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* Add DoclingParseV3 backend implementation Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Use docling-core with docling-parse types Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Fixes and test updates Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Fix streams Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Fix streams Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Reset tests Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * update test cases Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * update test units Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Add back DoclingParse v1 backend, pipeline options Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Update locks Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * fix: update docling-core to 2.22.0 Update dependency library docling-core to latest release 2.22.0 Fix regression tests and ground truth files Signed-off-by: Cesar Berrospi Ramis <75900930+ceberam@users.noreply.github.com> * Ground-truth files updated Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Update tests, use TextCell.from_ocr property Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Text fixes, new test data Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Rename docling backend to v4 Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Test all backends, fixes Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Reset all tests to use docling-parse v1 for now Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Fixes for DPv4 backend init, better test coverage Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * test_input_doc use default backend Signed-off-by: Christoph Auer <cau@zurich.ibm.com> --------- Signed-off-by: Christoph Auer <cau@zurich.ibm.com> Signed-off-by: Cesar Berrospi Ramis <75900930+ceberam@users.noreply.github.com> Co-authored-by: Cesar Berrospi Ramis <75900930+ceberam@users.noreply.github.com>
86 lines
2.5 KiB
Python
86 lines
2.5 KiB
Python
import json
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import os
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from pathlib import Path
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from pytest import warns
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from docling.datamodel.base_models import InputFormat
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from docling.datamodel.document import ConversionResult, DoclingDocument
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from docling.document_converter import DocumentConverter
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from .test_data_gen_flag import GEN_TEST_DATA
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from .verify_utils import verify_document, verify_export
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GENERATE = GEN_TEST_DATA
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def get_csv_paths():
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# Define the directory you want to search
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directory = Path(f"./tests/data/csv/")
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# List all CSV files in the directory and its subdirectories
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return sorted(directory.rglob("*.csv"))
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def get_csv_path(name: str):
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# Return the matching CSV file path
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return Path(f"./tests/data/csv/{name}.csv")
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def get_converter():
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converter = DocumentConverter(allowed_formats=[InputFormat.CSV])
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return converter
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def test_e2e_valid_csv_conversions():
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valid_csv_paths = get_csv_paths()
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converter = get_converter()
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for csv_path in valid_csv_paths:
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print(f"converting {csv_path}")
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gt_path = csv_path.parent.parent / "groundtruth" / "docling_v2" / csv_path.name
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conv_result: ConversionResult = converter.convert(csv_path)
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doc: DoclingDocument = conv_result.document
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pred_md: str = doc.export_to_markdown()
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assert verify_export(pred_md, str(gt_path) + ".md"), "export to md"
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pred_itxt: str = doc._export_to_indented_text(
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max_text_len=70, explicit_tables=False
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)
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assert verify_export(
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pred_itxt, str(gt_path) + ".itxt"
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), "export to indented-text"
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assert verify_document(
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pred_doc=doc,
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gtfile=str(gt_path) + ".json",
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generate=GENERATE,
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), "export to json"
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def test_e2e_invalid_csv_conversions():
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csv_too_few_columns = get_csv_path("csv-too-few-columns")
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csv_too_many_columns = get_csv_path("csv-too-many-columns")
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csv_inconsistent_header = get_csv_path("csv-inconsistent-header")
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converter = get_converter()
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print(f"converting {csv_too_few_columns}")
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with warns(UserWarning, match="Inconsistent column lengths"):
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converter.convert(csv_too_few_columns)
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print(f"converting {csv_too_many_columns}")
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with warns(UserWarning, match="Inconsistent column lengths"):
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converter.convert(csv_too_many_columns)
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print(f"converting {csv_inconsistent_header}")
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with warns(UserWarning, match="Inconsistent column lengths"):
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converter.convert(csv_inconsistent_header)
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