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* 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>
73 lines
2.6 KiB
Python
Vendored
73 lines
2.6 KiB
Python
Vendored
import logging
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from pathlib import Path
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from docling_core.types.doc import ImageRefMode, TableItem, TextItem
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from docling.datamodel.base_models import InputFormat
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from docling.datamodel.pipeline_options import PdfPipelineOptions
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from docling.document_converter import DocumentConverter, PdfFormatOption
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_log = logging.getLogger(__name__)
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IMAGE_RESOLUTION_SCALE = 2.0
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# FIXME: put in your favorite translation code ....
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def translate(text: str, src: str = "en", dest: str = "de"):
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_log.warning("!!! IMPLEMENT HERE YOUR FAVORITE TRANSLATION CODE!!!")
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# from googletrans import Translator
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# Initialize the translator
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# translator = Translator()
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# Translate text from English to German
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# text = "Hello, how are you?"
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# translated = translator.translate(text, src="en", dest="de")
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return text
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def main():
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logging.basicConfig(level=logging.INFO)
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input_doc_path = Path("./tests/data/pdf/2206.01062.pdf")
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output_dir = Path("scratch")
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# Important: For operating with page images, we must keep them, otherwise the DocumentConverter
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# will destroy them for cleaning up memory.
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# This is done by setting PdfPipelineOptions.images_scale, which also defines the scale of images.
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# scale=1 correspond of a standard 72 DPI image
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# The PdfPipelineOptions.generate_* are the selectors for the document elements which will be enriched
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# with the image field
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pipeline_options = PdfPipelineOptions()
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pipeline_options.images_scale = IMAGE_RESOLUTION_SCALE
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pipeline_options.generate_page_images = True
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pipeline_options.generate_picture_images = True
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doc_converter = DocumentConverter(
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format_options={
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InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
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}
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)
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conv_res = doc_converter.convert(input_doc_path)
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conv_doc = conv_res.document
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doc_filename = conv_res.input.file
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# Save markdown with embedded pictures in original text
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md_filename = output_dir / f"{doc_filename}-with-images-orig.md"
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conv_doc.save_as_markdown(md_filename, image_mode=ImageRefMode.EMBEDDED)
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for element, _level in conv_res.document.iterate_items():
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if isinstance(element, TextItem):
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element.orig = element.text
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element.text = translate(text=element.text)
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elif isinstance(element, TableItem):
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for cell in element.data.table_cells:
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cell.text = translate(text=element.text)
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# Save markdown with embedded pictures in translated text
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md_filename = output_dir / f"{doc_filename}-with-images-translated.md"
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conv_doc.save_as_markdown(md_filename, image_mode=ImageRefMode.EMBEDDED)
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