Abhishek-D7
commited on
Commit
•
ead05da
1
Parent(s):
4b0f080
Create app.py
Browse files
app.py
ADDED
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import tensorflow as tf
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import streamlit as st
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from transformers import T5Tokenizer, T5ForConditionalGeneration, MarianMTModel, MarianTokenizer
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def load_summarization_model():
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model = T5ForConditionalGeneration.from_pretrained('t5-small')
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tokenizer = T5Tokenizer.from_pretrained('t5-small')
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return model, tokenizer
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summarization_model, summarization_tokenizer = load_summarization_model()
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def load_translation_models():
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models = {}
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tokenizers = {}
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language_pairs = {
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'en-fr': 'Helsinki-NLP/opus-mt-en-fr',
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'fr-en': 'Helsinki-NLP/opus-mt-fr-en',
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'en-de': 'Helsinki-NLP/opus-mt-en-de',
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'de-en': 'Helsinki-NLP/opus-mt-de-en',
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'en-hi': 'Helsinki-NLP/opus-mt-en-hi',
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'hi-en': 'Helsinki-NLP/opus-mt-hi-en',
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'fr-de': 'Helsinki-NLP/opus-mt-fr-de',
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'de-fr': 'Helsinki-NLP/opus-mt-de-fr',
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'fr-hi': 'Helsinki-NLP/opus-mt-fr-hi',
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'hi-fr': 'Helsinki-NLP/opus-mt-hi-fr',
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'de-hi': 'Helsinki-NLP/opus-mt-de-hi',
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'hi-de': 'Helsinki-NLP/opus-mt-hi-de'
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}
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for pair, model_name in language_pairs.items():
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models[pair] = MarianMTModel.from_pretrained(model_name)
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tokenizers[pair] = MarianTokenizer.from_pretrained(model_name)
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return models, tokenizers
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translation_models, translation_tokenizers = load_translation_models()
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def summarize_text(article):
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inputs = summarization_tokenizer.encode("summarize: " + article, return_tensors="pt", max_length=512, truncation=True)
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summary_ids = summarization_model.generate(inputs, max_length=64, min_length=10, length_penalty=2.0, num_beams=4, early_stopping=True)
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return summarization_tokenizer.decode(summary_ids[0], skip_special_tokens=True)
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def translate_text(text, source_lang, target_lang):
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if source_lang == target_lang:
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return text
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language_pair = f'{source_lang}-{target_lang}'
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model = translation_models[language_pair]
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tokenizer = translation_tokenizers[language_pair]
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inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
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translated = model.generate(**inputs)
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return tokenizer.decode(translated[0], skip_special_tokens=True)
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st.title("Multilingual Text Summarizer and Translator")
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option = st.selectbox('Choose a task', ('Summarize and Translate'))
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if option == 'Summarize and Translate':
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article = st.text_area("Enter the article text here:")
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source_lang = st.selectbox('Source Language', ('en', 'fr', 'de', 'hi'))
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if st.button("Generate Summary"):
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summary = summarize_text(article)
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st.write("Summary:", summary)
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target_lang = st.selectbox('Translate Summary to', ('en', 'fr', 'de', 'hi'))
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if st.button("Translate Summary"):
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translated_summary = translate_text(summary, source_lang, target_lang)
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st.write("Translated Summary:", translated_summary)
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if st.checkbox("Translate Original Article"):
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target_lang_article = st.selectbox('Translate Article to', ('en', 'fr', 'de', 'hi'), key='article')
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translated_article = translate_text(article, source_lang, target_lang_article)
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st.write("Translated Article:", translated_article)
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