Update agent.py

agent.py

@@ -192,10 +192,23 @@ def build_graph(provider: str = "groq"):
     # Bind tools to LLM
     llm_with_tools = llm.bind_tools(tools)
 
-    # Node
     def assistant(state: MessagesState):
         """Assistant node"""
-        return {"messages": [llm_with_tools.invoke(state["messages"])]}
+        print("\n🧠 Final prompt to model:")
+        for m in state["messages"]:
+            print(f"{m.type.upper()}: {m.content[:300]}...\n")  # truncate for readability
+        
+        response = llm_with_tools.invoke(state["messages"])
+        
+        print("💬 Model response:", response.content[:500], "\n")
+        return {"messages": [response]}
+
+    # Node
+    # def assistant(state: MessagesState):
+    #     """Assistant node"""
+    #     return {"messages": [llm_with_tools.invoke(state["messages"])]}
+
+        
     
     # def retriever(state: MessagesState):
     #     """Retriever node"""
@@ -213,44 +226,27 @@ def build_graph(provider: str = "groq"):
             return {"messages": []}
         
         query = messages[0].content
-        similar_question = vector_store.similarity_search(query)
+        print(f"\n🔍 Query to vector store: {query}")
+        
+        try:
+            similar_question = vector_store.similarity_search(query)
+        except Exception as e:
+            print(f"❌ similarity_search failed: {e}")
+            return {"messages": messages}
         
         if not similar_question:
             print("⚠️ No similar questions found.")
             return {"messages": messages}
         
+        print(f"✅ Found {len(similar_question)} similar question(s).")
+        print("📄 First retrieved doc:\n", similar_question[0].page_content)
+        
         example_msg = HumanMessage(
-            content=f"Here I provide a similar question and answer for reference:\n\n{similar_question[0].page_content}",
+            content=f"Here I provide a similar question and answer for reference:\n\n{similar_question[0].page_content}"
         )
-        
         return {"messages": [sys_msg] + messages + [example_msg]}
 
-    #     def retriever(state: MessagesState):
-    #         """Retriever node"""
-    #         messages = state.get("messages", [])
-    #         if not messages:
-    #             print("⚠️ No messages received in retriever node.")
-    #             return {"messages": []}
-        
-    #         query = messages[0].content
-    #         print(f"🔍 Querying vector store with: {query}")
-        
-    #         try:
-    #             similar_question = vector_store.similarity_search(query)
-    #             print(f"✅ Retrieved {len(similar_question)} similar questions.")
-    #         except Exception as e:
-    #             print(f"❌ Error during similarity_search: {e}")
-    #             return {"messages": messages}
-        
-    #         if not similar_question:
-    #             print("⚠️ No similar questions found.")
-    #             return {"messages": messages}
-        
-    #         example_msg = HumanMessage(
-    #             content=f"Here I provide a similar question and answer for reference:\n\n{similar_question[0].page_content}"
-    #         )
-        
-    #         return {"messages": [sys_msg] + messages + [example_msg]}
+
 
 
     builder = StateGraph(MessagesState)
@@ -277,4 +273,5 @@ if __name__ == "__main__":
     messages = [HumanMessage(content=question)]
     messages = graph.invoke({"messages": messages})
     for m in messages["messages"]:
-        m.pretty_print()
+        m.pretty_print()
+