Update app.py

app.py

@@ -14,19 +14,24 @@ MODEL_K2H_REPO = "ankitklakra/kurukh-to-hindi"
 MODEL_H2K_REPO = "ankitklakra/hindi-to-kurukh"
 SHEET_NAME = "Kurukh_Feedback_Log"
 
-# --- LOAD MODELS ---
-print(f"🚀 Starting App with Gradio Version: {gr.__version__}")
 
 print("Loading Translation Models...")
-tokenizer = AutoTokenizer.from_pretrained("google/mt5-small")
-model_k2h = AutoModelForSeq2SeqLM.from_pretrained(MODEL_K2H_REPO)
-model_h2k = AutoModelForSeq2SeqLM.from_pretrained(MODEL_H2K_REPO)
+try:
+    tokenizer = AutoTokenizer.from_pretrained("google/mt5-small")
+    model_k2h = AutoModelForSeq2SeqLM.from_pretrained(MODEL_K2H_REPO)
+    model_h2k = AutoModelForSeq2SeqLM.from_pretrained(MODEL_H2K_REPO)
 
-pipe_k2h = pipeline("text2text-generation", model=model_k2h, tokenizer=tokenizer)
-pipe_h2k = pipeline("text2text-generation", model=model_h2k, tokenizer=tokenizer)
+    pipe_k2h = pipeline("text2text-generation", model=model_k2h, tokenizer=tokenizer)
+    pipe_h2k = pipeline("text2text-generation", model=model_h2k, tokenizer=tokenizer)
+except Exception as e:
+    print(f"Error loading translation models: {e}")
 
 print("Loading Voice Model...")
-asr_pipeline = pipeline("automatic-speech-recognition", model="openai/whisper-tiny")
+try:
+    asr_pipeline = pipeline("automatic-speech-recognition", model="openai/whisper-tiny")
+except Exception as e:
+    print(f"Error loading whisper model: {e}")
+    asr_pipeline = None
 
 # --- HELPER FUNCTIONS ---
 def transliterate_to_hindi(text):
@@ -40,7 +45,6 @@ def transliterate_to_hindi(text):
 
 def save_to_sheet(original, translation, correction, direction):
     # --- VALIDATION CHECK ---
-   
     if not original or not original.strip():
         return "⚠️ Error: Original text is missing."
     
@@ -62,7 +66,6 @@ def save_to_sheet(original, translation, correction, direction):
 
         sheet = client.open(SHEET_NAME).sheet1
 
-        # Check if header exists, if not add it
         if not sheet.get_all_values():
             sheet.append_row(
                 [
@@ -83,7 +86,7 @@ def save_to_sheet(original, translation, correction, direction):
         return f"❌ Error: {str(e)}"
 
 def speech_to_text(audio_path):
-    if audio_path is None:
+    if audio_path is None or asr_pipeline is None:
         return ""
     return asr_pipeline(audio_path)["text"]
 
@@ -219,16 +222,16 @@ with gr.Blocks(title="Kurukh AI Translator") as demo:
                     output_audio = gr.Audio(
                         label="🔊 Listen (Hindi Only)", interactive=False
                     )
-               
+            
+            # --- EXAMPLES SECTION ---
             gr.Markdown("### 💡 Try these examples:")
-                gr.Examples(
+            gr.Examples(
                 examples=[
-                    
+                   
                     # 1. Kurukh (Devanagari Script)
-
                     ["निघै नामे इन्द्रा हिकै?", "Kurukh -> Hindi", False], 
                     
-                    # 2. Hindi (Devanagari Script - Sentence)
+                    # 2. Hindi (Devanagari Script)
                     ["तुम कहाँ जा रहे हो?", "Hindi -> Kurukh", False], 
                     
                     # 3. Hinglish (Roman Script -> needs Transliteration)
@@ -273,11 +276,5 @@ with gr.Blocks(title="Kurukh AI Translator") as demo:
     gr.HTML(
         "<center style='color:#777;'>Built with ❤️ for the Kurukh Community</center>"
     )
-    
-    translate_btn.click(
-        fn=lambda orig, trans, direc: (orig, trans, direc),
-        inputs=[input_text, output_text, direction],
-        outputs=[fb_original, fb_ai_output, fb_direction]
-    )
 
-demo.launch()
+demo.launch()