List Collections

curl --request POST \
  --url https://api.mixpeek.com/v1/collections/list \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "limit": 500,
  "page_size": 500,
  "offset": 5000,
  "page": 2,
  "filters": {},
  "sort": {
    "field": "created_at",
    "direction": "desc"
  },
  "sorts": [
    {}
  ],
  "search": "<string>",
  "case_sensitive": false
}
'

import requests

url = "https://api.mixpeek.com/v1/collections/list"

payload = {
    "limit": 500,
    "page_size": 500,
    "offset": 5000,
    "page": 2,
    "filters": {},
    "sort": {
        "field": "created_at",
        "direction": "desc"
    },
    "sorts": [{}],
    "search": "<string>",
    "case_sensitive": False
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    limit: 500,
    page_size: 500,
    offset: 5000,
    page: 2,
    filters: {},
    sort: {field: 'created_at', direction: 'desc'},
    sorts: [{}],
    search: '<string>',
    case_sensitive: false
  })
};

fetch('https://api.mixpeek.com/v1/collections/list', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.mixpeek.com/v1/collections/list",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'limit' => 500,
    'page_size' => 500,
    'offset' => 5000,
    'page' => 2,
    'filters' => [
        
    ],
    'sort' => [
        'field' => 'created_at',
        'direction' => 'desc'
    ],
    'sorts' => [
        [
                
        ]
    ],
    'search' => '<string>',
    'case_sensitive' => false
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.mixpeek.com/v1/collections/list"

	payload := strings.NewReader("{\n  \"limit\": 500,\n  \"page_size\": 500,\n  \"offset\": 5000,\n  \"page\": 2,\n  \"filters\": {},\n  \"sort\": {\n    \"field\": \"created_at\",\n    \"direction\": \"desc\"\n  },\n  \"sorts\": [\n    {}\n  ],\n  \"search\": \"<string>\",\n  \"case_sensitive\": false\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.mixpeek.com/v1/collections/list")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"limit\": 500,\n  \"page_size\": 500,\n  \"offset\": 5000,\n  \"page\": 2,\n  \"filters\": {},\n  \"sort\": {\n    \"field\": \"created_at\",\n    \"direction\": \"desc\"\n  },\n  \"sorts\": [\n    {}\n  ],\n  \"search\": \"<string>\",\n  \"case_sensitive\": false\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.mixpeek.com/v1/collections/list")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"limit\": 500,\n  \"page_size\": 500,\n  \"offset\": 5000,\n  \"page\": 2,\n  \"filters\": {},\n  \"sort\": {\n    \"field\": \"created_at\",\n    \"direction\": \"desc\"\n  },\n  \"sorts\": [\n    {}\n  ],\n  \"search\": \"<string>\",\n  \"case_sensitive\": false\n}"

response = http.request(request)
puts response.read_body

{
  "results": [
    {
      "collection_name": "<string>",
      "feature_extractor": {
        "feature_extractor_name": "<string>",
        "version": "<string>",
        "feature_extractor_id": "<string>",
        "params": {},
        "parameters": {
          "extractor_type": "audio_fingerprint_extractor",
          "normalize_embeddings": true,
          "sample_rate": 48000,
          "segment_duration_sec": 5,
          "segment_hop_sec": 2.5
        },
        "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": {
        "bucket_ids": [
          "bkt_marketing_videos"
        ],
        "source_namespace_id": "<string>",
        "collection_id": "col_video_frames",
        "collection_ids": [
          "col_us_products",
          "col_eu_products"
        ],
        "inherited_bucket_ids": [
          "bkt_marketing_videos"
        ],
        "source_filters": {
          "filters": {
            "AND": [
              {
                "field": "blobs.type",
                "operator": "eq",
                "value": "video"
              }
            ]
          }
        }
      },
      "collection_id": "<string>",
      "description": "Video frames extracted at 1 FPS with CLIP embeddings",
      "input_schema": {
        "properties": {
          "title": {
            "type": "string"
          },
          "content": {
            "type": "text"
          }
        }
      },
      "output_schema": {
        "properties": {
          "title": {
            "type": "string"
          },
          "text_extractor_v1_embedding": {
            "type": "array"
          }
        }
      },
      "source_bucket_schemas": null,
      "source_lineage": [
        {
          "source_config": {
            "bucket_ids": [
              "bkt_marketing_videos"
            ],
            "source_namespace_id": "<string>",
            "collection_id": "col_video_frames",
            "collection_ids": [
              "col_us_products",
              "col_eu_products"
            ],
            "inherited_bucket_ids": [
              "bkt_marketing_videos"
            ],
            "source_filters": {
              "filters": {
                "AND": [
                  {
                    "field": "blobs.type",
                    "operator": "eq",
                    "value": "video"
                  }
                ]
              }
            }
          },
          "feature_extractor": {
            "feature_extractor_name": "<string>",
            "version": "<string>",
            "feature_extractor_id": "<string>",
            "params": {},
            "parameters": {
              "extractor_type": "audio_fingerprint_extractor",
              "normalize_embeddings": true,
              "sample_rate": 48000,
              "segment_duration_sec": 5,
              "segment_hop_sec": 2.5
            },
            "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>"
      ],
      "embedding_task": "<string>",
      "enabled": true,
      "metadata": {
        "environment": "production",
        "project": "Q4_campaign",
        "team": "data-science"
      },
      "schedule": {
        "trigger_type": "<string>",
        "schedule_config": {},
        "description": "<string>"
      },
      "trigger_id": "<string>",
      "created_at": "2023-11-07T05:31:56Z",
      "updated_at": "2023-11-07T05:31:56Z",
      "lifecycle_state": "active",
      "s3_vector_index": "<string>",
      "last_lifecycle_transition": "2023-11-07T05:31:56Z",
      "tiering_rules": [
        {
          "enabled": false,
          "threshold_days": 123
        }
      ],
      "document_count": 123,
      "schema_version": 1,
      "last_schema_sync": "2023-11-07T05:31:56Z",
      "schema_sync_enabled": true,
      "document_schema": null,
      "schema_validation": "off",
      "taxonomy_applications": null,
      "cluster_applications": null,
      "alert_applications": null,
      "retriever_enrichments": null,
      "vector_count": 123,
      "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
  }
}

{
  "status": 123,
  "error": {
    "message": "<string>",
    "type": "<string>",
    "code": "<string>",
    "details": {}
  },
  "success": false
}

{
  "status": 123,
  "error": {
    "message": "<string>",
    "type": "<string>",
    "code": "<string>",
    "details": {}
  },
  "success": false
}

{
  "status": 123,
  "error": {
    "message": "<string>",
    "type": "<string>",
    "code": "<string>",
    "details": {}
  },
  "success": false
}

{
  "status": 123,
  "error": {
    "message": "<string>",
    "type": "<string>",
    "code": "<string>",
    "details": {}
  },
  "success": false
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>",
      "input": "<unknown>",
      "ctx": {}
    }
  ]
}

{
  "status": 123,
  "error": {
    "message": "<string>",
    "type": "<string>",
    "code": "<string>",
    "details": {}
  },
  "success": false
}

POST

collections

list

List Collections

curl --request POST \
  --url https://api.mixpeek.com/v1/collections/list \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "limit": 500,
  "page_size": 500,
  "offset": 5000,
  "page": 2,
  "filters": {},
  "sort": {
    "field": "created_at",
    "direction": "desc"
  },
  "sorts": [
    {}
  ],
  "search": "<string>",
  "case_sensitive": false
}
'

import requests

url = "https://api.mixpeek.com/v1/collections/list"

payload = {
    "limit": 500,
    "page_size": 500,
    "offset": 5000,
    "page": 2,
    "filters": {},
    "sort": {
        "field": "created_at",
        "direction": "desc"
    },
    "sorts": [{}],
    "search": "<string>",
    "case_sensitive": False
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    limit: 500,
    page_size: 500,
    offset: 5000,
    page: 2,
    filters: {},
    sort: {field: 'created_at', direction: 'desc'},
    sorts: [{}],
    search: '<string>',
    case_sensitive: false
  })
};

fetch('https://api.mixpeek.com/v1/collections/list', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.mixpeek.com/v1/collections/list",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'limit' => 500,
    'page_size' => 500,
    'offset' => 5000,
    'page' => 2,
    'filters' => [
        
    ],
    'sort' => [
        'field' => 'created_at',
        'direction' => 'desc'
    ],
    'sorts' => [
        [
                
        ]
    ],
    'search' => '<string>',
    'case_sensitive' => false
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.mixpeek.com/v1/collections/list"

	payload := strings.NewReader("{\n  \"limit\": 500,\n  \"page_size\": 500,\n  \"offset\": 5000,\n  \"page\": 2,\n  \"filters\": {},\n  \"sort\": {\n    \"field\": \"created_at\",\n    \"direction\": \"desc\"\n  },\n  \"sorts\": [\n    {}\n  ],\n  \"search\": \"<string>\",\n  \"case_sensitive\": false\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.mixpeek.com/v1/collections/list")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"limit\": 500,\n  \"page_size\": 500,\n  \"offset\": 5000,\n  \"page\": 2,\n  \"filters\": {},\n  \"sort\": {\n    \"field\": \"created_at\",\n    \"direction\": \"desc\"\n  },\n  \"sorts\": [\n    {}\n  ],\n  \"search\": \"<string>\",\n  \"case_sensitive\": false\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.mixpeek.com/v1/collections/list")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"limit\": 500,\n  \"page_size\": 500,\n  \"offset\": 5000,\n  \"page\": 2,\n  \"filters\": {},\n  \"sort\": {\n    \"field\": \"created_at\",\n    \"direction\": \"desc\"\n  },\n  \"sorts\": [\n    {}\n  ],\n  \"search\": \"<string>\",\n  \"case_sensitive\": false\n}"

response = http.request(request)
puts response.read_body

{
  "results": [
    {
      "collection_name": "<string>",
      "feature_extractor": {
        "feature_extractor_name": "<string>",
        "version": "<string>",
        "feature_extractor_id": "<string>",
        "params": {},
        "parameters": {
          "extractor_type": "audio_fingerprint_extractor",
          "normalize_embeddings": true,
          "sample_rate": 48000,
          "segment_duration_sec": 5,
          "segment_hop_sec": 2.5
        },
        "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": {
        "bucket_ids": [
          "bkt_marketing_videos"
        ],
        "source_namespace_id": "<string>",
        "collection_id": "col_video_frames",
        "collection_ids": [
          "col_us_products",
          "col_eu_products"
        ],
        "inherited_bucket_ids": [
          "bkt_marketing_videos"
        ],
        "source_filters": {
          "filters": {
            "AND": [
              {
                "field": "blobs.type",
                "operator": "eq",
                "value": "video"
              }
            ]
          }
        }
      },
      "collection_id": "<string>",
      "description": "Video frames extracted at 1 FPS with CLIP embeddings",
      "input_schema": {
        "properties": {
          "title": {
            "type": "string"
          },
          "content": {
            "type": "text"
          }
        }
      },
      "output_schema": {
        "properties": {
          "title": {
            "type": "string"
          },
          "text_extractor_v1_embedding": {
            "type": "array"
          }
        }
      },
      "source_bucket_schemas": null,
      "source_lineage": [
        {
          "source_config": {
            "bucket_ids": [
              "bkt_marketing_videos"
            ],
            "source_namespace_id": "<string>",
            "collection_id": "col_video_frames",
            "collection_ids": [
              "col_us_products",
              "col_eu_products"
            ],
            "inherited_bucket_ids": [
              "bkt_marketing_videos"
            ],
            "source_filters": {
              "filters": {
                "AND": [
                  {
                    "field": "blobs.type",
                    "operator": "eq",
                    "value": "video"
                  }
                ]
              }
            }
          },
          "feature_extractor": {
            "feature_extractor_name": "<string>",
            "version": "<string>",
            "feature_extractor_id": "<string>",
            "params": {},
            "parameters": {
              "extractor_type": "audio_fingerprint_extractor",
              "normalize_embeddings": true,
              "sample_rate": 48000,
              "segment_duration_sec": 5,
              "segment_hop_sec": 2.5
            },
            "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>"
      ],
      "embedding_task": "<string>",
      "enabled": true,
      "metadata": {
        "environment": "production",
        "project": "Q4_campaign",
        "team": "data-science"
      },
      "schedule": {
        "trigger_type": "<string>",
        "schedule_config": {},
        "description": "<string>"
      },
      "trigger_id": "<string>",
      "created_at": "2023-11-07T05:31:56Z",
      "updated_at": "2023-11-07T05:31:56Z",
      "lifecycle_state": "active",
      "s3_vector_index": "<string>",
      "last_lifecycle_transition": "2023-11-07T05:31:56Z",
      "tiering_rules": [
        {
          "enabled": false,
          "threshold_days": 123
        }
      ],
      "document_count": 123,
      "schema_version": 1,
      "last_schema_sync": "2023-11-07T05:31:56Z",
      "schema_sync_enabled": true,
      "document_schema": null,
      "schema_validation": "off",
      "taxonomy_applications": null,
      "cluster_applications": null,
      "alert_applications": null,
      "retriever_enrichments": null,
      "vector_count": 123,
      "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
  }
}

{
  "status": 123,
  "error": {
    "message": "<string>",
    "type": "<string>",
    "code": "<string>",
    "details": {}
  },
  "success": false
}

{
  "status": 123,
  "error": {
    "message": "<string>",
    "type": "<string>",
    "code": "<string>",
    "details": {}
  },
  "success": false
}

{
  "status": 123,
  "error": {
    "message": "<string>",
    "type": "<string>",
    "code": "<string>",
    "details": {}
  },
  "success": false
}

{
  "status": 123,
  "error": {
    "message": "<string>",
    "type": "<string>",
    "code": "<string>",
    "details": {}
  },
  "success": false
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>",
      "input": "<unknown>",
      "ctx": {}
    }
  ]
}

{
  "status": 123,
  "error": {
    "message": "<string>",
    "type": "<string>",
    "code": "<string>",
    "details": {}
  },
  "success": false
}

Authorizations

Authorization

string

header

required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Query Parameters

limit

integer | null

Required range: 1 <= x <= 1000

page_size

integer | null

Required range: 1 <= x <= 1000

offset

integer | null

Required range: 0 <= x <= 10000

page

integer | null

Required range: x >= 1

cursor

string | null

include_total

boolean

default:false

Body

application/json

Request model for listing collections.

Inherits body-level limit/page_size/offset/page (BACKE-2846) — body values win over query pagination via merge_body_pagination.

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

limit

integer | null

Page size. A body value wins over the limit query param.

Required range: 1 <= x <= 1000

page_size

integer | null

Alias for limit (page size). If both are given, limit wins.

Required range: 1 <= x <= 1000

offset

integer | null

Number of results to skip (legacy, use cursor instead). A body value wins over the offset query param.

Required range: 0 <= x <= 10000

page

integer | null

1-indexed page number. Folds to offset = (page-1) * limit. If both page and offset are given, offset wins.

Required range: x >= 1

filters

Filters · object | null

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 | null

Sort options for the results (single-column, legacy)

Show child attributes

sorts

Sorts · object[] | null

Sort options as a list of {field, direction} — the shape Studio datatables and the retriever list send. The first entry is the primary sort. Takes precedence over the singular sort.

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

Show child attributes

pagination

PaginationResponse · object

required

Pagination information

Show child attributes

total_count

integer

required

Total number of collections matching the query

stats

CollectionListStats · object | null

Aggregate statistics across all collections in the result

Show child attributes

Describe collection features Export Collection

Organization

Namespaces

Buckets

Feature Extractors

Batch Queue

Collections

Documents

Retrievers

Taxonomies

Clusters

Triggers

Alerts

Webhooks

Apps

Agent Sessions

Annotations

Templates

Manifest

Discovery

Analytics

Notifications

Tasks

Inference

Resource Search

Pricing

List Collections

Authorizations

Query Parameters

Body

Response