mirror of
https://github.com/deepset-ai/haystack.git
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39 lines
2.2 KiB
Python
39 lines
2.2 KiB
Python
from haystack import Finder
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def test_faq_retriever_in_memory_store(monkeypatch):
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monkeypatch.setenv("EMBEDDING_FIELD_NAME", "embedding")
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from haystack.database.memory import InMemoryDocumentStore
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from haystack.retriever.elasticsearch import EmbeddingRetriever
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document_store = InMemoryDocumentStore()
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documents = [
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{'name': 'How to test this library?', 'text': 'By running tox in the command line!', 'meta': {'question': 'How to test this library?'}},
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{'name': 'blah blah blah', 'text': 'By running tox in the command line!', 'meta': {'question': 'blah blah blah'}},
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{'name': 'blah blah blah', 'text': 'By running tox in the command line!', 'meta': {'question': 'blah blah blah'}},
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{'name': 'blah blah blah', 'text': 'By running tox in the command line!', 'meta': {'question': 'blah blah blah'}},
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{'name': 'blah blah blah', 'text': 'By running tox in the command line!', 'meta': {'question': 'blah blah blah'}},
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{'name': 'blah blah blah', 'text': 'By running tox in the command line!', 'meta': {'question': 'blah blah blah'}},
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{'name': 'blah blah blah', 'text': 'By running tox in the command line!', 'meta': {'question': 'blah blah blah'}},
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{'name': 'blah blah blah', 'text': 'By running tox in the command line!', 'meta': {'question': 'blah blah blah'}},
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{'name': 'blah blah blah', 'text': 'By running tox in the command line!', 'meta': {'question': 'blah blah blah'}},
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{'name': 'blah blah blah', 'text': 'By running tox in the command line!', 'meta': {'question': 'blah blah blah'}},
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{'name': 'blah blah blah', 'text': 'By running tox in the command line!', 'meta': {'question': 'blah blah blah'}},
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]
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retriever = EmbeddingRetriever(document_store=document_store, embedding_model="deepset/sentence_bert", gpu=False)
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embedded = []
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for doc in documents:
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doc['embedding'] = retriever.create_embedding([doc['meta']['question']])[0]
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embedded.append(doc)
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document_store.write_documents(embedded)
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finder = Finder(reader=None, retriever=retriever)
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prediction = finder.get_answers_via_similar_questions(question="How to test this?", top_k_retriever=1)
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assert len(prediction.get('answers', [])) == 1
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