LangChain Reference home pageLangChain ReferenceLangChain Reference
  • GitHub
  • Main Docs
Deep Agents
LangChain
LangGraph
Integrations
LangSmith
LangChain
  • Universal
  • Hub
  • Node
  • Load
  • Serializable
  • Encoder Backed
  • File System
  • In Memory
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
  • Load
  • Serializable
  • Memory
  • Messages
  • Tool
  • Output Parsers
  • Openai Functions
  • Openai Tools
  • Outputs
  • Prompt Values
  • Prompts
  • Retrievers
  • Document Compressors
  • Runnables
  • Graph
  • Singletons
  • Stores
  • Structured Query
  • 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
  • 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
UniversalHubNodeLoadSerializableEncoder BackedFile SystemIn Memory
LangChain Core
AgentsCachesBaseDispatchWebManagerPromisesChat HistoryContextBaseLangsmithDocumentsEmbeddingsErrorsExample SelectorsIndexingBaseChat ModelsLlmsProfileLoadSerializableMemoryMessagesToolOutput ParsersOpenai FunctionsOpenai ToolsOutputsPrompt ValuesPromptsRetrieversDocument CompressorsRunnablesGraphSingletonsStoresStructured QueryToolsBaseConsoleLog StreamRun CollectorTracer LangchainStreamAsync CallerChunk ArrayContextEnvEvent Source ParseFormatFunction CallingHashJson PatchJson SchemaMathSsrfStreamTestingTiktokenTypesVectorstores
Text Splitters
MCP Adapters
Language
Theme
JavaScript@langchain/coreutilstestingFakeVectorStoreaddDocuments
Methodā—Since v1.0

addDocuments

Method to add documents to the memory vector store. It extracts the text from each document, generates embeddings for them, and adds the resulting vectors to the store.

Copy
addDocuments(documents: Document<Record<string, any>>[]): Promise<void>

Parameters

NameTypeDescription
documents*Document<Record<string, any>>[]

Array of Document instances to be added to the store.

View source on GitHub