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")
        with gr.Row():
            dd_url = gr.Dropdown(label="(e.g. https://www.3gpp.org/ftp/TSG_SA/WG1_Serv/TSGS1_105_Athens/Docs)", multiselect=False, value="https://www.3gpp.org/ftp/", allow_custom_value=True, scale=9)
            btn_search = gr.Button("Search")
        btn_extract = gr.Button("Extract excel from URL")
        tb_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", multiselect=False)
        gr.Markdown("### The predefined categories can be modified at any time")
        df_category = gr.DataFrame(label='categories', value=df_cate, interactive=True)
        btn_classif = gr.Button("Categorize")

    with gr.Tab("Charts Generation"):
        with gr.Row():
            dd_label1 = gr.Dropdown(label="Label 1", multiselect=False)
            dd_label2 = gr.Dropdown(label="Label 2", multiselect=False, value="")
        btn_chart = gr.Button("Generate Bar Plot")
        plt_figure = gr.Plot()

    with gr.Tab("Chart Generation"):
        gr.Markdown("## 🚧 Actuellement en maintenance 🚧")
        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("Company info")
        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")


    btn_search.click(browse_folder, inputs=dd_url, outputs=dd_url)
    dd_url.change(browse_folder, inputs=dd_url, outputs=dd_url)
    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=[dd_url, fi_excel], outputs=[fi_excel, tb_message])
    
    mist_button.click(chat_with_mistral, inputs=[dd_source_ask, tb_destcol, tb_prompt, tb_filename, fi_excel], outputs=[fi_excel, df_output])
    
    btn_classif.click(classification, inputs=[dd_source_class, fi_excel, df_category], 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)