Mirrors/blakeblackshear.frigate
1
0
Fork 0
mirror of https://github.com/blakeblackshear/frigate.git synced 2025-09-05 17:51:36 +02:00
Code Issues Projects Releases Wiki Activity

Improved prompt

Browse Source
This commit is contained in:
Nicolas Mowen 2025-08-13 18:53:15 -06:00
parent 4b33e3765e
commit 6a56ec8463
1 changed files with 18 additions and 12 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

30
frigate/genai/__init__.py
View File

@ -65,6 +65,12 @@ class GenAIClient:
context_prompt = f"""
Please analyze the sequence of images ({len(thumbnails)} total) taken in chronological order from the perspective of the {review_data["camera"].replace("_", " ")} security camera.
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): 0-1 confidence in the analysis.
- `potential_threat_level` (integer): 0, 1, or 2 as defined below.
{get_concern_prompt()}
Your task is to provide a clear, security-focused description of the scene that:
1. States exactly what is happening based on observable actions and movements.
2. Identifies and emphasizes behaviors that match patterns of suspicious activity.
@ -78,25 +84,25 @@ When forming your description:
- Focus on behaviors that are uncharacteristic of innocent activity: loitering without clear purpose, avoiding cameras, inspecting vehicles/doors, changing behavior when lights activate, scanning surroundings without an apparent benign reason.
- **Benign context override**: If scanning or looking around is clearly part of an innocent activity (such as playing with a dog, gardening, supervising children, or watching for a pet), do not treat it as suspicious.
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): 0-1 confidence in the analysis.
- `potential_threat_level` (integer): 0, 1, or 2 as defined below.
{get_concern_prompt()}
Recognized Objects:
- These are people, vehicles, or other entities that the system has positively identified.
- Always use these names or labels directly in the scene description instead of generic terms.
- If a recognized object is a known resident, family member, neighbor, frequent visitor, or commonly seen vehicle/service, this generally reduces suspicion unless clear malicious activity is observed.
- Recognized objects: {list(set(review_data["recognized_objects"])) or "None"}
Sequence details:
- Frame 1 = earliest, Frame 10 = latest
- Activity occurred at {review_data["timestamp"].strftime("%I:%M %p")}
- Detected objects: {list(set(review_data["objects"]))}
- Zones involved: {review_data["zones"]}
Threat-level definitions:
- 0 — Typical or expected activity for this location/time (includes residents, guests, or known animals engaged in normal activities, even if they glance around or scan surroundings).
- 1 — Unusual or suspicious activity: At least one security-relevant behavior is present **and not explainable by a normal residential activity**.
- 2 — Active or immediate threat: Breaking in, vandalism, aggression, weapon display.
Sequence details:
- Frame 1 = earliest, Frame 10 = latest
- Activity occurred at {review_data["timestamp"].strftime("%I:%M %p")}
- Detected objects: {list(set(review_data["objects"]))}
- Recognized objects: {list(set(review_data["recognized_objects"])) or "None"}
- Zones involved: {review_data["zones"]}
**IMPORTANT:**
- Output must be one flat JSON object, nothing else.
- Values must be plain strings, floats, or integers — no nested objects, no extra commentary.
{get_language_prompt()}
"""