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POST
/
v1
/
collections
/
list
List Collections
curl --request POST \
  --url https://api.mixpeek.com/v1/collections/list \
  --header 'Content-Type: application/json' \
  --data '
{
  "filters": {},
  "sort": {
    "field": "created_at",
    "direction": "desc"
  },
  "search": "<string>",
  "case_sensitive": false
}
'
{
  "results": [
    {
      "collection_name": "<string>",
      "input_schema": {
        "properties": {}
      },
      "output_schema": {
        "properties": {}
      },
      "feature_extractor": {
        "feature_extractor_name": "<string>",
        "version": "<string>",
        "feature_extractor_id": "<string>",
        "params": {},
        "parameters": {
          "chunk_overlap": 0,
          "chunk_size": 1000,
          "description": "E-commerce product search (no chunking, default settings)",
          "expected_behavior": "Find semantically similar products even if they use different wording. Entire product description becomes one document.",
          "extractor_type": "text_extractor",
          "input_example": "wireless bluetooth headphones with noise cancelling",
          "split_by": "none",
          "use_case": "Search 1M products by natural language descriptions",
          "split_method": "time",
          "time_split_interval": 10
        },
        "input_mappings": {
          "image": "product_image",
          "text": "title"
        },
        "field_passthrough": [
          {
            "source_path": "<string>",
            "target_path": "title",
            "default": "Unknown",
            "required": false
          }
        ],
        "include_all_source_fields": false
      },
      "source": {
        "type": "bucket",
        "bucket_ids": [
          "bkt_marketing_videos"
        ],
        "collection_id": "col_video_frames",
        "collection_ids": [
          "col_us_products",
          "col_eu_products"
        ],
        "inherited_bucket_ids": [
          "bkt_marketing_videos"
        ],
        "source_filters": {
          "description": "Filter only video content",
          "filters": {
            "AND": [
              {
                "field": "blobs.type",
                "operator": "eq",
                "value": "video"
              }
            ]
          }
        }
      },
      "collection_id": "<string>",
      "description": "Video frames extracted at 1 FPS with CLIP embeddings",
      "source_bucket_schemas": null,
      "source_lineage": [
        {
          "source_config": {
            "type": "bucket",
            "bucket_ids": [
              "bkt_marketing_videos"
            ],
            "collection_id": "col_video_frames",
            "collection_ids": [
              "col_us_products",
              "col_eu_products"
            ],
            "inherited_bucket_ids": [
              "bkt_marketing_videos"
            ],
            "source_filters": {
              "description": "Filter only video content",
              "filters": {
                "AND": [
                  {
                    "field": "blobs.type",
                    "operator": "eq",
                    "value": "video"
                  }
                ]
              }
            }
          },
          "feature_extractor": {
            "feature_extractor_name": "<string>",
            "version": "<string>",
            "feature_extractor_id": "<string>",
            "params": {},
            "parameters": {
              "chunk_overlap": 0,
              "chunk_size": 1000,
              "description": "E-commerce product search (no chunking, default settings)",
              "expected_behavior": "Find semantically similar products even if they use different wording. Entire product description becomes one document.",
              "extractor_type": "text_extractor",
              "input_example": "wireless bluetooth headphones with noise cancelling",
              "split_by": "none",
              "use_case": "Search 1M products by natural language descriptions",
              "split_method": "time",
              "time_split_interval": 10
            },
            "input_mappings": {
              "image": "product_image",
              "text": "title"
            },
            "field_passthrough": [
              {
                "source_path": "<string>",
                "target_path": "title",
                "default": "Unknown",
                "required": false
              }
            ],
            "include_all_source_fields": false
          },
          "output_schema": {
            "properties": {}
          }
        }
      ],
      "vector_indexes": [
        "<unknown>"
      ],
      "payload_indexes": [
        "<unknown>"
      ],
      "enabled": true,
      "metadata": {
        "environment": "production",
        "project": "Q4_campaign",
        "team": "data-science"
      },
      "created_at": "2023-11-07T05:31:56Z",
      "updated_at": "2023-11-07T05:31:56Z",
      "document_count": 123,
      "schema_version": 1,
      "last_schema_sync": "2023-11-07T05:31:56Z",
      "schema_sync_enabled": true,
      "taxonomy_applications": null,
      "cluster_applications": null,
      "taxonomy_count": 123,
      "retriever_count": 123
    }
  ],
  "pagination": {
    "total": 123,
    "page": 123,
    "page_size": 123,
    "total_pages": 123,
    "next_page": "<string>",
    "previous_page": "<string>",
    "next_cursor": "<string>"
  },
  "total_count": 123,
  "stats": {
    "total_documents": 0,
    "avg_documents_per_collection": 0,
    "collections_with_taxonomies": 0,
    "total_feature_extractors": 0,
    "total_taxonomies": 0,
    "total_retrievers": 0
  }
}

Headers

​
Authorization
string

REQUIRED: Bearer token authentication using your API key. Format: 'Bearer sk_xxxxxxxxxxxxx'. You can create API keys in the Mixpeek dashboard under Organization Settings.

Examples:

"Bearer YOUR_API_KEY"

"Bearer YOUR_STRIPE_API_KEY"

​
X-Namespace
string

REQUIRED: Namespace identifier for scoping this request. All resources (collections, buckets, taxonomies, etc.) are scoped to a namespace. You can provide either the namespace name or namespace ID. Format: ns_xxxxxxxxxxxxx (ID) or a custom name like 'my-namespace'

Examples:

"ns_abc123def456"

"production"

"my-namespace"

Query Parameters

​
limit
integer | null
Required range: 1 <= x <= 1000
​
offset
integer | null
Required range: 0 <= x <= 10000
​
cursor
string | null
​
include_total
boolean
default:false

Body

application/json

Request model for listing collections.

To filter by taxonomy, use dot notation in filters: filters.AND = [{"field": "taxonomy_applications.taxonomy_id", "operator": "eq", "value": "tax_123"}]

​
filters
Filters · object

Filters to apply when listing collections. Supports nested field filtering like 'taxonomy_applications.taxonomy_id'. Format: {"AND": [{"field": "field_name", "operator": "eq", "value": "value"}]}

​
sort
SortOption · object

Sort options for the results

​
search
string | null

Search term for wildcard search across collection_id, collection_name, description, and other text fields

​
case_sensitive
boolean
default:false

If True, filters and search will be case-sensitive

Response

Successful Response

Response model for listing collections.

​
results
CollectionResponse · object[]
required

List of collections

​
pagination
PaginationResponse · object
required

Pagination information

​
total_count
integer
required

Total number of collections matching the query

​
stats
CollectionListStats · object

Aggregate statistics across all collections in the result