coslynx/OpenAI-API-Wrapper-Service

• 📍 Overview
• 📦 Features
• 📂 Structure
• 💻 Installation
• 🏗️ Usage
• 🌐 Hosting
• 📄 License
• 👏 Authors

This repository contains a Minimum Viable Product (MVP) for a Python backend service that acts as a user-friendly wrapper for OpenAI's API. It simplifies the process of interacting with OpenAI's powerful language models, allowing developers to easily integrate AI capabilities into their projects.

├── api
│   ├── routes
│   │   ├── openai_routes.py
│   ├── dependencies
│   │   ├── openai_service.py
│   ├── models
│   │   ├── openai_models.py
├── config
│   ├── settings.py
├── utils
│   ├── logger.py
│   └── exceptions.py
├── tests
│   └── unit
│       └── test_openai_service.py
├── main.py
├── requirements.txt
├── .gitignore
├── startup.sh
├── commands.json
├── .env.example
├── .env
└── Dockerfile

• Python 3.9+
• pip
• PostgreSQL (optional)

1. Clone the repository:

   git clone https://.com/coslynx/OpenAI-API-Wrapper-Service.git
   cd OpenAI-API-Wrapper-Service

2. Install dependencies:

   pip install -r requirements.txt

3. Set up the database:

   # If using a database:
   # - Create a PostgreSQL database.
   # - Configure database connection details in the .env file.

4. Configure environment variables:

   cp .env.example .env
   # Fill in the OPENAI_API_KEY with your OpenAI API key.
   # Fill in any database connection details if using a database.

1. Start the server:

   uvicorn main:app --host 0.0.0.0 --port 5000

2. Access the API:

   • API endpoint: http://localhost:5000/openai/generate_response

• config/settings.py: Defines global settings for the application, including API keys, database connections, and debugging options.
• .env: Stores environment-specific variables that should not be committed to the repository (e.g., API keys, database credentials).

1. Generating Text:

Request:

{
  "model": "text-davinci-003",
  "prompt": "Write a short story about a cat who goes on an adventure."
}

Response:

{
  "response": "Once upon a time, in a quaint little cottage nestled amidst a lush garden, there lived a mischievous tabby cat named Whiskers. Whiskers, with his emerald eyes and a coat as sleek as midnight, had an insatiable curiosity for the unknown. One sunny afternoon, as Whiskers was lounging on the windowsill, his gaze fell upon a peculiar object in the garden - a tiny, silver key. Intrigued, he leaped down from his perch and snatched the key in his paws. With a mischievous glint in his eyes, Whiskers knew he had stumbled upon an adventure. "
}

2. Translating Text:

Request:

{
  "model": "gpt-3.5-turbo",
  "prompt": "Translate 'Hello, world!' into Spanish."
}

Response:

{
  "response": "¡Hola, mundo!"
}

3. Summarizing Text:

Request:

{
  "model": "text-davinci-003",
  "prompt": "Summarize the following text: 'The quick brown fox jumps over the lazy dog.'"
}

Response:

{
  "response": "A quick brown fox jumps over a lazy dog."
}

1. Create a virtual environment:

   python3 -m venv env
   source env/bin/activate

2. Install dependencies:

   pip install -r requirements.txt

3. Set environment variables:

   cp .env.example .env
   # Fill in the required environment variables.

4. Start the server:

   uvicorn main:app --host 0.0.0.0 --port 5000

Note: For production deployment, consider using a web server like Gunicorn or Uvicorn with appropriate configurations. You can also use cloud services like Heroku or AWS for easier deployment.

This Minimum Viable Product (MVP) is licensed under the GNU AGPLv3 license.

This MVP was entirely generated using artificial intelligence through CosLynx.com.

No human was directly involved in the coding process of the repository: OpenAI-API-Wrapper-Service

For any questions or concerns regarding this AI-generated MVP, please contact CosLynx at:

• Website: CosLynx.com
• Twitter: @CosLynxAI

Create Your Custom MVP in Minutes With CosLynxAI!