pass pydantic model to cognify #369
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WalkthroughThe changes in the pull request primarily involve updates to the Changes
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🔇 Additional comments (4)cognee/api/v1/cognify/cognify_v2.py (4)
The imports are well-organized, properly grouped, and the explicit line continuations improve readability. Line range hint The error handling implementation includes:
Implement batch processing or remove unused configuration. The task_config with batch_size parameter is still not being utilized in the extract_graph_from_data implementation. This could lead to memory issues when processing large datasets since all chunks are processed simultaneously. Consider either:
This applies to other tasks in the pipeline that have similar batch_size configurations. #!/bin/bash
# Check implementation of extract_graph_from_data for batch processing
ast-grep --pattern 'def extract_graph_from_data($$$)' -A 20
# Check other task implementations for batch processing
fd "tasks.*\.py$" --exec ast-grep --pattern 'batch_size' {}
The function signature changes are well-implemented with proper type hints and backward compatibility. However, let's verify that all callers are prepared for this change. Also applies to: 62-62 ✅ Verification successfulThe graph_model parameter change is safe and backward compatible All existing calls to Key findings from the codebase scan:
🏁 Scripts executedThe following scripts were executed for the analysis: Script: #!/bin/bash
# Search for direct calls to cognify or run_cognify_pipeline
rg "cognify\(|run_cognify_pipeline\(" -A 2
# Search for any test files that might need updating
fd "test.*cognify.*\.py$" --exec cat {}
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Actionable comments posted: 1
🧹 Outside diff range and nitpick comments (2)
cognee/api/v1/cognify/cognify_v2.py (2)
Line range hint
33-61: Update cognify function to handle graph_model parameterThe
cognifyfunction callsrun_cognify_pipelinebut doesn't pass thegraph_modelparameter. While this works due to the default value, consider exposing this parameter in thecognifyfunction signature for consistency and to allow users to specify custom models at the top level.-async def cognify(datasets: Union[str, list[str]] = None, user: User = None): +async def cognify( + datasets: Union[str, list[str]] = None, + user: User = None, + graph_model: BaseModel = KnowledgeGraph +): if user is None: user = await get_default_user() # ... for dataset in datasets: dataset_name = generate_dataset_name(dataset.name) if dataset_name in existing_datasets_map: - awaitables.append(run_cognify_pipeline(dataset, user)) + awaitables.append(run_cognify_pipeline(dataset, user, graph_model))
Line range hint
62-90: Consider documenting the graph_model parameter usageThis change introduces flexibility in graph model customization, which is a significant architectural enhancement. Consider:
- Adding docstring documentation for the
graph_modelparameter- Creating example custom models in the documentation
- Adding validation to ensure custom models have required fields/methods
This will help users understand how to properly implement and use custom graph models.
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cognee/api/v1/cognify/cognify_v2.py(3 hunks)
🔇 Additional comments (2)
cognee/api/v1/cognify/cognify_v2.py (2)
5-24: LGTM! Clean import organization
The imports are well-organized and the addition of BaseModel from pydantic supports the new type annotation.
62-62: Verify KnowledgeGraph model inheritance
Let's verify that KnowledgeGraph actually inherits from BaseModel to ensure type safety.
✅ Verification successful
KnowledgeGraph inheritance is correctly implemented
The verification confirms that KnowledgeGraph properly inherits from pydantic.BaseModel as shown in cognee/shared/data_models.py. The default value in the function signature is type-safe and correctly implemented.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for KnowledgeGraph class definition
ast-grep --pattern 'class KnowledgeGraph($$$BaseModel$$$):'
Length of output: 61
Script:
#!/bin/bash
# Let's try a broader search for KnowledgeGraph class definition and its imports
rg "class KnowledgeGraph" -A 5
# Also search for imports related to KnowledgeGraph and BaseModel
rg "from.*KnowledgeGraph|import.*KnowledgeGraph|from.*BaseModel|import.*BaseModel"
Length of output: 4190
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