openAI API简易使用教程
准备
- 创建openAI 账号(https://platform.openai.com/overview),右上角personal,创建API key。
2. 安装包
pip install openaipip install --upgrade tiktoken
tiktoken 是用来计算每次查询时的token数,因为openAI是根据token数计费,不是必须安装。
API调用
api key 可以直接明文写在代码中,也可以通过环境变量方式获取
import osimport openai# OPENAI_API_KEY是自己设定的环境变量名openai.api_key = os.getenv("OPENAI_API_KEY")# 明文openai.api_key = *************
openAI提供了几种不同场景的模型,主要有text completion、code completion、chat completion、image completion,例如chat completion,则调用方式为
openai.ChatCompletion.create( model="gpt-3.5-turbo", messages=[ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "Who won the world series in 2020?"}, {"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."}, {"role": "user", "content": "Where was it played?"} ])
其中
model 是具体的模型,gpt-3.5-turbo是openAI最先进的语言模型,当然也可以用其他模型。
role,三种固定值,
system:类似一种前提,表示后续的对话以此情景为基础;
user:提问者;
assistant:当对话需要结合上下文时,通过它让模型知道之前的对话内容。
content是具体的对话内容
发起一次请求到响应会存在几秒钟的延迟,response 格式如下所示
{ 'id': 'chatcmpl-6p9XYPYSTTRi0xEviKjjilqrWU2Ve', 'object': 'chat.completion', 'created': 1677649420, 'model': 'gpt-3.5-turbo', 'usage': {'prompt_tokens': 56, 'completion_tokens': 31, 'total_tokens': 87}, 'choices': [ { 'message': { 'role': 'assistant', 'content': 'The 2020 World Series was played in Arlington, Texas at the Globe Life Field, which was the new home stadium for the Texas Rangers.'}, 'finish_reason': 'stop', 'index': 0 } ]}
提取回复内容response['choices'][0]['message']['content']
每次response中不同finish-reason值代表不同状态:
- stop:API返回完整内容
- length:由于max_token限制,回答不完整。
- content_filter:回复被过滤
- null:API还在思考答案
计算token数量
openAI的gpt-3.5-turbo-0301模型token最多4096,超过限制只能缩短请求内容。
而且请求的token和回复的token数会被加一起计费,例如说输入了10个token,openAI回复了20个token,那么最终收费是按照30个token进行收费。
import tiktokenencoding = tiktoken.encoding_for_model("gpt-3.5-turbo")def num_tokens_from_string(string: str, encoding_name: str) -> int: """Returns the number of tokens in a text string.""" encoding = tiktoken.get_encoding(encoding_name) num_tokens = len(encoding.encode(string)) return num_tokensnum_tokens_from_string("tiktoken is great!", "cl100k_base")
how to count tokens with tiktoken
示例
- 中文请求
# 中文Reponse = openai.ChatCompletion.create( model="gpt-3.5-turbo", messages=[ {"role": "user", "content": "上海在哪里"}, ])
回复
{ "choices": [ { "finish_reason": "stop", "index": 0, "message": { "content": "\n\n\u4e0a\u6d77\u4f4d\u4e8e\u4e2d\u56fd\u4e1c\u90e8\u6cbf\u6d77\u5730\u5e26\uff0c\u6bd7\u90bb\u6c5f\u82cf\u548c\u6d59\u6c5f\u4e24\u7701\uff0c\u5904\u4e8e\u957f\u6c5f\u53e3\u548c\u676d\u5dde\u6e7e\u4e4b\u95f4\uff0c\u5730\u7406\u5750\u6807\u4e3a31.23\u00b0N, 121.47\u00b0E\u3002", "role": "assistant" } } ], "created": 1678794854, "id": "chatcmpl-6txWIqBPu6GIbaN7fwnosvKzfkLEE", "model": "gpt-3.5-turbo-0301", "object": "chat.completion", "usage": { "completion_tokens": 63, "prompt_tokens": 13, "total_tokens": 76 }}
- 翻译
reponse = openai.ChatCompletion.create( model="gpt-3.5-turbo", messages=[ {"role": "system", "content": "You are a helpful assistant that translates English to French."}, {"role": "user", "content": 'Translate the following English text to French: "{text}"'}])
回复
{ "choices": [ { "finish_reason": "stop", "index": 0, "message": { "content": "Je suis d\u00e9sol\u00e9, je ne peux pas traduire cette demande car il n'y a pas de texte fourni entre les accolades. Veuillez ajouter du texte \u00e0 traduire.", "role": "assistant" } } ], "created": 1678798886, "id": "chatcmpl-6tyZKMOnfUUeRIszSmgovSKvzsNfA", "model": "gpt-3.5-turbo-0301", "object": "chat.completion", "usage": { "completion_tokens": 41, "prompt_tokens": 34, "total_tokens": 75 }}
也可以不加system
reponse = openai.ChatCompletion.create( model="gpt-3.5-turbo", messages=[ {"role": "user", "content": 'Translate the following English text to French: "{text}"'}])
回复:
{ "choices": [ { "finish_reason": "stop", "index": 0, "message": { "content": "\n\n\"{text}\" is already in English and does not need to be translated.", "role": "assistant" } } ], "created": 1678799017, "id": "chatcmpl-6tybRxkYc92IE1mXELPuWnw2OFmgE", "model": "gpt-3.5-turbo-0301", "object": "chat.completion", "usage": { "completion_tokens": 17, "prompt_tokens": 18, "total_tokens": 35 }}
来源地址:https://blog.csdn.net/yaogepila/article/details/129539084
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