langchain.js
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    Document loader integration with LangSmith.

    Load
    import { LangSmithLoader } from '@langchain/core/document_loaders/langsmith';
    import { Client } from 'langsmith';

    const langSmithClient = new Client({
    apiKey: process.env.LANGSMITH_API_KEY,
    })

    const loader = new LangSmithLoader({
    datasetId: "9a3b36f7-b308-40a5-9b46-6613853b6330",
    limit: 1,
    });

    const docs = await loader.load();
    [
      {
        pageContent: '{\n  "input_key_str": "string",\n  "input_key_bool": true\n}',
        metadata: {
          id: '8523d9e9-c123-4b23-9b46-21021nds289e',
          created_at: '2024-08-19T17:09:14.806441+00:00',
          modified_at: '2024-08-19T17:09:14.806441+00:00',
          name: '#8517 @ brace-test-dataset',
          dataset_id: '9a3b36f7-b308-40a5-9b46-6613853b6330',
          source_run_id: null,
          metadata: [Object],
          inputs: [Object],
          outputs: [Object]
        }
      }
    ]
    

    Hierarchy (View Summary)

    Index

    Constructors

    Properties

    asOf?: string | Date
    client: Client
    contentKey: string[]
    datasetId?: string
    datasetName?: string
    exampleIds?: string[]
    filter?: string
    formatContent: (content: any) => string
    inlineS3Urls?: boolean
    limit?: number
    metadata?: KVMap
    offset?: number
    splits?: string[]

    Methods

    • Loads the documents.

      Returns Promise<Document<Record<string, any>>[]>

      A Promise that resolves with an array of Document instances.

    • Parameters

      Returns Promise<Document<Record<string, any>>[]>

      A Promise that resolves with an array of Document instances, each split according to the provided TextSplitter.

      Use this.load() and splitter.splitDocuments() individually. Loads the documents and splits them using a specified text splitter.