mirror of
https://github.com/deepset-ai/haystack.git
synced 2025-07-24 01:10:45 +00:00
59608ca474
* Unify CI tests (from #2466) * Update Documentation & Code Style * Change folder names * Fix markers list * Remove marker 'slow', replaced with 'integration' * Soften children check * Start ES first so it has time to boot while Python is setup * Run the full workflow * Try to make pip upgrade on Windows * Set KG tests as integration * Update Documentation & Code Style * typo * faster pylint * Make Pylint use the cache * filter diff files for pylint * debug pylint statement * revert pylint changes * Remove path from asserted log (fails on Windows) * Skip preprocessor test on Windows * Tackling Windows specific failures * Fix pytest command for windows suites * Remove \ from command * Move poppler test into integration * Skip opensearch test on windows * Add tolerance in reader sas score for Windows * Another pytorch approx * Raise time limit for unit tests :( * Skip poppler test on Windows CI * Specify to pull with FF only in docs check * temporarily run the docs check immediately * Allow merge commit for now * Try without fetch depth * Accelerating test * Accelerating test * Add repository and ref alongside fetch-depth * Separate out code&docs check from tests * Use setup-python cache * Delete custom action * Remove the pull step in the docs check, will find a way to run on bot commits * Add requirements.txt in .github for caching * Actually install dependencies * Change deps group for pylint * Unclear why the requirements.txt is still required :/ * Fix the code check python setup * Install all deps for pylint * Make the autoformat check depend on tests and doc updates workflows * Try installing dependencies in another order * Try again to install the deps * quoting the paths * Ad back the requirements * Try again to install rest_api and ui * Change deps group * Duplicate haystack install line * See if the cache is the problem * Disable also in mypy, who knows * split the install step * Split install step everywhere * Revert "Separate out code&docs check from tests" This reverts commit 1cd59b15ffc5b984e1d642dcbf4c8ccc2bb6c9bd. * Add back the action * Proactive support for audio (see text2speech branch) * Fix label generator tests * Remove install of libsndfile1 on win temporarily * exclude audio tests on win * install ffmpeg for integration tests Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
82 lines
3.8 KiB
Python
82 lines
3.8 KiB
Python
import pytest
|
|
|
|
from haystack.pipelines import TranslationWrapperPipeline, ExtractiveQAPipeline
|
|
|
|
from haystack.schema import Answer
|
|
|
|
|
|
@pytest.mark.integration
|
|
@pytest.mark.parametrize("retriever_with_docs", ["tfidf"], indirect=True)
|
|
def test_extractive_qa_answers(reader, retriever_with_docs, document_store_with_docs):
|
|
pipeline = ExtractiveQAPipeline(reader=reader, retriever=retriever_with_docs)
|
|
prediction = pipeline.run(query="Who lives in Berlin?", params={"Retriever": {"top_k": 10}, "Reader": {"top_k": 3}})
|
|
assert prediction is not None
|
|
assert type(prediction["answers"][0]) == Answer
|
|
assert prediction["query"] == "Who lives in Berlin?"
|
|
assert prediction["answers"][0].answer == "Carla"
|
|
assert prediction["answers"][0].score <= 1
|
|
assert prediction["answers"][0].score >= 0
|
|
assert prediction["answers"][0].meta["meta_field"] == "test1"
|
|
assert prediction["answers"][0].context == "My name is Carla and I live in Berlin"
|
|
|
|
assert len(prediction["answers"]) == 3
|
|
|
|
|
|
@pytest.mark.integration
|
|
@pytest.mark.parametrize("retriever_with_docs", ["tfidf"], indirect=True)
|
|
def test_extractive_qa_answers_without_normalized_scores(reader_without_normalized_scores, retriever_with_docs):
|
|
pipeline = ExtractiveQAPipeline(reader=reader_without_normalized_scores, retriever=retriever_with_docs)
|
|
prediction = pipeline.run(query="Who lives in Berlin?", params={"Reader": {"top_k": 3}})
|
|
assert prediction is not None
|
|
assert prediction["query"] == "Who lives in Berlin?"
|
|
assert prediction["answers"][0].answer == "Carla"
|
|
assert prediction["answers"][0].score <= 11
|
|
assert prediction["answers"][0].score >= 10
|
|
assert prediction["answers"][0].meta["meta_field"] == "test1"
|
|
assert prediction["answers"][0].context == "My name is Carla and I live in Berlin"
|
|
|
|
assert len(prediction["answers"]) == 3
|
|
|
|
|
|
@pytest.mark.parametrize("retriever_with_docs", ["tfidf"], indirect=True)
|
|
def test_extractive_qa_offsets(reader, retriever_with_docs):
|
|
pipeline = ExtractiveQAPipeline(reader=reader, retriever=retriever_with_docs)
|
|
prediction = pipeline.run(query="Who lives in Berlin?", params={"Retriever": {"top_k": 5}})
|
|
|
|
start = prediction["answers"][0].offsets_in_context[0].start
|
|
end = prediction["answers"][0].offsets_in_context[0].end
|
|
|
|
assert start == 11
|
|
assert end == 16
|
|
|
|
assert prediction["answers"][0].context[start:end] == prediction["answers"][0].answer
|
|
|
|
|
|
@pytest.mark.integration
|
|
@pytest.mark.parametrize("retriever_with_docs", ["tfidf"], indirect=True)
|
|
def test_extractive_qa_answers_single_result(reader, retriever_with_docs):
|
|
pipeline = ExtractiveQAPipeline(reader=reader, retriever=retriever_with_docs)
|
|
query = "testing finder"
|
|
prediction = pipeline.run(query=query, params={"Retriever": {"top_k": 1}, "Reader": {"top_k": 1}})
|
|
assert prediction is not None
|
|
assert len(prediction["answers"]) == 1
|
|
|
|
|
|
@pytest.mark.integration
|
|
@pytest.mark.parametrize("retriever_with_docs", ["tfidf"], indirect=True)
|
|
@pytest.mark.parametrize("reader", ["farm"], indirect=True)
|
|
def test_extractive_qa_answers_with_translator(reader, retriever_with_docs, en_to_de_translator, de_to_en_translator):
|
|
base_pipeline = ExtractiveQAPipeline(reader=reader, retriever=retriever_with_docs)
|
|
pipeline = TranslationWrapperPipeline(
|
|
input_translator=de_to_en_translator, output_translator=en_to_de_translator, pipeline=base_pipeline
|
|
)
|
|
|
|
prediction = pipeline.run(query="Wer lebt in Berlin?", params={"Reader": {"top_k": 3}})
|
|
assert prediction is not None
|
|
assert prediction["query"] == "Wer lebt in Berlin?"
|
|
assert "Carla" in prediction["answers"][0].answer
|
|
assert prediction["answers"][0].score <= 1
|
|
assert prediction["answers"][0].score >= 0
|
|
assert prediction["answers"][0].meta["meta_field"] == "test1"
|
|
assert prediction["answers"][0].context == "My name is Carla and I live in Berlin"
|