import gradio as gr import polars as pl # favourite_langs = {"English": "en", "Romanian": "ro", "German": "de", "-----": "-----"} favourite_langs = {"English": "en", "Romanian": "ro", "German": "de"} options = list(favourite_langs.keys()) models = ['ENRO', 'DERO'] # English, Romanian def search_text(input_text, sselected_language, tselected_language, model_name, hits, toggle_case): # df = pl.read_csv('hf://datasets/TiberiuCristianLeon/2RO/ENRO/ENRO.tsv', separator='\t') # df = pl.read_parquet('hf://datasets/TiberiuCristianLeon/RSSNEWS/data/train-00000-of-00001.parquet') # df = pl.read_parquet('https://huggingface.co/datasets/TiberiuCristianLeon/2RO/resolve/refs%2Fconvert%2Fparquet/default/train/0000.parquet') path_to_model = f"https://huggingface.co/api/datasets/TiberiuCristianLeon/2RO/parquet/{model_name.lower()}/train/0.parquet" df = pl.read_parquet(path_to_model) # Filter rows # df.filter(pl.col(sselected_language).str.contains(input_text)).head(hits) # print(df.head(hits)) if toggle_case: filtered = df.filter(pl.col(sselected_language).str.contains(input_text).alias("literal")) # case sensitive else: filtered = df.filter(pl.col(sselected_language).str.contains(f"(?i){input_text}").alias("literal")) # (?i) case insensitive # filtered = df.filter(pl.col(sselected_language).str.contains_any([input_text], ascii_case_insensitive=True).alias("contains_any")) print(toggle_case, filtered.head(hits)) # print(filtered) # Extract rows list_of_arrays = filtered.select([sselected_language, tselected_language]).head(hits) # for dataframe type="numpy" # list_of_arrays = filtered.select([sselected_language, tselected_language]).head(hits).to_numpy() message_text = f'Done! Found {len(list_of_arrays)} entries' return list_of_arrays, message_text # Define a function to swap dropdown values def swap_languages(src_lang, tgt_lang): return tgt_lang, src_lang def create_interface(): with gr.Blocks() as interface: gr.Markdown("## Search Text in Dataset") with gr.Row(): input_text = gr.Textbox(label="Enter text to search:", placeholder="Type your text here...", info="Press Enter key to start search") with gr.Row(): sselected_language = gr.Dropdown(choices=options, value = options[0], label="Source language", interactive=True) tselected_language = gr.Dropdown(choices=options, value = options[1], label="Target language", interactive=True) swap_button = gr.Button("Swap Languages") swap_button.click(fn=swap_languages, inputs=[sselected_language, tselected_language], outputs=[sselected_language, tselected_language]) toggle_case = gr.Checkbox(info="Case sensitive search", label="Toggle case sensitive search", value=True, interactive=True, visible=True) model_name = gr.Dropdown(choices=models, label="Select a dataset", value = models[0], interactive=True) search_button = gr.Button("Search") translated_text = gr.Dataframe(label="Returned entries:", interactive=False, headers=[options[0], options [1]], datatype=["str", "str"], col_count=(2, "fixed"), type="polars", wrap=True, show_row_numbers=False, show_copy_button=True) message_text = gr.Textbox(label="Messages:", placeholder="Display field for status and error messages", interactive=False) hits = gr.Slider( minimum=1, maximum=100, value=10, step=5, label="Number of returned hits") search_button.click( search_text, inputs=[input_text, sselected_language, tselected_language, model_name, hits, toggle_case], outputs=[translated_text, message_text] ) # Submit the form when Enter is pressed in the input_text textbox input_text.submit( search_text, inputs=[input_text, sselected_language, tselected_language, model_name, hits, toggle_case], outputs=[translated_text, message_text] ) return interface if __name__ == "__main__": interface = create_interface() interface.launch()