Indexes

A VectorStoreIndex built with the default SimpleVectorStore is used in-process, then the service restarts and rebuilds the index from documents every boot, re-embedding the whole corpus.

Persist via storage_context.persist(persist_dir=...) (docstore + index_store + vector store) and reload with load_index_from_storage(StorageContext.from_defaults(persist_dir=...)). Do not re-run from_documents on every boot. For external vector stores, reconstruct the index from the existing store,…

An integrator calls VectorStoreIndex.from_documents(docs) expecting it to write to their Qdrant collection, but never passed a StorageContext, so nodes land in the in-memory SimpleVectorStore.

Pass storage_context=StorageContext.from_defaults(vector_store=QdrantVectorStore(...)) (or build via VectorStoreIndex.from_vector_store(...)). Confirm vectors actually land in Qdrant — the default in-memory store silently 'works' until restart, masking the misconfiguration.

New documents arrive hourly. The integrator inserts them directly into the external vector store via its native client, bypassing index.insert / insert_nodes, so the LlamaIndex docstore never learns about them.

Insert through the index (index.insert(document) or insert_nodes(nodes)) so the docstore, index_store, and vector store stay consistent. Bypassing LlamaIndex to write the vector store directly leaves refresh/delete and ref-doc tracking unable to manage those nodes.