v5

latestOpenAPI 3.1.02026-08-025631,1012.8 MB

Namespace Extractors

Get extractor details

Get detailed information about a specific extractor.

Works for both builtin extractors and custom plugins.

Parameters:

extractor_id: Extractor identifier (e.g., 'text_extractor_v1', 'my_custom_plugin_1_0_0')

Response includes:

Full schema information (input, output, parameters)
Vector index configuration
For custom plugins: deployment status, validation status

get/v1/namespaces/{namespace_id}/extractors/{extractor_id}

Path parameters

namespace_idstring required

extractor_idstring required

Response

Extractor details

feature_extractor_namestring required

Name of the feature extractor

versionstring required

Version of the feature extractor

feature_extractor_idstring required

Unique identifier (name_version)

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

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

descriptionstring required

Human-readable description

iconstring

Lucide-react icon name for frontend rendering

input_schemaobject required

JSON schema for input data

output_schemaobject required

JSON schema for output data

parameter_schemaobject nullable

JSON schema for parameters

type_modestring nullable

What input types this extractor can handle: 'type_specific' (only one type, e.g. video-only) or 'multimodal' (handles multiple types with conditional processing). 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', 'thumbnail': 'image'}). For multimodal extractors: null.

inference_typestring nullable

Kind of real-time inference this extractor provides: 'embedding', 'rerank', 'classify', 'generate', or 'general'. Determines which retriever stages are compatible. Null if the extractor is batch-only.

supported_input_typesstring[]

Supported input types (video, image, text, etc.)

max_inputsobject

Maximum number of inputs per type

default_parametersobject

Default parameter values

position_fieldsstring[]

Fields that identify unique positions within output documents. Used for deterministic document ID generation.

feature_uristring nullable

Primary feature URI (e.g., mixpeek://text_extractor@v1/embedding)

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

plugin_idstring nullable

Plugin ID (custom plugins only)

deployedboolean nullable

Whether the plugin is deployed (custom plugins only)

validation_status'passed' | 'failed' | 'pending' nullable

Validation status (custom plugins only)

created_atstring date-time nullable

Creation timestamp (custom plugins only)

updated_atstring date-time nullable

Last update timestamp (custom plugins only)

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"
    }
  ]
}