Adds LangChain Document objects to the vector store.
Embedded
Python SDK
JS/TS
add_documents(
documents: List[Document],
ids: Optional[List[str]] = None,
**kwargs
) -> List[str]
Parameters
| Parameter | Type | Description |
|---|
documents | List[Document] | List of LangChain Document objects to add |
ids | Optional[List[str]] | (Optional) List of IDs for the documents (auto-generated if not provided) |
**kwargs | Any | Additional keyword arguments passed to add_texts |
Returns
List[str]: List of IDs for the added documentsExample Usage
from langchain_core.documents import Document
# Create documents with metadata
documents = [
Document(
page_content="Introduction to machine learning",
metadata={"chapter": 1, "topic": "ML basics"}
),
Document(
page_content="Deep learning fundamentals",
metadata={"chapter": 2, "topic": "Neural networks"}
)
]
# Add documents to the store
ids = store.add_documents(documents)
print(f"Added {len(ids)} documents")
add_documents(
documents: List[Document],
ids: Optional[List[str]] = None,
**kwargs
) -> List[str]
Parameters
| Parameter | Type | Description |
|---|
documents | List[Document] | List of LangChain Document objects to add |
ids | Optional[List[str]] | (Optional) List of IDs for the documents (auto-generated if not provided) |
**kwargs | Any | Additional keyword arguments passed to add_texts |
Returns
List[str]: List of IDs for the added documentsExample Usage
from langchain_core.documents import Document
documents = [
Document(
page_content="Introduction to machine learning",
metadata={"chapter": 1, "topic": "ML basics"}
),
Document(
page_content="Deep learning fundamentals",
metadata={"chapter": 2, "topic": "Neural networks"}
)
]
ids = store.add_documents(documents)
addDocuments(
documents: Document[],
options?: { ids?: string[] }
): Promise<string[]>
Parameters
| Parameter | Type | Description |
|---|
documents | Document[] | Array of LangChain Document objects to add |
options | object | (Optional) Options object with optional ids array |
Returns
Promise<string[]>: Array of IDs for the added documentsExample Usage
import { Document } from '@langchain/core/documents';
const documents = [
new Document({
pageContent: "Introduction to machine learning",
metadata: { chapter: 1, topic: "ML basics" }
}),
new Document({
pageContent: "Deep learning fundamentals",
metadata: { chapter: 2, topic: "Neural networks" }
})
];
const ids = await store.addDocuments(documents);
Async
The Embedded and Python SDK provide async versions of this method prefixed with a:# aadd_documents — async variant
ids = await store.aadd_documents(documents)
JS/TS methods are natively async — all signatures above already return Promise<...>. No separate async variant is needed.
