Create app.py

app.py

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+import gradio as gr
+from transformers import MarianMTModel, MarianTokenizer
+from langdetect import detect
+from sacremoses import MosesTokenizer, MosesDetokenizer
+
+# Supported languages for translation
+SUPPORTED_LANGUAGES = {
+    "en": "English",
+    "fr": "French",
+    "es": "Spanish",
+    "de": "German",
+    "it": "Italian"
+}
+
+def translate_text(text, target_lang="fr"):
+    # Detect input text language
+    input_lang = detect(text)
+
+    # Load pre-trained translation model
+    model_name = f'Helsinki-NLP/opus-mt-{input_lang}-{target_lang}'
+    model = MarianMTModel.from_pretrained(model_name)
+    tokenizer = MarianTokenizer.from_pretrained(model_name)
+
+    # Tokenize input text
+    inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
+
+    # Translate input text
+    translated = model.generate(**inputs)
+
+    # Decode translated text
+    translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
+
+    return translated_text
+
+# Function for translating text using Gradio
+def translate_interface(text, target_language):
+    translated_text = translate_text(text, target_language)
+    return translated_text
+
+# Create Gradio interface
+inputs = gr.Textbox(lines=3, label="Enter the text to translate")
+target_language = gr.Dropdown(choices=list(SUPPORTED_LANGUAGES.keys()), label="Target Language")
+output = gr.Textbox(placeholder="Translated Text", label="Translated Text")
+
+gr.Interface(fn=translate_interface, inputs=[inputs, target_language], outputs=output, title="Text Translation", theme="compact").launch(debug = True)