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import time | |
from toolbox import update_ui, get_conf, update_ui_lastest_msg | |
from toolbox import check_packages, report_exception | |
model_name = '云雀大模型' | |
def validate_key(): | |
YUNQUE_SECRET_KEY = get_conf("YUNQUE_SECRET_KEY") | |
if YUNQUE_SECRET_KEY == '': return False | |
return True | |
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", | |
observe_window:list=[], console_slience:bool=False): | |
""" | |
⭐ 多线程方法 | |
函数的说明请见 request_llms/bridge_all.py | |
""" | |
watch_dog_patience = 5 | |
response = "" | |
if validate_key() is False: | |
raise RuntimeError('请配置YUNQUE_SECRET_KEY') | |
from .com_skylark2api import YUNQUERequestInstance | |
sri = YUNQUERequestInstance() | |
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_llms/bridge_all.py | |
""" | |
chatbot.append((inputs, "")) | |
yield from update_ui(chatbot=chatbot, history=history) | |
# 尝试导入依赖,如果缺少依赖,则给出安装建议 | |
try: | |
check_packages(["zhipuai"]) | |
except: | |
yield from update_ui_lastest_msg(f"导入软件依赖失败。使用该模型需要额外依赖,安装方法```pip install --upgrade zhipuai```。", | |
chatbot=chatbot, history=history, delay=0) | |
return | |
if validate_key() is False: | |
yield from update_ui_lastest_msg(lastmsg="[Local Message] 请配置HUOSHAN_API_KEY", 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_skylark2api import YUNQUERequestInstance | |
sri = YUNQUERequestInstance() | |
response = f"[Local Message] 等待{model_name}响应中 ..." | |
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) |