Wrapper around Baidu ERNIE large language models that use the Chat endpoint.

To use you should have the BAIDU_API_KEY and BAIDU_SECRET_KEY environment variable set.

Hierarchy

Implements

  • BaiduWenxinChatInput

Constructors

Properties

ParsedCallOptions: Omit<BaseLanguageModelCallOptions, never>
accessToken: string
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 = "ERNIE-Bot-turbo"
streaming: boolean = false
verbose: boolean

Whether to print out response text.

baiduApiKey?: string
baiduSecretKey?: string
callbacks?: Callbacks
metadata?: Record<string, unknown>
penaltyScore?: number
prefixMessages?: WenxinMessage[]
tags?: string[]
temperature?: number
topP?: number
userId?: string

Accessors

Methods

  • Get the identifying parameters for the model

    Returns {
        model_name: string;
        penalty_score?: number;
        stream?: boolean;
        system?: string;
        temperature?: number;
        top_p?: number;
        user_id?: string;
    }

    • model_name: string
    • Optional penalty_score?: number
    • Optional stream?: boolean
    • Optional system?: string
    • Optional temperature?: number
    • Optional top_p?: number
    • Optional user_id?: 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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