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import os
import platform
import signal
import time
from transformers import AutoTokenizer, AutoModel
from multi_input import MultiInputInCmd
if __name__ == "__main__":
tokenizer = AutoTokenizer.from_pretrained("E:\ProjectEX\LLM\ChatGLM-6B\chatglm-6b-int4", trust_remote_code=True)
model = AutoModel.from_pretrained("E:\ProjectEX\LLM\ChatGLM-6B\chatglm-6b-int4", trust_remote_code=True).float()
model = model.quantize(bits=4,
kernel_file="E:\ProjectEX\LLM\ChatGLM-6B\chatglm-6b-int4\quantization_kernels_parallel.so")
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\nChatGLM-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：")
input_fun = MultiInputInCmd("\n用户：")
all_input_lines = input_fun.run()
# handle as normal message
query = ''
for index in range(len(all_input_lines)):
if index == len(all_input_lines) - 1:
query = query + all_input_lines[index]
else:
query = query + all_input_lines[index] + '\n'
if query.strip() == "stop":
break
if query.strip() == "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
last_index = 0
start = time.time()
for response, history in model.stream_chat(tokenizer, query, history=history):
if stop_stream:
stop_stream = False
break
else:
print(response[last_index:], end='', flush=True)
last_index = len(response)
signal.signal(signal.SIGINT, signal_handler)
print((time.time() - start) / last_index)
print('')
main() |