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464 lines
26 KiB
464 lines
26 KiB
# coding=utf-8
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from UI工具 import *
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import gradio as gr
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webui_title = """▶▶▶▶智能菜单系统◀◀◀◀"""
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with gr.Blocks() as demo:
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gr.Markdown(webui_title)
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with gr.Tab("菜单推荐"):
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with gr.Tab("基于知识库的推荐"):
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with gr.Row():
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with gr.Column(scale=10):
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chatbot = gr.Chatbot([[None,zhishiku_init1]],label='基于知识库的菜单推荐',show_label=True,height=850)
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query = gr.Textbox(show_label=True, label="请输入你的喜好，按回车提交")
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with gr.Column(scale=5):
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knowledge_set = gr.Accordion("知识库更新", visible=True,open=False)
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answer_set = gr.Accordion("回答参数设置", visible=True,open=False)
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with knowledge_set:
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O_data_path = gr.Textbox(label="数据储存地址",
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placeholder=args.original_data_path,
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lines=1,
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interactive=True,
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visible=True)
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P_data_path = gr.Textbox(label="向量库保存地址",
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placeholder=args.preprocessed_data_path,
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lines=1,
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interactive=True,
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visible=True)
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emb_name = gr.Textbox(label="embedding模型",
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placeholder='默认模型：'+args.embeddings_model_name,
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lines=1,
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interactive=True,
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visible=True)
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chunk_size = gr.Number(value=args.chunk_size,
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label="数据切分最大长度",
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interactive=True,
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visible=True,
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minimum=1,
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precision=0)
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chunk_overlap = gr.Number(value=args.chunk_overlap,
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label="数据片段最大重合",
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interactive=True,
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visible=True,
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minimum=0,
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precision=0)
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chunk_size.change(fn=change_chunk_size,
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inputs=[chunk_size],
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outputs=[])
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chunk_overlap.change(fn=change_chunk_overlap,
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inputs=[chunk_overlap],
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outputs=[])
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db_update = gr.Button(value="更新知识库", visible=True)
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O_data_path.change(fn=change_data_path,
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inputs=[O_data_path],
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outputs=[])
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P_data_path.change(fn=change_P_data_path,
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inputs=[P_data_path],
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outputs=[])
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emb_name.change(fn=change_emb_name,
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inputs=[emb_name],
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outputs=[])
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db_update.click(fn=db_update_click1,
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inputs=[chatbot],
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outputs=[chatbot])
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with answer_set:
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search_top_k = gr.Number(value=args.topk_1,
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label="获取知识库内容条数",
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interactive=True,
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visible=True,
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minimum=1,
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maximum=50,
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precision=0)
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model_name = gr.Textbox(label="模型名字",
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placeholder=args.pretrained_model_name,
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lines=1,
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interactive=True,
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visible=True)
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model_top_k = gr.Number(value=args.topk,
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label="模型回答tok",
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interactive=True,
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visible=True,
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minimum=1,
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maximum=50,
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precision=0)
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model_temperature = gr.Slider(0, 1,
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value=args.temperature,
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step=0.01,
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label="模型回答温度",
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interactive=True)
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search_top_k.change(fn=change_search_top_k,
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inputs=[search_top_k],
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outputs=[])
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model_top_k.change(fn=change_model_top_k,
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inputs=[model_top_k],
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outputs=[])
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model_temperature.change(fn=change_model_temperature,
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inputs=[model_temperature],
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outputs=[])
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model_name.change(fn=change_model_name,
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inputs=[model_name],
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outputs=[])
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query.submit(fn=get_answer,
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inputs=[query, chatbot],
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outputs=[chatbot, query])
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clear = gr.ClearButton([chatbot], value='清除记录')
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clear_cash = gr.Button(value="清理显存", visible=True)
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clear_cash.click(fn=clean_memory,
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inputs=[chatbot],
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outputs=[chatbot])
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with gr.Tab("基于菜单的推荐"):
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with gr.Row():
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with gr.Column(scale=10):
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chatbot = gr.Chatbot([[None,caidan_init0]],label='基于菜单的推荐', show_label=True,height=850)
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query = gr.Textbox(show_label=True, label="请输入你的喜好，按回车提交")
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with gr.Column(scale=5):
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with gr.Tab("上传pdf菜单"):
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caidan = gr.Textbox(label="菜单地址",
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placeholder=args.path_caidan,
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lines=1,
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interactive=True,
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visible=True)
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caidan.change(fn=change_caidan_path,
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inputs=[caidan])
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with gr.Tab("添加图片文件"):
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tu_caidan = gr.Image(label="添加图片文件", show_label=False, type='filepath')
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tu_caidan.change(fn=change_caidan_path,
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inputs=[tu_caidan])
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answer_set = gr.Accordion("回答参数设置", visible=True, open=True)
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with answer_set:
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model_name = gr.Textbox(label="模型名字",
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placeholder="默认模型："+args.pretrained_model_name,
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lines=1,
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interactive=True,
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visible=True)
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model_top_k = gr.Number(value=args.topk,
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label="模型回答tok",
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interactive=True,
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visible=True,
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minimum=1,
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maximum=50,
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precision=0,)
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model_temperature = gr.Slider(0, 1,
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value=args.temperature,
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step=0.01,
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label="模型回答温度",
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interactive=True)
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model_top_k.change(fn=change_model_top_k,
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inputs=[model_top_k],
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outputs=[])
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model_temperature.change(fn=change_model_temperature,
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inputs=[model_temperature],
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outputs=[])
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model_name.change(fn=change_model_name,
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inputs=[model_name],
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outputs=[])
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query.submit(fn=get_answer_caidan,
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inputs=[query, chatbot],
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outputs=[chatbot, query])
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clear1 = gr.ClearButton([chatbot], value='清除记录')
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clear_cash = gr.Button(value="清理显存", visible=True)
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clear_cash.click(fn=clean_memory,
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inputs=[chatbot],
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outputs=[chatbot])
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with gr.Tab("大模型随机推荐"):
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with gr.Row():
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with gr.Column(scale=10):
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chatbot = gr.Chatbot([[None,damodel_init0]],label='大模型随机推荐', show_label=True, height=850)
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query = gr.Textbox(label='请输入你的喜好，按回车提交',show_label=True)
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with gr.Column(scale=5):
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answer_set = gr.Accordion("回答参数设置", visible=True)
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with answer_set:
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model_name = gr.Textbox(label="模型名字",
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placeholder="默认模型："+ args.pretrained_model_name,
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lines=1,
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interactive=True,
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visible=True)
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model_top_k = gr.Number(value=args.topk,
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label="模型回答tok",
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interactive=True,
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visible=True,
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minimum=1,
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maximum=50,
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precision=0,
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)
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model_temperature = gr.Slider(0, 1,
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value=args.temperature,
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step=0.01,
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label="模型回答温度",
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interactive=True)
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model_top_k.change(fn=change_model_top_k,
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inputs=[model_top_k],
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outputs=[])
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model_temperature.change(fn=change_model_temperature,
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inputs=[model_temperature],
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outputs=[])
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model_name.change(fn=change_model_name,
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inputs=[model_name],
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outputs=[])
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query.submit(fn=get_answer_model,
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inputs=[query, chatbot],
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outputs=[chatbot, query])
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clear2 = gr.ClearButton([chatbot], value='清除记录')
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clear_cash = gr.Button(value="清理显存", visible=True)
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clear_cash.click(fn=clean_memory,
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inputs=[chatbot],
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outputs=[chatbot])
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with gr.Tab("自定义推荐"):
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with gr.Row():
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with gr.Column(scale=10):
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chatbot = gr.Chatbot(label='自定义推荐', show_label=True, height=850)
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clear3 = gr.ClearButton([chatbot], value='清除记录')
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with gr.Column(scale=5):
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with gr.Tab("从文件中获取随机内容"):
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suijidz = gr.Textbox(label="随机内容地址",
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placeholder='默认地址：'+ args.path_zidingyi,
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lines=1,
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interactive=True,
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visible=True)
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suiji_num = gr.Number(value=args.num_select,
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label="随机数目",
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minimum=1,
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precision=0,
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interactive=True)
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suijidz.change(fn=change_path_zidingyi,
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inputs=[suijidz],
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outputs=[suijidz])
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suiji_num.input(fn=change_suiji_num,
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inputs=[suiji_num])
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suiji_1 = gr.Button(value="开始随机", visible=True)
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suiji_1.click(fn=Random_selection1,
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inputs=[chatbot],
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outputs=[chatbot])
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with gr.Tab("手动输入随机内容"):
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suiji_nr2 = gr.Textbox(label="请输入随机内容",
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placeholder='在这输入随机内容，一行是一条内容',
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lines=12,
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interactive=True,
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visible=True)
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suiji_num = gr.Number(value=args.num_select,
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label="随机数目",
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minimum=1,
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precision=0,
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interactive=True)
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suiji_num.input(fn=change_suiji_num,
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inputs=[suiji_num])
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suiji_2 = gr.Button(value="开始随机", visible=True)
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suiji_2.click(fn=Random_selection2,
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inputs=[chatbot,suiji_nr2],
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outputs=[chatbot])
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with gr.Tab("智能识别"):
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with gr.Row():
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with gr.Column(scale=10):
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Chatbot = gr.Chatbot([[None,zhinengshibie]],label='智能识别', show_label=True, height=850)
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clear4 = gr.ClearButton([Chatbot], value='清除记录')
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with gr.Column(scale=4):
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mode1 = gr.Radio(["菜品识别", "果蔬识别"],label="识别模式",value='菜品识别')
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answer_set = gr.Accordion("参数设置", visible=True,open=False)
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with answer_set:
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shitu_top_k = gr.Number(value=args.top_num,
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label="模型回答tok",
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interactive=True,
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visible=True,
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minimum=1,
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maximum=20,
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precision=0,
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)
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shitu_filter_threshold = gr.Slider(0, 1,
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value=args.filter_threshold,
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step=0.01,
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label="图片识别阈值",
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interactive=True)
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shitu_baike_num = gr.Number(value=args.baike_num,
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label="百科回答数",
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interactive=True,
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visible=True,
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minimum=1,
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maximum=20,
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precision=0)
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shitu_top_k.change(fn=change_shitu_top_k,
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inputs=[shitu_top_k])
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shitu_filter_threshold.change(fn=change_shitu_filter_threshold,
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inputs=[shitu_filter_threshold])
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shitu_baike_num.change(fn=change_shitu_baike_num,
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inputs=[shitu_baike_num])
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with gr.Tab("添加图片文件"):
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filepath = gr.Image(label="添加图片文件",show_label=False,type='filepath')
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tupian_sb = gr.Button(value="开启图片识别", visible=True)
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tupian_sb.click(fn=tupian_shibie,
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inputs=[mode1,filepath,Chatbot],
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outputs=[Chatbot])
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with gr.Tab("菜单规划"):
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with gr.Row():
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with gr.Column(scale=10):
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chatbot = gr.Chatbot([],label='菜单规划',show_label=True, height=850)
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query = gr.Textbox(show_label=True, label="请输入你的食材，按回车提交")
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query2 = gr.Textbox(show_label=True, label="请输入你想制作的菜肴进行询问，按回车提交")
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with gr.Column(scale=5):
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mode2 = gr.Radio(["启用", "不启用"], label="是否启用知识库", value='启用')
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knowledge_set = gr.Accordion("知识库设定", visible=True,open=False)
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answer_set = gr.Accordion("回答参数设置", visible=True, open=False)
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with knowledge_set:
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O_data_path = gr.Textbox(label="数据储存地址",
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placeholder=args.original_data_path_g,
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lines=1,
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interactive=True,
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visible=True)
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P_data_path = gr.Textbox(label="向量库保存地址",
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placeholder=args.preprocessed_data_path_g,
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lines=1,
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interactive=True,
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visible=True)
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emb_name = gr.Textbox(label="embedding模型",
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placeholder='默认模型：' + args.embeddings_model_name,
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lines=1,
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interactive=True,
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visible=True)
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chunk_size = gr.Number(value=args.chunk_size,
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label="数据切分最大长度",
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interactive=True,
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visible=True,
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minimum=1,
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precision=0)
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chunk_overlap = gr.Number(value=args.chunk_overlap,
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label="数据片段最大重合",
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interactive=True,
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visible=True,
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minimum=0,
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precision=0)
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chunk_size.change(fn=change_chunk_size,
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inputs=[chunk_size],
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outputs=[])
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chunk_overlap.change(fn=change_chunk_overlap,
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inputs=[chunk_overlap],
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outputs=[])
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db_update = gr.Button(value="更新知识库", visible=True)
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O_data_path.change(fn=change_data_path_g,
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inputs=[O_data_path],
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outputs=[])
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P_data_path.change(fn=change_P_data_path_g,
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inputs=[P_data_path],
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outputs=[])
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emb_name.change(fn=change_emb_name,
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inputs=[emb_name],
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outputs=[])
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db_update.click(fn=db_update_click,
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inputs=[chatbot],
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outputs=[chatbot])
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with answer_set:
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search_top_k = gr.Number(value=args.topk_1,
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label="获取知识库内容条数",
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interactive=True,
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visible=True,
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minimum=1,
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maximum=50,
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precision=0)
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model_name = gr.Textbox(label="模型名字",
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placeholder=args.pretrained_model_name,
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lines=1,
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interactive=True,
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visible=True)
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model_top_k = gr.Number(value=args.topk,
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label="模型回答tok",
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interactive=True,
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visible=True,
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minimum=1,
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maximum=50,
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precision=0)
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model_temperature = gr.Slider(0, 1,
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value=args.temperature,
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step=0.01,
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label="模型回答温度",
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interactive=True)
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search_top_k.change(fn=change_search_top_k,
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inputs=[search_top_k],
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outputs=[])
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model_top_k.change(fn=change_model_top_k,
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inputs=[model_top_k],
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outputs=[])
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model_temperature.change(fn=change_model_temperature,
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inputs=[model_temperature],
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outputs=[])
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model_name.change(fn=change_model_name,
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inputs=[model_name],
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outputs=[])
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query.submit(fn=get_answer_guihua,
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inputs=[query, chatbot,mode2],
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outputs=[chatbot, query])
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query2.submit(fn=get_answer_guihua2,
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inputs=[query2, chatbot, mode2],
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outputs=[chatbot, query2])
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clear5 = gr.ClearButton([chatbot], value='清除记录')
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clear_cash = gr.Button(value="清理显存", visible=True)
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clear_cash.click(fn=clean_memory,
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inputs=[chatbot],
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outputs=[chatbot])
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with gr.Tab("自由对话"):
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with gr.Row():
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with gr.Column(scale=10):
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chatbot = gr.Chatbot([],label='自由对话',show_label=True, height=950)
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query = gr.Textbox(show_label=True, label="在这输入，开始自由对话")
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with gr.Column(scale=5):
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model_name = gr.Textbox(label="模型名字",
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placeholder=args.pretrained_model_name,
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lines=1,
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interactive=True,
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visible=True)
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model_top_k = gr.Number(value=args.topk,
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label="模型回答tok",
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interactive=True,
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visible=True,
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minimum=1,
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maximum=50,
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precision=0)
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model_temperature = gr.Slider(0, 1,
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value=args.temperature,
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step=0.01,
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label="模型回答温度",
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interactive=True)
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model_top_k.change(fn=change_model_top_k,
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inputs=[model_top_k],
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outputs=[])
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model_temperature.change(fn=change_model_temperature,
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inputs=[model_temperature],
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outputs=[])
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model_name.change(fn=change_model_name,
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inputs=[model_name],
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outputs=[])
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query.submit(fn=ziyouduihau,
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inputs=[query, chatbot],
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outputs=[chatbot, query])
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clear6 = gr.ClearButton([chatbot], value='清除记录')
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demo.queue(concurrency_count=3).launch(server_name='localhost',server_port=7989) |