​
Node Details

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

​
Input Parameters

  1. Vector Store
    • Label: Vector Store
    • Name: vectorStore
    • Type: VectorStore
    • Description: The vector store to be used for document retrieval.
  2. Language Model
    • Label: Language Model
    • Name: model
    • Type: BaseLanguageModel
    • Description: The language model used to generate alternative questions.
  3. Prompt
    • Label: Prompt
    • Name: modelPrompt
    • Type: string
    • Description: The prompt template for the language model to generate alternative questions. Use {question} to refer to the original question.
    • Default: A predefined prompt that instructs the AI to generate 3 different versions of the given user question.

​
Functionality

  1. The node initializes with the provided vector store, language model, and prompt template.
  2. When executed, it takes the user’s input query and uses the language model to generate multiple alternative questions based on the prompt.
  3. These alternative questions are then used to query the vector store, potentially retrieving a more diverse and comprehensive set of relevant documents.

​
Usage

This retriever is particularly useful in scenarios where:
  • The user’s initial query might not capture all aspects of their information need.
  • The desired information could be expressed in various ways in the document collection.
  • A broader exploration of the topic is beneficial.

​
Output

The node returns a MultiQueryRetriever instance, which can be used to retrieve documents based on the original query and its generated alternatives.

​
Note

The verbose output (for debugging) is controlled by the DEBUG environment variable. Set it to ‘true’ to enable verbose mode.