openai-quickstart-python

OpenAI API Quickstart - Python

OpenAI API Quickstart - Python is a versatile repository designed to help users explore and experiment with various OpenAI API endpoints such as chat and assistants. The repository provides a comprehensive collection of quickstart applications, making it a valuable resource for developers eager to get hands-on experience with the OpenAI API.

Getting Started with OpenAI API

To dive into the OpenAI API journey, the repository offers a basic code example to initiate your first request using the OpenAI Python SDK, which can be found here. The initial steps involve ensuring that you have the correct dependencies installed, as illustrated in the OpenAI quickstart documentation for Python.

Here's a quick look at how one can interact with the OpenAI API through a simple code snippet:

from openai import OpenAI
client = OpenAI()

completion = client.chat.completions.create(
  model="gpt-3.5-turbo",
  messages=[
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": "Hello!"}
  ]
)

print(completion.choices[0].message)

This code demonstrates how to utilize the GPT-3.5 turbo model for creating chat-style completions, simulating a conversation between a system and a user.

Setting Up the Project

Setting up the OpenAI Quickstart Python project involves several steps, each crucial for the successful running of the applications. Below is a simplified guide:

1. Python Installation: Ensure Python is installed on your machine. If not, you can download it from Python.org.

2. Repository Cloning: Clone the project repository to your local machine using Git. This can be done by visiting the repository page and using the clone option documented here.

3. Navigating the Project Directory: Use the terminal or command prompt to move into the cloned project directory with the command:

   $ cd openai-quickstart-python
   

4. Virtual Environment Creation: Set up a virtual environment to keep dependencies isolated.

   • On macOS, run the following commands:

     $ python -m venv venv
     $ . venv/bin/activate
     

   • On Windows, execute:

     > python -m venv venv
     > .\venv\Scripts\activate
     

5. Dependency Installation: With the virtual environment active, install all necessary packages from the requirements.txt file:

   $ pip install -r requirements.txt
   

6. Environment Variables Setup: Copy the example environment variables file:

   $ cp .env.example .env
   

   Add your OpenAI API key to this newly copied .env file to enable API interactions.

7. Running the Application: The method to run the application depends on the specific application setup. If it's based on Flask (as in the chat-basic example), use:

   $ flask run
   

   You can then access the application in your web browser at http://localhost:5000.

   For simple Python scripts, you can execute:

   $ python my_file.py
   

By following these steps, users can seamlessly set up and run the OpenAI Quickstart Python applications, exploring the power and flexibility of OpenAI's API. This repository, with its examples and instructions, is an excellent resource for developers interested in machine learning and AI-based conversation applications.