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import gradio as gr | |
from scrape_3gpp import * | |
from excel_chat import * | |
from classification import * | |
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.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, 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]) | |
demo.launch(debug=True) |