> ## Documentation Index > Fetch the complete documentation index at: https://docs.pinecone.io/llms.txt > Use this file to discover all available pages before exploring further. # Fetch vectors > The `fetch` operation looks up and returns vectors, by ID, from a single namespace. The returned vectors include the vector data and/or metadata. For on-demand indexes, since vector values are retrieved from object storage, fetch operations may have increased latency. If you only need metadata or IDs, consider using the query operation with `includeValues` set to `false` instead. For guidance and examples, see [Fetch data](https://docs.pinecone.io/guides/manage-data/fetch-data). ```python Python theme={null} # pip install "pinecone[grpc]" from pinecone.grpc import PineconeGRPC as Pinecone pc = Pinecone(api_key="YOUR_API_KEY") index = pc.Index("pinecone-index") index.fetch(ids=["id-1", "id-2"], namespace="example-namespace") ``` ```javascript JavaScript theme={null} // npm install @pinecone-database/pinecone import { Pinecone } from '@pinecone-database/pinecone' const pc = new Pinecone({ apiKey: 'YOUR_API_KEY' }) const index = pc.index('pinecone-index') const fetchResult = await index.namespace('example-namespace').fetch(['id-1', 'id-2']); ``` ```java Java theme={null} import io.pinecone.clients.Index; import io.pinecone.clients.Pinecone; import io.pinecone.proto.FetchResponse; import java.util.Arrays; import java.util.List; public class FetchExample { public static void main(String[] args) { Pinecone pc = new Pinecone.Builder("YOUR_API_KEY").build(); Index index = pc.getIndexConnection("pinecone-index"); List ids = Arrays.asList("id-1", "id-2"); FetchResponse fetchResponse = index.fetch(ids, "example-namespace"); System.out.println(fetchResponse); } } ``` ```shell curl theme={null} PINECONE_API_KEY="YOUR_API_KEY" INDEX_HOST="INDEX_HOST" curl -X GET "https://$INDEX_HOST/vectors/fetch?ids=id-1&ids=id-2&namespace=example-namespace" \ -H "Api-Key: $PINECONE_API_KEY" \ -H "X-Pinecone-Api-Version: 2024-04" ``` ## OpenAPI ````yaml https://raw.githubusercontent.com/pinecone-io/pinecone-api/refs/heads/main/2024-04/data_2024-04.oas.yaml get /vectors/fetch openapi: 3.0.3 info: title: Pinecone Data Plane API description: >- Pinecone is a vector database that makes it easy to search and retrieve billions of high-dimensional vectors. version: 2024-04 contact: name: Pinecone Support url: https://support.pinecone.io email: support@pinecone.io license: name: Apache 2.0 url: https://www.apache.org/licenses/LICENSE-2.0 servers: - url: https://{index_host} variables: index_host: default: unknown description: host of the index security: - ApiKeyAuth: [] tags: - name: Data Plane externalDocs: description: More Pinecone.io API docs url: https://docs.pinecone.io/introduction paths: /vectors/fetch: get: tags: - Data Plane summary: Fetch vectors description: >- The `fetch` operation looks up and returns vectors, by ID, from a single namespace. The returned vectors include the vector data and/or metadata. For on-demand indexes, since vector values are retrieved from object storage, fetch operations may have increased latency. If you only need metadata or IDs, consider using the query operation with `includeValues` set to `false` instead. For guidance and examples, see [Fetch data](https://docs.pinecone.io/guides/manage-data/fetch-data). operationId: fetch parameters: - name: ids description: The vector IDs to fetch. Does not accept values containing spaces. in: query required: true explode: true schema: type: array items: type: string - name: namespace in: query required: false schema: type: string responses: '200': description: A successful response. content: application/json: schema: $ref: '#/components/schemas/FetchResponse' default: description: An unexpected error response. content: application/json: schema: $ref: '#/components/schemas/rpcStatus' components: schemas: FetchResponse: type: object properties: vectors: type: object additionalProperties: $ref: '#/components/schemas/Vector' title: >- The fetched vectors, in the form of a map between the fetched ids and the fetched vectors namespace: type: string example: example-namespace description: The namespace of the vectors. usage: $ref: '#/components/schemas/Usage' description: The response for the `fetch` operation. example: vectors: id-1: id: id-1 values: - 1 - 1.5 id-2: id: id-2 values: - 2 - 1 namespace: example-namespace usage: readUnits: 1 rpcStatus: type: object properties: code: type: integer format: int32 message: type: string details: type: array items: $ref: '#/components/schemas/protobufAny' Vector: type: object properties: id: type: string example: example-vector-1 description: This is the vector's unique id. maxLength: 512 minLength: 1 required: - id values: type: array example: - 0.1 - 0.2 - 0.3 - 0.4 - 0.5 - 0.6 - 0.7 - 0.8 items: type: number format: float description: This is the vector data included in the request. maxLength: 20000 minLength: 1 required: - values sparseValues: $ref: '#/components/schemas/SparseValues' metadata: type: object example: genre: documentary year: 2019 description: This is the metadata included in the request. required: - id - values Usage: type: object properties: readUnits: type: integer format: int64 example: 5 description: The number of read units consumed by this operation. protobufAny: type: object properties: typeUrl: type: string value: type: string format: byte SparseValues: type: object description: >- Vector sparse data. Represented as a list of indices and a list of corresponded values, which must be with the same length. properties: indices: type: array description: The indices of the sparse data. example: - 1 - 312 - 822 - 14 - 980 items: type: integer format: int64 maxLength: 1000 minLength: 1 required: - indices values: type: array description: >- The corresponding values of the sparse data, which must be with the same length as the indices. example: - 0.1 - 0.2 - 0.3 - 0.4 - 0.5 items: type: number format: float maxLength: 1000 minLength: 1 required: - values required: - indices - values securitySchemes: ApiKeyAuth: type: apiKey name: Api-Key description: >- An API Key is required to call Pinecone APIs. Get yours from the [console](https://app.pinecone.io/). in: header ````