AI Backend Wrapper

A Python-based backend service to simplify access to OpenAI's powerful AI capabilities.

Developed with the software and tools below.

📑 Table of Contents

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

📍 Overview

The repository contains the code for the AI Backend Wrapper MVP, a Python-based backend service built with FastAPI, PostgreSQL, and OpenAI API. It simplifies accessing OpenAI's powerful AI capabilities by providing a standardized interface for users to send requests and receive processed responses.

📦 Features

	Feature	Description
⚙️	Architecture	The codebase follows a modular architectural pattern with separate directories for different functionalities, ensuring easier maintenance and scalability.
📄	Documentation	The repository includes a README file that provides a detailed overview of the MVP, its dependencies, and usage instructions.
🔗	Dependencies	The codebase relies on various external libraries and packages such as FastAPI, SQLAlchemy, PyJWT, OpenAI, and other supporting libraries, which are essential for building and handling API requests, interacting with the database, and utilizing OpenAI's services.
🧩	Modularity	The modular structure allows for easier maintenance and reusability of the code, with separate directories and files for different functionalities such as request handling, API calls, and database interactions.
🧪	Testing	Implement unit tests using frameworks like pytest to ensure the reliability and robustness of the codebase.
⚡️	Performance	The performance of the system can be optimized based on factors such as the database configuration, caching strategies, and efficient API calls. Consider implementing performance optimizations for better efficiency.
🔐	Security	Enhance security by implementing measures such as input validation, secure API key management, and data sanitization.
🔀	Version Control	Utilizes Git for version control with a GitHub Actions workflow file for automated build and release processes.
🔌	Integrations	Interacts with OpenAI's API, PostgreSQL database, and utilizes the FastAPI framework to handle HTTP requests.
📶	Scalability	Design the system to handle increased user load and data volume, utilizing caching strategies and database optimizations for better scalability.

📂 Structure

└── api
    └── main.py

💻 Installation

🔧 Prerequisites

• Python 3.9+
• PostgreSQL 13+
• Docker (optional)

🚀 Setup Instructions

1. Clone the repository:

   git clone https://github.com/coslynx/AI-Backend-Wrapper.git
   cd AI-Backend-Wrapper

2. Install dependencies:

   pip install -r requirements.txt

3. Set up the database:

   # Create the database
   createdb ai_backend_wrapper
   
   # Set up database user (if needed)
   psql -c "CREATE USER ai_backend_wrapper_user WITH PASSWORD 'your_password';"
   
   # Grant permissions to the user
   psql -c "GRANT ALL PRIVILEGES ON DATABASE ai_backend_wrapper TO ai_backend_wrapper_user;"
   
   # Update .env with the database connection details
   cp .env.example .env

4. Configure environment variables:

   # Update .env file with your OpenAI API key, database credentials, and other settings

🏗️ Usage

🏃‍♂️ Running the MVP

1. Start the backend application:

   uvicorn api.main:app --host 0.0.0.0 --port 8000 --reload

2. Access the API:

   • Use a tool like Postman or curl to send requests to the API endpoints.

🌐 Hosting

🚀 Deployment Instructions

1. Build a Docker image:

   docker build -t ai-backend-wrapper .

2. Push the image to a container registry:

   docker push your-docker-hub-username/ai-backend-wrapper

3. Deploy the image to a container orchestration platform like Kubernetes:

   # (Kubernetes deployment configuration specific to your platform)

🔑 Environment Variables

Provide a comprehensive list of all required environment variables, their purposes, and example values:

• OPENAI_API_KEY: Your OpenAI API key.
• DATABASE_URL: Connection string for the PostgreSQL database. Example: postgresql://user:password@host:port/database
• SECRET_KEY: A secret key for JWT authentication.

📜 API Documentation

🔍 Endpoints

Provide a comprehensive list of all API endpoints, their methods, required parameters, and expected responses. For example:

• POST /generate_text
  • Description: Generate text using a specific OpenAI model.
  • Body:

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

  • Response:

    {
      "text": "The quick brown fox jumps over the lazy dog. It was a beautiful day."
    }

• POST /translate
  • Description: Translate text from one language to another.
  • Body:

    {
      "text": "Hello, world!",
      "source_language": "en",
      "target_language": "fr"
    }

  • Response:

    {
      "text": "Bonjour le monde !"
    }

• POST /summarize
  • Description: Summarize a given text.
  • Body:

    {
      "text": "This is a very long and detailed article about the history of artificial intelligence."
    }

  • Response:

    {
      "summary": "This article discusses the development of artificial intelligence from its early beginnings to the present day."
    }

🔒 Authentication

For the MVP, the authentication is not included. However, you can implement JWT authentication for secure access to API endpoints in future iterations.

📜 License & Attribution

📄 License

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

🤖 AI-Generated MVP

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

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

📞 Contact

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

• Website: CosLynx.com
• Twitter: @CosLynxAI

🌐 CosLynx.com

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