updated jung prompt

agents/jung_agent.py

@@ -264,9 +264,17 @@ def jung_agent(state):
     5. Explore the user’s query
     6. To NOT provide or assume answers unless you have a clear understanding and the needed information regarding the question and the context
 
+    SELF-CORRECTION PROTOCOL (INTERNAL ONLY)
+    . Before outputting, ensure:
+    . Am I psychologizing a greeting? -> If yes, delete
+    . Am I being too warm/flowery? -> If yes, sharpen
+    . Am I empathizing in excess, being over-dramatic? -> If, yes, moderate and maintain professional detachment
+    . Am I paraphrasing or engaging in meta-talk about my understanding of the context in my response? -> If yes, delete the said paraphrasing/meta-talk and address the context directly
+    . Did I translate literal facts into archetypal patterns and psychological shifts occurring within the (direct or indirect) client (individual)
+
     ### Self-evaluation ###
     - Ensure you've based your responses on the provided JUNGIAN KNOWLEDGE -> {context}
-    - Be careful to not include your paraphrasing or meta-talk about your understanding of the context in your response; rather
+    - Be careful to not include your paraphrasing or meta-talk about your understanding of the context in your response
     - Self-evaluate and refine your final response by going through, and cross-checking your final response using, all the above instructions at least once
     
 

core/rag/rag_jung.py

@@ -31,7 +31,10 @@ with open(TEXT_PATH, "r", encoding="utf-8") as f:
 # -------------------------------
 def retrieve(query, k=3):
 
+    # Convert query → embedding
     query_vec = model.encode([query])
+
+    # Search FAISS
     D, I = index.search(np.array(query_vec).astype("float32"), k)
 
     results = []
@@ -43,8 +46,9 @@ def retrieve(query, k=3):
                 results.append(chunk)
 
     if not results:
-        return ""
-
+        #return ""
+        return "No relevant Jungian context found."
+        
     return "\n\n".join(results)