import gradio as gr from scrape_3gpp import * from excel_chat import * from classification import * from chart_generation import * from charts_advanced import * # def update_label(label1): # return gr.update(choices=list(df.columns)) with gr.Blocks() as demo: gr.Markdown("## Extaction, Classification and AI tool") with gr.Tab("File extraction"): gr.Markdown(" Put either just a link, or a link and an excel file with an 'Actions' column") tb_url = gr.Textbox(label="URL (e.g. https://www.3gpp.org/ftp/TSG_SA/WG1_Serv/TSGS1_105_Athens/Docs)") btn_extract = gr.Button("Extract excel from URL") tb_status_message = gr.Textbox(label="Status") with gr.Tab("Query on columns with mistral"): dd_source_ask = gr.Dropdown(label="Source Column(s)", multiselect=True) tb_destcol = gr.Textbox(label="Destination column label (e.g. Summary, ELI5, PAB)") tb_prompt = gr.Textbox(label="Prompt") tb_filename = gr.Textbox(label="Specific File Name (Optional)") mist_button = gr.Button("Ask AI") with gr.Tab("Classification by topic"): dd_source_class = gr.Dropdown(label="Source Column(s)", multiselect=False) btn_classif = gr.Button("Categorize") with gr.Tab("Charts Generation"): with gr.Row(): dd_label1 = gr.Dropdown(label="Source Column", multiselect=False) dd_label2 = gr.Dropdown(label="Source Column", multiselect=False) btn_chart = gr.Button("Generate Bar Plot") plt_figure = gr.Plot() with gr.Tab("Chart Generation"): with gr.Tab("Overall"): btn_overall = gr.Button("Overall Review") with gr.Tab("By Expert"): rd_exp=gr.Radio(["Satellite Networks / Nicolas", "Emergency Communication / Dorin", "Trend Analysis / Ly-Thanh", "Security Trust / Mireille", "Distributed Networks / Guillaume", "Network Security / Khawla", "USIM Management / Vincent", "Eco-Design / Pierre"], label="Expert Name") btn_expert = gr.Button("Top 10 by expert") with gr.Tab("By Company"): tb_com=gr.Textbox(label="Company Name",info="You can write 1, 2 or 3 company names at the same time") btn_type = gr.Button("Document type by company") with gr.Row(): plt_chart = gr.Plot(label="Graphique") plt_chart2 = gr.Plot(label="Graphique") plt_chart3 = gr.Plot(label="Graphique") with gr.Accordion("Excel Preview", open=False): df_output = gr.DataFrame() fi_excel = gr.File(label="Excel File") fi_excel.change(get_columns, inputs=[fi_excel], outputs=[dd_source_ask, dd_source_class, dd_label1, dd_label2, df_output]) btn_extract.click(extractionPrincipale, inputs=[tb_url, fi_excel], outputs=[fi_excel, tb_status_message]) mist_button.click(chat_with_mistral, inputs=[dd_source_ask, tb_destcol, tb_prompt, tb_filename, fi_excel, tb_url], outputs=[fi_excel, df_output]) btn_classif.click(classification, inputs=[dd_source_class, fi_excel], outputs=[fi_excel, df_output]) btn_chart.click(create_bar_plot, inputs=[fi_excel, dd_label1, dd_label2], outputs=[plt_figure]) btn_overall.click(generate_company_chart,inputs=[fi_excel], outputs=[plt_chart]) btn_overall.click(status_chart,inputs=[fi_excel], outputs=[plt_chart2]) btn_overall.click(category_chart,inputs=[fi_excel], outputs=[plt_chart3]) btn_expert.click(chart_by_expert,inputs=[fi_excel,rd_exp], outputs=[plt_chart]) btn_type.click(company_document_type,inputs=[fi_excel,tb_com], outputs=[plt_chart]) # dd_label1.change(update_label, inputs=[dd_label1], outputs=[dd_label2]) demo.launch(debug=True)