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import gradio as gr |
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import pandas as pd |
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from datasets import load_dataset |
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def load_data(): |
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dataset = load_dataset("your-username/your-dataset-name", split="train") |
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df = pd.DataFrame(dataset) |
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lemmas = {} |
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current_lemma = None |
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for _, row in df.iterrows(): |
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if row['#ORTO'] == '---': |
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current_lemma = None |
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elif current_lemma is None: |
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current_lemma = row['#ORTO'].replace("ORTO:", "") |
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lemmas[current_lemma] = [] |
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else: |
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lemma_data = { |
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'PPOS': row['#PPOS'].replace("PPOS:", "") if pd.notna(row['#PPOS']) else "", |
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'PHON1': row['#PHON1'].replace("PHON:", "") if pd.notna(row['#PHON1']) else "", |
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'PHON2': row['#PHON2'].replace("PHON:", "") if pd.notna(row['#PHON2']) else "", |
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'COMM': row['#COMM'] if pd.notna(row['#COMM']) else "" |
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} |
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lemmas[current_lemma].append(lemma_data) |
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return lemmas |
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lemmas = load_data() |
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def search_lemma(lemma): |
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results = lemmas.get(lemma, None) |
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if not results: |
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return f"No results found for {lemma}" |
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response = f"Results for {lemma}:\n\n" |
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response += "PPOS\tPHON1\tPHON2\tCOMM\n" |
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for result in results: |
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response += f"{result['PPOS']}\t{result['PHON1']}\t{result['PHON2']}\t{result['COMM']}\n" |
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return response |
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iface = gr.Interface( |
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fn=search_lemma, |
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inputs="text", |
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outputs="text", |
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title="Lemma Search", |
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description="Enter a lemma to search for its declensions and pronunciations." |
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) |
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if __name__ == "__main__": |
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iface.launch() |
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