collection.add

def add(  
ids: OneOrMany[ID],  
embeddings: OneOrMany[Embedding] | OneOrMany[PyEmbedding] | None = None,  
metadatas: OneOrMany[Metadata] | None = None,  
documents: OneOrMany[Document] | None = None,  
images: OneOrMany[Image] | None = None,  
uris: OneOrMany[URI] | None = None  
) -> None

collection.add(
    ids=["1", "2", "3"],
    documents=["doc1", "doc2", "doc3"],
    embeddings=[[0.1,0.2,0.3], [0.4,0.5,0.6], [0.7,0.8,0.9]],
    metadatas=[{"tag": "a"}, {"tag": "b"}, {"tag": "c"}]
)

Add embeddings to the data store.

Args

ids
The ids of the embeddings you wish to add

embeddings
The embeddings to add. If None, embeddings will be computed based on the documents or images using the embedding_function set for the Collection. Optional.

metadatas
The metadata to associate with the embeddings. When querying, you can filter on this metadata. Optional.

documents
The documents to associate with the embeddings. Optional.

images
The images to associate with the embeddings. Optional.

uris
The uris of the images to associate with the embeddings. Optional.

Returns

output
None

Raises

ValueError
If you don't provide either embeddings or documents

ValueError
If the length of ids, embeddings, metadatas, or documents don't match

ValueError
If you don't provide an embedding function and don't provide embeddings

ValueError
If you provide both embeddings and documents

ValueError
If you provide an id that already exists