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Merge remote-tracking branch 'origin/dev' into feat/use-experiment-logs

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# Conflicts:
#	src/control_backend/agents/llm/llm_agent.py
This commit is contained in:
Twirre Meulenbelt
2026-01-27 18:42:18 +01:00
parent 941aa00b7b 0413e0f710
commit 4b6980a26e
8 changed files with 267 additions and 41 deletions
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6
src/control_backend/agents/bdi/bdi_core_agent.py
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@@ -348,7 +348,7 @@ class BDICoreAgent(BaseAgent):
yield
@self.actions.add(".reply_with_goal", 3)
def _reply_with_goal(agent: "BDICoreAgent", term, intention):
def _reply_with_goal(agent, term, intention):
"""
Let the LLM generate a response to a user's utterance with the current norms and a
specific goal.
@@ -524,10 +524,6 @@ class BDICoreAgent(BaseAgent):
yield
@self.actions.add(".notify_ui", 0)
def _notify_ui(agent, term, intention):
pass
async def _send_to_llm(self, text: str, norms: str, goals: str):
"""
Sends a text query to the LLM agent asynchronously.

3
src/control_backend/agents/bdi/text_belief_extractor_agent.py
View File

@@ -345,6 +345,9 @@ class TextBeliefExtractorAgent(BaseAgent):
async with httpx.AsyncClient() as client:
response = await client.post(
settings.llm_settings.local_llm_url,
headers={"Authorization": f"Bearer {settings.llm_settings.api_key}"}
if settings.llm_settings.api_key
else {},
json={
"model": settings.llm_settings.local_llm_model,
"messages": [{"role": "user", "content": prompt}],

58
src/control_backend/agents/llm/llm_agent.py
View File

@@ -1,3 +1,4 @@
import asyncio
import json
import logging
import re
@@ -35,6 +36,10 @@ class LLMAgent(BaseAgent):
def __init__(self, name: str):
super().__init__(name)
self.history = []
self._querying = False
self._interrupted = False
self._interrupted_message = ""
self._go_ahead = asyncio.Event()
async def setup(self):
self.logger.info("Setting up %s.", self.name)
@@ -53,13 +58,13 @@ class LLMAgent(BaseAgent):
case "prompt_message":
try:
prompt_message = LLMPromptMessage.model_validate_json(msg.body)
await self._process_bdi_message(prompt_message)
self.add_behavior(self._process_bdi_message(prompt_message)) # no block
except ValidationError:
self.logger.debug("Prompt message from BDI core is invalid.")
case "assistant_message":
self.history.append({"role": "assistant", "content": msg.body})
self._apply_conversation_message({"role": "assistant", "content": msg.body})
case "user_message":
self.history.append({"role": "user", "content": msg.body})
self._apply_conversation_message({"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.")
@@ -76,12 +81,45 @@ class LLMAgent(BaseAgent):
:param message: The parsed prompt message containing text, norms, and goals.
"""
if self._querying:
self.logger.debug("Received another BDI prompt while processing previous message.")
self._interrupted = True # interrupt the previous processing
await self._go_ahead.wait() # wait until we get the go-ahead
message.text = f"{self._interrupted_message} {message.text}"
self._go_ahead.clear()
self._querying = True
full_message = ""
async for chunk in self._query_llm(message.text, message.norms, message.goals):
if self._interrupted:
self._interrupted_message = message.text
self.logger.debug("Interrupted processing of previous message.")
break
await self._send_reply(chunk)
full_message += chunk
self.logger.debug("Finished processing BDI message. Response sent in chunks to BDI core.")
await self._send_full_reply(full_message)
else:
self._querying = False
self._apply_conversation_message(
{
"role": "assistant",
"content": full_message,
}
)
self.logger.debug(
"Finished processing BDI message. Response sent in chunks to BDI core."
)
await self._send_full_reply(full_message)
self._go_ahead.set()
self._interrupted = False
def _apply_conversation_message(self, message: dict[str, str]):
if len(self.history) > 0 and message["role"] == self.history[-1]["role"]:
self.history[-1]["content"] += " " + message["content"]
return
self.history.append(message)
async def _send_reply(self, msg: str):
"""
@@ -166,13 +204,6 @@ class LLMAgent(BaseAgent):
full_message,
extra={"role": "assistant", "reference": message_id, "partial": False},
)
self.history.append(
{
"role": "assistant",
"content": full_message,
}
)
except httpx.HTTPError as err:
self.logger.error("HTTP error.", exc_info=err)
yield "LLM service unavailable."
@@ -192,6 +223,9 @@ class LLMAgent(BaseAgent):
async with client.stream(
"POST",
settings.llm_settings.local_llm_url,
headers={"Authorization": f"Bearer {settings.llm_settings.api_key}"}
if settings.llm_settings.api_key
else {},
json={
"model": settings.llm_settings.local_llm_model,
"messages": messages,

4
src/control_backend/agents/perception/transcription_agent/speech_recognizer.py
View File

@@ -145,4 +145,6 @@ class OpenAIWhisperSpeechRecognizer(SpeechRecognizer):
def recognize_speech(self, audio: np.ndarray) -> str:
self.load_model()
return whisper.transcribe(self.model, audio, **self._get_decode_options(audio))["text"]
return whisper.transcribe(self.model, audio, **self._get_decode_options(audio))[
"text"
].strip()

15
src/control_backend/agents/user_interrupt/user_interrupt_agent.py
View File

@@ -9,7 +9,7 @@ from control_backend.agents.bdi.agentspeak_generator import AgentSpeakGenerator
from control_backend.core.agent_system import InternalMessage
from control_backend.core.config import settings
from control_backend.schemas.belief_message import Belief, BeliefMessage
from control_backend.schemas.program import ConditionalNorm, Program
from control_backend.schemas.program import ConditionalNorm, Goal, Program
from control_backend.schemas.ri_message import (
GestureCommand,
PauseCommand,
@@ -249,6 +249,16 @@ class UserInterruptAgent(BaseAgent):
self._cond_norm_map = {}
self._cond_norm_reverse_map = {}
def _register_goal(goal: Goal):
"""Recursively register goals and their subgoals."""
slug = AgentSpeakGenerator.slugify(goal)
self._goal_map[str(goal.id)] = slug
self._goal_reverse_map[slug] = str(goal.id)
for step in goal.plan.steps:
if isinstance(step, Goal):
_register_goal(step)
for phase in program.phases:
for trigger in phase.triggers:
slug = AgentSpeakGenerator.slugify(trigger)
@@ -256,8 +266,7 @@ class UserInterruptAgent(BaseAgent):
self._trigger_reverse_map[slug] = str(trigger.id)
for goal in phase.goals:
self._goal_map[str(goal.id)] = AgentSpeakGenerator.slugify(goal)
self._goal_reverse_map[AgentSpeakGenerator.slugify(goal)] = str(goal.id)
_register_goal(goal)
for goal, id in self._goal_reverse_map.items():
self.logger.debug(f"Goal mapping: UI ID {goal} -> {id}")

1
src/control_backend/core/config.py
View File

@@ -123,6 +123,7 @@ class LLMSettings(BaseModel):
local_llm_url: str = "http://localhost:1234/v1/chat/completions"
local_llm_model: str = "gpt-oss"
api_key: str = ""
chat_temperature: float = 1.0
code_temperature: float = 0.3
n_parallel: int = 4