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| import gradio as gr | |
| from src.chatbot import chatbot, keyword_search | |
| with gr.Blocks() as App: | |
| with gr.Tab("ChatBot"): | |
| #Apply RAG using chatbut function from local file ChatBot.py | |
| gr.ChatInterface(chatbot, | |
| title="PoliticsToYou", | |
| description= "This chatbot uses the infomation of speeches of the german parliament (since 2021) \ | |
| to get insight on the view points of the german parties and the debate of the parliament.", | |
| examples=["Wie steht die CDU zur Cannabislegalisierung?","Was waren die wichtigsten Themen in der aktuellen Legislaturperiode?"], #change to meaningful examples | |
| cache_examples=False, #true increases the loading time | |
| ) | |
| with gr.Tab("KeyWordSearch"): | |
| with gr.Blocks() as Block: | |
| #Keyword Input | |
| keyword_box = gr.Textbox(label='keyword') | |
| #Additional Input (hidden) | |
| with gr.Accordion('Detailed filters', open=False): | |
| #Row orientation | |
| with gr.Row() as additional_input: | |
| n_slider = gr.Slider(label="Number of Results", minimum=1, maximum=100, step=1, value=10) | |
| party_dopdown = gr.Dropdown(choices=['CDU/CSU','SPD','FDP','Grüne','not found','DIE LINKE.','PDS','KPD'], label='Party') | |
| search_btn = gr.Button('Search') | |
| with gr.Column(visible=False) as output_col: | |
| results_df = gr.Dataframe(label='Results', interactive=False) | |
| #Download results from keyword search | |
| with gr.Accordion('Would you like to download your results?', open=False) as download_row: | |
| with gr.Row(): | |
| ftype_dropdown = gr.Dropdown(choices=["csv","excel","json"], label="Format") | |
| export_btn = gr.Button('Export') | |
| file = gr.File(file_types=[".xlsx", ".csv", ".json"], visible=False) | |
| #Keyword Search on click | |
| def search(keyword, n, party): #ToDo: Include party and timedate | |
| return { | |
| output_col: gr.Column(visible=True), | |
| results_df: keyword_search(query=keyword, n=n, party_filter=party), | |
| } | |
| search_btn.click( | |
| fn=search, | |
| inputs=[keyword_box, n_slider, party_dopdown], | |
| outputs=[output_col, results_df], | |
| ) | |
| #Export data to a downloadable format | |
| def export(df, keyword, ftype=None): | |
| if ftype == "csv": | |
| file = f'{keyword}.csv' | |
| df.to_csv(file, index = False) | |
| return gr.File(value=file,visible=True) | |
| elif ftype == "json": | |
| file = f'{keyword}.json' | |
| df.to_json(file, index = True) | |
| return gr.File(value=file,visible=True) | |
| else: | |
| file = f'{keyword}.xlsx' | |
| df.to_excel(file, index = True) | |
| return gr.File(value=file,visible=True) | |
| export_btn.click( | |
| fn=export, | |
| inputs=[results_df, keyword_box, ftype_dropdown], | |
| outputs=[file], | |
| ) | |
| if __name__ == "__main__": | |
| App.launch(share=False) #true not supported on hf spaces | |