Collections are where processed documents live. They define how outputs are stored after feature extraction and serve as the main retrieval surface.

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Overview

  • What they store: Structured documents produced by feature extractors.
  • Inputs: Typically ingest from a bucket (raw objects) or another collection.
  • Consistency: All documents in a collection share a schema determined by configured feature extractors.
  • Retrieval: Retrievers query one or more collections to return ranked results.

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Collection model

Minimum fields when creating a collection. See the endpoint at Create Collection. 
{
  "collection_name": "products_v1",
  "description": "Product catalog (images + text)",
  "source": {"type": "BUCKET", "bucket_id": "bkt_123"},
  "feature_extractors": [
    {
      "feature_extractor_name": "gte_modernbert_base",
      "version": "1.0.0"
    }
  ],
  "metadata": {"env": "prod"}
}
  • source.type: BUCKET or COLLECTION.
  • feature_extractors: Which models generate vectors/fields for documents.
  • metadata: User-defined metadata attached to the collection record.

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Create a collection

  • API: Create Collection
  • Method: POST
  • Path: /v1/collections
  • Reference: API Reference
curl -X POST https://api.mixpeek.com/v1/collections \
  -H "Authorization: Bearer $API_KEY" \
  -H "X-Namespace: ns_123" \
  -H "Content-Type: application/json" \
  -d '{
    "collection_name": "products_v1",
    "description": "Product catalog (images + text)",
    "source": {"type": "BUCKET", "bucket_id": "bkt_123"},
    "feature_extractors": [
      {"feature_extractor_name": "gte_modernbert_base", "version": "1.0.0"}
    ]
  }'

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Describe available features

List configured feature addresses and metadata for a collection.
  • API: Describe Collection Features
  • Method: GET
  • Path: /v1/collections/{collection_identifier}/features
  • Reference: API Reference

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Manage collections

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Documents in collections

Documents are created by pipelines and stored in the target collection. Use Collection Documents APIs to read/update.

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Used by

  • Retrievers: Query collections for search results.
  • Taxonomies: Enrich documents using similarity joins; configured against collection IDs.
  • Clusters: Build and analyze clusters over vectors from one or more collections.

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Behavior & validation

  • Schema: Determined by feature extractor outputs; documents must conform.
  • Lineage: Documents maintain references to the source object and processing metadata.
  • Enablement: Collections can be enabled/disabled via the update endpoint.

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See also

Buckets

Define schemas for raw objects and register uploads

Feature Extractors

Supported extractors and configurations

Retrievers

Compose staged pipelines to search collections

Collection Documents

APIs to query and manage documents