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- # -*- coding:utf-8 -*-
- import json
- import time
- from typing import Dict, Any, Union
- import requests
- from pydantic import ValidationError
- from gpt.gpt_check import Article, Annotation
- from tools.loglog import logger, simple_logger, log_err_e, temp_logger
- from tools.new_mysql import MySQLUploader
- m = MySQLUploader()
- def get_openai_model(model_text: str):
- """模糊获得模型名"""
- if "3.5" in model_text or "3.5-turbo" in model_text or "3.5turbo" in model_text:
- model = "gpt-3.5-turbo"
- elif "4o" in model_text or "gpt4o" in model_text:
- model = "gpt-4o"
- elif "4turbo" in model_text or "4-turbo" in model_text:
- model = "gpt-4-turbo"
- else:
- model = "gpt-4o"
- return model
- def insert_ip_token(ip, demo_name, gpt_content, prompt_tokens, completion_tokens, total_tokens):
- sql = "insert into consumer_token (ip,demo_name,gpt_content,prompt_tokens,completion_tokens,total_tokens) values (%s,%s,%s,%s,%s,%s)"
- m.execute_(sql, (ip, demo_name, str(gpt_content), prompt_tokens, completion_tokens, total_tokens))
- def get_answer_from_gpt(question, real_ip="localhost", demo_name="无", model="gpt-4o", max_tokens=3500, temperature: float = 0,
- json_resp: Union[Dict[Any, Any], bool] = False, n=1, check_fucn=None, sys_prompt=None):
- model = get_openai_model(model)
- d2 = {"model": model, "messages": [], "max_tokens": max_tokens, "temperature": temperature, 'n': n}
- if sys_prompt:
- d2['messages'].append({"role": "system", "content": sys_prompt})
- d2['messages'].append({"role": "user", "content": question})
- if json_resp is True:
- d2["response_format"] = {"type": "json_object"}
- elif json_resp is False:
- pass
- else:
- d2["response_format"] = json_resp
- for num_count in range(3):
- try:
- response = requests.post(f'http://170.106.108.95/v1/chat/completions', json=d2)
- r_json = response.json()
- if r2 := r_json.get("choices", None):
- if n > 1:
- gpt_res = []
- for i in r2:
- gpt_res.append(i["message"]["content"])
- else:
- gpt_res = r2[0]["message"]["content"]
- gpt_content = str(gpt_res)
- prompt_tokens = r_json["usage"]["prompt_tokens"]
- completion_tokens = r_json["usage"]["completion_tokens"]
- total_tokens = r_json["usage"]["total_tokens"]
- insert_ip_token(real_ip, demo_name, gpt_content, prompt_tokens, completion_tokens, total_tokens)
- simple_logger.info(f"问题日志:\n{question}\n回答日志:\n{gpt_res}")
- if not check_fucn:
- return gpt_res
- check_result = check_fucn(str(gpt_res))
- if check_result:
- return gpt_res
- else:
- raise Exception(f"第{num_count + 1}次共3次,GPT的校验没有通过,校验函数:{check_fucn.__name__}")
- elif r_json.get("message") == "IP address blocked":
- print("IP address blocked")
- raise Exception("IP address blocked")
- else:
- print(f"小错误:{question[:10]}")
- logger.error(response.text)
- except Exception as e:
- logger.info(f"小报错忽略{e}")
- time.sleep(10)
- logger.critical("get_answer_from_gpt 严重错误,3次后都失败了")
- def get_article_gpt_pydantic(question, real_ip="localhost", demo_name="无", model="gpt-4.1", max_tokens=3500, temperature: float = 0, n=1,
- check_fucn=None, sys_prompt=None, task_id=0, exercise_id=0):
- """
- 异步获取文章
- :param question: 问题
- :param real_ip: 真实IP
- :param demo_name: 项目名称
- :param model: 模型名称
- :param max_tokens: 最大token数
- :param temperature: 温度
- :param n: 生成数量
- :param check_fucn: 校验函数
- :param sys_prompt: 系统提示
- :param task_id: 任务id
- :param exercise_id: 学案id
- :return: 文章内容
- """
- d2 = {"model": model, "messages": [], "max_tokens": max_tokens, "temperature": temperature, "n": n,
- "response_format": {'type': 'json_schema', 'json_schema': {'name': 'Article', 'schema': {'$defs': {'Candidate': {
- 'properties': {'label': {'allOf': [{'$ref': '#/$defs/Options'}], 'description': 'ABCD序号的一种', 'title': '序号'},
- 'text': {'description': '英文,ABCD选项的文本', 'title': '选项文本', 'type': 'string'},
- 'isRight': {'allOf': [{'$ref': '#/$defs/IsRight'}], 'description': '1是正确,0是错误', 'title': '是否是正确答案'}},
- 'required': ['label', 'text', 'isRight'], 'title': 'Candidate', 'type': 'object'}, 'DifficultSentence': {
- 'properties': {'english': {'description': '文章中的一句难句', 'title': '英语难句', 'type': 'string'},
- 'chinese': {'description': '对英语难句的翻译', 'title': '中文难句', 'type': 'string'}}, 'required': ['english', 'chinese'],
- 'title': 'DifficultSentence', 'type': 'object'}, 'IsRight': {'enum': [1, 0], 'title': 'IsRight', 'type': 'integer'},
- 'Options': {'enum': ['A', 'B', 'C', 'D'],
- 'title': 'Options',
- 'type': 'string'},
- 'Question': {'properties': {'trunk': {
- 'description': '用英语给出的选择题题目',
- 'title': '选择题题目', 'type': 'string'},
- 'analysis': {
- 'description': '中文,选择题的分析思路;不要给出答案的ABCD序号',
- 'title': '选择题分析',
- 'type': 'string'},
- 'candidates': {
- 'description': '一共4个选择题',
- 'items': {
- '$ref': '#/$defs/Candidate'},
- 'title': '选项对象',
- 'type': 'array'}},
- 'required': ['trunk',
- 'analysis',
- 'candidates'],
- 'title': 'Question',
- 'type': 'object'}},
- 'properties': {'difficultSentences': {
- 'description': '挑选一句难句对象',
- 'items': {'$ref': '#/$defs/DifficultSentence'},
- 'title': '难句对象', 'type': 'array'},
- 'usedMeanIds': {
- 'items': {'type': 'integer'},
- 'title': '用到的词义id',
- 'type': 'array'}, 'questions': {
- 'description': '针对英语文章的选择题',
- 'items': {'$ref': '#/$defs/Question'},
- 'title': '问题对象', 'type': 'array'},
- 'englishArticle': {
- 'description': '',
- 'title': '英语文章',
- 'type': 'string'},
- 'chineseArticle': {
- 'description': '',
- 'title': '中文翻译',
- 'type': 'string'}},
- 'required': ['difficultSentences', 'usedMeanIds',
- 'questions', 'englishArticle',
- 'chineseArticle'], 'title': 'Article',
- 'type': 'object'}}}
- }
- if sys_prompt:
- d2['messages'].append({"role": "system", "content": sys_prompt})
- d2['messages'].append({"role": "user", "content": question})
- for num_count in range(3):
- try:
- response = requests.post('http://170.106.108.95/v1/chat/completions', json=d2)
- r_json = response.json()
- for choice in r_json["choices"]:
- Article.model_validate_json(choice["message"]["content"])
- simple_logger.info(f"问题日志task_id:{task_id},exercise_id:{exercise_id}\n回答日志:\n{r_json}")
- return r_json
- except ValidationError as e:
- logger.error(f"gpt回复校验失败task_id:{task_id},exercise_id:{exercise_id}:")
- except requests.exceptions.RequestException as e:
- logger.error(f"HTTP请求错误task_id:{task_id},exercise_id:{exercise_id}: {str(e)}")
- time.sleep(1)
- except json.decoder.JSONDecodeError as e:
- if 'response' in locals() and response is not None:
- logger.error(f"json格式化错误task_id:{task_id},exercise_id:{exercise_id}:{response.text}")
- except Exception as e:
- log_err_e(e, f"其他错误task_id:{task_id},exercise_id:{exercise_id}")
- def get_annotation_gpt_pydantic(question, real_ip="localhost", demo_name="无", model="gpt-4.1", max_tokens=3500, temperature: float = 0, n=1,
- check_fucn=None, sys_prompt=None, task_id=0, exercise_id=0):
- """
- 异步获取文章
- :param question: 问题
- :param real_ip: 真实IP
- :param demo_name: 项目名称
- :param model: 模型名称
- :param max_tokens: 最大token数
- :param temperature: 温度
- :param n: 生成数量
- :param check_fucn: 校验函数
- :param sys_prompt: 系统提示
- :param task_id: 任务id
- :param exercise_id: 学案id
- :return: 标注内容
- """
- d2 = {"model": model, "messages": [], "max_tokens": max_tokens, "temperature": temperature, "n": n,
- "response_format": {'type': 'json_schema', 'json_schema': {'name': 'Annotation', 'schema': {'properties': {
- 'annotation_text': {'description': '对句子或文章的每个单词进行词义id的标注', 'examples': ['an[33] apple[123]'], 'title': '标注文本', 'type': 'string'}},
- 'required': ['annotation_text'],
- 'title': 'Annotation', 'type': 'object'}}}
- }
- if sys_prompt:
- d2['messages'].append({"role": "system", "content": sys_prompt})
- d2['messages'].append({"role": "user", "content": question})
- for num_count in range(3):
- try:
- response = requests.post('http://170.106.108.95/v1/chat/completions', json=d2)
- r_json = response.json()
- for choice in r_json["choices"]:
- Annotation.model_validate_json(choice["message"]["content"])
- temp_logger.info(f"日志task_id:{task_id},exercise_id:{exercise_id}:\n问题日志:\n{question}")
- simple_logger.info(f"日志task_id:{task_id},exercise_id:{exercise_id}:\n回答日志:\n{r_json}")
- return r_json
- except ValidationError as e:
- logger.error(f"gpt回复校验失败task_id:{task_id},exercise_id:{exercise_id}:")
- except requests.exceptions.RequestException as e:
- logger.error(f"HTTP请求错误task_id:{task_id},exercise_id:{exercise_id}: {str(e)}")
- time.sleep(1)
- except json.decoder.JSONDecodeError as e:
- if 'response' in locals() and response is not None:
- logger.error(f"json格式化错误task_id:{task_id},exercise_id:{exercise_id}:{response.text}")
- except Exception as e:
- log_err_e(e, f"其他错误task_id:{task_id},exercise_id:{exercise_id}")
- def parse_gpt_phon_to_tuplelist(text: str) -> list:
- """解析gpt返回的音标数据"""
- result = []
- if not text:
- return []
- for i in text.split("\n"):
- ii = i.split("***")
- if len(ii) >= 3:
- result.append((ii[0].strip(), ii[1].strip(), ii[2].strip()))
- return result
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