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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, value="")
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) |