OpenAI API Tutorial – Integrate GPT and AI Models in Python

Learn how to use the OpenAI API to access GPT and other AI models. This beginner-friendly tutorial covers API setup, text generation, question answering, and integration with Python applications.

1. Introduction

The OpenAI API allows developers to access powerful AI models like GPT for text generation, summarization, translation, and reasoning.

  1. Enables integration of AI models into applications, websites, and workflows.
  2. Supports multiple models including GPT-3, GPT-3.5, GPT-4, and Codex.

2. Setup

  1. Sign up at OpenAI and get your API key.
  2. Install the OpenAI Python library:

pip install openai

3. Basic Usage

3.1 Text Generation


import openai

openai.api_key = "YOUR_API_KEY"

response = openai.Completion.create(
model="text-davinci-003",
prompt="Write a short poem about AI transforming education.",
max_tokens=100
)

print(response.choices[0].text.strip())

3.2 Chat with GPT


from openai import OpenAI

client = OpenAI(api_key="YOUR_API_KEY")

response = client.chat.completions.create(
model="gpt-4",
messages=[
{"role": "user", "content": "Explain the basics of Generative AI in simple terms."}
]
)

print(response.choices[0].message.content)

4. Features

  1. Text Generation: Creative writing, summaries, translations.
  2. Conversational AI: Chatbots and virtual assistants.
  3. Code Generation: Codex model for programming assistance.
  4. Custom Workflows: Fine-tune models for domain-specific tasks.
  5. Embeddings: Semantic search and vector similarity.

5. Best Practices

  1. Keep your API key secure.
  2. Limit token usage to control costs.
  3. Use temperature and max_tokens to adjust creativity and length.
  4. Combine OpenAI API with LangChain, Hugging Face, or LlamaIndex for advanced workflows.
  5. Monitor API usage and logs for optimization and debugging.

6. Outcome

After learning the OpenAI API, beginners will be able to:

  1. Integrate GPT and other AI models into Python applications.
  2. Build text generation, chatbot, and question-answering applications.
  3. Control model output with prompts and parameters.
  4. Combine OpenAI API with frameworks like LangChain and Hugging Face for scalable AI solutions.