Merge remote-tracking branch 'origin/feat/reset-experiment-and-phase' into feat/visual-emotion-recognition

src/control_backend/core/agent_system.py

@@ -120,7 +120,7 @@ class BaseAgent(ABC):
             task.cancel()
         self.logger.info(f"Agent {self.name} stopped")
 
-    async def send(self, message: InternalMessage):
+    async def send(self, message: InternalMessage, should_log: bool = True):
         """
         Send a message to another agent.
 
@@ -142,13 +142,17 @@ class BaseAgent(ABC):
 
             if target:
                 await target.inbox.put(message)
-                self.logger.debug(f"Sent message {message.body} to {message.to} via regular inbox.")
+                if should_log:
+                    self.logger.debug(
+                        f"Sent message {message.body} to {message.to} via regular inbox."
+                    )
             else:
                 # Apparently target agent is on a different process, send via ZMQ
                 topic = f"internal/{receiver}".encode()
                 body = message.model_dump_json().encode()
                 await self._internal_pub_socket.send_multipart([topic, body])
-                self.logger.debug(f"Sent message {message.body} to {message.to} via ZMQ.")
+                if should_log:
+                    self.logger.debug(f"Sent message {message.body} to {message.to} via ZMQ.")
 
     async def _process_inbox(self):
         """
@@ -158,7 +162,6 @@ class BaseAgent(ABC):
         """
         while self._running:
             msg = await self.inbox.get()
-            self.logger.debug(f"Received message from {msg.sender}.")
             await self.handle_message(msg)
 
     async def _receive_internal_zmq_loop(self):
@@ -201,7 +204,16 @@ class BaseAgent(ABC):
 
         :param coro: The coroutine to execute as a task.
         """
-        task = asyncio.create_task(coro)
+
+        async def try_coro(coro_: Coroutine):
+            try:
+                await coro_
+            except asyncio.CancelledError:
+                self.logger.debug("A behavior was canceled successfully: %s", coro_)
+            except Exception:
+                self.logger.warning("An exception occurred in a behavior.", exc_info=True)
+
+        task = asyncio.create_task(try_coro(coro))
         self._tasks.add(task)
         task.add_done_callback(self._tasks.discard)
         return task

src/control_backend/core/config.py

@@ -74,10 +74,12 @@ class BehaviourSettings(BaseModel):
     :ivar vad_prob_threshold: Probability threshold for Voice Activity Detection.
     :ivar vad_initial_since_speech: Initial value for 'since speech' counter in VAD.
     :ivar vad_non_speech_patience_chunks: Number of non-speech chunks to wait before speech ended.
+    :ivar vad_begin_silence_chunks: The number of chunks of silence to prepend to speech chunks.
     :ivar transcription_max_concurrent_tasks: Maximum number of concurrent transcription tasks.
     :ivar transcription_words_per_minute: Estimated words per minute for transcription timing.
     :ivar transcription_words_per_token: Estimated words per token for transcription timing.
     :ivar transcription_token_buffer: Buffer for transcription tokens.
+    :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
@@ -89,7 +91,8 @@ class BehaviourSettings(BaseModel):
     # VAD settings
     vad_prob_threshold: float = 0.5
     vad_initial_since_speech: int = 100
-    vad_non_speech_patience_chunks: int = 3
+    vad_non_speech_patience_chunks: int = 15
+    vad_begin_silence_chunks: int = 6
 
     # transcription behaviour
     transcription_max_concurrent_tasks: int = 3
@@ -97,6 +100,9 @@ class BehaviourSettings(BaseModel):
     transcription_words_per_token: float = 0.75  # (3 words = 4 tokens)
     transcription_token_buffer: int = 10
 
+    # Text belief extractor settings
+    conversation_history_length_limit: int = 10
+
 
 class LLMSettings(BaseModel):
     """
@@ -104,12 +110,19 @@ class LLMSettings(BaseModel):
 
     :ivar local_llm_url: URL for the local LLM API.
     :ivar local_llm_model: Name of the local LLM model to use.
+    :ivar chat_temperature: The temperature to use while generating chat responses.
+    :ivar code_temperature: The temperature to use while generating code-like responses like during
+        belief inference.
+    :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
+    code_temperature: float = 0.3
+    n_parallel: int = 4
 
 
 class VADSettings(BaseModel):