Update state messages and Add agent depths

src/agents.py

@@ -31,6 +31,14 @@ def __init__(self):
                 agent_name = agent_name.split(".")[0]
                 self.prompts[agent_name] = f.read()
 
+        self.depths = {
+            "intent_classifier": 1,
+            "general_campus_query": 2,
+            "course_query": 2,
+            "not_related_query": 2,
+            "long_term_memory": 3,
+        }
+
     def _get_prompt(
         self, agent_name: str, user_input: str, agent_scratchpad=False
     ) -> ChatPromptTemplate:
@@ -63,7 +71,7 @@ def intent_classifier(self, query: str, chat_history: str) -> str:
             }
         )
 
-        return result
+        return result.content
 
     def general_campus_query(self, query: str, chat_history: str) -> str:
         PROMPT_TEMPLATE = self._get_prompt(

src/nodes.py

@@ -9,44 +9,55 @@
 
 
 def intent_classifier(state: State):
-    query = state["messages"][0].content
-    result = agents.intent_classifier(query, state.get("chat_history", ""))
-
+    query = state["messages"][-agents.depths["intent_classifier"]].content
+    result = AIMessage(agents.intent_classifier(query, state.get("chat_history", "")))
     return {"messages": [result]}
 
 
 def course_query(state: State):
-    query = state["messages"][0].content
+    query = state["messages"][-agents.depths["course_query"]].content
     result = AIMessage("Course query not implemented yet")
     # Add short term memory here once implemented.
     return {"messages": [result]}
 
 
 def general_campus_query(state: State):
-    query = state["messages"][0].content
-    result = agents.general_campus_query(query, state.get("chat_history", ""))
-    add_short_term_memory(state["user_id"], query, result, "general_campus_query")
+    query = state["messages"][-agents.depths["general_campus_query"]].content
+    result = AIMessage(
+        agents.general_campus_query(query, state.get("chat_history", ""))
+    )
+    add_short_term_memory(
+        state["user_id"],
+        query,
+        result.content,
+        "general_campus_query",
+    )
     return {"messages": [result]}
 
 
 def not_related_query(state: State):
-    query = state["messages"][0].content
+    query = state["messages"][-agents.depths["not_related_query"]].content
     result = AIMessage(
         "I'm sorry, I don't understand the question, if it relates to campus please rephrase."
     )
     add_short_term_memory(
-        state["user_id"], query, not_related_query, "intent_classifier"
+        state["user_id"],
+        query,
+        "not_related_query",
+        "intent_classifier",
     )
     return {"messages": [result]}
 
 
 def long_term_memory(state: State):
-    query = state["messages"][0].content
+    query = state["messages"][-agents.depths["long_term_memory"]].content
     user_id = state["user_id"]
     long_term_memories = parse_long_term_memory(state.get("long_term_memories", []))
-    result = agents.long_term_memory(
-        user_id,
-        query,
-        long_term_memories,
+    result = AIMessage(
+        agents.long_term_memory(
+            user_id,
+            query,
+            long_term_memories,
+        )
     )
     return {"messages": [result]}

src/state.py

@@ -1,5 +1,6 @@
 from typing import Annotated, Optional
 
+from langchain_core.messages import AIMessage, HumanMessage
 from langgraph.graph.message import add_messages
 from typing_extensions import TypedDict
 
@@ -8,6 +9,6 @@
 
 class State(TypedDict):
     user_id: str
-    messages: Annotated[list, add_messages]
+    messages: Annotated[list[AIMessage | HumanMessage], add_messages]
     chat_history: Optional[str]
     long_term_memories: Optional[list[LongTermMemory]]