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import os
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import platform
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import signal
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import sys
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from transformers import AutoTokenizer, AutoModel
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import readline
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tokenizer = AutoTokenizer.from_pretrained("THUDM/visualglm-6b", trust_remote_code=True)
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model = AutoModel.from_pretrained("THUDM/visualglm-6b", trust_remote_code=True).half().cuda()
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model = model.eval()
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os_name = platform.system()
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clear_command = 'cls' if os_name == 'Windows' else 'clear'
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stop_stream = False
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def build_prompt(history, prefix):
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prompt = prefix
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for query, response in history:
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prompt += f"\n\n用户：{query}"
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prompt += f"\n\nChatGLM-6B：{response}"
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return prompt
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def signal_handler(signal, frame):
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global stop_stream
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stop_stream = True
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def main():
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global stop_stream
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while True:
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history = []
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prefix = "欢迎使用 VisualGLM-6B 模型，输入图片路径和内容即可进行对话，clear 清空对话历史，stop 终止程序"
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print(prefix)
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image_path = input("\n请输入图片路径：")
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if image_path == "stop":
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break
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prefix = prefix + "\n" + image_path
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query = "描述这张图片。"
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while True:
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count = 0
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for response, history in model.stream_chat(tokenizer, image_path, query, history=history):
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if stop_stream:
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stop_stream = False
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break
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else:
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count += 1
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if count % 8 == 0:
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os.system(clear_command)
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print(build_prompt(history, prefix), flush=True)
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signal.signal(signal.SIGINT, signal_handler)
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os.system(clear_command)
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print(build_prompt(history, prefix), flush=True)
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query = input("\n用户：")
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if query.strip() == "clear":
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break
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if query.strip() == "stop":
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sys.exit(0)
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if __name__ == "__main__":
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main()
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