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feat: Support audio input (#1763)
* scaffolding in place Signed-off-by: Peter Staar <taa@zurich.ibm.com> * doing scaffolding for audio pipeline Signed-off-by: Peter Staar <taa@zurich.ibm.com> * WIP: got first transcription working Signed-off-by: Peter Staar <taa@zurich.ibm.com> * all working, time to start cleaning up Signed-off-by: Peter Staar <taa@zurich.ibm.com> * first working ASR pipeline Signed-off-by: Peter Staar <taa@zurich.ibm.com> * added openai-whisper as a first transcription model Signed-off-by: Peter Staar <taa@zurich.ibm.com> * updating with asr_options Signed-off-by: Peter Staar <taa@zurich.ibm.com> * finalised the first working ASR pipeline with Whisper Signed-off-by: Peter Staar <taa@zurich.ibm.com> * use whisper from the latest git commit Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * Update docling/datamodel/pipeline_options.py Co-authored-by: Michele Dolfi <97102151+dolfim-ibm@users.noreply.github.com> Signed-off-by: Peter W. J. Staar <91719829+PeterStaar-IBM@users.noreply.github.com> * Update docling/datamodel/pipeline_options.py Co-authored-by: Michele Dolfi <97102151+dolfim-ibm@users.noreply.github.com> Signed-off-by: Peter W. J. Staar <91719829+PeterStaar-IBM@users.noreply.github.com> * updated comment Signed-off-by: Peter Staar <taa@zurich.ibm.com> * AudioBackend -> DummyBackend Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * file rename Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Rename to NoOpBackend, add test for ASR pipeline Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Support every format in NoOpBackend Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Add missing audio file and test Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Install ffmpeg system dependency for ASR test Signed-off-by: Christoph Auer <cau@zurich.ibm.com> --------- Signed-off-by: Peter Staar <taa@zurich.ibm.com> Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> Signed-off-by: Peter W. J. Staar <91719829+PeterStaar-IBM@users.noreply.github.com> Signed-off-by: Christoph Auer <cau@zurich.ibm.com> Co-authored-by: Michele Dolfi <dol@zurich.ibm.com> Co-authored-by: Michele Dolfi <97102151+dolfim-ibm@users.noreply.github.com> Co-authored-by: Christoph Auer <cau@zurich.ibm.com>
This commit is contained in:
Peter W. J. Staar
GitHub
parent
d26dac61a8
commit
1557e7ce3e
4
.github/workflows/checks.yml
vendored
4
.github/workflows/checks.yml
vendored
@ -22,8 +22,8 @@ jobs:
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python-version: ['3.9', '3.10', '3.11', '3.12', '3.13']
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steps:
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- uses: actions/checkout@v4
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- name: Install tesseract
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run: sudo apt-get update && sudo apt-get install -y tesseract-ocr tesseract-ocr-eng tesseract-ocr-fra tesseract-ocr-deu tesseract-ocr-spa tesseract-ocr-script-latn libleptonica-dev libtesseract-dev pkg-config
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- name: Install tesseract and ffmpeg
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run: sudo apt-get update && sudo apt-get install -y ffmpeg tesseract-ocr tesseract-ocr-eng tesseract-ocr-fra tesseract-ocr-deu tesseract-ocr-spa tesseract-ocr-script-latn libleptonica-dev libtesseract-dev pkg-config
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- name: Set TESSDATA_PREFIX
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run: |
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echo "TESSDATA_PREFIX=$(dpkg -L tesseract-ocr-eng | grep tessdata$)" >> "$GITHUB_ENV"
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51
docling/backend/noop_backend.py
Normal file
51
docling/backend/noop_backend.py
Normal file
@ -0,0 +1,51 @@
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import logging
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from io import BytesIO
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from pathlib import Path
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from typing import Set, Union
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from docling.backend.abstract_backend import AbstractDocumentBackend
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from docling.datamodel.base_models import InputFormat
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from docling.datamodel.document import InputDocument
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_log = logging.getLogger(__name__)
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class NoOpBackend(AbstractDocumentBackend):
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"""
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A no-op backend that only validates input existence.
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Used e.g. for audio files where actual processing is handled by the ASR pipeline.
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"""
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def __init__(self, in_doc: "InputDocument", path_or_stream: Union[BytesIO, Path]):
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super().__init__(in_doc, path_or_stream)
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_log.debug(f"NoOpBackend initialized for: {path_or_stream}")
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# Validate input
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try:
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if isinstance(self.path_or_stream, BytesIO):
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# Check if stream has content
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self.valid = len(self.path_or_stream.getvalue()) > 0
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_log.debug(
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f"BytesIO stream length: {len(self.path_or_stream.getvalue())}"
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)
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elif isinstance(self.path_or_stream, Path):
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# Check if file exists
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self.valid = self.path_or_stream.exists()
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_log.debug(f"File exists: {self.valid}")
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else:
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self.valid = False
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except Exception as e:
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_log.error(f"NoOpBackend validation failed: {e}")
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self.valid = False
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def is_valid(self) -> bool:
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return self.valid
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@classmethod
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def supports_pagination(cls) -> bool:
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return False
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@classmethod
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def supported_formats(cls) -> Set[InputFormat]:
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return set(InputFormat)
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@ -29,6 +29,15 @@ from docling.backend.docling_parse_v4_backend import DoclingParseV4DocumentBacke
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from docling.backend.pdf_backend import PdfDocumentBackend
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from docling.backend.pypdfium2_backend import PyPdfiumDocumentBackend
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from docling.datamodel.accelerator_options import AcceleratorDevice, AcceleratorOptions
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from docling.datamodel.asr_model_specs import (
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WHISPER_BASE,
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WHISPER_LARGE,
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WHISPER_MEDIUM,
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WHISPER_SMALL,
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WHISPER_TINY,
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WHISPER_TURBO,
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AsrModelType,
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)
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from docling.datamodel.base_models import (
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ConversionStatus,
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FormatToExtensions,
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@ -37,12 +46,14 @@ from docling.datamodel.base_models import (
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)
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from docling.datamodel.document import ConversionResult
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from docling.datamodel.pipeline_options import (
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AsrPipelineOptions,
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EasyOcrOptions,
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OcrOptions,
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PaginatedPipelineOptions,
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PdfBackend,
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PdfPipeline,
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PdfPipelineOptions,
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PipelineOptions,
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ProcessingPipeline,
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TableFormerMode,
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VlmPipelineOptions,
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)
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@ -54,8 +65,14 @@ from docling.datamodel.vlm_model_specs import (
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SMOLDOCLING_TRANSFORMERS,
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VlmModelType,
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)
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from docling.document_converter import DocumentConverter, FormatOption, PdfFormatOption
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from docling.document_converter import (
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AudioFormatOption,
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DocumentConverter,
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FormatOption,
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PdfFormatOption,
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)
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from docling.models.factories import get_ocr_factory
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from docling.pipeline.asr_pipeline import AsrPipeline
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from docling.pipeline.vlm_pipeline import VlmPipeline
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warnings.filterwarnings(action="ignore", category=UserWarning, module="pydantic|torch")
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@ -296,13 +313,17 @@ def convert( # noqa: C901
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),
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] = ImageRefMode.EMBEDDED,
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pipeline: Annotated[
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PdfPipeline,
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ProcessingPipeline,
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typer.Option(..., help="Choose the pipeline to process PDF or image files."),
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] = PdfPipeline.STANDARD,
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] = ProcessingPipeline.STANDARD,
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vlm_model: Annotated[
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VlmModelType,
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typer.Option(..., help="Choose the VLM model to use with PDF or image files."),
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] = VlmModelType.SMOLDOCLING,
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asr_model: Annotated[
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AsrModelType,
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typer.Option(..., help="Choose the ASR model to use with audio/video files."),
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] = AsrModelType.WHISPER_TINY,
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ocr: Annotated[
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bool,
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typer.Option(
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@ -450,12 +471,14 @@ def convert( # noqa: C901
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),
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] = None,
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):
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log_format = "%(asctime)s\t%(levelname)s\t%(name)s: %(message)s"
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if verbose == 0:
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logging.basicConfig(level=logging.WARNING)
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logging.basicConfig(level=logging.WARNING, format=log_format)
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elif verbose == 1:
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logging.basicConfig(level=logging.INFO)
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logging.basicConfig(level=logging.INFO, format=log_format)
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else:
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logging.basicConfig(level=logging.DEBUG)
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logging.basicConfig(level=logging.DEBUG, format=log_format)
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settings.debug.visualize_cells = debug_visualize_cells
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settings.debug.visualize_layout = debug_visualize_layout
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@ -530,9 +553,12 @@ def convert( # noqa: C901
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ocr_options.lang = ocr_lang_list
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accelerator_options = AcceleratorOptions(num_threads=num_threads, device=device)
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pipeline_options: PaginatedPipelineOptions
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# pipeline_options: PaginatedPipelineOptions
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pipeline_options: PipelineOptions
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if pipeline == PdfPipeline.STANDARD:
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format_options: Dict[InputFormat, FormatOption] = {}
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if pipeline == ProcessingPipeline.STANDARD:
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pipeline_options = PdfPipelineOptions(
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allow_external_plugins=allow_external_plugins,
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enable_remote_services=enable_remote_services,
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@ -574,7 +600,13 @@ def convert( # noqa: C901
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pipeline_options=pipeline_options,
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backend=backend, # pdf_backend
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)
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elif pipeline == PdfPipeline.VLM:
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format_options = {
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InputFormat.PDF: pdf_format_option,
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InputFormat.IMAGE: pdf_format_option,
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}
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elif pipeline == ProcessingPipeline.VLM:
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pipeline_options = VlmPipelineOptions(
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enable_remote_services=enable_remote_services,
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)
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@ -600,13 +632,48 @@ def convert( # noqa: C901
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pipeline_cls=VlmPipeline, pipeline_options=pipeline_options
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)
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format_options = {
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InputFormat.PDF: pdf_format_option,
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InputFormat.IMAGE: pdf_format_option,
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}
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elif pipeline == ProcessingPipeline.ASR:
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pipeline_options = AsrPipelineOptions(
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# enable_remote_services=enable_remote_services,
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# artifacts_path = artifacts_path
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)
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if asr_model == AsrModelType.WHISPER_TINY:
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pipeline_options.asr_options = WHISPER_TINY
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elif asr_model == AsrModelType.WHISPER_SMALL:
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pipeline_options.asr_options = WHISPER_SMALL
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elif asr_model == AsrModelType.WHISPER_MEDIUM:
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pipeline_options.asr_options = WHISPER_MEDIUM
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elif asr_model == AsrModelType.WHISPER_BASE:
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pipeline_options.asr_options = WHISPER_BASE
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elif asr_model == AsrModelType.WHISPER_LARGE:
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pipeline_options.asr_options = WHISPER_LARGE
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elif asr_model == AsrModelType.WHISPER_TURBO:
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pipeline_options.asr_options = WHISPER_TURBO
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else:
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_log.error(f"{asr_model} is not known")
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raise ValueError(f"{asr_model} is not known")
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_log.info(f"pipeline_options: {pipeline_options}")
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audio_format_option = AudioFormatOption(
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pipeline_cls=AsrPipeline,
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pipeline_options=pipeline_options,
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)
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format_options = {
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InputFormat.AUDIO: audio_format_option,
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}
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if artifacts_path is not None:
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pipeline_options.artifacts_path = artifacts_path
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# audio_pipeline_options.artifacts_path = artifacts_path
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format_options: Dict[InputFormat, FormatOption] = {
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InputFormat.PDF: pdf_format_option,
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InputFormat.IMAGE: pdf_format_option,
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}
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doc_converter = DocumentConverter(
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allowed_formats=from_formats,
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format_options=format_options,
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@ -614,6 +681,7 @@ def convert( # noqa: C901
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start_time = time.time()
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_log.info(f"paths: {input_doc_paths}")
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conv_results = doc_converter.convert_all(
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input_doc_paths, headers=parsed_headers, raises_on_error=abort_on_error
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)
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92
docling/datamodel/asr_model_specs.py
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92
docling/datamodel/asr_model_specs.py
Normal file
@ -0,0 +1,92 @@
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import logging
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from enum import Enum
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from pydantic import (
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AnyUrl,
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)
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from docling.datamodel.accelerator_options import AcceleratorDevice
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from docling.datamodel.pipeline_options_asr_model import (
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# AsrResponseFormat,
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# ApiAsrOptions,
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InferenceAsrFramework,
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InlineAsrNativeWhisperOptions,
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TransformersModelType,
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)
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_log = logging.getLogger(__name__)
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WHISPER_TINY = InlineAsrNativeWhisperOptions(
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repo_id="tiny",
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inference_framework=InferenceAsrFramework.WHISPER,
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verbose=True,
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timestamps=True,
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word_timestamps=True,
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temperatue=0.0,
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max_new_tokens=256,
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max_time_chunk=30.0,
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)
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WHISPER_SMALL = InlineAsrNativeWhisperOptions(
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repo_id="small",
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inference_framework=InferenceAsrFramework.WHISPER,
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verbose=True,
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timestamps=True,
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word_timestamps=True,
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temperatue=0.0,
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max_new_tokens=256,
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max_time_chunk=30.0,
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)
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WHISPER_MEDIUM = InlineAsrNativeWhisperOptions(
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repo_id="medium",
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inference_framework=InferenceAsrFramework.WHISPER,
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verbose=True,
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timestamps=True,
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word_timestamps=True,
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temperatue=0.0,
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max_new_tokens=256,
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max_time_chunk=30.0,
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)
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WHISPER_BASE = InlineAsrNativeWhisperOptions(
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repo_id="base",
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inference_framework=InferenceAsrFramework.WHISPER,
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verbose=True,
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timestamps=True,
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word_timestamps=True,
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temperatue=0.0,
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max_new_tokens=256,
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max_time_chunk=30.0,
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)
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WHISPER_LARGE = InlineAsrNativeWhisperOptions(
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repo_id="large",
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inference_framework=InferenceAsrFramework.WHISPER,
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verbose=True,
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timestamps=True,
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word_timestamps=True,
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temperatue=0.0,
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max_new_tokens=256,
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max_time_chunk=30.0,
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)
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WHISPER_TURBO = InlineAsrNativeWhisperOptions(
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repo_id="turbo",
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inference_framework=InferenceAsrFramework.WHISPER,
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verbose=True,
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timestamps=True,
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word_timestamps=True,
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temperatue=0.0,
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max_new_tokens=256,
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max_time_chunk=30.0,
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)
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class AsrModelType(str, Enum):
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WHISPER_TINY = "whisper_tiny"
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WHISPER_SMALL = "whisper_small"
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WHISPER_MEDIUM = "whisper_medium"
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WHISPER_BASE = "whisper_base"
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WHISPER_LARGE = "whisper_large"
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WHISPER_TURBO = "whisper_turbo"
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@ -49,6 +49,7 @@ class InputFormat(str, Enum):
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XML_USPTO = "xml_uspto"
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XML_JATS = "xml_jats"
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JSON_DOCLING = "json_docling"
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AUDIO = "audio"
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class OutputFormat(str, Enum):
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@ -73,6 +74,7 @@ FormatToExtensions: Dict[InputFormat, List[str]] = {
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InputFormat.XLSX: ["xlsx", "xlsm"],
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InputFormat.XML_USPTO: ["xml", "txt"],
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InputFormat.JSON_DOCLING: ["json"],
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InputFormat.AUDIO: ["wav", "mp3"],
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}
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FormatToMimeType: Dict[InputFormat, List[str]] = {
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@ -104,6 +106,7 @@ FormatToMimeType: Dict[InputFormat, List[str]] = {
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],
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InputFormat.XML_USPTO: ["application/xml", "text/plain"],
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InputFormat.JSON_DOCLING: ["application/json"],
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InputFormat.AUDIO: ["audio/x-wav", "audio/mpeg", "audio/wav", "audio/mp3"],
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}
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MimeTypeToFormat: dict[str, list[InputFormat]] = {
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@ -249,7 +249,7 @@ class _DocumentConversionInput(BaseModel):
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backend: Type[AbstractDocumentBackend]
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if format not in format_options.keys():
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_log.error(
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f"Input document {obj.name} does not match any allowed format."
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f"Input document {obj.name} with format {format} does not match any allowed format: ({format_options.keys()})"
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)
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backend = _DummyBackend
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else:
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@ -318,6 +318,8 @@ class _DocumentConversionInput(BaseModel):
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mime = mime or _DocumentConversionInput._detect_csv(content)
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mime = mime or "text/plain"
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formats = MimeTypeToFormat.get(mime, [])
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_log.info(f"detected formats: {formats}")
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if formats:
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if len(formats) == 1 and mime not in ("text/plain"):
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return formats[0]
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@ -11,8 +11,13 @@ from pydantic import (
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)
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from typing_extensions import deprecated
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from docling.datamodel import asr_model_specs
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# Import the following for backwards compatibility
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from docling.datamodel.accelerator_options import AcceleratorDevice, AcceleratorOptions
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from docling.datamodel.pipeline_options_asr_model import (
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InlineAsrOptions,
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)
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from docling.datamodel.pipeline_options_vlm_model import (
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||||
ApiVlmOptions,
|
||||
InferenceFramework,
|
||||
@ -260,6 +265,11 @@ class VlmPipelineOptions(PaginatedPipelineOptions):
|
||||
)
|
||||
|
||||
|
||||
class AsrPipelineOptions(PipelineOptions):
|
||||
asr_options: Union[InlineAsrOptions] = asr_model_specs.WHISPER_TINY
|
||||
artifacts_path: Optional[Union[Path, str]] = None
|
||||
|
||||
|
||||
class PdfPipelineOptions(PaginatedPipelineOptions):
|
||||
"""Options for the PDF pipeline."""
|
||||
|
||||
@ -297,6 +307,7 @@ class PdfPipelineOptions(PaginatedPipelineOptions):
|
||||
)
|
||||
|
||||
|
||||
class PdfPipeline(str, Enum):
|
||||
class ProcessingPipeline(str, Enum):
|
||||
STANDARD = "standard"
|
||||
VLM = "vlm"
|
||||
ASR = "asr"
|
||||
|
||||
57
docling/datamodel/pipeline_options_asr_model.py
Normal file
57
docling/datamodel/pipeline_options_asr_model.py
Normal file
@ -0,0 +1,57 @@
|
||||
from enum import Enum
|
||||
from typing import Any, Dict, List, Literal, Optional, Union
|
||||
|
||||
from pydantic import AnyUrl, BaseModel
|
||||
from typing_extensions import deprecated
|
||||
|
||||
from docling.datamodel.accelerator_options import AcceleratorDevice
|
||||
from docling.datamodel.pipeline_options_vlm_model import (
|
||||
# InferenceFramework,
|
||||
TransformersModelType,
|
||||
)
|
||||
|
||||
|
||||
class BaseAsrOptions(BaseModel):
|
||||
kind: str
|
||||
# prompt: str
|
||||
|
||||
|
||||
class InferenceAsrFramework(str, Enum):
|
||||
# MLX = "mlx" # disabled for now
|
||||
# TRANSFORMERS = "transformers" # disabled for now
|
||||
WHISPER = "whisper"
|
||||
|
||||
|
||||
class InlineAsrOptions(BaseAsrOptions):
|
||||
kind: Literal["inline_model_options"] = "inline_model_options"
|
||||
|
||||
repo_id: str
|
||||
|
||||
verbose: bool = False
|
||||
timestamps: bool = True
|
||||
|
||||
temperature: float = 0.0
|
||||
max_new_tokens: int = 256
|
||||
max_time_chunk: float = 30.0
|
||||
|
||||
torch_dtype: Optional[str] = None
|
||||
supported_devices: List[AcceleratorDevice] = [
|
||||
AcceleratorDevice.CPU,
|
||||
AcceleratorDevice.CUDA,
|
||||
AcceleratorDevice.MPS,
|
||||
]
|
||||
|
||||
@property
|
||||
def repo_cache_folder(self) -> str:
|
||||
return self.repo_id.replace("/", "--")
|
||||
|
||||
|
||||
class InlineAsrNativeWhisperOptions(InlineAsrOptions):
|
||||
inference_framework: InferenceAsrFramework = InferenceAsrFramework.WHISPER
|
||||
|
||||
language: str = "en"
|
||||
supported_devices: List[AcceleratorDevice] = [
|
||||
AcceleratorDevice.CPU,
|
||||
AcceleratorDevice.CUDA,
|
||||
]
|
||||
word_timestamps: bool = True
|
||||
@ -19,6 +19,7 @@ from docling.backend.md_backend import MarkdownDocumentBackend
|
||||
from docling.backend.msexcel_backend import MsExcelDocumentBackend
|
||||
from docling.backend.mspowerpoint_backend import MsPowerpointDocumentBackend
|
||||
from docling.backend.msword_backend import MsWordDocumentBackend
|
||||
from docling.backend.noop_backend import NoOpBackend
|
||||
from docling.backend.xml.jats_backend import JatsDocumentBackend
|
||||
from docling.backend.xml.uspto_backend import PatentUsptoDocumentBackend
|
||||
from docling.datamodel.base_models import (
|
||||
@ -41,6 +42,7 @@ from docling.datamodel.settings import (
|
||||
settings,
|
||||
)
|
||||
from docling.exceptions import ConversionError
|
||||
from docling.pipeline.asr_pipeline import AsrPipeline
|
||||
from docling.pipeline.base_pipeline import BasePipeline
|
||||
from docling.pipeline.simple_pipeline import SimplePipeline
|
||||
from docling.pipeline.standard_pdf_pipeline import StandardPdfPipeline
|
||||
@ -118,6 +120,11 @@ class PdfFormatOption(FormatOption):
|
||||
backend: Type[AbstractDocumentBackend] = DoclingParseV4DocumentBackend
|
||||
|
||||
|
||||
class AudioFormatOption(FormatOption):
|
||||
pipeline_cls: Type = AsrPipeline
|
||||
backend: Type[AbstractDocumentBackend] = NoOpBackend
|
||||
|
||||
|
||||
def _get_default_option(format: InputFormat) -> FormatOption:
|
||||
format_to_default_options = {
|
||||
InputFormat.CSV: FormatOption(
|
||||
@ -156,6 +163,7 @@ def _get_default_option(format: InputFormat) -> FormatOption:
|
||||
InputFormat.JSON_DOCLING: FormatOption(
|
||||
pipeline_cls=SimplePipeline, backend=DoclingJSONBackend
|
||||
),
|
||||
InputFormat.AUDIO: FormatOption(pipeline_cls=AsrPipeline, backend=NoOpBackend),
|
||||
}
|
||||
if (options := format_to_default_options.get(format)) is not None:
|
||||
return options
|
||||
|
||||
253
docling/pipeline/asr_pipeline.py
Normal file
253
docling/pipeline/asr_pipeline.py
Normal file
@ -0,0 +1,253 @@
|
||||
import logging
|
||||
import os
|
||||
import re
|
||||
from io import BytesIO
|
||||
from pathlib import Path
|
||||
from typing import List, Optional, Union, cast
|
||||
|
||||
from docling_core.types.doc import DoclingDocument, DocumentOrigin
|
||||
|
||||
# import whisper # type: ignore
|
||||
# import librosa
|
||||
# import numpy as np
|
||||
# import soundfile as sf # type: ignore
|
||||
from docling_core.types.doc.labels import DocItemLabel
|
||||
from pydantic import BaseModel, Field, validator
|
||||
|
||||
from docling.backend.abstract_backend import AbstractDocumentBackend
|
||||
from docling.backend.noop_backend import NoOpBackend
|
||||
|
||||
# from pydub import AudioSegment # type: ignore
|
||||
# from transformers import WhisperForConditionalGeneration, WhisperProcessor, pipeline
|
||||
from docling.datamodel.accelerator_options import (
|
||||
AcceleratorOptions,
|
||||
)
|
||||
from docling.datamodel.base_models import (
|
||||
ConversionStatus,
|
||||
FormatToMimeType,
|
||||
)
|
||||
from docling.datamodel.document import ConversionResult, InputDocument
|
||||
from docling.datamodel.pipeline_options import (
|
||||
AsrPipelineOptions,
|
||||
)
|
||||
from docling.datamodel.pipeline_options_asr_model import (
|
||||
InlineAsrNativeWhisperOptions,
|
||||
# AsrResponseFormat,
|
||||
InlineAsrOptions,
|
||||
)
|
||||
from docling.datamodel.pipeline_options_vlm_model import (
|
||||
InferenceFramework,
|
||||
)
|
||||
from docling.datamodel.settings import settings
|
||||
from docling.pipeline.base_pipeline import BasePipeline
|
||||
from docling.utils.accelerator_utils import decide_device
|
||||
from docling.utils.profiling import ProfilingScope, TimeRecorder
|
||||
|
||||
_log = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class _ConversationWord(BaseModel):
|
||||
text: str
|
||||
start_time: Optional[float] = Field(
|
||||
None, description="Start time in seconds from video start"
|
||||
)
|
||||
end_time: Optional[float] = Field(
|
||||
None, ge=0, description="End time in seconds from video start"
|
||||
)
|
||||
|
||||
|
||||
class _ConversationItem(BaseModel):
|
||||
text: str
|
||||
start_time: Optional[float] = Field(
|
||||
None, description="Start time in seconds from video start"
|
||||
)
|
||||
end_time: Optional[float] = Field(
|
||||
None, ge=0, description="End time in seconds from video start"
|
||||
)
|
||||
speaker_id: Optional[int] = Field(None, description="Numeric speaker identifier")
|
||||
speaker: Optional[str] = Field(
|
||||
None, description="Speaker name, defaults to speaker-{speaker_id}"
|
||||
)
|
||||
words: Optional[list[_ConversationWord]] = Field(
|
||||
None, description="Individual words with time-stamps"
|
||||
)
|
||||
|
||||
def __lt__(self, other):
|
||||
if not isinstance(other, _ConversationItem):
|
||||
return NotImplemented
|
||||
return self.start_time < other.start_time
|
||||
|
||||
def __eq__(self, other):
|
||||
if not isinstance(other, _ConversationItem):
|
||||
return NotImplemented
|
||||
return self.start_time == other.start_time
|
||||
|
||||
def to_string(self) -> str:
|
||||
"""Format the conversation entry as a string"""
|
||||
result = ""
|
||||
if (self.start_time is not None) and (self.end_time is not None):
|
||||
result += f"[time: {self.start_time}-{self.end_time}] "
|
||||
|
||||
if self.speaker is not None:
|
||||
result += f"[speaker:{self.speaker}] "
|
||||
|
||||
result += self.text
|
||||
return result
|
||||
|
||||
|
||||
class _NativeWhisperModel:
|
||||
def __init__(
|
||||
self,
|
||||
enabled: bool,
|
||||
artifacts_path: Optional[Path],
|
||||
accelerator_options: AcceleratorOptions,
|
||||
asr_options: InlineAsrNativeWhisperOptions,
|
||||
):
|
||||
"""
|
||||
Transcriber using native Whisper.
|
||||
"""
|
||||
self.enabled = enabled
|
||||
|
||||
_log.info(f"artifacts-path: {artifacts_path}")
|
||||
_log.info(f"accelerator_options: {accelerator_options}")
|
||||
|
||||
if self.enabled:
|
||||
try:
|
||||
import whisper # type: ignore
|
||||
except ImportError:
|
||||
raise ImportError(
|
||||
"whisper is not installed. Please install it via `pip install openai-whisper` or do `uv sync --extra asr`."
|
||||
)
|
||||
self.asr_options = asr_options
|
||||
self.max_tokens = asr_options.max_new_tokens
|
||||
self.temperature = asr_options.temperature
|
||||
|
||||
self.device = decide_device(
|
||||
accelerator_options.device,
|
||||
supported_devices=asr_options.supported_devices,
|
||||
)
|
||||
_log.info(f"Available device for Whisper: {self.device}")
|
||||
|
||||
self.model_name = asr_options.repo_id
|
||||
_log.info(f"loading _NativeWhisperModel({self.model_name})")
|
||||
if artifacts_path is not None:
|
||||
_log.info(f"loading {self.model_name} from {artifacts_path}")
|
||||
self.model = whisper.load_model(
|
||||
name=self.model_name,
|
||||
device=self.device,
|
||||
download_root=str(artifacts_path),
|
||||
)
|
||||
else:
|
||||
self.model = whisper.load_model(
|
||||
name=self.model_name, device=self.device
|
||||
)
|
||||
|
||||
self.verbose = asr_options.verbose
|
||||
self.timestamps = asr_options.timestamps
|
||||
self.word_timestamps = asr_options.word_timestamps
|
||||
|
||||
def run(self, conv_res: ConversionResult) -> ConversionResult:
|
||||
audio_path: Path = Path(conv_res.input.file).resolve()
|
||||
|
||||
try:
|
||||
conversation = self.transcribe(audio_path)
|
||||
|
||||
# Ensure we have a proper DoclingDocument
|
||||
origin = DocumentOrigin(
|
||||
filename=conv_res.input.file.name or "audio.wav",
|
||||
mimetype="audio/x-wav",
|
||||
binary_hash=conv_res.input.document_hash,
|
||||
)
|
||||
conv_res.document = DoclingDocument(
|
||||
name=conv_res.input.file.stem or "audio.wav", origin=origin
|
||||
)
|
||||
|
||||
for citem in conversation:
|
||||
conv_res.document.add_text(
|
||||
label=DocItemLabel.TEXT, text=citem.to_string()
|
||||
)
|
||||
|
||||
conv_res.status = ConversionStatus.SUCCESS
|
||||
return conv_res
|
||||
|
||||
except Exception as exc:
|
||||
_log.error(f"Audio tranciption has an error: {exc}")
|
||||
|
||||
conv_res.status = ConversionStatus.FAILURE
|
||||
return conv_res
|
||||
|
||||
def transcribe(self, fpath: Path) -> list[_ConversationItem]:
|
||||
result = self.model.transcribe(
|
||||
str(fpath), verbose=self.verbose, word_timestamps=self.word_timestamps
|
||||
)
|
||||
|
||||
convo: list[_ConversationItem] = []
|
||||
for _ in result["segments"]:
|
||||
item = _ConversationItem(
|
||||
start_time=_["start"], end_time=_["end"], text=_["text"], words=[]
|
||||
)
|
||||
if "words" in _ and self.word_timestamps:
|
||||
item.words = []
|
||||
for __ in _["words"]:
|
||||
item.words.append(
|
||||
_ConversationWord(
|
||||
start_time=__["start"],
|
||||
end_time=__["end"],
|
||||
text=__["word"],
|
||||
)
|
||||
)
|
||||
convo.append(item)
|
||||
|
||||
return convo
|
||||
|
||||
|
||||
class AsrPipeline(BasePipeline):
|
||||
def __init__(self, pipeline_options: AsrPipelineOptions):
|
||||
super().__init__(pipeline_options)
|
||||
self.keep_backend = True
|
||||
|
||||
self.pipeline_options: AsrPipelineOptions = pipeline_options
|
||||
|
||||
artifacts_path: Optional[Path] = None
|
||||
if pipeline_options.artifacts_path is not None:
|
||||
artifacts_path = Path(pipeline_options.artifacts_path).expanduser()
|
||||
elif settings.artifacts_path is not None:
|
||||
artifacts_path = Path(settings.artifacts_path).expanduser()
|
||||
|
||||
if artifacts_path is not None and not artifacts_path.is_dir():
|
||||
raise RuntimeError(
|
||||
f"The value of {artifacts_path=} is not valid. "
|
||||
"When defined, it must point to a folder containing all models required by the pipeline."
|
||||
)
|
||||
|
||||
if isinstance(self.pipeline_options.asr_options, InlineAsrNativeWhisperOptions):
|
||||
asr_options: InlineAsrNativeWhisperOptions = (
|
||||
self.pipeline_options.asr_options
|
||||
)
|
||||
self._model = _NativeWhisperModel(
|
||||
enabled=True, # must be always enabled for this pipeline to make sense.
|
||||
artifacts_path=artifacts_path,
|
||||
accelerator_options=pipeline_options.accelerator_options,
|
||||
asr_options=asr_options,
|
||||
)
|
||||
else:
|
||||
_log.error(f"No model support for {self.pipeline_options.asr_options}")
|
||||
|
||||
def _determine_status(self, conv_res: ConversionResult) -> ConversionStatus:
|
||||
status = ConversionStatus.SUCCESS
|
||||
return status
|
||||
|
||||
@classmethod
|
||||
def get_default_options(cls) -> AsrPipelineOptions:
|
||||
return AsrPipelineOptions()
|
||||
|
||||
def _build_document(self, conv_res: ConversionResult) -> ConversionResult:
|
||||
_log.info(f"start _build_document in AsrPipeline: {conv_res.input.file}")
|
||||
with TimeRecorder(conv_res, "doc_build", scope=ProfilingScope.DOCUMENT):
|
||||
self._model.run(conv_res=conv_res)
|
||||
|
||||
return conv_res
|
||||
|
||||
@classmethod
|
||||
def is_backend_supported(cls, backend: AbstractDocumentBackend):
|
||||
return isinstance(backend, NoOpBackend)
|
||||
@ -99,6 +99,9 @@ rapidocr = [
|
||||
# 'onnxruntime (>=1.7.0,<2.0.0) ; python_version >= "3.10"',
|
||||
# 'onnxruntime (>=1.7.0,<1.20.0) ; python_version < "3.10"',
|
||||
]
|
||||
asr = [
|
||||
"openai-whisper>=20240930",
|
||||
]
|
||||
|
||||
[dependency-groups]
|
||||
dev = [
|
||||
@ -145,6 +148,9 @@ constraints = [
|
||||
package = true
|
||||
default-groups = "all"
|
||||
|
||||
[tool.uv.sources]
|
||||
openai-whisper = { git = "https://github.com/openai/whisper.git", rev = "dd985ac4b90cafeef8712f2998d62c59c3e62d22" }
|
||||
|
||||
[tool.setuptools.packages.find]
|
||||
include = ["docling*"]
|
||||
|
||||
|
||||
BIN
tests/data/audio/sample_10s.mp3
vendored
Normal file
BIN
tests/data/audio/sample_10s.mp3
vendored
Normal file
Binary file not shown.
59
tests/test_asr_pipeline.py
Normal file
59
tests/test_asr_pipeline.py
Normal file
@ -0,0 +1,59 @@
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
|
||||
from docling.datamodel import asr_model_specs
|
||||
from docling.datamodel.base_models import ConversionStatus, InputFormat
|
||||
from docling.datamodel.document import ConversionResult
|
||||
from docling.datamodel.pipeline_options import AsrPipelineOptions
|
||||
from docling.document_converter import AudioFormatOption, DocumentConverter
|
||||
from docling.pipeline.asr_pipeline import AsrPipeline
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def test_audio_path():
|
||||
return Path("./tests/data/audio/sample_10s.mp3")
|
||||
|
||||
|
||||
def get_asr_converter():
|
||||
"""Create a DocumentConverter configured for ASR with whisper_turbo model."""
|
||||
pipeline_options = AsrPipelineOptions()
|
||||
pipeline_options.asr_options = asr_model_specs.WHISPER_TINY
|
||||
|
||||
converter = DocumentConverter(
|
||||
format_options={
|
||||
InputFormat.AUDIO: AudioFormatOption(
|
||||
pipeline_cls=AsrPipeline,
|
||||
pipeline_options=pipeline_options,
|
||||
)
|
||||
}
|
||||
)
|
||||
return converter
|
||||
|
||||
|
||||
def test_asr_pipeline_conversion(test_audio_path):
|
||||
"""Test ASR pipeline conversion using whisper_turbo model on sample_10s.mp3."""
|
||||
# Check if the test audio file exists
|
||||
assert test_audio_path.exists(), f"Test audio file not found: {test_audio_path}"
|
||||
|
||||
converter = get_asr_converter()
|
||||
|
||||
# Convert the audio file
|
||||
doc_result: ConversionResult = converter.convert(test_audio_path)
|
||||
|
||||
# Verify conversion was successful
|
||||
assert doc_result.status == ConversionStatus.SUCCESS, (
|
||||
f"Conversion failed with status: {doc_result.status}"
|
||||
)
|
||||
|
||||
# Verify we have a document
|
||||
assert doc_result.document is not None, "No document was created"
|
||||
|
||||
# Verify we have text content (transcribed audio)
|
||||
texts = doc_result.document.texts
|
||||
assert len(texts) > 0, "No text content found in transcribed audio"
|
||||
|
||||
# Print transcribed text for verification (optional, for debugging)
|
||||
print(f"Transcribed text from {test_audio_path.name}:")
|
||||
for i, text_item in enumerate(texts):
|
||||
print(f" {i + 1}: {text_item.text}")
|
||||
357
uv.lock
generated
357
uv.lock
generated
@ -7,11 +7,14 @@ resolution-markers = [
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'arm64' and sys_platform == 'darwin'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'arm64' and sys_platform == 'darwin'",
|
||||
"python_full_version == '3.10.*' and platform_machine == 'arm64' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12.4' and platform_machine != 'arm64' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.13' and platform_machine != 'arm64' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12.4' and python_full_version < '3.13' and platform_machine != 'arm64' and sys_platform == 'darwin'",
|
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"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'arm64' and sys_platform == 'darwin'",
|
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"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.13' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
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"python_full_version >= '3.12.4' and python_full_version < '3.13' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
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"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
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"(python_full_version >= '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
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"(python_full_version >= '3.12.4' and python_full_version < '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and python_full_version < '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
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"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
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"python_full_version == '3.11.*' and platform_machine != 'arm64' and sys_platform == 'darwin'",
|
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"python_full_version == '3.11.*' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
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@ -536,11 +539,14 @@ resolution-markers = [
|
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"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'arm64' and sys_platform == 'darwin'",
|
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"python_full_version == '3.11.*' and platform_machine == 'arm64' and sys_platform == 'darwin'",
|
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"python_full_version == '3.10.*' and platform_machine == 'arm64' and sys_platform == 'darwin'",
|
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"python_full_version >= '3.12.4' and platform_machine != 'arm64' and sys_platform == 'darwin'",
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"python_full_version >= '3.13' and platform_machine != 'arm64' and sys_platform == 'darwin'",
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"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
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"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
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"(python_full_version >= '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
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"(python_full_version >= '3.12.4' and python_full_version < '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and python_full_version < '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
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"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
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"python_full_version == '3.11.*' and platform_machine != 'arm64' and sys_platform == 'darwin'",
|
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"python_full_version == '3.11.*' and platform_machine == 'aarch64' and sys_platform == 'linux'",
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@ -844,6 +850,9 @@ dependencies = [
|
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]
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[package.optional-dependencies]
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asr = [
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{ name = "openai-whisper" },
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]
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ocrmac = [
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{ name = "ocrmac", marker = "sys_platform == 'darwin'" },
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]
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@ -918,6 +927,7 @@ requires-dist = [
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{ name = "mlx-vlm", marker = "python_full_version >= '3.10' and platform_machine == 'arm64' and sys_platform == 'darwin' and extra == 'vlm'", specifier = ">=0.1.22" },
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{ name = "onnxruntime", marker = "extra == 'rapidocr'", specifier = ">=1.7.0,<2.0.0" },
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{ name = "openai-whisper", marker = "extra == 'asr'", git = "https://github.com/openai/whisper.git?rev=dd985ac4b90cafeef8712f2998d62c59c3e62d22" },
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{ name = "pandas", specifier = ">=2.1.4,<3.0.0" },
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{ name = "pillow", specifier = ">=10.0.0,<12.0.0" },
|
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@ -937,7 +947,7 @@ requires-dist = [
|
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{ name = "transformers", marker = "extra == 'vlm'", specifier = ">=4.46.0,<5.0.0" },
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{ name = "typer", specifier = ">=0.12.5,<0.17.0" },
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]
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|
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provides-extras = ["tesserocr", "ocrmac", "vlm", "rapidocr", "asr"]
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[package.metadata.requires-dev]
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constraints = [
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@ -1752,11 +1762,14 @@ resolution-markers = [
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"python_full_version == '3.11.*' and platform_machine == 'arm64' and sys_platform == 'darwin'",
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"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
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"(python_full_version >= '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
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"(python_full_version >= '3.12.4' and python_full_version < '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and python_full_version < '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
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"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
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"(python_full_version >= '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.12.4' and python_full_version < '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and python_full_version < '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_machine != 'arm64' and sys_platform == 'darwin'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
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@ -3425,13 +3621,29 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/c3/16/873b955beda7bada5b0d798d3a601b2ff210e44ad5169f6d405b93892103/onnxruntime-1.22.0-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:64845709f9e8a2809e8e009bc4c8f73b788cee9c6619b7d9930344eae4c9cd36", size = 16427482, upload-time = "2025-05-09T20:26:20.376Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "openai-whisper"
|
||||
version = "20240930"
|
||||
source = { git = "https://github.com/openai/whisper.git?rev=dd985ac4b90cafeef8712f2998d62c59c3e62d22#dd985ac4b90cafeef8712f2998d62c59c3e62d22" }
|
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|
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{ name = "more-itertools" },
|
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{ name = "numba", version = "0.61.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.10'" },
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{ name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" },
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{ name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.10'" },
|
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{ name = "tiktoken" },
|
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{ name = "torch" },
|
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{ name = "tqdm" },
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|
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|
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|
||||
[[package]]
|
||||
name = "opencv-python"
|
||||
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|
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source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
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{ name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" },
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{ name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.10'" },
|
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{ name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version >= '3.10' and python_full_version < '3.13' and platform_machine != 'arm64') or (python_full_version >= '3.10' and python_full_version < '3.13' and sys_platform != 'darwin') or (python_full_version >= '3.10' and platform_machine == 'arm64' and sys_platform == 'darwin')" },
|
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]
|
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sdist = { url = "https://files.pythonhosted.org/packages/4a/e7/b70a2d9ab205110d715906fc8ec83fbb00404aeb3a37a0654fdb68eb0c8c/opencv-python-4.10.0.84.tar.gz", hash = "sha256:72d234e4582e9658ffea8e9cae5b63d488ad06994ef12d81dc303b17472f3526", size = 95103981, upload-time = "2024-06-17T18:29:56.757Z" }
|
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@ -3654,11 +3866,14 @@ resolution-markers = [
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"python_full_version == '3.11.*' and platform_machine == 'arm64' and sys_platform == 'darwin'",
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"python_full_version == '3.10.*' and platform_machine == 'arm64' and sys_platform == 'darwin'",
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"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and sys_platform == 'linux'",
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"python_full_version >= '3.13' and platform_machine == 'aarch64' and sys_platform == 'linux'",
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"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
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"(python_full_version >= '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
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"(python_full_version >= '3.12.4' and python_full_version < '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and python_full_version < '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
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"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
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"python_full_version == '3.11.*' and platform_machine != 'arm64' and sys_platform == 'darwin'",
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"python_full_version == '3.11.*' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
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@ -4890,17 +5105,17 @@ version = "1.4.4"
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|
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|
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|
||||
{ name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.10' and python_full_version < '3.13'" },
|
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{ name = "onnxruntime", version = "1.19.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" },
|
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{ name = "onnxruntime", version = "1.22.0", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version >= '3.10' and python_full_version < '3.13') or (python_full_version >= '3.10' and platform_machine != 'arm64') or (python_full_version >= '3.10' and sys_platform != 'darwin')" },
|
||||
{ name = "opencv-python", marker = "python_full_version < '3.13' or platform_machine != 'arm64' or sys_platform != 'darwin'" },
|
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{ name = "pillow", marker = "python_full_version < '3.13' or platform_machine != 'arm64' or sys_platform != 'darwin'" },
|
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{ name = "pyclipper", marker = "python_full_version < '3.13' or platform_machine != 'arm64' or sys_platform != 'darwin'" },
|
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{ name = "pyyaml", marker = "python_full_version < '3.13' or platform_machine != 'arm64' or sys_platform != 'darwin'" },
|
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|
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{ name = "opencv-python", marker = "python_full_version < '3.13'" },
|
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{ name = "pillow", marker = "python_full_version < '3.13'" },
|
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{ name = "pyclipper", marker = "python_full_version < '3.13'" },
|
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{ name = "pyyaml", marker = "python_full_version < '3.13'" },
|
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{ name = "shapely", version = "2.0.7", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" },
|
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{ name = "shapely", version = "2.1.1", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version >= '3.10' and python_full_version < '3.13') or (python_full_version >= '3.10' and platform_machine != 'arm64') or (python_full_version >= '3.10' and sys_platform != 'darwin')" },
|
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{ name = "six", marker = "python_full_version < '3.13' or platform_machine != 'arm64' or sys_platform != 'darwin'" },
|
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{ name = "tqdm", marker = "python_full_version < '3.13' or platform_machine != 'arm64' or sys_platform != 'darwin'" },
|
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{ name = "shapely", version = "2.1.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.10' and python_full_version < '3.13'" },
|
||||
{ name = "six", marker = "python_full_version < '3.13'" },
|
||||
{ name = "tqdm", marker = "python_full_version < '3.13'" },
|
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|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/ba/12/1e5497183bdbe782dbb91bad1d0d2297dba4d2831b2652657f7517bfc6df/rapidocr_onnxruntime-1.4.4-py3-none-any.whl", hash = "sha256:971d7d5f223a7a808662229df1ef69893809d8457d834e6373d3854bc1782cbf", size = 14915192, upload-time = "2025-01-17T01:48:25.104Z" },
|
||||
@ -5313,11 +5528,14 @@ resolution-markers = [
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.12.4' and python_full_version < '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and python_full_version < '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_machine != 'arm64' and sys_platform == 'darwin'",
|
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"python_full_version == '3.11.*' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
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@ -5458,11 +5676,14 @@ resolution-markers = [
|
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"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'arm64' and sys_platform == 'darwin'",
|
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"python_full_version == '3.11.*' and platform_machine == 'arm64' and sys_platform == 'darwin'",
|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.12.4' and python_full_version < '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and python_full_version < '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_machine != 'arm64' and sys_platform == 'darwin'",
|
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|
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@ -5668,11 +5889,14 @@ resolution-markers = [
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
||||
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|
||||
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|
||||
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|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.12.4' and python_full_version < '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and python_full_version < '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_machine != 'arm64' and sys_platform == 'darwin'",
|
||||
"python_full_version == '3.11.*' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
||||
@ -5915,11 +6139,14 @@ resolution-markers = [
|
||||
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|
||||
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|
||||
"python_full_version == '3.11.*' and platform_machine == 'arm64' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12.4' and platform_machine != 'arm64' and sys_platform == 'darwin'",
|
||||
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|
||||
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|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'arm64' and sys_platform == 'darwin'",
|
||||
"python_full_version >= '3.12.4' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.13' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12.4' and python_full_version < '3.13' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
||||
"(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.12.4' and python_full_version < '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and python_full_version < '3.13' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
|
||||
"python_full_version == '3.11.*' and platform_machine != 'arm64' and sys_platform == 'darwin'",
|
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"python_full_version == '3.11.*' and platform_machine == 'aarch64' and sys_platform == 'linux'",
|
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@ -5933,6 +6160,48 @@ wheels = [
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|
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|
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[[package]]
|
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|
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|
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||||
[[package]]
|
||||
name = "tinycss2"
|
||||
version = "1.4.0"
|
||||
|
||||
Loading…
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Reference in New Issue
Block a user