Update app.py

app.py

@@ -37,18 +37,12 @@ index = faiss.IndexFlatL2(embedding_dim)
 def preprocess_query(query):
     tokens = query.lower().split()
     epilepsy_keywords = ["seizure", "epilepsy", "convulsion", "neurology", "brain activity", "headache related to epilepsy"] # Added specific phrase
-    healthcare_keywords = ["headache", "fever", "blood pressure", "diabetes", "cough", "flu", "nutrition", "mental health", "pain", "legs", "body pain", "health", "medical", "symptoms", "treatment", "disease", "illness"] # Extended healthcare keywords - added "illness"
+    healthcare_keywords = ["headache", "fever", "blood pressure", "diabetes", "cough", "flu", "nutrition", "mental health", "pain", "legs", "body pain", "health", "medical", "symptoms", "treatment", "disease"] # Extended healthcare keywords
 
     is_epilepsy_related = any(k in tokens for k in epilepsy_keywords)
     is_healthcare_related = any(k in tokens for k in healthcare_keywords) and not is_epilepsy_related # Healthcare but NOT epilepsy
     is_general = not is_epilepsy_related and not is_healthcare_related # Truly general queries
 
-    print(f"Query: {query}") # Debugging prints
-    print(f"Tokens: {tokens}")
-    print(f"Is Epilepsy Related: {is_epilepsy_related}")
-    print(f"Is Healthcare Related: {is_healthcare_related}")
-    print(f"Is General: {is_general}")
-
     return tokens, is_epilepsy_related, is_healthcare_related, is_general
 
 # Function to Generate Response with Chat History
@@ -116,7 +110,7 @@ def generate_response(user_query, chat_history):
         except Exception as e:
             model_response = f"⚠️ Error generating response with LLaMA: {e}"
 
-        return f"**NeuroGuard:** ✅ **Epilepsy Focused Response:**\n{pubmedbert_insights}\n\n**Response:**\n{model_response}" # Modified response intro
+        return f"**NeuroGuard:** ✅ **Analysis:**\n{pubmedbert_insights}\n\n**Response:**\n{model_response}"
 
     # If Healthcare Related but Not Epilepsy - Provide General Wellness Tips and Basic Remedies
     elif is_healthcare_related:
@@ -141,7 +135,7 @@ def generate_response(user_query, chat_history):
             "- 🩺 **Important:** These tips are for general wellness and informational purposes only, and are not medical advice. Always consult a healthcare professional for any specific health concerns or before making significant changes to your health regimen."
         )
 
-        response_content = f"**NeuroGuard:** 🩺 **General Health Assistance:** While my primary focus is epilepsy, this seems to be a general health-related question. Here's some information that might help:\n\n" # Modified response intro
+        response_content = f"**NeuroGuard:** 🩺 It seems your question '{user_query}' is about general health. While I focus on epilepsy, here's some information that might help:\n\n" # Use original user_query
         response_content += suggested_remedy
         response_content += general_health_tips # Always include general tips
 
@@ -151,8 +145,8 @@ def generate_response(user_query, chat_history):
     # If General Query (Not Healthcare or Epilepsy Related) - Provide a different response
     elif is_general:
         return (
-            f"**NeuroGuard:** 💡 **Not Epilepsy or Health Related:**  It seems your question '{user_query}' is outside my areas of expertise, which are epilepsy and general health. \n\n" # Modified response intro
-            "**Tip:** For topics unrelated to epilepsy or health, you might find better answers using a general search engine or a chatbot trained on a broader range of topics."
+            f"**NeuroGuard:** 💡  My expertise is focused on epilepsy and general health.  For topics outside of these areas, like '{user_query}', I may not be the best resource. \n\n" # Use original user_query
+            "**Tip:** For general knowledge questions, you might find better answers using a general search engine or a chatbot trained on a broader range of topics."
         )
 
     # Fallback - should ideally not reach here