All Implemented Interfaces:


public final class ChatCompletionCreateParams.Body

Nested Class Summary

Nested Classes
Modifier and Type	Class	Description
`public final class`	`ChatCompletionCreateParams.Body.Builder`	A builder for Body.

Field Summary

Fields
Modifier and Type	Field	Description

Constructor Summary

Constructors
Constructor	Description

Enum Constant Summary

Enum Constants
Enum Constant	Description

Method Summary

Modifier and Type	Method	Description
`final List<ChatCompletionMessageParam>`	`messages()`	A list of messages comprising the conversation so far.
`final ChatModel`	`model()`	ID of the model to use.
`final Optional<ChatCompletionAudioParam>`	`audio()`	Parameters for audio output.
`final Optional<Double>`	`frequencyPenalty()`	Number between -2.0 and 2.0.
`final Optional<ChatCompletionCreateParams.FunctionCall>`	`functionCall()`	Deprecated in favor of `tool_choice`.
`final Optional<List<ChatCompletionCreateParams.Function>>`	`functions()`	Deprecated in favor of `tools`.
`final Optional<ChatCompletionCreateParams.LogitBias>`	`logitBias()`	Modify the likelihood of specified tokens appearing in the completion.
`final Optional<Boolean>`	`logprobs()`	Whether to return log probabilities of the output tokens or not.
`final Optional<Long>`	`maxCompletionTokens()`	An upper bound for the number of tokens that can be generated for a completion, including visible output tokens and reasoning tokens.
`final Optional<Long>`	`maxTokens()`	The maximum number of /tokenizer that can be generated in the chat completion.
`final Optional<Metadata>`	`metadata()`	Set of 16 key-value pairs that can be attached to an object.
`final Optional<List<ChatCompletionModality>>`	`modalities()`	Output types that you would like the model to generate for this request.
`final Optional<Long>`	`n()`	How many chat completion choices to generate for each input message.
`final Optional<Boolean>`	`parallelToolCalls()`	Whether to enable parallel function calling during tool use.
`final Optional<ChatCompletionPredictionContent>`	`prediction()`	Static predicted output content, such as the content of a text file that is being regenerated.
`final Optional<Double>`	`presencePenalty()`	Number between -2.0 and 2.0.
`final Optional<ChatCompletionReasoningEffort>`	`reasoningEffort()`	o1 and o3-mini models onlyConstrains effort on reasoning for reasoning models.
`final Optional<ChatCompletionCreateParams.ResponseFormat>`	`responseFormat()`	An object specifying the format that the model must output.
`final Optional<Long>`	`seed()`	This feature is in Beta.
`final Optional<ChatCompletionCreateParams.ServiceTier>`	`serviceTier()`	Specifies the latency tier to use for processing the request.
`final Optional<ChatCompletionCreateParams.Stop>`	`stop()`	Up to 4 sequences where the API will stop generating further tokens.
`final Optional<Boolean>`	`store()`	Whether or not to store the output of this chat completion request for use in our model distillation or evals products.
`final Optional<ChatCompletionStreamOptions>`	`streamOptions()`	Options for streaming response.
`final Optional<Double>`	`temperature()`	What sampling temperature to use, between 0 and 2.
`final Optional<ChatCompletionToolChoiceOption>`	`toolChoice()`	Controls which (if any) tool is called by the model.
`final Optional<List<ChatCompletionTool>>`	`tools()`	A list of tools the model may call.
`final Optional<Long>`	`topLogprobs()`	An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability.
`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 Optional<String>`	`user()`	A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
`final JsonField<List<ChatCompletionMessageParam>>`	`_messages()`	A list of messages comprising the conversation so far.
`final JsonField<ChatModel>`	`_model()`	ID of the model to use.
`final JsonField<ChatCompletionAudioParam>`	`_audio()`	Parameters for audio output.
`final JsonField<Double>`	`_frequencyPenalty()`	Number between -2.0 and 2.0.
`final JsonField<ChatCompletionCreateParams.FunctionCall>`	`_functionCall()`	Deprecated in favor of `tool_choice`.
`final JsonField<List<ChatCompletionCreateParams.Function>>`	`_functions()`	Deprecated in favor of `tools`.
`final JsonField<ChatCompletionCreateParams.LogitBias>`	`_logitBias()`	Modify the likelihood of specified tokens appearing in the completion.
`final JsonField<Boolean>`	`_logprobs()`	Whether to return log probabilities of the output tokens or not.
`final JsonField<Long>`	`_maxCompletionTokens()`	An upper bound for the number of tokens that can be generated for a completion, including visible output tokens and reasoning tokens.
`final JsonField<Long>`	`_maxTokens()`	The maximum number of /tokenizer that can be generated in the chat completion.
`final JsonField<Metadata>`	`_metadata()`	Set of 16 key-value pairs that can be attached to an object.
`final JsonField<List<ChatCompletionModality>>`	`_modalities()`	Output types that you would like the model to generate for this request.
`final JsonField<Long>`	`_n()`	How many chat completion choices to generate for each input message.
`final JsonField<Boolean>`	`_parallelToolCalls()`	Whether to enable parallel function calling during tool use.
`final JsonField<ChatCompletionPredictionContent>`	`_prediction()`	Static predicted output content, such as the content of a text file that is being regenerated.
`final JsonField<Double>`	`_presencePenalty()`	Number between -2.0 and 2.0.
`final JsonField<ChatCompletionReasoningEffort>`	`_reasoningEffort()`	o1 and o3-mini models onlyConstrains effort on reasoning for reasoning models.
`final JsonField<ChatCompletionCreateParams.ResponseFormat>`	`_responseFormat()`	An object specifying the format that the model must output.
`final JsonField<Long>`	`_seed()`	This feature is in Beta.
`final JsonField<ChatCompletionCreateParams.ServiceTier>`	`_serviceTier()`	Specifies the latency tier to use for processing the request.
`final JsonField<ChatCompletionCreateParams.Stop>`	`_stop()`	Up to 4 sequences where the API will stop generating further tokens.
`final JsonField<Boolean>`	`_store()`	Whether or not to store the output of this chat completion request for use in our model distillation or evals products.
`final JsonField<ChatCompletionStreamOptions>`	`_streamOptions()`	Options for streaming response.
`final JsonField<Double>`	`_temperature()`	What sampling temperature to use, between 0 and 2.
`final JsonField<ChatCompletionToolChoiceOption>`	`_toolChoice()`	Controls which (if any) tool is called by the model.
`final JsonField<List<ChatCompletionTool>>`	`_tools()`	A list of tools the model may call.
`final JsonField<Long>`	`_topLogprobs()`	An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability.
`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 JsonField<String>`	`_user()`	A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
`final Map<String, JsonValue>`	`_additionalProperties()`
`final ChatCompletionCreateParams.Body`	`validate()`
`final ChatCompletionCreateParams.Body.Builder`	`toBuilder()`
`Boolean`	`equals(Object other)`
`Integer`	`hashCode()`
`String`	`toString()`
`final static ChatCompletionCreateParams.Body.Builder`	`builder()`

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
- Method Detail
  - messages
```
 final List<ChatCompletionMessageParam> messages()
```
    A list of messages comprising the conversation so far. Depending on the model you use, different message types (modalities) are supported, like text, images, and audio.
  - model
```
 final ChatModel model()
```
    ID of the model to use. See the model endpoint compatibility table for details on which models work with the Chat API.
  - audio
```
 final Optional<ChatCompletionAudioParam> audio()
```
    Parameters for audio output. Required when audio output is requested with modalities: ["audio"]. Learn more.
  - frequencyPenalty
```
 final Optional<Double> frequencyPenalty()
```
    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.
  - functionCall
```
@Deprecated(message = "deprecated") final Optional<ChatCompletionCreateParams.FunctionCall> functionCall()
```
    Deprecated in favor of tool_choice.
    Controls which (if any) function is called by the model.
    none means the model will not call a function and instead generates a message.
    auto means the model can pick between generating a message or calling a function.
    Specifying a particular function via {"name": "my_function"} forces the model to call that function.
    none is the default when no functions are present. auto is the default if functions are present.
  - functions
```
@Deprecated(message = "deprecated") final Optional<List<ChatCompletionCreateParams.Function>> functions()
```
    Deprecated in favor of tools.
    A list of functions the model may generate JSON inputs for.
  - logitBias
```
 final Optional<ChatCompletionCreateParams.LogitBias> logitBias()
```
    Modify the likelihood of specified tokens appearing in the completion.
    Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. 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.
  - logprobs
```
 final Optional<Boolean> logprobs()
```
    Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the content of message.
  - maxCompletionTokens
```
 final Optional<Long> maxCompletionTokens()
```
    An upper bound for the number of tokens that can be generated for a completion, including visible output tokens and reasoning tokens.
  - maxTokens
```
@Deprecated(message = "deprecated") final Optional<Long> maxTokens()
```
    The maximum number of /tokenizer that can be generated in the chat completion. This value can be used to control costs for text generated via API.
    This value is now deprecated in favor of max_completion_tokens, and is not compatible with o1 series models.
  - 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.
  - modalities
```
 final Optional<List<ChatCompletionModality>> modalities()
```
    Output types that you would like the model to generate for this request. Most models are capable of generating text, which is the default:
    ["text"]
    The gpt-4o-audio-preview model can also be used to generate audio. To request that this model generate both text and audio responses, you can use:
    ["text", "audio"]
  - n
```
 final Optional<Long> n()
```
    How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep n as 1 to minimize costs.
  - parallelToolCalls
```
 final Optional<Boolean> parallelToolCalls()
```
    Whether to enable parallel function calling during tool use.
  - prediction
```
 final Optional<ChatCompletionPredictionContent> prediction()
```
    Static predicted output content, such as the content of a text file that is being regenerated.
  - presencePenalty
```
 final Optional<Double> presencePenalty()
```
    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.
  - reasoningEffort
```
 final Optional<ChatCompletionReasoningEffort> reasoningEffort()
```
    o1 and o3-mini models only
    Constrains effort on reasoning for reasoning models. Currently supported values are low, medium, and high. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.
  - responseFormat
```
 final Optional<ChatCompletionCreateParams.ResponseFormat> responseFormat()
```
    An object specifying the format that the model must output.
    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.
  - seed
```
 final Optional<Long> seed()
```
    This feature is in Beta. 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.
  - serviceTier
```
 final Optional<ChatCompletionCreateParams.ServiceTier> serviceTier()
```
    Specifies the latency tier to use for processing the request. This parameter is relevant for customers subscribed to the scale tier service:
    If set to 'auto', and the Project is Scale tier enabled, the system will utilize scale tier credits until they are exhausted.
    If set to 'auto', and the Project is not Scale tier enabled, the request will be processed using the default service tier with a lower uptime SLA and no latency guarantee.
    If set to 'default', the request will be processed using the default service tier with a lower uptime SLA and no latency guarantee.
    When not set, the default behavior is 'auto'.
  - stop
```
 final Optional<ChatCompletionCreateParams.Stop> stop()
```
    Up to 4 sequences where the API will stop generating further tokens.
  - store
```
 final Optional<Boolean> store()
```
    Whether or not to store the output of this chat completion request for use in our model distillation or evals products.
  - streamOptions
```
 final Optional<ChatCompletionStreamOptions> streamOptions()
```
    Options for streaming response. Only set this when you set stream: true.
  - 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. We generally recommend altering this or top_p but not both.
  - toolChoice
```
 final Optional<ChatCompletionToolChoiceOption> toolChoice()
```
    Controls which (if any) tool is called by the model. none means the model will not call any tool and instead generates a message. auto means the model can pick between generating a message or calling one or more tools. required means the model must call one or more tools. Specifying a particular tool via {"type": "function", "function": {"name": "my_function"}} forces the model to call that tool.
    none is the default when no tools are present. auto is the default if tools are present.
  - tools
```
 final Optional<List<ChatCompletionTool>> tools()
```
    A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported.
  - topLogprobs
```
 final Optional<Long> topLogprobs()
```
    An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability. logprobs must be set to true if this parameter is used.
  - 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.
  - user
```
 final Optional<String> user()
```
    A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.
  - _messages
```
 final JsonField<List<ChatCompletionMessageParam>> _messages()
```
    A list of messages comprising the conversation so far. Depending on the model you use, different message types (modalities) are supported, like text, images, and audio.
  - _model
```
 final JsonField<ChatModel> _model()
```
    ID of the model to use. See the model endpoint compatibility table for details on which models work with the Chat API.
  - _audio
```
 final JsonField<ChatCompletionAudioParam> _audio()
```
    Parameters for audio output. Required when audio output is requested with modalities: ["audio"]. Learn more.
  - _frequencyPenalty
```
 final JsonField<Double> _frequencyPenalty()
```
    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.
  - _functionCall
```
@Deprecated(message = "deprecated") final JsonField<ChatCompletionCreateParams.FunctionCall> _functionCall()
```
    Deprecated in favor of tool_choice.
    Controls which (if any) function is called by the model.
    none means the model will not call a function and instead generates a message.
    auto means the model can pick between generating a message or calling a function.
    Specifying a particular function via {"name": "my_function"} forces the model to call that function.
    none is the default when no functions are present. auto is the default if functions are present.
  - _functions
```
@Deprecated(message = "deprecated") final JsonField<List<ChatCompletionCreateParams.Function>> _functions()
```
    Deprecated in favor of tools.
    A list of functions the model may generate JSON inputs for.
  - _logitBias
```
 final JsonField<ChatCompletionCreateParams.LogitBias> _logitBias()
```
    Modify the likelihood of specified tokens appearing in the completion.
    Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. 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.
  - _logprobs
```
 final JsonField<Boolean> _logprobs()
```
    Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the content of message.
  - _maxCompletionTokens
```
 final JsonField<Long> _maxCompletionTokens()
```
    An upper bound for the number of tokens that can be generated for a completion, including visible output tokens and reasoning tokens.
  - _maxTokens
```
@Deprecated(message = "deprecated") final JsonField<Long> _maxTokens()
```
    The maximum number of /tokenizer that can be generated in the chat completion. This value can be used to control costs for text generated via API.
    This value is now deprecated in favor of max_completion_tokens, and is not compatible with o1 series models.
  - _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.
  - _modalities
```
 final JsonField<List<ChatCompletionModality>> _modalities()
```
    Output types that you would like the model to generate for this request. Most models are capable of generating text, which is the default:
    ["text"]
    The gpt-4o-audio-preview model can also be used to generate audio. To request that this model generate both text and audio responses, you can use:
    ["text", "audio"]
  - _n
```
 final JsonField<Long> _n()
```
    How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep n as 1 to minimize costs.
  - _parallelToolCalls
```
 final JsonField<Boolean> _parallelToolCalls()
```
    Whether to enable parallel function calling during tool use.
  - _prediction
```
 final JsonField<ChatCompletionPredictionContent> _prediction()
```
    Static predicted output content, such as the content of a text file that is being regenerated.
  - _presencePenalty
```
 final JsonField<Double> _presencePenalty()
```
    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.
  - _reasoningEffort
```
 final JsonField<ChatCompletionReasoningEffort> _reasoningEffort()
```
    o1 and o3-mini models only
    Constrains effort on reasoning for reasoning models. Currently supported values are low, medium, and high. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.
  - _responseFormat
```
 final JsonField<ChatCompletionCreateParams.ResponseFormat> _responseFormat()
```
    An object specifying the format that the model must output.
    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.
  - _seed
```
 final JsonField<Long> _seed()
```
    This feature is in Beta. 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.
  - _serviceTier
```
 final JsonField<ChatCompletionCreateParams.ServiceTier> _serviceTier()
```
    Specifies the latency tier to use for processing the request. This parameter is relevant for customers subscribed to the scale tier service:
    If set to 'auto', and the Project is Scale tier enabled, the system will utilize scale tier credits until they are exhausted.
    If set to 'auto', and the Project is not Scale tier enabled, the request will be processed using the default service tier with a lower uptime SLA and no latency guarantee.
    If set to 'default', the request will be processed using the default service tier with a lower uptime SLA and no latency guarantee.
    When not set, the default behavior is 'auto'.
  - _stop
```
 final JsonField<ChatCompletionCreateParams.Stop> _stop()
```
    Up to 4 sequences where the API will stop generating further tokens.
  - _store
```
 final JsonField<Boolean> _store()
```
    Whether or not to store the output of this chat completion request for use in our model distillation or evals products.
  - _streamOptions
```
 final JsonField<ChatCompletionStreamOptions> _streamOptions()
```
    Options for streaming response. Only set this when you set stream: true.
  - _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. We generally recommend altering this or top_p but not both.
  - _toolChoice
```
 final JsonField<ChatCompletionToolChoiceOption> _toolChoice()
```
    Controls which (if any) tool is called by the model. none means the model will not call any tool and instead generates a message. auto means the model can pick between generating a message or calling one or more tools. required means the model must call one or more tools. Specifying a particular tool via {"type": "function", "function": {"name": "my_function"}} forces the model to call that tool.
    none is the default when no tools are present. auto is the default if tools are present.
  - _tools
```
 final JsonField<List<ChatCompletionTool>> _tools()
```
    A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported.
  - _topLogprobs
```
 final JsonField<Long> _topLogprobs()
```
    An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability. logprobs must be set to true if this parameter is used.
  - _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.
  - _user
```
 final JsonField<String> _user()
```
    A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.
  - _additionalProperties
```
 final Map<String, JsonValue> _additionalProperties()
```
  - validate
```
 final ChatCompletionCreateParams.Body validate()
```
  - toBuilder
```
 final ChatCompletionCreateParams.Body.Builder toBuilder()
```
  - equals
```
 Boolean equals(Object other)
```
  - hashCode
```
 Integer hashCode()
```
  - toString
```
 String toString()
```
  - builder
```
 final static ChatCompletionCreateParams.Body.Builder builder()
```

Class ChatCompletionCreateParams.Body

Nested Class Summary

Field Summary

Constructor Summary

Enum Constant Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

Method Detail

messages

model

audio

frequencyPenalty

functionCall

functions

logitBias

logprobs

maxCompletionTokens

maxTokens

metadata

modalities

n

parallelToolCalls

prediction

presencePenalty

reasoningEffort

responseFormat

seed

serviceTier

stop

store

streamOptions

temperature

toolChoice

tools

topLogprobs

topP

user

_messages

_model

_audio

_frequencyPenalty

_functionCall

_functions

_logitBias

_logprobs

_maxCompletionTokens

_maxTokens

_metadata

_modalities

_n

_parallelToolCalls

_prediction

_presencePenalty

_reasoningEffort

_responseFormat

_seed

_serviceTier

_stop

_store

_streamOptions

_temperature

_toolChoice

_tools

_topLogprobs

_topP

_user

_additionalProperties

validate

toBuilder

equals

hashCode

toString

builder