pip install openai

from openai import OpenAI

client = OpenAI()  # Uses OPENAI_API_KEY env var

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)

npm install openai

import OpenAI from "openai";

const client = new OpenAI();  // Uses OPENAI_API_KEY env var

const response = await client.chat.completions.create({
  model: "gpt-4o",
  messages: [{ role: "user", content: "Hello!" }],
});
console.log(response.choices[0].message.content);

export OPENAI_API_KEY="sk-..."
export OPENAI_ORG_ID="org-..."      # Optional
export OPENAI_PROJECT_ID="proj-..." # Optional

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hi"}]
)

stream = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hi"}],
    stream=True
)
for chunk in stream:
    print(chunk.choices[0].delta.content or "", end="")

response = client.embeddings.create(
    model="text-embedding-3-small",
    input="Hello world"
)
vector = response.data[0].embedding

response = client.images.generate(
    model="dall-e-3",
    prompt="A sunset over mountains",
    size="1024x1024"
)
url = response.data[0].url

with open("audio.mp3", "rb") as f:
    transcript = client.audio.transcriptions.create(
        model="whisper-1",
        file=f
    )
print(transcript.text)

from openai import OpenAI, APIError, RateLimitError

client = OpenAI()

try:
    response = client.chat.completions.create(...)
except RateLimitError:
    # Retry with backoff
except APIError as e:
    print(f"API error: {e.status_code}")