XIao
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8e9c07644f
@ -207,6 +207,8 @@ ZHIPUAI_MODEL = "" # 此选项已废弃，不再需要填写
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# Claude API KEY
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ANTHROPIC_API_KEY = ""
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# 月之暗面 API KEY
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MOONSHOT_API_KEY = ""
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# Mathpix 拥有执行PDF的OCR功能，但是需要注册账号
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MATHPIX_APPID = ""
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@ -296,7 +296,35 @@ model_info = {
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"token_cnt": get_token_num_gpt35,
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},
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}
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# -=-=-=-=-=-=- 月之暗面 -=-=-=-=-=-=-
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from request_llms.bridge_moonshot import predict as moonshot_ui
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from request_llms.bridge_moonshot import predict_no_ui_long_connection as moonshot_no_ui
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model_info.update({
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"moonshot-v1-8k": {
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"fn_with_ui": moonshot_ui,
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"fn_without_ui": moonshot_no_ui,
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"endpoint": None,
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"max_token": 1024 * 8,
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"tokenizer": tokenizer_gpt35,
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"token_cnt": get_token_num_gpt35,
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},
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"moonshot-v1-32k": {
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"fn_with_ui": moonshot_ui,
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"fn_without_ui": moonshot_no_ui,
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"endpoint": None,
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"max_token": 1024 * 32,
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"tokenizer": tokenizer_gpt35,
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"token_cnt": get_token_num_gpt35,
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},
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"moonshot-v1-128k": {
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"fn_with_ui": moonshot_ui,
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"fn_without_ui": moonshot_no_ui,
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"endpoint": None,
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"max_token": 1024 * 128,
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"tokenizer": tokenizer_gpt35,
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"token_cnt": get_token_num_gpt35,
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}
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})
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# -=-=-=-=-=-=- api2d 对齐支持 -=-=-=-=-=-=-
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for model in AVAIL_LLM_MODELS:
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if model.startswith('api2d-') and (model.replace('api2d-','') in model_info.keys()):
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192
request_llms/bridge_moonshot.py
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192
request_llms/bridge_moonshot.py
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@ -0,0 +1,192 @@
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# encoding: utf-8
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# @Time : 2024/3/3
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# @Author : Spike
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# @Descr :
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import json
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import os
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import time
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from toolbox import get_conf, update_ui
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import requests
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class MoonShotInit:
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def __init__(self):
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self.llm_model = None
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self.url = 'https://api.moonshot.cn/v1/chat/completions'
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self.api_key = get_conf('MOONSHOT_API_KEY')
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def __converter_file(self, user_input: str):
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what_ask = []
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for f in user_input.splitlines():
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if os.path.exists(f):
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files = []
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if os.path.isdir(f):
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file_list = os.listdir(f)
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files.extend([os.path.join(f, file) for file in file_list])
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else:
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files.append(f)
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for file in files:
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if file.split('.')[-1] in ['pdf']:
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with open(file, 'r') as fp:
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from crazy_functions.crazy_utils import read_and_clean_pdf_text
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file_content, _ = read_and_clean_pdf_text(fp)
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what_ask.append({"role": "system", "content": file_content})
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return what_ask
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def __converter_user(self, user_input: str):
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what_i_ask_now = {"role": "user", "content": user_input}
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return what_i_ask_now
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def __conversation_history(self, history):
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conversation_cnt = len(history) // 2
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messages = []
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if conversation_cnt:
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for index in range(0, 2 * conversation_cnt, 2):
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what_i_have_asked = {
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"role": "user",
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"content": str(history[index])
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}
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what_gpt_answer = {
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"role": "assistant",
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"content": str(history[index + 1])
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}
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if what_i_have_asked["content"] != "":
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if what_gpt_answer["content"] == "": continue
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messages.append(what_i_have_asked)
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messages.append(what_gpt_answer)
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else:
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messages[-1]['content'] = what_gpt_answer['content']
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return messages
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def _analysis_content(self, chuck):
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chunk_decoded = chuck.decode("utf-8")
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chunk_json = {}
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content = ""
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try:
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chunk_json = json.loads(chunk_decoded[6:])
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content = chunk_json['choices'][0]["delta"].get("content", "")
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except:
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pass
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return chunk_decoded, chunk_json, content
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def generate_payload(self, inputs, llm_kwargs, history, system_prompt, stream):
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self.llm_model = llm_kwargs['llm_model']
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llm_kwargs.update({'use-key': self.api_key})
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messages = []
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if system_prompt:
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messages.append({"role": "system", "content": system_prompt})
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messages.extend(self.__converter_file(inputs))
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messages.extend(self.__conversation_history(history))
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messages.append(self.__converter_user(inputs))
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header = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {self.api_key}",
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}
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payload = {
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"model": self.llm_model,
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"messages": messages,
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"temperature": llm_kwargs.get('temperature', 0.3), # 1.0,
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"top_p": llm_kwargs.get('top_p', 1.0), # 1.0,
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"n": llm_kwargs.get('n_choices', 1),
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"stream": stream
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}
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return payload, header
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def generate_messages(self, inputs, llm_kwargs, history, system_prompt, stream):
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payload, headers = self.generate_payload(inputs, llm_kwargs, history, system_prompt, stream)
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response = requests.post(self.url, headers=headers, json=payload, stream=stream)
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chunk_content = ""
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gpt_bro_result = ""
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for chuck in response.iter_lines():
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chunk_decoded, check_json, content = self._analysis_content(chuck)
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chunk_content += chunk_decoded
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if content:
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gpt_bro_result += content
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yield content, gpt_bro_result, ''
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else:
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error_msg = msg_handle_error(llm_kwargs, chunk_decoded)
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if error_msg:
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yield error_msg, gpt_bro_result, error_msg
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break
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def msg_handle_error(llm_kwargs, chunk_decoded):
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use_ket = llm_kwargs.get('use-key', '')
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api_key_encryption = use_ket[:8] + '****' + use_ket[-5:]
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openai_website = f' 请登录OpenAI查看详情 https://platform.openai.com/signup api-key: `{api_key_encryption}`'
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error_msg = ''
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if "does not exist" in chunk_decoded:
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error_msg = f"[Local Message] Model {llm_kwargs['llm_model']} does not exist. 模型不存在, 或者您没有获得体验资格."
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elif "Incorrect API key" in chunk_decoded:
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error_msg = f"[Local Message] Incorrect API key. OpenAI以提供了不正确的API_KEY为由, 拒绝服务." + openai_website
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elif "exceeded your current quota" in chunk_decoded:
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error_msg = "[Local Message] You exceeded your current quota. OpenAI以账户额度不足为由, 拒绝服务." + openai_website
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elif "account is not active" in chunk_decoded:
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error_msg = "[Local Message] Your account is not active. OpenAI以账户失效为由, 拒绝服务." + openai_website
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elif "associated with a deactivated account" in chunk_decoded:
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error_msg = "[Local Message] You are associated with a deactivated account. OpenAI以账户失效为由, 拒绝服务." + openai_website
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elif "API key has been deactivated" in chunk_decoded:
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error_msg = "[Local Message] API key has been deactivated. OpenAI以账户失效为由, 拒绝服务." + openai_website
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elif "bad forward key" in chunk_decoded:
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error_msg = "[Local Message] Bad forward key. API2D账户额度不足."
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elif "Not enough point" in chunk_decoded:
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error_msg = "[Local Message] Not enough point. API2D账户点数不足."
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elif 'error' in str(chunk_decoded).lower():
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try:
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error_msg = json.dumps(json.loads(chunk_decoded[:6]), indent=4, ensure_ascii=False)
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except:
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error_msg = chunk_decoded
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return error_msg
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def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream=True, additional_fn=None):
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chatbot.append([inputs, ""])
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if additional_fn is not None:
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from core_functional import handle_core_functionality
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inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
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yield from update_ui(chatbot=chatbot, history=history, msg="等待响应") # 刷新界面
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gpt_bro_init = MoonShotInit()
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history.extend([inputs, ''])
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stream_response = gpt_bro_init.generate_messages(inputs, llm_kwargs, history, system_prompt, stream)
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for content, gpt_bro_result, error_bro_meg in stream_response:
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chatbot[-1] = [inputs, gpt_bro_result]
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history[-1] = gpt_bro_result
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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if error_bro_meg:
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chatbot[-1] = [inputs, error_bro_meg]
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history = history[:-2]
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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break
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def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None,
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console_slience=False):
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gpt_bro_init = MoonShotInit()
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watch_dog_patience = 60 # 看门狗的耐心, 设置10秒即可
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stream_response = gpt_bro_init.generate_messages(inputs, llm_kwargs, history, sys_prompt, True)
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gpt_bro_result = ''
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for content, gpt_bro_result, error_bro_meg in stream_response:
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gpt_bro_result += content
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if error_bro_meg:
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if len(observe_window) >= 3:
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observe_window[2] = error_bro_meg
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return f'{gpt_bro_result} 对话错误'
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# 观测窗
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if len(observe_window) >= 1:
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observe_window[0] = gpt_bro_result
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if len(observe_window) >= 2:
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if (time.time() - observe_window[1]) > watch_dog_patience:
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observe_window[2] = "请求超时，程序终止。"
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raise RuntimeError(f"{gpt_bro_result} 程序终止。")
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return gpt_bro_result
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if __name__ == '__main__':
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moon_ai = MoonShotInit()
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for g in moon_ai.generate_messages('hello', {'llm_model': 'moonshot-v1-8k'},
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[], '', True):
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print(g)
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