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d49e92e21c
* change class names to bm25 * Update Documentation & Code Style * Update Documentation & Code Style * Update Documentation & Code Style * Add back all_terms_must_match * fix syntax * Update Documentation & Code Style * Update Documentation & Code Style * Creating a wrapper for old ES retriever with deprecated wrapper * Update Documentation & Code Style * New method for deprecating old ESRetriever * New attempt for deprecating the ESRetriever * Reverting to the simplest solution - warning logged * Update Documentation & Code Style Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: Sara Zan <sara.zanzottera@deepset.ai>
47 lines
1.9 KiB
Python
47 lines
1.9 KiB
Python
import pytest
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from haystack.nodes.retriever.sparse import BM25Retriever
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from haystack.nodes.reader import FARMReader
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from haystack.pipelines import Pipeline
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from haystack.nodes.extractor import EntityExtractor, simplify_ner_for_qa
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@pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
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def test_extractor(document_store_with_docs):
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es_retriever = BM25Retriever(document_store=document_store_with_docs)
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ner = EntityExtractor()
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reader = FARMReader(model_name_or_path="deepset/roberta-base-squad2", num_processes=0)
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pipeline = Pipeline()
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pipeline.add_node(component=es_retriever, name="ESRetriever", inputs=["Query"])
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pipeline.add_node(component=ner, name="NER", inputs=["ESRetriever"])
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pipeline.add_node(component=reader, name="Reader", inputs=["NER"])
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prediction = pipeline.run(
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query="Who lives in Berlin?", params={"ESRetriever": {"top_k": 1}, "Reader": {"top_k": 1}}
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)
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entities = [entity["word"] for entity in prediction["answers"][0].meta["entities"]]
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assert "Carla" in entities
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assert "Berlin" in entities
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@pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
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def test_extractor_output_simplifier(document_store_with_docs):
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es_retriever = BM25Retriever(document_store=document_store_with_docs)
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ner = EntityExtractor()
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reader = FARMReader(model_name_or_path="deepset/roberta-base-squad2", num_processes=0)
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pipeline = Pipeline()
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pipeline.add_node(component=es_retriever, name="ESRetriever", inputs=["Query"])
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pipeline.add_node(component=ner, name="NER", inputs=["ESRetriever"])
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pipeline.add_node(component=reader, name="Reader", inputs=["NER"])
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prediction = pipeline.run(
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query="Who lives in Berlin?", params={"ESRetriever": {"top_k": 1}, "Reader": {"top_k": 1}}
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)
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simplified = simplify_ner_for_qa(prediction)
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assert simplified[0] == {"answer": "Carla", "entities": ["Carla"]}
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