docling/tests/test_options.py
Peter W. J. Staar cfdf4cea25
feat: new vlm-models support (#1570)
* feat: adding new vlm-models support

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* fixed the transformers

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* got microsoft/Phi-4-multimodal-instruct to work

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* working on vlm's

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* refactoring the VLM part

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* all working, now serious refacgtoring necessary

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* refactoring the download_model

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* added the formulate_prompt

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* pixtral 12b runs via MLX and native transformers

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* added the VlmPredictionToken

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* refactoring minimal_vlm_pipeline

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* fixed the MyPy

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* added pipeline_model_specializations file

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* need to get Phi4 working again ...

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* finalising last points for vlms support

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* fixed the pipeline for Phi4

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* streamlining all code

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* reformatted the code

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* fixing the tests

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* added the html backend to the VLM pipeline

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* fixed the static load_from_doctags

Signed-off-by: Peter Staar <taa@zurich.ibm.com>

* restore stable imports

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* use AutoModelForVision2Seq for Pixtral and review example (including rename)

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* remove unused value

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* refactor instances of VLM models

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* skip compare example in CI

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* use lowercase and uppercase only

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* add new minimal_vlm example and refactor pipeline_options_vlm_model for cleaner import

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* rename pipeline_vlm_model_spec

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* move more argument to options and simplify model init

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* add supported_devices

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* remove not-needed function

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* exclude minimal_vlm

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* missing file

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* add message for transformers version

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* rename to specs

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* use module import and remove MLX from non-darwin

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* remove hf_vlm_model and add extra_generation_args

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* use single HF VLM model class

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* remove torch type

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* add docs for vision models

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

---------

Signed-off-by: Peter Staar <taa@zurich.ibm.com>
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
Co-authored-by: Michele Dolfi <dol@zurich.ibm.com>
2025-06-02 17:01:06 +02:00

173 lines
5.7 KiB
Python

import os
from pathlib import Path
import pytest
from docling.backend.docling_parse_backend import DoclingParseDocumentBackend
from docling.backend.docling_parse_v2_backend import DoclingParseV2DocumentBackend
from docling.backend.docling_parse_v4_backend import DoclingParseV4DocumentBackend
from docling.backend.pypdfium2_backend import PyPdfiumDocumentBackend
from docling.datamodel.accelerator_options import AcceleratorDevice, AcceleratorOptions
from docling.datamodel.base_models import ConversionStatus, InputFormat, QualityGrade
from docling.datamodel.document import ConversionResult
from docling.datamodel.pipeline_options import (
PdfPipelineOptions,
TableFormerMode,
)
from docling.document_converter import DocumentConverter, PdfFormatOption
@pytest.fixture
def test_doc_path():
return Path("./tests/data/pdf/2206.01062.pdf")
def get_converters_with_table_options():
for cell_matching in [True, False]:
for mode in [TableFormerMode.FAST, TableFormerMode.ACCURATE]:
pipeline_options = PdfPipelineOptions()
pipeline_options.do_ocr = False
pipeline_options.do_table_structure = True
pipeline_options.table_structure_options.do_cell_matching = cell_matching
pipeline_options.table_structure_options.mode = mode
converter = DocumentConverter(
format_options={
InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
}
)
yield converter
def test_accelerator_options():
# Check the default options
ao = AcceleratorOptions()
assert ao.num_threads == 4, "Wrong default num_threads"
assert ao.device == AcceleratorDevice.AUTO, "Wrong default device"
# Use API
ao2 = AcceleratorOptions(num_threads=2, device=AcceleratorDevice.MPS)
ao3 = AcceleratorOptions(num_threads=3, device=AcceleratorDevice.CUDA)
assert ao2.num_threads == 2
assert ao2.device == AcceleratorDevice.MPS
assert ao3.num_threads == 3
assert ao3.device == AcceleratorDevice.CUDA
# Use envvars (regular + alternative) and default values
os.environ["OMP_NUM_THREADS"] = "1"
ao.__init__()
assert ao.num_threads == 1
assert ao.device == AcceleratorDevice.AUTO
os.environ["DOCLING_DEVICE"] = "cpu"
ao.__init__()
assert ao.device == AcceleratorDevice.CPU
assert ao.num_threads == 1
# Use envvars and override in init
os.environ["DOCLING_DEVICE"] = "cpu"
ao4 = AcceleratorOptions(num_threads=5, device=AcceleratorDevice.MPS)
assert ao4.num_threads == 5
assert ao4.device == AcceleratorDevice.MPS
# Use regular and alternative envvar
os.environ["DOCLING_NUM_THREADS"] = "2"
ao5 = AcceleratorOptions()
assert ao5.num_threads == 2
assert ao5.device == AcceleratorDevice.CPU
# Use wrong values
is_exception = False
try:
os.environ["DOCLING_DEVICE"] = "wrong"
ao5.__init__()
except Exception as ex:
print(ex)
is_exception = True
assert is_exception
# Use misformatted alternative envvar
del os.environ["DOCLING_NUM_THREADS"]
del os.environ["DOCLING_DEVICE"]
os.environ["OMP_NUM_THREADS"] = "wrong"
ao6 = AcceleratorOptions()
assert ao6.num_threads == 4
assert ao6.device == AcceleratorDevice.AUTO
def test_e2e_conversions(test_doc_path):
for converter in get_converters_with_table_options():
print(f"converting {test_doc_path}")
doc_result: ConversionResult = converter.convert(test_doc_path)
assert doc_result.status == ConversionStatus.SUCCESS
def test_page_range(test_doc_path):
converter = DocumentConverter()
doc_result: ConversionResult = converter.convert(test_doc_path, page_range=(9, 9))
assert doc_result.status == ConversionStatus.SUCCESS
assert doc_result.input.page_count == 9
assert doc_result.document.num_pages() == 1
doc_result: ConversionResult = converter.convert(
test_doc_path, page_range=(10, 10), raises_on_error=False
)
assert doc_result.status == ConversionStatus.FAILURE
def test_ocr_coverage_threshold(test_doc_path):
pipeline_options = PdfPipelineOptions()
pipeline_options.do_ocr = True
pipeline_options.ocr_options.bitmap_area_threshold = 1.1
converter = DocumentConverter(
format_options={
InputFormat.PDF: PdfFormatOption(
pipeline_options=pipeline_options,
)
}
)
test_doc_path = Path("./tests/data_scanned/ocr_test.pdf")
doc_result: ConversionResult = converter.convert(test_doc_path)
# this should have generated no results, since we set a very high threshold
assert len(doc_result.document.texts) == 0
def test_parser_backends(test_doc_path):
pipeline_options = PdfPipelineOptions()
pipeline_options.do_ocr = False
pipeline_options.do_table_structure = False
for backend_t in [
DoclingParseV4DocumentBackend,
DoclingParseV2DocumentBackend,
DoclingParseDocumentBackend,
PyPdfiumDocumentBackend,
]:
converter = DocumentConverter(
format_options={
InputFormat.PDF: PdfFormatOption(
pipeline_options=pipeline_options,
backend=backend_t,
)
}
)
test_doc_path = Path("./tests/data/pdf/code_and_formula.pdf")
doc_result: ConversionResult = converter.convert(test_doc_path)
assert doc_result.status == ConversionStatus.SUCCESS
def test_confidence(test_doc_path):
converter = DocumentConverter()
doc_result: ConversionResult = converter.convert(test_doc_path, page_range=(6, 9))
assert doc_result.confidence.mean_grade == QualityGrade.EXCELLENT
assert doc_result.confidence.low_grade == QualityGrade.EXCELLENT