Cascade graph extraction fails with TypeError due to parameter name mismatch

[YizukiAme]

Bug Description

extract_graph_from_data() in extract_graph_from_data_v2.py passes ontology_adapter= as a keyword argument to integrate_chunk_graphs(), but the receiving function's signature expects ontology_resolver=:

# extract_graph_from_data_v2.py L59-64
return await integrate_chunk_graphs(
    data_chunks=data_chunks,
    chunk_graphs=chunk_graphs,
    graph_model=KnowledgeGraph,
    ontology_adapter=ontology_adapter,  # ← wrong keyword
)

# extract_graph_from_data.py L56-60
async def integrate_chunk_graphs(
    data_chunks: list[DocumentChunk],
    chunk_graphs: list,
    graph_model: Type[BaseModel],
    ontology_resolver: BaseOntologyResolver,  # ← expected keyword
    ...
    **kwargs,
)

Because integrate_chunk_graphs accepts **kwargs, the mismatched keyword is silently absorbed and ontology_resolver ends up missing — causing a TypeError at runtime on the cascade extraction path.

The same inconsistency exists in get_default_tasks_by_indices.py, where ontology_adapter is passed as a task kwarg instead of going through the config["ontology_config"]["ontology_resolver"] path.

Steps to Reproduce

Call extract_graph_from_data() from extract_graph_from_data_v2 with any ontology resolver → TypeError: integrate_chunk_graphs() missing 1 required positional argument: 'ontology_resolver'.

Expected Behavior

The ontology resolver should be forwarded correctly under the ontology_resolver parameter name.

Environment

• Branch: dev (commit 452333a)
• Python 3.12

[github-actions]

Hello @YizukiAme, thank you for your interest in our work!

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[coderabbitai]

🔗 Related PRs

#1802 - feat: add support to pass custom parameters in llm adapters during cognify [merged]

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