Allow configuring additional concerns that users may want the AI to note

This commit is contained in:
Nicolas Mowen 2025-08-11 11:49:19 -06:00
parent e5e4cbf12a
commit c873c1c902
6 changed files with 77 additions and 37 deletions

View File

@ -69,6 +69,10 @@ class GenAIReviewConfig(FrigateBaseModel):
)
alerts: bool = Field(default=True, title="Enable GenAI for alerts.")
detections: bool = Field(default=False, title="Enable GenAI for detections.")
additional_concerns: list[str] = Field(
default=[],
title="Additional concerns that GenAI should make note of on this camera.",
)
debug_save_thumbnails: bool = Field(
default=False,
title="Save thumbnails sent to generative AI for debugging purposes.",

View File

@ -46,8 +46,9 @@ class ReviewDescriptionProcessor(PostProcessorApi):
return
camera = data["after"]["camera"]
camera_config = self.config.cameras[camera]
if not self.config.cameras[camera].review.genai.enabled:
if not camera_config.review.genai.enabled:
return
id = data["after"]["id"]
@ -59,12 +60,12 @@ class ReviewDescriptionProcessor(PostProcessorApi):
if (
final_data["severity"] == "alert"
and not self.config.cameras[camera].review.genai.alerts
and not camera_config.review.genai.alerts
):
return
elif (
final_data["severity"] == "detection"
and not self.config.cameras[camera].review.genai.detections
and not camera_config.review.genai.detections
):
return
@ -86,9 +87,7 @@ class ReviewDescriptionProcessor(PostProcessorApi):
if ret:
thumbs.append(jpg.tobytes())
if self.config.cameras[
data["after"]["camera"]
].review.genai.debug_save_thumbnails:
if camera_config.review.genai.debug_save_thumbnails:
id = data["after"]["id"]
Path(os.path.join(CLIPS_DIR, f"genai-requests/{id}")).mkdir(
parents=True, exist_ok=True
@ -112,6 +111,7 @@ class ReviewDescriptionProcessor(PostProcessorApi):
camera,
final_data,
thumbs,
camera_config.review.genai.additional_concerns,
),
).start()
@ -161,6 +161,7 @@ def run_analysis(
camera: str,
final_data: dict[str, str],
thumbs: list[bytes],
concerns: list[str],
) -> None:
start = datetime.datetime.now().timestamp()
metadata = genai_client.generate_review_description(
@ -172,6 +173,7 @@ def run_analysis(
"timestamp": datetime.datetime.fromtimestamp(final_data["end_time"]),
},
thumbs,
concerns,
)
review_inference_speed.update(datetime.datetime.now().timestamp() - start)

View File

@ -13,3 +13,7 @@ class ReviewMetadata(BaseModel):
le=3,
description="An integer representing the potential threat level (1-3). 1: Minor anomaly. 2: Moderate concern. 3: High threat. Only include this field if a clear security concern is observable; otherwise, omit it.",
)
other_concerns: list[str] | None = Field(
default=None,
description="Other concerns highlighted by the user that are observed.",
)

View File

@ -37,39 +37,53 @@ class GenAIClient:
self.provider = self._init_provider()
def generate_review_description(
self, review_data: dict[str, Any], thumbnails: list[bytes]
self,
review_data: dict[str, Any],
thumbnails: list[bytes],
concerns: list[str],
) -> ReviewMetadata | None:
"""Generate a description for the review item activity."""
if concerns:
concern_list = "\n - ".join(concerns)
other_concerns = f"""
- `other_concerns` (list of strings): Include a list of any of the following concerns that are occurring:
- {concern_list}
"""
else:
other_concerns = None
context_prompt = f"""
Please analyze the image(s), which are in chronological order, strictly from the perspective of the {review_data["camera"].replace("_", " ")} 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, while also:
- Clearly stating **what is happening** based on observable actions and movements.
- Including **reasonable, evidence-based inferences** about the likely activity or context, but only if directly supported by visible details.
Your task is to provide a **neutral, factual, and objective description** of the scene, while also:
- Clearly stating **what is happening** based on observable actions and movements.
- Including **reasonable, evidence-based inferences** about the likely activity or context, but only if directly supported by visible details.
When forming your description:
- **Facts first**: Describe the time, physical setting, people, and objects exactly as seen.
- **Then context**: Briefly note plausible purposes or activities (e.g., appears to be delivering a package if carrying a box to a door).
- Clearly separate certain facts (A person is holding an object with horizontal rungs) from reasonable inferences (likely a ladder).
- Do not speculate beyond what is visible, and do not imply hostility, criminal intent, or other strong judgments unless there is unambiguous visual evidence.
When forming your description:
- **Facts first**: Describe the time, physical setting, people, and objects exactly as seen.
- **Then context**: Briefly note plausible purposes or activities (e.g., appears to be delivering a package if carrying a box to a door).
- Clearly separate certain facts (A person is holding an object with horizontal rungs) from reasonable inferences (likely a ladder).
- Do not speculate beyond what is visible, and do not imply hostility, criminal intent, or other strong judgments unless there is unambiguous visual evidence.
Here is information already known:
- Activity occurred at {review_data["timestamp"].strftime("%I:%M %p")}
- Detected objects: {review_data["objects"]}
- Recognized objects: {review_data["recognized_objects"]}
- Zones involved: {review_data["zones"]}
Here is information already known:
- Activity occurred at {review_data["timestamp"].strftime("%I:%M %p")}
- Detected objects: {review_data["objects"]}
- Recognized objects: {review_data["recognized_objects"]}
- Zones involved: {review_data["zones"]}
Your response **MUST** be a flat JSON object with:
- `scene` (string): A full description including setting, entities, actions, and any plausible supported inferences.
- `confidence` (float): A number 01 for overall confidence in the analysis.
- `potential_threat_level` (integer, optional): Include only if there is a clear, observable security concern:
- 0 = Normal activity is occurring
- 1 = Unusual but not overtly threatening
- 2 = Suspicious or potentially harmful
- 3 = Clear and immediate threat
Your response **MUST** be a flat JSON object with:
- `scene` (string): A full description including setting, entities, actions, and any plausible supported inferences.
- `confidence` (float): A number 0-1 for overall confidence in the analysis.
- `potential_threat_level` (integer, optional): Include only if there is a clear, observable security concern:
- 0 = Normal activity is occurring
- 1 = Unusual but not overtly threatening
- 2 = Suspicious or potentially harmful
- 3 = Clear and immediate threat
{other_concerns}
**IMPORTANT:**
- Values must be plain strings, floats, or integers no nested objects, no extra commentary.
**IMPORTANT:**
- Values must be plain strings, floats, or integers no nested objects, no extra commentary.
"""
logger.debug(
f"Sending {len(thumbnails)} images to create review description on {review_data['camera']}"

View File

@ -76,20 +76,35 @@ export default function ReviewDetailDialog({
const aiAnalysis = useMemo(() => review?.data?.metadata, [review]);
const aiThreatLevel = useMemo(() => {
if (!aiAnalysis?.potential_threat_level) {
console.log(
`${aiAnalysis?.potential_threat_level} || ${aiAnalysis?.other_concerns}`,
);
if (
!aiAnalysis ||
(!aiAnalysis.potential_threat_level && !aiAnalysis.other_concerns)
) {
return "None";
}
let concerns = "";
switch (aiAnalysis.potential_threat_level) {
case ThreatLevel.UNUSUAL:
return "Unusual Activity";
concerns = "• Unusual Activity\n";
break;
case ThreatLevel.SUSPICIOUS:
return "Suspicious Activity";
concerns = "• Suspicious Activity\n";
break;
case ThreatLevel.DANGER:
return "Danger";
concerns = "• Danger\n";
break;
}
return "Unknown";
(aiAnalysis.other_concerns ?? []).forEach((c) => {
concerns += `${c}\n`;
});
return concerns || "None";
}, [aiAnalysis]);
const hasMismatch = useMemo(() => {
@ -267,7 +282,7 @@ export default function ReviewDetailDialog({
<div className="text-sm">{aiAnalysis.scene}</div>
<div className="text-sm text-primary/40">Score</div>
<div className="text-sm">{aiAnalysis.confidence * 100}%</div>
<div className="text-sm text-primary/40">Threat Level</div>
<div className="text-sm text-primary/40">Concerns</div>
<div className="text-sm">{aiThreatLevel}</div>
</div>
)}

View File

@ -22,6 +22,7 @@ export type ReviewData = {
scene: string;
confidence: number;
potential_threat_level?: number;
other_concerns?: string[];
};
};