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