python如何调用GPT系列的api接口，实现想要的功能

目录

问题描述：

问题解决：

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问题描述：

随着各种LLMs (Large Language Models）的出现，如何调用各种LLMs的api成为了经常会遇见的问题。

问题解决：

下面仅以生成给定sentence的复述句为例，说明如何应用。

data: 存放在.txt文件中，按行存放，每一行是一个句子

⚠️： 只能在本地运行，不可以在服务器上运行，并且，🪜要打开。

代码实现：

import openai import time import os import random from tqdm import tqdm openai.api_key = "YOUR API KEY" # GPT4.0 openai.api_base = ' api.ngapi.top/v1' def get_response(prompt, temperature=0.5, max_tokens=2048): completion = openai.ChatCompletion.create( # model="gpt-3.5-turbo", model="gpt-4", temperature=0, top_p=0, # max_tokens=max_tokens, messages=[ {"role": "user", "content": f"{prompt}"} ] ) return completion def generate_prompt(all_sentences): # all_asps是一个list prompts = [] for cur_sent in all_sentences: # all_compared_pair是一个list:[asp,sub,obj] # prompt = "Please generate just one synonymous sentence for the given sentence. The current given sentence is : '{}'".format(cur_sent) prompt = f"Generate a paraphrased version of the following sentence: {cur_sent}" prompts.append(prompt) return prompts import re def process_sentence(sentence): # 定义要添加空格的特殊字符, 比如’s special_chars = [',', '.', '\'', '’', '“', '”', '(', ')', '[', ']', '{', '}', ':', ';', '?', '!'] # '-'， 因为sub,obj中存在很多以'-'为连字符的sub,obj，所以原始句子中，这部分不可以加空格 # 在特殊字符前添加空格 for char in special_chars: if char == '(': # 特别的，左括号是在后面加空格 sentence = sentence = re.sub(rf'([{char}])', r'\1 ', sentence) else: sentence = re.sub(rf'([{char}])', r' \1', sentence) return sentence def get_res(all_sentences, wirte_path): if os.path.exists(wirte_path): res_file = open(wirte_path) begin = len(res_file.readlines()) + 1 # 断点续传 res_file.close() else: begin = 0 with open(wirte_path, 'a', buffering=1) as res_file: count = 0 for p in tqdm(generate_prompt(all_sentences), total=len(all_sentences)): print(p) count += 1 if count < begin: continue try: res = get_response(p)['choices'][0]['message']['content'] # print("res", res) processed_res = process_sentence(res) # 处理成以单词，标点符号等为分隔符，空格 # print("processed_res", processed_res) if "The server is overloaded or not ready yet" in processed_res: time.sleep(30) res_file.write("####" + '\n') else: res_file.write(processed_res + '\n') except Exception as e: if isinstance(e, openai.error.RateLimitError): time.sleep(30) # 处理拥挤的函数，就只是睡着而已 res = get_response(p)['choices'][0]['message']['content'] processed_res = process_sentence(res) # res_file.write(processed_res + '\n') else: print(e) exit(-1) # print("the number of prompt is :", count) from pdb import set_trace as stop dataset_list = ['14lap','14res', '15res', '16res'] name_list = ['train', 'test', 'dev'] # name_list = ['dev'] # dataset_list = ['14lap'] for dataset in dataset_list: for name in name_list: # print("dataste", dataset) # print("name", name) sentence_path = f"/Users/qtxu/Workplace/Chatgpt/ATE_Task/{dataset}/{name}_sentence.txt" write_path = f'/Users/qtxu/Workplace/Chatgpt/ATE_Task/{dataset}/{name}_paraphrase_sentence.txt' with open(sentence_path,"r") as fr: lines = fr.readlines() all_sentences = [] for line in lines: all_sentences.append(line) # print("all_sentences", all_sentences) get_res(all_sentences, write_path)