Create app.py

app.py

@@ -0,0 +1,63 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load the translation pipeline
+pipe = pipeline("translation", model="facebook/nllb-200-distilled-600M")
+
+# Define the translation function
+def translate_text(text, source_language, target_language, max_length=200):
+    # Define source and target languages (e.g., 'eng_Latn' -> 'fra_Latn')
+    language_pair = f"{source_language}-{target_language}"
+    response = pipe(
+        text,
+        src_lang=source_language,
+        tgt_lang=target_language,
+        max_length=max_length
+    )
+    return response[0]['translation_text']
+
+# Create the Gradio app interface
+with gr.Blocks() as app:
+    gr.Markdown("## Translation App")
+    gr.Markdown(
+        "Enter text in the source language, and the model will translate it to the target language. "
+        "This app uses the `facebook/nllb-200-distilled-600M` model."
+    )
+
+    with gr.Row():
+        input_text = gr.Textbox(
+            label="Input Text",
+            placeholder="Type the text to translate...",
+            lines=4
+        )
+        output_translation = gr.Textbox(label="Translated Text", lines=4)
+
+    with gr.Row():
+        source_language = gr.Textbox(
+            label="Source Language Code",
+            placeholder="e.g., eng_Latn (for English)"
+        )
+        target_language = gr.Textbox(
+            label="Target Language Code",
+            placeholder="e.g., fra_Latn (for French)"
+        )
+
+    max_length = gr.Slider(
+        label="Max Length",
+        minimum=50,
+        maximum=500,
+        step=50,
+        value=200
+    )
+
+    submit_button = gr.Button("Translate")
+    
+    submit_button.click(
+        fn=translate_text,
+        inputs=[input_text, source_language, target_language, max_length],
+        outputs=output_translation
+    )
+
+# Launch the app
+if __name__ == "__main__":
+    app.launch()