Update app.py

app.py

@@ -49,14 +49,44 @@ if query and dataset:
             # Search in the vector database for the closest matches
             distances, indices = index.search(query_embedding, k=1)  # Limit to the top 1 result
             
+            # Debug: Display the index search results
+            st.write("Debug: Index search results:", indices, distances)
+            
             # Retrieve the most relevant context from the metadata
             retrieved_context = metadata[indices[0][0]]  # Get the top 1 context
             
+            # Debug: Display the retrieved context
+            st.write("Debug: Retrieved context:", retrieved_context)
+            
             # Extract the most relevant part of the context
             relevant_context = extract_relevant_context(retrieved_context)
             
+            # Debug: Display the relevant context
+            st.write("Debug: Relevant context used in prompt:", relevant_context)
+            
             # Construct a concise prompt
             prompt = f"Context: {relevant_context}\n\nQuery: {query}\n\nAnswer concisely:"
+            
+            # Debug: Display the final prompt
+            st.write("Debug: Prompt sent to model:", prompt)
+            
             result = query_huggingface_model(prompt)
             
-            # Handling the list resul
+            # Handling the list result and clean up output
+            if isinstance(result, list) and len(result) > 0:
+                generated_text = result[0].get("generated_text", "No response from model")
+                
+                # Debug: Display the generated text from the model
+                st.write("Debug: Generated text from model:", generated_text)
+                
+                # Format the output to show only the query and the answer
+                final_output = format_response(query, generated_text.strip())
+                
+                # Display the final formatted output
+                st.write("Chatbot:", final_output)
+            else:
+                st.write("Chatbot: No response from model or error occurred")
+        else:
+            st.write("Vector database or metadata not found for the selected dataset.")
+    else:
+        st.write("Access denied: You do not have permission to access this dataset.")