from llama_index.core import Settings, VectorStoreIndex
from llama_index.core.embeddings import MockEmbedding
from llama_index.core.schema import TextNode
from llama_index.core.vector_stores import (
    ExactMatchFilter,
    FilterCondition,
    MetadataFilters,
)

Settings.embed_model = MockEmbedding(embed_dim=8)

nodes = [
    TextNode(text="Refund requests require billing review.", metadata={"tenant": "atlas", "source": "billing"}),
    TextNode(text="Shipping claims require logistics review.", metadata={"tenant": "atlas", "source": "logistics"}),
    TextNode(text="Refund exports require finance approval.", metadata={"tenant": "contoso", "source": "billing"}),
]

index = VectorStoreIndex(nodes)