Merge pull request #2667 from arc53/chore/bump-docling-2.119

chore: bump docling

application/core/settings.py

@@ -95,6 +95,7 @@ class Settings(BaseSettings):
     # Pages docling's threaded pipeline buffers in flight; the library
     # default (100) drives worker RSS to ~3 GB on a mid-size PDF.
     DOCLING_PIPELINE_QUEUE_MAX_SIZE: int = 2
+    DOCLING_COMPILE_TORCH_MODELS: bool = False
     DOCLING_TABULAR_MAX_BYTES: int = 2_000_000
     DOCLING_MARKUP_MAX_BYTES: int = 8_000_000
     ATTACHMENT_TEXT_MAX_BYTES: int = 5_000_000

application/parser/document_reader.py

@@ -252,6 +252,9 @@ def _docling_structured(path: Path, *, ocr_enabled: bool, include_tables: bool,
     else:
         from docling.document_converter import DocumentConverter
 
+        from application.parser.file.docling_parser import _apply_inference_settings
+
+        _apply_inference_settings()
         converter = DocumentConverter()
         doc = converter.convert(str(path)).document
         markdown = doc.export_to_markdown()

application/parser/file/docling_parser.py

@@ -43,6 +43,29 @@ def _apply_pipeline_caps(pipeline_options) -> None:
             setattr(pipeline_options, name, value)
 
 
+def _apply_inference_settings() -> None:
+    """Set docling's global torch.compile toggle from ``DOCLING_COMPILE_TORCH_MODELS``.
+
+    docling compiles its layout/table/OCR models with ``torch.compile`` by
+    default. For DocsGPT's one-shot, per-file parses that warmup is never
+    amortized, and it hard-fails wherever TorchInductor cannot build: it emits
+    invalid Metal on Apple Silicon, and its C++ path does not quote the ``-L``
+    library path, so any install directory containing a space fails to build.
+
+    Guarded so docling builds without the inference settings are unaffected.
+    """
+    from application.core.settings import settings
+
+    try:
+        from docling.datamodel.settings import settings as docling_settings
+    except ImportError:  # pragma: no cover - docling always present here
+        return
+
+    inference = getattr(docling_settings, "inference", None)
+    if inference is not None and hasattr(inference, "compile_torch_models"):
+        inference.compile_torch_models = settings.DOCLING_COMPILE_TORCH_MODELS
+
+
 def _tabular_content_size(file: Path) -> int:
     """Effective content size of a tabular file, in bytes.
 
@@ -256,6 +279,8 @@ class DoclingParser(BaseParser):
         )
         from docling.datamodel.pipeline_options import PdfPipelineOptions
 
+        _apply_inference_settings()
+
         pipeline_options = PdfPipelineOptions(
             do_ocr=self.ocr_enabled,
             do_table_structure=self.table_structure,

application/requirements.txt

@@ -12,7 +12,7 @@ cryptography==50.0.0
 dataclasses-json==0.6.7
 daytona==0.203.0
 defusedxml==0.7.1
-docling==2.84.0
+docling==2.119.0
 rapidocr==3.9.2
 onnxruntime==1.28.0
 docx2txt==0.9

docs/content/Guides/ocr.mdx

@@ -51,6 +51,22 @@ By default, Docling parser classes use RapidOCR options (language default: `engl
 Parser internals like OCR language and force-full-page OCR are currently set by code defaults, not separate `.env` settings.
 </Callout>
 
+### Model compilation
+
+Docling runs its layout, table, and OCR models through `torch.compile` by
+default. DocsGPT turns that off. On x86-64 Linux, compiling raised the first
+parse of a two-page PDF from 8.4s to 58.6s while steady-state parsing stayed
+at 1.5s either way, so the warmup is overhead a per-file parse never recovers.
+Compiling also fails outright on Apple Silicon, on install paths containing a
+space, on Windows without MSVC, and in slim images with no C compiler.
+
+```env
+DOCLING_COMPILE_TORCH_MODELS=false
+```
+
+Set it to `true` only if you are parsing large batches on a machine where the
+warmup pays for itself.
+
 ## Attachment Behavior by Model Support
 
 When attachments are used in chat, behavior depends on the selected model/provider:

tests/parser/file/test_docling_parser.py

@@ -891,3 +891,123 @@ class TestTabularGateSeam:
 
         with pytest.raises(DocumentParseError):
             DoclingCSVParser().parse_file(path)
+
+
+# =====================================================================
+# torch.compile inference setting
+# =====================================================================
+
+
+@pytest.mark.unit
+class TestApplyInferenceSettings:
+    """_apply_inference_settings governs docling's torch.compile of its models.
+
+    docling >= 2.92 compiles its layout/OCR models with torch.compile by
+    default, which hard-fails TorchInductor's Metal codegen on Apple Silicon
+    and buys nothing for one-shot parses.
+    """
+
+    def test_disables_torch_compile_by_default(self, monkeypatch):
+        from application.parser.file.docling_parser import _apply_inference_settings
+
+        class Inference:
+            compile_torch_models = True
+
+        class DoclingSettings:
+            inference = Inference()
+
+        docling_settings = DoclingSettings()
+        monkeypatch.setattr(
+            "docling.datamodel.settings.settings", docling_settings, raising=False
+        )
+
+        _apply_inference_settings()
+
+        assert docling_settings.inference.compile_torch_models is False
+
+    def test_opt_in_reenables_torch_compile(self, monkeypatch):
+        from application.core.settings import settings
+        from application.parser.file.docling_parser import _apply_inference_settings
+
+        monkeypatch.setattr(
+            settings, "DOCLING_COMPILE_TORCH_MODELS", True, raising=False
+        )
+
+        class Inference:
+            compile_torch_models = False
+
+        class DoclingSettings:
+            inference = Inference()
+
+        docling_settings = DoclingSettings()
+        monkeypatch.setattr(
+            "docling.datamodel.settings.settings", docling_settings, raising=False
+        )
+
+        _apply_inference_settings()
+
+        assert docling_settings.inference.compile_torch_models is True
+
+    def test_noop_on_docling_without_inference_settings(self, monkeypatch):
+        """Builds predating the inference settings must be a silent no-op."""
+        from application.parser.file.docling_parser import _apply_inference_settings
+
+        class DoclingSettings:
+            pass
+
+        monkeypatch.setattr(
+            "docling.datamodel.settings.settings", DoclingSettings(), raising=False
+        )
+
+        _apply_inference_settings()  # must not raise
+
+    def test_create_converter_applies_inference_settings(self, monkeypatch):
+        """The cap is worthless unless the converter path actually calls it."""
+        from application.parser.file.docling_parser import DoclingParser
+
+        called = []
+        monkeypatch.setattr(
+            "application.parser.file.docling_parser._apply_inference_settings",
+            lambda: called.append(True),
+        )
+        monkeypatch.setattr(
+            "docling.document_converter.DocumentConverter",
+            MagicMock(),
+        )
+
+        DoclingParser(ocr_enabled=False)._create_converter()
+
+        assert called == [True]
+
+    def test_inference_settings_applied_before_options_are_built(self, monkeypatch):
+        """Ordering is load-bearing, not incidental.
+
+        ``compile_model`` is a ``default_factory`` that reads docling's global
+        at *option construction* time, so flipping the global after building
+        ``PdfPipelineOptions`` is silently ignored. Pin the order.
+        """
+        import docling.datamodel.pipeline_options as dpo
+
+        from application.parser.file.docling_parser import DoclingParser
+
+        events = []
+        monkeypatch.setattr(
+            "application.parser.file.docling_parser._apply_inference_settings",
+            lambda: events.append("settings"),
+        )
+
+        real_options = dpo.PdfPipelineOptions
+
+        def _tracking_options(*args, **kwargs):
+            events.append("options")
+            return real_options(*args, **kwargs)
+
+        monkeypatch.setattr(dpo, "PdfPipelineOptions", _tracking_options)
+        monkeypatch.setattr("docling.document_converter.DocumentConverter", MagicMock())
+
+        DoclingParser(ocr_enabled=False)._create_converter()
+
+        assert events == ["settings", "options"], (
+            "torch.compile must be disabled before PdfPipelineOptions is "
+            f"constructed, got {events}"
+        )

tests/parser/test_document_reader.py

@@ -516,3 +516,51 @@ def test_bound_parse_payload_small_content_not_flagged():
     out = bound_parse_payload({"output": "text", "content": "hi"}, max_chars=10)
     assert out["content"] == "hi"
     assert out["truncated"] is False
+
+
+# ---------------------------------------------------------------------------
+# vanilla-converter fallback honors the torch.compile toggle
+# ---------------------------------------------------------------------------
+@pytest.mark.unit
+def test_vanilla_converter_applies_inference_settings(monkeypatch, tmp_path):
+    """The fallback builds its own DocumentConverter, so it must disable
+    torch.compile itself — the configured-parser path can't do it for it."""
+    import sys
+    import types
+
+    called = []
+    monkeypatch.setattr(
+        "application.parser.file.docling_parser._apply_inference_settings",
+        lambda: called.append(True),
+    )
+
+    class _Doc:
+        texts = []
+        tables = []
+        pages = {}
+
+        def export_to_markdown(self):
+            return "# md"
+
+        def export_to_dict(self):
+            return {"texts": []}
+
+    class _Converter:
+        def convert(self, *a, **k):
+            assert called == [True], "converter built before torch.compile was disabled"
+            return types.SimpleNamespace(document=_Doc())
+
+    fake_docling = types.ModuleType("docling")
+    fake_dc_module = types.ModuleType("docling.document_converter")
+    fake_dc_module.DocumentConverter = _Converter
+    fake_docling.document_converter = fake_dc_module
+    monkeypatch.setitem(sys.modules, "docling", fake_docling)
+    monkeypatch.setitem(sys.modules, "docling.document_converter", fake_dc_module)
+
+    path = tmp_path / "doc.pdf"
+    path.write_bytes(b"%PDF")
+
+    out = dr._docling_structured(path, ocr_enabled=False, include_tables=False, parser=None)
+
+    assert out["markdown"] == "# md"
+    assert called == [True]