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POST
/
analyze-frame
{
  "error": {
    "code": "BAD_REQUEST",
    "message": "Invalid base64 frame data: Incorrect padding",
    "remediation": "Ensure frame_b64 is valid base64-encoded JPEG data"
  }
}

{
  "answer": "Yes, there is a person visible in the center of the frame.",
  "triggered": true,
  "latency_ms": 1250,
  "frame_b64": null
}
Analyze a pre-captured image frame with VLM. Use this when you have your own frame capture mechanism (like TrioClaw) and just need VLM analysis — no stream URL validation or capture required.

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How It Differs From Other Endpoints

  • POST /analyze-frame — Accepts raw base64 frame, no stream URL
  • POST /check-once — Captures frame from stream URL, validates liveness
  • POST /live-monitor — Creates continuous monitoring job

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Use Cases

  • TrioClaw — Desktop app that captures frames locally and needs VLM analysis
  • Custom pipelines — Your own frame capture (RTSP, screenshots, etc.)
  • Batch processing — Analyze many pre-captured images without stream overhead

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Question Styles

Supports two question types:

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Yes/No Conditions

"Is there a person?"
"Is the traffic light red?"
"Are cars moving?"
Response includes triggered: true/false.

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Open-Ended Questions

"What do you see?"
"Describe the weather conditions."
"What is the text in this image?"
Response includes answer with full description, triggered: null.

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Request

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Response

{
  "answer": "Yes, there is a person visible in the center of the frame.",
  "triggered": true,
  "latency_ms": 1250,
  "frame_b64": null
}

{
  "answer": "The image shows a blue sky with scattered white clouds.",
  "triggered": null,
  "latency_ms": 890,
  "frame_b64": "/9j/4AAQSkZJRg..."
}

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Error Handling

{
  "error": {
    "code": "BAD_REQUEST",
    "message": "Invalid base64 frame data: Incorrect padding",
    "remediation": "Ensure frame_b64 is valid base64-encoded JPEG data"
  }
}

{
  "error": {
    "code": "BAD_REQUEST",
    "message": "Frame data too small — expected a JPEG image",
    "remediation": "Ensure the base64 data represents a valid JPEG image"
  }
}

Authorizations

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Authorization
string
header
required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Body

application/json

Request to analyze a single image frame with VLM.

Used by TrioClaw and other clients that capture their own frames and just need VLM analysis — no stream URL or live validation needed.

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frame_b64
string
required

Base64-encoded JPEG image (raw base64, no data: URI prefix)

Minimum string length: 1
​
question
string
required

Question or condition about the image (e.g., 'what do you see?' or 'is there a person?')

Required string length: 1 - 1000
​
include_frame
boolean
default:false

Include the frame back in the response

Response

Successful Response

Response from frame analysis.

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answer
string
required

VLM's analysis of the image

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latency_ms
integer
required

Total processing time in milliseconds

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triggered
boolean | null

Whether a yes/no condition was met (null for open-ended questions)

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frame_b64
string | null

The analyzed frame (only if include_frame was true)