OpenAI Vector stores API

openapi: 3.2.0
info:
  title: OpenAI Vector stores API
  description: The OpenAI REST API. Please see https://platform.openai.com/docs/api-reference for more details.
  version: 2.3.0
  termsOfService: https://openai.com/policies/terms-of-use
  contact:
    name: OpenAI Support
    url: https://help.openai.com/
  license:
    name: MIT
    url: https://github.com/openai/openai-openapi/blob/master/LICENSE
servers:
- url: https://api.openai.com/v1
security:
- ApiKeyAuth: []
tags:
- name: Vector stores
paths:
  /vector_stores:
    get:
      operationId: listVectorStores
      tags:
      - Vector stores
      summary: Returns a list of vector stores.
      parameters:
      - name: limit
        in: query
        description: 'A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.

          '
        required: false
        schema:
          type: integer
          default: 20
      - name: order
        in: query
        description: 'Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for descending order.

          '
        schema:
          type: string
          default: desc
          enum:
          - asc
          - desc
      - name: after
        in: query
        description: 'A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.

          '
        schema:
          type: string
      - name: before
        in: query
        description: 'A cursor for use in pagination. `before` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, starting with obj_foo, your subsequent call can include before=obj_foo in order to fetch the previous page of the list.

          '
        schema:
          type: string
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListVectorStoresResponse'
      x-oaiMeta:
        name: List vector stores
        group: vector_stores
        examples:
          request:
            curl: "curl https://api.openai.com/v1/vector_stores \\\n  -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\"\n"
            python: "import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n    api_key=os.environ.get(\"OPENAI_API_KEY\"),  # This is the default and can be omitted\n)\npage = client.vector_stores.list()\npage = page.data[0]\nprint(page.id)"
            javascript: "import OpenAI from \"openai\";\nconst openai = new OpenAI();\n\nasync function main() {\n  const vectorStores = await openai.vectorStores.list();\n  console.log(vectorStores);\n}\n\nmain();\n"
            node.js: "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted\n});\n\n// Automatically fetches more pages as needed.\nfor await (const vectorStore of client.vectorStores.list()) {\n  console.log(vectorStore.id);\n}"
            go: "package main\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\n\t\"github.com/openai/openai-go\"\n\t\"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n\tclient := openai.NewClient(\n\t\toption.WithAPIKey(\"My API Key\"),\n\t)\n\tpage, err := client.VectorStores.List(context.TODO(), openai.VectorStoreListParams{})\n\tif err != nil {\n\t\tpanic(err.Error())\n\t}\n\tfmt.Printf(\"%+v\\n\", page)\n}\n"
            java: "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.VectorStoreListPage;\nimport com.openai.models.vectorstores.VectorStoreListParams;\n\npublic final class Main {\n    private Main() {}\n\n    public static void main(String[] args) {\n        OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n        VectorStoreListPage page = client.vectorStores().list();\n    }\n}"
            ruby: 'require "openai"


              openai = OpenAI::Client.new(api_key: "My API Key")


              page = openai.vector_stores.list


              puts(page)'
          response: "{\n  \"object\": \"list\",\n  \"data\": [\n    {\n      \"id\": \"vs_abc123\",\n      \"object\": \"vector_store\",\n      \"created_at\": 1699061776,\n      \"name\": \"Support FAQ\",\n      \"description\": \"Contains commonly asked questions and answers, organized by topic.\",\n      \"bytes\": 139920,\n      \"file_counts\": {\n        \"in_progress\": 0,\n        \"completed\": 3,\n        \"failed\": 0,\n        \"cancelled\": 0,\n        \"total\": 3\n      }\n    },\n    {\n      \"id\": \"vs_abc456\",\n      \"object\": \"vector_store\",\n      \"created_at\": 1699061776,\n      \"name\": \"Support FAQ v2\",\n      \"description\": null,\n      \"bytes\": 139920,\n      \"file_counts\": {\n        \"in_progress\": 0,\n        \"completed\": 3,\n        \"failed\": 0,\n        \"cancelled\": 0,\n        \"total\": 3\n      }\n    }\n  ],\n  \"first_id\": \"vs_abc123\",\n  \"last_id\": \"vs_abc456\",\n  \"has_more\": false\n}\n"
    post:
      operationId: createVectorStore
      tags:
      - Vector stores
      summary: Create a vector store.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateVectorStoreRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreObject'
      x-oaiMeta:
        name: Create vector store
        group: vector_stores
        examples:
          request:
            curl: "curl https://api.openai.com/v1/vector_stores \\\n  -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\" \\\n  -d '{\n    \"name\": \"Support FAQ\"\n  }'\n"
            python: "import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n    api_key=os.environ.get(\"OPENAI_API_KEY\"),  # This is the default and can be omitted\n)\nvector_store = client.vector_stores.create()\nprint(vector_store.id)"
            javascript: "import OpenAI from \"openai\";\nconst openai = new OpenAI();\n\nasync function main() {\n  const vectorStore = await openai.vectorStores.create({\n    name: \"Support FAQ\"\n  });\n  console.log(vectorStore);\n}\n\nmain();\n"
            node.js: "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted\n});\n\nconst vectorStore = await client.vectorStores.create();\n\nconsole.log(vectorStore.id);"
            go: "package main\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\n\t\"github.com/openai/openai-go\"\n\t\"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n\tclient := openai.NewClient(\n\t\toption.WithAPIKey(\"My API Key\"),\n\t)\n\tvectorStore, err := client.VectorStores.New(context.TODO(), openai.VectorStoreNewParams{})\n\tif err != nil {\n\t\tpanic(err.Error())\n\t}\n\tfmt.Printf(\"%+v\\n\", vectorStore.ID)\n}\n"
            java: "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.VectorStore;\nimport com.openai.models.vectorstores.VectorStoreCreateParams;\n\npublic final class Main {\n    private Main() {}\n\n    public static void main(String[] args) {\n        OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n        VectorStore vectorStore = client.vectorStores().create();\n    }\n}"
            ruby: 'require "openai"


              openai = OpenAI::Client.new(api_key: "My API Key")


              vector_store = openai.vector_stores.create


              puts(vector_store)'
          response: "{\n  \"id\": \"vs_abc123\",\n  \"object\": \"vector_store\",\n  \"created_at\": 1699061776,\n  \"name\": \"Support FAQ\",\n  \"description\": \"Contains commonly asked questions and answers, organized by topic.\",\n  \"bytes\": 139920,\n  \"file_counts\": {\n    \"in_progress\": 0,\n    \"completed\": 3,\n    \"failed\": 0,\n    \"cancelled\": 0,\n    \"total\": 3\n  }\n}\n"
  /vector_stores/{vector_store_id}:
    get:
      operationId: getVectorStore
      tags:
      - Vector stores
      summary: Retrieves a vector store.
      parameters:
      - in: path
        name: vector_store_id
        required: true
        schema:
          type: string
        description: The ID of the vector store to retrieve.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreObject'
      x-oaiMeta:
        name: Retrieve vector store
        group: vector_stores
        examples:
          request:
            curl: "curl https://api.openai.com/v1/vector_stores/vs_abc123 \\\n  -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\"\n"
            python: "import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n    api_key=os.environ.get(\"OPENAI_API_KEY\"),  # This is the default and can be omitted\n)\nvector_store = client.vector_stores.retrieve(\n    \"vector_store_id\",\n)\nprint(vector_store.id)"
            javascript: "import OpenAI from \"openai\";\nconst openai = new OpenAI();\n\nasync function main() {\n  const vectorStore = await openai.vectorStores.retrieve(\n    \"vs_abc123\"\n  );\n  console.log(vectorStore);\n}\n\nmain();\n"
            node.js: "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted\n});\n\nconst vectorStore = await client.vectorStores.retrieve('vector_store_id');\n\nconsole.log(vectorStore.id);"
            go: "package main\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\n\t\"github.com/openai/openai-go\"\n\t\"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n\tclient := openai.NewClient(\n\t\toption.WithAPIKey(\"My API Key\"),\n\t)\n\tvectorStore, err := client.VectorStores.Get(context.TODO(), \"vector_store_id\")\n\tif err != nil {\n\t\tpanic(err.Error())\n\t}\n\tfmt.Printf(\"%+v\\n\", vectorStore.ID)\n}\n"
            java: "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.VectorStore;\nimport com.openai.models.vectorstores.VectorStoreRetrieveParams;\n\npublic final class Main {\n    private Main() {}\n\n    public static void main(String[] args) {\n        OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n        VectorStore vectorStore = client.vectorStores().retrieve(\"vector_store_id\");\n    }\n}"
            ruby: 'require "openai"


              openai = OpenAI::Client.new(api_key: "My API Key")


              vector_store = openai.vector_stores.retrieve("vector_store_id")


              puts(vector_store)'
          response: "{\n  \"id\": \"vs_abc123\",\n  \"object\": \"vector_store\",\n  \"created_at\": 1699061776\n}\n"
    post:
      operationId: modifyVectorStore
      tags:
      - Vector stores
      summary: Modifies a vector store.
      parameters:
      - in: path
        name: vector_store_id
        required: true
        schema:
          type: string
        description: The ID of the vector store to modify.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/UpdateVectorStoreRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreObject'
      x-oaiMeta:
        name: Modify vector store
        group: vector_stores
        examples:
          request:
            curl: "curl https://api.openai.com/v1/vector_stores/vs_abc123 \\\n  -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\"\n  -d '{\n    \"name\": \"Support FAQ\"\n  }'\n"
            python: "import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n    api_key=os.environ.get(\"OPENAI_API_KEY\"),  # This is the default and can be omitted\n)\nvector_store = client.vector_stores.update(\n    vector_store_id=\"vector_store_id\",\n)\nprint(vector_store.id)"
            javascript: "import OpenAI from \"openai\";\nconst openai = new OpenAI();\n\nasync function main() {\n  const vectorStore = await openai.vectorStores.update(\n    \"vs_abc123\",\n    {\n      name: \"Support FAQ\"\n    }\n  );\n  console.log(vectorStore);\n}\n\nmain();\n"
            node.js: "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted\n});\n\nconst vectorStore = await client.vectorStores.update('vector_store_id');\n\nconsole.log(vectorStore.id);"
            go: "package main\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\n\t\"github.com/openai/openai-go\"\n\t\"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n\tclient := openai.NewClient(\n\t\toption.WithAPIKey(\"My API Key\"),\n\t)\n\tvectorStore, err := client.VectorStores.Update(\n\t\tcontext.TODO(),\n\t\t\"vector_store_id\",\n\t\topenai.VectorStoreUpdateParams{},\n\t)\n\tif err != nil {\n\t\tpanic(err.Error())\n\t}\n\tfmt.Printf(\"%+v\\n\", vectorStore.ID)\n}\n"
            java: "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.VectorStore;\nimport com.openai.models.vectorstores.VectorStoreUpdateParams;\n\npublic final class Main {\n    private Main() {}\n\n    public static void main(String[] args) {\n        OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n        VectorStore vectorStore = client.vectorStores().update(\"vector_store_id\");\n    }\n}"
            ruby: 'require "openai"


              openai = OpenAI::Client.new(api_key: "My API Key")


              vector_store = openai.vector_stores.update("vector_store_id")


              puts(vector_store)'
          response: "{\n  \"id\": \"vs_abc123\",\n  \"object\": \"vector_store\",\n  \"created_at\": 1699061776,\n  \"name\": \"Support FAQ\",\n  \"description\": \"Contains commonly asked questions and answers, organized by topic.\",\n  \"bytes\": 139920,\n  \"file_counts\": {\n    \"in_progress\": 0,\n    \"completed\": 3,\n    \"failed\": 0,\n    \"cancelled\": 0,\n    \"total\": 3\n  }\n}\n"
    delete:
      operationId: deleteVectorStore
      tags:
      - Vector stores
      summary: Delete a vector store.
      parameters:
      - in: path
        name: vector_store_id
        required: true
        schema:
          type: string
        description: The ID of the vector store to delete.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/DeleteVectorStoreResponse'
      x-oaiMeta:
        name: Delete vector store
        group: vector_stores
        examples:
          request:
            curl: "curl https://api.openai.com/v1/vector_stores/vs_abc123 \\\n  -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\" \\\n  -X DELETE\n"
            python: "import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n    api_key=os.environ.get(\"OPENAI_API_KEY\"),  # This is the default and can be omitted\n)\nvector_store_deleted = client.vector_stores.delete(\n    \"vector_store_id\",\n)\nprint(vector_store_deleted.id)"
            javascript: "import OpenAI from \"openai\";\nconst openai = new OpenAI();\n\nasync function main() {\n  const deletedVectorStore = await openai.vectorStores.delete(\n    \"vs_abc123\"\n  );\n  console.log(deletedVectorStore);\n}\n\nmain();\n"
            node.js: "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted\n});\n\nconst vectorStoreDeleted = await client.vectorStores.delete('vector_store_id');\n\nconsole.log(vectorStoreDeleted.id);"
            go: "package main\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\n\t\"github.com/openai/openai-go\"\n\t\"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n\tclient := openai.NewClient(\n\t\toption.WithAPIKey(\"My API Key\"),\n\t)\n\tvectorStoreDeleted, err := client.VectorStores.Delete(context.TODO(), \"vector_store_id\")\n\tif err != nil {\n\t\tpanic(err.Error())\n\t}\n\tfmt.Printf(\"%+v\\n\", vectorStoreDeleted.ID)\n}\n"
            java: "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.VectorStoreDeleteParams;\nimport com.openai.models.vectorstores.VectorStoreDeleted;\n\npublic final class Main {\n    private Main() {}\n\n    public static void main(String[] args) {\n        OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n        VectorStoreDeleted vectorStoreDeleted = client.vectorStores().delete(\"vector_store_id\");\n    }\n}"
            ruby: 'require "openai"


              openai = OpenAI::Client.new(api_key: "My API Key")


              vector_store_deleted = openai.vector_stores.delete("vector_store_id")


              puts(vector_store_deleted)'
          response: "{\n  id: \"vs_abc123\",\n  object: \"vector_store.deleted\",\n  deleted: true\n}\n"
  /vector_stores/{vector_store_id}/file_batches:
    post:
      operationId: createVectorStoreFileBatch
      tags:
      - Vector stores
      summary: Create a vector store file batch.
      description: 'The maximum number of files in a single batch request is 2000.

        Vector store file attach requests are rate limited per vector store (300 requests per minute across both this endpoint and `/vector_stores/{vector_store_id}/files`).

        For ingesting multiple files into the same vector store, this batch endpoint is recommended.

        '
      parameters:
      - in: path
        name: vector_store_id
        required: true
        schema:
          type: string
          example: vs_abc123
        description: 'The ID of the vector store for which to create a File Batch.

          '
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateVectorStoreFileBatchRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreFileBatchObject'
      x-oaiMeta:
        name: Create vector store file batch
        group: vector_stores
        description: 'Attaches multiple files to a vector store in one request. This is the recommended approach for multi-file ingestion, especially because per-vector-store file attach writes are rate-limited (300 requests/minute shared with `/vector_stores/{vector_store_id}/files`).

          '
        examples:
          request:
            curl: "curl https://api.openai.com/v1/vector_stores/vs_abc123/file_batches \\\n    -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n    -H \"Content-Type: application/json \\\n    -H \"OpenAI-Beta: assistants=v2\" \\\n    -d '{\n      \"files\": [\n        {\n          \"file_id\": \"file-abc123\",\n          \"attributes\": {\"category\": \"finance\"}\n        },\n        {\n          \"file_id\": \"file-abc456\",\n          \"chunking_strategy\": {\n            \"type\": \"static\",\n            \"max_chunk_size_tokens\": 1200,\n            \"chunk_overlap_tokens\": 200\n          }\n        }\n      ]\n    }'\n"
            python: "import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n    api_key=os.environ.get(\"OPENAI_API_KEY\"),  # This is the default and can be omitted\n)\nvector_store_file_batch = client.vector_stores.file_batches.create(\n    vector_store_id=\"vs_abc123\",\n)\nprint(vector_store_file_batch.id)"
            javascript: "import OpenAI from \"openai\";\nconst openai = new OpenAI();\n\nasync function main() {\n  const myVectorStoreFileBatch = await openai.vectorStores.fileBatches.create(\n    \"vs_abc123\",\n    {\n      files: [\n        {\n          file_id: \"file-abc123\",\n          attributes: { category: \"finance\" },\n        },\n        {\n          file_id: \"file-abc456\",\n          chunking_strategy: {\n            type: \"static\",\n            max_chunk_size_tokens: 1200,\n            chunk_overlap_tokens: 200,\n          },\n        },\n      ]\n    }\n  );\n  console.log(myVectorStoreFileBatch);\n}\n\nmain();\n"
            node.js: "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted\n});\n\nconst vectorStoreFileBatch = await client.vectorStores.fileBatches.create('vs_abc123');\n\nconsole.log(vectorStoreFileBatch.id);"
            go: "package main\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\n\t\"github.com/openai/openai-go\"\n\t\"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n\tclient := openai.NewClient(\n\t\toption.WithAPIKey(\"My API Key\"),\n\t)\n\tvectorStoreFileBatch, err := client.VectorStores.FileBatches.New(\n\t\tcontext.TODO(),\n\t\t\"vs_abc123\",\n\t\topenai.VectorStoreFileBatchNewParams{},\n\t)\n\tif err != nil {\n\t\tpanic(err.Error())\n\t}\n\tfmt.Printf(\"%+v\\n\", vectorStoreFileBatch.ID)\n}\n"
            java: "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.filebatches.FileBatchCreateParams;\nimport com.openai.models.vectorstores.filebatches.VectorStoreFileBatch;\n\npublic final class Main {\n    private Main() {}\n\n    public static void main(String[] args) {\n        OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n        VectorStoreFileBatch vectorStoreFileBatch = client.vectorStores().fileBatches().create(\"vs_abc123\");\n    }\n}"
            ruby: 'require "openai"


              openai = OpenAI::Client.new(api_key: "My API Key")


              vector_store_file_batch = openai.vector_stores.file_batches.create("vs_abc123")


              puts(vector_store_file_batch)'
          response: "{\n  \"id\": \"vsfb_abc123\",\n  \"object\": \"vector_store.file_batch\",\n  \"created_at\": 1699061776,\n  \"vector_store_id\": \"vs_abc123\",\n  \"status\": \"in_progress\",\n  \"file_counts\": {\n    \"in_progress\": 1,\n    \"completed\": 1,\n    \"failed\": 0,\n    \"cancelled\": 0,\n    \"total\": 0,\n  }\n}\n"
  /vector_stores/{vector_store_id}/file_batches/{batch_id}:
    get:
      operationId: getVectorStoreFileBatch
      tags:
      - Vector stores
      summary: Retrieves a vector store file batch.
      parameters:
      - in: path
        name: vector_store_id
        required: true
        schema:
          type: string
          example: vs_abc123
        description: The ID of the vector store that the file batch belongs to.
      - in: path
        name: batch_id
        required: true
        schema:
          type: string
          example: vsfb_abc123
        description: The ID of the file batch being retrieved.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreFileBatchObject'
      x-oaiMeta:
        name: Retrieve vector store file batch
        group: vector_stores
        examples:
          request:
            curl: "curl https://api.openai.com/v1/vector_stores/vs_abc123/file_batches/vsfb_abc123 \\\n  -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\"\n"
            python: "import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n    api_key=os.environ.get(\"OPENAI_API_KEY\"),  # This is the default and can be omitted\n)\nvector_store_file_batch = client.vector_stores.file_batches.retrieve(\n    batch_id=\"vsfb_abc123\",\n    vector_store_id=\"vs_abc123\",\n)\nprint(vector_store_file_batch.id)"
            javascript: "import OpenAI from \"openai\";\nconst openai = new OpenAI();\n\nasync function main() {\n  const vectorStoreFileBatch = await openai.vectorStores.fileBatches.retrieve(\n    \"vsfb_abc123\",\n    { vector_store_id: \"vs_abc123\" }\n  );\n  console.log(vectorStoreFileBatch);\n}\n\nmain();\n"
            node.js: "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted\n});\n\nconst vectorStoreFileBatch = await client.vectorStores.fileBatches.retrieve('vsfb_abc123', {\n  vector_store_id: 'vs_abc123',\n});\n\nconsole.log(vectorStoreFileBatch.id);"
            go: "package main\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\n\t\"github.com/openai/openai-go\"\n\t\"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n\tclient := openai.NewClient(\n\t\toption.WithAPIKey(\"My API Key\"),\n\t)\n\tvectorStoreFileBatch, err := client.VectorStores.FileBatches.Get(\n\t\tcontext.TODO(),\n\t\t\"vs_abc123\",\n\t\t\"vsfb_abc123\",\n\t)\n\tif err != nil {\n\t\tpanic(err.Error())\n\t}\n\tfmt.Printf(\"%+v\\n\", vectorStoreFileBatch.ID)\n}\n"
            java: "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.filebatches.FileBatchRetrieveParams;\nimport com.openai.models.vectorstores.filebatches.VectorStoreFileBatch;\n\npublic final class Main {\n    private Main() {}\n\n    public static void main(String[] args) {\n        OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n        FileBatchRetrieveParams params = FileBatchRetrieveParams.builder()\n            .vectorStoreId(\"vs_abc123\")\n            .batchId(\"vsfb_abc123\")\n            .build();\n        VectorStoreFileBatch vectorStoreFileBatch = client.vectorStores().fileBatches().retrieve(params);\n    }\n}"
            ruby: 'require "openai"


              openai = OpenAI::Client.new(api_key: "My API Key")


              vector_store_file_batch = openai.vector_stores.file_batches.retrieve("vsfb_abc123", vector_store_id: "vs_abc123")


              puts(vector_store_file_batch)'
          response: "{\n  \"id\": \"vsfb_abc123\",\n  \"object\": \"vector_store.file_batch\",\n  \"created_at\": 1699061776,\n  \"vector_store_id\": \"vs_abc123\",\n  \"status\": \"in_progress\",\n  \"file_counts\": {\n    \"in_progress\": 1,\n    \"completed\": 1,\n    \"failed\": 0,\n    \"cancelled\": 0,\n    \"total\": 0,\n  }\n}\n"
  /vector_stores/{vector_store_id}/file_batches/{batch_id}/cancel:
    post:
      operationId: cancelVectorStoreFileBatch
      tags:
      - Vector stores
      summary: Cancel a vector store file batch. This attempts to cancel the processing of files in this batch as soon as possible.
      parameters:
      - in: path
        name: vector_store_id
        required: true
        schema:
          type: string
        description: The ID of the vector store that the file batch belongs to.
      - in: path
        name: batch_id
        required: true
        schema:
          type: string
        description: The ID of the file batch to cancel.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreFileBatchObject'
      x-oaiMeta:
        name: Cancel vector store file batch
        group: vector_stores
        examples:
          request:
            curl: "curl https://api.openai.com/v1/vector_stores/vs_abc123/files_batches/vsfb_abc123/cancel \\\n  -H \"Authorization: Bearer $OPENAI_API_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\" \\\n  -X POST\n"
            python: "import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n    api_key=os.environ.get(\"OPENAI_API_KEY\"),  # This is the default and can be omitted\n)\nvector_store_file_batch = client.vector_stores.file_batches.cancel(\n    batch_id=\"batch_id\",\n    vector_store_id=\"vector_store_id\",\n)\nprint(vector_store_file_batch.id)"
            javascript: "import OpenAI from \"openai\";\nconst openai = new OpenAI();\n\nasync function main() {\n  const deletedVectorStoreFileBatch = await openai.vectorStores.fileBatches.cancel(\n    \"vsfb_abc123\",\n    { vector_store_id: \"vs_abc123\" }\n  );\n  console.log(deletedVectorStoreFileBatch);\n}\n\nmain();\n"
            node.js: "import OpenAI from 'openai';\n\nconst client = new OpenAI({\n  apiKey: process.env['OPENAI_API_KEY'], // This is the default and can be omitted\n});\n\nconst vectorStoreFileBatch = await client.vectorStores.fileBatches.cancel('batch_id', {\n  vector_store_id: 'vector_store_id',\n});\n\nconsole.log(vectorStoreFileBatch.id);"
            go: "package main\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\n\t\"github.com/openai/openai-go\"\n\t\"github.com/openai/openai-go/option\"\n)\n\nfunc main() {\n\tclient := openai.NewClient(\n\t\toption.WithAPIKey(\"My API Key\"),\n\t)\n\tvectorStoreFileBatch, err := client.VectorStores.FileBatches.Cancel(\n\t\tcontext.TODO(),\n\t\t\"vector_store_id\",\n\t\t\"batch_id\",\n\t)\n\tif err != nil {\n\t\tpanic(err.Error())\n\t}\n\tfmt.Printf(\"%+v\\n\", vectorStoreFileBatch.ID)\n}\n"
            java: "package com.openai.example;\n\nimport com.openai.client.OpenAIClient;\nimport com.openai.client.okhttp.OpenAIOkHttpClient;\nimport com.openai.models.vectorstores.filebatches.FileBatchCancelParams;\nimport com.openai.models.vectorstores.filebatches.VectorStoreFileBatch;\n\npublic final class Main {\n    private Main() {}\n\n    public static void main(String[] args) {\n        OpenAIClient client = OpenAIOkHttpClient.fromEnv();\n\n        FileBatchCancelParams params = FileBatchCancelParams.builder()\n            .vectorStoreId(\"vector_store_id\")\n            .batchId(\"batch_id\")\n            .build();\n        VectorStoreFileBatch vectorStoreFileBatch = client.vectorStores().fileBatches().cancel(params);\n    }\n}"
            ruby: 'require "openai"


              openai = OpenAI::Client.new(api_key: "My API Key")


              vector_store_file_batch = openai.vector_stores.file_batches.cancel("batch_id", vector_store_id: "vector_store_id")


              puts(vector_store_file_batch)'
          response: "{\n  \"id\": \"vsfb_abc123\",\n  \"object\": \"vector_store.file_batch\",\n  \"created_at\": 1699061776,\n  \"vector_store_id\": \"vs_abc123\",\n  \"status\": \"in_progress\",\n  \"file_counts\": {\n    \"in_progress\": 12,\n    \"completed\": 3,\n    \"failed\": 0,\n    \"cancelled\": 0,\n    \"total\": 15,\n  }\n}\n"
  /vector_stores/{vector_store_id}/file_batches/{batch_id}/files:
    get:
      operationId: listFilesInVectorStoreBatch
      tags:
      - Vector stores
      summary: Returns a list of vector store files in a batch.
      parameters:
      - name: vector_store_id
        in: path
        description: The ID of the vector store that the files belong to.
        required: true
        schema:
          type: string
      - name: batch_id
        in: path
        description: The ID of the file batch that the files belong to.
        required: true
        schema:
          type: string
      - name: limit
        in: query
        description: 'A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.

          '
        required: false
        schema:
          type: integer
          default: 20
      - name: order
        in: query
        description: 'Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for descending order.

          '
        schema:
          type: string
          default: desc
          enum:
          - asc
          - desc
      - name: after
        in: query
        description: 'A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 object

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# Full source: https://raw.githubusercontent.com/api-evangelist/openai/refs/heads/main/openapi/openai-vector-stores-api-openapi.yml