haystack/test/nodes/test_file_converter.py

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import os
import subprocess
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import pytest
from haystack.nodes import (
MarkdownConverter,
DocxToTextConverter,
PDFToTextConverter,
PDFToTextOCRConverter,
TikaConverter,
AzureConverter,
ParsrConverter,
)
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from ..conftest import SAMPLES_PATH
[RAG] Integrate "Retrieval-Augmented Generation" with Haystack (#484) * Adding dummy generator implementation * Adding tutorial to try the model * Committing current non working code * Committing current update where we need to call generate function directly and need to convert embedding to tensor way * Addressing review comments. * Refactoring finder, and implementing rag_generator class. * Refined the implementation of RAGGenerator and now it is in clean shape * Renaming RAGGenerator to RAGenerator * Reverting change from finder.py and addressing review comments * Remove support for RagSequenceForGeneration * Utilizing embed_passage function from DensePassageRetriever * Adding sample test data to verify generator output * Updating testing script * Updating testing script * Fixing bug related to top_k * Updating latest farm dependency * Comment out farm dependency * Reverting changes from TransformersReader * Adding transformers dataset to compare transformers and haystack generator implementation * Using generator_encoder instead of question_encoder to generate context_input_ids * Adding workaround to install FARM dependency from master branch * Removing unnecessary changes * Fixing generator test * Removing transformers datasets * Fixing generator test * Some cleanup and updating TODO comments * Adding tutorial notebook * Updating tutorials with comments * Explicitly passing token model in RAG test * Addressing review comments * Fixing notebook * Refactoring tests to reduce memory footprint * Split generator tests in separate ci step and before running it reclaim memory by terminating containers * Moving tika dependent test to separate dir * Remove unwanted code * Brining reader under session scope * Farm is now session object hence restoring changes from default value * Updating assert for pdf converter * Dummy commit to trigger CI flow * REducing memory footprint required for generator tests * Fixing mypy issues * Marking test with tika and elasticsearch markers. Reverting changes in CI and pytest splits * reducing changes * Fixing CI * changing elastic search ci * Fixing test error * Disabling return of embedding * Marking generator test as well * Refactoring tutorials * Increasing ES memory to 750M * Trying another fix for ES CI * Reverting CI changes * Splitting tests in CI * Generator and non-generator markers split * Adding pytest.ini to add markers and enable strict-markers option * Reducing elastic search container memory * Simplifying generator test by using documents with embedding directly * Bump up farm to 0.5.0
2020-10-30 18:06:02 +01:00
@pytest.mark.tika
@pytest.mark.parametrize("Converter", [PDFToTextConverter, TikaConverter, PDFToTextOCRConverter])
Add CI for windows runner (#1458) * Feat: Removing use of temp file while downloading archive from url along with adding CI for windows and mac platform * Windows CI by default installing pytorch gpu hence updating CI to pick cpu version * fixing mac cache build issue * updating windows pip install command for torch * another attempt * updating ci * Adding sudo * fixing ls failure on windows * another attempt to fix build issue * Saving env variable of test files * Adding debug log * Github action differ on windows * adding debug * anohter attempt * Windows have different ways to receive env * fixing template * minor fx * Adding debug * Removing use of json * Adding back fromJson * addin toJson * removing print * anohter attempt * disabling parallel run at least for testing * installing docker for mac runner * correcting docker install command * Linux dockers are not suported in windows * Removing mac changes * Upgrading pytorch * using lts pytorch * Separating win and ubuntu * Install java 11 * enabling linux container env * docker cli command * docker cli command * start elastic service * List all service * correcting service name * Attempt to fix multiple test run * convert to json * another attempt to check * Updating build cache step * attempt * Add tika * Separating windows CI * Changing CI name * Skipping test which does not work in windows * Skipping tests for windows * create cleanup function in conftest * adding skipif marker on tests * Run windows PR on only push to master * Addressing review comments * Enabling windows ci for this PR * Tika init is being called when importing tika function * handling tika import issue * handling tika import issue in test * Fixing import issue * removing tika fixure * Removing fixture from tests * Disable windows ci on pull request * Add back extra pytorch install step Co-authored-by: Malte Pietsch <malte.pietsch@deepset.ai>
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def test_convert(Converter):
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converter = Converter()
document = converter.run(file_paths=SAMPLES_PATH / "pdf" / "sample_pdf_1.pdf")[0]["documents"][0]
pages = document.content.split("\f")
assert (
len(pages) != 1 and pages[0] != ""
), f'{type(converter).__name__} did return a single empty page indicating a potential issue with your installed poppler version. Try installing via "conda install -c conda-forge poppler" and check test_pdftoppm_command_format()'
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assert len(pages) == 4 # the sample PDF file has four pages.
assert pages[0] != "" # the page 1 of PDF contains text.
assert pages[2] == "" # the page 3 of PDF file is empty.
# assert text is retained from the document.
# As whitespace can differ (\n," ", etc.), we standardize all to simple whitespace
page_standard_whitespace = " ".join(pages[0].split())
assert "Adobe Systems made the PDF specification available free of charge in 1993." in page_standard_whitespace
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def test_pdftoppm_command_format():
# Haystack's PDFToTextOCRConverter uses pdf2image, which calls pdftoppm internally.
# Some installations of pdftoppm are incompatible with Haystack and won't raise an error but just return empty converted documents
# This test runs pdftoppm directly to check whether pdftoppm accepts the command format that pdf2image uses in Haystack
proc = subprocess.Popen(
["pdftoppm", f"{SAMPLES_PATH}/pdf/sample_pdf_1.pdf"], stdout=subprocess.PIPE, stderr=subprocess.PIPE
)
out, err = proc.communicate()
# If usage info of pdftoppm is sent to stderr then it's because Haystack's pdf2image uses an incompatible command format
assert (
not err
), 'Your installation of poppler is incompatible with Haystack. Try installing via "conda install -c conda-forge poppler"'
@pytest.mark.parametrize("Converter", [PDFToTextConverter])
def test_pdf_encoding(Converter):
converter = Converter()
document = converter.run(file_paths=SAMPLES_PATH / "pdf" / "sample_pdf_2.pdf")[0]["documents"][0]
assert "ɪ" in document.content
document = converter.run(file_paths=SAMPLES_PATH / "pdf" / "sample_pdf_2.pdf", encoding="Latin1")[0]["documents"][0]
assert "ɪ" not in document.content
@pytest.mark.parametrize("Converter", [PDFToTextConverter])
def test_pdf_ligatures(Converter):
converter = Converter()
document = converter.run(file_paths=SAMPLES_PATH / "pdf" / "sample_pdf_2.pdf")[0]["documents"][0]
assert "" not in document.content
assert "ɪ" in document.content
document = converter.run(file_paths=SAMPLES_PATH / "pdf" / "sample_pdf_2.pdf", known_ligatures={})[0]["documents"][
0
]
assert "" in document.content
assert "ɪ" in document.content
document = converter.run(file_paths=SAMPLES_PATH / "pdf" / "sample_pdf_2.pdf", known_ligatures={"ɪ": "i"})[0][
"documents"
][0]
assert "" in document.content
assert "ɪ" not in document.content
[RAG] Integrate "Retrieval-Augmented Generation" with Haystack (#484) * Adding dummy generator implementation * Adding tutorial to try the model * Committing current non working code * Committing current update where we need to call generate function directly and need to convert embedding to tensor way * Addressing review comments. * Refactoring finder, and implementing rag_generator class. * Refined the implementation of RAGGenerator and now it is in clean shape * Renaming RAGGenerator to RAGenerator * Reverting change from finder.py and addressing review comments * Remove support for RagSequenceForGeneration * Utilizing embed_passage function from DensePassageRetriever * Adding sample test data to verify generator output * Updating testing script * Updating testing script * Fixing bug related to top_k * Updating latest farm dependency * Comment out farm dependency * Reverting changes from TransformersReader * Adding transformers dataset to compare transformers and haystack generator implementation * Using generator_encoder instead of question_encoder to generate context_input_ids * Adding workaround to install FARM dependency from master branch * Removing unnecessary changes * Fixing generator test * Removing transformers datasets * Fixing generator test * Some cleanup and updating TODO comments * Adding tutorial notebook * Updating tutorials with comments * Explicitly passing token model in RAG test * Addressing review comments * Fixing notebook * Refactoring tests to reduce memory footprint * Split generator tests in separate ci step and before running it reclaim memory by terminating containers * Moving tika dependent test to separate dir * Remove unwanted code * Brining reader under session scope * Farm is now session object hence restoring changes from default value * Updating assert for pdf converter * Dummy commit to trigger CI flow * REducing memory footprint required for generator tests * Fixing mypy issues * Marking test with tika and elasticsearch markers. Reverting changes in CI and pytest splits * reducing changes * Fixing CI * changing elastic search ci * Fixing test error * Disabling return of embedding * Marking generator test as well * Refactoring tutorials * Increasing ES memory to 750M * Trying another fix for ES CI * Reverting CI changes * Splitting tests in CI * Generator and non-generator markers split * Adding pytest.ini to add markers and enable strict-markers option * Reducing elastic search container memory * Simplifying generator test by using documents with embedding directly * Bump up farm to 0.5.0
2020-10-30 18:06:02 +01:00
@pytest.mark.tika
2020-08-17 11:21:09 +02:00
@pytest.mark.parametrize("Converter", [PDFToTextConverter, TikaConverter])
Add CI for windows runner (#1458) * Feat: Removing use of temp file while downloading archive from url along with adding CI for windows and mac platform * Windows CI by default installing pytorch gpu hence updating CI to pick cpu version * fixing mac cache build issue * updating windows pip install command for torch * another attempt * updating ci * Adding sudo * fixing ls failure on windows * another attempt to fix build issue * Saving env variable of test files * Adding debug log * Github action differ on windows * adding debug * anohter attempt * Windows have different ways to receive env * fixing template * minor fx * Adding debug * Removing use of json * Adding back fromJson * addin toJson * removing print * anohter attempt * disabling parallel run at least for testing * installing docker for mac runner * correcting docker install command * Linux dockers are not suported in windows * Removing mac changes * Upgrading pytorch * using lts pytorch * Separating win and ubuntu * Install java 11 * enabling linux container env * docker cli command * docker cli command * start elastic service * List all service * correcting service name * Attempt to fix multiple test run * convert to json * another attempt to check * Updating build cache step * attempt * Add tika * Separating windows CI * Changing CI name * Skipping test which does not work in windows * Skipping tests for windows * create cleanup function in conftest * adding skipif marker on tests * Run windows PR on only push to master * Addressing review comments * Enabling windows ci for this PR * Tika init is being called when importing tika function * handling tika import issue * handling tika import issue in test * Fixing import issue * removing tika fixure * Removing fixture from tests * Disable windows ci on pull request * Add back extra pytorch install step Co-authored-by: Malte Pietsch <malte.pietsch@deepset.ai>
2021-10-29 13:52:28 +05:30
def test_table_removal(Converter):
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converter = Converter(remove_numeric_tables=True)
document = converter.convert(file_path=SAMPLES_PATH / "pdf" / "sample_pdf_1.pdf")[0]
pages = document.content.split("\f")
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# assert numeric rows are removed from the table.
assert "324" not in pages[0]
assert "54x growth" not in pages[0]
[RAG] Integrate "Retrieval-Augmented Generation" with Haystack (#484) * Adding dummy generator implementation * Adding tutorial to try the model * Committing current non working code * Committing current update where we need to call generate function directly and need to convert embedding to tensor way * Addressing review comments. * Refactoring finder, and implementing rag_generator class. * Refined the implementation of RAGGenerator and now it is in clean shape * Renaming RAGGenerator to RAGenerator * Reverting change from finder.py and addressing review comments * Remove support for RagSequenceForGeneration * Utilizing embed_passage function from DensePassageRetriever * Adding sample test data to verify generator output * Updating testing script * Updating testing script * Fixing bug related to top_k * Updating latest farm dependency * Comment out farm dependency * Reverting changes from TransformersReader * Adding transformers dataset to compare transformers and haystack generator implementation * Using generator_encoder instead of question_encoder to generate context_input_ids * Adding workaround to install FARM dependency from master branch * Removing unnecessary changes * Fixing generator test * Removing transformers datasets * Fixing generator test * Some cleanup and updating TODO comments * Adding tutorial notebook * Updating tutorials with comments * Explicitly passing token model in RAG test * Addressing review comments * Fixing notebook * Refactoring tests to reduce memory footprint * Split generator tests in separate ci step and before running it reclaim memory by terminating containers * Moving tika dependent test to separate dir * Remove unwanted code * Brining reader under session scope * Farm is now session object hence restoring changes from default value * Updating assert for pdf converter * Dummy commit to trigger CI flow * REducing memory footprint required for generator tests * Fixing mypy issues * Marking test with tika and elasticsearch markers. Reverting changes in CI and pytest splits * reducing changes * Fixing CI * changing elastic search ci * Fixing test error * Disabling return of embedding * Marking generator test as well * Refactoring tutorials * Increasing ES memory to 750M * Trying another fix for ES CI * Reverting CI changes * Splitting tests in CI * Generator and non-generator markers split * Adding pytest.ini to add markers and enable strict-markers option * Reducing elastic search container memory * Simplifying generator test by using documents with embedding directly * Bump up farm to 0.5.0
2020-10-30 18:06:02 +01:00
@pytest.mark.tika
2020-08-17 11:21:09 +02:00
@pytest.mark.parametrize("Converter", [PDFToTextConverter, TikaConverter])
Add CI for windows runner (#1458) * Feat: Removing use of temp file while downloading archive from url along with adding CI for windows and mac platform * Windows CI by default installing pytorch gpu hence updating CI to pick cpu version * fixing mac cache build issue * updating windows pip install command for torch * another attempt * updating ci * Adding sudo * fixing ls failure on windows * another attempt to fix build issue * Saving env variable of test files * Adding debug log * Github action differ on windows * adding debug * anohter attempt * Windows have different ways to receive env * fixing template * minor fx * Adding debug * Removing use of json * Adding back fromJson * addin toJson * removing print * anohter attempt * disabling parallel run at least for testing * installing docker for mac runner * correcting docker install command * Linux dockers are not suported in windows * Removing mac changes * Upgrading pytorch * using lts pytorch * Separating win and ubuntu * Install java 11 * enabling linux container env * docker cli command * docker cli command * start elastic service * List all service * correcting service name * Attempt to fix multiple test run * convert to json * another attempt to check * Updating build cache step * attempt * Add tika * Separating windows CI * Changing CI name * Skipping test which does not work in windows * Skipping tests for windows * create cleanup function in conftest * adding skipif marker on tests * Run windows PR on only push to master * Addressing review comments * Enabling windows ci for this PR * Tika init is being called when importing tika function * handling tika import issue * handling tika import issue in test * Fixing import issue * removing tika fixure * Removing fixture from tests * Disable windows ci on pull request * Add back extra pytorch install step Co-authored-by: Malte Pietsch <malte.pietsch@deepset.ai>
2021-10-29 13:52:28 +05:30
def test_language_validation(Converter, caplog):
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converter = Converter(valid_languages=["en"])
converter.convert(file_path=SAMPLES_PATH / "pdf" / "sample_pdf_1.pdf")
assert "samples/pdf/sample_pdf_1.pdf is not one of ['en']." not in caplog.text
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converter = Converter(valid_languages=["de"])
converter.convert(file_path=SAMPLES_PATH / "pdf" / "sample_pdf_1.pdf")
assert "samples/pdf/sample_pdf_1.pdf is not one of ['de']." in caplog.text
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def test_docx_converter():
converter = DocxToTextConverter()
document = converter.convert(file_path=SAMPLES_PATH / "docx" / "sample_docx.docx")[0]
assert document.content.startswith("Sample Docx File")
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def test_markdown_converter():
converter = MarkdownConverter()
document = converter.convert(file_path=SAMPLES_PATH / "markdown" / "sample.md")[0]
assert document.content.startswith("What to build with Haystack")
def test_azure_converter():
# Check if Form Recognizer endpoint and credential key in environment variables
if "AZURE_FORMRECOGNIZER_ENDPOINT" in os.environ and "AZURE_FORMRECOGNIZER_KEY" in os.environ:
converter = AzureConverter(
endpoint=os.environ["AZURE_FORMRECOGNIZER_ENDPOINT"],
credential_key=os.environ["AZURE_FORMRECOGNIZER_KEY"],
save_json=True,
)
docs = converter.convert(file_path=SAMPLES_PATH / "pdf" / "sample_pdf_1.pdf")
assert len(docs) == 2
assert docs[0].content_type == "table"
assert docs[0].content.shape[0] == 4 # number of rows
assert docs[0].content.shape[1] == 5 # number of columns, Form Recognizer assumes there are 5 columns
assert list(docs[0].content.columns) == ["", "Column 1", "", "Column 2", "Column 3"]
assert list(docs[0].content.iloc[3]) == ["D", "$54.35", "", "$6345.", ""]
assert (
docs[0].meta["preceding_context"] == "specification. These proprietary technologies are not "
"standardized and their\nspecification is published only on "
"Adobe's website. Many of them are also not\nsupported by "
"popular third-party implementations of PDF."
)
assert docs[0].meta["following_context"] == ""
assert docs[1].content_type == "text"
assert docs[1].content.startswith("A sample PDF file")
def test_parsr_converter():
converter = ParsrConverter()
docs = converter.convert(file_path=str((SAMPLES_PATH / "pdf" / "sample_pdf_1.pdf").absolute()))
assert len(docs) == 2
assert docs[0].content_type == "table"
assert docs[0].content.shape[0] == 4 # number of rows
assert docs[0].content.shape[1] == 4
assert list(docs[0].content.columns) == ["", "Column 1", "Column 2", "Column 3"]
assert list(docs[0].content.iloc[3]) == ["D", "$54.35", "$6345.", ""]
assert (
docs[0].meta["preceding_context"] == "specification. These proprietary technologies are not "
"standardized and their\nspecification is published only on "
"Adobe's website. Many of them are also not\nsupported by popular "
"third-party implementations of PDF."
)
assert docs[0].meta["following_context"] == ""
assert docs[1].content_type == "text"
assert docs[1].content.startswith("A sample PDF file")
assert docs[1].content.endswith("Page 4 of Sample PDF\n… the page 3 is empty.")