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openAI API简易使用教程

准备

  1. 创建openAI 账号(https://platform.openai.com/overview),右上角personal,创建API key。

在这里插入图片描述
2. 安装包

pip install openai
pip 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 os
import 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 tiktoken
encoding = tiktoken.encoding_for_model("gpt-3.5-turbo")defnum_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_tokens

num_tokens_from_string("tiktoken is great!","cl100k_base")

how to count tokens with tiktoken

示例

  1. 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}}
  1. 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}}

本文转载自: https://blog.csdn.net/yaogepila/article/details/129539084
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