API Reference

Beta

Assistants

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Create assistant

Deprecated

beta.assistants.create(**kwargs) -> Assistant { id, created_at, description, 10 more }

POST/assistants

Create assistant

ParametersExpand Collapse

model: String | ChatModel

ID of the model to use. You can use the List models API to see all of your available models, or see our Model overview for descriptions of them.

One of the following:

String = String

ChatModel = :"gpt-5.6-sol" | :"gpt-5.6-terra" | :"gpt-5.6-luna" | 78 more

One of the following:

:"gpt-5.6-sol"

:"gpt-5.6-terra"

:"gpt-5.6-luna"

:"gpt-5.4"

:"gpt-5.4-mini"

:"gpt-5.4-nano"

:"gpt-5.4-mini-2026-03-17"

:"gpt-5.4-nano-2026-03-17"

:"gpt-5.3-chat-latest"

:"gpt-5.2"

:"gpt-5.2-2025-12-11"

:"gpt-5.2-chat-latest"

:"gpt-5.2-pro"

:"gpt-5.2-pro-2025-12-11"

:"gpt-5.1"

:"gpt-5.1-2025-11-13"

:"gpt-5.1-codex"

:"gpt-5.1-mini"

:"gpt-5.1-chat-latest"

:"gpt-5"

:"gpt-5-mini"

:"gpt-5-nano"

:"gpt-5-2025-08-07"

:"gpt-5-mini-2025-08-07"

:"gpt-5-nano-2025-08-07"

:"gpt-5-chat-latest"

:"gpt-4.1"

:"gpt-4.1-mini"

:"gpt-4.1-nano"

:"gpt-4.1-2025-04-14"

:"gpt-4.1-mini-2025-04-14"

:"gpt-4.1-nano-2025-04-14"

:"o4-mini"

:"o4-mini-2025-04-16"

:o3

:"o3-2025-04-16"

:"o3-mini"

:"o3-mini-2025-01-31"

:o1

:"o1-2024-12-17"

:"o1-preview"

:"o1-preview-2024-09-12"

:"o1-mini"

:"o1-mini-2024-09-12"

:"gpt-4o"

:"gpt-4o-2024-11-20"

:"gpt-4o-2024-08-06"

:"gpt-4o-2024-05-13"

:"gpt-4o-audio-preview"

:"gpt-4o-audio-preview-2024-10-01"

:"gpt-4o-audio-preview-2024-12-17"

:"gpt-4o-audio-preview-2025-06-03"

:"gpt-4o-mini-audio-preview"

:"gpt-4o-mini-audio-preview-2024-12-17"

:"gpt-4o-search-preview"

:"gpt-4o-mini-search-preview"

:"gpt-4o-search-preview-2025-03-11"

:"gpt-4o-mini-search-preview-2025-03-11"

:"chatgpt-4o-latest"

:"codex-mini-latest"

:"gpt-4o-mini"

:"gpt-4o-mini-2024-07-18"

:"gpt-4-turbo"

:"gpt-4-turbo-2024-04-09"

:"gpt-4-0125-preview"

:"gpt-4-turbo-preview"

:"gpt-4-1106-preview"

:"gpt-4-vision-preview"

:"gpt-4"

:"gpt-4-0314"

:"gpt-4-0613"

:"gpt-4-32k"

:"gpt-4-32k-0314"

:"gpt-4-32k-0613"

:"gpt-3.5-turbo"

:"gpt-3.5-turbo-16k"

:"gpt-3.5-turbo-0301"

:"gpt-3.5-turbo-0613"

:"gpt-3.5-turbo-1106"

:"gpt-3.5-turbo-0125"

:"gpt-3.5-turbo-16k-0613"

description: String

The description of the assistant. The maximum length is 512 characters.

maxLength512

instructions: String

The system instructions that the assistant uses. The maximum length is 256,000 characters.

maxLength256000

metadata: Metadata

Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

name: String

The name of the assistant. The maximum length is 256 characters.

maxLength256

reasoning_effort: ReasoningEffort

Constrains effort on reasoning for reasoning models. Currently supported values are none, minimal, low, medium, high, xhigh, and max. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response. Not all reasoning models support every value. See the reasoning guide for model-specific support.

One of the following:

:none

:minimal

:low

:medium

:high

:xhigh

:max

response_format: AssistantResponseFormatOption

Specifies the format that the model must output. Compatible with GPT-4o, GPT-4 Turbo, and all GPT-3.5 Turbo models since gpt-3.5-turbo-1106.

Setting to { "type": "json_schema", "json_schema": {...} } enables Structured Outputs which ensures the model will match your supplied JSON schema. Learn more in the Structured Outputs guide.

Setting to { "type": "json_object" } enables JSON mode, which ensures the message the model generates is valid JSON.

Important: when using JSON mode, you must also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly “stuck” request. Also note that the message content may be partially cut off if finish_reason="length", which indicates the generation exceeded max_tokens or the conversation exceeded the max context length.

One of the following:

AssistantResponseFormatOption = :auto

auto is the default value

class ResponseFormatText { type }

Default response format. Used to generate text responses.

type: :text

The type of response format being defined. Always text.

class ResponseFormatJSONObject { type }

JSON object response format. An older method of generating JSON responses. Using json_schema is recommended for models that support it. Note that the model will not generate JSON without a system or user message instructing it to do so.

type: :json_object

The type of response format being defined. Always json_object.

class ResponseFormatJSONSchema { json_schema, type }

JSON Schema response format. Used to generate structured JSON responses. Learn more about Structured Outputs.

json_schema: JSONSchema{ name, description, schema, strict}

Structured Outputs configuration options, including a JSON Schema.

name: String

The name of the response format. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.

description: String

A description of what the response format is for, used by the model to determine how to respond in the format.

schema: Hash[Symbol, untyped]

The schema for the response format, described as a JSON Schema object. Learn how to build JSON schemas here.

strict: bool

Whether to enable strict schema adherence when generating the output. If set to true, the model will always follow the exact schema defined in the schema field. Only a subset of JSON Schema is supported when strict is true. To learn more, read the Structured Outputs guide.

type: :json_schema

The type of response format being defined. Always json_schema.

temperature: Float

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.

minimum0

maximum2

tool_resources: ToolResources{ code_interpreter, file_search}

A set of resources that are used by the assistant’s tools. The resources are specific to the type of tool. For example, the code_interpreter tool requires a list of file IDs, while the file_search tool requires a list of vector store IDs.

code_interpreter: CodeInterpreter{ file_ids}

file_ids: Array[String]

A list of file IDs made available to the code_interpreter tool. There can be a maximum of 20 files associated with the tool.

file_search: FileSearch{ vector_store_ids, vector_stores}

vector_store_ids: Array[String]

The vector store attached to this assistant. There can be a maximum of 1 vector store attached to the assistant.

vector_stores: Array[VectorStore{ chunking_strategy, file_ids, metadata}]

A helper to create a vector store with file_ids and attach it to this assistant. There can be a maximum of 1 vector store attached to the assistant.

chunking_strategy: Auto{ type} | Static{ static, type}

The chunking strategy used to chunk the file(s). If not set, will use the auto strategy.

One of the following:

class Auto { type }

The default strategy. This strategy currently uses a max_chunk_size_tokens of 800 and chunk_overlap_tokens of 400.

type: :auto

Always auto.

class Static { static, type }

static: Static{ chunk_overlap_tokens, max_chunk_size_tokens}

chunk_overlap_tokens: Integer

The number of tokens that overlap between chunks. The default value is 400.

Note that the overlap must not exceed half of max_chunk_size_tokens.

max_chunk_size_tokens: Integer

The maximum number of tokens in each chunk. The default value is 800. The minimum value is 100 and the maximum value is 4096.

minimum100

maximum4096

type: :static

Always static.

file_ids: Array[String]

A list of file IDs to add to the vector store. For vector stores created before Nov 2025, there can be a maximum of 10,000 files in a vector store. For vector stores created starting in Nov 2025, the limit is 100,000,000 files.

metadata: Metadata

Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

tools: Array[untyped]

A list of tool enabled on the assistant. There can be a maximum of 128 tools per assistant. Tools can be of types code_interpreter, file_search, or function.

top_p: Float

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.

minimum0

maximum1

ReturnsExpand Collapse

class Assistant { id, created_at, description, 10 more }

Represents an assistant that can call the model and use tools.

id: String

The identifier, which can be referenced in API endpoints.

created_at: Integer

The Unix timestamp (in seconds) for when the assistant was created.

formatunixtime

description: String

The description of the assistant. The maximum length is 512 characters.

maxLength512

instructions: String

The system instructions that the assistant uses. The maximum length is 256,000 characters.

maxLength256000

metadata: Metadata

Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

model: String

ID of the model to use. You can use the List models API to see all of your available models, or see our Model overview for descriptions of them.

name: String

The name of the assistant. The maximum length is 256 characters.

maxLength256

object: :assistant

The object type, which is always assistant.

tools: Array[untyped]

A list of tool enabled on the assistant. There can be a maximum of 128 tools per assistant. Tools can be of types code_interpreter, file_search, or function.

response_format: AssistantResponseFormatOption

Specifies the format that the model must output. Compatible with GPT-4o, GPT-4 Turbo, and all GPT-3.5 Turbo models since gpt-3.5-turbo-1106.

Setting to { "type": "json_schema", "json_schema": {...} } enables Structured Outputs which ensures the model will match your supplied JSON schema. Learn more in the Structured Outputs guide.

Setting to { "type": "json_object" } enables JSON mode, which ensures the message the model generates is valid JSON.

Important: when using JSON mode, you must also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly “stuck” request. Also note that the message content may be partially cut off if finish_reason="length", which indicates the generation exceeded max_tokens or the conversation exceeded the max context length.

One of the following:

AssistantResponseFormatOption = :auto

auto is the default value

class ResponseFormatText { type }

Default response format. Used to generate text responses.

type: :text

The type of response format being defined. Always text.

class ResponseFormatJSONObject { type }

JSON object response format. An older method of generating JSON responses. Using json_schema is recommended for models that support it. Note that the model will not generate JSON without a system or user message instructing it to do so.

type: :json_object

The type of response format being defined. Always json_object.

class ResponseFormatJSONSchema { json_schema, type }

JSON Schema response format. Used to generate structured JSON responses. Learn more about Structured Outputs.

json_schema: JSONSchema{ name, description, schema, strict}

Structured Outputs configuration options, including a JSON Schema.

name: String

The name of the response format. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.

description: String

A description of what the response format is for, used by the model to determine how to respond in the format.

schema: Hash[Symbol, untyped]

The schema for the response format, described as a JSON Schema object. Learn how to build JSON schemas here.

strict: bool

Whether to enable strict schema adherence when generating the output. If set to true, the model will always follow the exact schema defined in the schema field. Only a subset of JSON Schema is supported when strict is true. To learn more, read the Structured Outputs guide.

type: :json_schema

The type of response format being defined. Always json_schema.

temperature: Float

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.

minimum0

maximum2

tool_resources: ToolResources{ code_interpreter, file_search}

A set of resources that are used by the assistant’s tools. The resources are specific to the type of tool. For example, the code_interpreter tool requires a list of file IDs, while the file_search tool requires a list of vector store IDs.

code_interpreter: CodeInterpreter{ file_ids}

file_ids: Array[String]

A list of file IDs made available to the `code_interpreter“ tool. There can be a maximum of 20 files associated with the tool.

file_search: FileSearch{ vector_store_ids}

vector_store_ids: Array[String]

The ID of the vector store attached to this assistant. There can be a maximum of 1 vector store attached to the assistant.

top_p: Float

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.

minimum0

maximum1

Create assistant

Ruby

HTTP

TypeScript

Python

Java

Go

Ruby

CLI Tool

require "openai"

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

assistant = openai.beta.assistants.create(model: :"gpt-4o")

puts(assistant)

200 example

{
  "id": "id",
  "created_at": 0,
  "description": "description",
  "instructions": "instructions",
  "metadata": {
    "foo": "string"
  },
  "model": "model",
  "name": "name",
  "object": "assistant",
  "tools": [
    {}
  ],
  "response_format": "auto",
  "temperature": 1,
  "tool_resources": {
    "code_interpreter": {
      "file_ids": [
        "string"
      ]
    },
    "file_search": {
      "vector_store_ids": [
        "string"
      ]
    }
  },
  "top_p": 1
}

Returns Examples

200 example

{
  "id": "id",
  "created_at": 0,
  "description": "description",
  "instructions": "instructions",
  "metadata": {
    "foo": "string"
  },
  "model": "model",
  "name": "name",
  "object": "assistant",
  "tools": [
    {}
  ],
  "response_format": "auto",
  "temperature": 1,
  "tool_resources": {
    "code_interpreter": {
      "file_ids": [
        "string"
      ]
    },
    "file_search": {
      "vector_store_ids": [
        "string"
      ]
    }
  },
  "top_p": 1
}