Class BetaAssistantCreateParams
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- All Implemented Interfaces:
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com.openai.core.Params
public final class BetaAssistantCreateParams implements Params
Create an assistant with a model and instructions.
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Nested Class Summary
Nested Classes Modifier and Type Class Description public final class
BetaAssistantCreateParams.Body
public final class
BetaAssistantCreateParams.Builder
A builder for BetaAssistantCreateParams.
public final class
BetaAssistantCreateParams.ReasoningEffort
o1 and o3-mini models only
Constrains effort on reasoning for reasoning models. Currently supported values are
low
,medium
, andhigh
. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.public final class
BetaAssistantCreateParams.ToolResources
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 thefile_search
tool requires a list of vector store IDs.
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Method Summary
Modifier and Type Method Description final ChatModel
model()
ID of the model to use. final Optional<String>
description()
The description of the assistant. final Optional<String>
instructions()
The system instructions that the assistant uses. final Optional<Metadata>
metadata()
Set of 16 key-value pairs that can be attached to an object. final Optional<String>
name()
The name of the assistant. final Optional<BetaAssistantCreateParams.ReasoningEffort>
reasoningEffort()
o1 and o3-mini models onlyConstrains effort on reasoning for reasoning models. final Optional<AssistantResponseFormatOption>
responseFormat()
Specifies the format that the model must output. final Optional<Double>
temperature()
What sampling temperature to use, between 0 and 2. final Optional<BetaAssistantCreateParams.ToolResources>
toolResources()
A set of resources that are used by the assistant's tools. final Optional<List<AssistantTool>>
tools()
A list of tool enabled on the assistant. final Optional<Double>
topP()
An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. final JsonField<ChatModel>
_model()
ID of the model to use. final JsonField<String>
_description()
The description of the assistant. final JsonField<String>
_instructions()
The system instructions that the assistant uses. final JsonField<Metadata>
_metadata()
Set of 16 key-value pairs that can be attached to an object. final JsonField<String>
_name()
The name of the assistant. final JsonField<BetaAssistantCreateParams.ReasoningEffort>
_reasoningEffort()
o1 and o3-mini models onlyConstrains effort on reasoning for reasoning models. final JsonField<AssistantResponseFormatOption>
_responseFormat()
Specifies the format that the model must output. final JsonField<Double>
_temperature()
What sampling temperature to use, between 0 and 2. final JsonField<BetaAssistantCreateParams.ToolResources>
_toolResources()
A set of resources that are used by the assistant's tools. final JsonField<List<AssistantTool>>
_tools()
A list of tool enabled on the assistant. final JsonField<Double>
_topP()
An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. final Map<String, JsonValue>
_additionalBodyProperties()
final Headers
_additionalHeaders()
final QueryParams
_additionalQueryParams()
Headers
_headers()
The full set of headers in the parameters, including both fixed and additional headers. QueryParams
_queryParams()
The full set of query params in the parameters, including both fixed and additional query params. final BetaAssistantCreateParams.Builder
toBuilder()
Boolean
equals(Object other)
Integer
hashCode()
String
toString()
final static BetaAssistantCreateParams.Builder
builder()
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Method Detail
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model
final ChatModel model()
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.
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description
final Optional<String> description()
The description of the assistant. The maximum length is 512 characters.
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instructions
final Optional<String> instructions()
The system instructions that the assistant uses. The maximum length is 256,000 characters.
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metadata
final Optional<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.
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reasoningEffort
final Optional<BetaAssistantCreateParams.ReasoningEffort> reasoningEffort()
o1 and o3-mini models only
Constrains effort on reasoning for reasoning models. Currently supported values are
low
,medium
, andhigh
. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.
-
responseFormat
final Optional<AssistantResponseFormatOption> responseFormat()
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 exceededmax_tokens
or the conversation exceeded the max context length.
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temperature
final Optional<Double> temperature()
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.
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toolResources
final Optional<BetaAssistantCreateParams.ToolResources> toolResources()
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 thefile_search
tool requires a list of vector store IDs.
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tools
final Optional<List<AssistantTool>> tools()
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
, orfunction
.
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topP
final Optional<Double> topP()
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.
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_model
final JsonField<ChatModel> _model()
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.
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_description
final JsonField<String> _description()
The description of the assistant. The maximum length is 512 characters.
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_instructions
final JsonField<String> _instructions()
The system instructions that the assistant uses. The maximum length is 256,000 characters.
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_metadata
final JsonField<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.
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_name
final JsonField<String> _name()
The name of the assistant. The maximum length is 256 characters.
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_reasoningEffort
final JsonField<BetaAssistantCreateParams.ReasoningEffort> _reasoningEffort()
o1 and o3-mini models only
Constrains effort on reasoning for reasoning models. Currently supported values are
low
,medium
, andhigh
. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.
-
_responseFormat
final JsonField<AssistantResponseFormatOption> _responseFormat()
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 exceededmax_tokens
or the conversation exceeded the max context length.
-
_temperature
final JsonField<Double> _temperature()
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.
-
_toolResources
final JsonField<BetaAssistantCreateParams.ToolResources> _toolResources()
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 thefile_search
tool requires a list of vector store IDs.
-
_tools
final JsonField<List<AssistantTool>> _tools()
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
, orfunction
.
-
_topP
final JsonField<Double> _topP()
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.
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_additionalBodyProperties
final Map<String, JsonValue> _additionalBodyProperties()
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_additionalHeaders
final Headers _additionalHeaders()
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_additionalQueryParams
final QueryParams _additionalQueryParams()
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_headers
Headers _headers()
The full set of headers in the parameters, including both fixed and additional headers.
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_queryParams
QueryParams _queryParams()
The full set of query params in the parameters, including both fixed and additional query params.
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toBuilder
final BetaAssistantCreateParams.Builder toBuilder()
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builder
final static BetaAssistantCreateParams.Builder builder()
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