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Node Details

  • Name: RRFRetriever
  • Type: RRFRetriever
  • Category: Retrievers
  • Version: 1.0
  • Base Classes: RRFRetriever, BaseRetriever

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Input Parameters

  1. Vector Store Retriever (required)
    • Type: VectorStoreRetriever
    • Description: The base retriever used for initial document retrieval.
  2. Language Model (required)
    • Type: BaseLanguageModel
    • Description: The language model used for generating synthetic queries.
  3. Query (optional)
    • Type: string
    • Description: Custom query to retrieve documents. If not specified, the user’s question will be used.
  4. Query Count (optional)
    • Type: number
    • Default: 4
    • Description: Number of synthetic queries to generate.
  5. Top K (optional)
    • Type: number
    • Description: Number of top results to fetch. Defaults to the TopK of the Base Retriever.
  6. Constant (optional)
    • Type: number
    • Default: 60
    • Description: A constant added to the rank, controlling the balance between high-ranked and lower-ranked items.

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Outputs

  1. Reciprocal Rank Fusion Retriever
    • Type: RRFRetriever, BaseRetriever
    • Description: The initialized RRF retriever object.
  2. Document
    • Type: Document, json
    • Description: Array of document objects containing metadata and pageContent.
  3. Text
    • Type: string, json
    • Description: Concatenated string from pageContent of retrieved documents.

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How It Works

  1. The node initializes a ReciprocalRankFusion object using the provided language model, base retriever, and configuration parameters.
  2. It then wraps this object in a ContextualCompressionRetriever for additional processing.
  3. Depending on the selected output, the node can return:
    • The retriever object itself
    • An array of relevant documents
    • A concatenated text of the retrieved documents’ content

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Use Cases

  • Improving search relevance in document retrieval systems
  • Enhancing question-answering systems with more diverse and relevant context
  • Boosting the performance of RAG (Retrieval-Augmented Generation) applications

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Notes

  • The node uses escape character handling for text output to ensure proper formatting.
  • The synthetic query generation and re-ranking process happens internally within the ReciprocalRankFusion class.