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Update app.py
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app.py
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import gradio as gr
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from transformers import pipeline
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# Загружаем
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sentiment_pipeline = pipeline("sentiment-analysis")
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# Функция для анализа тональности текста
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def analyze_sentiment(text):
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result = sentiment_pipeline(text)[0]
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return f"Label: {result['label']}, Confidence: {result['score']:.4f}"
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"I love programming, it's so much fun!",
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"This movie was terrible, I hated it.",
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"The weather is nice today.",
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"Gradio is an amazing tool for building ML demos!"
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]
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# Запускаем интерфейс
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import gradio as gr
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from transformers import pipeline
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# Загружаем модели для анализа тональности и суммаризации текста
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sentiment_pipeline = pipeline("sentiment-analysis")
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summarization_pipeline = pipeline("summarization")
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# Функция для анализа тональности текста
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def analyze_sentiment(text):
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result = sentiment_pipeline(text)[0]
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return f"Label: {result['label']}, Confidence: {result['score']:.4f}"
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# Функция для суммаризации текста
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def summarize_text(text):
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result = summarization_pipeline(text, max_length=50, min_length=25, do_sample=False)
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return result[0]['summary_text']
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# Примеры текстов для анализа тональности
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sentiment_examples = [
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"I love programming, it's so much fun!",
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"This movie was terrible, I hated it.",
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"The weather is nice today.",
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"Gradio is an amazing tool for building ML demos!"
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]
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# Примеры текстов для суммаризации
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summarization_examples = [
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"Gradio is a powerful tool for building machine learning demos. It allows developers to quickly create interactive interfaces for their models.",
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"The weather today is sunny with a slight breeze. It's a perfect day to go outside and enjoy nature.",
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"Artificial intelligence is transforming industries by automating tasks and providing insights from large datasets."
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]
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# Создаем интерфейс Gradio с вкладками
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with gr.Blocks() as demo:
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with gr.Tab("Sentiment Analysis"):
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gr.Interface(
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fn=analyze_sentiment,
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inputs=gr.Textbox(lines=2, placeholder="Введите текст для анализа тональности..."),
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outputs="text",
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title="Анализ тональности текста",
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description="Введите текст, чтобы определить его тональность.",
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examples=sentiment_examples,
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examples_per_page=5
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)
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with gr.Tab("Text Summarization"):
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gr.Interface(
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fn=summarize_text,
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inputs=gr.Textbox(lines=5, placeholder="Введите текст для суммаризации..."),
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outputs="text",
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title="Суммаризация текста",
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description="Введите текст, чтобы получить его краткое содержание.",
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examples=summarization_examples,
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examples_per_page=3
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)
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# Запускаем интерфейс
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demo.launch()
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