镜像自地址
https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-06 14:36:48 +00:00
83 行
3.7 KiB
Python
83 行
3.7 KiB
Python
|
|
from transformers import AutoModel, AutoTokenizer
|
|
import time
|
|
import importlib
|
|
from toolbox import update_ui, get_conf
|
|
|
|
|
|
global chatglm_model, chatglm_tokenizer
|
|
|
|
chatglm_model = None
|
|
chatglm_tokenizer = None
|
|
|
|
def model_loader():
|
|
global chatglm_model, chatglm_tokenizer
|
|
if chatglm_tokenizer is None:
|
|
chatglm_tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True)
|
|
if chatglm_model is None: # 尚未加载
|
|
device, = get_conf('LOCAL_MODEL_DEVICE')
|
|
if device=='cpu':
|
|
chatglm_model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).float()
|
|
else:
|
|
chatglm_model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).half().cuda()
|
|
chatglm_model = chatglm_model.eval()
|
|
chatglm_model = chatglm_model.eval()
|
|
|
|
def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
|
|
"""
|
|
函数的说明请见 request_llm/bridge_all.py
|
|
"""
|
|
global chatglm_model, chatglm_tokenizer
|
|
if chatglm_model is None:
|
|
observe_window[0] = "ChatGLM尚未加载，加载需要一段时间 ……"
|
|
|
|
model_loader()
|
|
# chatglm 没有 sys_prompt 接口，因此把prompt加入 history
|
|
history_feedin = []
|
|
for i in range(len(history)//2):
|
|
history_feedin.append(["What can I do?", sys_prompt] )
|
|
history_feedin.append([history[2*i], history[2*i+1]] )
|
|
|
|
watch_dog_patience = 5 # 看门狗 (watchdog) 的耐心, 设置5秒即可
|
|
response = ""
|
|
for response, history in chatglm_model.stream_chat(chatglm_tokenizer, inputs, history=history_feedin, max_length=llm_kwargs['max_length'],
|
|
top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
|
|
# 观测窗，把已经获取的数据显示出去
|
|
observe_window[0] = response
|
|
# 看门狗 (watchdog)，如果超过期限没有喂狗，则终止
|
|
if len(observe_window) >= 2:
|
|
if (time.time()-observe_window[1]) > watch_dog_patience:
|
|
raise RuntimeError("程序终止。")
|
|
# if not console_slience:
|
|
# print(response)
|
|
return response
|
|
|
|
|
|
def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
|
|
"""
|
|
函数的说明请见 request_llm/bridge_all.py
|
|
"""
|
|
global chatglm_model, chatglm_tokenizer
|
|
chatbot.append((inputs, ""))
|
|
if chatglm_model is None:
|
|
chatbot[-1] = (inputs, "ChatGLM尚未加载，加载需要一段时间 ……")
|
|
yield from update_ui(chatbot=chatbot, history=[])
|
|
model_loader()
|
|
|
|
if additional_fn is not None:
|
|
import core_functional
|
|
importlib.reload(core_functional) # 热更新prompt
|
|
core_functional = core_functional.get_core_functions()
|
|
if "PreProcess" in core_functional[additional_fn]: inputs = core_functional[additional_fn]["PreProcess"](inputs) # 获取预处理函数（如果有的话）
|
|
inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
|
|
|
|
|
|
history_feedin = []
|
|
for i in range(len(history)//2):
|
|
history_feedin.append(["What can I do?", system_prompt] )
|
|
history_feedin.append([history[2*i], history[2*i+1]] )
|
|
|
|
for response, history in chatglm_model.stream_chat(chatglm_tokenizer, inputs, history=history_feedin, max_length=llm_kwargs['max_length'],
|
|
top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
|
|
chatbot[-1] = (inputs, response)
|
|
yield from update_ui(chatbot=chatbot, history=history) |