TimeWeightedVectorStoreRetriever retrieves documents based on their time-weighted relevance. ref: https://github.com/langchain-ai/langchain/blob/master/libs/langchain/langchain/retrievers/time_weighted_retriever.py

Hierarchy

Constructors

Properties

callbacks?: Callbacks
metadata?: Record<string, unknown>
tags?: string[]
verbose?: boolean

Methods

  • NOTE: When adding documents to a vector store, use addDocuments via retriever instead of directly to the vector store. This is because it is necessary to process the document in prepareDocuments.

    Parameters

    • docs: Document<Record<string, any>>[]

      The documents to add to vector store in the retriever

    Returns Promise<void>

  • Default implementation of batch, which calls invoke N times. Subclasses should override this method if they can batch more efficiently.

    Parameters

    • inputs: string[]

      Array of inputs to each batch call.

    • Optional options: Partial<BaseCallbackConfig> | Partial<BaseCallbackConfig>[]

      Either a single call options object to apply to each batch call or an array for each call.

    • Optional batchOptions: RunnableBatchOptions & {
          returnExceptions?: false;
      }

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

    An array of RunOutputs, or mixed RunOutputs and errors if batchOptions.returnExceptions is set

  • Parameters

    Returns Promise<(Error | Document<Record<string, any>>[])[]>

  • Parameters

    Returns Promise<(Error | Document<Record<string, any>>[])[]>

  • Get the memory stream of documents.

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

    The memory stream of documents.

  • Main method used to retrieve relevant documents. It takes a query string and an optional configuration object, and returns a promise that resolves to an array of Document objects. This method handles the retrieval process, including starting and ending callbacks, and error handling.

    Parameters

    • query: string

      The query string to retrieve relevant documents for.

    • Optional config: Callbacks | BaseCallbackConfig

      Optional configuration object for the retrieval process.

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

    A promise that resolves to an array of Document objects.

  • Parameters

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

  • Create a new runnable sequence that runs each individual runnable in series, piping the output of one runnable into another runnable or runnable-like.

    Type Parameters

    • NewRunOutput

    Parameters

    • coerceable: RunnableLike<Document<Record<string, any>>[], NewRunOutput>

      A runnable, function, or object whose values are functions or runnables.

    Returns RunnableSequence<string, Exclude<NewRunOutput, Error>>

    A new runnable sequence.

  • Set the memory stream of documents.

    Parameters

    • memoryStream: Document<Record<string, any>>[]

      The new memory stream of documents.

    Returns void

  • Stream output in chunks.

    Parameters

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

    A readable stream that is also an iterable.

  • 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

    • input: string
    • Optional options: Partial<BaseCallbackConfig>
    • Optional streamOptions: Omit<LogStreamCallbackHandlerInput, "autoClose">

    Returns AsyncGenerator<RunLogPatch, any, unknown>

  • Default implementation of transform, which buffers input and then calls stream. Subclasses should override this method if they can start producing output while input is still being generated.

    Parameters

    Returns AsyncGenerator<Document<Record<string, any>>[], any, unknown>

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