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synced 2026-04-27 17:17:40 +03:00
Allow configuring additional concerns that users may want the AI to note
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parent
e5e4cbf12a
commit
c873c1c902
@ -69,6 +69,10 @@ class GenAIReviewConfig(FrigateBaseModel):
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)
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alerts: bool = Field(default=True, title="Enable GenAI for alerts.")
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detections: bool = Field(default=False, title="Enable GenAI for detections.")
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additional_concerns: list[str] = Field(
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default=[],
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title="Additional concerns that GenAI should make note of on this camera.",
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)
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debug_save_thumbnails: bool = Field(
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default=False,
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title="Save thumbnails sent to generative AI for debugging purposes.",
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@ -46,8 +46,9 @@ class ReviewDescriptionProcessor(PostProcessorApi):
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return
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camera = data["after"]["camera"]
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camera_config = self.config.cameras[camera]
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if not self.config.cameras[camera].review.genai.enabled:
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if not camera_config.review.genai.enabled:
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return
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id = data["after"]["id"]
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@ -59,12 +60,12 @@ class ReviewDescriptionProcessor(PostProcessorApi):
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if (
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final_data["severity"] == "alert"
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and not self.config.cameras[camera].review.genai.alerts
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and not camera_config.review.genai.alerts
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):
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return
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elif (
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final_data["severity"] == "detection"
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and not self.config.cameras[camera].review.genai.detections
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and not camera_config.review.genai.detections
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):
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return
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@ -86,9 +87,7 @@ class ReviewDescriptionProcessor(PostProcessorApi):
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if ret:
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thumbs.append(jpg.tobytes())
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if self.config.cameras[
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data["after"]["camera"]
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].review.genai.debug_save_thumbnails:
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if camera_config.review.genai.debug_save_thumbnails:
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id = data["after"]["id"]
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Path(os.path.join(CLIPS_DIR, f"genai-requests/{id}")).mkdir(
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parents=True, exist_ok=True
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@ -112,6 +111,7 @@ class ReviewDescriptionProcessor(PostProcessorApi):
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camera,
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final_data,
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thumbs,
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camera_config.review.genai.additional_concerns,
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),
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).start()
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@ -161,6 +161,7 @@ def run_analysis(
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camera: str,
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final_data: dict[str, str],
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thumbs: list[bytes],
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concerns: list[str],
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) -> None:
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start = datetime.datetime.now().timestamp()
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metadata = genai_client.generate_review_description(
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@ -172,6 +173,7 @@ def run_analysis(
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"timestamp": datetime.datetime.fromtimestamp(final_data["end_time"]),
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},
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thumbs,
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concerns,
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)
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review_inference_speed.update(datetime.datetime.now().timestamp() - start)
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@ -13,3 +13,7 @@ class ReviewMetadata(BaseModel):
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le=3,
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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.",
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)
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other_concerns: list[str] | None = Field(
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default=None,
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description="Other concerns highlighted by the user that are observed.",
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)
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@ -37,39 +37,53 @@ class GenAIClient:
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self.provider = self._init_provider()
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def generate_review_description(
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self, review_data: dict[str, Any], thumbnails: list[bytes]
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self,
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review_data: dict[str, Any],
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thumbnails: list[bytes],
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concerns: list[str],
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) -> ReviewMetadata | None:
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"""Generate a description for the review item activity."""
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if concerns:
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concern_list = "\n - ".join(concerns)
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other_concerns = f"""
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- `other_concerns` (list of strings): Include a list of any of the following concerns that are occurring:
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- {concern_list}
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"""
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else:
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other_concerns = None
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context_prompt = f"""
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Please analyze the image(s), which are in chronological order, strictly from the perspective of the {review_data["camera"].replace("_", " ")} security camera.
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Please analyze the image(s), which are in chronological order, strictly from the perspective of the {review_data["camera"].replace("_", " ")} security camera.
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Your task is to provide a **neutral, factual, and objective description** of the scene, while also:
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- Clearly stating **what is happening** based on observable actions and movements.
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- Including **reasonable, evidence-based inferences** about the likely activity or context, but only if directly supported by visible details.
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Your task is to provide a **neutral, factual, and objective description** of the scene, while also:
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- Clearly stating **what is happening** based on observable actions and movements.
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- Including **reasonable, evidence-based inferences** about the likely activity or context, but only if directly supported by visible details.
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When forming your description:
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- **Facts first**: Describe the time, physical setting, people, and objects exactly as seen.
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- **Then context**: Briefly note plausible purposes or activities (e.g., “appears to be delivering a package” if carrying a box to a door).
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- Clearly separate certain facts (“A person is holding an object with horizontal rungs”) from reasonable inferences (“likely a ladder”).
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- Do not speculate beyond what is visible, and do not imply hostility, criminal intent, or other strong judgments unless there is unambiguous visual evidence.
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When forming your description:
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- **Facts first**: Describe the time, physical setting, people, and objects exactly as seen.
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- **Then context**: Briefly note plausible purposes or activities (e.g., “appears to be delivering a package” if carrying a box to a door).
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- Clearly separate certain facts (“A person is holding an object with horizontal rungs”) from reasonable inferences (“likely a ladder”).
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- Do not speculate beyond what is visible, and do not imply hostility, criminal intent, or other strong judgments unless there is unambiguous visual evidence.
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Here is information already known:
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- Activity occurred at {review_data["timestamp"].strftime("%I:%M %p")}
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- Detected objects: {review_data["objects"]}
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- Recognized objects: {review_data["recognized_objects"]}
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- Zones involved: {review_data["zones"]}
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Here is information already known:
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- Activity occurred at {review_data["timestamp"].strftime("%I:%M %p")}
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- Detected objects: {review_data["objects"]}
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- Recognized objects: {review_data["recognized_objects"]}
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- Zones involved: {review_data["zones"]}
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Your response **MUST** be a flat JSON object with:
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- `scene` (string): A full description including setting, entities, actions, and any plausible supported inferences.
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- `confidence` (float): A number 0–1 for overall confidence in the analysis.
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- `potential_threat_level` (integer, optional): Include only if there is a clear, observable security concern:
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- 0 = Normal activity is occurring
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- 1 = Unusual but not overtly threatening
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- 2 = Suspicious or potentially harmful
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- 3 = Clear and immediate threat
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Your response **MUST** be a flat JSON object with:
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- `scene` (string): A full description including setting, entities, actions, and any plausible supported inferences.
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- `confidence` (float): A number 0-1 for overall confidence in the analysis.
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- `potential_threat_level` (integer, optional): Include only if there is a clear, observable security concern:
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- 0 = Normal activity is occurring
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- 1 = Unusual but not overtly threatening
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- 2 = Suspicious or potentially harmful
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- 3 = Clear and immediate threat
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{other_concerns}
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**IMPORTANT:**
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- Values must be plain strings, floats, or integers — no nested objects, no extra commentary.
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**IMPORTANT:**
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- Values must be plain strings, floats, or integers — no nested objects, no extra commentary.
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"""
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logger.debug(
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f"Sending {len(thumbnails)} images to create review description on {review_data['camera']}"
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@ -76,20 +76,35 @@ export default function ReviewDetailDialog({
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const aiAnalysis = useMemo(() => review?.data?.metadata, [review]);
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const aiThreatLevel = useMemo(() => {
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if (!aiAnalysis?.potential_threat_level) {
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console.log(
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`${aiAnalysis?.potential_threat_level} || ${aiAnalysis?.other_concerns}`,
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);
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if (
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!aiAnalysis ||
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(!aiAnalysis.potential_threat_level && !aiAnalysis.other_concerns)
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) {
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return "None";
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}
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let concerns = "";
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switch (aiAnalysis.potential_threat_level) {
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case ThreatLevel.UNUSUAL:
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return "Unusual Activity";
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concerns = "• Unusual Activity\n";
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break;
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case ThreatLevel.SUSPICIOUS:
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return "Suspicious Activity";
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concerns = "• Suspicious Activity\n";
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break;
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case ThreatLevel.DANGER:
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return "Danger";
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concerns = "• Danger\n";
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break;
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}
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return "Unknown";
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(aiAnalysis.other_concerns ?? []).forEach((c) => {
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concerns += `• ${c}\n`;
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});
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return concerns || "None";
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}, [aiAnalysis]);
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const hasMismatch = useMemo(() => {
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@ -267,7 +282,7 @@ export default function ReviewDetailDialog({
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<div className="text-sm">{aiAnalysis.scene}</div>
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<div className="text-sm text-primary/40">Score</div>
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<div className="text-sm">{aiAnalysis.confidence * 100}%</div>
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<div className="text-sm text-primary/40">Threat Level</div>
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<div className="text-sm text-primary/40">Concerns</div>
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<div className="text-sm">{aiThreatLevel}</div>
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</div>
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)}
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@ -22,6 +22,7 @@ export type ReviewData = {
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scene: string;
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confidence: number;
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potential_threat_level?: number;
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other_concerns?: string[];
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};
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};
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