feat!: Docling v2 (#117)
--------- Signed-off-by: Christoph Auer <cau@zurich.ibm.com> Signed-off-by: Maxim Lysak <mly@zurich.ibm.com> Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> Signed-off-by: Panos Vagenas <35837085+vagenas@users.noreply.github.com> Co-authored-by: Maxim Lysak <mly@zurich.ibm.com> Co-authored-by: Michele Dolfi <dol@zurich.ibm.com> Co-authored-by: Panos Vagenas <35837085+vagenas@users.noreply.github.com>
This commit is contained in:
Christoph Auer
GitHub
@@ -1,18 +0,0 @@
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from pathlib import Path
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from typing import Callable, Iterable, List
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from docling.datamodel.base_models import Page
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from docling.datamodel.pipeline_options import PipelineOptions
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class BaseModelPipeline:
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def __init__(self, artifacts_path: Path, pipeline_options: PipelineOptions):
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self.model_pipe: List[Callable] = []
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self.artifacts_path = artifacts_path
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self.pipeline_options = pipeline_options
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def apply(self, page_batch: Iterable[Page]) -> Iterable[Page]:
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for model in self.model_pipe:
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page_batch = model(page_batch)
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yield from page_batch
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190
docling/pipeline/base_pipeline.py
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190
docling/pipeline/base_pipeline.py
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@@ -0,0 +1,190 @@
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import functools
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import logging
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import time
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import traceback
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from abc import ABC, abstractmethod
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from typing import Callable, Iterable, List
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from docling_core.types.doc import DoclingDocument, NodeItem
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from docling.backend.abstract_backend import AbstractDocumentBackend
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from docling.backend.pdf_backend import PdfDocumentBackend
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from docling.datamodel.base_models import (
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ConversionStatus,
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DoclingComponentType,
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ErrorItem,
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Page,
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)
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from docling.datamodel.document import ConversionResult, InputDocument
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from docling.datamodel.pipeline_options import PipelineOptions
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from docling.datamodel.settings import settings
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from docling.models.base_model import BaseEnrichmentModel
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from docling.utils.utils import chunkify
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_log = logging.getLogger(__name__)
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class BasePipeline(ABC):
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def __init__(self, pipeline_options: PipelineOptions):
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self.pipeline_options = pipeline_options
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self.build_pipe: List[Callable] = []
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self.enrichment_pipe: List[BaseEnrichmentModel] = []
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def execute(self, in_doc: InputDocument, raises_on_error: bool) -> ConversionResult:
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conv_res = ConversionResult(input=in_doc)
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_log.info(f"Processing document {in_doc.file.name}")
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try:
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# These steps are building and assembling the structure of the
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# output DoclingDocument
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conv_res = self._build_document(in_doc, conv_res)
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conv_res = self._assemble_document(in_doc, conv_res)
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# From this stage, all operations should rely only on conv_res.output
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conv_res = self._enrich_document(in_doc, conv_res)
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conv_res.status = self._determine_status(in_doc, conv_res)
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except Exception as e:
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conv_res.status = ConversionStatus.FAILURE
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if raises_on_error:
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raise e
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return conv_res
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@abstractmethod
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def _build_document(
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self, in_doc: InputDocument, conv_res: ConversionResult
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) -> ConversionResult:
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pass
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def _assemble_document(
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self, in_doc: InputDocument, conv_res: ConversionResult
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) -> ConversionResult:
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return conv_res
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def _enrich_document(
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self, in_doc: InputDocument, conv_res: ConversionResult
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) -> ConversionResult:
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def _filter_elements(
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doc: DoclingDocument, model: BaseEnrichmentModel
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) -> Iterable[NodeItem]:
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for element, _level in doc.iterate_items():
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if model.is_processable(doc=doc, element=element):
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yield element
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for model in self.enrichment_pipe:
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for element_batch in chunkify(
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_filter_elements(conv_res.document, model),
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settings.perf.elements_batch_size,
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):
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# TODO: currently we assume the element itself is modified, because
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# we don't have an interface to save the element back to the document
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for element in model(
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doc=conv_res.document, element_batch=element_batch
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): # Must exhaust!
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pass
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return conv_res
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@abstractmethod
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def _determine_status(
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self, in_doc: InputDocument, conv_res: ConversionResult
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) -> ConversionStatus:
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pass
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@classmethod
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@abstractmethod
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def get_default_options(cls) -> PipelineOptions:
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pass
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@classmethod
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@abstractmethod
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def is_backend_supported(cls, backend: AbstractDocumentBackend):
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pass
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# def _apply_on_elements(self, element_batch: Iterable[NodeItem]) -> Iterable[Any]:
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# for model in self.build_pipe:
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# element_batch = model(element_batch)
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#
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# yield from element_batch
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class PaginatedPipeline(BasePipeline): # TODO this is a bad name.
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def _apply_on_pages(self, page_batch: Iterable[Page]) -> Iterable[Page]:
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for model in self.build_pipe:
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page_batch = model(page_batch)
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yield from page_batch
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def _build_document(
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self, in_doc: InputDocument, conv_res: ConversionResult
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) -> ConversionResult:
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if not isinstance(in_doc._backend, PdfDocumentBackend):
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raise RuntimeError(
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f"The selected backend {type(in_doc._backend).__name__} for {in_doc.file} is not a PDF backend. "
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f"Can not convert this with a PDF pipeline. "
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f"Please check your format configuration on DocumentConverter."
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)
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# conv_res.status = ConversionStatus.FAILURE
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# return conv_res
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for i in range(0, in_doc.page_count):
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conv_res.pages.append(Page(page_no=i))
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try:
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# Iterate batches of pages (page_batch_size) in the doc
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for page_batch in chunkify(conv_res.pages, settings.perf.page_batch_size):
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start_pb_time = time.time()
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# 1. Initialise the page resources
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init_pages = map(
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functools.partial(self.initialize_page, in_doc), page_batch
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)
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# 2. Run pipeline stages
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pipeline_pages = self._apply_on_pages(init_pages)
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for p in pipeline_pages: # Must exhaust!
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pass
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end_pb_time = time.time() - start_pb_time
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_log.debug(f"Finished converting page batch time={end_pb_time:.3f}")
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except Exception as e:
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conv_res.status = ConversionStatus.FAILURE
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trace = "\n".join(traceback.format_exception(e))
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_log.warning(
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f"Encountered an error during conversion of document {in_doc.document_hash}:\n"
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f"{trace}"
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)
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raise e
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finally:
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# Always unload the PDF backend, even in case of failure
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if in_doc._backend:
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in_doc._backend.unload()
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return conv_res
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def _determine_status(
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self, in_doc: InputDocument, conv_res: ConversionResult
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) -> ConversionStatus:
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status = ConversionStatus.SUCCESS
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for page in conv_res.pages:
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if page._backend is None or not page._backend.is_valid():
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conv_res.errors.append(
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ErrorItem(
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component_type=DoclingComponentType.DOCUMENT_BACKEND,
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module_name=type(page._backend).__name__,
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error_message=f"Page {page.page_no} failed to parse.",
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)
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)
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status = ConversionStatus.PARTIAL_SUCCESS
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return status
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# Initialise and load resources for a page
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@abstractmethod
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def initialize_page(self, doc: InputDocument, page: Page) -> Page:
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pass
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59
docling/pipeline/simple_pipeline.py
Normal file
59
docling/pipeline/simple_pipeline.py
Normal file
@@ -0,0 +1,59 @@
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import logging
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from docling.backend.abstract_backend import (
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AbstractDocumentBackend,
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DeclarativeDocumentBackend,
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)
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from docling.datamodel.base_models import ConversionStatus
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from docling.datamodel.document import ConversionResult, InputDocument
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from docling.datamodel.pipeline_options import PipelineOptions
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from docling.pipeline.base_pipeline import BasePipeline
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_log = logging.getLogger(__name__)
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class SimplePipeline(BasePipeline):
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"""SimpleModelPipeline.
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This class is used at the moment for formats / backends
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which produce straight DoclingDocument output.
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"""
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def __init__(self, pipeline_options: PipelineOptions):
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super().__init__(pipeline_options)
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def _build_document(
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self, in_doc: InputDocument, conv_res: ConversionResult
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) -> ConversionResult:
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if not isinstance(in_doc._backend, DeclarativeDocumentBackend):
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raise RuntimeError(
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f"The selected backend {type(in_doc._backend).__name__} for {in_doc.file} is not a declarative backend. "
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f"Can not convert this with simple pipeline. "
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f"Please check your format configuration on DocumentConverter."
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)
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# conv_res.status = ConversionStatus.FAILURE
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# return conv_res
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# Instead of running a page-level pipeline to build up the document structure,
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# the backend is expected to be of type DeclarativeDocumentBackend, which can output
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# a DoclingDocument straight.
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conv_res.document = in_doc._backend.convert()
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return conv_res
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def _determine_status(
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self, in_doc: InputDocument, conv_res: ConversionResult
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) -> ConversionStatus:
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# This is called only if the previous steps didn't raise.
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# Since we don't have anything else to evaluate, we can
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# safely return SUCCESS.
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return ConversionStatus.SUCCESS
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@classmethod
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def get_default_options(cls) -> PipelineOptions:
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return PipelineOptions()
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@classmethod
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def is_backend_supported(cls, backend: AbstractDocumentBackend):
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return isinstance(backend, DeclarativeDocumentBackend)
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@@ -1,66 +0,0 @@
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from pathlib import Path
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from docling.datamodel.pipeline_options import (
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EasyOcrOptions,
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PipelineOptions,
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TesseractCliOcrOptions,
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TesseractOcrOptions,
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)
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from docling.models.base_ocr_model import BaseOcrModel
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from docling.models.easyocr_model import EasyOcrModel
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from docling.models.layout_model import LayoutModel
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from docling.models.table_structure_model import TableStructureModel
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from docling.models.tesseract_ocr_cli_model import TesseractOcrCliModel
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from docling.models.tesseract_ocr_model import TesseractOcrModel
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from docling.pipeline.base_model_pipeline import BaseModelPipeline
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class StandardModelPipeline(BaseModelPipeline):
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_layout_model_path = "model_artifacts/layout/beehive_v0.0.5_pt"
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_table_model_path = "model_artifacts/tableformer"
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def __init__(self, artifacts_path: Path, pipeline_options: PipelineOptions):
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super().__init__(artifacts_path, pipeline_options)
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ocr_model: BaseOcrModel
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if isinstance(pipeline_options.ocr_options, EasyOcrOptions):
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ocr_model = EasyOcrModel(
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enabled=pipeline_options.do_ocr,
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options=pipeline_options.ocr_options,
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)
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elif isinstance(pipeline_options.ocr_options, TesseractCliOcrOptions):
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ocr_model = TesseractOcrCliModel(
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enabled=pipeline_options.do_ocr,
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options=pipeline_options.ocr_options,
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)
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elif isinstance(pipeline_options.ocr_options, TesseractOcrOptions):
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ocr_model = TesseractOcrModel(
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enabled=pipeline_options.do_ocr,
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options=pipeline_options.ocr_options,
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)
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else:
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raise RuntimeError(
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f"The specified OCR kind is not supported: {pipeline_options.ocr_options.kind}."
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)
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self.model_pipe = [
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# OCR
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ocr_model,
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# Layout
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LayoutModel(
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config={
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"artifacts_path": artifacts_path
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/ StandardModelPipeline._layout_model_path
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}
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),
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# Table structure
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TableStructureModel(
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config={
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"artifacts_path": artifacts_path
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/ StandardModelPipeline._table_model_path,
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"enabled": pipeline_options.do_table_structure,
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"mode": pipeline_options.table_structure_options.mode,
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"do_cell_matching": pipeline_options.table_structure_options.do_cell_matching,
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}
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),
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]
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198
docling/pipeline/standard_pdf_pipeline.py
Normal file
198
docling/pipeline/standard_pdf_pipeline.py
Normal file
@@ -0,0 +1,198 @@
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import logging
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from pathlib import Path
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from typing import Optional
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from docling_core.types.doc import DocItem, ImageRef, PictureItem, TableItem
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from docling.backend.abstract_backend import AbstractDocumentBackend
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from docling.backend.pdf_backend import PdfDocumentBackend
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from docling.datamodel.base_models import AssembledUnit, Page
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from docling.datamodel.document import ConversionResult, InputDocument
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from docling.datamodel.pipeline_options import (
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EasyOcrOptions,
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PdfPipelineOptions,
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TesseractCliOcrOptions,
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TesseractOcrOptions,
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)
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from docling.models.base_ocr_model import BaseOcrModel
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from docling.models.ds_glm_model import GlmModel, GlmOptions
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from docling.models.easyocr_model import EasyOcrModel
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from docling.models.layout_model import LayoutModel
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from docling.models.page_assemble_model import PageAssembleModel, PageAssembleOptions
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from docling.models.page_preprocessing_model import (
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PagePreprocessingModel,
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PagePreprocessingOptions,
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)
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from docling.models.table_structure_model import TableStructureModel
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from docling.models.tesseract_ocr_cli_model import TesseractOcrCliModel
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from docling.models.tesseract_ocr_model import TesseractOcrModel
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from docling.pipeline.base_pipeline import PaginatedPipeline
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_log = logging.getLogger(__name__)
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class StandardPdfPipeline(PaginatedPipeline):
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_layout_model_path = "model_artifacts/layout/beehive_v0.0.5_pt"
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_table_model_path = "model_artifacts/tableformer"
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def __init__(self, pipeline_options: PdfPipelineOptions):
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super().__init__(pipeline_options)
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self.pipeline_options: PdfPipelineOptions
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if pipeline_options.artifacts_path is None:
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self.artifacts_path = self.download_models_hf()
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else:
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self.artifacts_path = Path(pipeline_options.artifacts_path)
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keep_images = (
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self.pipeline_options.generate_page_images
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or self.pipeline_options.generate_picture_images
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or self.pipeline_options.generate_table_images
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)
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self.glm_model = GlmModel(options=GlmOptions())
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if (ocr_model := self.get_ocr_model()) is None:
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raise RuntimeError(
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f"The specified OCR kind is not supported: {pipeline_options.ocr_options.kind}."
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)
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self.build_pipe = [
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# Pre-processing
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PagePreprocessingModel(
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options=PagePreprocessingOptions(
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images_scale=pipeline_options.images_scale
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)
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),
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# OCR
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ocr_model,
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# Layout model
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LayoutModel(
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artifacts_path=self.artifacts_path
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/ StandardPdfPipeline._layout_model_path
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),
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# Table structure model
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TableStructureModel(
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enabled=pipeline_options.do_table_structure,
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artifacts_path=self.artifacts_path
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/ StandardPdfPipeline._table_model_path,
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options=pipeline_options.table_structure_options,
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),
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# Page assemble
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PageAssembleModel(options=PageAssembleOptions(keep_images=keep_images)),
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]
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self.enrichment_pipe = [
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# Other models working on `NodeItem` elements in the DoclingDocument
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]
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@staticmethod
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def download_models_hf(
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local_dir: Optional[Path] = None, force: bool = False
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) -> Path:
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from huggingface_hub import snapshot_download
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download_path = snapshot_download(
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repo_id="ds4sd/docling-models",
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force_download=force,
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local_dir=local_dir,
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revision="v2.0.1",
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)
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return Path(download_path)
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def get_ocr_model(self) -> Optional[BaseOcrModel]:
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if isinstance(self.pipeline_options.ocr_options, EasyOcrOptions):
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return EasyOcrModel(
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enabled=self.pipeline_options.do_ocr,
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options=self.pipeline_options.ocr_options,
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)
|
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elif isinstance(self.pipeline_options.ocr_options, TesseractCliOcrOptions):
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return TesseractOcrCliModel(
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enabled=self.pipeline_options.do_ocr,
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options=self.pipeline_options.ocr_options,
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)
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elif isinstance(self.pipeline_options.ocr_options, TesseractOcrOptions):
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return TesseractOcrModel(
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enabled=self.pipeline_options.do_ocr,
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options=self.pipeline_options.ocr_options,
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)
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return None
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def initialize_page(self, doc: InputDocument, page: Page) -> Page:
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page._backend = doc._backend.load_page(page.page_no) # type: ignore
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if page._backend is not None and page._backend.is_valid():
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page.size = page._backend.get_size()
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return page
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|
||||
def _assemble_document(
|
||||
self, in_doc: InputDocument, conv_res: ConversionResult
|
||||
) -> ConversionResult:
|
||||
all_elements = []
|
||||
all_headers = []
|
||||
all_body = []
|
||||
|
||||
for p in conv_res.pages:
|
||||
assert p.assembled is not None
|
||||
for el in p.assembled.body:
|
||||
all_body.append(el)
|
||||
for el in p.assembled.headers:
|
||||
all_headers.append(el)
|
||||
for el in p.assembled.elements:
|
||||
all_elements.append(el)
|
||||
|
||||
conv_res.assembled = AssembledUnit(
|
||||
elements=all_elements, headers=all_headers, body=all_body
|
||||
)
|
||||
|
||||
conv_res.document = self.glm_model(conv_res)
|
||||
|
||||
# Generate page images in the output
|
||||
if self.pipeline_options.generate_page_images:
|
||||
for page in conv_res.pages:
|
||||
assert page.image is not None
|
||||
page_no = page.page_no + 1
|
||||
conv_res.document.pages[page_no].image = ImageRef.from_pil(
|
||||
page.image, dpi=int(72 * self.pipeline_options.images_scale)
|
||||
)
|
||||
|
||||
# Generate images of the requested element types
|
||||
if (
|
||||
self.pipeline_options.generate_picture_images
|
||||
or self.pipeline_options.generate_table_images
|
||||
):
|
||||
scale = self.pipeline_options.images_scale
|
||||
for element, _level in conv_res.document.iterate_items():
|
||||
if not isinstance(element, DocItem) or len(element.prov) == 0:
|
||||
continue
|
||||
if (
|
||||
isinstance(element, PictureItem)
|
||||
and self.pipeline_options.generate_picture_images
|
||||
) or (
|
||||
isinstance(element, TableItem)
|
||||
and self.pipeline_options.generate_table_images
|
||||
):
|
||||
page_ix = element.prov[0].page_no - 1
|
||||
page = conv_res.pages[page_ix]
|
||||
assert page.size is not None
|
||||
assert page.image is not None
|
||||
|
||||
crop_bbox = (
|
||||
element.prov[0]
|
||||
.bbox.scaled(scale=scale)
|
||||
.to_top_left_origin(page_height=page.size.height * scale)
|
||||
)
|
||||
|
||||
cropped_im = page.image.crop(crop_bbox.as_tuple())
|
||||
element.image = ImageRef.from_pil(cropped_im, dpi=int(72 * scale))
|
||||
|
||||
return conv_res
|
||||
|
||||
@classmethod
|
||||
def get_default_options(cls) -> PdfPipelineOptions:
|
||||
return PdfPipelineOptions()
|
||||
|
||||
@classmethod
|
||||
def is_backend_supported(cls, backend: AbstractDocumentBackend):
|
||||
return isinstance(backend, PdfDocumentBackend)
|
||||
Reference in New Issue
Block a user