feat: norms and goals to llm

base goals and norms can be defined in llm_instructions.py
cleaned the code

ref: N25B-215

src/control_backend/agents/llm/llm.py

@@ -15,6 +15,7 @@ from spade.message import Message
 from spade.template import Template
 
 from control_backend.core.config import settings
+from control_backend.agents.llm.llm_instructions import LLMInstructions
 
 
 class LLMAgent(Agent):
@@ -32,7 +33,7 @@ class LLMAgent(Agent):
         the BDI Core Agent and handle them.
         """
 
-        async def run(self) -> None:
+        async def run(self):
             """
             Receives SPADE messages and processes only those originating from the
             configured BDI agent.
@@ -54,7 +55,7 @@ class LLMAgent(Agent):
             else:
                 self.agent.logger.debug("Message ignored (not from BDI Core Agent)")
 
-        async def _process_bdi_message(self, message: Message) -> None:
+        async def _process_bdi_message(self, message: Message):
             """
             Forwards user text to the LLM and replies with the generated text.
             """
@@ -62,14 +63,13 @@ class LLMAgent(Agent):
             llm_response = await self._query_llm(user_text)
             await self._reply(llm_response)
 
-        async def _reply(self, msg: str) -> None:
+        async def _reply(self, msg: str):
             """
             Sends a response message back to the BDI Core Agent.
             """
             reply = Message(
                 to= settings.agent_settings.bdi_core_agent_name + '@' + settings.agent_settings.host,
-                body= msg,
-                thread= "llm_response",
+                body= msg
             )
             await self.send(reply)
             self.agent.logger.info("Reply sent to BDI Core Agent")
@@ -82,15 +82,30 @@ class LLMAgent(Agent):
             :return: LLM-generated content or fallback message.
             """
             async with httpx.AsyncClient(timeout=120.0) as client:
+                # Example dynamic content for future (optional)
+                
+                instructions = LLMInstructions()
+                developer_instruction = instructions.build_developer_instruction()
+                
                 response = await client.post(
                     settings.llm_settings.local_llm_url,
                     headers={"Content-Type": "application/json"},
                     json={
                         "model": settings.llm_settings.local_llm_model,
-                        "messages": [{"role": "user", "content": prompt}],
-                        "temperature": 0.3,
+                        "messages": [
+                            {
+                                "role": "developer",
+                                "content": developer_instruction
+                            },
+                            {
+                                "role": "user",
+                                "content": prompt
+                            }
+                        ],
+                        "temperature": 0.3
                     },
                 )
+
                 try:
                     response.raise_for_status()
                     data: dict[str, Any] = response.json()
@@ -104,15 +119,12 @@ class LLMAgent(Agent):
                     self.agent.logger.error("Unexpected error: %s", err)
                     return "Error processing the request."
 
-    async def setup(self) -> None:
+    async def setup(self):
         """
         Sets up the SPADE behaviour to filter and process messages from the
         BDI Core Agent.
         """
         self.logger.info("LLMAgent setup complete")
 
-        template = Template()
-        template.sender = settings.agent_settings.bdi_core_agent_name + '@' + settings.agent_settings.host
-
         behaviour = self.ReceiveMessageBehaviour()
-        self.add_behaviour(behaviour, template)
+        self.add_behaviour(behaviour)