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Code Issues Actions 2 Packages Projects Releases Wiki Activity

testing prompt changes

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This commit is contained in:
Nicolas Mowen 2025-08-07 05:37:37 -06:00
parent 22fb06ff53
commit 9316f0ea80
2 changed files with 19 additions and 13 deletions
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8
frigate/embeddings/maintainer.py
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@ -152,10 +152,6 @@ class EmbeddingMaintainer(threading.Thread):
self.detected_license_plates: dict[str, dict[str, Any]] = {} self.detected_license_plates: dict[str, dict[str, Any]] = {}
self.post_processors.append(
ReviewDescriptionProcessor(self.config, self.metrics)
)
# model runners to share between realtime and post processors # model runners to share between realtime and post processors
if self.config.lpr.enabled: if self.config.lpr.enabled:
lpr_model_runner = LicensePlateModelRunner( lpr_model_runner = LicensePlateModelRunner(
@ -210,6 +206,10 @@ class EmbeddingMaintainer(threading.Thread):
# post processors # post processors
self.post_processors: list[PostProcessorApi] = [] self.post_processors: list[PostProcessorApi] = []
self.post_processors.append(
ReviewDescriptionProcessor(self.config, self.metrics)
)
if self.config.lpr.enabled: if self.config.lpr.enabled:
self.post_processors.append( self.post_processors.append(
LicensePlatePostProcessor( LicensePlatePostProcessor(

24
frigate/genai/__init__.py
View File

@ -9,6 +9,7 @@ from typing import Any, Optional
from playhouse.shortcuts import model_to_dict from playhouse.shortcuts import model_to_dict
from frigate.config import CameraConfig, FrigateConfig, GenAIConfig, GenAIProviderEnum from frigate.config import CameraConfig, FrigateConfig, GenAIConfig, GenAIProviderEnum
from frigate.data_processing.post.types import ReviewMetadata
from frigate.models import Event from frigate.models import Event
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -40,19 +41,24 @@ class GenAIClient:
"""Generate a description for the review item activity.""" """Generate a description for the review item activity."""
context_prompt = f""" context_prompt = f"""
Here is additional context about the scene from a security camera: Here is additional context about the scene from a security camera:
{json.dumps(review_data, indent=2)} The following objects were detected: {review_data['objects']}
The following recognized objects were detected: {review_data['recognized_objects']}
The activity happened in the following zones: {review_data['zones']}
Please analyze the image(s), which are in chronological order, strictly from the perspective of a security camera. Please analyze the image(s), which are in chronological order, strictly from the perspective of the {review_data["camera"].replace("_", " ")} security camera.
Your task is to provide a **neutral, factual, and objective description** of the scene. Your task is to provide a **neutral, factual, and objective description** of the scene.
**Do not make assumptions about intent, emotions, or potential threats.**
Focus solely on observable actions, visible entities, and the environment. Focus solely on observable actions, visible entities, and the environment.
Describe: Your response **MUST** be a flat JSON object with the following fields:
- What is happening? - `scene` (string): A single, comprehensive description of the entire visual scene.
- Who or what is visible? - `action` (string): A single description of any key actions or movements.
- What are the entities doing? - `potential_threat_level` (integer, optional): An integer from 0 to 3. Only include if a clear security concern is visible. Omit if no threat.
- What is the environmental context (e.g., time of day, weather, lighting)?
""" **IMPORTANT:** The value for each field (e.g., "scene", "action") must be a plain string or integer, NOT another JSON object or a description of the field itself.
Provide the response in the exact JSON format specified by this schema:
{ReviewMetadata.model_json_schema()}
"""
logger.info(f"processing {review_data}") logger.info(f"processing {review_data}")
logger.info(f"Got GenAI review: {self._send(context_prompt, thumbnails)}") logger.info(f"Got GenAI review: {self._send(context_prompt, thumbnails)}")