4cc6e3ea5e
* draft for picture description models Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * vlm description using AutoModelForVision2Seq Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * add generation options Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * update vlm API Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * allow only localhost traffic Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * rename model Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * do not run with vlm api Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * more renaming Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * fix examples path Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * apply CLI download login Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * fix name of cli argument Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> * use with_smolvlm in models download Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> --------- Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
108 lines
3.1 KiB
Python
108 lines
3.1 KiB
Python
import logging
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import warnings
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from enum import Enum
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from pathlib import Path
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from typing import Annotated, Optional
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import typer
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from rich.console import Console
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from rich.logging import RichHandler
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from docling.datamodel.settings import settings
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from docling.utils.model_downloader import download_models
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warnings.filterwarnings(action="ignore", category=UserWarning, module="pydantic|torch")
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warnings.filterwarnings(action="ignore", category=FutureWarning, module="easyocr")
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console = Console()
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err_console = Console(stderr=True)
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app = typer.Typer(
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name="Docling models helper",
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no_args_is_help=True,
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add_completion=False,
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pretty_exceptions_enable=False,
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)
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class _AvailableModels(str, Enum):
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LAYOUT = "layout"
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TABLEFORMER = "tableformer"
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CODE_FORMULA = "code_formula"
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PICTURE_CLASSIFIER = "picture_classifier"
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SMOLVLM = "smolvlm"
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EASYOCR = "easyocr"
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@app.command("download")
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def download(
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output_dir: Annotated[
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Path,
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typer.Option(
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...,
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"-o",
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"--output-dir",
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help="The directory where all the models are downloaded.",
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),
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] = (settings.cache_dir / "models"),
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force: Annotated[
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bool, typer.Option(..., help="If true, the download will be forced")
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] = False,
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models: Annotated[
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Optional[list[_AvailableModels]],
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typer.Argument(
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help=f"Models to download (default behavior: all will be downloaded)",
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),
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] = None,
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quiet: Annotated[
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bool,
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typer.Option(
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...,
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"-q",
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"--quiet",
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help="No extra output is generated, the CLI prints only the directory with the cached models.",
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),
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] = False,
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):
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if not quiet:
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FORMAT = "%(message)s"
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logging.basicConfig(
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level=logging.INFO,
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format="[blue]%(message)s[/blue]",
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datefmt="[%X]",
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handlers=[RichHandler(show_level=False, show_time=False, markup=True)],
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)
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to_download = models or [m for m in _AvailableModels]
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output_dir = download_models(
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output_dir=output_dir,
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force=force,
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progress=(not quiet),
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with_layout=_AvailableModels.LAYOUT in to_download,
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with_tableformer=_AvailableModels.TABLEFORMER in to_download,
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with_code_formula=_AvailableModels.CODE_FORMULA in to_download,
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with_picture_classifier=_AvailableModels.PICTURE_CLASSIFIER in to_download,
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with_smolvlm=_AvailableModels.SMOLVLM in to_download,
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with_easyocr=_AvailableModels.EASYOCR in to_download,
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)
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if quiet:
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typer.echo(output_dir)
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else:
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typer.secho(f"\nModels downloaded into: {output_dir}.", fg="green")
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console.print(
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"\n",
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"Docling can now be configured for running offline using the local artifacts.\n\n",
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"Using the CLI:",
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f"`docling --artifacts-path={output_dir} FILE`",
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"\n",
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"Using Python: see the documentation at <https://ds4sd.github.io/docling/usage>.",
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)
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click_app = typer.main.get_command(app)
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if __name__ == "__main__":
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app()
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