Update app.py

app.py

@@ -79,10 +79,20 @@ def respond(
         if val[1]:
             messages.append({"role": "assistant", "content": val[1]})
 
-    # 🔹 Search policy text efficiently
+    # 🔹 Retrieve policy info related to the query
     policy_context = search_policy(message)
+
     if policy_context:
-        messages.append({"role": "system", "content": f"Relevant Policy Info:\n{policy_context}"})
+        # 🔹 Force the LLM to use retrieved policy text
+        system_context = f"""
+        You are an expert in Colorado public assistance policies. 
+        Below is relevant information retrieved from official policy documents:
+
+        {policy_context}
+
+        Based on this information, answer the user's question accurately and concisely.
+        """
+        messages.append({"role": "system", "content": system_context})
 
     messages.append({"role": "user", "content": message})
 
@@ -98,6 +108,7 @@ def respond(
         response += token
         yield response
 
+
 # 🔹 Gradio Chat Interface
 demo = gr.ChatInterface(
     respond,