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# coding=utf-8
# Implement stream chat in command line for ChatGLM fine-tuned with PEFT.
# This code is largely borrowed from https://github.com/THUDM/ChatGLM-6B/blob/main/cli_demo.py
import os
import signal
import platform
from utils import ModelArguments, load_pretrained
from transformers import HfArgumentParser
os_name = platform.system()
clear_command = "cls" if os_name == "Windows" else "clear"
stop_stream = False
welcome = "欢迎使用 ChatGLM-6B 模型，输入内容即可对话，clear清空对话历史，stop终止程序"
def build_prompt(history):
prompt = welcome
for query, response in history:
prompt += f"\n\nUser: {query}"
prompt += f"\n\nChatGLM-6B: {response}"
return prompt
def signal_handler(signal, frame):
global stop_stream
stop_stream = True
def main():
global stop_stream
parser = HfArgumentParser(ModelArguments)
model_args, = parser.parse_args_into_dataclasses()
model, tokenizer = load_pretrained(model_args)
model = model.cuda()
model.eval()
history = []
print(welcome)
while True:
try:
query = input("\nInput: ")
except UnicodeDecodeError:
print("Detected decoding error at the inputs, please set the terminal encoding to utf-8.")
continue
except Exception:
raise
if query.strip() == "stop":
break
if query.strip() == "clear":
history = []
os.system(clear_command)
print(welcome)
continue
count = 0
for _, 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()
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