Wrapper around Minimax large language models that use the Chat endpoint.

To use you should have the MINIMAX_GROUP_ID and MINIMAX_API_KEY environment variable set.

Hierarchy

Implements

  • MinimaxChatInput

Constructors

Properties

ParsedCallOptions: Omit<ChatMinimaxCallOptions, never>
apiUrl: string
caller: AsyncCaller

The async caller should be used by subclasses to make any async calls, which will thus benefit from the concurrency and retry logic.

modelName: string = "abab5.5-chat"
streaming: boolean = false
verbose: boolean

Whether to print out response text.

basePath?: string = "https://api.minimax.chat/v1"
beamWidth?: number
botSetting?: BotSetting[]
callbacks?: Callbacks
continueLastMessage?: boolean
defaultBotName?: string = "Assistant"
defaultUserName?: string = "I"
headers?: Record<string, string>
maskSensitiveInfo?: boolean
metadata?: Record<string, unknown>
minimaxApiKey?: string
minimaxGroupId?: string
prefixMessages?: MinimaxChatCompletionRequestMessage[]
proVersion?: boolean = true
prompt?: string
replyConstraints?: ReplyConstraints
roleMeta?: RoleMeta
skipInfoMask?: boolean
tags?: string[]
temperature?: number = 0.9
tokensToGenerate?: number
topP?: number = 0.8
useStandardSse?: boolean

Accessors

Methods

  • Get the identifying parameters for the model

    Returns {
        model: string;
        beam_width?: number;
        bot_setting?: BotSetting[];
        functions?: Function[];
        mask_sensitive_info?: boolean;
        plugins?: string[];
        prompt?: string;
        reply_constraints?: ReplyConstraints;
        role_meta?: RoleMeta;
        sample_messages?: MinimaxChatCompletionRequestMessage[];
        skip_info_mask?: boolean;
        stream?: boolean;
        temperature?: number;
        tokens_to_generate?: number;
        top_p?: number;
        use_standard_sse?: boolean;
    }

    • model: string
    • Optional beam_width?: number
    • Optional bot_setting?: BotSetting[]
    • Optional functions?: Function[]

      A list of functions the model may generate JSON inputs for.

    • Optional mask_sensitive_info?: boolean
    • Optional plugins?: string[]
    • Optional prompt?: string
    • Optional reply_constraints?: ReplyConstraints
    • Optional role_meta?: RoleMeta
    • Optional sample_messages?: MinimaxChatCompletionRequestMessage[]
    • Optional skip_info_mask?: boolean
    • Optional stream?: boolean
    • Optional temperature?: number
    • Optional tokens_to_generate?: number
    • Optional top_p?: number
    • Optional use_standard_sse?: boolean
  • Convert a list of messages to the format expected by the model.

    Parameters

    Returns undefined | MinimaxChatCompletionRequestMessage[]

  • Predicts the next message based on a text input.

    Parameters

    • text: string

      The text input.

    • Optional options: string[] | ChatMinimaxCallOptions

      The call options or an array of stop sequences.

    • Optional callbacks: Callbacks

      The callbacks for the language model.

    Returns Promise<string>

    A Promise that resolves to a string.

  • Stream all output from a runnable, as reported to the callback system. This includes all inner runs of LLMs, Retrievers, Tools, etc. Output is streamed as Log objects, which include a list of jsonpatch ops that describe how the state of the run has changed in each step, and the final state of the run. The jsonpatch ops can be applied in order to construct state.

    Parameters

    Returns AsyncGenerator<RunLogPatch, any, unknown>

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