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import os
import platform
import signal
import sys

from transformers import AutoTokenizer, AutoModel
import readline

tokenizer = AutoTokenizer.from_pretrained("THUDM/visualglm-6b", trust_remote_code=True)
model = AutoModel.from_pretrained("THUDM/visualglm-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, prefix):
    prompt = prefix
    for query, response in history:
        prompt += f"\n\n็”จๆˆท๏ผš{query}"
        prompt += f"\n\nChatGLM-6B๏ผš{response}"
    return prompt


def signal_handler(signal, frame):
    global stop_stream
    stop_stream = True


def main():
    global stop_stream
    while True:
        history = []
        prefix = "ๆฌข่ฟŽไฝฟ็”จ VisualGLM-6B ๆจกๅž‹๏ผŒ่พ“ๅ…ฅๅ›พ็‰‡่ทฏๅพ„ๅ’Œๅ†…ๅฎนๅณๅฏ่ฟ›่กŒๅฏน่ฏ๏ผŒclear ๆธ…็ฉบๅฏน่ฏๅŽ†ๅฒ๏ผŒstop ็ปˆๆญข็จ‹ๅบ"
        print(prefix)
        image_path = input("\n่ฏท่พ“ๅ…ฅๅ›พ็‰‡่ทฏๅพ„๏ผš")
        if image_path == "stop":
            break
        prefix = prefix + "\n" + image_path
        query = "ๆ่ฟฐ่ฟ™ๅผ ๅ›พ็‰‡ใ€‚"
        while True:
            count = 0
            for response, history in model.stream_chat(tokenizer, image_path, 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, prefix), flush=True)
                        signal.signal(signal.SIGINT, signal_handler)
            os.system(clear_command)
            print(build_prompt(history, prefix), flush=True)
            query = input("\n็”จๆˆท๏ผš")
            if query.strip() == "clear":
                break
            if query.strip() == "stop":
                sys.exit(0)


if __name__ == "__main__":
    main()