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33 lines
1.1 KiB
Python
33 lines
1.1 KiB
Python
from typing import Optional, Any, List, Union, Tuple
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from cognee.eval_framework.benchmark_adapters.base_benchmark_adapter import BaseBenchmarkAdapter
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class DummyAdapter(BaseBenchmarkAdapter):
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def load_corpus(
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self,
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limit: Optional[int] = None,
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seed: int = 42,
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load_golden_context: bool = False,
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instance_filter: Optional[Union[str, List[str], List[int]]] = None,
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) -> Tuple[List[str], List[dict[str, Any]]]:
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corpus_list = [
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"The cognee is an AI memory engine that supports different vector and graph databases",
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"Neo4j is a graph database supported by cognee",
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]
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qa_pair = {
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"answer": "Yes",
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"question": "Is Neo4j supported by cognee?",
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"type": "dummy",
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}
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if load_golden_context:
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qa_pair["golden_context"] = "Cognee supports Neo4j and NetworkX"
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question_answer_pairs = [qa_pair]
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# Instance filtering is not applicable for the dummy adapter as it always returns the same data
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# but we include the parameter for API consistency
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return corpus_list, question_answer_pairs
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