From bece44bf7ddd4471cdf7b9bd2c9d3cc4fa774ddf Mon Sep 17 00:00:00 2001 From: Storm Date: Fri, 24 Oct 2025 17:25:25 +0200 Subject: [PATCH] feat: implemented basic belief-from-text extractor The communication with other agents has been tested with mock data as the other agents (transcriber and belief collector) are not yet implemented. ref: N25B-208 --- .../bdi/behaviours/text_belief_extractor.py | 76 +++++++++++++++++++ src/control_backend/agents/bdi/test_agent.py | 26 +++++++ .../agents/bdi/text_extractor.py | 10 +++ src/control_backend/main.py | 8 +- 4 files changed, 119 insertions(+), 1 deletion(-) create mode 100644 src/control_backend/agents/bdi/behaviours/text_belief_extractor.py create mode 100644 src/control_backend/agents/bdi/test_agent.py create mode 100644 src/control_backend/agents/bdi/text_extractor.py diff --git a/src/control_backend/agents/bdi/behaviours/text_belief_extractor.py b/src/control_backend/agents/bdi/behaviours/text_belief_extractor.py new file mode 100644 index 0000000..c73a42e --- /dev/null +++ b/src/control_backend/agents/bdi/behaviours/text_belief_extractor.py @@ -0,0 +1,76 @@ +import asyncio +from spade.behaviour import CyclicBehaviour +import logging +from spade.message import Message +import json +from control_backend.core.config import settings + + +class BeliefFromText(CyclicBehaviour): + logger = logging.getLogger("Belief From Text") + + # TODO: LLM prompt nog hardcoded + llm_instruction_prompt = """ + You are an information extraction assistent for a BDI agent. Your task is to extract values from + a user's text to bind a list of ungrounded beliefs. Rules: + You will receive a JSON object with "beliefs" (a list of ungrounded AgentSpeak beliefs) and "text" (user's transcript). + Analyze the text to find values that sematically match the variables (X,Y,Z) in the beliefs. + A single piece of text might contain multiple instances that match a belief. + Respond ONLY with a single JSON object. + The JSON object's keys should be the belief functors (e.g., "weather"). + The value for each key must be a list of lists. + Each inner list must contain the extracted arguments (as strings) for one instance of that belief. + CRITICAL: If no information in the text matches a belief, DO NOT include that key in your response. + """ + + # on_start agent receives message containing the beliefs to look out for and sets up the LLM with instruction prompt + #async def on_start(self): + # msg = await self.receive(timeout=0.1) + # self.beliefs = dict uit message + # send instruction prompt to LLM + + beliefs: dict[str,list[str]] + beliefs = { + "mood": ["X"], + "car": ["Y"] + } + + async def run(self): + msg = await self.receive(timeout=0.1) + if msg: + sender = msg.sender.node + match sender: + # TODO: Change to Transcriber agent name once implemented + case settings.agent_settings.test_agent_name: + self.logger.info("Received text from transcriber.") + await self._process_transcription(msg.body) + case _: + self.logger.info("Received message from other agent.") + pass + await asyncio.sleep(1) + + async def _process_transcription(self,text: str): + text_prompt = f"Text: {text}" + + beliefs_prompt = "These are the beliefs to be bound:\n" + for belief, values in self.beliefs.items(): + beliefs_prompt += f"{belief}({', '.join(values)})\n" + + prompt = text_prompt + beliefs_prompt + self.logger.info(prompt) + #prompt_msg = Message(to="LLMAgent@whatever") + #response = self.send(prompt_msg) + + # Mock response; response is beliefs in JSON format, it parses do dict[str,list[list[str]]] + response = '{"mood": [["happy"]]}' + # Verify by trying to parse + try: + json.loads(response) + belief_message = Message(to=settings.agent_settings.bdi_core_agent_name + '@' + settings.agent_settings.host, body=response) + belief_message.thread = "beliefs" + + await self.send(belief_message) + self.logger.info("Sent beliefs to BDI.") + except: + #loading failed so the response is in wrong format, throw warning (let LLM respond to ask again?) + self.logger.warning("Received LLM response in incorrect format.") \ No newline at end of file diff --git a/src/control_backend/agents/bdi/test_agent.py b/src/control_backend/agents/bdi/test_agent.py new file mode 100644 index 0000000..eea2065 --- /dev/null +++ b/src/control_backend/agents/bdi/test_agent.py @@ -0,0 +1,26 @@ +import spade +from spade.agent import Agent +from spade.behaviour import OneShotBehaviour +from spade.message import Message +from spade.template import Template +from control_backend.core.config import AgentSettings, settings + +class SenderAgent(Agent): + class InformBehav(OneShotBehaviour): + async def run(self): + msg = Message(to=settings.agent_settings.text_belief_extractor_agent_name + '@' + settings.agent_settings.host) # Instantiate the message + msg.body = "This is a test input to extract beliefs from.\n" # Set the message content + + await self.send(msg) + print("Message sent!") + + # set exit_code for the behaviour + self.exit_code = "Job Finished!" + + # stop agent from behaviour + await self.agent.stop() + + async def setup(self): + print("SenderAgent started") + self.b = self.InformBehav() + self.add_behaviour(self.b) \ No newline at end of file diff --git a/src/control_backend/agents/bdi/text_extractor.py b/src/control_backend/agents/bdi/text_extractor.py new file mode 100644 index 0000000..2806a73 --- /dev/null +++ b/src/control_backend/agents/bdi/text_extractor.py @@ -0,0 +1,10 @@ +import spade +from spade.agent import Agent +import logging + +from control_backend.agents.bdi.behaviours.text_belief_extractor import BeliefFromText + +class TBeliefExtractor(Agent): + async def setup(self): + self.b = BeliefFromText() + self.add_behaviour(self.b) \ No newline at end of file diff --git a/src/control_backend/main.py b/src/control_backend/main.py index 1f377c4..10b4081 100644 --- a/src/control_backend/main.py +++ b/src/control_backend/main.py @@ -13,6 +13,8 @@ import zmq # Internal imports from control_backend.agents.bdi.bdi_core import BDICoreAgent +from control_backend.agents.bdi.text_extractor import TBeliefExtractor +from control_backend.agents.bdi.test_agent import SenderAgent from control_backend.api.v1.router import api_router from control_backend.core.config import AgentSettings, settings from control_backend.core.zmq_context import context @@ -32,8 +34,12 @@ async def lifespan(app: FastAPI): logger.info("Internal publishing socket bound to %s", internal_comm_socket) # Initiate agents - bdi_core = BDICoreAgent(settings.agent_settings.bdi_core_agent_name + '@' + settings.agent_settings.host, settings.agent_settings.bdi_core_agent_name, "src/control_backend/agents/bdi/rules.asl") + bdi_core = BDICoreAgent(settings.agent_settings.bdi_core_agent_name + '@' + settings.agent_settings.host, "pohpu7-huqsyH-qutduk", "src/control_backend/agents/bdi/rules.asl") await bdi_core.start() + text_belief_extractor = TBeliefExtractor(settings.agent_settings.text_belief_extractor_agent_name + '@' + settings.agent_settings.host, "pohpu7-huqsyH-qutduk") + await text_belief_extractor.start() + test_agent = SenderAgent(settings.agent_settings.test_agent_name + '@' + settings.agent_settings.host, "pohpu7-huqsyH-qutduk") + await test_agent.start() yield