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44 lines
1.9 KiB
Python
44 lines
1.9 KiB
Python
from gradio_client import Client
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# 该函数通过调用Gradio Client API与RKLLM模型进行交互
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def chat_with_rkllm(user_message, history=[]):
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# 实例化Gradio Client，用户需要根据自己部署的具体网址进行修改
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client = Client("http://172.16.10.102:8080/")
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# 调用Gradio Client API进行交互，内部的API主要包括：
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# /get_user_input：模型获取用户输入，并将输入添加至历史记录history
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# /get_RKLLM_output：RKLLM利用已包含输入的历史记录history生成回复
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_, history = client.predict(user_message=user_message, history=history, api_name="/get_user_input")
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result_history = client.predict(history=history, api_name="/get_RKLLM_output")
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return result_history
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if __name__ == '__main__':
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#初始化聊天记录
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result_history = []
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print("============================")
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print("在终端中输入您的问题，即可与 RKLLM 模型进行对话....")
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print("============================")
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# 进入循环，持续获取用户输入，并与RKLLM模型进行对话
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while True:
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try:
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user_message = input("请输入您的问题：")
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if user_message == "exit":
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print("============================")
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print("程序正在退出......")
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print("============================")
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break
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else:
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# 调用chat_with_rkllm函数，获取模型的回复
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result_history = chat_with_rkllm(user_message, result_history)
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# 打印模型输出
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print("Q:", result_history[-1][0])
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print("A:", result_history[-1][1])
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except KeyboardInterrupt:
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print("\n")
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print("============================")
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print("程序正在退出......")
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print("============================")
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break
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