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import os
import platform
import signal
from transformers import AutoTokenizer , AutoModel
tokenizer = AutoTokenizer . from_pretrained ( " THUDM/chatglm-6b " , trust_remote_code = True )
model = AutoModel . from_pretrained ( " THUDM/chatglm-6b " , trust_remote_code = True ) . half ( ) . cuda ( )
model = model . eval ( )
os_name = platform . system ( )
clear_command = ' cls ' if os_name == ' Windows ' else ' clear '
stop_stream = False
def build_prompt ( history ) :
prompt = " 欢迎使用 ChatGLM-6B 模型, 输入内容即可进行对话, clear 清空对话历史, stop 终止程序 "
for query , response in history :
prompt + = f " \n \n 用户: { query } "
prompt + = f " \n \n ChatGLM-6B: { response } "
return prompt
def signal_handler ( signal , frame ) :
global stop_stream
stop_stream = True
def main ( ) :
history = [ ]
global stop_stream
print ( " 欢迎使用 ChatGLM-6B 模型, 输入内容即可进行对话, clear 清空对话历史, stop 终止程序 " )
while True :
query = input ( " \n 用户: " )
if query == " stop " :
break
if query == " clear " :
history = [ ]
os . system ( clear_command )
print ( " 欢迎使用 ChatGLM-6B 模型, 输入内容即可进行对话, clear 清空对话历史, stop 终止程序 " )
continue
count = 0
for response , history in model . stream_chat ( tokenizer , query , history = history ) :
if stop_stream :
stop_stream = False
break
else :
count + = 1
if count % 8 == 0 :
os . system ( clear_command )
print ( build_prompt ( history ) , flush = True )
signal . signal ( signal . SIGINT , signal_handler )
os . system ( clear_command )
print ( build_prompt ( history ) , flush = True )
if __name__ == " __main__ " :
main ( )