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From this llmsherpa example (https://github.com/nlmatics/llmsherpa), I am trying to run this chunk:

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from llama_index.core import Document
from llama_index.core import VectorStoreIndex

index = VectorStoreIndex(embed_model=embed_model)
for chunk in doc.chunks():
    index.insert(Document(text=chunk.to_context_text(), extra_info={}))
query_engine = index.as_query_engine()

# Let's run one query
response = query_engine.query("Tell me about Europe.")
print(response)

and I get

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ValueError                                Traceback (most recent call last)
Cell In[18], line 4
      1 from llama_index.core import Document
      2 from llama_index.core import VectorStoreIndex
----> 4 index = VectorStoreIndex(embed_model=embed_model)
      5 for chunk in doc.chunks():
      6     index.insert(Document(text=chunk.to_context_text(), extra_info={}))

...
---> 59     raise ValueError("One of nodes, objects, or index_struct must be provided.")
     60 if index_struct is not None and nodes is not None:
     61     raise ValueError("Only one of nodes or index_struct can be provided.")

ValueError: One of nodes, objects, or index_struct must be provided.

Is this something that has changed in the newest llamaindex version? Any ideas on how I can fix it?

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