eveyuyi/ChatGPT_Prompts
0
1# -*- coding:utf-8 -*-2from __future__ import annotations3from typing import TYPE_CHECKING, List4 5import logging6import json7import os8import requests9import urllib310 11from tqdm import tqdm12import colorama13from duckduckgo_search import ddg14import asyncio15import aiohttp16 17from presets import *18from llama_func import *19from utils import *20 21# logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] [%(filename)s:%(lineno)d] %(message)s")22 23if TYPE_CHECKING:24 from typing import TypedDict25 26 class DataframeData(TypedDict):27 headers: List[str]28 data: List[List[str | int | bool]]29 30 31initial_prompt = "You are a helpful assistant."32API_URL = "https://api.openai.com/v1/chat/completions"33HISTORY_DIR = "history"34TEMPLATES_DIR = "templates"35 36def get_response(37 openai_api_key, system_prompt, history, temperature, top_p, stream, selected_model38):39 headers = {40 "Content-Type": "application/json",41 "Authorization": f"Bearer {openai_api_key}",42 }43 44 history = [construct_system(system_prompt), *history]45 46 payload = {47 "model": selected_model,48 "messages": history, # [{"role": "user", "content": f"{inputs}"}],49 "temperature": temperature, # 1.0,50 "top_p": top_p, # 1.0,51 "n": 1,52 "stream": stream,53 "presence_penalty": 0,54 "frequency_penalty": 0,55 }56 if stream:57 timeout = timeout_streaming58 else:59 timeout = timeout_all60 61 # 获取环境变量中的代理设置62 http_proxy = os.environ.get("HTTP_PROXY") or os.environ.get("http_proxy")63 https_proxy = os.environ.get("HTTPS_PROXY") or os.environ.get("https_proxy")64 65 # 如果存在代理设置，使用它们66 proxies = {}67 if http_proxy:68 logging.info(f"Using HTTP proxy: {http_proxy}")69 proxies["http"] = http_proxy70 if https_proxy:71 logging.info(f"Using HTTPS proxy: {https_proxy}")72 proxies["https"] = https_proxy73 74 # 如果有代理，使用代理发送请求，否则使用默认设置发送请求75 if proxies:76 response = requests.post(77 API_URL,78 headers=headers,79 json=payload,80 stream=True,81 timeout=timeout,82 proxies=proxies,83 )84 else:85 response = requests.post(86 API_URL,87 headers=headers,88 json=payload,89 stream=True,90 timeout=timeout,91 )92 return response93 94 95def stream_predict(96 openai_api_key,97 system_prompt,98 history,99 inputs,100 chatbot,101 all_token_counts,102 top_p,103 temperature,104 selected_model,105 fake_input=None,106 display_append=""107):108 def get_return_value():109 return chatbot, history, status_text, all_token_counts110 111 logging.info("实时回答模式")112 partial_words = ""113 counter = 0114 status_text = "开始实时传输回答……"115 history.append(construct_user(inputs))116 history.append(construct_assistant(""))117 if fake_input:118 chatbot.append((fake_input, ""))119 else:120 chatbot.append((inputs, ""))121 user_token_count = 0122 if len(all_token_counts) == 0:123 system_prompt_token_count = count_token(construct_system(system_prompt))124 user_token_count = (125 count_token(construct_user(inputs)) + system_prompt_token_count126 )127 else:128 user_token_count = count_token(construct_user(inputs))129 all_token_counts.append(user_token_count)130 logging.info(f"输入token计数: {user_token_count}")131 yield get_return_value()132 try:133 response = get_response(134 openai_api_key,135 system_prompt,136 history,137 temperature,138 top_p,139 True,140 selected_model,141 )142 except requests.exceptions.ConnectTimeout:143 status_text = (144 standard_error_msg + connection_timeout_prompt + error_retrieve_prompt145 )146 yield get_return_value()147 return148 except requests.exceptions.ReadTimeout:149 status_text = standard_error_msg + read_timeout_prompt + error_retrieve_prompt150 yield get_return_value()151 return152 153 yield get_return_value()154 error_json_str = ""155 156 for chunk in response.iter_lines():157 if counter == 0:158 counter += 1159 continue160 counter += 1161 # check whether each line is non-empty162 if chunk:163 chunk = chunk.decode()164 chunklength = len(chunk)165 try:166 chunk = json.loads(chunk[6:])167 except json.JSONDecodeError:168 logging.info(chunk)169 error_json_str += chunk170 status_text = f"JSON解析错误。请重置对话。收到的内容: {error_json_str}"171 yield get_return_value()172 continue173 # decode each line as response data is in bytes174 if chunklength > 6 and "delta" in chunk["choices"][0]:175 finish_reason = chunk["choices"][0]["finish_reason"]176 status_text = construct_token_message(177 sum(all_token_counts), stream=True178 )179 if finish_reason == "stop":180 yield get_return_value()181 break182 try:183 partial_words = (184 partial_words + chunk["choices"][0]["delta"]["content"]185 )186 except KeyError:187 status_text = (188 standard_error_msg189 + "API回复中找不到内容。很可能是Token计数达到上限了。请重置对话。当前Token计数: "190 + str(sum(all_token_counts))191 )192 yield get_return_value()193 break194 history[-1] = construct_assistant(partial_words)195 chatbot[-1] = (chatbot[-1][0], partial_words+display_append)196 all_token_counts[-1] += 1197 yield get_return_value()198 199 200def predict_all(201 openai_api_key,202 system_prompt,203 history,204 inputs,205 chatbot,206 all_token_counts,207 top_p,208 temperature,209 selected_model,210 fake_input=None,211 display_append=""212):213 logging.info("一次性回答模式")214 history.append(construct_user(inputs))215 history.append(construct_assistant(""))216 if fake_input:217 chatbot.append((fake_input, ""))218 else:219 chatbot.append((inputs, ""))220 all_token_counts.append(count_token(construct_user(inputs)))221 try:222 response = get_response(223 openai_api_key,224 system_prompt,225 history,226 temperature,227 top_p,228 False,229 selected_model,230 )231 except requests.exceptions.ConnectTimeout:232 status_text = (233 standard_error_msg + connection_timeout_prompt + error_retrieve_prompt234 )235 return chatbot, history, status_text, all_token_counts236 except requests.exceptions.ProxyError:237 status_text = standard_error_msg + proxy_error_prompt + error_retrieve_prompt238 return chatbot, history, status_text, all_token_counts239 except requests.exceptions.SSLError:240 status_text = standard_error_msg + ssl_error_prompt + error_retrieve_prompt241 return chatbot, history, status_text, all_token_counts242 response = json.loads(response.text)243 content = response["choices"][0]["message"]["content"]244 history[-1] = construct_assistant(content)245 chatbot[-1] = (chatbot[-1][0], content+display_append)246 total_token_count = response["usage"]["total_tokens"]247 all_token_counts[-1] = total_token_count - sum(all_token_counts)248 status_text = construct_token_message(total_token_count)249 return chatbot, history, status_text, all_token_counts250 251 252def predict(253 openai_api_key,254 system_prompt,255 history,256 inputs,257 chatbot,258 all_token_counts,259 top_p,260 temperature,261 stream=False,262 selected_model=MODELS[0],263 use_websearch=False,264 files = None,265 should_check_token_count=True,266): # repetition_penalty, top_k267 logging.info("输入为：" + colorama.Fore.BLUE + f"{inputs}" + colorama.Style.RESET_ALL)268 if files:269 msg = "构建索引中……（这可能需要比较久的时间）"270 logging.info(msg)271 yield chatbot, history, msg, all_token_counts272 index = construct_index(openai_api_key, file_src=files)273 msg = "索引构建完成，获取回答中……"274 yield chatbot, history, msg, all_token_counts275 history, chatbot, status_text = chat_ai(openai_api_key, index, inputs, history, chatbot)276 yield chatbot, history, status_text, all_token_counts277 return278 279 old_inputs = ""280 link_references = []281 if use_websearch:282 search_results = ddg(inputs, max_results=5)283 old_inputs = inputs284 web_results = []285 for idx, result in enumerate(search_results):286 logging.info(f"搜索结果{idx + 1}：{result}")287 domain_name = urllib3.util.parse_url(result["href"]).host288 web_results.append(f'[{idx+1}]"{result["body"]}"\nURL: {result["href"]}')289 link_references.append(f"{idx+1}. [{domain_name}]({result['href']})\n")290 link_references = "\n\n" + "".join(link_references)291 inputs = (292 replace_today(WEBSEARCH_PTOMPT_TEMPLATE)293 .replace("{query}", inputs)294 .replace("{web_results}", "\n\n".join(web_results))295 )296 else:297 link_references = ""298 299 if len(openai_api_key) != 51:300 status_text = standard_error_msg + no_apikey_msg301 logging.info(status_text)302 chatbot.append((inputs, ""))303 if len(history) == 0:304 history.append(construct_user(inputs))305 history.append("")306 all_token_counts.append(0)307 else:308 history[-2] = construct_user(inputs)309 yield chatbot, history, status_text, all_token_counts310 return311 312 yield chatbot, history, "开始生成回答……", all_token_counts313 314 if stream:315 logging.info("使用流式传输")316 iter = stream_predict(317 openai_api_key,318 system_prompt,319 history,320 inputs,321 chatbot,322 all_token_counts,323 top_p,324 temperature,325 selected_model,326 fake_input=old_inputs,327 display_append=link_references328 )329 for chatbot, history, status_text, all_token_counts in iter:330 yield chatbot, history, status_text, all_token_counts331 else:332 logging.info("不使用流式传输")333 chatbot, history, status_text, all_token_counts = predict_all(334 openai_api_key,335 system_prompt,336 history,337 inputs,338 chatbot,339 all_token_counts,340 top_p,341 temperature,342 selected_model,343 fake_input=old_inputs,344 display_append=link_references345 )346 yield chatbot, history, status_text, all_token_counts347 348 logging.info(f"传输完毕。当前token计数为{all_token_counts}")349 if len(history) > 1 and history[-1]["content"] != inputs:350 logging.info(351 "回答为："352 + colorama.Fore.BLUE353 + f"{history[-1]['content']}"354 + colorama.Style.RESET_ALL355 )356 357 if stream:358 max_token = max_token_streaming359 else:360 max_token = max_token_all361 362 if sum(all_token_counts) > max_token and should_check_token_count:363 status_text = f"精简token中{all_token_counts}/{max_token}"364 logging.info(status_text)365 yield chatbot, history, status_text, all_token_counts366 iter = reduce_token_size(367 openai_api_key,368 system_prompt,369 history,370 chatbot,371 all_token_counts,372 top_p,373 temperature,374 max_token//2,375 selected_model=selected_model,376 )377 for chatbot, history, status_text, all_token_counts in iter:378 status_text = f"Token 达到上限，已自动降低Token计数至 {status_text}"379 yield chatbot, history, status_text, all_token_counts380 381 382def retry(383 openai_api_key,384 system_prompt,385 history,386 chatbot,387 token_count,388 top_p,389 temperature,390 stream=False,391 selected_model=MODELS[0],392):393 logging.info("重试中……")394 if len(history) == 0:395 yield chatbot, history, f"{standard_error_msg}上下文是空的", token_count396 return397 history.pop()398 inputs = history.pop()["content"]399 token_count.pop()400 iter = predict(401 openai_api_key,402 system_prompt,403 history,404 inputs,405 chatbot,406 token_count,407 top_p,408 temperature,409 stream=stream,410 selected_model=selected_model,411 )412 logging.info("重试中……")413 for x in iter:414 yield x415 logging.info("重试完毕")416 417 418def reduce_token_size(419 openai_api_key,420 system_prompt,421 history,422 chatbot,423 token_count,424 top_p,425 temperature,426 max_token_count,427 selected_model=MODELS[0],428):429 logging.info("开始减少token数量……")430 iter = predict(431 openai_api_key,432 system_prompt,433 history,434 summarize_prompt,435 chatbot,436 token_count,437 top_p,438 temperature,439 selected_model=selected_model,440 should_check_token_count=False,441 )442 logging.info(f"chatbot: {chatbot}")443 flag = False444 for chatbot, history, status_text, previous_token_count in iter:445 num_chat = find_n(previous_token_count, max_token_count)446 if flag:447 chatbot = chatbot[:-1]448 flag = True449 history = history[-2*num_chat:] if num_chat > 0 else []450 token_count = previous_token_count[-num_chat:] if num_chat > 0 else []451 msg = f"保留了最近{num_chat}轮对话"452 yield chatbot, history, msg + "，" + construct_token_message(453 sum(token_count) if len(token_count) > 0 else 0,454 ), token_count455 logging.info(msg)456 logging.info("减少token数量完毕")