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app.py
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import streamlit as st
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from transformers import pipeline
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from PyDictionary import PyDictionary
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# Load translation model for English to Urdu
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@st.cache_resource
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def load_translation_model():
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return pipeline("translation", model="Helsinki-NLP/opus-mt-en-ur")
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translator = load_translation_model()
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# Initialize PyDictionary for word meanings and synonyms
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dictionary = PyDictionary()
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# Streamlit App
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st.title("Bilingual Dictionary")
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st.write("Find meanings in **English** and **Urdu**, along with synonyms for any word!")
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# Input word
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word = st.text_input("Enter a word:", "").strip()
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if word:
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# Get word meaning
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with st.spinner("Fetching meaning in English..."):
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meaning = dictionary.meaning(word)
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if meaning:
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st.subheader("Meaning in English:")
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for part_of_speech, definitions in meaning.items():
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st.write(f"**{part_of_speech.capitalize()}**:")
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for definition in definitions:
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st.write(f"- {definition}")
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# Translate English definition to Urdu
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with st.spinner("Translating to Urdu..."):
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try:
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urdu_translation = translator(definition)
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st.write(f"**In Urdu:** {urdu_translation[0]['translation_text']}")
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except Exception as e:
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st.error("Could not translate the definition.")
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else:
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st.error("No meaning found for the word!")
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# Get synonyms
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with st.spinner("Fetching synonyms..."):
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synonyms = dictionary.synonym(word)
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if synonyms:
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st.subheader("Synonyms:")
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st.write(", ".join(synonyms))
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else:
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st.error("No synonyms found!")
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