Every API here is available over the APIs.io API and to AI agents over MCP.
openapi: 3.0.1
info:
title: Qdrant Aliases Beta API
description: "API description for Qdrant vector search engine.\n\nThis document describes CRUD and search operations on collections of points (vectors with payload).\n\nQdrant supports any combinations of `should`, `min_should`, `must` and `must_not` conditions, which makes it possible to use in applications when object could not be described solely by vector. It could be location features, availability flags, and other custom properties businesses should take into account.\n## Examples\nThis examples cover the most basic use-cases - collection creation and basic vector search.\n### Create collection\nFirst - let's create a collection with dot-production metric.\n```\ncurl -X PUT 'http://localhost:6333/collections/test_collection' \\\n -H 'Content-Type: application/json' \\\n --data-raw '{\n \"vectors\": {\n \"size\": 4,\n \"distance\": \"Dot\"\n }\n }'\n\n```\nExpected response:\n```\n{\n \"result\": true,\n \"status\": \"ok\",\n \"time\": 0.031095451\n}\n```\nWe can ensure that collection was created:\n```\ncurl 'http://localhost:6333/collections/test_collection'\n```\nExpected response:\n```\n{\n \"result\": {\n \"status\": \"green\",\n \"segments_count\": 5,\n \"disk_data_size\": 0,\n \"ram_data_size\": 0,\n \"config\": {\n \"params\": {\n \"vectors\": {\n \"size\": 4,\n \"distance\": \"Dot\"\n }\n },\n \"hnsw_config\": {\n \"m\": 16,\n \"ef_construct\": 100,\n \"full_scan_threshold\": 10000\n },\n \"optimizer_config\": {\n \"deleted_threshold\": 0.2,\n \"vacuum_min_vector_number\": 1000,\n \"default_segment_number\": 2,\n \"max_segment_size\": null,\n \"memmap_threshold\": null,\n \"indexing_threshold\": 20000,\n \"flush_interval_sec\": 5,\n \"max_optimization_threads\": null\n },\n \"wal_config\": {\n \"wal_capacity_mb\": 32,\n \"wal_segments_ahead\": 0\n }\n }\n },\n \"status\": \"ok\",\n \"time\": 2.1199e-05\n}\n```\n\n### Add points\nLet's now add vectors with some payload:\n```\ncurl -L -X PUT 'http://localhost:6333/collections/test_collection/points?wait=true' \\ -H 'Content-Type: application/json' \\ --data-raw '{\n \"points\": [\n {\"id\": 1, \"vector\": [0.05, 0.61, 0.76, 0.74], \"payload\": {\"city\": \"Berlin\"}},\n {\"id\": 2, \"vector\": [0.19, 0.81, 0.75, 0.11], \"payload\": {\"city\": [\"Berlin\", \"London\"] }},\n {\"id\": 3, \"vector\": [0.36, 0.55, 0.47, 0.94], \"payload\": {\"city\": [\"Berlin\", \"Moscow\"] }},\n {\"id\": 4, \"vector\": [0.18, 0.01, 0.85, 0.80], \"payload\": {\"city\": [\"London\", \"Moscow\"] }},\n {\"id\": 5, \"vector\": [0.24, 0.18, 0.22, 0.44], \"payload\": {\"count\": [0]}},\n {\"id\": 6, \"vector\": [0.35, 0.08, 0.11, 0.44]}\n ]\n}'\n```\nExpected response:\n```\n{\n \"result\": {\n \"operation_id\": 0,\n \"status\": \"completed\"\n },\n \"status\": \"ok\",\n \"time\": 0.000206061\n}\n```\n### Search with filtering\nLet's start with a basic request:\n```\ncurl -L -X POST 'http://localhost:6333/collections/test_collection/points/search' \\ -H 'Content-Type: application/json' \\ --data-raw '{\n \"vector\": [0.2,0.1,0.9,0.7],\n \"top\": 3\n}'\n```\nExpected response:\n```\n{\n \"result\": [\n { \"id\": 4, \"score\": 1.362, \"payload\": null, \"version\": 0 },\n { \"id\": 1, \"score\": 1.273, \"payload\": null, \"version\": 0 },\n { \"id\": 3, \"score\": 1.208, \"payload\": null, \"version\": 0 }\n ],\n \"status\": \"ok\",\n \"time\": 0.000055785\n}\n```\nBut result is different if we add a filter:\n```\ncurl -L -X POST 'http://localhost:6333/collections/test_collection/points/search' \\ -H 'Content-Type: application/json' \\ --data-raw '{\n \"filter\": {\n \"should\": [\n {\n \"key\": \"city\",\n \"match\": {\n \"value\": \"London\"\n }\n }\n ]\n },\n \"vector\": [0.2, 0.1, 0.9, 0.7],\n \"top\": 3\n}'\n```\nExpected response:\n```\n{\n \"result\": [\n { \"id\": 4, \"score\": 1.362, \"payload\": null, \"version\": 0 },\n { \"id\": 2, \"score\": 0.871, \"payload\": null, \"version\": 0 }\n ],\n \"status\": \"ok\",\n \"time\": 0.000093972\n}\n```\n"
contact:
email: andrey@vasnetsov.com
license:
name: Apache 2.0
url: http://www.apache.org/licenses/LICENSE-2.0.html
version: master
servers:
- url: '{protocol}://{hostname}:{port}'
variables:
protocol:
enum:
- http
- https
default: http
hostname:
default: localhost
port:
default: '6333'
security:
- api-key: []
- bearerAuth: []
- {}
tags:
- name: Beta
description: Beta features, do not depend on these yet.
paths:
/issues:
get:
summary: Get issues
description: Get a report of performance issues and configuration suggestions
operationId: get_issues
tags:
- Beta
responses:
'200':
description: Successful response
content:
application/json:
schema:
type: object
4XX:
description: error
delete:
summary: Clear issues
description: Removes all issues reported so far
operationId: clear_issues
tags:
- Beta
responses:
default:
description: error
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
4XX:
description: error
content:
application/json:
schema:
$ref: '#/components/schemas/ErrorResponse'
'200':
description: successful operation
content:
application/json:
schema:
type: object
properties:
usage:
default: null
anyOf:
- $ref: '#/components/schemas/Usage'
- nullable: true
time:
type: number
format: float
description: Time spent to process this request
example: 0.002
status:
type: string
example: ok
result:
type: boolean
components:
schemas:
HardwareUsage:
description: Usage of the hardware resources, spent to process the request
type: object
required:
- cpu
- payload_index_io_read
- payload_index_io_write
- payload_io_read
- payload_io_write
- vector_io_read
- vector_io_write
properties:
cpu:
type: integer
format: uint
minimum: 0
payload_io_read:
type: integer
format: uint
minimum: 0
payload_io_write:
type: integer
format: uint
minimum: 0
payload_index_io_read:
type: integer
format: uint
minimum: 0
payload_index_io_write:
type: integer
format: uint
minimum: 0
vector_io_read:
type: integer
format: uint
minimum: 0
vector_io_write:
type: integer
format: uint
minimum: 0
Usage:
description: Usage of the hardware resources, spent to process the request
type: object
properties:
hardware:
anyOf:
- $ref: '#/components/schemas/HardwareUsage'
- nullable: true
inference:
anyOf:
- $ref: '#/components/schemas/InferenceUsage'
- nullable: true
ErrorResponse:
type: object
properties:
time:
type: number
format: float
description: Time spent to process this request
status:
type: object
properties:
error:
type: string
description: Description of the occurred error.
result:
type: object
nullable: true
InferenceUsage:
type: object
required:
- models
properties:
models:
type: object
additionalProperties:
$ref: '#/components/schemas/ModelUsage'
ModelUsage:
type: object
required:
- tokens
properties:
tokens:
type: integer
format: uint64
minimum: 0
securitySchemes:
api-key:
type: apiKey
in: header
name: api-key
description: Authorization key, either read-write or read-only
bearerAuth:
type: http
scheme: bearer
externalDocs:
description: Find out more about Qdrant applications and demo
url: https://qdrant.tech/documentation/