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fix: Resolve deadlock and attribute error in embedding maintainer initialization

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Updates the trigger embedding calculation to call embedding methods directly instead of using ZMQ. This prevents a deadlock during initialization where the ZMQ responder is not yet polling for requests.

Also updates sync_triggers to pass the camera name and trigger name to the calculation method, fixing an AttributeError where trigger.name was accessed on a TriggerConfig object.
This commit is contained in:
user 2025-12-11 14:03:56 -05:00
parent 9cdc10008d
commit 6407e4ba55
1 changed files with 11 additions and 20 deletions
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31
frigate/embeddings/embeddings.py
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@ -12,9 +12,6 @@ from peewee import DoesNotExist, IntegrityError
from PIL import Image
from playhouse.shortcuts import model_to_dict
from frigate.comms.embeddings_updater import (
EmbeddingsRequestEnum,
)
from frigate.comms.inter_process import InterProcessRequestor
from frigate.config import FrigateConfig
from frigate.config.classification import SemanticSearchModelEnum
@ -495,7 +492,7 @@ class Embeddings:
or thumbnail_missing
):
existing_trigger.embedding = self._calculate_trigger_embedding(
trigger
trigger, trigger_name, camera.name
)
needs_embedding_update = True
@ -532,7 +529,7 @@ class Embeddings:
)
# Calculate embedding for new trigger
embedding = self._calculate_trigger_embedding(trigger)
embedding = self._calculate_trigger_embedding(trigger, trigger_name, camera.name)
Trigger.create(
camera=camera.name,
@ -588,13 +585,12 @@ class Embeddings:
f"Failed to delete thumbnail for trigger with data {event_id} in {camera}: {e}"
)
def _calculate_trigger_embedding(self, trigger) -> bytes:
def _calculate_trigger_embedding(self, trigger, trigger_name: str, camera_name: str) -> bytes:
"""Calculate embedding for a trigger based on its type and data."""
if trigger.type == "description":
logger.debug(f"Generating embedding for trigger description {trigger.name}")
embedding = self.requestor.send_data(
EmbeddingsRequestEnum.embed_description.value,
{"id": None, "description": trigger.data, "upsert": False},
logger.debug(f"Generating embedding for trigger description {trigger_name}")
embedding = self.embed_description(
None, trigger.data, upsert=False
)
return embedding.astype(np.float32).tobytes()
@ -616,27 +612,22 @@ class Embeddings:
try:
with open(
os.path.join(
TRIGGER_DIR, trigger.camera, f"{trigger.data}.webp"
TRIGGER_DIR, camera_name, f"{trigger.data}.webp"
),
"rb",
) as f:
thumbnail = f.read()
except Exception as e:
logger.error(
f"Failed to read thumbnail for trigger {trigger.name} with ID {trigger.data}: {e}"
f"Failed to read thumbnail for trigger {trigger_name} with ID {trigger.data}: {e}"
)
return b""
logger.debug(
f"Generating embedding for trigger thumbnail {trigger.name} with ID {trigger.data}"
f"Generating embedding for trigger thumbnail {trigger_name} with ID {trigger.data}"
)
embedding = self.requestor.send_data(
EmbeddingsRequestEnum.embed_thumbnail.value,
{
"id": str(trigger.data),
"thumbnail": str(thumbnail),
"upsert": False,
},
embedding = self.embed_thumbnail(
str(trigger.data), thumbnail, upsert=False
)
return embedding.astype(np.float32).tobytes()