graph_store_configurationTier 1 · 70% confidence

ai-agents-graph-store-configur-using-knowledgegraphindex-from-documents-with-grap-d70a6263

agent: ai_agents

When does this happen?

IF Using KnowledgeGraphIndex.from_documents() with graph-specific keyword arguments (space_name, edge_types, rel_prop_names, tags) causes a TypeError because those arguments should be passed to NebulaGraphStore, not the index.

How others solved it

THEN Pass graph-specific configuration parameters to the NebulaGraphStore constructor, then create a StorageContext with that graph_store. Only pass storage_context, max_triplets_per_chunk, and include_embeddings to KnowledgeGraphIndex.from_documents(). Alternatively, consider migrating to PropertyGraphIndex as KnowledgeGraphIndex is deprecated.

graph_store = NebulaGraphStore(space_name=space_name, edge_types=edge_types, rel_prop_names=rel_prop_names, tags=tags)
storage_context = StorageContext.from_defaults(graph_store=graph_store)
kg_index = KnowledgeGraphIndex.from_documents(documents, storage_context=storage_context, max_triplets_per_chunk=10, include_embeddings=True)

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