How to create vector store index from deeplake local database?

[Alnasser0]

How do I create a vector store index if I used deeplake.load(path) function?

[dosubot[bot]]

To create a vector store index from a Deep Lake local database using the deeplake.load(path) function, follow these steps:

1. Load the Deep Lake dataset using deeplake.load(path), where path is the path to your local dataset.
2. Create a DeepLakeVectorStore using the loaded dataset.
3. Use the VectorStoreIndex.from_documents method to create an index from your documents and the storage context.

Here's a code snippet to illustrate the process:

import deeplake
from llama_index.core import VectorStoreIndex, StorageContext
from llama_index.vector_stores.deeplake import DeepLakeVectorStore

# Load the Deep Lake dataset
dataset_path = "./dataset/paul_graham"
ds = deeplake.load(dataset_path)

# Create the Deep Lake Vector Store
vector_store = DeepLakeVectorStore(dataset_path=dataset_path, overwrite=True)
storage_context = StorageContext.from_defaults(vector_store=vector_store)

# Create the index from documents
index = VectorStoreIndex.from_documents(documents, storage_context=storage_context)

This code demonstrates how to load a Deep Lake dataset and create a vector store index from it ^[1].

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