langchain.js
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    Interface FriendliParams

    The FriendliParams interface defines the input parameters for the Friendli class.

    interface FriendliParams {
        baseUrl?: string;
        frequencyPenalty?: number;
        friendliTeam?: string;
        friendliToken?: string;
        maxTokens?: number;
        model?: string;
        modelKwargs?: Record<string, unknown>;
        stop?: string[];
        temperature?: number;
        topP?: number;
    }

    Hierarchy (View Summary)

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    Properties

    baseUrl? frequencyPenalty? friendliTeam? friendliToken? maxTokens? model? modelKwargs? stop? temperature? topP?

    Properties

    baseUrl?: string

    Base endpoint url.

    frequencyPenalty?: number

    Number between -2.0 and 2.0. Positive values penalizes tokens that have been sampled, taking into account their frequency in the preceding text. This penalization diminishes the model's tendency to reproduce identical lines verbatim.

    friendliTeam?: string

    Friendli team ID to run as.

    friendliToken?: string

    Friendli personal access token to run as.

    maxTokens?: number

    Number between -2.0 and 2.0. Positive values penalizes tokens that have been sampled at least once in the existing text. presence_penalty: Optional[float] = None The maximum number of tokens to generate. The length of your input tokens plus max_tokens should not exceed the model's maximum length (e.g., 2048 for OpenAI GPT-3)

    model?: string

    Model name to use.

    modelKwargs?: Record<string, unknown>

    Additional kwargs to pass to the model.

    stop?: string[]

    When one of the stop phrases appears in the generation result, the API will stop generation. The phrase is included in the generated result. If you are using beam search, all of the active beams should contain the stop phrase to terminate generation. Before checking whether a stop phrase is included in the result, the phrase is converted into tokens.

    temperature?: number

    Sampling temperature. Smaller temperature makes the generation result closer to greedy, argmax (i.e., top_k = 1) sampling. If it is None, then 1.0 is used.

    topP?: number

    Tokens comprising the top top_p probability mass are kept for sampling. Numbers between 0.0 (exclusive) and 1.0 (inclusive) are allowed. If it is None, then 1.0 is used by default.

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