majiahui@haimaqingfan.com
2 years ago
14 changed files with 1755 additions and 789 deletions
@ -0,0 +1,803 @@ |
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from flask import Flask, jsonify, Response |
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from flask import request |
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import redis |
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import uuid |
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import json |
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import time |
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import threading |
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from threading import Thread |
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from flask import send_file, send_from_directory |
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import os |
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from flask import make_response |
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import openai |
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import base64 |
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import re |
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import urllib.parse as pa |
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import socket |
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from serve_config_1 import Config |
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import requests |
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config = Config() |
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app = Flask(__name__) |
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app.config["JSON_AS_ASCII"] = False |
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s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) |
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s.connect(("8.8.8.8", 80)) |
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localhostip = s.getsockname()[0] |
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|
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lock = threading.RLock() |
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pool = redis.ConnectionPool(host=config.reids_ip, port=config.reids_port, max_connections=50, db=config.reids_db, password=config.reids_password) |
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redis_ = redis.Redis(connection_pool=pool, decode_responses=True) |
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thanks = "致谢" |
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references = "参考文献" |
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flask_serves_env = "http://{}:{}".format(localhostip,config.flask_port) |
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paper_download_url = flask_serves_env + "/download?filename_path={}/paper.docx" |
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paper_start_download_url = flask_serves_env + "/download?filename_path={}/paper_start.docx" |
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redis_key_name_openaikey_bad_dict = "openaikey_bad_list_{}".format(str(localhostip)) |
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redis_key_name_openaikey_list = "openaikey_list_{}".format(str(localhostip)) |
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redis_title = "redis_title" |
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|
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redis_title_ing = "redis_title_ing" |
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redis_small_task = "redis_small_task" |
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redis_res = "redis_res" |
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for i in config.openaikey_list: |
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redis_.rpush(redis_key_name_openaikey_list, i) |
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redis_.hset(redis_key_name_openaikey_bad_dict, "1", "1") |
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redis_.persist(redis_key_name_openaikey_list) |
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redis_.persist(redis_key_name_openaikey_bad_dict) |
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|
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|
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def request_api_chatgpt(api_key, prompt): |
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OPENAI_API_KEY = api_key |
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url = "https://api.openai.com/v1/chat/completions" |
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headers = { |
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"Content-Type": "application/json", |
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"Authorization": f"Bearer {OPENAI_API_KEY}" |
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} |
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data = { |
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"model": "gpt-3.5-turbo", |
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"messages": [ |
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{"role": "user", "content": prompt}, |
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], |
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"temperature": 0.5 |
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} |
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response = requests.post(url, |
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headers=headers, |
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data=json.dumps(data), |
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timeout=240) |
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return response |
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def chat_kaitibaogao(api_key, uuid, main_parameter,task_type): |
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try: |
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response =request_api_chatgpt(api_key, config.kaitibaogao_prompt.format(main_parameter[0])) |
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res = response.json() |
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kaitibaogao = res["choices"][0]["message"]["content"] |
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redis_.rpush(redis_key_name_openaikey_list, api_key) |
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redis_.persist(redis_key_name_openaikey_list) |
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except: |
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""" |
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发送警报 |
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""" |
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kaitibaogao = "" |
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kaitibaogao_task = { |
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"task_type": task_type, |
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"uuid": uuid, |
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"main_parameter": main_parameter |
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} |
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time.sleep(3) |
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small_task = json.dumps(kaitibaogao_task, ensure_ascii=False) |
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redis_.lpush(redis_small_task, small_task) |
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redis_.rpush(redis_key_name_openaikey_list, api_key) |
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redis_.persist(redis_key_name_openaikey_list) |
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redis_.hset(redis_key_name_openaikey_bad_dict, uuid, str((api_key,task_type))) |
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return |
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lock.acquire() |
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res_dict_str = redis_.hget(redis_res, uuid) |
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res_dict = json.loads(res_dict_str) |
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res_dict["tasking_num"] += 1 |
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print("子任务进度".format(uuid),res_dict["tasking_num"]) |
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res_dict["开题报告"] = kaitibaogao |
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res_dict_str = json.dumps(res_dict, ensure_ascii=False) |
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redis_.hset(redis_res, uuid, res_dict_str) |
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lock.release() |
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def chat_abstract_keyword(api_key, uuid, main_parameter, task_type): |
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try: |
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# 生成中文摘要 |
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response =request_api_chatgpt(api_key, config.chinese_abstract_prompt.format(main_parameter[0])) |
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res = response.json() |
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chinese_abstract = res["choices"][0]["message"]["content"] |
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# 生成英文的摘要 |
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response = request_api_chatgpt(api_key, config.english_abstract_prompt.format(chinese_abstract)) |
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res = response.json() |
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english_abstract = res["choices"][0]["message"]["content"] |
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# 生成中文关键字 |
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response = request_api_chatgpt(api_key, config.chinese_keyword_prompt.format(chinese_abstract)) |
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res = response.json() |
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chinese_keyword = res["choices"][0]["message"]["content"] |
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# 生成英文关键字 |
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response = request_api_chatgpt(api_key, config.english_keyword_prompt.format(chinese_keyword)) |
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res = response.json() |
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english_keyword = res["choices"][0]["message"]["content"] |
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redis_.rpush(redis_key_name_openaikey_list, api_key) |
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redis_.persist(redis_key_name_openaikey_list) |
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except: |
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""" |
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发送警报 |
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""" |
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chinese_abstract = "" |
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english_abstract = "" |
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chinese_keyword = "" |
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english_keyword = "" |
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chat_abstract_task = { |
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"task_type": task_type, |
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"uuid": uuid, |
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"main_parameter": main_parameter |
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} |
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time.sleep(3) |
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small_task = json.dumps(chat_abstract_task, ensure_ascii=False) |
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redis_.lpush(redis_small_task, small_task) |
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redis_.rpush(redis_key_name_openaikey_list, api_key) |
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redis_.persist(redis_key_name_openaikey_list) |
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redis_.hset(redis_key_name_openaikey_bad_dict, uuid, str((api_key,task_type))) |
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return |
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paper_abstract_keyword = { |
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"中文摘要": chinese_abstract, |
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"英文摘要": english_abstract, |
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"中文关键词": chinese_keyword, |
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"英文关键词": english_keyword |
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} |
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# json_str = json.dumps(paper_abstract_keyword, indent=4, ensure_ascii=False) |
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# abstract_keyword_path = os.path.join(uuid_path, "abstract_keyword.json") |
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# with open(abstract_keyword_path, 'w') as json_file: |
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# json_file.write(json_str) |
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# |
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# lock.acquire() |
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# api_key_list.append(api_key) |
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# lock.release() |
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lock.acquire() |
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res_dict_str = redis_.hget(redis_res, uuid) |
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res_dict = json.loads(res_dict_str) |
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res_dict["tasking_num"] += 1 |
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print("子任务进度".format(uuid),res_dict["tasking_num"]) |
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res_dict["中文摘要"] = paper_abstract_keyword["中文摘要"] |
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res_dict["英文摘要"] = paper_abstract_keyword["英文摘要"] |
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res_dict["中文关键词"] = paper_abstract_keyword["中文关键词"] |
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res_dict["英文关键词"] = paper_abstract_keyword["英文关键词"] |
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res_dict_str = json.dumps(res_dict, ensure_ascii=False) |
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redis_.hset(redis_res, uuid, res_dict_str) |
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lock.release() |
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def chat_content(api_key, uuid, main_parameter, task_type): |
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''' |
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:param api_key: |
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:param uuid: |
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:param main_parameter: |
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:return: |
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''' |
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content_index = main_parameter[0] |
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title = main_parameter[1] |
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mulu = main_parameter[2] |
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subtitle = main_parameter[3] |
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prompt = main_parameter[4] |
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if subtitle[:2] == "@@": |
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res_content = subtitle[2:] |
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redis_.rpush(redis_key_name_openaikey_list, api_key) |
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redis_.persist(redis_key_name_openaikey_list) |
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else: |
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try: |
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response = request_api_chatgpt(api_key, prompt.format(title, mulu, subtitle)) |
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res = response.json() |
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res_content = res["choices"][0]["message"]["content"] |
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redis_.rpush(redis_key_name_openaikey_list, api_key) |
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redis_.persist(redis_key_name_openaikey_list) |
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except: |
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""" |
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发送警报 |
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""" |
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res_content = "" |
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paper_content = { |
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"task_type": "paper_content", |
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"uuid": uuid, |
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"main_parameter": main_parameter |
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} |
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time.sleep(3) |
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small_task = json.dumps(paper_content, ensure_ascii=False) |
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redis_.lpush(redis_small_task, small_task) |
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redis_.rpush(redis_key_name_openaikey_list, api_key) |
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redis_.persist(redis_key_name_openaikey_list) |
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redis_.hset(redis_key_name_openaikey_bad_dict, uuid, str((api_key, task_type))) |
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return |
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lock.acquire() |
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res_dict_str = redis_.hget(redis_res, uuid) |
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res_dict = json.loads(res_dict_str) |
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res_dict["tasking_num"] += 1 |
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print("子任务进度".format(uuid), res_dict["tasking_num"]) |
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table_of_contents = res_dict["table_of_contents"] |
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table_of_contents[content_index] = res_content |
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res_dict["table_of_contents"] = table_of_contents |
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res_dict_str = json.dumps(res_dict, ensure_ascii=False) |
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redis_.hset(redis_res, uuid, res_dict_str) |
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lock.release() |
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def chat_thanks(api_key, uuid, main_parameter, task_type): |
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''' |
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:param api_key: |
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:param uuid: |
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:param main_parameter: |
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:return: |
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''' |
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# title, |
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# thank_prompt |
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title = main_parameter[0] |
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prompt = main_parameter[1] |
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try: |
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response = request_api_chatgpt(api_key, prompt.format(title)) |
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res = response.json() |
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res_content = res["choices"][0]["message"]["content"] |
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redis_.rpush(redis_key_name_openaikey_list, api_key) |
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redis_.persist(redis_key_name_openaikey_list) |
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except: |
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""" |
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发送警报 |
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""" |
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res_content = "" |
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thanks_task = { |
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"task_type": "thanks_task", |
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"uuid": uuid, |
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"main_parameter": main_parameter |
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} |
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time.sleep(3) |
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small_task = json.dumps(thanks_task, ensure_ascii=False) |
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redis_.lpush(redis_small_task, small_task) |
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redis_.rpush(redis_key_name_openaikey_list, api_key) |
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redis_.persist(redis_key_name_openaikey_list) |
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redis_.hset(redis_key_name_openaikey_bad_dict, uuid, str((api_key, task_type))) |
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return |
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lock.acquire() |
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res_dict_str = redis_.hget(redis_res, uuid) |
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res_dict = json.loads(res_dict_str) |
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res_dict["tasking_num"] += 1 |
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print("子任务进度".format(uuid), res_dict["tasking_num"]) |
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res_dict["致谢"] = res_content |
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res_dict_str = json.dumps(res_dict, ensure_ascii=False) |
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redis_.hset(redis_res, uuid, res_dict_str) |
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lock.release() |
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def chat_references(api_key, uuid, main_parameter, task_type): |
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''' |
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:param api_key: |
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:param uuid: |
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:param main_parameter: |
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:return: |
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''' |
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# title, |
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# mulu, |
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# references_prompt |
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title = main_parameter[0] |
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mulu = main_parameter[1] |
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prompt = main_parameter[2] |
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try: |
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response = request_api_chatgpt(api_key, prompt.format(title, mulu)) |
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res = response.json() |
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res_content = res["choices"][0]["message"]["content"] |
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redis_.rpush(redis_key_name_openaikey_list, api_key) |
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redis_.persist(redis_key_name_openaikey_list) |
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except: |
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""" |
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发送警报 |
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""" |
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res_content = "" |
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references_task = { |
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"task_type": "references_task", |
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"uuid": uuid, |
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"main_parameter": [ |
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title, |
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mulu, |
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config.references_prompt |
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] |
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} |
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time.sleep(3) |
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small_task = json.dumps(references_task, ensure_ascii=False) |
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redis_.lpush(redis_small_task, small_task) |
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redis_.rpush(redis_key_name_openaikey_list, api_key) |
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redis_.persist(redis_key_name_openaikey_list) |
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redis_.hset(redis_key_name_openaikey_bad_dict, uuid, str((api_key, task_type))) |
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return |
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# 加锁 读取resis并存储结果 |
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lock.acquire() |
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res_dict_str = redis_.hget(redis_res, uuid) |
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res_dict = json.loads(res_dict_str) |
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res_dict["tasking_num"] += 1 |
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print("子任务进度".format(uuid), res_dict["tasking_num"]) |
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res_dict["参考文献"] = res_content |
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res_dict_str = json.dumps(res_dict, ensure_ascii=False) |
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redis_.hset(redis_res, uuid, res_dict_str) |
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lock.release() |
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|
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def threading_mulu(api_key, title, uuid): |
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''' |
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生成目录并吧任务拆解进入子任务的redis_list中和储存结果的redis_list中 |
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:return: |
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''' |
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try: |
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response = request_api_chatgpt(api_key, config.mulu_prompt.format(title)) |
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res = response.json() |
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mulu = res["choices"][0]["message"]["content"] |
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redis_.rpush(redis_key_name_openaikey_list, api_key) |
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redis_.persist(redis_key_name_openaikey_list) |
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except: |
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""" |
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发送警报 |
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""" |
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res_content = "" |
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time.sleep(3) |
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redis_.lpush(redis_title, json.dumps({"id": uuid, "title": title}, ensure_ascii=False)) # 加入redis |
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redis_.persist(redis_key_name_openaikey_list) |
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|
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redis_.rpush(redis_key_name_openaikey_list, api_key) |
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redis_.persist(redis_key_name_openaikey_list) |
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redis_.hset(redis_key_name_openaikey_bad_dict, uuid, str(api_key,"mulu")) |
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return |
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|
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try: |
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mulu_list = str(mulu).split("\n") |
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mulu_list = [i.strip() for i in mulu_list if i != ""] |
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print(mulu_list) |
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cun_bool = False |
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table_of_contents = [mulu_list[0]] |
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for i in mulu_list[1:]: |
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result_second_biaoti_list = re.findall(config.pantten_second_biaoti, i) |
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result_other_biaoti_list = re.findall(config.pantten_other_biaoti, i) |
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if result_second_biaoti_list != []: |
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table_of_contents.append("@@" + i) |
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cun_bool = True |
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continue |
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if cun_bool == False: |
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continue |
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else: |
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if result_other_biaoti_list != []: |
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table_of_contents.append("@@" + i) |
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else: |
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table_of_contents.append(i) |
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print(table_of_contents) |
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# table_of_contents = table_of_contents[:3] + table_of_contents[-1:] |
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# print(table_of_contents) |
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thanks_references_bool_table = table_of_contents[-3:] |
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# thanks = "致谢" |
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# references = "参考文献" |
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if references in thanks_references_bool_table: |
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table_of_contents.remove(references) |
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if thanks in thanks_references_bool_table: |
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table_of_contents.remove(thanks) |
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|
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# table_of_contents.append(thanks) |
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# table_of_contents.append(references) |
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|
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# if thanks not in thanks_bool_table: |
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# table_of_contents.insert(-1, "致谢") |
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# |
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# if thanks not in thanks_bool_table: |
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# table_of_contents.insert(-1, "致谢") |
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print(len(table_of_contents)) |
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|
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small_task_list = [] |
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# api_key, |
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# index, |
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# title, |
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# mulu, |
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# subtitle, |
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# prompt |
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kaitibaogao_task = { |
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"task_type": "kaitibaogao", |
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"uuid": uuid, |
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"main_parameter": [title] |
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} |
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|
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chat_abstract_task = { |
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"task_type": "chat_abstract", |
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"uuid": uuid, |
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"main_parameter": [title] |
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} |
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small_task_list.append(kaitibaogao_task) |
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small_task_list.append(chat_abstract_task) |
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content_index = 0 |
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while True: |
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if content_index == len(table_of_contents): |
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break |
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subtitle = table_of_contents[content_index] |
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if content_index == 0: |
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prompt = config.first_title_prompt |
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elif subtitle == "参考文献": |
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prompt = config.references_prompt |
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elif subtitle == "致谢": |
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prompt = config.thank_prompt |
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else: |
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prompt = config.small_title_prompt |
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print("请求的所有参数", |
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content_index, |
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title, |
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subtitle, |
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prompt) |
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|
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paper_content = { |
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"task_type": "paper_content", |
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"uuid": uuid, |
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"main_parameter": [ |
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content_index, |
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title, |
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mulu, |
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subtitle, |
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prompt |
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] |
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} |
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|
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small_task_list.append(paper_content) |
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content_index += 1 |
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|
|||
thanks_task = { |
|||
"task_type": "thanks_task", |
|||
"uuid": uuid, |
|||
"main_parameter": [ |
|||
title, |
|||
config.thank_prompt |
|||
] |
|||
} |
|||
|
|||
references_task = { |
|||
"task_type": "references_task", |
|||
"uuid": uuid, |
|||
"main_parameter": [ |
|||
title, |
|||
mulu, |
|||
config.references_prompt |
|||
] |
|||
} |
|||
|
|||
small_task_list.append(thanks_task) |
|||
small_task_list.append(references_task) |
|||
|
|||
for small_task in small_task_list: |
|||
small_task = json.dumps(small_task, ensure_ascii=False) |
|||
redis_.rpush(redis_small_task, small_task) |
|||
|
|||
|
|||
res = { |
|||
"uuid": uuid, |
|||
"num_small_task": len(small_task_list), |
|||
"tasking_num": 0, |
|||
"标题": title, |
|||
"目录": mulu, |
|||
"开题报告": "", |
|||
"任务书": "", |
|||
"中文摘要": "", |
|||
"英文摘要": "", |
|||
"中文关键词": "", |
|||
"英文关键词": "", |
|||
"正文": "", |
|||
"致谢": "", |
|||
"参考文献": "", |
|||
"table_of_contents": [""] * len(table_of_contents) |
|||
} |
|||
|
|||
res = json.dumps(res, ensure_ascii=False) |
|||
redis_.hset(redis_res, uuid, res) |
|||
except: |
|||
print("目录程序错误") |
|||
|
|||
|
|||
def threading_1(): |
|||
# title, redis_key_name_openaikey_list |
|||
''' |
|||
生成目录 |
|||
:param title: |
|||
:param redis_key_name_openaikey_list: |
|||
:return: |
|||
''' |
|||
while True: |
|||
if redis_.llen(redis_small_task) != 0: # 若队列中有元素就跳过 |
|||
time.sleep(1) |
|||
continue |
|||
elif redis_.llen(redis_title) != 0 and redis_.llen(redis_key_name_openaikey_list) != 0: |
|||
title_uuid_dict_str = redis_.lpop(redis_title).decode('UTF-8') |
|||
api_key = redis_.lpop(redis_key_name_openaikey_list).decode('UTF-8') |
|||
# redis_title:{"id": id_, "title": title} |
|||
title_uuid_dict = json.loads(title_uuid_dict_str) |
|||
|
|||
title = title_uuid_dict["title"] |
|||
uuid_id = title_uuid_dict["id"] |
|||
|
|||
t = Thread(target=threading_mulu, args=(api_key, |
|||
title, |
|||
uuid_id, |
|||
)) |
|||
t.start() |
|||
else: |
|||
time.sleep(1) |
|||
continue |
|||
|
|||
|
|||
def threading_2(): |
|||
''' |
|||
顺序读取子任务 |
|||
:return: |
|||
''' |
|||
while True: |
|||
if redis_.llen(redis_small_task) != 0 and redis_.llen(redis_key_name_openaikey_list) != 0: |
|||
# 执行小标题的任务 |
|||
api_key = redis_.lpop(redis_key_name_openaikey_list).decode('UTF-8') |
|||
small_title = redis_.lpop(redis_small_task).decode('UTF-8') |
|||
small_title = json.loads(small_title) |
|||
task_type = small_title["task_type"] |
|||
uuid = small_title["uuid"] |
|||
main_parameter = small_title["main_parameter"] |
|||
|
|||
# "task_type": "paper_content", |
|||
# "uuid": uuid, |
|||
# "main_parameter": [ |
|||
# "task_type": "paper_content", |
|||
# "task_type": "chat_abstract", |
|||
# "task_type": "kaitibaogao", |
|||
|
|||
if task_type == "kaitibaogao": |
|||
t = Thread(target=chat_kaitibaogao, args=(api_key, |
|||
uuid, |
|||
main_parameter, |
|||
task_type)) |
|||
t.start() |
|||
elif task_type == "chat_abstract": |
|||
t = Thread(target=chat_abstract_keyword, args=(api_key, |
|||
uuid, |
|||
main_parameter, |
|||
task_type)) |
|||
t.start() |
|||
elif task_type == "paper_content": |
|||
t = Thread(target=chat_content, args=(api_key, |
|||
uuid, |
|||
main_parameter, |
|||
task_type)) |
|||
t.start() |
|||
elif task_type == "thanks_task": |
|||
t = Thread(target=chat_thanks, args=(api_key, |
|||
uuid, |
|||
main_parameter, |
|||
task_type)) |
|||
t.start() |
|||
elif task_type == "references_task": |
|||
t = Thread(target=chat_references, args=(api_key, |
|||
uuid, |
|||
main_parameter, |
|||
task_type)) |
|||
t.start() |
|||
else: |
|||
time.sleep(1) |
|||
continue |
|||
|
|||
|
|||
def threading_3(): |
|||
while True: |
|||
res_end_list = [] |
|||
res_dict = redis_.hgetall(redis_res) |
|||
for key, values in res_dict.items(): |
|||
values_dict = json.loads(values) |
|||
# "num_small_task": len(small_task_list) - 1, |
|||
# "tasking_num": 0, |
|||
if int(values_dict["num_small_task"]) == int(values_dict["tasking_num"]): |
|||
res_end_list.append(key) |
|||
if res_end_list != []: |
|||
for key in res_end_list: |
|||
redis_.hdel(redis_res, key) |
|||
|
|||
res_str = res_dict[key].decode("utf-8") |
|||
json_str = json.dumps(res_str, indent=4, ensure_ascii=False) |
|||
|
|||
key = str(key, encoding="utf-8") |
|||
uuid_path = os.path.join(config.project_data_txt_path, key) |
|||
|
|||
os.makedirs(uuid_path) |
|||
|
|||
paper_content_path = os.path.join(uuid_path, "paper_content.json") |
|||
with open(paper_content_path, 'w') as json_file: |
|||
json_file.write(json_str) |
|||
|
|||
save_word_paper = os.path.join(uuid_path, "paper.docx") |
|||
save_word_paper_start = os.path.join(uuid_path, "paper_start.docx") |
|||
print("java_path", paper_content_path, ) |
|||
os.system( |
|||
"java -Dfile.encoding=UTF-8 -jar '/home/majiahui/ChatGPT_Sever/aiXieZuoPro.jar' '{}' '{}' '{}'".format( |
|||
paper_content_path, |
|||
save_word_paper, |
|||
save_word_paper_start)) |
|||
|
|||
url_path_paper = paper_download_url.format(key) |
|||
url_path_kaiti = paper_start_download_url.format(key) |
|||
return_text = str({"id": key, |
|||
"content_url_path": url_path_paper, |
|||
"content_report_url_path": url_path_kaiti, |
|||
"probabilities": None, |
|||
"status_code": 200}) |
|||
redis_.srem(redis_title_ing, key) |
|||
redis_.set(key, return_text, 28800) |
|||
|
|||
time.sleep(1) |
|||
|
|||
|
|||
# def main(title): |
|||
# # print(request.remote_addr) |
|||
# # title = request.json["title"] |
|||
# |
|||
# id_ = str(uuid.uuid1()) |
|||
# print(id_) |
|||
# redis_.rpush(redis_title, json.dumps({"id": id_, "title": title})) # 加入redis |
|||
|
|||
|
|||
@app.route("/chat", methods=["POST"]) |
|||
def chat(): |
|||
print(request.remote_addr) |
|||
title = request.json["title"] |
|||
id_ = str(uuid.uuid1()) |
|||
print(id_) |
|||
redis_.rpush(redis_title, json.dumps({"id": id_, "title": title},ensure_ascii=False)) # 加入redis |
|||
redis_.persist(redis_key_name_openaikey_list) |
|||
return_text = {"texts": {'id': id_, }, "probabilities": None, "status_code": 200} |
|||
print("ok") |
|||
redis_.sadd(redis_title_ing, id_) |
|||
|
|||
return jsonify(return_text) # 返回结果 |
|||
|
|||
|
|||
@app.route("/download", methods=['GET']) |
|||
def download_file(): |
|||
# 需要知道2个参数, 第1个参数是本地目录的path, 第2个参数是文件名(带扩展名) |
|||
# directory = os.path.join(project_data_txt_path, filename) # 假设在当前目录 |
|||
|
|||
# uuid_path, word_name = str(filename).split("/") |
|||
# word_path_root = os.path.join(project_data_txt_path, uuid_path) |
|||
# response = make_response(send_from_directory(word_path_root, word_name, as_attachment=True)) |
|||
# response.headers["Content-Disposition"] = "attachment; filename={}".format(filename.encode().decode('latin-1')) |
|||
filename_path = request.args.get('filename_path', '') |
|||
filename = filename_path.split("/")[1] |
|||
path_name = os.path.join(config.project_data_txt_path, filename_path) |
|||
with open(path_name, 'rb') as f: |
|||
stream = f.read() |
|||
response = Response(stream, content_type='application/octet-stream') |
|||
response.headers['Content-disposition'] = 'attachment; filename={}'.format(filename) |
|||
return response |
|||
|
|||
|
|||
@app.route("/search", methods=["POST"]) |
|||
def search(): |
|||
id_ = request.json['id'] # 获取用户query中的文本 例如"I love you" |
|||
result = redis_.get(id_) # 获取该query的模型结果 |
|||
|
|||
# if redis_.hexists(redis_key_name_openaikey_bad_dict, id_) == True: |
|||
# result_text = {'code': "204", 'text': "", 'probabilities': None} |
|||
if result is not None: |
|||
# redis_.delete(id_) |
|||
# result_dict = result.decode('UTF-8') |
|||
|
|||
result_dict = eval(result) |
|||
# return_text = {"id":query_id, "load_result_path": load_result_path, "probabilities": None, "status_code": 200} |
|||
query_id = result_dict["id"] |
|||
# "content_url_path": url_path_paper, |
|||
# "content_report_url_path": url_path_kaiti, |
|||
content_url_path = result_dict["content_url_path"] |
|||
content_report_url_path = result_dict["content_report_url_path"] |
|||
probabilities = result_dict["probabilities"] |
|||
result_text = {'code': 200, |
|||
'content_url_path': content_url_path, |
|||
'content_report_url_path': content_report_url_path, |
|||
'probabilities': probabilities} |
|||
else: |
|||
querying_list = list(redis_.smembers(redis_title_ing)) |
|||
querying_set = set() |
|||
for i in querying_list: |
|||
querying_set.add(i.decode()) |
|||
|
|||
querying_bool = False |
|||
if id_ in querying_set: |
|||
querying_bool = True |
|||
|
|||
query_list_json = redis_.lrange(redis_title, 0, -1) |
|||
query_set_ids = set() |
|||
for i in query_list_json: |
|||
data_dict = json.loads(i) |
|||
query_id = data_dict['id'] |
|||
query_set_ids.add(query_id) |
|||
|
|||
query_bool = False |
|||
if id_ in query_set_ids: |
|||
query_bool = True |
|||
|
|||
if querying_bool == True and query_bool == True: |
|||
result_text = {'code': "201", 'text': "", 'probabilities': None} |
|||
elif querying_bool == True and query_bool == False: |
|||
result_text = {'code': "202", 'text': "", 'probabilities': None} |
|||
else: |
|||
result_text = {'code': "203", 'text': "", 'probabilities': None} |
|||
return jsonify(result_text) # 返回结果 |
|||
|
|||
|
|||
# threading_1 # 根据标题获取子任务，存入子任务序列 |
|||
# threading_2 # 根据子任务生成结果，存入结果序列 |
|||
# threading_3 # 根据存储的结果序列，看是否完成，如果完成输出json文件以及word |
|||
t = Thread(target=threading_1) |
|||
t.start() |
|||
t = Thread(target=threading_2) |
|||
t.start() |
|||
t = Thread(target=threading_3) |
|||
t.start() |
|||
|
|||
if __name__ == '__main__': |
|||
# main("大型商业建筑人员疏散设计研究") |
|||
app.run(host="0.0.0.0", port=config.flask_port, threaded=True, debug=False) |
|||
@ -0,0 +1,3 @@ |
|||
国外服务器1 104.244.89.190 |
|||
国外服务器2 107.182.189.58 |
|||
国外服务器3 104.244.90.248 |
|||
@ -0,0 +1 @@ |
|||
nohup python flask_serve_1.py > myout.file_1 2>&1 & |
|||
@ -1,45 +1,40 @@ |
|||
|
|||
|
|||
class Config: |
|||
def __init__(self): |
|||
|
|||
# 目录提取拼接相关参数 |
|||
self.pantten_second_biaoti = '[2二ⅡⅠ][、.]\s{0,}?[\u4e00-\u9fa5]+' |
|||
self.pantten_other_biaoti = '[2-9二三四五六七八九ⅡⅢⅣⅤⅥⅦⅧⅨ][、.]\s{0,}?[\u4e00-\u9fa5]+' |
|||
|
|||
# chatgpt 接口相关参数 |
|||
self.mulu_prompt = "请帮我根据题目为“{}”生成一个论文目录" |
|||
self.first_title_prompt = "论文题目是“{}”，目录是“{}”，请把其中的大标题“{}”的内容补充完整，补充内容字数在100字左右" |
|||
self.small_title_prompt = "论文题目是“{}”，目录是“{}”，请把其中的小标题“{}”的内容补充完整，补充内容字数在100字左右" |
|||
self.first_title_prompt = "论文题目是“{}”，目录是“{}”，请把其中的大标题“{}”的内容补充完整，补充内容字数在800字左右" |
|||
self.small_title_prompt = "论文题目是“{}”，目录是“{}”，请把其中的小标题“{}”的内容补充完整，补充内容字数在800字左右" |
|||
self.references_prompt = "论文题目是“{}”，目录是“{}”，请为这篇论文生成15篇左右的参考文献，要求其中有有中文参考文献不低于12篇，英文参考文献不低于2篇" |
|||
self.thank_prompt = "请以“{}”为题写一篇论文的致谢" |
|||
self.kaitibaogao_prompt = "请以《{}》为题目生成研究的主要的内容、背景、目的、意义，要求不少于100字" |
|||
self.chinese_abstract_prompt = "请以《{}》为题目生成论文摘要，要求生成的字数在100字左右" |
|||
self.kaitibaogao_prompt = "请以《{}》为题目生成研究的主要的内容、背景、目的、意义，要求不少于1500字" |
|||
self.chinese_abstract_prompt = "请以《{}》为题目生成论文摘要，要求生成的字数在800字左右" |
|||
self.english_abstract_prompt = "请把“{}”这段文字翻译成英文" |
|||
self.chinese_keyword_prompt = "请为“{}”这段论文摘要生成3-5个关键字" |
|||
self.english_keyword_prompt = "请把“{}”这几个关键字翻译成英文" |
|||
self.dabiaoti = ["二", "三", "四", "五", "六", "七", "八", "九"] |
|||
self.project_data_txt_path = "/home/majiahui/ChatGPT_Sever/new_data_txt" |
|||
self.openaikey_list = ["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", |
|||
"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", |
|||
"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" |
|||
self.openaikey_list = ["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", |
|||
"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", |
|||
"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", |
|||
"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", |
|||
"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", |
|||
"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", |
|||
"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", |
|||
] |
|||
# "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", |
|||
# "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" |
|||
# "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", |
|||
# "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", |
|||
# "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", |
|||
# "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" |
|||
|
|||
# 流程相关参数 |
|||
self.thanks = "致谢" |
|||
self.references = "参考文献" |
|||
|
|||
# flask port |
|||
self.flask_port = "14000" |
|||
self.flask_port = "14002" |
|||
|
|||
# redis config |
|||
self.reids_ip = 'localhost' |
|||
self.reids_port = 63179 |
|||
self.reids_db = 2 |
|||
self.reids_password='Zhicheng123*' |
|||
self.reids_password = 'Zhicheng123*' |
|||
|
|||
@ -0,0 +1,39 @@ |
|||
|
|||
|
|||
class Config: |
|||
def __init__(self): |
|||
|
|||
# 目录提取拼接相关参数 |
|||
self.pantten_second_biaoti = '[2二ⅡⅠ][、.]\s{0,}?[\u4e00-\u9fa5]+' |
|||
self.pantten_other_biaoti = '[2-9二三四五六七八九ⅡⅢⅣⅤⅥⅦⅧⅨ][、.]\s{0,}?[\u4e00-\u9fa5]+' |
|||
|
|||
# chatgpt 接口相关参数 |
|||
self.mulu_prompt = "请帮我根据题目为“{}”生成一个论文目录" |
|||
self.first_title_prompt = "论文题目是“{}”，目录是“{}”，请把其中的大标题“{}”的内容补充完整，补充内容字数在100字左右" |
|||
self.small_title_prompt = "论文题目是“{}”，目录是“{}”，请把其中的小标题“{}”的内容补充完整，补充内容字数在100字左右" |
|||
self.references_prompt = "论文题目是“{}”，目录是“{}”，请为这篇论文生成15篇左右的参考文献，要求其中有有中文参考文献不低于12篇，英文参考文献不低于2篇" |
|||
self.thank_prompt = "请以“{}”为题写一篇论文的致谢" |
|||
self.kaitibaogao_prompt = "请以《{}》为题目生成研究的主要的内容、背景、目的、意义，要求不少于100字" |
|||
self.chinese_abstract_prompt = "请以《{}》为题目生成论文摘要，要求生成的字数在100字左右" |
|||
self.english_abstract_prompt = "请把“{}”这段文字翻译成英文" |
|||
self.chinese_keyword_prompt = "请为“{}”这段论文摘要生成3-5个关键字" |
|||
self.english_keyword_prompt = "请把“{}”这几个关键字翻译成英文" |
|||
self.dabiaoti = ["二", "三", "四", "五", "六", "七", "八", "九"] |
|||
self.project_data_txt_path = "/home/majiahui/ChatGPT_Sever/new_data_txt" |
|||
self.openaikey_list = [ |
|||
|
|||
] |
|||
|
|||
|
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# 流程相关参数 |
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self.thanks = "致谢" |
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self.references = "参考文献" |
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|
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# flask port |
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self.flask_port = "14000" |
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|
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# redis config |
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self.reids_ip = '104.244.89.190' |
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self.reids_port = 63179 |
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self.reids_db = 2 |
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self.reids_password='Zhicheng123*' |
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Reference in new issue