How to serialize a VectorStoreIndex?

[BrianP8701]

I want to serialize a VectorStoreIndex so i can save it to cloud and use it repeatedly for rag, but both pickle and dill dont work. DO you guys have another method to serialize it? Cuz its rlly bogging down my system having to create it everytime.

[dosubot[bot]]

🤖

Hi there,

You can use the built-in methods provided by the LlamaIndex codebase for serializing and deserializing a VectorStoreIndex object.

For serialization, you can use the persist method. This method saves the VectorStoreIndex object to a directory. Here's an example:

from llama_index import VectorStoreIndex

# Assuming you have a VectorStoreIndex object named index
index = VectorStoreIndex.from_vector_store(vector_store)

# Persist the index
index.persist('path/to/save/index')

For deserialization, you can use the from_persist_path method. This method loads the VectorStoreIndex object from a directory. Here's an example:

from llama_index import VectorStoreIndex

# Load the index
index = VectorStoreIndex.from_persist_path('path/to/save/index')

Please note that you need to replace 'path/to/save/index' with the actual path where you want to save or load the index from.

These methods are defined in the simple.py file in the vector_stores directory of the LlamaIndex codebase. You can find more information about these methods in the source code: llama_index/vector_stores/simple.py

I hope this helps! Let me know if you have any other questions.

Sources

• docs/examples/low_level/vector_store.ipynb
• llama_index/vector_stores/simple.py

---

This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

If you want to continue the conversation, start your reply with @dosu-bot.

[BrianP8701]

@dosu-bot Its not working im getting this error:
(venv) (base) brianprzezdziecki@Brians-MacBook-Pro-6 OI_Memory % /Users/brianprzezdziecki/Code/OI_Memory/venv/bin/python /Users/brianprzezdziecki/Code/OI_Mem
ory/oi_cloud/test.py
--- 4.245954990386963 seconds ---
['abstractmethods', 'annotations', 'class', 'class_getitem', 'delattr', 'dict', 'dir', 'doc', 'eq', 'format', 'ge', 'getattribute', 'getstate', 'gt', 'hash', 'init', 'init_subclass', 'le', 'lt', 'module', 'ne', 'new', 'orig_bases', 'parameters', 'reduce', 'reduce_ex', 'repr', 'setattr', 'sizeof', 'slots', 'str', 'subclasshook', 'weakref', '_abc_impl', '_add_nodes_to_index', '_aget_node_with_embedding', '_async_add_nodes_to_index', '_build_index_from_nodes', '_delete_node', '_docstore', '_get_node_with_embedding', '_graph_store', '_index_struct', '_insert', '_is_protocol', '_service_context', '_show_progress', '_storage_context', '_store_nodes_override', '_use_async', '_vector_store', 'as_chat_engine', 'as_query_engine', 'as_retriever', 'build_index_from_nodes', 'delete', 'delete_nodes', 'delete_ref_doc', 'docstore', 'from_documents', 'from_vector_store', 'index_id', 'index_struct', 'index_struct_cls', 'insert', 'insert_nodes', 'ref_doc_info', 'refresh', 'refresh_ref_docs', 'service_context', 'set_index_id', 'storage_context', 'summary', 'update', 'update_ref_doc', 'vector_store']
Traceback (most recent call last):
File "/Users/brianprzezdziecki/Code/OI_Memory/oi_cloud/test.py", line 18, in
index = VectorStoreIndex.from_vector_store(index)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/brianprzezdziecki/Code/OI_Memory/venv/lib/python3.11/site-packages/llama_index/indices/vector_store/base.py", line 65, in from_vector_store
if not vector_store.stores_text:
^^^^^^^^^^^^^^^^^^^^^^^^
AttributeError: 'VectorStoreIndex' object has no attribute 'stores_text'

with this code:
from llama_index import VectorStoreIndex
from llama_index import SimpleDirectoryReader
import time

start_time = time.time()
index=VectorStoreIndex([])

documents = SimpleDirectoryReader('test_library', recursive=True).load_data()
for doc in documents:
index.insert(doc)
retriever = index.as_retriever()
print("--- %s seconds ---" % (time.time() - start_time))
print(dir(index))

Assuming you have a VectorStoreIndex object named index

index = VectorStoreIndex.from_vector_store(index)

Persist the index

index.persist('saved_index.json')

Inside of test_library is just a small pdf

[dosubot]

🤖

Hello,

The error you're encountering is due to the VectorStoreIndex object trying to access the stores_text attribute, which does not exist in the VectorStore class. This attribute is used to determine whether the vector store keeps the text data of the nodes, which is crucial for serialization and the overall functioning of the VectorStoreIndex object.

In your case, it seems like you're trying to serialize a VectorStoreIndex object that was created from a class that does not have the stores_text attribute. To resolve this issue, you need to ensure that the class being used to create the VectorStoreIndex object has the stores_text attribute.

If the class is defined in your code, you can add a stores_text attribute to it. Here's an example:

class YourVectorStore(BasePydanticVectorStore):
    stores_text = True
    # rest of your code

Then, when you create a YourVectorStore object, the stores_text attribute will be set to True:

your_vector_store = YourVectorStore()

And finally, you can create a VectorStoreIndex object from this YourVectorStore:

vector_store_index = VectorStoreIndex.from_vector_store(your_vector_store)

This should resolve the AttributeError you're encountering.

Also, I found a similar issue in the LlamaIndex repository: [Bug]: from_vector_store function not working?. The solution provided there might be helpful for you.

Please let me know if this resolves your issue or if you need further assistance.

Sources

• [Bug]: from_vector_store function not working?
• llama_index/indices/vector_store/base.py
• llama_index/vector_stores/postgres.py
• llama_index/vector_stores/simple.py

---

This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

If you want to continue the conversation, start your reply with @dosu-bot.

[logan-markewich]

@BrianP8701 the bot was a little off

You can use the following to save/load to disk. You can also change the storage backend using fsspec, to use something like S3

index.storage_context.persist(persist_dir="./storage")

from llama_index import StorageContext, load_index_from_storage
storage_context = StorageContext.from_defaults(persist_dir="./storage")

# optional service context
loaded_index = load_index_from_storage(storage_context, service_context=service_context)

https://docs.llamaindex.ai/en/stable/core_modules/data_modules/storage/save_load.html#using-a-remote-backend