LangChain Reference home pageLangChain ReferenceLangChain Reference
  • GitHub
  • Main Docs
Deep Agents
LangChain
LangGraph
Integrations
LangSmith
LangChain
  • Browser
  • Universal
  • Hub
  • Node
  • Load
  • Serializable
  • Encoder Backed
  • File System
  • In Memory
  • Tools
LangChain Core
  • Agents
  • Caches
  • Base
  • Dispatch
  • Web
  • Manager
  • Promises
  • Chat History
  • Context
  • Base
  • Langsmith
  • Documents
  • Embeddings
  • Errors
  • Example Selectors
  • Indexing
  • Base
  • Chat Models
  • Llms
  • Profile
  • Structured Output
  • Load
  • Serializable
  • Memory
  • Messages
  • Tool
  • Output Parsers
  • Openai Functions
  • Openai Tools
  • Outputs
  • Prompt Values
  • Prompts
  • Retrievers
  • Document Compressors
  • Runnables
  • Graph
  • Singletons
  • Stores
  • Structured Query
  • Testing
  • Tools
  • Base
  • Console
  • Log Stream
  • Run Collector
  • Tracer Langchain
  • Stream
  • Async Caller
  • Chunk Array
  • Context
  • Env
  • Event Source Parse
  • Format
  • Function Calling
  • Hash
  • Json Patch
  • Json Schema
  • Math
  • Ssrf
  • Standard Schema
  • Stream
  • Testing
  • Tiktoken
  • Types
  • Vectorstores
Text Splitters
MCP Adapters
⌘I

LangChain Assistant

Ask a question to get started

Enter to send•Shift+Enter new line

Menu

LangChain
BrowserUniversalHubNodeLoadSerializableEncoder BackedFile SystemIn MemoryTools
LangChain Core
AgentsCachesBaseDispatchWebManagerPromisesChat HistoryContextBaseLangsmithDocumentsEmbeddingsErrorsExample SelectorsIndexingBaseChat ModelsLlmsProfileStructured OutputLoadSerializableMemoryMessagesToolOutput ParsersOpenai FunctionsOpenai ToolsOutputsPrompt ValuesPromptsRetrieversDocument CompressorsRunnablesGraphSingletonsStoresStructured QueryTestingToolsBaseConsoleLog StreamRun CollectorTracer LangchainStreamAsync CallerChunk ArrayContextEnvEvent Source ParseFormatFunction CallingHashJson PatchJson SchemaMathSsrfStandard SchemaStreamTestingTiktokenTypesVectorstores
Text Splitters
MCP Adapters
Language
Theme
JavaScript@langchain/coreutilstestingFakeRetriever_getRelevantDocuments
Methodā—Since v0.3

_getRelevantDocuments

Placeholder method for retrieving relevant documents based on a query.

This method is intended to be implemented by subclasses and will be converted to an abstract method in the next major release. Currently, it throws an error if not implemented, ensuring that custom retrievers define the specific retrieval logic.

Copy
_getRelevantDocuments(_query: string): Promise<Document<Record<string, any>>[]>

Parameters

NameTypeDescription
_query*string

The query string used to search for relevant documents.

View source on GitHub