LLamaindex index.storage_context.persist() not storing vector_store

Question

index.storage_context.persist() is not storing the vector_store and creating thevector_store.json file

When I try to load from disk and run sc2 = StorageContext.from_defaults(persist_dir='./storage'), i get the following error:

No existing llama_index.vector_stores.simple found at ./storage/vector_store.json, skipping load.

Not sure if this information is relevant, but there is only 1 document in my documents directory for embedding

Full Code:

with open('KPMGOutlook/kpmgoutlook.text', 'w') as file: file.write(kpmg_text)

documents = SimpleDirectoryReader('KPMGOutlook').load_data()

vector_store = ChromaVectorStore(chroma_collection) storage_context = StorageContext.from_defaults(vector_store=vector_store,persist_dir='storage')

index = GPTVectorStoreIndex.from_documents(documents, storage_context=storage_context)

index.storage_context.persist()

query_engine = index.as_query_engine()

#Querying document. this works fine r = query_engine.query("Which economy has the most positive outlook?") print(r)

#This line gives me the error sc2 = StorageContext.from_defaults(persist_dir='./storage')

Answer 1

Check this LlamaIndex documentation

It says that you have to give a reference to your ServiceContext object if you had initialized your index with a custom ServiceContext object.

Hope this solves your issue.