v5

latestOpenAPI 3.1.02026-08-025631,1012.8 MB
Feature Extractors

List Feature Extractors

List all available feature extractors grouped by category

get/v1/collections/features/extractors

Response

Successful Response

feature_extractor_namestring required
versionstring required
feature_extractor_idstring required
descriptionstring required
iconstring required
categorystring

Category of this extractor, used for UI grouping and filtering. Examples: 'text', 'image', 'multimodal', 'audio', 'video', 'document', 'face', 'corpus', 'utility', 'safety', 'classification', 'web', 'custom'.

source'builtin' | 'custom' | 'community'

The source/origin of a feature extractor.

Values: BUILTIN: Core extractors shipped with Mixpeek (text, image, multimodal, etc.) CUSTOM: User-created extractors uploaded to their namespace (Enterprise only) COMMUNITY: Community-contributed extractors from the Mixpeek marketplace

This field helps API consumers understand:

  • What level of support/maintenance to expect
  • Whether the extractor is available to all users or namespace-specific
  • Licensing and attribution requirements
type_modestring nullable

What input types this extractor can handle: 'type_specific' (only one type) or 'multimodal' (handles multiple types). Type-specific extractors cannot use automatic-typed bucket properties.

expected_input_typesobject nullable

For type-specific extractors: maps input keys to required types (e.g., {'video': 'video'}). For multimodal extractors: null.

inference_typestring nullable

Kind of real-time inference this extractor provides: 'embedding', 'rerank', 'classify', 'generate', or 'general'. Null if batch-only.

input_schemaobject required
output_schemaobject required
parameter_schemaobject nullable required
supported_input_typesstring[] required
max_inputsobject required
default_parametersobject required
position_fieldsstring[]

Output fields that uniquely identify each document within a source object. Enables idempotent reprocessing: rerunning a batch produces the same document IDs, so existing documents are updated instead of creating duplicates. Works with bucket unique_key to enable fully deterministic document IDs. Empty list means single-output extractor (one document per source). Read-only (set by extractor).

capabilitiesstring[]

What this extractor can do: 'batch' (feature extraction during ingestion), 'realtime' (query-time inference for retriever stages)

example_usageobject nullable

Minimal working configuration for namespace + collection + input_mappings + parameters

Example response

[
  {
    "required_vector_indexes": [
      {
        "description": "Vector index for text embeddings using E5-Large model.",
        "index": {
          "datatype": "float32",
          "description": "Dense vector embedding for text content",
          "dimensions": 1024,
          "distance": "cosine",
          "inference_name": "multilingual_e5_large_instruct_v1",
          "name": "text_extractor_v1_embedding",
          "supported_inputs": [
            "text",
            "string"
          ],
          "type": "dense"
        },
        "name": "embedding",
        "type": "single"
      }
    ],
    "required_payload_indexes": [
      {
        "description": "User-created text index for full-text search",
        "field_name": "metadata.description",
        "is_protected": false,
        "type": "text"
      }
    ],
    "position_fields": [
      "start_time",
      "end_time"
    ]
  }
]