creating app.py

app.py

@@ -0,0 +1,42 @@
+import torch
+import gradio as gr
+
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+language_codes = {
+    'English': 'en',
+    'French': 'fr',
+    'German': 'de',
+    'Spanish': 'es',
+    'Italian': 'it',
+    'Dutch': 'nl',
+    'Portuguese': 'pt',
+    'Russian': 'ru',
+    'Chinese': 'zh',
+    'Japanese': 'ja',
+    'Korean': 'ko',
+    'Arabic': 'ar'
+}
+def language_translator(source, target,text):
+    task = f'translation_{language_codes[source]}_to_{language_codes[target]}'
+    
+    translator = pipeline(task, model="google-t5/t5-small")
+    translation = translator(text)
+
+    return translation[0]['translation_text']
+
+gr.close_all()
+
+
+demo = gr.Interface(language_translator,
+                    inputs=[gr.Dropdown(['English','French','German','Spanish','Italian','Dutch','Portuguese','Russian','Chinese','Japanese','Korean','Arabic'],
+                                        label='Source Language', value='English' ),
+                            gr.Dropdown(['English','French','German','Spanish','Italian','Dutch','Portuguese','Russian','Chinese','Japanese','Korean','Arabic'],
+                                        label='Target Language', value='French' ),
+                            gr.Textbox(label='Text to Translate', lines=5)],
+
+                    outputs=[gr.Textbox(label="Translated Text", lines=5)],
+                    title="Gen AI Learning Project 4: Language Translator",
+                    description="This Application uses 'google-t5/t5-small' llm to provide translation service")
+demo.launch()