60 lines
3.2 KiB
Python
60 lines
3.2 KiB
Python
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import os
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import platform
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import signal
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from transformers import AutoTokenizer, AutoModel
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import readline
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tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm3-6b", trust_remote_code=True)
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model = AutoModel.from_pretrained("THUDM/chatglm3-6b", trust_remote_code=True).cuda()
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# 多显卡支持，使用下面两行代替上面一行，将num_gpus改为你实际的显卡数量
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# from utils import load_model_on_gpus
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# model = load_model_on_gpus("THUDM/chatglm3-6b", num_gpus=2)
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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):
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prompt = "欢迎使用 ChatGLM3-6B 模型，输入内容即可进行对话，clear 清空对话历史，stop 终止程序"
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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\nChatGLM3-6B：{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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tools = [{'name': 'track', 'description': '追踪指定股票的实时价格', 'parameters': {'type': 'object', 'properties': {'symbol': {'description': '需要追踪的股票代码'}}, 'required': []}}, {'name': '/text-to-speech', 'description': '将文本转换为语音', 'parameters': {'type': 'object', 'properties': {'text': {'description': '需要转换成语音的文本'}, 'voice': {'description': '要使用的语音类型（男声、女声等）'}, 'speed': {'description': '语音的速度（快、中等、慢等）'}}, 'required': []}}, {'name': '/image_resizer', 'description': '调整图片的大小和尺寸', 'parameters': {'type': 'object', 'properties': {'image_file': {'description': '需要调整大小的图片文件'}, 'width': {'description': '需要调整的宽度值'}, 'height': {'description': '需要调整的高度值'}}, 'required': []}}, {'name': '/foodimg', 'description': '通过给定的食品名称生成该食品的图片', 'parameters': {'type': 'object', 'properties': {'food_name': {'description': '需要生成图片的食品名称'}}, 'required': []}}]
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system_item = {"role": "system",
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"content": "Answer the following questions as best as you can. You have access to the following tools:",
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"tools": tools}
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def main():
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past_key_values, history = None, [system_item]
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role = "user"
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global stop_stream
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print("欢迎使用 ChatGLM3-6B 模型，输入内容即可进行对话，clear 清空对话历史，stop 终止程序")
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while True:
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query = input("\n用户：") if role == "user" else input("\n结果：")
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if query.strip() == "stop":
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break
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if query.strip() == "clear":
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past_key_values, history = None, [system_item]
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role = "user"
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os.system(clear_command)
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print("欢迎使用 ChatGLM3-6B 模型，输入内容即可进行对话，clear 清空对话历史，stop 终止程序")
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continue
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print("\nChatGLM：", end="")
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response, history = model.chat(tokenizer, query, history=history, role=role)
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print(response, end="", flush=True)
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print("")
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if isinstance(response, dict):
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role = "observation"
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if __name__ == "__main__":
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main()
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