from llama_index.core import Document, Settings, VectorStoreIndex
from llama_index.core.embeddings import MockEmbedding
from llama_index.core.llms import MockLLM


Settings.llm = MockLLM()
Settings.embed_model = MockEmbedding(embed_dim=8)

documents = [
    Document(
        text=(
            "Acme support answers refund questions from the policy index. "
            "Refund requests remain eligible for 30 days after purchase."
        )
    )
]
index = VectorStoreIndex.from_documents(documents)