openai-python

openai-python

默认10分钟超时，错误会重试2次，支持文件上传,并提供由 HTTPX 提供支持的同步和异步客户端。

文档：https://platform.openai.com/docs

Usage

hello world:

pip install openai
pip install python-dotenv

from openai import OpenAI

client = OpenAI()  # 自动从.env 获取 apikey

chat_completion = client.chat.completions.create(
    messages=[
        {
            "role": "user",
            "content": "Say this is a test",
        }
    ],
    model="gpt-3.5-turbo",
)

异步：

import asyncio
from openai import AsyncOpenAI, APIStatusError, AsyncStream
from openai.types.chat import (
    ChatCompletionChunk,
)
client = AsyncOpenAI()

async def main() -> None:
    chat_completion = await client.chat.completions.create(
        messages=[
            {
                "role": "user",
                "content": "Say this is a test",
            }
        ],
        model="gpt-3.5-turbo",
    )


asyncio.run(main())

流输出

from openai import OpenAI

client = OpenAI()

stream = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "Say this is a test"}],
    stream=True,
)
for part in stream:
    print(part.choices[0].delta.content or "")

在 notebook 中这样写比较好(notebook 不方便写.env等web应用)：

openai.api_key = '...'

# all client options can be configured just like the `OpenAI` instantiation counterpart
openai.base_url = "https://..."
openai.default_headers = {"x-foo": "true"}

completion = openai.chat.completions.create(
    model="gpt-4",
    messages=[
        {
            "role": "user",
            "content": "How do I output all files in a directory using Python?",
        },
    ],
)
print(completion.choices[0].message.content)

文件上传

from pathlib import Path
from openai import OpenAI

client = OpenAI()

client.files.create(
    file=Path("input.jsonl"),
    purpose="fine-tune",
)

支持调用 AzureOpenAI，公用相同接口

from openai import AzureOpenAI

# gets the API Key from environment variable AZURE_OPENAI_API_KEY
client = AzureOpenAI(
    api_version="2023-07-01-preview"
    azure_endpoint="https://example-endpoint.openai.azure.com",
)

completion = client.chat.completions.create(
    model="deployment-name",  # e.g. gpt-35-instant
    messages=[
        {
            "role": "user",
            "content": "How do I output all files in a directory using Python?",
        },
    ],
)
print(completion.model_dump_json(indent=2))