Portkey Vector Stores API

The Vector Stores API from Portkey — 8 operation(s) for vector stores.

OpenAPI Specification

portkey-vector-stores-api-openapi.yml Raw ↑
openapi: 3.0.0
info:
  title: Portkey Analytics > Graphs Vector Stores API
  description: The Portkey REST API. Please see https://portkey.ai/docs/api-reference for more details.
  version: 2.0.0
  termsOfService: https://portkey.ai/terms
  contact:
    name: Portkey Developer Forum
    url: https://portkey.wiki/community
  license:
    name: MIT
    url: https://github.com/Portkey-AI/portkey-openapi/blob/master/LICENSE
servers:
- url: https://api.portkey.ai/v1
  description: Portkey API Public Endpoint
security:
- Portkey-Key: []
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, ending 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'
      security:
      - Portkey-Key: []
        Virtual-Key: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
      - Portkey-Key: []
        Config: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
        Custom-Host: []
      x-code-samples:
      - lang: curl
        source: "curl https://api.portkey.ai/v1/vector_stores \\\n  -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n  -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\"\n"
      - lang: python
        source: "from portkey_ai import Portkey\n\nclient = Portkey(\n  api_key = \"PORTKEY_API_KEY\",\n  virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\nvector_stores = client.beta.vector_stores.list()\nprint(vector_stores)\n"
      - lang: javascript
        source: "import Portkey from 'portkey-ai';\n\nconst client = new Portkey({\n  apiKey: 'PORTKEY_API_KEY',\n  virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n  const vectorStores = await client.beta.vectorStores.list();\n  console.log(vectorStores);\n}\n\nmain();\n"
        response: "{\n  \"object\": \"list\",\n  \"data\": [\n    {\n      \"id\": \"vs_abc123\",\n      \"object\": \"vector_store\",\n      \"created_at\": 1699061776,\n      \"name\": \"Support FAQ\",\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      \"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'
      security:
      - Portkey-Key: []
        Virtual-Key: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
      - Portkey-Key: []
        Config: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
        Custom-Host: []
      x-code-samples:
      - lang: curl
        source: "curl https://api.portkey.ai/v1/vector_stores \\\n  -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n  -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\"\n  -d '{\n    \"name\": \"Support FAQ\"\n}'\n"
      - lang: python
        source: "from portkey_ai import Portkey\n\nclient = Portkey(\n  api_key = \"PORTKEY_API_KEY\",\n  virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\nvector_store = client.beta.vector_stores.create(\n  name=\"Support FAQ\"\n)\nprint(vector_store)\n"
      - lang: javascript
        source: "import Portkey from 'portkey-ai';\n\nconst client = new Portkey({\n  apiKey: 'PORTKEY_API_KEY',\n  virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n  const vectorStore = await client.beta.vectorStores.create({\n    name: \"Support FAQ\"\n  });\n  console.log(vectorStore);\n}\n\nmain();\n"
        response: "{\n  \"id\": \"vs_abc123\",\n  \"object\": \"vector_store\",\n  \"created_at\": 1699061776,\n  \"name\": \"Support FAQ\",\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'
      security:
      - Portkey-Key: []
        Virtual-Key: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
      - Portkey-Key: []
        Config: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
        Custom-Host: []
      x-code-samples:
      - lang: curl
        source: "curl https://api.portkey.ai/v1/vector_stores/vs_abc123 \\\n  -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n  -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\"\n"
      - lang: python
        source: "from portkey_ai import Portkey\n\nclient = Portkey(\n  api_key = \"PORTKEY_API_KEY\",\n  virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\nvector_store = client.beta.vector_stores.retrieve(\n  vector_store_id=\"vs_abc123\"\n)\nprint(vector_store)\n"
      - lang: javascript
        source: "import Portkey from 'portkey-ai';\n\nconst client = new Portkey({\n  apiKey: 'PORTKEY_API_KEY',\n  virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n  const vectorStore = await client.beta.vectorStores.retrieve(\n    \"vs_abc123\"\n  );\n  console.log(vectorStore);\n}\n\nmain();\n"
        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'
      security:
      - Portkey-Key: []
        Virtual-Key: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
      - Portkey-Key: []
        Config: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
        Custom-Host: []
      x-code-samples:
      - lang: curl
        source: "curl https://api.portkey.ai/v1/vector_stores/vs_abc123 \\\n  -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n  -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\"\n  -d '{\n    \"name\": \"Support FAQ\"\n  }'\n"
      - lang: python
        source: "from portkey_ai import Portkey\n\nclient = Portkey(\n  api_key = \"PORTKEY_API_KEY\",\n  virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\nvector_store = client.beta.vector_stores.update(\n  vector_store_id=\"vs_abc123\",\n  name=\"Support FAQ\"\n)\nprint(vector_store)\n"
      - lang: javascript
        source: "import Portkey from 'portkey-ai';\n\nconst client = new Portkey({\n  apiKey: 'PORTKEY_API_KEY',\n  virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n  const vectorStore = await client.beta.vectorStores.update(\n    \"vs_abc123\",\n    {\n      name: \"Support FAQ\"\n    }\n  );\n  console.log(vectorStore);\n}\n\nmain();\n"
        response: "{\n  \"id\": \"vs_abc123\",\n  \"object\": \"vector_store\",\n  \"created_at\": 1699061776,\n  \"name\": \"Support FAQ\",\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'
      security:
      - Portkey-Key: []
        Virtual-Key: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
      - Portkey-Key: []
        Config: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
        Custom-Host: []
      x-code-samples:
      - lang: curl
        source: "curl https://api.portkey.ai/v1/vector_stores/vs_abc123 \\\n  -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n  -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\" \\\n  -X DELETE\n"
      - lang: python
        source: "from portkey_ai import Portkey\n\nclient = Portkey(\n  api_key = \"PORTKEY_API_KEY\",\n  virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\ndeleted_vector_store = client.beta.vector_stores.delete(\n  vector_store_id=\"vs_abc123\"\n)\nprint(deleted_vector_store)\n"
      - lang: javascript
        source: "import Portkey from 'portkey-ai';\n\nconst client = new Portkey({\n  apiKey: 'PORTKEY_API_KEY',\n  virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n  const deletedVectorStore = await client.beta.vectorStores.del(\n    \"vs_abc123\"\n  );\n  console.log(deletedVectorStore);\n}\n\nmain();\n"
        response: "{\n  \"id\": \"vs_abc123\",\n  \"object\": \"vector_store.deleted\",\n  \"deleted\": true\n}\n"
  /vector_stores/{vector_store_id}/files:
    get:
      operationId: listVectorStoreFiles
      tags:
      - Vector Stores
      summary: Returns a list of vector store files.
      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: 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, ending with obj_foo, your subsequent call can include before=obj_foo in order to fetch the previous page of the list.

          '
        schema:
          type: string
      - name: filter
        in: query
        description: Filter by file status. One of `in_progress`, `completed`, `failed`, `cancelled`.
        schema:
          type: string
          enum:
          - in_progress
          - completed
          - failed
          - cancelled
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ListVectorStoreFilesResponse'
      security:
      - Portkey-Key: []
        Virtual-Key: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
      - Portkey-Key: []
        Config: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
        Custom-Host: []
      x-code-samples:
      - lang: curl
        source: "curl https://api.portkey.ai/v1/vector_stores/vs_abc123/files \\\n  -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n  -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\"\n"
      - lang: python
        source: "from portkey_ai import Portkey\n\nclient = Portkey(\n  api_key = \"PORTKEY_API_KEY\",\n  virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\nvector_store_files = client.beta.vector_stores.files.list(\n  vector_store_id=\"vs_abc123\"\n)\nprint(vector_store_files)\n"
      - lang: javascript
        source: "import Portkey from 'portkey-ai';\n\nconst client = new Portkey({\n  apiKey: 'PORTKEY_API_KEY',\n  virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n  const vectorStoreFiles = await client.beta.vectorStores.files.list(\n    \"vs_abc123\"\n  );\n  console.log(vectorStoreFiles);\n}\n\nmain();\n"
        response: "{\n  \"object\": \"list\",\n  \"data\": [\n    {\n      \"id\": \"file-abc123\",\n      \"object\": \"vector_store.file\",\n      \"created_at\": 1699061776,\n      \"vector_store_id\": \"vs_abc123\"\n    },\n    {\n      \"id\": \"file-abc456\",\n      \"object\": \"vector_store.file\",\n      \"created_at\": 1699061776,\n      \"vector_store_id\": \"vs_abc123\"\n    }\n  ],\n  \"first_id\": \"file-abc123\",\n  \"last_id\": \"file-abc456\",\n  \"has_more\": false\n}\n"
    post:
      operationId: createVectorStoreFile
      tags:
      - Vector Stores
      summary: Create a vector store file by attaching a [File](https://platform.openai.com/docs/api-reference/files) to a [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object).
      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.

          '
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateVectorStoreFileRequest'
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreFileObject'
      security:
      - Portkey-Key: []
        Virtual-Key: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
      - Portkey-Key: []
        Config: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
        Custom-Host: []
      x-code-samples:
      - lang: curl
        source: "curl https://api.portkey.ai/v1/vector_stores/vs_abc123/files \\\n  -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n  -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\" \\\n  -d '{\n    \"file_id\": \"file-abc123\"\n  }'\n"
      - lang: python
        source: "from portkey_ai import Portkey\n\nclient = Portkey(\n  api_key = \"PORTKEY_API_KEY\",\n  virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\nvector_store_file = client.beta.vector_stores.files.create(\n  vector_store_id=\"vs_abc123\",\n  file_id=\"file-abc123\"\n)\nprint(vector_store_file)\n"
      - lang: javascript
        source: "import Portkey from 'portkey-ai';\n\nconst client = new Portkey({\n  apiKey: 'PORTKEY_API_KEY',\n  virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n  const myVectorStoreFile = await client.beta.vectorStores.files.create(\n    \"vs_abc123\",\n    {\n      file_id: \"file-abc123\"\n    }\n  );\n  console.log(myVectorStoreFile);\n}\n\nmain();\n"
        response: "{\n  \"id\": \"file-abc123\",\n  \"object\": \"vector_store.file\",\n  \"created_at\": 1699061776,\n  \"usage_bytes\": 1234,\n  \"vector_store_id\": \"vs_abcd\",\n  \"status\": \"completed\",\n  \"last_error\": null\n}\n"
  /vector_stores/{vector_store_id}/files/{file_id}:
    get:
      operationId: getVectorStoreFile
      tags:
      - Vector Stores
      summary: Retrieves a vector store file.
      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 belongs to.
      - in: path
        name: file_id
        required: true
        schema:
          type: string
          example: file-abc123
        description: The ID of the file being retrieved.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/VectorStoreFileObject'
      security:
      - Portkey-Key: []
        Virtual-Key: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
      - Portkey-Key: []
        Config: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
        Custom-Host: []
      x-code-samples:
      - lang: curl
        source: "curl https://api.portkey.ai/v1/vector_stores/vs_abc123/files/file-abc123 \\\n  -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n  -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\"\n"
      - lang: python
        source: "from portkey_ai import Portkey\n\nclient = Portkey(\n  api_key = \"PORTKEY_API_KEY\",\n  virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\nvector_store_file = client.beta.vector_stores.files.retrieve(\n  vector_store_id=\"vs_abc123\",\n  file_id=\"file-abc123\"\n)\nprint(vector_store_file)\n"
      - lang: javascript
        source: "import Portkey from 'portkey-ai';\n\nconst client = new Portkey({\n  apiKey: 'PORTKEY_API_KEY',\n  virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n  const vectorStoreFile = await client.beta.vectorStores.files.retrieve(\n    \"vs_abc123\",\n    \"file-abc123\"\n  );\n  console.log(vectorStoreFile);\n}\n\nmain();\n"
        response: "{\n  \"id\": \"file-abc123\",\n  \"object\": \"vector_store.file\",\n  \"created_at\": 1699061776,\n  \"vector_store_id\": \"vs_abcd\",\n  \"status\": \"completed\",\n  \"last_error\": null\n}\n"
    delete:
      operationId: deleteVectorStoreFile
      tags:
      - Vector Stores
      summary: Delete a vector store file. This will remove the file from the vector store but the file itself will not be deleted. To delete the file, use the [delete file](https://platform.openai.com/docs/api-reference/files/delete) endpoint.
      parameters:
      - in: path
        name: vector_store_id
        required: true
        schema:
          type: string
        description: The ID of the vector store that the file belongs to.
      - in: path
        name: file_id
        required: true
        schema:
          type: string
        description: The ID of the file to delete.
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/DeleteVectorStoreFileResponse'
      security:
      - Portkey-Key: []
        Virtual-Key: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
      - Portkey-Key: []
        Config: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
        Custom-Host: []
      x-code-samples:
      - lang: curl
        source: "curl https://api.portkey.ai/v1/vector_stores/vs_abc123/files/file-abc123 \\\n  -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n  -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\" \\\n  -X DELETE\n"
      - lang: python
        source: "from portkey_ai import Portkey\n\nclient = Portkey(\n  api_key = \"PORTKEY_API_KEY\",\n  virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\ndeleted_vector_store_file = client.beta.vector_stores.files.delete(\n    vector_store_id=\"vs_abc123\",\n    file_id=\"file-abc123\"\n)\nprint(deleted_vector_store_file)\n"
      - lang: javascript
        source: "import Portkey from 'portkey-ai';\n\nconst client = new Portkey({\n  apiKey: 'PORTKEY_API_KEY',\n  virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n  const deletedVectorStoreFile = await client.beta.vectorStores.files.del(\n    \"vs_abc123\",\n    \"file-abc123\"\n  );\n  console.log(deletedVectorStoreFile);\n}\n\nmain();\n"
        response: "{\n  \"id\": \"file-abc123\",\n  \"object\": \"vector_store.file.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.
      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'
      security:
      - Portkey-Key: []
        Virtual-Key: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
      - Portkey-Key: []
        Config: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
        Custom-Host: []
      x-code-samples:
      - lang: curl
        source: "curl https://api.portkey.ai/v1/vector_stores/vs_abc123/file_batches \\\n  -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n  -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n  -H \"Content-Type: application/json \\\n  -H \"OpenAI-Beta: assistants=v2\" \\\n  -d '{\n    \"file_ids\": [\"file-abc123\", \"file-abc456\"]\n  }'\n"
      - lang: python
        source: "from portkey_ai import Portkey\n\nclient = Portkey(\n  api_key = \"PORTKEY_API_KEY\",\n  virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\nvector_store_file_batch = client.beta.vector_stores.file_batches.create(\n  vector_store_id=\"vs_abc123\",\n  file_ids=[\"file-abc123\", \"file-abc456\"]\n)\nprint(vector_store_file_batch)\n"
      - lang: javascript
        source: "import Portkey from 'portkey-ai';\n\nconst client = new Portkey({\n  apiKey: 'PORTKEY_API_KEY',\n  virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n  const myVectorStoreFileBatch = await client.beta.vectorStores.fileBatches.create(\n    \"vs_abc123\",\n    {\n      file_ids: [\"file-abc123\", \"file-abc456\"]\n    }\n  );\n  console.log(myVectorStoreFileBatch);\n}\n\nmain();\n"
        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'
      security:
      - Portkey-Key: []
        Virtual-Key: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
      - Portkey-Key: []
        Config: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
        Custom-Host: []
      x-code-samples:
      - lang: curl
        source: "curl https://api.portkey.ai/v1/vector_stores/vs_abc123/files_batches/vsfb_abc123 \\\n  -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n  -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\"\n"
      - lang: python
        source: "from portkey_ai import Portkey\n\nclient = Portkey(\n  api_key = \"PORTKEY_API_KEY\",\n  virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\nvector_store_file_batch = client.beta.vector_stores.file_batches.retrieve(\n  vector_store_id=\"vs_abc123\",\n  batch_id=\"vsfb_abc123\"\n)\nprint(vector_store_file_batch)\n"
      - lang: javascript
        source: "import Portkey from 'portkey-ai';\n\nconst client = new Portkey({\n  apiKey: 'PORTKEY_API_KEY',\n  virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n  const vectorStoreFileBatch = await client.beta.vectorStores.fileBatches.retrieve(\n    \"vs_abc123\",\n    \"vsfb_abc123\"\n  );\n  console.log(vectorStoreFileBatch);\n}\n\nmain();\n"
        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'
      security:
      - Portkey-Key: []
        Virtual-Key: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
      - Portkey-Key: []
        Config: []
      - Portkey-Key: []
        Provider-Auth: []
        Provider-Name: []
        Custom-Host: []
      x-code-samples:
      - lang: curl
        source: "curl https://api.portkey.ai/v1/vector_stores/vs_abc123/files_batches/vsfb_abc123/cancel \\\n  -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n  -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n  -H \"Content-Type: application/json\" \\\n  -H \"OpenAI-Beta: assistants=v2\" \\\n  -X POST\n"
      - lang: python
        source: "from portkey_ai import Portkey\n\nclient = Portkey(\n  api_key = \"PORTKEY_API_KEY\",\n  virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\ndeleted_vector_store_file_batch = client.beta.vector_stores.file_batches.cancel(\n    vector_store_id=\"vs_abc123\",\n    file_batch_id=\"vsfb_abc123\"\n)\nprint(deleted_vector_store_file_batch)\n"
      - lang: javascript
        source: "import Portkey from 'portkey-ai';\n\nconst client = new Portkey({\n  apiKey: 'PORTKEY_API_KEY',\n  virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n  const deletedVectorStoreFileBatch = await client.vector_stores.fileBatches.cancel(\n    \"vs_abc123\",\n    \"vsfb_abc123\"\n  );\n  console.log(deletedVectorStoreFileBatch);\n}\n\nmain();\n"
        response: "{\n  \"id\": \"vsfb_abc123\",\n  \"object\": \"vector_store.file_batch\",\n  \"created_at\": 1699061776,\n  \"vector_store_id\": \"vs_abc123\",\n  \"status\": \"cancelling\",\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 ob

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