Updating an Index

Every LlamaIndex data structure allows insertion, deletion, and update.


You can β€œinsert” a new Document into any index data structure, after building the index initially. The underlying mechanism behind insertion depends on the index structure. For instance, for the list index, a new Document is inserted as additional node(s) in the list. For the vector store index, a new Document (and embedding) is inserted into the underlying document/embedding store.

An example notebook showcasing our insert capabilities is given here. In this notebook we showcase how to construct an empty index, manually create Document objects, and add those to our index data structures.

An example code snippet is given below:

index = GPTListIndex([])

embed_model = OpenAIEmbedding()
doc_chunks = []
for i, text in enumerate(text_chunks):
    doc = Document(text, doc_id=f"doc_id_{i}")

# insert
for doc_chunk in doc_chunks:


You can β€œdelete” a Document from most index data structures by specifying a document_id. (NOTE: the tree index currently does not support deletion). All nodes corresponding to the document will be deleted.

NOTE: In order to delete a Document, that Document must have a doc_id specified when first loaded into the index.



If a Document is already present within an index, you can β€œupdate” a Document with the same doc_id (for instance, if the information in the Document has changed).

# NOTE: the document has a `doc_id` specified