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30 lines
1.1 KiB
Python
30 lines
1.1 KiB
Python
# coding=utf-8
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import argparse
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from fastllm_pytools import llm
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def args_parser():
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parser = argparse.ArgumentParser(description = 'qwen_chat_demo')
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parser.add_argument('-p', '--path', type = str, required = True, default = '', help = '模型文件的路径')
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args = parser.parse_args()
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return args
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if __name__ == "__main__":
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args = args_parser()
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model = llm.model(args.path)
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history = []
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print("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：")
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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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history = []
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print("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("AI:", end = "")
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curResponse = ""
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for response in model.stream_response(query, history = history, do_sample = True, top_p = 0.8, top_k = 1, temperature = 1.0, repeat_penalty = 1.0):
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curResponse += response
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print(response, flush = True, end = "")
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history.append((query, curResponse)) |