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Merge branch 'dev' into feat/extra-agentspeak-functionality

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# Conflicts:
#	src/control_backend/agents/bdi/bdi_program_manager.py
#	src/control_backend/agents/llm/llm_agent.py
#	test/unit/agents/bdi/test_bdi_program_manager.py
This commit is contained in:
Kasper Marinus
2026-01-07 17:46:48 +01:00
parent 8a77e8e1c7 612a96940d
commit 240624f887
13 changed files with 168 additions and 42 deletions
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2
src/control_backend/agents/actuation/robot_gesture_agent.py
View File

@@ -33,7 +33,7 @@ class RobotGestureAgent(BaseAgent):
def __init__(
self,
name: str,
address=settings.zmq_settings.ri_command_address,
address: str,
bind=False,
gesture_data=None,
single_gesture_data=None,

17
src/control_backend/agents/bdi/bdi_program_manager.py
View File

@@ -167,12 +167,28 @@ class BDIProgramManager(BaseAgent):
await self.send(message)
async def _send_clear_llm_history(self):
"""
Clear the LLM Agent's conversation history.
Sends an empty history to the LLM Agent to reset its state.
"""
message = InternalMessage(
to=settings.agent_settings.llm_name,
sender=self.name,
body="clear_history",
threads="clear history message",
)
await self.send(message)
self.logger.debug("Sent message to LLM agent to clear history.")
async def _receive_programs(self):
"""
Continuous loop that receives program updates from the HTTP endpoint.
It listens to the ``program`` topic on the internal ZMQ SUB socket.
When a program is received, it is validated and forwarded to BDI via :meth:`_send_to_bdi`.
Additionally, the LLM history is cleared via :meth:`_send_clear_llm_history`.
"""
while True:
topic, body = await self.sub_socket.recv_multipart()
@@ -189,6 +205,7 @@ class BDIProgramManager(BaseAgent):
self._create_agentspeak_and_send_to_bdi(program),
self._send_beliefs_to_semantic_belief_extractor(),
self._send_goals_to_semantic_belief_extractor(),
self._send_clear_llm_history(),
)
async def setup(self):

4
src/control_backend/agents/communication/ri_communication_agent.py
View File

@@ -38,7 +38,7 @@ class RICommunicationAgent(BaseAgent):
def __init__(
self,
name: str,
address=settings.zmq_settings.ri_command_address,
address=settings.zmq_settings.ri_communication_address,
bind=False,
):
super().__init__(name)
@@ -168,7 +168,7 @@ class RICommunicationAgent(BaseAgent):
bind = port_data["bind"]
if not bind:
addr = f"tcp://localhost:{port}"
addr = f"tcp://{settings.ri_host}:{port}"
else:
addr = f"tcp://*:{port}"

6
src/control_backend/agents/llm/llm_agent.py
View File

@@ -57,8 +57,12 @@ class LLMAgent(BaseAgent):
self.history.append({"role": "assistant", "content": msg.body})
case "user_message":
self.history.append({"role": "user", "content": msg.body})
elif msg.sender == settings.agent_settings.bdi_program_manager_name:
if msg.body == "clear_history":
self.logger.debug("Clearing conversation history.")
self.history.clear()
else:
self.logger.debug("Message ignored (not from BDI core.")
self.logger.debug("Message ignored.")
async def _process_bdi_message(self, message: LLMPromptMessage):
"""

12
src/control_backend/agents/perception/vad_agent.py
View File

@@ -103,12 +103,11 @@ class VADAgent(BaseAgent):
self._connect_audio_in_socket()
audio_out_port = self._connect_audio_out_socket()
if audio_out_port is None:
audio_out_address = self._connect_audio_out_socket()
if audio_out_address is None:
self.logger.error("Could not bind output socket, stopping.")
await self.stop()
return
audio_out_address = f"tcp://localhost:{audio_out_port}"
# Connect to internal communication socket
self.program_sub_socket = azmq.Context.instance().socket(zmq.SUB)
@@ -161,13 +160,14 @@ class VADAgent(BaseAgent):
self.audio_in_socket.connect(self.audio_in_address)
self.audio_in_poller = SocketPoller[bytes](self.audio_in_socket)
def _connect_audio_out_socket(self) -> int | None:
def _connect_audio_out_socket(self) -> str | None:
"""
Returns the port bound, or None if binding failed.
Returns the address that was bound to, or None if binding failed.
"""
try:
self.audio_out_socket = azmq.Context.instance().socket(zmq.PUB)
return self.audio_out_socket.bind_to_random_port("tcp://localhost", max_tries=100)
self.audio_out_socket.bind(settings.zmq_settings.vad_pub_address)
return settings.zmq_settings.vad_pub_address
except zmq.ZMQBindError:
self.logger.error("Failed to bind an audio output socket after 100 tries.")
self.audio_out_socket = None

31
src/control_backend/core/config.py
View File

@@ -1,3 +1,12 @@
"""
An exhaustive overview of configurable options. All of these can be set using environment variables
by nesting with double underscores (__). Start from the ``Settings`` class.
For example, ``settings.ri_host`` becomes ``RI_HOST``, and
``settings.zmq_settings.ri_communication_address`` becomes
``ZMQ_SETTINGS__RI_COMMUNICATION_ADDRESS``.
"""
from pydantic import BaseModel
from pydantic_settings import BaseSettings, SettingsConfigDict
@@ -8,16 +17,17 @@ class ZMQSettings(BaseModel):
:ivar internal_pub_address: Address for the internal PUB socket.
:ivar internal_sub_address: Address for the internal SUB socket.
:ivar ri_command_address: Address for sending commands to the Robot Interface.
:ivar ri_communication_address: Address for receiving communication from the Robot Interface.
:ivar vad_agent_address: Address for the Voice Activity Detection (VAD) agent.
:ivar ri_communication_address: Address for the endpoint that the Robot Interface connects to.
:ivar vad_pub_address: Address that the VAD agent binds to and publishes audio segments to.
"""
# ATTENTION: When adding/removing settings, make sure to update the .env.example file
internal_pub_address: str = "tcp://localhost:5560"
internal_sub_address: str = "tcp://localhost:5561"
ri_command_address: str = "tcp://localhost:0000"
ri_communication_address: str = "tcp://*:5555"
internal_gesture_rep_adress: str = "tcp://localhost:7788"
vad_pub_address: str = "inproc://vad_stream"
class AgentSettings(BaseModel):
@@ -36,6 +46,8 @@ class AgentSettings(BaseModel):
:ivar robot_speech_name: Name of the Robot Speech Agent.
"""
# ATTENTION: When adding/removing settings, make sure to update the .env.example file
# agent names
bdi_core_name: str = "bdi_core_agent"
bdi_belief_collector_name: str = "belief_collector_agent"
@@ -68,6 +80,8 @@ class BehaviourSettings(BaseModel):
:ivar conversation_history_length_limit: The maximum amount of messages to extract beliefs from.
"""
# ATTENTION: When adding/removing settings, make sure to update the .env.example file
sleep_s: float = 1.0
comm_setup_max_retries: int = 5
socket_poller_timeout_ms: int = 100
@@ -99,6 +113,8 @@ class LLMSettings(BaseModel):
:ivar n_parallel: The number of parallel calls allowed to be made to the LLM.
"""
# ATTENTION: When adding/removing settings, make sure to update the .env.example file
local_llm_url: str = "http://localhost:1234/v1/chat/completions"
local_llm_model: str = "gpt-oss"
chat_temperature: float = 1.0
@@ -115,6 +131,8 @@ class VADSettings(BaseModel):
:ivar sample_rate_hz: Sample rate in Hz for the VAD model.
"""
# ATTENTION: When adding/removing settings, make sure to update the .env.example file
repo_or_dir: str = "snakers4/silero-vad"
model_name: str = "silero_vad"
sample_rate_hz: int = 16000
@@ -128,6 +146,8 @@ class SpeechModelSettings(BaseModel):
:ivar openai_model_name: Model name for OpenAI-based speech recognition.
"""
# ATTENTION: When adding/removing settings, make sure to update the .env.example file
# model identifiers for speech recognition
mlx_model_name: str = "mlx-community/whisper-small.en-mlx"
openai_model_name: str = "small.en"
@@ -139,6 +159,7 @@ class Settings(BaseSettings):
:ivar app_title: Title of the application.
:ivar ui_url: URL of the frontend UI.
:ivar ri_host: The hostname of the Robot Interface.
:ivar zmq_settings: ZMQ configuration.
:ivar agent_settings: Agent name configuration.
:ivar behaviour_settings: Behavior configuration.
@@ -151,6 +172,8 @@ class Settings(BaseSettings):
ui_url: str = "http://localhost:5173"
ri_host: str = "localhost"
zmq_settings: ZMQSettings = ZMQSettings()
agent_settings: AgentSettings = AgentSettings()