Update translation.py
Browse files- translation.py +11 -7
translation.py
CHANGED
@@ -4,22 +4,22 @@ import torch
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@st.cache_resource
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def _load_default_model():
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model_name = "Helsinki-NLP/opus-mt-en-fr"
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tokenizer = MarianTokenizer.from_pretrained(model_name)
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model = MarianMTModel.from_pretrained(model_name)
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return tokenizer, model
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@st.cache_resource
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def load_model(
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try:
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if
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return _load_default_model()
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model_name = f"Helsinki-NLP/opus-mt-{
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tokenizer = MarianTokenizer.from_pretrained(model_name)
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model = MarianMTModel.from_pretrained(model_name)
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return tokenizer, model
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except Exception as e:
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st.warning(f"No direct model for {
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return _load_default_model()
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@st.cache_data
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@@ -28,7 +28,7 @@ def translate_cached(text, source_lang, target_lang):
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"Hindi": "hi", "Chinese": "zh", "Arabic": "ar", "Russian": "ru", "Japanese": "ja"}.get(source_lang, "en")
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tgt_code = {"English": "en", "French": "fr", "Spanish": "es", "German": "de",
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"Hindi": "hi", "Chinese": "zh", "Arabic": "ar", "Russian": "ru", "Japanese": "ja"}.get(target_lang, "fr")
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tokenizer, model = load_model(src_code,
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inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=500)
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with torch.no_grad():
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translated = model.generate(**inputs, max_length=500)
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@@ -37,7 +37,11 @@ def translate_cached(text, source_lang, target_lang):
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def translate(text, source_lang, target_lang):
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if not text:
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return "No text provided."
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LANGUAGES = {"English": "en", "French": "fr", "Spanish": "es", "German": "de",
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"Hindi": "hi", "Chinese": "zh", "Arabic": "ar", "Russian": "ru", "Japanese": "ja"}
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@st.cache_resource
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def _load_default_model():
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model_name = "Helsinki-NLP/opus-mt-en-fr"
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tokenizer = MarianTokenizer.from_pretrained(model_name)
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model = MarianMTModel.from_pretrained(model_name)
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return tokenizer, model
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@st.cache_resource
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def load_model(source_lang, target_lang):
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try:
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if source_lang == target_lang: # Avoid same language error
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return _load_default_model()
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model_name = f"Helsinki-NLP/opus-mt-{source_lang}-{target_lang}"
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tokenizer = MarianTokenizer.from_pretrained(model_name)
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model = MarianMTModel.from_pretrained(model_name)
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return tokenizer, model
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except Exception as e:
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st.warning(f"No direct model for {source_lang} to {target_lang}. Using cached en-fr.")
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return _load_default_model()
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@st.cache_data
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"Hindi": "hi", "Chinese": "zh", "Arabic": "ar", "Russian": "ru", "Japanese": "ja"}.get(source_lang, "en")
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tgt_code = {"English": "en", "French": "fr", "Spanish": "es", "German": "de",
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"Hindi": "hi", "Chinese": "zh", "Arabic": "ar", "Russian": "ru", "Japanese": "ja"}.get(target_lang, "fr")
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tokenizer, model = load_model(src_code, tgt_code)
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inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=500)
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with torch.no_grad():
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translated = model.generate(**inputs, max_length=500)
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def translate(text, source_lang, target_lang):
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if not text:
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return "No text provided."
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try:
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return translate_cached(text, source_lang, target_lang)
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except Exception as e:
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st.error(f"Translation error: {str(e)}. Using input as fallback.")
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return text
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LANGUAGES = {"English": "en", "French": "fr", "Spanish": "es", "German": "de",
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"Hindi": "hi", "Chinese": "zh", "Arabic": "ar", "Russian": "ru", "Japanese": "ja"}
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