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Nicolas Mowen 2025-08-09 13:38:41 -06:00
parent 5876695aa1
commit 686fdef665
1 changed files with 22 additions and 19 deletions
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41
frigate/genai/__init__.py
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@ -41,31 +41,34 @@ class GenAIClient:
"""Generate a description for the review item activity."""
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.
Your task is to provide a **neutral, factual, and objective description** of the scene, while also including **reasonable, evidence-based inferences** about the likely context or activity — but do not make unfounded assumptions.
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:
- Base all statements on visible details in the images.
- You may deduce plausible intent or context only if supported by clear, observable evidence (e.g., someone carrying tools toward a car may indicate vehicle maintenance).
- Avoid implying hostility, criminal intent, or other strong judgments unless the visual evidence is unambiguous.
- Distinguish between what is certain (facts) and what appears likely (reasonable inference).
- **Facts first**: Describe the 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 a ladder”) from reasonable inferences (“likely performing maintenance”).
- 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 some information we already know:
- The activity occurred at {review_data["timestamp"].strftime("%I:%M %p")}
- 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"]}
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 the following fields:
- `scene` (string): A comprehensive description of the setting and entities, including relevant context and plausible inferences if supported by visual evidence.
- `confidence` (float): A float between 0 and 1 representing your overall confidence in this analysis.
- `potential_threat_level` (integer, optional): 1–3 scale. Only include if a clear security concern is visible:
- 1 = Unusual but not overtly threatening
- 2 = Suspicious or potentially harmful
- 3 = Clear and immediate threat
Omit this field entirely if there is no observable security concern.
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:
- 1 = Unusual but not overtly threatening
- 2 = Suspicious or potentially harmful
- 3 = Clear and immediate threat
Omit this field if no concern is evident.
**IMPORTANT:**
Values for each field must be plain strings or integers — no nested objects or explanatory text.
- Values must be plain strings, floats, or integers — no nested objects, no extra commentary.
"""
response = self._send(context_prompt, thumbnails)