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https://github.com/datumbrain/openai-flask-starter
Starter project with OpenAI + Flask and template HTML.
https://github.com/datumbrain/openai-flask-starter
chatbot conversational-agent conversational-agents conversational-bot conversational-bots flask gpt openai python
Last synced: 29 days ago
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Starter project with OpenAI + Flask and template HTML.
- Host: GitHub
- URL: https://github.com/datumbrain/openai-flask-starter
- Owner: datumbrain
- License: mit
- Created: 2024-09-12T10:35:10.000Z (2 months ago)
- Default Branch: main
- Last Pushed: 2024-09-13T19:09:47.000Z (2 months ago)
- Last Synced: 2024-10-01T10:22:48.878Z (about 1 month ago)
- Topics: chatbot, conversational-agent, conversational-agents, conversational-bot, conversational-bots, flask, gpt, openai, python
- Language: HTML
- Homepage:
- Size: 391 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 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](https://beta.openai.com/signup/).
## Installation
1. **Clone the Repository**:
```bash
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:
```bash
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
```
3. **Install Dependencies**:
Install the required packages using `requirements.txt`:
```bash
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`:
```bash
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:
```bash
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**:
```bash
docker-compose build
```
2. **Run the Application**:
```bash
docker-compose up
```
The app will be available at `http://127.0.0.1:5899/`.
## Project Structure
```raw
.
├── .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.