Every API here is available over the APIs.io API and to AI agents over MCP.
openapi: 3.0.0
info:
title: Portkey Analytics > Graphs Completions 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: Completions
description: Given a prompt, the model will return one or more predicted completions, and can also return the probabilities of alternative tokens at each position.
paths:
/completions:
servers:
- url: https://api.portkey.ai/v1
description: Portkey API Public Endpoint
- url: SELF_HOSTED_GATEWAY_URL
description: Self-Hosted Gateway URL
post:
operationId: createCompletion
tags:
- Completions
summary: Completions
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CreateCompletionRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/CreateCompletionResponse'
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
label: Default
source: "curl https://api.portkey.ai/v1/completions \\\n -H \"Content-Type: application/json\" \\\n -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n -d '{\n \"model\": \"gpt-3.5-turbo-instruct\",\n \"prompt\": \"Say this is a test\",\n \"max_tokens\": 7,\n \"temperature\": 0\n }'\n"
- lang: python
label: Default
source: "from portkey_ai import Portkey\n\nportkey = Portkey(\n api_key = \"PORTKEY_API_KEY\",\n virtual_key = \"PROVIDER_VIRTUAL_KEY\"\n)\n\nresponse = portkey.completions.create(\n model=\"gpt-3.5-turbo-instruct\",\n prompt=\"Say this is a test\",\n max_tokens=7,\n temperature=0\n)\n\nprint(response)\n"
- lang: javascript
label: Default
source: "import Portkey from 'portkey-ai';\n\nconst portkey = new Portkey({\n apiKey: 'PORTKEY_API_KEY',\n virtualKey: 'PROVIDER_VIRTUAL_KEY'\n});\n\nasync function main() {\n const response = await portkey.completions.create({\n model: \"gpt-3.5-turbo-instruct\",\n prompt: \"Say this is a test.\",\n max_tokens: 7,\n temperature: 0,\n });\n\n console.log(response);\n}\n\nmain();\n"
- lang: javascript
label: Self-Hosted
source: "import Portkey from 'portkey-ai';\n\nconst portkey = new Portkey({\n apiKey: 'PORTKEY_API_KEY',\n virtualKey: 'PROVIDER_VIRTUAL_KEY',\n baseUrl: 'SELF_HOSTED_GATEWAY_URL'\n});\n\nasync function main() {\n const response = await client.completions.create({\n model: \"gpt-3.5-turbo-instruct\",\n prompt: \"Say this is a test.\",\n max_tokens: 7,\n temperature: 0,\n });\n\n console.log(response);\n}\n\nmain();\n"
- lang: python
label: Self-Hosted
source: "from portkey_ai import Portkey\n\nportkey = Portkey(\n api_key = \"PORTKEY_API_KEY\",\n virtual_key = \"PROVIDER_VIRTUAL_KEY\",\n base_url = \"SELF_HOSTED_GATEWAY_URL\"\n)\n\nresponse = portkey.completions.create(\n model=\"gpt-3.5-turbo-instruct\",\n prompt=\"Say this is a test\",\n max_tokens=7,\n temperature=0\n)\n\nprint(response)\n"
- lang: curl
label: Self-Hosted
source: "curl https://SELF_HOSTED_GATEWAY_URL/completions \\\n -H \"Content-Type: application/json\" \\\n -H \"x-portkey-api-key: $PORTKEY_API_KEY\" \\\n -H \"x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY\" \\\n -d '{\n \"model\": \"gpt-3.5-turbo-instruct\",\n \"prompt\": \"Say this is a test\",\n \"max_tokens\": 7,\n \"temperature\": 0\n }'\n"
components:
schemas:
CompletionUsage:
type: object
description: Usage statistics for the completion request.
properties:
completion_tokens:
type: integer
description: Number of tokens in the generated completion.
prompt_tokens:
type: integer
description: Number of tokens in the prompt.
total_tokens:
type: integer
description: Total number of tokens used in the request (prompt + completion).
completion_tokens_details:
type: object
nullable: true
description: Breakdown of tokens used in a completion.
properties:
reasoning_tokens:
type: integer
description: Tokens generated by the model for reasoning.
accepted_prediction_tokens:
type: integer
description: When using Predicted Outputs, the number of tokens in the prediction that appeared in the completion.
rejected_prediction_tokens:
type: integer
description: When using Predicted Outputs, the number of tokens in the prediction that did not appear in the completion.
prompt_tokens_details:
type: object
nullable: true
description: Breakdown of tokens used in the prompt.
properties:
cached_tokens:
type: integer
description: Cached tokens present in the prompt.
required:
- prompt_tokens
- completion_tokens
- total_tokens
CreateCompletionRequest:
type: object
properties:
model:
description: 'ID of the model to use. You can use the [List models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](https://platform.openai.com/docs/models/overview) for descriptions of them.
'
anyOf:
- type: string
- type: string
enum:
- gpt-3.5-turbo-instruct
- davinci-002
- babbage-002
x-oaiTypeLabel: string
prompt:
description: 'The prompt(s) to generate completions for, encoded as a string, array of strings, array of tokens, or array of token arrays.
Note that <|endoftext|> is the document separator that the model sees during training, so if a prompt is not specified the model will generate as if from the beginning of a new document.
'
default: <|endoftext|>
nullable: true
oneOf:
- type: string
default: ''
example: This is a test.
- type: array
items:
type: string
default: ''
example: This is a test.
- type: array
minItems: 1
items:
type: integer
example: '[1212, 318, 257, 1332, 13]'
- type: array
minItems: 1
items:
type: array
minItems: 1
items:
type: integer
example: '[[1212, 318, 257, 1332, 13]]'
best_of:
type: integer
default: 1
minimum: 0
maximum: 20
nullable: true
description: 'Generates `best_of` completions server-side and returns the "best" (the one with the highest log probability per token). Results cannot be streamed.
When used with `n`, `best_of` controls the number of candidate completions and `n` specifies how many to return – `best_of` must be greater than `n`.
**Note:** Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`.
'
echo:
type: boolean
default: false
nullable: true
description: 'Echo back the prompt in addition to the completion
'
frequency_penalty:
type: number
default: 0
minimum: -2
maximum: 2
nullable: true
description: 'Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model''s likelihood to repeat the same line verbatim.
[See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation/parameter-details)
'
logit_bias:
type: object
x-oaiTypeLabel: map
default: null
nullable: true
additionalProperties:
type: integer
description: 'Modify the likelihood of specified tokens appearing in the completion.
Accepts a JSON object that maps tokens (specified by their token ID in the GPT tokenizer) to an associated bias value from -100 to 100. You can use this [tokenizer tool](https://platform.openai.com/tokenizer?view=bpe) to convert text to token IDs. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.
As an example, you can pass `{"50256": -100}` to prevent the <|endoftext|> token from being generated.
'
logprobs:
type: integer
minimum: 0
maximum: 5
default: null
nullable: true
description: 'Include the log probabilities on the `logprobs` most likely output tokens, as well the chosen tokens. For example, if `logprobs` is 5, the API will return a list of the 5 most likely tokens. The API will always return the `logprob` of the sampled token, so there may be up to `logprobs+1` elements in the response.
The maximum value for `logprobs` is 5.
'
max_tokens:
type: integer
minimum: 0
default: 16
example: 16
nullable: true
description: 'The maximum number of [tokens](https://platform.openai.com/tokenizer?view=bpe) that can be generated in the completion.
The token count of your prompt plus `max_tokens` cannot exceed the model''s context length. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.
'
n:
type: integer
minimum: 1
maximum: 128
default: 1
example: 1
nullable: true
description: 'How many completions to generate for each prompt.
**Note:** Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`.
'
presence_penalty:
type: number
default: 0
minimum: -2
maximum: 2
nullable: true
description: 'Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model''s likelihood to talk about new topics.
[See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation/parameter-details)
'
seed:
type: integer
minimum: -9223372036854775808
maximum: 9223372036854775807
nullable: true
description: 'If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same `seed` and parameters should return the same result.
Determinism is not guaranteed, and you should refer to the `system_fingerprint` response parameter to monitor changes in the backend.
'
stop:
description: 'Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.
'
default: null
nullable: true
oneOf:
- type: string
default: <|endoftext|>
example: '
'
nullable: true
- type: array
minItems: 1
maxItems: 4
items:
type: string
example: '["\n"]'
stream:
description: 'Whether to stream back partial progress. If set, tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-UShttps://platform.openai.com/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by a `data: [DONE]` message. [Example Python code](https://cookbook.openai.com/examples/how_to_stream_completions).
'
type: boolean
nullable: true
default: false
stream_options:
$ref: '#/components/schemas/ChatCompletionStreamOptions'
suffix:
description: 'The suffix that comes after a completion of inserted text.
This parameter is only supported for `gpt-3.5-turbo-instruct`.
'
default: null
nullable: true
type: string
example: test.
temperature:
type: number
minimum: 0
maximum: 2
default: 1
example: 1
nullable: true
description: 'What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.
We generally recommend altering this or `top_p` but not both.
'
top_p:
type: number
minimum: 0
maximum: 1
default: 1
example: 1
nullable: true
description: 'An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.
We generally recommend altering this or `temperature` but not both.
'
user:
type: string
example: user-1234
description: 'A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids).
'
required:
- model
- prompt
ChatCompletionStreamOptions:
description: 'Options for streaming response. Only set this when you set `stream: true`.
'
type: object
nullable: true
default: null
properties:
include_usage:
type: boolean
description: 'If set, an additional chunk will be streamed before the `data: [DONE]` message. The `usage` field on this chunk shows the token usage statistics for the entire request, and the `choices` field will always be an empty array. All other chunks will also include a `usage` field, but with a null value.
'
CreateCompletionResponse:
type: object
description: 'Represents a completion response from the API. Note: both the streamed and non-streamed response objects share the same shape (unlike the chat endpoint).
'
properties:
id:
type: string
description: A unique identifier for the completion.
choices:
type: array
description: The list of completion choices the model generated for the input prompt.
items:
type: object
required:
- finish_reason
- index
- logprobs
- text
properties:
finish_reason:
type: string
description: 'The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence,
`length` if the maximum number of tokens specified in the request was reached,
or `content_filter` if content was omitted due to a flag from our content filters.
'
enum:
- stop
- length
- content_filter
index:
type: integer
logprobs:
type: object
nullable: true
properties:
text_offset:
type: array
items:
type: integer
token_logprobs:
type: array
items:
type: number
tokens:
type: array
items:
type: string
top_logprobs:
type: array
items:
type: object
additionalProperties:
type: number
text:
type: string
created:
type: integer
description: The Unix timestamp (in seconds) of when the completion was created.
model:
type: string
description: The model used for completion.
system_fingerprint:
type: string
description: 'This fingerprint represents the backend configuration that the model runs with.
Can be used in conjunction with the `seed` request parameter to understand when backend changes have been made that might impact determinism.
'
object:
type: string
description: The object type, which is always "text_completion"
enum:
- text_completion
usage:
$ref: '#/components/schemas/CompletionUsage'
required:
- id
- object
- created
- model
- choices
x-code-samples:
name: The completion object
legacy: true
example: "{\n \"id\": \"cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7\",\n \"object\": \"text_completion\",\n \"created\": 1589478378,\n \"model\": \"gpt-4-turbo\",\n \"choices\": [\n {\n \"text\": \"\\n\\nThis is indeed a test\",\n \"index\": 0,\n \"logprobs\": null,\n \"finish_reason\": \"length\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 5,\n \"completion_tokens\": 7,\n \"total_tokens\": 12\n }\n}\n"
securitySchemes:
Portkey-Key:
type: apiKey
in: header
name: x-portkey-api-key
Virtual-Key:
type: apiKey
in: header
name: x-portkey-virtual-key
Provider-Auth:
type: http
scheme: bearer
Provider-Name:
type: apiKey
in: header
name: x-portkey-provider
Config:
type: apiKey
in: header
name: x-portkey-config
Custom-Host:
type: apiKey
in: header
name: x-portkey-custom-host
x-server-groups:
ControlPlaneServers:
- url: https://api.portkey.ai/v1
description: Portkey API Public Endpoint
- url: SELF_HOSTED_CONTROL_PLANE_URL
description: Self-Hosted Control Plane URL
DataPlaneServers:
- url: https://api.portkey.ai/v1
description: Portkey API Public Endpoint
- url: SELF_HOSTED_GATEWAY_URL
description: Self-Hosted Gateway URL
PublicServers:
- url: https://api.portkey.ai
description: Portkey Public API (no auth required)
x-mint:
mcp:
enabled: true
name: Portkey MCP
description: Official MCP Server for Portkey Docs & APIs
x-code-samples:
navigationGroups:
- id: endpoints
title: Endpoints
- id: assistants
title: Assistants
- id: legacy
title: Legacy
groups:
- id: audio
title: Audio
description: 'Learn how to turn audio into text or text into audio.
Related guide: [Speech to text](https://platform.openai.com/docs/guides/speech-to-text)
'
navigationGroup: endpoints
sections:
- type: endpoint
key: createSpeech
path: createSpeech
- type: endpoint
key: createTranscription
path: createTranscription
- type: endpoint
key: createTranslation
path: createTranslation
- type: object
key: CreateTranscriptionResponseJson
path: json-object
- type: object
key: CreateTranscriptionResponseVerboseJson
path: verbose-json-object
- id: chat
title: Chat
description: 'Given a list of messages comprising a conversation, the model will return a response.
Related guide: [Chat Completions](https://platform.openai.com/docs/guides/text-generation)
'
navigationGroup: endpoints
sections:
- type: endpoint
key: createChatCompletion
path: create
- type: object
key: CreateChatCompletionResponse
path: object
- type: object
key: CreateChatCompletionStreamResponse
path: streaming
- id: realtime
title: Realtime
description: 'WebSocket proxy for provider Realtime APIs (`GET` upgrade). Use `wss://` with the same `/v1` data-plane base as other gateway routes.
Related guide: [OpenAI Realtime API](https://platform.openai.com/docs/guides/realtime)
'
navigationGroup: endpoints
sections:
- type: endpoint
key: connectRealtime
path: connect
- id: embeddings
title: Embeddings
description: 'Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms.
Related guide: [Embeddings](https://platform.openai.com/docs/guides/embeddings)
'
navigationGroup: endpoints
sections:
- type: endpoint
key: createEmbedding
path: create
- type: object
key: Embedding
path: object
- id: rerank
title: Rerank
description: 'Rerank a list of documents based on their relevance to a query. Reranking improves search results by scoring documents based on semantic relevance rather than keyword matching.
Supported providers: Cohere, Voyage, Jina, Pinecone, Bedrock, Azure AI.
'
navigationGroup: endpoints
sections:
- type: endpoint
key: createRerank
path: create
- type: object
key: CreateRerankResponse
path: object
- id: fine-tuning
title: Fine-tuning
description: 'Manage fine-tuning jobs to tailor a model to your specific training data.
Related guide: [Fine-tune models](https://platform.openai.com/docs/guides/fine-tuning)
'
navigationGroup: endpoints
sections:
- type: endpoint
key: createFineTuningJob
path: create
- type: endpoint
key: listPaginatedFineTuningJobs
path: list
- type: endpoint
key: listFineTuningEvents
path: list-events
- type: endpoint
key: listFineTuningJobCheckpoints
path: list-checkpoints
- type: endpoint
key: retrieveFineTuningJob
path: retrieve
- type: endpoint
key: cancelFineTuningJob
path: cancel
- type: object
key: FinetuneChatRequestInput
path: chat-input
- type: object
key: FinetuneCompletionRequestInput
path: completions-input
- type: object
key: FineTuningJob
path: object
- type: object
key: FineTuningJobEvent
path: event-object
- type: object
key: FineTuningJobCheckpoint
path: checkpoint-object
- id: batch
title: Batch
description: 'Create large batches of API requests for asynchronous processing. The Batch API returns completions within 24 hours for a 50% discount.
Related guide: [Batch](https://platform.openai.com/docs/guides/batch)
'
navigationGroup: endpoints
sections:
- type: endpoint
key: createBatch
path: create
- type: endpoint
key: retrieveBatch
path: retrieve
- type: endpoint
key: cancelBatch
path: cancel
- type: endpoint
key: listBatches
path: list
- type: object
key: Batch
path: object
- type: object
key: BatchRequestInput
path: request-input
- type: object
key: BatchRequestOutput
path: request-output
- id: files
title: Files
description: 'Files are used to upload documents that can be used with features like [Assistants](https://platform.openai.com/docs/api-reference/assistants), [Fine-tuning](https://platform.openai.com/docs/api-reference/fine-tuning), and [Batch API](https://platform.openai.com/docs/guides/batch).
'
navigationGroup: endpoints
sections:
- type: endpoint
key: createFile
path: create
- type: endpoint
key: listFiles
path: list
- type: endpoint
key: retrieveFile
path: retrieve
- type: endpoint
key: deleteFile
path: delete
- type: endpoint
key: downloadFile
path: retrieve-contents
- type: object
key: OpenAIFile
path: object
- id: images
title: Images
description: 'Given a prompt and/or an input image, the model will generate a new image.
Related guide: [Image generation](https://platform.openai.com/docs/guides/images)
'
navigationGroup: endpoints
sections:
- type: endpoint
key: createImage
path: create
- type: endpoint
key: createImageEdit
path: createEdit
- type: endpoint
key: createImageVariation
path: createVariation
- type: object
key: Image
path: object
- id: models
title: Models
description: 'List and describe the various models available in the API. You can refer to the [Models](https://platform.openai.com/docs/models) documentation to understand what models are available and the differences between them.
'
navigationGroup: endpoints
sections:
- type: endpoint
key: listModels
path: list
- type: endpoint
key: retrieveModel
path: retrieve
- type: endpoint
key: deleteModel
path: delete
- type: object
key: Model
path: object
- id: moderations
title: Moderations
description: 'Given some input text, outputs if the model classifies it as potentially harmful across several categories.
Related guide: [Moderations](https://platform.openai.com/docs/guides/moderation)
'
navigationGroup: endpoints
sections:
- type: endpoint
key: createModeration
path: create
- type: object
key: CreateModerationResponse
path: object
- id: assistants
title: Assistants
beta: true
description: 'Build assistants that can call models and use tools to perform tasks.
[Get started with the Assistants API](https://platform.openai.com/docs/assistants)
'
navigationGroup: assistants
sections:
- type: endpoint
key: createAssistant
path: createAssistant
- type: endpoint
key: listAssistants
path: listAssistants
- type: endpoint
key: getAssistant
path: getAssistant
- type: endpoint
key: modifyAssistant
path: modifyAssistant
- type: endpoint
key: deleteAssistant
path: deleteAssistant
- type: object
key: AssistantObject
path: object
- id: threads
title: Threads
beta: true
description: 'Create threads that assistants can interact with.
Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview)
'
navigationGroup: assistants
sections:
- type: endpoint
key: createThread
path: createThread
- type: endpoint
key: getThread
path: getThread
- type: endpoint
key: modifyThread
path: modifyThread
- type: endpoint
key: deleteThread
path: deleteThread
- type: object
key: ThreadObject
path: object
- id: messages
title: Messages
beta: true
description: 'Create messages within threads
Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview)
'
navigationGroup: assistants
sections:
- type: endpoint
key: createMessage
path: createMessage
- type: endpoint
key: listMessages
path: listMessages
- type: endpoint
key: getMessage
path: getMessage
- type: endpoint
key: modifyMessage
path: modifyMessage
- type: endpoint
key: deleteMessage
path: deleteMessage
- type: object
key: MessageObject
path: object
- id: runs
title: Runs
beta: true
description: 'Represents an execution run on a thread.
Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview)
'
navigationGroup: assistants
sections:
- type: endpoint
key: createRun
path: createRun
- type: endpoint
key: createThreadAndRun
path: createThreadAndRun
- type: endpoint
key: listRuns
path: listRuns
- type: endpoint
key: getRun
path: getRun
- type: endpoint
key: modifyRun
path: modifyRun
- type: endpoint
key: submitToolOuputsToRun
path: submitToolOutputs
- type: endpoint
key: cancelRun
path: cancelRun
- type: object
key: RunObject
path: object
- id: run-steps
title: Run Steps
beta: true
description: 'Represents the steps (model and tool calls) taken during the run.
Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview)
'
navigationGroup: assistants
sections:
- type: endpoint
key: listRunSteps
path: listRunSteps
- type: endpoint
key: getRunStep
path: getRunStep
- type: object
key: RunStepObject
path: step-object
- id: vector-stores
title: Vector Stores
beta: true
description: 'Vector stores are used to store files for use by the `file_search` tool.
Related guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search)
'
navigationGroup: assistants
sections:
- type: endpoint
key: createVectorStore
path: create
- type: endpoint
key: listVectorStores
path: list
- type: endpoint
key: getVectorStore
path: retrieve
- type: endpoint
key: modifyVectorStore
path: modify
- type: endpoint
key: deleteVectorStore
path: delete
- type: object
key: VectorStoreObject
path: object
- id: vector-stores-files
title: Vector Store Files
beta: true
description: 'Vector store files represent files inside a vector store.
Related guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search)
'
navigationGroup: assistants
sections:
- type: endpoint
key: createVectorStoreFile
path: createFile
- type: endpoint
key: listVectorStoreFiles
path: listFiles
- type: endpoint
key: getVectorStoreFile
path: getFile
- type: endpoint
key: deleteVectorStoreFile
path: deleteFile
- type: object
key: VectorStoreFileObject
path: file-object
- id: vector-stores-file-batches
title: Vector Store File Batches
beta: true
description: 'Vector store file batches represent operations to add multiple files to a vector store.
Related guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search)
'
navigationGroup: assistants
sections:
- type: endpoint
key: createVectorStoreFileBatch
path: createBatch
- type: endpoint
key: getVectorStoreFileBatch
path: getBatch
- type: endpoint
key: cancelVectorStoreFileBatch
path: cancelBatch
- type: endpoint
key: listFilesInVectorStoreBatch
path: listBatchFiles
- type: object
key: VectorStoreFileBatchObject
path: batch-object
- id: assistants-streaming
title: Streaming
beta: true
description: 'Stream the result of executing a Run or resuming a Run after submitting tool outputs.
You can stream events from the [Create Thread and Run](https://platform.o
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# Full source: https://raw.githubusercontent.com/api-evangelist/portkey/refs/heads/main/openapi/portkey-completions-api-openapi.yml