调用openai接口 import openaiimport osopenai.api_key = ('申请的key')model_engine_id = "text-davinci-002"prompt = "帮我生成一段话，因为工作的原因，错误过了和女朋友的约会 "completions = openai.Completion.create( engine=model_engine_id, prompt=prompt, max_tokens=60,)message = comple...
# create a chat completion chat_completion = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Listen to your"}]) API的响应存储在chat_completion变量中。打印chat_completion,我们可以看到它类似于一个由6个键值对组成的字典。 {'id': 'chatcmpl-7dk1Jk...
client = OpenAI(api_key=api_key) def recognize_multiple_images(): response = client.chat.completions.create( model="gpt-4-vision-preview", messages=[ { "role": "user", "content": [ { "type": "image_url", "image_url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/G...
Introducing the Realtime API Introducing the Realtime API Introducing the Realtime API ProductOct 1, 2024 Introducing vision to the fine-tuning API ProductOct 1, 2024 Prompt Caching in the API ProductOct 1, 2024 Model Distillation in the API ResearchSep 12, 2024 ResearchSep 12, 2024 Research...
2､使用模型响应调用天气接口的API 这一步会调用服务端的get_current_weather方法，获取对应地区的天气...
我不打算深入介绍模型参数的微调,更多相关内容,请点击这里(https://platform.openai.com/docs/api-reference/chat/create)。 此处,我给这个函数起了个别名:h,为的是简化输入: 很好,下面我们来尝试一点有用的功能。 Data GPT 我发现自己最常使用的一种模式是:提示+数据。
api_key = "在这里输入你的API密钥", api_version = "2023-09-01-preview")deployment_name = "在这里输入你的部署名称"context = [{'role': 'user', 'content': "在这里输入你希望指示AI做的事情,例如上例的小说写作要求"}]response = client.chat.completions.create( model=deployment_name, messages...
openai.Completion.create 接口参数说明 引言:对于接口,不了解参数含义,就不知道它能咋用?而了解参数的含义最好有例子,基于这个认知,整理了OpenAI几个主要API的接口参数说明。 OpenAI的completions接口是一种自然语言处理API,可用于各种文本生成任务,例如: 文本摘要:给定一篇文章,生成一个简短的摘要。
limit misuse by end users. As we gain more experience operating the API in practice, we will continually refine the categories of use we are able to support, both to broaden the range of applications we can support, and to create finer-grained categories for those we have misuse concerns ...
client = OpenAI(api_key=api_key) def recognize_image(): response = client.chat.completions.create( model="gpt-4-vision-preview", messages=[ { "role":"user", "content": [ {"type":"text","text":"这个图片里面有什么"}, { "type":"image_url", ...