Create app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import json
+
+# Load the tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained("Darwin29/lumina-translate")
+model = AutoModelForSeq2SeqLM.from_pretrained("Darwin29/lumina-translate")
+
+# Translation function (English to Iban and Iban to English)
+def translate_text(text, translation_direction):
+    if translation_direction == "English to Iban":
+        # Translate English to Iban
+        inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=512)
+        outputs = model.generate(**inputs)
+        translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        return json.dumps({"input_text": text, "translated_text": translated_text, "language": "en-to-iban"})
+    
+    elif translation_direction == "Iban to English":
+        # Translate Iban to English (you'll need a reverse model or translation setup here)
+        inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=512)
+        outputs = model.generate(**inputs)
+        translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        return json.dumps({"input_text": text, "translated_text": translated_text, "language": "iban-to-en"})
+
+# Define the Gradio interface with a dropdown to select translation direction
+iface = gr.Interface(
+    fn=translate_text,
+    inputs=[
+        gr.Textbox(label="Enter Text (English or Iban)"),
+        gr.Radio(["English to Iban", "Iban to English"], label="Select Translation Direction")
+    ],
+    outputs=gr.JSON(),
+    title="English-Iban Translator",
+    description="This app translates between English and Iban. Choose the translation direction."
+)
+
+# Launch the app
+iface.launch()