Interface TogetherAICallOptions

interface TogetherAICallOptions {
    callbacks?: Callbacks;
    configurable?: Record<string, any>;
    logprobs?: number;
    ls_structured_output_format?: {
        kwargs: {
            method: string;
        };
        schema?: JsonSchema7Type;
    };
    maxConcurrency?: number;
    maxTokens?: number;
    metadata?: Record<string, unknown>;
    model?: string;
    modelName?: string;
    recursionLimit?: number;
    repetitionPenalty?: number;
    runId?: string;
    runName?: string;
    safetyModel?: string;
    signal?: AbortSignal;
    stop?: string[];
    tags?: string[];
    temperature?: number;
    timeout?: number;
    topK?: number;
    topP?: number;
}

Hierarchy

  • BaseLLMCallOptions
  • Pick<TogetherAIInputs,
        | "modelName"
        | "model"
        | "temperature"
        | "topP"
        | "topK"
        | "repetitionPenalty"
        | "logprobs"
        | "safetyModel"
        | "maxTokens"
        | "stop">
    • TogetherAICallOptions

Properties

callbacks? configurable? logprobs? ls_structured_output_format? maxConcurrency? maxTokens? metadata? model? modelName? recursionLimit? repetitionPenalty? runId? runName? safetyModel? signal? stop? tags? temperature? timeout? topK? topP?

Properties

Optionalcallbacks

callbacks?: Callbacks

Callbacks for this call and any sub-calls (eg. a Chain calling an LLM). Tags are passed to all callbacks, metadata is passed to handle*Start callbacks.

Optionalconfigurable

configurable?: Record<string, any>

Runtime values for attributes previously made configurable on this Runnable, or sub-Runnables.

Optionallogprobs

logprobs?: number

An integer that specifies how many top token log probabilities are included in the response for each token generation step.

Optionalls_structured_output_format

ls_structured_output_format?: {
    kwargs: {
        method: string;
    };
    schema?: JsonSchema7Type;
}

Describes the format of structured outputs. This should be provided if an output is considered to be structured

Type declaration

  • kwargs: {
        method: string;
    }

    An object containing the method used for structured output (e.g., "jsonMode").

    • method: string
  • Optionalschema?: JsonSchema7Type

    The JSON schema describing the expected output structure.

OptionalmaxConcurrency

maxConcurrency?: number

Maximum number of parallel calls to make.

OptionalmaxTokens

maxTokens?: number

Limit the number of tokens generated.

Optionalmetadata

metadata?: Record<string, unknown>

Metadata for this call and any sub-calls (eg. a Chain calling an LLM). Keys should be strings, values should be JSON-serializable.

Optionalmodel

model?: string

The name of the model to query.

OptionalmodelName

modelName?: string

The name of the model to query. Alias for model

OptionalrecursionLimit

recursionLimit?: number

Maximum number of times a call can recurse. If not provided, defaults to 25.

OptionalrepetitionPenalty

repetitionPenalty?: number

A number that controls the diversity of generated text by reducing the likelihood of repeated sequences. Higher values decrease repetition.

Default

{1}

OptionalrunId

runId?: string

Unique identifier for the tracer run for this call. If not provided, a new UUID will be generated.

OptionalrunName

runName?: string

Name for the tracer run for this call. Defaults to the name of the class.

OptionalsafetyModel

safetyModel?: string

Run an LLM-based input-output safeguard model on top of any model.

Optionalsignal

signal?: AbortSignal

Abort signal for this call. If provided, the call will be aborted when the signal is aborted.

See

https://developer.mozilla.org/en-US/docs/Web/API/AbortSignal

Optionalstop

stop?: string[]

Stop tokens to use for this call. If not provided, the default stop tokens for the model will be used.

Optionaltags

tags?: string[]

Tags for this call and any sub-calls (eg. a Chain calling an LLM). You can use these to filter calls.

Optionaltemperature

temperature?: number

A decimal number that determines the degree of randomness in the response. A value of 1 will always yield the same output. A temperature less than 1 favors more correctness and is appropriate for question answering or summarization. A value greater than 1 introduces more randomness in the output.

Default

{0.7}

Optionaltimeout

timeout?: number

Timeout for this call in milliseconds.

OptionaltopK

topK?: number

The topK parameter is used to limit the number of choices for the next predicted word or token. It specifies the maximum number of tokens to consider at each step, based on their probability of occurrence. This technique helps to speed up the generation process and can improve the quality of the generated text by focusing on the most likely options.

Default

{50}

OptionaltopP

topP?: number

The topP (nucleus) parameter is used to dynamically adjust the number of choices for each predicted token based on the cumulative probabilities. It specifies a probability threshold, below which all less likely tokens are filtered out. This technique helps to maintain diversity and generate more fluent and natural-sounding text.

Default

{0.7}

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