updated

backend/services/codingo_chatbot.py

@@ -177,13 +177,16 @@ def _build_prompt(query: str, context: str) -> str:
     Returns:
         A formatted string prompt ready for submission to the Groq LLM.
     """
-    system_prompt = (
-        "You are LUNA, the friendly AI assistant for the Codingo recruitment "
-        "platform. You only answer questions using the information provided "
-        "in the context below. If the context does not contain the answer, "
-        "respond politely that you don't know. Keep your answers concise and "
-        "helpful."
-    )
+    system_prompt = """
+        You are LUNA, the official AI assistant of Codingo, an AI-powered recruitment platform.
+        You must:
+        - Answer questions using ONLY the provided context.
+        - Be concise, clear, and professional.
+        - If the context does not have the answer, politely say you do not know.
+        - Never make up features or information not in the context.
+        - Always focus on Codingo’s platform, services, and functionality.
+        """
+
 
     if context:
         return (
@@ -203,7 +206,7 @@ def _build_prompt(query: str, context: str) -> str:
         )
 
 
-def get_response(query: str, k: int = 3, score_threshold: float = 1.5) -> str:
+def get_response(query: str, k: int = 3, score_threshold: float = 2.0) -> str:
     """
     Generate a response to the user's query using the shared Groq LLM and the
     chatbot's knowledge base.  The function retrieves relevant context
@@ -251,10 +254,18 @@ def get_response(query: str, k: int = 3, score_threshold: float = 1.5) -> str:
 
     # If no relevant context is found, politely admit ignorance
     if not relevant:
-        return (
-            "I'm sorry, I don't know the answer to that question based on my knowledge. "
-            "Could you ask something else about Codingo or its services?"
-        )
+        try:
+            with open(CHATBOT_TXT_PATH, encoding="utf-8") as f:
+                full_context = f.read()
+            context = full_context
+        except FileNotFoundError:
+            return (
+                "I'm sorry, I don't know the answer to that question based on my knowledge. "
+                "Could you ask something else about Codingo or its services?"
+            )
+    else:
+        context = "\n\n".join(relevant[:2])
+
 
     # Concatenate the most relevant passages for context (use top 2)
     context = "\n\n".join(relevant[:2])