Create app.py

app.py

@@ -0,0 +1,53 @@
+# app.py
+
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+import gradio as gr
+
+# Initialize the translation pipeline with the google-t5/t5-base model
+text_translator = pipeline("translation", model="google/t5-base")
+
+# Dictionary mapping destination languages to their T5-compatible names
+language_mapping = {
+    "German": "German",
+    "Eastern Panjabi": "Punjabi",
+    "Sanskrit": "Sanskrit",
+    "Urdu": "Urdu",
+    "Tamil": "Tamil",
+    "Telugu": "Telugu",
+    "Yue Chinese": "Chinese",
+    "Chinese (Simplified)": "Chinese",
+    "Chinese (Traditional)": "Chinese",
+    "Hindi": "Hindi",
+    "French": "French",
+    "Spanish": "Spanish"
+}
+
+def translate_text(text, destination_language):
+    dest_language = language_mapping.get(destination_language)
+    
+    if dest_language is None:
+        return "Unsupported language selected."
+
+    # T5 model requires a specific format for the translation task
+    translation_prompt = f"translate English to {dest_language}: {text}"
+    
+    translation = text_translator(translation_prompt)
+    return translation[0]["translation_text"]
+
+gr.close_all()
+
+demo = gr.Interface(
+    fn=translate_text,
+    inputs=[
+        gr.Textbox(label="Input text to translate", lines=6), 
+        gr.Dropdown(list(language_mapping.keys()), label="Select destination language")
+    ],
+    outputs=[gr.Textbox(label="Translated text", lines=4)],
+    title="Language translator (model- Google T5 Base)",
+    description="THIS APPLICATION WILL BE USED TO TRANSLATE ENGLISH TO MULTIPLE LANGUAGES",
+    theme=gr.themes.Soft(),
+    concurrency_limit=16
+)
+
+demo.launch()