Find answers from the community

Updated 3 months ago

I successfully have a property graph

I successfully have a property graph index and use azure ai search as a vector store. However, I am a bit confused on what's going on.

Plain Text
import nest_asyncio
from llama_index.core import PropertyGraphIndex

# Apply nest_asyncio to allow nested use of asyncio.run()
nest_asyncio.apply()


# Load documents and create index based on the use_existing_index flag
if use_existing_index:
    storage_context = StorageContext.from_defaults(vector_store=vector_store)
    index = PropertyGraphIndex.from_documents([], storage_context=storage_context)
else:
    # Load documents
    storage_context = StorageContext.from_defaults(vector_store=vector_store)

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


Plain Text
retriever = index.as_retriever(
    include_text=False,  # include source text, default True
)

nodes = retriever.retrieve("What happened at Interleaf and Viaweb?")

for node in nodes:
    print(node.text)
Attachment
image.png
Add a reply
Sign up and join the conversation on Discord