fix: on topic guardrail

changes guardrail's prompt to take into consideration the conversation instead of just the latest message.
changes the agent's messages to be AI to give the guardrail an opportunity to distinguish between user and ai messages correctly.

app/llm/guardrails/on_topic.py

@@ -33,13 +33,17 @@ def on_topic_guard():
         "assistant capabilities inquiry",
         "information gathering about applications",
         "information gathering about access",
+        "asking for clarification about the conversation or previous messages",
         "action repetition request",
     ]
     template = """
-      Your job is to determine if the user's input is on topic. 
+      Your job is to determine if the conversation is on topic. 
       Any of the following topics are allowed, together or individually: 
       {allowed_topics}
 
+      The conversation is valid if the entire conversation is on topic or if the latest human message
+      tries to bring it back on topic.
+
       {format_instructions}
     """
     pv = {

app/llm/nodes.py

@@ -3,7 +3,7 @@
 import json
 from types import coroutine
 
-from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
+from langchain_core.messages import AIMessage, ToolMessage
 
 from app.llm.guardrails.on_topic import topical_guardrail
 from app.llm.tools.deny_access_tool import create_deny_provision_tool
@@ -43,7 +43,7 @@ def agent_node(state, agent_creator, name):
     if isinstance(result, ToolMessage):
         pass
     else:
-        result = HumanMessage(content=result["output"], name=name)
+        result = AIMessage(content=result["output"], name=name)
 
     return {
         MEMORY_KEY: [result],