Upload app.py

app.py

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+# -*- coding: utf-8 -*-
+"""app.py
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1UBKp9Q5WTAiaXvsRK_6KupUXBI3i05wH
+"""
+
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+import gradio as gr
+
+# Dictionary mapping target languages to Helsinki models
+LANG_MODELS = {
+    "German": "Helsinki-NLP/opus-mt-en-de",
+    "French": "Helsinki-NLP/opus-mt-en-fr",
+    "Spanish": "Helsinki-NLP/opus-mt-en-es",
+    "Italian": "Helsinki-NLP/opus-mt-en-it",
+    "Japanese": "Helsinki-NLP/opus-mt-en-jap",
+}
+
+# Preload models for speed (optional, you can also load on demand)
+model_cache = {}
+tokenizer_cache = {}
+
+def translate_text_multi(text, target_lang):
+    model_name = LANG_MODELS.get(target_lang)
+    if not model_name:
+        return "Error: language not supported."
+
+    # Load model/tokenizer if not already loaded
+    if model_name not in model_cache:
+        tokenizer_cache[model_name] = AutoTokenizer.from_pretrained(model_name)
+        model_cache[model_name] = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+    tokenizer = tokenizer_cache[model_name]
+    model = model_cache[model_name]
+
+    inputs = tokenizer(text, return_tensors="pt")
+    outputs = model.generate(**inputs)
+    translated = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return translated
+
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("## 🌐 Multi-language Translator")
+    input_text = gr.Textbox(label="Enter English text", lines=4)
+    target_language = gr.Dropdown(choices=list(LANG_MODELS.keys()), value="German", label="Target Language")
+    output_text = gr.Textbox(label="Translation", lines=4)
+
+    translate_btn = gr.Button("Translate")
+    translate_btn.click(fn=translate_text_multi, inputs=[input_text, target_language], outputs=output_text)
+
+demo.launch()