Classify input features using VSA similarity against feature-based class…

Required scope: write

POST /api/v1/nsr/vsa/classify

cURL

curl --request POST \
  --url 'https://api.nsr.stateset.com/api/v1/nsr/vsa/classify' \
  --header "X-API-Key: $STATESET_NSR_API_KEY" \
  --header 'Content-Type: application/json' \
  --data '{
  "class_prototypes": [
    {
      "features": [],
      "label": "Replacement tent pole set"
    }
  ],
  "input_features": [
    "string"
  ],
  "top_k": 1
}'

200

{
  "dimension": 1,
  "enabled": true,
  "prediction": "string",
  "results": [
    [
      {
        "0": "s",
        "1": "t",
        "2": "r",
        "3": "i",
        "4": "n",
        "5": "g"
      }
    ]
  ],
  "score": 7.5
}

Required scope: write

Request body

VSAClassifyRequest

class_prototypes · VSAClassPrototype[] · required

Class prototypes expressed as feature bundles

input_features · string[] · required

Input feature concept names (e.g., [‘has_fur’, ‘meows’])

top_k · integer

Number of results to return (default: 5)

Response

VSAClassifyResponse

dimension · integer · required

Vector dimension

enabled · boolean · required

Whether VSA is enabled

prediction · string

Predicted class label (highest similarity)

results · object[][] · required

Ranked results (label, similarity)

score · number (double)

Similarity score for the predicted class

Status codes

Code	Meaning
200	Classification result
400	Invalid request
401	Unauthorized — missing or invalid credentials
403	Forbidden — the key/token lacks the required scope
429	Rate limited — see Retry-After / X-RateLimit-Reset
503	VSA not enabled

cURL

curl --request POST \
  --url 'https://api.nsr.stateset.com/api/v1/nsr/vsa/classify' \
  --header "X-API-Key: $STATESET_NSR_API_KEY" \
  --header 'Content-Type: application/json' \
  --data '{
  "class_prototypes": [
    {
      "features": [],
      "label": "Replacement tent pole set"
    }
  ],
  "input_features": [
    "string"
  ],
  "top_k": 1
}'

200

{
  "dimension": 1,
  "enabled": true,
  "prediction": "string",
  "results": [
    [
      {
        "0": "s",
        "1": "t",
        "2": "r",
        "3": "i",
        "4": "n",
        "5": "g"
      }
    ]
  ],
  "score": 7.5
}