import time import threading import importlib from toolbox import update_ui, get_conf, update_ui_lastest_msg from multiprocessing import Process, Pipe model_name = '星火认知大模型' def validate_key(): XFYUN_APPID, = get_conf('XFYUN_APPID', ) if XFYUN_APPID == '00000000' or XFYUN_APPID == '': return False return True def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=[], console_slience=False): """ ⭐多线程方法 函数的说明请见 request_llm/bridge_all.py """ watch_dog_patience = 5 response = "" if validate_key() is False: raise RuntimeError('请配置讯飞星火大模型的XFYUN_APPID, XFYUN_API_KEY, XFYUN_API_SECRET') from .com_sparkapi import SparkRequestInstance sri = SparkRequestInstance() for response in sri.generate(inputs, llm_kwargs, history, sys_prompt): if len(observe_window) >= 1: observe_window[0] = response if len(observe_window) >= 2: if (time.time()-observe_window[1]) > watch_dog_patience: raise RuntimeError("程序终止。") return response def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None): """ ⭐单线程方法 函数的说明请见 request_llm/bridge_all.py """ chatbot.append((inputs, "")) yield from update_ui(chatbot=chatbot, history=history) if validate_key() is False: yield from update_ui_lastest_msg(lastmsg="[Local Message]: 请配置讯飞星火大模型的XFYUN_APPID, XFYUN_API_KEY, XFYUN_API_SECRET", chatbot=chatbot, history=history, delay=0) return if additional_fn is not None: from core_functional import handle_core_functionality inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot) # 开始接收回复 from .com_sparkapi import SparkRequestInstance sri = SparkRequestInstance() for response in sri.generate(inputs, llm_kwargs, history, system_prompt): chatbot[-1] = (inputs, response) yield from update_ui(chatbot=chatbot, history=history) # 总结输出 if response == f"[Local Message]: 等待{model_name}响应中 ...": response = f"[Local Message]: {model_name}响应异常 ..." history.extend([inputs, response]) yield from update_ui(chatbot=chatbot, history=history)