Update app.py

app.py

@@ -58,16 +58,30 @@ st.write("This model will score your reviews in your CSV file and generate a rep
 # Load models with caching to avoid reloading on every run
 @st.cache_resource
 def load_models():
+    score_pipe = None
+    gemma_pipe = None
+    
     try:
-        score_pipe = pipeline("text-classification", model="nlptown/bert-base-multilingual-uncased-sentiment", device=0)
+        st.info("Loading sentiment analysis model...")
+        score_pipe = pipeline("text-classification", 
+                              model="nlptown/bert-base-multilingual-uncased-sentiment", 
+                              device=0)
+        st.success("Sentiment analysis model loaded successfully!")
     except Exception as e:
         st.error(f"Error loading score model: {e}")
-        score_pipe = None
+    
     try:
-        gemma_pipe = pipeline("text-generation", model="google/gemma-3-1b-it", device=0, torch_dtype=torch.bfloat16)
+        st.info("Loading Gemma model...")
+        # Try with correct model name - either gemma-2-1b-it or gemma-7b-it
+        gemma_pipe = pipeline("text-generation", 
+                              model="google/gemma-2-1b-it",  # Check model name
+                              device=0, 
+                              torch_dtype=torch.bfloat16)
+        st.success("Gemma model loaded successfully!")
     except Exception as e:
         st.error(f"Error loading Gemma model: {e}")
-        gemma_pipe = None
+        st.error(f"Detailed error: {type(e).__name__}: {str(e)}")
+    
     return score_pipe, gemma_pipe