Update app.py

app.py

@@ -2,25 +2,18 @@ import gradio as gr
 from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
 
 # --- CONFIGURATION ---
-
-MODEL_K2H_REPO = "ankitklakra/kurukh-to-hindi"
-MODEL_H2K_REPO = "ankitklakra/hindi-to-kurukh"
+MODEL_K2H_REPO = "ankitklakra/kurukh-to-hindi"  
+MODEL_H2K_REPO = "ankitklakra/hindi-to-kurukh"  
 
 # --- LOAD RESOURCES ---
-# 1. Load the "Dictionary" (Tokenizer) from Google
-
 print("Loading Tokenizer...")
 tokenizer = AutoTokenizer.from_pretrained("google/mt5-small")
 
-# 2. Load the "Brains" (Your Custom Models)
-print("Loading Kurukh -> Hindi Model...")
+print("Loading Models...")
 model_k2h = AutoModelForSeq2SeqLM.from_pretrained(MODEL_K2H_REPO)
-
-print("Loading Hindi -> Kurukh Model...")
 model_h2k = AutoModelForSeq2SeqLM.from_pretrained(MODEL_H2K_REPO)
 
-# 3. Create the Pipelines
-
+# Create Pipelines
 pipe_k2h = pipeline("text2text-generation", model=model_k2h, tokenizer=tokenizer)
 pipe_h2k = pipeline("text2text-generation", model=model_h2k, tokenizer=tokenizer)
 
@@ -29,26 +22,20 @@ def translate_text(text, direction):
     if not text:
         return ""
     
-    # Select the correct pipeline
-    if direction == "Kurukh -> Hindi":
-        target_pipeline = pipe_k2h
-    else:
-        target_pipeline = pipe_h2k
+    target_pipeline = pipe_k2h if direction == "Kurukh -> Hindi" else pipe_h2k
     
-    # Translate
-    results = target_pipeline(text, max_length=128)
-    return results[0]['generated_text']
+    try:
+        results = target_pipeline(text, max_length=128)
+        return results[0]['generated_text']
+    except Exception as e:
+        return f"Error: {str(e)}"
 
-# --- THE USER INTERFACE ---
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
+# --- THE UI ---
+
+with gr.Blocks() as demo:
     
-    gr.Markdown(
-        """
-        # 🇮🇳 AI Kurukh (Kurux) Translator
-        ### Preserving Tribal Languages with Artificial Intelligence
-        *Powered by Custom Fine-Tuned Google mT5 Models*
-        """
-    )
+    gr.Markdown("# 🇮🇳 AI Kurukh (Kurux) Translator")
+    gr.Markdown("### Preserving Tribal Languages with Artificial Intelligence")
     
     with gr.Row():
         direction = gr.Radio(
@@ -58,21 +45,11 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
         )
     
     with gr.Row():
-        with gr.Column():
-            input_text = gr.Textbox(
-                label="Input Text", 
-                placeholder="Type your sentence here...", 
-                lines=5
-            )
-            translate_btn = gr.Button("Translate 🚀", variant="primary")
-        
-        with gr.Column():
-            output_text = gr.Textbox(
-                label="Translation Result", 
-                lines=5, 
-                show_copy_button=True
-            )
+        input_text = gr.Textbox(label="Input Text", lines=5, placeholder="Type here...")
+        output_text = gr.Textbox(label="Translation Result", lines=5)
             
+    translate_btn = gr.Button("Translate 🚀", variant="primary")
+    
     gr.Examples(
         examples=[
             ["निघै नामे इन्द्रा हिकै?", "Kurukh -> Hindi"],
@@ -80,11 +57,9 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
             ["तुम्हारा नाम क्या है?", "Hindi -> Kurukh"],
             ["मुझे पानी दो।", "Hindi -> Kurukh"]
         ],
-        inputs=[input_text, direction],
-        label="Click on an example to test:"
+        inputs=[input_text, direction]
     )
 
     translate_btn.click(fn=translate_text, inputs=[input_text, direction], outputs=output_text)
 
-# Launch
 demo.launch()