information
├── README.md               # Project documentation
├── docker-compose.yml      # Docker Compose configuration
├── main.py                 # Flask server and chatbot logic
├── requirements.txt        # Project dependencies
└── templates/
    ├── index.html          # Frontend HTML for interacting with the chatbot
    └── styles/
        └── custom.css      # custom CSS styling

Usage

Once the app is running, open your browser and go to http://127.0.0.1:5899/. Type a message in the input box, and the chatbot will respond using the GPT-4 model.

License

This project is licensed under the MIT License.