> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://api.qdrant.tech/v-1-18-x/api-reference/collections/create-vector-name/llms.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://api.qdrant.tech/_mcp/server. # Create named vector PUT http://localhost:6333/collections/{collection_name}/vectors/{vector_name} Content-Type: application/json Create a new named vector on an existing collection Reference: https://api.qdrant.tech/api-reference/collections/create-vector-name ## Authentication - `api-key` header (required) — API Key authentication via header ## Servers - `http://localhost:6333` (http, default) - `https://localhost:6333` (https) ## Request ### Path parameters - `collection_name` (string, required) — Name of the collection - `vector_name` (string, required) — Name of the vector to create ### Query parameters - `wait` (boolean, optional) — If true, wait for changes to actually happen - `ordering` (enum, optional) — define ordering guarantees for the operation - Allowed values: `weak`, `medium`, `strong` - `timeout` (integer, optional) — Timeout for the operation ### Body (application/json) This endpoint expects a VectorNameConfig. - `VectorNameConfig` ## Response ### 200 successful operation - `usage` (CollectionsCollectionNameVectorsVectorNamePutResponsesContentApplicationJsonSchemaUsage, optional) - `time` (double, optional) — Time spent to process this request - `status` (string, optional) - `result` (UpdateResult, optional) ## Types ### DenseVectorNameConfig Wrapper for dense vector creation config. - `dense` (DenseVectorConfig, required) — Configuration for creating a new dense named vector. Only includes properties that define the vector space and cannot be changed after creation. Storage type, index type, and quantization are inferred. ### SparseVectorNameConfig Wrapper for sparse vector creation config. - `sparse` (SparseVectorConfig, required) — Configuration for creating a new sparse named vector. Only includes properties that define the vector space and cannot be changed after creation. ### CollectionsCollectionNameVectorsVectorNamePutResponsesContentApplicationJsonSchemaUsage ### UpdateResult - `status` (enum, required) — `Acknowledged` - Request is saved to WAL and will be process in a queue. `Completed` - Request is completed, changes are actual. `WaitTimeout` - Request is waiting for timeout. - Allowed values: `acknowledged`, `completed`, `wait_timeout` - `operation_id` (uint64, optional, nullable) — Sequential number of the operation ### DenseVectorConfig Configuration for creating a new dense named vector. Only includes properties that define the vector space and cannot be changed after creation. Storage type, index type, and quantization are inferred. - `size` (integer, required) — Dimensionality of the vectors - `distance` (enum, required) — Type of internal tags, build from payload Distance function types used to compare vectors - Allowed values: `Cosine`, `Euclid`, `Dot`, `Manhattan` - `multivector_config` (DenseVectorConfigMultivectorConfig, optional) — Configuration for multi-vector points (e.g., ColBERT) - `datatype` (DenseVectorConfigDatatype, optional) — Element storage type (Float32, Float16, Uint8) ### SparseVectorConfig Configuration for creating a new sparse named vector. Only includes properties that define the vector space and cannot be changed after creation. - `modifier` (SparseVectorConfigModifier, optional) — Value modifier for sparse vectors (e.g., IDF) - `datatype` (SparseVectorConfigDatatype, optional) — Datatype used to store weights in the index ### Usage Usage of the hardware resources, spent to process the request - `hardware` (UsageHardware, optional) - `inference` (UsageInference, optional) ### DenseVectorConfigMultivectorConfig Configuration for multi-vector points (e.g., ColBERT) ### DenseVectorConfigDatatype Element storage type (Float32, Float16, Uint8) ### SparseVectorConfigModifier Value modifier for sparse vectors (e.g., IDF) ### SparseVectorConfigDatatype Datatype used to store weights in the index ### UsageHardware ### UsageInference ### MultiVectorConfig - `comparator` (enum, required) - Allowed values: `max_sim` ### HardwareUsage Usage of the hardware resources, spent to process the request - `cpu` (integer, required) - `payload_io_read` (integer, required) - `payload_io_write` (integer, required) - `payload_index_io_read` (integer, required) - `payload_index_io_write` (integer, required) - `vector_io_read` (integer, required) - `vector_io_write` (integer, required) ### InferenceUsage - `models` (map from string to ModelUsage, required) ### ModelUsage - `tokens` (uint64, required) ## Examples **Request** ```json {} ``` **Response** ```json { "usage": { "hardware": { "cpu": 1, "payload_io_read": 1, "payload_io_write": 1, "payload_index_io_read": 1, "payload_index_io_write": 1, "vector_io_read": 1, "vector_io_write": 1 }, "inference": { "models": {} } }, "time": 0.002, "status": "ok", "result": { "status": "acknowledged", "operation_id": 1 } } ``` **SDK Code** ```python import requests url = "http://localhost:6333/collections/collection_name/vectors/vector_name" payload = {} headers = { "api-key": "", "Content-Type": "application/json" } response = requests.put(url, json=payload, headers=headers) print(response.json()) ``` ```javascript const url = 'http://localhost:6333/collections/collection_name/vectors/vector_name'; const options = { method: 'PUT', headers: {'api-key': '', 'Content-Type': 'application/json'}, body: '{}' }; try { const response = await fetch(url, options); const data = await response.json(); console.log(data); } catch (error) { console.error(error); } ``` ```go package main import ( "fmt" "strings" "net/http" "io" ) func main() { url := "http://localhost:6333/collections/collection_name/vectors/vector_name" payload := strings.NewReader("{}") req, _ := http.NewRequest("PUT", url, payload) req.Header.Add("api-key", "") req.Header.Add("Content-Type", "application/json") res, _ := http.DefaultClient.Do(req) defer res.Body.Close() body, _ := io.ReadAll(res.Body) fmt.Println(res) fmt.Println(string(body)) } ``` ```ruby require 'uri' require 'net/http' url = URI("http://localhost:6333/collections/collection_name/vectors/vector_name") http = Net::HTTP.new(url.host, url.port) request = Net::HTTP::Put.new(url) request["api-key"] = '' request["Content-Type"] = 'application/json' request.body = "{}" response = http.request(request) puts response.read_body ``` ```java import com.mashape.unirest.http.HttpResponse; import com.mashape.unirest.http.Unirest; HttpResponse response = Unirest.put("http://localhost:6333/collections/collection_name/vectors/vector_name") .header("api-key", "") .header("Content-Type", "application/json") .body("{}") .asString(); ``` ```php request('PUT', 'http://localhost:6333/collections/collection_name/vectors/vector_name', [ 'body' => '{}', 'headers' => [ 'Content-Type' => 'application/json', 'api-key' => '', ], ]); echo $response->getBody(); ``` ```csharp using RestSharp; var client = new RestClient("http://localhost:6333/collections/collection_name/vectors/vector_name"); var request = new RestRequest(Method.PUT); request.AddHeader("api-key", ""); request.AddHeader("Content-Type", "application/json"); request.AddParameter("application/json", "{}", ParameterType.RequestBody); IRestResponse response = client.Execute(request); ``` ```swift import Foundation let headers = [ "api-key": "", "Content-Type": "application/json" ] let parameters = [] as [String : Any] let postData = JSONSerialization.data(withJSONObject: parameters, options: []) let request = NSMutableURLRequest(url: NSURL(string: "http://localhost:6333/collections/collection_name/vectors/vector_name")! as URL, cachePolicy: .useProtocolCachePolicy, timeoutInterval: 10.0) request.httpMethod = "PUT" request.allHTTPHeaderFields = headers request.httpBody = postData as Data let session = URLSession.shared let dataTask = session.dataTask(with: request as URLRequest, completionHandler: { (data, response, error) -> Void in if (error != nil) { print(error as Any) } else { let httpResponse = response as? HTTPURLResponse print(httpResponse) } }) dataTask.resume() ```