Create Collection
curl --request POST \
--url https://api.mixpeek.com/v1/collections \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"collection_name": "<string>",
"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"
}
]
}
}
},
"feature_extractor": {
"feature_extractor_name": "<string>",
"version": "<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
},
"description": "<string>",
"input_schema": {
"properties": {}
},
"features": [
"<string>"
],
"enabled": true,
"metadata": {},
"schedule": {
"trigger_type": "<string>",
"schedule_config": {},
"description": "<string>"
},
"taxonomy_applications": [
{
"taxonomy_id": "<string>",
"execution_mode": "materialize",
"target_collection_id": "<string>",
"scroll_filters": {
"AND": [
{
"field": "name",
"operator": "eq",
"value": "John"
},
{
"field": "age",
"operator": "gte",
"value": 30
}
],
"OR": [
{
"field": "status",
"operator": "eq",
"value": "active"
},
{
"field": "role",
"operator": "eq",
"value": "admin"
}
],
"NOT": [
{
"field": "department",
"operator": "eq",
"value": "HR"
},
{
"field": "location",
"operator": "eq",
"value": "remote"
}
],
"case_sensitive": true
},
"execution_phase": 1,
"priority": 0,
"hierarchical_enrichment_style": "combined"
}
],
"cluster_applications": [
{
"cluster_id": "<string>",
"auto_execute_on_batch": true,
"min_document_threshold": 123,
"cooldown_seconds": 3600,
"execution_phase": 2,
"priority": 0
}
],
"alert_applications": [
{
"alert_id": "<string>",
"input_mappings": [
{
"input_key": "<string>",
"source": {
"path": "features.video_embedding",
"value": "col_known_incidents"
}
}
],
"execution_mode": "on_ingest",
"execution_phase": 3,
"priority": 0
}
],
"retriever_enrichments": [
{
"retriever_id": "<string>",
"input_mappings": [
{
"input_key": "<string>",
"source": {
"path": "features.video_embedding",
"value": "col_known_incidents"
}
}
],
"write_back_fields": [
{
"source_field": "<string>",
"target_field": "<string>",
"mode": "first"
}
],
"execution_phase": 4,
"priority": 0,
"scroll_filters": {
"AND": [
{
"field": "name",
"operator": "eq",
"value": "John"
},
{
"field": "age",
"operator": "gte",
"value": 30
}
],
"OR": [
{
"field": "status",
"operator": "eq",
"value": "active"
},
{
"field": "role",
"operator": "eq",
"value": "admin"
}
],
"NOT": [
{
"field": "department",
"operator": "eq",
"value": "HR"
},
{
"field": "location",
"operator": "eq",
"value": "remote"
}
],
"case_sensitive": true
},
"enabled": true
}
],
"embedding_task": "<string>"
}
'import requests
url = "https://api.mixpeek.com/v1/collections"
payload = {
"collection_name": "<string>",
"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"
}
] } }
},
"feature_extractor": {
"feature_extractor_name": "<string>",
"version": "<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
},
"description": "<string>",
"input_schema": { "properties": {} },
"features": ["<string>"],
"enabled": True,
"metadata": {},
"schedule": {
"trigger_type": "<string>",
"schedule_config": {},
"description": "<string>"
},
"taxonomy_applications": [
{
"taxonomy_id": "<string>",
"execution_mode": "materialize",
"target_collection_id": "<string>",
"scroll_filters": {
"AND": [
{
"field": "name",
"operator": "eq",
"value": "John"
},
{
"field": "age",
"operator": "gte",
"value": 30
}
],
"OR": [
{
"field": "status",
"operator": "eq",
"value": "active"
},
{
"field": "role",
"operator": "eq",
"value": "admin"
}
],
"NOT": [
{
"field": "department",
"operator": "eq",
"value": "HR"
},
{
"field": "location",
"operator": "eq",
"value": "remote"
}
],
"case_sensitive": True
},
"execution_phase": 1,
"priority": 0,
"hierarchical_enrichment_style": "combined"
}
],
"cluster_applications": [
{
"cluster_id": "<string>",
"auto_execute_on_batch": True,
"min_document_threshold": 123,
"cooldown_seconds": 3600,
"execution_phase": 2,
"priority": 0
}
],
"alert_applications": [
{
"alert_id": "<string>",
"input_mappings": [
{
"input_key": "<string>",
"source": {
"path": "features.video_embedding",
"value": "col_known_incidents"
}
}
],
"execution_mode": "on_ingest",
"execution_phase": 3,
"priority": 0
}
],
"retriever_enrichments": [
{
"retriever_id": "<string>",
"input_mappings": [
{
"input_key": "<string>",
"source": {
"path": "features.video_embedding",
"value": "col_known_incidents"
}
}
],
"write_back_fields": [
{
"source_field": "<string>",
"target_field": "<string>",
"mode": "first"
}
],
"execution_phase": 4,
"priority": 0,
"scroll_filters": {
"AND": [
{
"field": "name",
"operator": "eq",
"value": "John"
},
{
"field": "age",
"operator": "gte",
"value": 30
}
],
"OR": [
{
"field": "status",
"operator": "eq",
"value": "active"
},
{
"field": "role",
"operator": "eq",
"value": "admin"
}
],
"NOT": [
{
"field": "department",
"operator": "eq",
"value": "HR"
},
{
"field": "location",
"operator": "eq",
"value": "remote"
}
],
"case_sensitive": True
},
"enabled": True
}
],
"embedding_task": "<string>"
}
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({
collection_name: '<string>',
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'}]}}
},
feature_extractor: {
feature_extractor_name: '<string>',
version: '<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
},
description: '<string>',
input_schema: {properties: {}},
features: ['<string>'],
enabled: true,
metadata: {},
schedule: {trigger_type: '<string>', schedule_config: {}, description: '<string>'},
taxonomy_applications: [
{
taxonomy_id: '<string>',
execution_mode: 'materialize',
target_collection_id: '<string>',
scroll_filters: {
AND: [
{field: 'name', operator: 'eq', value: 'John'},
{field: 'age', operator: 'gte', value: 30}
],
OR: [
{field: 'status', operator: 'eq', value: 'active'},
{field: 'role', operator: 'eq', value: 'admin'}
],
NOT: [
{field: 'department', operator: 'eq', value: 'HR'},
{field: 'location', operator: 'eq', value: 'remote'}
],
case_sensitive: true
},
execution_phase: 1,
priority: 0,
hierarchical_enrichment_style: 'combined'
}
],
cluster_applications: [
{
cluster_id: '<string>',
auto_execute_on_batch: true,
min_document_threshold: 123,
cooldown_seconds: 3600,
execution_phase: 2,
priority: 0
}
],
alert_applications: [
{
alert_id: '<string>',
input_mappings: [
{
input_key: '<string>',
source: {path: 'features.video_embedding', value: 'col_known_incidents'}
}
],
execution_mode: 'on_ingest',
execution_phase: 3,
priority: 0
}
],
retriever_enrichments: [
{
retriever_id: '<string>',
input_mappings: [
{
input_key: '<string>',
source: {path: 'features.video_embedding', value: 'col_known_incidents'}
}
],
write_back_fields: [{source_field: '<string>', target_field: '<string>', mode: 'first'}],
execution_phase: 4,
priority: 0,
scroll_filters: {
AND: [
{field: 'name', operator: 'eq', value: 'John'},
{field: 'age', operator: 'gte', value: 30}
],
OR: [
{field: 'status', operator: 'eq', value: 'active'},
{field: 'role', operator: 'eq', value: 'admin'}
],
NOT: [
{field: 'department', operator: 'eq', value: 'HR'},
{field: 'location', operator: 'eq', value: 'remote'}
],
case_sensitive: true
},
enabled: true
}
],
embedding_task: '<string>'
})
};
fetch('https://api.mixpeek.com/v1/collections', 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",
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([
'collection_name' => '<string>',
'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'
]
]
]
]
],
'feature_extractor' => [
'feature_extractor_name' => '<string>',
'version' => '<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
],
'description' => '<string>',
'input_schema' => [
'properties' => [
]
],
'features' => [
'<string>'
],
'enabled' => true,
'metadata' => [
],
'schedule' => [
'trigger_type' => '<string>',
'schedule_config' => [
],
'description' => '<string>'
],
'taxonomy_applications' => [
[
'taxonomy_id' => '<string>',
'execution_mode' => 'materialize',
'target_collection_id' => '<string>',
'scroll_filters' => [
'AND' => [
[
'field' => 'name',
'operator' => 'eq',
'value' => 'John'
],
[
'field' => 'age',
'operator' => 'gte',
'value' => 30
]
],
'OR' => [
[
'field' => 'status',
'operator' => 'eq',
'value' => 'active'
],
[
'field' => 'role',
'operator' => 'eq',
'value' => 'admin'
]
],
'NOT' => [
[
'field' => 'department',
'operator' => 'eq',
'value' => 'HR'
],
[
'field' => 'location',
'operator' => 'eq',
'value' => 'remote'
]
],
'case_sensitive' => true
],
'execution_phase' => 1,
'priority' => 0,
'hierarchical_enrichment_style' => 'combined'
]
],
'cluster_applications' => [
[
'cluster_id' => '<string>',
'auto_execute_on_batch' => true,
'min_document_threshold' => 123,
'cooldown_seconds' => 3600,
'execution_phase' => 2,
'priority' => 0
]
],
'alert_applications' => [
[
'alert_id' => '<string>',
'input_mappings' => [
[
'input_key' => '<string>',
'source' => [
'path' => 'features.video_embedding',
'value' => 'col_known_incidents'
]
]
],
'execution_mode' => 'on_ingest',
'execution_phase' => 3,
'priority' => 0
]
],
'retriever_enrichments' => [
[
'retriever_id' => '<string>',
'input_mappings' => [
[
'input_key' => '<string>',
'source' => [
'path' => 'features.video_embedding',
'value' => 'col_known_incidents'
]
]
],
'write_back_fields' => [
[
'source_field' => '<string>',
'target_field' => '<string>',
'mode' => 'first'
]
],
'execution_phase' => 4,
'priority' => 0,
'scroll_filters' => [
'AND' => [
[
'field' => 'name',
'operator' => 'eq',
'value' => 'John'
],
[
'field' => 'age',
'operator' => 'gte',
'value' => 30
]
],
'OR' => [
[
'field' => 'status',
'operator' => 'eq',
'value' => 'active'
],
[
'field' => 'role',
'operator' => 'eq',
'value' => 'admin'
]
],
'NOT' => [
[
'field' => 'department',
'operator' => 'eq',
'value' => 'HR'
],
[
'field' => 'location',
'operator' => 'eq',
'value' => 'remote'
]
],
'case_sensitive' => true
],
'enabled' => true
]
],
'embedding_task' => '<string>'
]),
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"
payload := strings.NewReader("{\n \"collection_name\": \"<string>\",\n \"source\": {\n \"bucket_ids\": [\n \"bkt_marketing_videos\"\n ],\n \"source_namespace_id\": \"<string>\",\n \"collection_id\": \"col_video_frames\",\n \"collection_ids\": [\n \"col_us_products\",\n \"col_eu_products\"\n ],\n \"inherited_bucket_ids\": [\n \"bkt_marketing_videos\"\n ],\n \"source_filters\": {\n \"filters\": {\n \"AND\": [\n {\n \"field\": \"blobs.type\",\n \"operator\": \"eq\",\n \"value\": \"video\"\n }\n ]\n }\n }\n },\n \"feature_extractor\": {\n \"feature_extractor_name\": \"<string>\",\n \"version\": \"<string>\",\n \"params\": {},\n \"parameters\": {\n \"extractor_type\": \"audio_fingerprint_extractor\",\n \"normalize_embeddings\": true,\n \"sample_rate\": 48000,\n \"segment_duration_sec\": 5,\n \"segment_hop_sec\": 2.5\n },\n \"input_mappings\": {\n \"image\": \"product_image\",\n \"text\": \"title\"\n },\n \"field_passthrough\": [\n {\n \"source_path\": \"<string>\",\n \"target_path\": \"title\",\n \"default\": \"Unknown\",\n \"required\": false\n }\n ],\n \"include_all_source_fields\": false\n },\n \"description\": \"<string>\",\n \"input_schema\": {\n \"properties\": {}\n },\n \"features\": [\n \"<string>\"\n ],\n \"enabled\": true,\n \"metadata\": {},\n \"schedule\": {\n \"trigger_type\": \"<string>\",\n \"schedule_config\": {},\n \"description\": \"<string>\"\n },\n \"taxonomy_applications\": [\n {\n \"taxonomy_id\": \"<string>\",\n \"execution_mode\": \"materialize\",\n \"target_collection_id\": \"<string>\",\n \"scroll_filters\": {\n \"AND\": [\n {\n \"field\": \"name\",\n \"operator\": \"eq\",\n \"value\": \"John\"\n },\n {\n \"field\": \"age\",\n \"operator\": \"gte\",\n \"value\": 30\n }\n ],\n \"OR\": [\n {\n \"field\": \"status\",\n \"operator\": \"eq\",\n \"value\": \"active\"\n },\n {\n \"field\": \"role\",\n \"operator\": \"eq\",\n \"value\": \"admin\"\n }\n ],\n \"NOT\": [\n {\n \"field\": \"department\",\n \"operator\": \"eq\",\n \"value\": \"HR\"\n },\n {\n \"field\": \"location\",\n \"operator\": \"eq\",\n \"value\": \"remote\"\n }\n ],\n \"case_sensitive\": true\n },\n \"execution_phase\": 1,\n \"priority\": 0,\n \"hierarchical_enrichment_style\": \"combined\"\n }\n ],\n \"cluster_applications\": [\n {\n \"cluster_id\": \"<string>\",\n \"auto_execute_on_batch\": true,\n \"min_document_threshold\": 123,\n \"cooldown_seconds\": 3600,\n \"execution_phase\": 2,\n \"priority\": 0\n }\n ],\n \"alert_applications\": [\n {\n \"alert_id\": \"<string>\",\n \"input_mappings\": [\n {\n \"input_key\": \"<string>\",\n \"source\": {\n \"path\": \"features.video_embedding\",\n \"value\": \"col_known_incidents\"\n }\n }\n ],\n \"execution_mode\": \"on_ingest\",\n \"execution_phase\": 3,\n \"priority\": 0\n }\n ],\n \"retriever_enrichments\": [\n {\n \"retriever_id\": \"<string>\",\n \"input_mappings\": [\n {\n \"input_key\": \"<string>\",\n \"source\": {\n \"path\": \"features.video_embedding\",\n \"value\": \"col_known_incidents\"\n }\n }\n ],\n \"write_back_fields\": [\n {\n \"source_field\": \"<string>\",\n \"target_field\": \"<string>\",\n \"mode\": \"first\"\n }\n ],\n \"execution_phase\": 4,\n \"priority\": 0,\n \"scroll_filters\": {\n \"AND\": [\n {\n \"field\": \"name\",\n \"operator\": \"eq\",\n \"value\": \"John\"\n },\n {\n \"field\": \"age\",\n \"operator\": \"gte\",\n \"value\": 30\n }\n ],\n \"OR\": [\n {\n \"field\": \"status\",\n \"operator\": \"eq\",\n \"value\": \"active\"\n },\n {\n \"field\": \"role\",\n \"operator\": \"eq\",\n \"value\": \"admin\"\n }\n ],\n \"NOT\": [\n {\n \"field\": \"department\",\n \"operator\": \"eq\",\n \"value\": \"HR\"\n },\n {\n \"field\": \"location\",\n \"operator\": \"eq\",\n \"value\": \"remote\"\n }\n ],\n \"case_sensitive\": true\n },\n \"enabled\": true\n }\n ],\n \"embedding_task\": \"<string>\"\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")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"collection_name\": \"<string>\",\n \"source\": {\n \"bucket_ids\": [\n \"bkt_marketing_videos\"\n ],\n \"source_namespace_id\": \"<string>\",\n \"collection_id\": \"col_video_frames\",\n \"collection_ids\": [\n \"col_us_products\",\n \"col_eu_products\"\n ],\n \"inherited_bucket_ids\": [\n \"bkt_marketing_videos\"\n ],\n \"source_filters\": {\n \"filters\": {\n \"AND\": [\n {\n \"field\": \"blobs.type\",\n \"operator\": \"eq\",\n \"value\": \"video\"\n }\n ]\n }\n }\n },\n \"feature_extractor\": {\n \"feature_extractor_name\": \"<string>\",\n \"version\": \"<string>\",\n \"params\": {},\n \"parameters\": {\n \"extractor_type\": \"audio_fingerprint_extractor\",\n \"normalize_embeddings\": true,\n \"sample_rate\": 48000,\n \"segment_duration_sec\": 5,\n \"segment_hop_sec\": 2.5\n },\n \"input_mappings\": {\n \"image\": \"product_image\",\n \"text\": \"title\"\n },\n \"field_passthrough\": [\n {\n \"source_path\": \"<string>\",\n \"target_path\": \"title\",\n \"default\": \"Unknown\",\n \"required\": false\n }\n ],\n \"include_all_source_fields\": false\n },\n \"description\": \"<string>\",\n \"input_schema\": {\n \"properties\": {}\n },\n \"features\": [\n \"<string>\"\n ],\n \"enabled\": true,\n \"metadata\": {},\n \"schedule\": {\n \"trigger_type\": \"<string>\",\n \"schedule_config\": {},\n \"description\": \"<string>\"\n },\n \"taxonomy_applications\": [\n {\n \"taxonomy_id\": \"<string>\",\n \"execution_mode\": \"materialize\",\n \"target_collection_id\": \"<string>\",\n \"scroll_filters\": {\n \"AND\": [\n {\n \"field\": \"name\",\n \"operator\": \"eq\",\n \"value\": \"John\"\n },\n {\n \"field\": \"age\",\n \"operator\": \"gte\",\n \"value\": 30\n }\n ],\n \"OR\": [\n {\n \"field\": \"status\",\n \"operator\": \"eq\",\n \"value\": \"active\"\n },\n {\n \"field\": \"role\",\n \"operator\": \"eq\",\n \"value\": \"admin\"\n }\n ],\n \"NOT\": [\n {\n \"field\": \"department\",\n \"operator\": \"eq\",\n \"value\": \"HR\"\n },\n {\n \"field\": \"location\",\n \"operator\": \"eq\",\n \"value\": \"remote\"\n }\n ],\n \"case_sensitive\": true\n },\n \"execution_phase\": 1,\n \"priority\": 0,\n \"hierarchical_enrichment_style\": \"combined\"\n }\n ],\n \"cluster_applications\": [\n {\n \"cluster_id\": \"<string>\",\n \"auto_execute_on_batch\": true,\n \"min_document_threshold\": 123,\n \"cooldown_seconds\": 3600,\n \"execution_phase\": 2,\n \"priority\": 0\n }\n ],\n \"alert_applications\": [\n {\n \"alert_id\": \"<string>\",\n \"input_mappings\": [\n {\n \"input_key\": \"<string>\",\n \"source\": {\n \"path\": \"features.video_embedding\",\n \"value\": \"col_known_incidents\"\n }\n }\n ],\n \"execution_mode\": \"on_ingest\",\n \"execution_phase\": 3,\n \"priority\": 0\n }\n ],\n \"retriever_enrichments\": [\n {\n \"retriever_id\": \"<string>\",\n \"input_mappings\": [\n {\n \"input_key\": \"<string>\",\n \"source\": {\n \"path\": \"features.video_embedding\",\n \"value\": \"col_known_incidents\"\n }\n }\n ],\n \"write_back_fields\": [\n {\n \"source_field\": \"<string>\",\n \"target_field\": \"<string>\",\n \"mode\": \"first\"\n }\n ],\n \"execution_phase\": 4,\n \"priority\": 0,\n \"scroll_filters\": {\n \"AND\": [\n {\n \"field\": \"name\",\n \"operator\": \"eq\",\n \"value\": \"John\"\n },\n {\n \"field\": \"age\",\n \"operator\": \"gte\",\n \"value\": 30\n }\n ],\n \"OR\": [\n {\n \"field\": \"status\",\n \"operator\": \"eq\",\n \"value\": \"active\"\n },\n {\n \"field\": \"role\",\n \"operator\": \"eq\",\n \"value\": \"admin\"\n }\n ],\n \"NOT\": [\n {\n \"field\": \"department\",\n \"operator\": \"eq\",\n \"value\": \"HR\"\n },\n {\n \"field\": \"location\",\n \"operator\": \"eq\",\n \"value\": \"remote\"\n }\n ],\n \"case_sensitive\": true\n },\n \"enabled\": true\n }\n ],\n \"embedding_task\": \"<string>\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.mixpeek.com/v1/collections")
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 \"collection_name\": \"<string>\",\n \"source\": {\n \"bucket_ids\": [\n \"bkt_marketing_videos\"\n ],\n \"source_namespace_id\": \"<string>\",\n \"collection_id\": \"col_video_frames\",\n \"collection_ids\": [\n \"col_us_products\",\n \"col_eu_products\"\n ],\n \"inherited_bucket_ids\": [\n \"bkt_marketing_videos\"\n ],\n \"source_filters\": {\n \"filters\": {\n \"AND\": [\n {\n \"field\": \"blobs.type\",\n \"operator\": \"eq\",\n \"value\": \"video\"\n }\n ]\n }\n }\n },\n \"feature_extractor\": {\n \"feature_extractor_name\": \"<string>\",\n \"version\": \"<string>\",\n \"params\": {},\n \"parameters\": {\n \"extractor_type\": \"audio_fingerprint_extractor\",\n \"normalize_embeddings\": true,\n \"sample_rate\": 48000,\n \"segment_duration_sec\": 5,\n \"segment_hop_sec\": 2.5\n },\n \"input_mappings\": {\n \"image\": \"product_image\",\n \"text\": \"title\"\n },\n \"field_passthrough\": [\n {\n \"source_path\": \"<string>\",\n \"target_path\": \"title\",\n \"default\": \"Unknown\",\n \"required\": false\n }\n ],\n \"include_all_source_fields\": false\n },\n \"description\": \"<string>\",\n \"input_schema\": {\n \"properties\": {}\n },\n \"features\": [\n \"<string>\"\n ],\n \"enabled\": true,\n \"metadata\": {},\n \"schedule\": {\n \"trigger_type\": \"<string>\",\n \"schedule_config\": {},\n \"description\": \"<string>\"\n },\n \"taxonomy_applications\": [\n {\n \"taxonomy_id\": \"<string>\",\n \"execution_mode\": \"materialize\",\n \"target_collection_id\": \"<string>\",\n \"scroll_filters\": {\n \"AND\": [\n {\n \"field\": \"name\",\n \"operator\": \"eq\",\n \"value\": \"John\"\n },\n {\n \"field\": \"age\",\n \"operator\": \"gte\",\n \"value\": 30\n }\n ],\n \"OR\": [\n {\n \"field\": \"status\",\n \"operator\": \"eq\",\n \"value\": \"active\"\n },\n {\n \"field\": \"role\",\n \"operator\": \"eq\",\n \"value\": \"admin\"\n }\n ],\n \"NOT\": [\n {\n \"field\": \"department\",\n \"operator\": \"eq\",\n \"value\": \"HR\"\n },\n {\n \"field\": \"location\",\n \"operator\": \"eq\",\n \"value\": \"remote\"\n }\n ],\n \"case_sensitive\": true\n },\n \"execution_phase\": 1,\n \"priority\": 0,\n \"hierarchical_enrichment_style\": \"combined\"\n }\n ],\n \"cluster_applications\": [\n {\n \"cluster_id\": \"<string>\",\n \"auto_execute_on_batch\": true,\n \"min_document_threshold\": 123,\n \"cooldown_seconds\": 3600,\n \"execution_phase\": 2,\n \"priority\": 0\n }\n ],\n \"alert_applications\": [\n {\n \"alert_id\": \"<string>\",\n \"input_mappings\": [\n {\n \"input_key\": \"<string>\",\n \"source\": {\n \"path\": \"features.video_embedding\",\n \"value\": \"col_known_incidents\"\n }\n }\n ],\n \"execution_mode\": \"on_ingest\",\n \"execution_phase\": 3,\n \"priority\": 0\n }\n ],\n \"retriever_enrichments\": [\n {\n \"retriever_id\": \"<string>\",\n \"input_mappings\": [\n {\n \"input_key\": \"<string>\",\n \"source\": {\n \"path\": \"features.video_embedding\",\n \"value\": \"col_known_incidents\"\n }\n }\n ],\n \"write_back_fields\": [\n {\n \"source_field\": \"<string>\",\n \"target_field\": \"<string>\",\n \"mode\": \"first\"\n }\n ],\n \"execution_phase\": 4,\n \"priority\": 0,\n \"scroll_filters\": {\n \"AND\": [\n {\n \"field\": \"name\",\n \"operator\": \"eq\",\n \"value\": \"John\"\n },\n {\n \"field\": \"age\",\n \"operator\": \"gte\",\n \"value\": 30\n }\n ],\n \"OR\": [\n {\n \"field\": \"status\",\n \"operator\": \"eq\",\n \"value\": \"active\"\n },\n {\n \"field\": \"role\",\n \"operator\": \"eq\",\n \"value\": \"admin\"\n }\n ],\n \"NOT\": [\n {\n \"field\": \"department\",\n \"operator\": \"eq\",\n \"value\": \"HR\"\n },\n {\n \"field\": \"location\",\n \"operator\": \"eq\",\n \"value\": \"remote\"\n }\n ],\n \"case_sensitive\": true\n },\n \"enabled\": true\n }\n ],\n \"embedding_task\": \"<string>\"\n}"
response = http.request(request)
puts response.read_body{
"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
}{
"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
}Collections
Create Collection
Create a new processing collection linked to a namespace.
A collection defines the feature extraction pipeline that runs when objects are uploaded to a bucket. One feature extractor per collection.
Custom plugin collections:
When feature_extractor_name references a custom plugin, the collection’s vector
indexes are read from the plugin’s manifest.py features list. The features
entries must use these exact key names — wrong keys silently produce a collection
with no vector indexes and 0 documents will be written:
{
"feature_type": "embedding",
"feature_name": "my_embedding",
"embedding_dim": 768,
"distance_metric": "cosine"
}
Common wrong keys (will be ignored): type, name, dimensions, distance.
Vector schema: Custom plugin vectors are automatically added to the namespace’s Qdrant collection the first time a batch is processed, so there is no need to recreate the namespace when adding a plugin with new embedding types.
POST
/
v1
/
collections
Create Collection
curl --request POST \
--url https://api.mixpeek.com/v1/collections \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"collection_name": "<string>",
"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"
}
]
}
}
},
"feature_extractor": {
"feature_extractor_name": "<string>",
"version": "<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
},
"description": "<string>",
"input_schema": {
"properties": {}
},
"features": [
"<string>"
],
"enabled": true,
"metadata": {},
"schedule": {
"trigger_type": "<string>",
"schedule_config": {},
"description": "<string>"
},
"taxonomy_applications": [
{
"taxonomy_id": "<string>",
"execution_mode": "materialize",
"target_collection_id": "<string>",
"scroll_filters": {
"AND": [
{
"field": "name",
"operator": "eq",
"value": "John"
},
{
"field": "age",
"operator": "gte",
"value": 30
}
],
"OR": [
{
"field": "status",
"operator": "eq",
"value": "active"
},
{
"field": "role",
"operator": "eq",
"value": "admin"
}
],
"NOT": [
{
"field": "department",
"operator": "eq",
"value": "HR"
},
{
"field": "location",
"operator": "eq",
"value": "remote"
}
],
"case_sensitive": true
},
"execution_phase": 1,
"priority": 0,
"hierarchical_enrichment_style": "combined"
}
],
"cluster_applications": [
{
"cluster_id": "<string>",
"auto_execute_on_batch": true,
"min_document_threshold": 123,
"cooldown_seconds": 3600,
"execution_phase": 2,
"priority": 0
}
],
"alert_applications": [
{
"alert_id": "<string>",
"input_mappings": [
{
"input_key": "<string>",
"source": {
"path": "features.video_embedding",
"value": "col_known_incidents"
}
}
],
"execution_mode": "on_ingest",
"execution_phase": 3,
"priority": 0
}
],
"retriever_enrichments": [
{
"retriever_id": "<string>",
"input_mappings": [
{
"input_key": "<string>",
"source": {
"path": "features.video_embedding",
"value": "col_known_incidents"
}
}
],
"write_back_fields": [
{
"source_field": "<string>",
"target_field": "<string>",
"mode": "first"
}
],
"execution_phase": 4,
"priority": 0,
"scroll_filters": {
"AND": [
{
"field": "name",
"operator": "eq",
"value": "John"
},
{
"field": "age",
"operator": "gte",
"value": 30
}
],
"OR": [
{
"field": "status",
"operator": "eq",
"value": "active"
},
{
"field": "role",
"operator": "eq",
"value": "admin"
}
],
"NOT": [
{
"field": "department",
"operator": "eq",
"value": "HR"
},
{
"field": "location",
"operator": "eq",
"value": "remote"
}
],
"case_sensitive": true
},
"enabled": true
}
],
"embedding_task": "<string>"
}
'import requests
url = "https://api.mixpeek.com/v1/collections"
payload = {
"collection_name": "<string>",
"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"
}
] } }
},
"feature_extractor": {
"feature_extractor_name": "<string>",
"version": "<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
},
"description": "<string>",
"input_schema": { "properties": {} },
"features": ["<string>"],
"enabled": True,
"metadata": {},
"schedule": {
"trigger_type": "<string>",
"schedule_config": {},
"description": "<string>"
},
"taxonomy_applications": [
{
"taxonomy_id": "<string>",
"execution_mode": "materialize",
"target_collection_id": "<string>",
"scroll_filters": {
"AND": [
{
"field": "name",
"operator": "eq",
"value": "John"
},
{
"field": "age",
"operator": "gte",
"value": 30
}
],
"OR": [
{
"field": "status",
"operator": "eq",
"value": "active"
},
{
"field": "role",
"operator": "eq",
"value": "admin"
}
],
"NOT": [
{
"field": "department",
"operator": "eq",
"value": "HR"
},
{
"field": "location",
"operator": "eq",
"value": "remote"
}
],
"case_sensitive": True
},
"execution_phase": 1,
"priority": 0,
"hierarchical_enrichment_style": "combined"
}
],
"cluster_applications": [
{
"cluster_id": "<string>",
"auto_execute_on_batch": True,
"min_document_threshold": 123,
"cooldown_seconds": 3600,
"execution_phase": 2,
"priority": 0
}
],
"alert_applications": [
{
"alert_id": "<string>",
"input_mappings": [
{
"input_key": "<string>",
"source": {
"path": "features.video_embedding",
"value": "col_known_incidents"
}
}
],
"execution_mode": "on_ingest",
"execution_phase": 3,
"priority": 0
}
],
"retriever_enrichments": [
{
"retriever_id": "<string>",
"input_mappings": [
{
"input_key": "<string>",
"source": {
"path": "features.video_embedding",
"value": "col_known_incidents"
}
}
],
"write_back_fields": [
{
"source_field": "<string>",
"target_field": "<string>",
"mode": "first"
}
],
"execution_phase": 4,
"priority": 0,
"scroll_filters": {
"AND": [
{
"field": "name",
"operator": "eq",
"value": "John"
},
{
"field": "age",
"operator": "gte",
"value": 30
}
],
"OR": [
{
"field": "status",
"operator": "eq",
"value": "active"
},
{
"field": "role",
"operator": "eq",
"value": "admin"
}
],
"NOT": [
{
"field": "department",
"operator": "eq",
"value": "HR"
},
{
"field": "location",
"operator": "eq",
"value": "remote"
}
],
"case_sensitive": True
},
"enabled": True
}
],
"embedding_task": "<string>"
}
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({
collection_name: '<string>',
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'}]}}
},
feature_extractor: {
feature_extractor_name: '<string>',
version: '<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
},
description: '<string>',
input_schema: {properties: {}},
features: ['<string>'],
enabled: true,
metadata: {},
schedule: {trigger_type: '<string>', schedule_config: {}, description: '<string>'},
taxonomy_applications: [
{
taxonomy_id: '<string>',
execution_mode: 'materialize',
target_collection_id: '<string>',
scroll_filters: {
AND: [
{field: 'name', operator: 'eq', value: 'John'},
{field: 'age', operator: 'gte', value: 30}
],
OR: [
{field: 'status', operator: 'eq', value: 'active'},
{field: 'role', operator: 'eq', value: 'admin'}
],
NOT: [
{field: 'department', operator: 'eq', value: 'HR'},
{field: 'location', operator: 'eq', value: 'remote'}
],
case_sensitive: true
},
execution_phase: 1,
priority: 0,
hierarchical_enrichment_style: 'combined'
}
],
cluster_applications: [
{
cluster_id: '<string>',
auto_execute_on_batch: true,
min_document_threshold: 123,
cooldown_seconds: 3600,
execution_phase: 2,
priority: 0
}
],
alert_applications: [
{
alert_id: '<string>',
input_mappings: [
{
input_key: '<string>',
source: {path: 'features.video_embedding', value: 'col_known_incidents'}
}
],
execution_mode: 'on_ingest',
execution_phase: 3,
priority: 0
}
],
retriever_enrichments: [
{
retriever_id: '<string>',
input_mappings: [
{
input_key: '<string>',
source: {path: 'features.video_embedding', value: 'col_known_incidents'}
}
],
write_back_fields: [{source_field: '<string>', target_field: '<string>', mode: 'first'}],
execution_phase: 4,
priority: 0,
scroll_filters: {
AND: [
{field: 'name', operator: 'eq', value: 'John'},
{field: 'age', operator: 'gte', value: 30}
],
OR: [
{field: 'status', operator: 'eq', value: 'active'},
{field: 'role', operator: 'eq', value: 'admin'}
],
NOT: [
{field: 'department', operator: 'eq', value: 'HR'},
{field: 'location', operator: 'eq', value: 'remote'}
],
case_sensitive: true
},
enabled: true
}
],
embedding_task: '<string>'
})
};
fetch('https://api.mixpeek.com/v1/collections', 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",
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([
'collection_name' => '<string>',
'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'
]
]
]
]
],
'feature_extractor' => [
'feature_extractor_name' => '<string>',
'version' => '<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
],
'description' => '<string>',
'input_schema' => [
'properties' => [
]
],
'features' => [
'<string>'
],
'enabled' => true,
'metadata' => [
],
'schedule' => [
'trigger_type' => '<string>',
'schedule_config' => [
],
'description' => '<string>'
],
'taxonomy_applications' => [
[
'taxonomy_id' => '<string>',
'execution_mode' => 'materialize',
'target_collection_id' => '<string>',
'scroll_filters' => [
'AND' => [
[
'field' => 'name',
'operator' => 'eq',
'value' => 'John'
],
[
'field' => 'age',
'operator' => 'gte',
'value' => 30
]
],
'OR' => [
[
'field' => 'status',
'operator' => 'eq',
'value' => 'active'
],
[
'field' => 'role',
'operator' => 'eq',
'value' => 'admin'
]
],
'NOT' => [
[
'field' => 'department',
'operator' => 'eq',
'value' => 'HR'
],
[
'field' => 'location',
'operator' => 'eq',
'value' => 'remote'
]
],
'case_sensitive' => true
],
'execution_phase' => 1,
'priority' => 0,
'hierarchical_enrichment_style' => 'combined'
]
],
'cluster_applications' => [
[
'cluster_id' => '<string>',
'auto_execute_on_batch' => true,
'min_document_threshold' => 123,
'cooldown_seconds' => 3600,
'execution_phase' => 2,
'priority' => 0
]
],
'alert_applications' => [
[
'alert_id' => '<string>',
'input_mappings' => [
[
'input_key' => '<string>',
'source' => [
'path' => 'features.video_embedding',
'value' => 'col_known_incidents'
]
]
],
'execution_mode' => 'on_ingest',
'execution_phase' => 3,
'priority' => 0
]
],
'retriever_enrichments' => [
[
'retriever_id' => '<string>',
'input_mappings' => [
[
'input_key' => '<string>',
'source' => [
'path' => 'features.video_embedding',
'value' => 'col_known_incidents'
]
]
],
'write_back_fields' => [
[
'source_field' => '<string>',
'target_field' => '<string>',
'mode' => 'first'
]
],
'execution_phase' => 4,
'priority' => 0,
'scroll_filters' => [
'AND' => [
[
'field' => 'name',
'operator' => 'eq',
'value' => 'John'
],
[
'field' => 'age',
'operator' => 'gte',
'value' => 30
]
],
'OR' => [
[
'field' => 'status',
'operator' => 'eq',
'value' => 'active'
],
[
'field' => 'role',
'operator' => 'eq',
'value' => 'admin'
]
],
'NOT' => [
[
'field' => 'department',
'operator' => 'eq',
'value' => 'HR'
],
[
'field' => 'location',
'operator' => 'eq',
'value' => 'remote'
]
],
'case_sensitive' => true
],
'enabled' => true
]
],
'embedding_task' => '<string>'
]),
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"
payload := strings.NewReader("{\n \"collection_name\": \"<string>\",\n \"source\": {\n \"bucket_ids\": [\n \"bkt_marketing_videos\"\n ],\n \"source_namespace_id\": \"<string>\",\n \"collection_id\": \"col_video_frames\",\n \"collection_ids\": [\n \"col_us_products\",\n \"col_eu_products\"\n ],\n \"inherited_bucket_ids\": [\n \"bkt_marketing_videos\"\n ],\n \"source_filters\": {\n \"filters\": {\n \"AND\": [\n {\n \"field\": \"blobs.type\",\n \"operator\": \"eq\",\n \"value\": \"video\"\n }\n ]\n }\n }\n },\n \"feature_extractor\": {\n \"feature_extractor_name\": \"<string>\",\n \"version\": \"<string>\",\n \"params\": {},\n \"parameters\": {\n \"extractor_type\": \"audio_fingerprint_extractor\",\n \"normalize_embeddings\": true,\n \"sample_rate\": 48000,\n \"segment_duration_sec\": 5,\n \"segment_hop_sec\": 2.5\n },\n \"input_mappings\": {\n \"image\": \"product_image\",\n \"text\": \"title\"\n },\n \"field_passthrough\": [\n {\n \"source_path\": \"<string>\",\n \"target_path\": \"title\",\n \"default\": \"Unknown\",\n \"required\": false\n }\n ],\n \"include_all_source_fields\": false\n },\n \"description\": \"<string>\",\n \"input_schema\": {\n \"properties\": {}\n },\n \"features\": [\n \"<string>\"\n ],\n \"enabled\": true,\n \"metadata\": {},\n \"schedule\": {\n \"trigger_type\": \"<string>\",\n \"schedule_config\": {},\n \"description\": \"<string>\"\n },\n \"taxonomy_applications\": [\n {\n \"taxonomy_id\": \"<string>\",\n \"execution_mode\": \"materialize\",\n \"target_collection_id\": \"<string>\",\n \"scroll_filters\": {\n \"AND\": [\n {\n \"field\": \"name\",\n \"operator\": \"eq\",\n \"value\": \"John\"\n },\n {\n \"field\": \"age\",\n \"operator\": \"gte\",\n \"value\": 30\n }\n ],\n \"OR\": [\n {\n \"field\": \"status\",\n \"operator\": \"eq\",\n \"value\": \"active\"\n },\n {\n \"field\": \"role\",\n \"operator\": \"eq\",\n \"value\": \"admin\"\n }\n ],\n \"NOT\": [\n {\n \"field\": \"department\",\n \"operator\": \"eq\",\n \"value\": \"HR\"\n },\n {\n \"field\": \"location\",\n \"operator\": \"eq\",\n \"value\": \"remote\"\n }\n ],\n \"case_sensitive\": true\n },\n \"execution_phase\": 1,\n \"priority\": 0,\n \"hierarchical_enrichment_style\": \"combined\"\n }\n ],\n \"cluster_applications\": [\n {\n \"cluster_id\": \"<string>\",\n \"auto_execute_on_batch\": true,\n \"min_document_threshold\": 123,\n \"cooldown_seconds\": 3600,\n \"execution_phase\": 2,\n \"priority\": 0\n }\n ],\n \"alert_applications\": [\n {\n \"alert_id\": \"<string>\",\n \"input_mappings\": [\n {\n \"input_key\": \"<string>\",\n \"source\": {\n \"path\": \"features.video_embedding\",\n \"value\": \"col_known_incidents\"\n }\n }\n ],\n \"execution_mode\": \"on_ingest\",\n \"execution_phase\": 3,\n \"priority\": 0\n }\n ],\n \"retriever_enrichments\": [\n {\n \"retriever_id\": \"<string>\",\n \"input_mappings\": [\n {\n \"input_key\": \"<string>\",\n \"source\": {\n \"path\": \"features.video_embedding\",\n \"value\": \"col_known_incidents\"\n }\n }\n ],\n \"write_back_fields\": [\n {\n \"source_field\": \"<string>\",\n \"target_field\": \"<string>\",\n \"mode\": \"first\"\n }\n ],\n \"execution_phase\": 4,\n \"priority\": 0,\n \"scroll_filters\": {\n \"AND\": [\n {\n \"field\": \"name\",\n \"operator\": \"eq\",\n \"value\": \"John\"\n },\n {\n \"field\": \"age\",\n \"operator\": \"gte\",\n \"value\": 30\n }\n ],\n \"OR\": [\n {\n \"field\": \"status\",\n \"operator\": \"eq\",\n \"value\": \"active\"\n },\n {\n \"field\": \"role\",\n \"operator\": \"eq\",\n \"value\": \"admin\"\n }\n ],\n \"NOT\": [\n {\n \"field\": \"department\",\n \"operator\": \"eq\",\n \"value\": \"HR\"\n },\n {\n \"field\": \"location\",\n \"operator\": \"eq\",\n \"value\": \"remote\"\n }\n ],\n \"case_sensitive\": true\n },\n \"enabled\": true\n }\n ],\n \"embedding_task\": \"<string>\"\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")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"collection_name\": \"<string>\",\n \"source\": {\n \"bucket_ids\": [\n \"bkt_marketing_videos\"\n ],\n \"source_namespace_id\": \"<string>\",\n \"collection_id\": \"col_video_frames\",\n \"collection_ids\": [\n \"col_us_products\",\n \"col_eu_products\"\n ],\n \"inherited_bucket_ids\": [\n \"bkt_marketing_videos\"\n ],\n \"source_filters\": {\n \"filters\": {\n \"AND\": [\n {\n \"field\": \"blobs.type\",\n \"operator\": \"eq\",\n \"value\": \"video\"\n }\n ]\n }\n }\n },\n \"feature_extractor\": {\n \"feature_extractor_name\": \"<string>\",\n \"version\": \"<string>\",\n \"params\": {},\n \"parameters\": {\n \"extractor_type\": \"audio_fingerprint_extractor\",\n \"normalize_embeddings\": true,\n \"sample_rate\": 48000,\n \"segment_duration_sec\": 5,\n \"segment_hop_sec\": 2.5\n },\n \"input_mappings\": {\n \"image\": \"product_image\",\n \"text\": \"title\"\n },\n \"field_passthrough\": [\n {\n \"source_path\": \"<string>\",\n \"target_path\": \"title\",\n \"default\": \"Unknown\",\n \"required\": false\n }\n ],\n \"include_all_source_fields\": false\n },\n \"description\": \"<string>\",\n \"input_schema\": {\n \"properties\": {}\n },\n \"features\": [\n \"<string>\"\n ],\n \"enabled\": true,\n \"metadata\": {},\n \"schedule\": {\n \"trigger_type\": \"<string>\",\n \"schedule_config\": {},\n \"description\": \"<string>\"\n },\n \"taxonomy_applications\": [\n {\n \"taxonomy_id\": \"<string>\",\n \"execution_mode\": \"materialize\",\n \"target_collection_id\": \"<string>\",\n \"scroll_filters\": {\n \"AND\": [\n {\n \"field\": \"name\",\n \"operator\": \"eq\",\n \"value\": \"John\"\n },\n {\n \"field\": \"age\",\n \"operator\": \"gte\",\n \"value\": 30\n }\n ],\n \"OR\": [\n {\n \"field\": \"status\",\n \"operator\": \"eq\",\n \"value\": \"active\"\n },\n {\n \"field\": \"role\",\n \"operator\": \"eq\",\n \"value\": \"admin\"\n }\n ],\n \"NOT\": [\n {\n \"field\": \"department\",\n \"operator\": \"eq\",\n \"value\": \"HR\"\n },\n {\n \"field\": \"location\",\n \"operator\": \"eq\",\n \"value\": \"remote\"\n }\n ],\n \"case_sensitive\": true\n },\n \"execution_phase\": 1,\n \"priority\": 0,\n \"hierarchical_enrichment_style\": \"combined\"\n }\n ],\n \"cluster_applications\": [\n {\n \"cluster_id\": \"<string>\",\n \"auto_execute_on_batch\": true,\n \"min_document_threshold\": 123,\n \"cooldown_seconds\": 3600,\n \"execution_phase\": 2,\n \"priority\": 0\n }\n ],\n \"alert_applications\": [\n {\n \"alert_id\": \"<string>\",\n \"input_mappings\": [\n {\n \"input_key\": \"<string>\",\n \"source\": {\n \"path\": \"features.video_embedding\",\n \"value\": \"col_known_incidents\"\n }\n }\n ],\n \"execution_mode\": \"on_ingest\",\n \"execution_phase\": 3,\n \"priority\": 0\n }\n ],\n \"retriever_enrichments\": [\n {\n \"retriever_id\": \"<string>\",\n \"input_mappings\": [\n {\n \"input_key\": \"<string>\",\n \"source\": {\n \"path\": \"features.video_embedding\",\n \"value\": \"col_known_incidents\"\n }\n }\n ],\n \"write_back_fields\": [\n {\n \"source_field\": \"<string>\",\n \"target_field\": \"<string>\",\n \"mode\": \"first\"\n }\n ],\n \"execution_phase\": 4,\n \"priority\": 0,\n \"scroll_filters\": {\n \"AND\": [\n {\n \"field\": \"name\",\n \"operator\": \"eq\",\n \"value\": \"John\"\n },\n {\n \"field\": \"age\",\n \"operator\": \"gte\",\n \"value\": 30\n }\n ],\n \"OR\": [\n {\n \"field\": \"status\",\n \"operator\": \"eq\",\n \"value\": \"active\"\n },\n {\n \"field\": \"role\",\n \"operator\": \"eq\",\n \"value\": \"admin\"\n }\n ],\n \"NOT\": [\n {\n \"field\": \"department\",\n \"operator\": \"eq\",\n \"value\": \"HR\"\n },\n {\n \"field\": \"location\",\n \"operator\": \"eq\",\n \"value\": \"remote\"\n }\n ],\n \"case_sensitive\": true\n },\n \"enabled\": true\n }\n ],\n \"embedding_task\": \"<string>\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.mixpeek.com/v1/collections")
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 \"collection_name\": \"<string>\",\n \"source\": {\n \"bucket_ids\": [\n \"bkt_marketing_videos\"\n ],\n \"source_namespace_id\": \"<string>\",\n \"collection_id\": \"col_video_frames\",\n \"collection_ids\": [\n \"col_us_products\",\n \"col_eu_products\"\n ],\n \"inherited_bucket_ids\": [\n \"bkt_marketing_videos\"\n ],\n \"source_filters\": {\n \"filters\": {\n \"AND\": [\n {\n \"field\": \"blobs.type\",\n \"operator\": \"eq\",\n \"value\": \"video\"\n }\n ]\n }\n }\n },\n \"feature_extractor\": {\n \"feature_extractor_name\": \"<string>\",\n \"version\": \"<string>\",\n \"params\": {},\n \"parameters\": {\n \"extractor_type\": \"audio_fingerprint_extractor\",\n \"normalize_embeddings\": true,\n \"sample_rate\": 48000,\n \"segment_duration_sec\": 5,\n \"segment_hop_sec\": 2.5\n },\n \"input_mappings\": {\n \"image\": \"product_image\",\n \"text\": \"title\"\n },\n \"field_passthrough\": [\n {\n \"source_path\": \"<string>\",\n \"target_path\": \"title\",\n \"default\": \"Unknown\",\n \"required\": false\n }\n ],\n \"include_all_source_fields\": false\n },\n \"description\": \"<string>\",\n \"input_schema\": {\n \"properties\": {}\n },\n \"features\": [\n \"<string>\"\n ],\n \"enabled\": true,\n \"metadata\": {},\n \"schedule\": {\n \"trigger_type\": \"<string>\",\n \"schedule_config\": {},\n \"description\": \"<string>\"\n },\n \"taxonomy_applications\": [\n {\n \"taxonomy_id\": \"<string>\",\n \"execution_mode\": \"materialize\",\n \"target_collection_id\": \"<string>\",\n \"scroll_filters\": {\n \"AND\": [\n {\n \"field\": \"name\",\n \"operator\": \"eq\",\n \"value\": \"John\"\n },\n {\n \"field\": \"age\",\n \"operator\": \"gte\",\n \"value\": 30\n }\n ],\n \"OR\": [\n {\n \"field\": \"status\",\n \"operator\": \"eq\",\n \"value\": \"active\"\n },\n {\n \"field\": \"role\",\n \"operator\": \"eq\",\n \"value\": \"admin\"\n }\n ],\n \"NOT\": [\n {\n \"field\": \"department\",\n \"operator\": \"eq\",\n \"value\": \"HR\"\n },\n {\n \"field\": \"location\",\n \"operator\": \"eq\",\n \"value\": \"remote\"\n }\n ],\n \"case_sensitive\": true\n },\n \"execution_phase\": 1,\n \"priority\": 0,\n \"hierarchical_enrichment_style\": \"combined\"\n }\n ],\n \"cluster_applications\": [\n {\n \"cluster_id\": \"<string>\",\n \"auto_execute_on_batch\": true,\n \"min_document_threshold\": 123,\n \"cooldown_seconds\": 3600,\n \"execution_phase\": 2,\n \"priority\": 0\n }\n ],\n \"alert_applications\": [\n {\n \"alert_id\": \"<string>\",\n \"input_mappings\": [\n {\n \"input_key\": \"<string>\",\n \"source\": {\n \"path\": \"features.video_embedding\",\n \"value\": \"col_known_incidents\"\n }\n }\n ],\n \"execution_mode\": \"on_ingest\",\n \"execution_phase\": 3,\n \"priority\": 0\n }\n ],\n \"retriever_enrichments\": [\n {\n \"retriever_id\": \"<string>\",\n \"input_mappings\": [\n {\n \"input_key\": \"<string>\",\n \"source\": {\n \"path\": \"features.video_embedding\",\n \"value\": \"col_known_incidents\"\n }\n }\n ],\n \"write_back_fields\": [\n {\n \"source_field\": \"<string>\",\n \"target_field\": \"<string>\",\n \"mode\": \"first\"\n }\n ],\n \"execution_phase\": 4,\n \"priority\": 0,\n \"scroll_filters\": {\n \"AND\": [\n {\n \"field\": \"name\",\n \"operator\": \"eq\",\n \"value\": \"John\"\n },\n {\n \"field\": \"age\",\n \"operator\": \"gte\",\n \"value\": 30\n }\n ],\n \"OR\": [\n {\n \"field\": \"status\",\n \"operator\": \"eq\",\n \"value\": \"active\"\n },\n {\n \"field\": \"role\",\n \"operator\": \"eq\",\n \"value\": \"admin\"\n }\n ],\n \"NOT\": [\n {\n \"field\": \"department\",\n \"operator\": \"eq\",\n \"value\": \"HR\"\n },\n {\n \"field\": \"location\",\n \"operator\": \"eq\",\n \"value\": \"remote\"\n }\n ],\n \"case_sensitive\": true\n },\n \"enabled\": true\n }\n ],\n \"embedding_task\": \"<string>\"\n}"
response = http.request(request)
puts response.read_body{
"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
}{
"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
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Body
application/json
Request model for creating a new collection.
Collections process data from buckets or other collections using a single feature extractor.
KEY ARCHITECTURAL CHANGE: Each collection has EXACTLY ONE feature extractor.
- Use field_passthrough to include additional source fields in output documents
- Multiple extractors = multiple collections
- This simplifies processing and makes output schema deterministic
CRITICAL: To use input_mappings:
- Your source bucket MUST have a bucket_schema defined
- The input_mappings reference fields from that bucket_schema
- The system validates that mapped fields exist in the source schema
Example workflow:
- Create bucket with schema: { "properties": { "image": {"type": "image"}, "title": {"type": "string"} } }
- Upload objects conforming to that schema
- Create collection with:
- input_mappings: { "image": "image" }
- field_passthrough: [{"source_path": "title"}]
- Output documents will have both extractor outputs AND passthrough fields
Schema Computation:
- output_schema is computed IMMEDIATELY when collection is created
- output_schema = field_passthrough fields + extractor output fields
- No waiting for documents to be processed!
Name of the collection to create
Examples:
"video_frames"
"product_embeddings"
Source configuration (bucket or collection) for this collection
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Examples:
{
"bucket_ids": ["bkt_marketing_videos"],
"description": "Single bucket source",
"type": "bucket"
}
{
"bucket_ids": ["bkt_marketing_ads"],
"description": "Bucket source with video-only filter",
"source_filters": {
"filters": {
"AND": [
{
"field": "blobs.type",
"operator": "eq",
"value": "video"
}
]
}
},
"type": "bucket"
}
{
"bucket_ids": [
"bkt_us_products",
"bkt_eu_products",
"bkt_asia_products"
],
"description": "Multi-bucket source (region consolidation)",
"type": "bucket"
}
{
"bucket_ids": ["bkt_us_ads", "bkt_eu_ads", "bkt_asia_ads"],
"description": "Multi-bucket source with brand filter",
"source_filters": {
"filters": {
"OR": [
{
"field": "brand_name",
"operator": "in",
"value": ["Acme", "TechCo"]
},
{
"field": "category",
"operator": "eq",
"value": "premium"
}
]
}
},
"type": "bucket"
}
{
"collection_id": "col_video_frames",
"description": "Collection source (decomposition tree)",
"type": "collection"
}
{
"collection_id": "col_raw_frames",
"description": "Collection source with active documents only",
"source_filters": {
"filters": {
"AND": [
{
"field": "__fully_enriched",
"operator": "eq",
"value": true
},
{
"field": "quality_score",
"operator": "gte",
"value": 0.8
}
]
}
},
"type": "collection"
}
{
"collection_ids": [
"col_us_products",
"col_eu_products",
"col_asia_products"
],
"description": "Multi-collection source (cluster output)",
"type": "collection"
}
Single feature extractor for this collection. Use field_passthrough within the extractor config to include additional source fields. For multiple extractors, create multiple collections and use collection-to-collection pipelines. DEPRECATED for direct use: prefer features: [...] (contract v2 §6.2, D9) — extractor names are internal implementation.
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Examples:
{
"description": "Text extractor with field passthrough",
"feature_extractor_name": "text_extractor",
"field_passthrough": [
{ "required": true, "source_path": "title" },
{ "source_path": "author" }
],
"input_mappings": { "text": "content" },
"parameters": { "model": "text-embedding-3-small" },
"version": "v1"
}
{
"description": "Video extractor with campaign metadata",
"feature_extractor_name": "multimodal_extractor",
"field_passthrough": [
{ "source_path": "campaign_id" },
{ "source_path": "duration_seconds" }
],
"input_mappings": { "video": "video_url" },
"parameters": { "fps": 1 },
"version": "v1"
}
{
"description": "Image extractor with all source fields",
"feature_extractor_name": "image_extractor",
"include_all_source_fields": true,
"input_mappings": { "image": "product_image" },
"parameters": { "model": "clip-vit-base-patch32" },
"version": "v1"
}
{
"description": "Text extractor with field renaming",
"feature_extractor_name": "text_extractor",
"field_passthrough": [
{
"source_path": "metadata.author",
"target_path": "author"
},
{
"source_path": "metadata.created_at",
"target_path": "created_at"
}
],
"input_mappings": { "text": "content" },
"version": "v1"
}
Description of the collection
Input schema for the collection. If not provided, inferred from source bucket's bucket_schema or source collection's output_schema. REQUIRED for input_mappings to work - defines what fields can be mapped to feature extractors.
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What you want to search by: feature keys from GET /v1/collections/features (e.g. ['faces'] or ['custom:']). Resolved to the processing pipeline server-side — the preferred alternative to feature_extractor. Provide one or the other.
Whether the collection is enabled
Additional metadata for the collection
Optional schedule for automatic re-processing. Creates a COLLECTION_TRIGGER trigger behind the scenes. Supports cron and interval schedules.
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Optional taxonomy applications to automatically enrich documents in this collection. Each taxonomy will classify/enrich documents based on configured retriever matches.
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Optional cluster applications to automatically execute when batch processing completes. Each cluster enriches documents with cluster assignments (cluster_id, cluster_label, etc.).
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Optional alert applications to automatically execute when documents are ingested. Each alert runs a retriever against new documents and sends notifications if matches are found. Supports both ON_INGEST (triggered per batch) and SCHEDULED (periodic) execution modes.
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Optional retriever enrichments to run on documents during post-processing. Each enrichment executes a retriever pipeline and writes selected result fields back to the document. Use for: LLM classification, cross-collection joins, multi-stage enrichment at ingestion time.
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Override the embedding task hint for instruction-aware models (E5, Gemini). Defaults to 'retrieval_document' for indexing pipelines. Values: retrieval_document, retrieval_query, semantic_similarity, classification, clustering. Only change this if your primary use case is not retrieval (e.g., clustering or classification). Applied to all task-aware embedding models in this collection's extractor pipeline.
Response
Successful Response
Response model for collection endpoints.
REQUIRED. Human-readable name for the collection. Must be unique within the namespace. Used for: Display, lookups (can query by name or ID), organization. Format: Alphanumeric with underscores/hyphens, 3-100 characters. Examples: 'product_embeddings', 'video_frames', 'customer_documents'.
Required string length:
3 - 100Examples:
"video_frames"
"product_embeddings"
"customer_documents"
REQUIRED. Single feature extractor configuration for this collection. Defines: extractor name/version, input_mappings, field_passthrough, parameters. Task 9 change: ONE extractor per collection (previously supported multiple). For multiple extractors: Create multiple collections and use collection-to-collection pipelines. Use field_passthrough to include additional source fields beyond extractor outputs.
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Example:
{
"feature_extractor_name": "text_extractor",
"field_passthrough": [{ "source_path": "title" }],
"input_mappings": { "text": "content" },
"version": "v1"
}
REQUIRED. Source configuration defining where data comes from. Type 'bucket': Process objects from one or more buckets (tier 1). Type 'collection': Process documents from upstream collection(s) (tier 2+). For multi-bucket sources, all buckets must have compatible schemas. For multi-collection sources, all collections must have compatible schemas. Determines input_schema and enables decomposition trees.
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Examples:
{
"bucket_ids": ["bkt_articles"],
"type": "bucket"
}
{
"bucket_ids": ["bkt_us_products", "bkt_eu_products"],
"type": "bucket"
}
{
"collection_id": "col_video_frames",
"type": "collection"
}
{
"collection_ids": ["col_products_2023", "col_products_2024"],
"type": "collection"
}
NOT REQUIRED (auto-generated). Unique identifier for this collection. Used for: API paths, document queries, pipeline references. Format: 'col_' prefix + 10 random alphanumeric characters. Stable after creation - use for all collection references.
Examples:
"col_a1b2c3d4e5"
"col_xyz789abc"
"col_video_frames"
NOT REQUIRED. Human-readable description of the collection's purpose. Use for: Documentation, team communication, UI display. Common pattern: Describe what the collection contains and what processing is applied.
Example:
"Video frames extracted at 1 FPS with CLIP embeddings"
Auto-computed from source. Input schema defining fields available to the feature extractor. Source: bucket.bucket_schema (if source.type='bucket') OR upstream_collection.output_schema (if source.type='collection'). Determines: Which fields can be used in input_mappings and field_passthrough. This is the 'left side' of the transformation - what data goes IN. Format: BucketSchema with properties dict. Use for: Validating input_mappings, configuring field_passthrough.
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Example:
{
"properties": {
"title": { "type": "string" },
"content": { "type": "text" }
}
}
Auto-computed at creation. Output schema defining fields in final documents. Computed as: field_passthrough fields + extractor output fields (deterministic). Known IMMEDIATELY when collection is created - no waiting for documents! This is the 'right side' of the transformation - what data comes OUT. Use for: Understanding document structure, building queries, schema validation. Example: {title (passthrough), embedding (extractor output)} = output_schema.
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Example:
{
"properties": {
"title": { "type": "string" },
"text_extractor_v1_embedding": { "type": "array" }
}
}
NOT REQUIRED (auto-computed). Snapshot of bucket schemas at collection creation. Only populated for multi-bucket collections (source.type='bucket' with multiple bucket_ids). Key: bucket_id, Value: BucketSchema at time of collection creation. Used for: Schema compatibility validation, document lineage, debugging. Schema snapshot is immutable - bucket schema changes after collection creation do not affect this. Single-bucket collections may omit this field (schema in input_schema is sufficient).
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Example:
null
NOT REQUIRED (auto-computed). Lineage chain showing complete processing history. Each entry contains: source_config, feature_extractor, output_schema for one tier. Length indicates processing depth (1 = tier 1, 2 = tier 2, etc.). Use for: Understanding multi-tier pipelines, visualizing decomposition trees.
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Examples:
[]
[
{
"output_schema": {},
"source_config": {
"bucket_id": "bkt_videos",
"type": "bucket"
}
}
]
NOT REQUIRED (auto-computed from extractor). Vector indexes for semantic search. Populated from feature_extractor.required_vector_indexes. Defines: Which embeddings are indexed, dimensions, distance metrics. Use for: Understanding search capabilities, debugging vector queries.
Examples:
[]
[
{
"distance": "cosine",
"name": "text_extractor_v1_embedding",
"size": 1024
}
]
NOT REQUIRED (auto-computed from extractor + namespace). Payload indexes for filtering. Enables efficient filtering on metadata fields, timestamps, IDs. Populated from: extractor requirements + namespace defaults. Use for: Understanding which fields support fast filtering.
Examples:
[]
[
{
"field_name": "collection_id",
"type": "keyword"
}
]
Override the embedding task hint for instruction-aware models (E5, Gemini). Defaults to 'retrieval_document' for indexing pipelines. Values: retrieval_document, retrieval_query, semantic_similarity, classification, clustering. Applied to all task-aware embedding models in this collection's extractor pipeline.
NOT REQUIRED (defaults to True). Whether the collection accepts new documents. False: Collection exists but won't process new objects. True: Active and processing. Use for: Temporarily disabling collections without deletion.
Examples:
true
false
NOT REQUIRED. Additional user-defined metadata for the collection. Arbitrary key-value pairs for custom organization, tracking, configuration. Not used by the platform - purely for user purposes. Common uses: team ownership, project tags, deployment environment.
Example:
{
"environment": "production",
"project": "Q4_campaign",
"team": "data-science"
}
NOT REQUIRED. Schedule configuration for automatic re-processing. When set, a COLLECTION_TRIGGER trigger is created and linked to this collection.
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NOT REQUIRED. ID of the linked trigger for scheduled re-processing. Automatically set when a schedule is configured.
Timestamp when the collection was created. Automatically set by the system when the collection is first saved to the database.
Timestamp when the collection was last updated. Automatically updated by the system whenever the collection is modified.
Storage lifecycle state: 'active' (Qdrant + S3), 'cold' (S3 only), 'archived' (metadata only). Managed via lifecycle API.
S3 Vectors index name for this collection (e.g. 'col_{collection_id}').
Timestamp of the most recent lifecycle state change.
Automatic storage tiering rules (not enforced in V1).
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Number of documents in the collection
Version number for the output_schema. Increments automatically when schema is updated via document sampling. Used to track schema evolution and trigger downstream collection schema updates.
Timestamp of last automatic schema sync from document sampling. Used to debounce schema updates (prevents thrashing).
Whether automatic schema discovery and sync is enabled for this collection. When True, schema is periodically updated by sampling documents. When False, schema remains fixed at creation time.
NOT REQUIRED. JSON Schema for validating documents on create/update. When set with schema_validation='strict', non-conforming documents are rejected (422). When set with schema_validation='warn', violations are recorded but document is accepted. Schema follows JSON Schema draft-07 format. Only validates user-defined fields (system fields like _internal, collection_id, document_id are excluded from validation).
Example:
null
Document schema validation mode. 'strict': reject non-conforming documents with 422. 'warn': accept but attach _schema_violations field to the document. 'off': no validation (default, preserves current behavior).
Available options:
strict, warn, off Examples:
"off"
"strict"
"warn"
NOT REQUIRED. List of taxonomies to apply to documents in this collection. Each entry specifies: taxonomy_id, optional target_collection_id, optional filters. Enrichments are materialized (persisted to documents) during ingestion. Empty/null if no taxonomies attached. Use for: Categorization, hierarchical classification.
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Example:
null
NOT REQUIRED. List of clusters to automatically execute when batch processing completes. Each entry specifies: cluster_id, auto_execute_on_batch, min_document_threshold, cooldown_seconds. Clusters enrich source documents with cluster assignments (cluster_id, cluster_label, etc.). Empty/null if no clusters attached. Use for: Segmentation, grouping, pattern discovery.
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Example:
null
NOT REQUIRED. List of alerts to automatically execute when documents are ingested. Each entry specifies: alert_id, execution_mode, input_mappings, execution_phase, priority. Alerts run retrievers on ingested documents and send notifications when matches are found. Empty/null if no alerts attached. Use for: Content monitoring, safety detection, compliance alerts.
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Example:
null
NOT REQUIRED. List of retriever enrichments to run on documents during post-processing. Each entry specifies: retriever_id, input_mappings, write_back_fields, execution_phase, priority. Retriever enrichments execute a retriever pipeline and write selected result fields back to documents. Empty/null if no enrichments attached. Use for: LLM classification, cross-collection joins, enrichment.
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Example:
null
Total number of vector entries across all documents in this collection. Computed as document_count * number_of_vector_indexes. Each document stores one vector per configured vector index (e.g. a collection with 1 embedding produces 1 vector per document).
Number of taxonomies connected to this collection
Number of retrievers connected to this collection
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