diff --git a/docling_core/experimental/idoctags.py b/docling_core/experimental/idoctags.py
index 7990f4cd..e53853aa 100644
--- a/docling_core/experimental/idoctags.py
+++ b/docling_core/experimental/idoctags.py
@@ -1,34 +1,44 @@
"""Define classes for DocTags serialization."""
+import re
from enum import Enum
-from typing import Any, Final, Optional, Tuple
-from xml.dom.minidom import parseString
+from itertools import groupby
+from typing import Any, ClassVar, Final, Optional, cast
+from xml.dom.minidom import Element, parseString
from pydantic import BaseModel
from typing_extensions import override
from docling_core.transforms.serializer.base import (
+ BaseAnnotationSerializer,
BaseDocSerializer,
+ BaseFallbackSerializer,
+ BaseFormSerializer,
+ BaseInlineSerializer,
+ BaseKeyValueSerializer,
BaseListSerializer,
BaseMetaSerializer,
BasePictureSerializer,
BaseTableSerializer,
+ BaseTextSerializer,
SerializationResult,
)
-from docling_core.transforms.serializer.common import create_ser_result
-from docling_core.transforms.serializer.doctags import (
- DocTagsDocSerializer,
- DocTagsParams,
- DocTagsPictureSerializer,
- DocTagsTableSerializer,
- _get_delim,
- _wrap,
+from docling_core.transforms.serializer.common import (
+ CommonParams,
+ DocSerializer,
+ create_ser_result,
)
from docling_core.types.doc import (
BaseMeta,
+ BoundingBox,
+ CodeItem,
DescriptionMetaField,
DocItem,
DoclingDocument,
+ FloatingItem,
+ FormItem,
+ InlineGroup,
+ KeyValueItem,
ListGroup,
ListItem,
MetaFieldName,
@@ -36,164 +46,825 @@
NodeItem,
PictureClassificationMetaField,
PictureItem,
+ PictureMeta,
+ ProvenanceItem,
+ SectionHeaderItem,
+ Size,
SummaryMetaField,
+ TableCell,
TableData,
+ TableItem,
TabularChartMetaField,
+ TextItem,
)
-from docling_core.types.doc.labels import DocItemLabel
-from docling_core.types.doc.tokens import (
- _CodeLanguageToken,
- _PictureClassificationToken,
-)
+from docling_core.types.doc.base import CoordOrigin
+from docling_core.types.doc.labels import CodeLanguageLabel, DocItemLabel
+
+# Note: Intentionally avoid importing DocumentToken here to ensure
+# IDocTags uses only its own token vocabulary.
DOCTAGS_VERSION: Final = "1.0.0"
+DOCTAGS_RESOLUTION: int = 512
+
+
+def _wrap(text: str, wrap_tag: str) -> str:
+ return f"<{wrap_tag}>{text}"
+
+
+def _wrap_token(*, text: str, open_token: str) -> str:
+ close_token = IDocTagsVocabulary.create_closing_token(token=open_token)
+ return f"{open_token}{text}{close_token}"
+
+
+def _quantize_to_resolution(value: float, resolution: int) -> int:
+ """Quantize normalized value in [0,1] to [0,resolution]."""
+ n = int(round(resolution * value))
+ if n < 0:
+ return 0
+ if n > resolution:
+ return resolution
+ return n
+
+
+def _create_location_tokens_for_bbox(
+ *,
+ bbox: tuple[float, float, float, float],
+ page_w: float,
+ page_h: float,
+ xres: int,
+ yres: int,
+) -> str:
+ """Create four `` tokens for x0,y0,x1,y1 given a bbox."""
+ x0 = bbox[0] / page_w
+ y0 = bbox[1] / page_h
+ x1 = bbox[2] / page_w
+ y1 = bbox[3] / page_h
+
+ x0v = _quantize_to_resolution(min(x0, x1), xres)
+ y0v = _quantize_to_resolution(min(y0, y1), yres)
+ x1v = _quantize_to_resolution(max(x0, x1), xres)
+ y1v = _quantize_to_resolution(max(y0, y1), yres)
+
+ return (
+ IDocTagsVocabulary.create_location_token(value=x0v, resolution=xres)
+ + IDocTagsVocabulary.create_location_token(value=y0v, resolution=yres)
+ + IDocTagsVocabulary.create_location_token(value=x1v, resolution=xres)
+ + IDocTagsVocabulary.create_location_token(value=y1v, resolution=yres)
+ )
+
+
+def _create_location_tokens_for_item(
+ *,
+ item: "DocItem",
+ doc: "DoclingDocument",
+ xres: int = DOCTAGS_RESOLUTION,
+ yres: int = DOCTAGS_RESOLUTION,
+) -> str:
+ """Create concatenated `` tokens for an item's provenance."""
+ if not getattr(item, "prov", None):
+ return ""
+ out: list[str] = []
+ for prov in item.prov:
+ page_w, page_h = doc.pages[prov.page_no].size.as_tuple()
+ bbox = prov.bbox.to_top_left_origin(page_h).as_tuple()
+ out.append(
+ _create_location_tokens_for_bbox(
+ bbox=bbox, page_w=page_w, page_h=page_h, xres=xres, yres=yres
+ )
+ )
+ return "".join(out)
+
+
+class IDocTagsCategory(str, Enum):
+ """IDocTagsCtegory.
+
+ DocTags defines the following categories of elements:
+
+ - **root**: Elements that establish document scope such as
+ `doctag`.
+ - **special**: Elements that establish document pagination, such as
+ `page_break`, and `time_break`.
+ - **geometric**: Elements that capture geometric position as normalized
+ coordinates/bounding boxes (via repeated `location`) anchoring
+ block-level content to the page.
+ - **temporal**: Elements that capture temporal positions using
+ ``
+ and `` for a timestamp and a double
+ timestamp for time intervals.
+ - **semantic**: Block-level elements that convey document meaning
+ (e.g., titles, paragraphs, captions, lists, forms, tables, formulas,
+ code, pictures), optionally preceded by location tokens.
+ - **formatting**: Inline elements that modify textual presentation within
+ semantic content (e.g., `bold`, `italic`, `strikethrough`,
+ `superscript`, `subscript`, `rtl`, `inline class="formula|code|picture"`,
+ `br`).
+ - **grouping**: Elements that organize semantic blocks into logical
+ hierarchies and composites (e.g., `section`, `list`, `group type=*`)
+ and never carry location tokens.
+ - **structural**: Sequence tokens that define internal structure for
+ complex constructs (primarily OTSL table layout: `otsl`, `fcel`,
+ `ecel`, `lcel`, `ucel`, `xcel`, `nl`, `ched`, `rhed`, `corn`, `srow`;
+ and form parts like `key`/`value`).
+ - **content**: Lightweight content helpers used inside semantic blocks for
+ explicit payload and annotations (e.g., `marker`).
+ - **binary data**: Elements that embed or reference non-text payloads for
+ media—either inline as `base64` or via `uri`—allowed under `picture`,
+ `inline class="picture"`, or at page level.
+ - **metadata**: Elements that provide metadata about the document or its
+ components, contained within `head` and `meta` respectively.
+ - **continuation** tokens: Markers that indicate content spanning pages or
+ table boundaries (e.g., `thread`, `h_thread`, each with a required
+ `id` attribute) to stitch split content (e.g., across columns or pages).
+ """
+
+ ROOT = "root"
+ SPECIAL = "special"
+ METADATA = "metadata"
+ GEOMETRIC = "geometric"
+ TEMPORAL = "temporal"
+ SEMANTIC = "semantic"
+ FORMATTING = "formatting"
+ GROUPING = "grouping"
+ STRUCTURAL = "structural"
+ CONTENT = "content"
+ BINARY_DATA = "binary_data"
+ CONTINUATION = "continuation"
+
+
+class IDocTagsToken(str, Enum):
+ """IDocTagsToken.
+
+ This class implements the tokens from the Token table,
+
+ | # | Category | Token | Self-Closing [Yes/No] | Parametrized [Yes/No] | Attributes | Description |
+ |---|----------|-------|-----------------------|-----------------------|------------|-------------|
+ | 1 | Root Elements | `doctag` | No | Yes | `version` | Root container; optional semantic version `version`. |
+ | 2 | Special Elements | `page_break` | Yes | No | — | Page delimiter. |
+ | 3 | | `time_break` | Yes | No | — | Temporal segment delimiter. |
+ | 4 | Metadata Containers | `head` | No | No | — | Document-level metadata container. |
+ | 5 | | `meta` | No | No | — | Component-level metadata container. |
+ | 6 | Geometric Tokens | `location` | Yes | Yes | `value`, `resolution?` |
+ Geometric coordinate; `value` in [0, res]; optional `resolution`. |
+ | 7 | Temmporal Tokens | `hour` | Yes | Yes | `value` | Hours component; `value` in [0, 99]. |
+ | 8 | | `minute` | Yes | Yes | `value` | Minutes component; `value` in [0, 59]. |
+ | 9 | | `second` | Yes | Yes | `value` | Seconds component; `value` in [0, 59]. |
+ | 10 | | `centisecond` | Yes | Yes | `value` | Centiseconds component; `value` in [0, 99]. |
+ | 11 | Semantic Tokens | `title` | No | No | — | Document or section title (content). |
+ | 12 | | `heading` | No | Yes | `level` | Section header; `level` (N ≥ 1). |
+ | 13 | | `text` | No | No | — | Generic text content. |
+ | 14 | | `caption` | No | No | — | Caption for floating/grouped elements. |
+ | 15 | | `footnote` | No | No | — | Footnote content. |
+ | 16 | | `page_header` | No | No | — | Page header content. |
+ | 17 | | `page_footer` | No | No | — | Page footer content. |
+ | 18 | | `watermark` | No | No | — | Watermark indicator or content. |
+ | 19 | | `picture` | No | No | — |
+ Block image/graphic; at most one of `base64`/`uri`; may include `meta`
+ for classification; `otsl` may encode chart data. |
+ | 20 | | `form` | No | No | — | Form structure container. |
+ | 21 | | `formula` | No | No | — | Mathematical expression block. |
+ | 22 | | `code` | No | No | — | Code block. |
+ | 23 | | `list_text` | No | No | — | List item content. |
+ | 24 | | `checkbox` | No | Yes | `selected` |
+ Checkbox item; optional `selected` in {`true`,`false`} defaults to
+ `false`. |
+ | 25 | | `form_item` | No | No | — |
+ Form item; exactly one `key`; one or more of
+ `value`/`checkbox`/`marker`/`hint`. |
+ | 26 | | `form_heading` | No | Yes | `level?` | Form header; optional `level` (N ≥ 1). |
+ | 27 | | `form_text` | No | No | — | Form text block. |
+ | 28 | | `hint` | No | No | — | Hint for a fillable field (format/example/description). |
+ | 29 | Grouping Tokens | `section` | No | Yes | `level` | Document section; `level` (N ≥ 1). |
+ | 30 | | `list` | No | Yes | `ordered` |
+ List container; optional `ordered` in {`true`,`false`} defaults to
+ `false`. |
+ | 31 | | `group` | No | Yes | `type?` |
+ Generic group; no `location` tokens; associates composite content
+ (e.g., captions/footnotes). |
+ | 32 | | `floating_group` | No | Yes | `class` in {`table`,`picture`,`form`,`code`} |
+ Floating container that groups a floating component with its caption,
+ footnotes, and metadata; no `location` tokens. |
+ | 33 | Formatting Tokens | `bold` | No | No | — | Bold text. |
+ | 34 | | `italic` | No | No | — | Italic text. |
+ | 35 | | `strikethrough` | No | No | — | Strike-through text. |
+ | 36 | | `superscript` | No | No | — | Superscript text. |
+ | 37 | | `subscript` | No | No | — | Subscript text. |
+ | 38 | | `rtl` | No | No | — | Right-to-left text direction. |
+ | 39 | | `inline` | No | Yes | `class` in {`formula`,`code`,`picture`} |
+ Inline content; if `class="picture"`, may include one of `base64` or
+ `uri`. |
+ | 40 | | `br` | Yes | No | — | Line break. |
+ | 41 | Structural Tokens (OTSL) | `otsl` | No | No | — | Table structure container. |
+ | 42 | | `fcel` | Yes | No | — | New cell with content. |
+ | 43 | | `ecel` | Yes | No | — | New cell without content. |
+ | 44 | | `ched` | Yes | No | — | Column header cell. |
+ | 45 | | `rhed` | Yes | No | — | Row header cell. |
+ | 46 | | `corn` | Yes | No | — | Corner header cell. |
+ | 47 | | `srow` | Yes | No | — | Section row separator cell. |
+ | 48 | | `lcel` | Yes | No | — | Merge with left neighbor (horizontal span). |
+ | 49 | | `ucel` | Yes | No | — | Merge with upper neighbor (vertical span). |
+ | 50 | | `xcel` | Yes | No | — | Merge with left and upper neighbors (2D span). |
+ | 51 | | `nl` | Yes | No | — | New line (row separator). |
+ | 52 | Continuation Tokens | `thread` | Yes | Yes | `id` |
+ Continuation marker for split content; reuse same `id` across parts. |
+ | 53 | | `h_thread` | Yes | Yes | `id` | Horizontal stitching marker for split tables; reuse same `id`. |
+ | 54 | Binary Data Tokens | `base64` | No | No | — | Embedded binary data (base64). |
+ | 55 | | `uri` | No | No | — | External resource reference. |
+ | 56 | Content Tokens | `marker` | No | No | — | List/form marker content. |
+ | 57 | | `facets` | No | No | — | Container for application-specific derived properties. |
+ | 58 | Structural Tokens (Form) | `key` | No | No | — | Form item key (child of `form_item`). |
+ | 59 | | `value` | No | No | — | Form item value (child of `form_item`). |
+ """
+
+ # Root and metadata
+ DOCUMENT = "doctag"
+ HEAD = "head"
+ META = "meta"
+
+ # Special
+ PAGE_BREAK = "page_break"
+ TIME_BREAK = "time_break"
+
+ # Geometric and temporal
+ LOCATION = "location"
+ HOUR = "hour"
+ MINUTE = "minute"
+ SECOND = "second"
+ CENTISECOND = "centisecond"
+
+ # Semantic
+ TITLE = "title"
+ HEADING = "heading"
+ TEXT = "text"
+ CAPTION = "caption"
+ FOOTNOTE = "footnote"
+ PAGE_HEADER = "page_header"
+ PAGE_FOOTER = "page_footer"
+ WATERMARK = "watermark"
+ PICTURE = "picture"
+ FORM = "form"
+ FORM_ITEM = "form_item"
+ FORM_HEADING = "form_heading"
+ FORM_TEXT = "form_text"
+ HINT = "hint"
+ FORMULA = "formula"
+ CODE = "code"
+ LIST_TEXT = "list_text"
+ # LIST_ITEM = "list_item"
+ CHECKBOX = "checkbox"
+ OTSL = "otsl" # this will take care of the structure in the table.
+
+ # Grouping
+ SECTION = "section"
+ LIST = "list"
+ GROUP = "group"
+ FLOATING_GROUP = "floating_group"
+ # ORDERED_LIST = "ordered_list"
+ # UNORDERED_LIST = "unordered_list"
+
+ # Formatting
+ BOLD = "bold"
+ ITALIC = "italic"
+ STRIKETHROUGH = "strikethrough"
+ SUPERSCRIPT = "superscript"
+ SUBSCRIPT = "subscript"
+ RTL = "rtl"
+ INLINE = "inline"
+ BR = "br"
+
+ # Structural
+ # -- Tables
+ FCEL = "fcel"
+ ECEL = "ecel"
+ CHED = "ched"
+ RHED = "rhed"
+ CORN = "corn"
+ SROW = "srow"
+ LCEL = "lcel"
+ UCEL = "ucel"
+ XCEL = "xcel"
+ NL = "nl"
+ # -- Forms
+ KEY = "key"
+ IMPLICIT_KEY = "implicit_key"
+ VALUE = "value"
+
+ # Continuation
+ THREAD = "thread"
+ H_THREAD = "h_thread"
+
+ # Binary data / content helpers
+ BASE64 = "base64"
+ URI = "uri"
+ MARKER = "marker"
+ FACETS = "facets"
+
+
+class IDocTagsAttributeKey(str, Enum):
+ """Attribute keys allowed on DocTags tokens."""
+ VERSION = "version"
+ VALUE = "value"
+ RESOLUTION = "resolution"
+ LEVEL = "level"
+ SELECTED = "selected"
+ ORDERED = "ordered"
+ TYPE = "type"
+ CLASS = "class"
+ ID = "id"
-class IDocTagsTableToken(str, Enum):
- """Class to represent an LLM friendly representation of a Table."""
- CELL_LABEL_COLUMN_HEADER = ""
- CELL_LABEL_ROW_HEADER = ""
- CELL_LABEL_SECTION_HEADER = ""
- CELL_LABEL_DATA = ""
+class IDocTagsAttributeValue(str, Enum):
+ """Enumerated values for specific DocTags attributes."""
- OTSL_ECEL = "" # empty cell
- OTSL_FCEL = "" # cell with content
- OTSL_LCEL = "" # left looking cell,
- OTSL_UCEL = "" # up looking cell,
- OTSL_XCEL = "" # 2d extension cell (cross cell),
- OTSL_NL = "" # new line,
- OTSL_CHED = "" # - column header cell,
- OTSL_RHED = "" # - row header cell,
- OTSL_SROW = "" # - section row cell
+ # Generic boolean-like values
+ TRUE = "true"
+ FALSE = "false"
+
+ # Inline class values
+ FORMULA = "formula"
+ CODE = "code"
+ PICTURE = "picture"
+
+ # Floating group class values
+ DOCUMENT_INDEX = "document_index"
+ TABLE = "table"
+ FORM = "form"
+
+
+class IDocTagsVocabulary(BaseModel):
+ """IDocTagsVocabulary."""
+
+ # Allowed attributes per token (defined outside the Enum to satisfy mypy)
+ ALLOWED_ATTRIBUTES: ClassVar[dict[IDocTagsToken, set["IDocTagsAttributeKey"]]] = {
+ IDocTagsToken.DOCUMENT: {
+ IDocTagsAttributeKey.VERSION,
+ },
+ IDocTagsToken.LOCATION: {
+ IDocTagsAttributeKey.VALUE,
+ IDocTagsAttributeKey.RESOLUTION,
+ },
+ IDocTagsToken.HOUR: {IDocTagsAttributeKey.VALUE},
+ IDocTagsToken.MINUTE: {IDocTagsAttributeKey.VALUE},
+ IDocTagsToken.SECOND: {IDocTagsAttributeKey.VALUE},
+ IDocTagsToken.CENTISECOND: {IDocTagsAttributeKey.VALUE},
+ IDocTagsToken.HEADING: {IDocTagsAttributeKey.LEVEL},
+ IDocTagsToken.FORM_HEADING: {IDocTagsAttributeKey.LEVEL},
+ IDocTagsToken.CHECKBOX: {IDocTagsAttributeKey.SELECTED},
+ IDocTagsToken.SECTION: {IDocTagsAttributeKey.LEVEL},
+ IDocTagsToken.LIST: {IDocTagsAttributeKey.ORDERED},
+ IDocTagsToken.GROUP: {IDocTagsAttributeKey.TYPE},
+ IDocTagsToken.FLOATING_GROUP: {IDocTagsAttributeKey.CLASS},
+ IDocTagsToken.INLINE: {IDocTagsAttributeKey.CLASS},
+ IDocTagsToken.THREAD: {IDocTagsAttributeKey.ID},
+ IDocTagsToken.H_THREAD: {IDocTagsAttributeKey.ID},
+ }
+
+ # Allowed values for specific attributes (enumerations)
+ # Structure: token -> attribute name -> set of allowed string values
+ ALLOWED_ATTRIBUTE_VALUES: ClassVar[
+ dict[
+ IDocTagsToken,
+ dict["IDocTagsAttributeKey", set["IDocTagsAttributeValue"]],
+ ]
+ ] = {
+ # Grouping and inline enumerations
+ IDocTagsToken.LIST: {
+ IDocTagsAttributeKey.ORDERED: {
+ IDocTagsAttributeValue.TRUE,
+ IDocTagsAttributeValue.FALSE,
+ }
+ },
+ IDocTagsToken.CHECKBOX: {
+ IDocTagsAttributeKey.SELECTED: {
+ IDocTagsAttributeValue.TRUE,
+ IDocTagsAttributeValue.FALSE,
+ }
+ },
+ IDocTagsToken.INLINE: {
+ IDocTagsAttributeKey.CLASS: {
+ IDocTagsAttributeValue.FORMULA,
+ IDocTagsAttributeValue.CODE,
+ IDocTagsAttributeValue.PICTURE,
+ }
+ },
+ IDocTagsToken.FLOATING_GROUP: {
+ IDocTagsAttributeKey.CLASS: {
+ IDocTagsAttributeValue.DOCUMENT_INDEX,
+ IDocTagsAttributeValue.TABLE,
+ IDocTagsAttributeValue.PICTURE,
+ IDocTagsAttributeValue.FORM,
+ IDocTagsAttributeValue.CODE,
+ }
+ },
+ # Other attributes (e.g., level, type, id) are not enumerated here
+ }
+
+ ALLOWED_ATTRIBUTE_RANGE: ClassVar[
+ dict[IDocTagsToken, dict["IDocTagsAttributeKey", tuple[int, int]]]
+ ] = {
+ # Geometric: value in [0, res]; resolution optional.
+ # Keep conservative defaults aligned with existing usage.
+ IDocTagsToken.LOCATION: {
+ IDocTagsAttributeKey.VALUE: (0, DOCTAGS_RESOLUTION),
+ IDocTagsAttributeKey.RESOLUTION: (DOCTAGS_RESOLUTION, DOCTAGS_RESOLUTION),
+ },
+ # Temporal components
+ IDocTagsToken.HOUR: {IDocTagsAttributeKey.VALUE: (0, 99)},
+ IDocTagsToken.MINUTE: {IDocTagsAttributeKey.VALUE: (0, 59)},
+ IDocTagsToken.SECOND: {IDocTagsAttributeKey.VALUE: (0, 59)},
+ IDocTagsToken.CENTISECOND: {IDocTagsAttributeKey.VALUE: (0, 99)},
+ # Levels (N ≥ 1)
+ IDocTagsToken.HEADING: {IDocTagsAttributeKey.LEVEL: (1, 6)},
+ IDocTagsToken.FORM_HEADING: {IDocTagsAttributeKey.LEVEL: (1, 6)},
+ IDocTagsToken.SECTION: {IDocTagsAttributeKey.LEVEL: (1, 6)},
+ # Continuation markers (id length constraints)
+ IDocTagsToken.THREAD: {IDocTagsAttributeKey.ID: (1, 10)},
+ IDocTagsToken.H_THREAD: {IDocTagsAttributeKey.ID: (1, 10)},
+ }
+
+ # Self-closing tokens map
+ IS_SELFCLOSING: ClassVar[dict[IDocTagsToken, bool]] = {
+ IDocTagsToken.PAGE_BREAK: True,
+ IDocTagsToken.TIME_BREAK: True,
+ IDocTagsToken.LOCATION: True,
+ IDocTagsToken.HOUR: True,
+ IDocTagsToken.MINUTE: True,
+ IDocTagsToken.SECOND: True,
+ IDocTagsToken.CENTISECOND: True,
+ IDocTagsToken.BR: True,
+ # OTSL structural tokens are emitted as self-closing markers
+ IDocTagsToken.FCEL: True,
+ IDocTagsToken.ECEL: True,
+ IDocTagsToken.CHED: True,
+ IDocTagsToken.RHED: True,
+ IDocTagsToken.CORN: True,
+ IDocTagsToken.SROW: True,
+ IDocTagsToken.LCEL: True,
+ IDocTagsToken.UCEL: True,
+ IDocTagsToken.XCEL: True,
+ IDocTagsToken.NL: True,
+ # Continuation markers
+ IDocTagsToken.THREAD: True,
+ IDocTagsToken.H_THREAD: True,
+ }
@classmethod
- def get_special_tokens(
- cls,
- ):
- """Return all table-related special tokens.
+ def create_closing_token(cls, *, token: str) -> str:
+ r"""Create a closing tag from an opening tag string.
- Includes the opening/closing OTSL tags and each enum token value.
+ Example: "" -> ""
+ Validates the tag and ensures it is not self-closing.
+ If `token` is already a valid closing tag, it is returned unchanged.
"""
- special_tokens: list[str] = ["", ""]
- for token in cls:
- special_tokens.append(f"{token.value}")
+ if not isinstance(token, str) or not token.strip():
+ raise ValueError("token must be a non-empty string")
- return special_tokens
+ s = token.strip()
+ # Already a closing tag: validate and return as-is
+ if s.startswith("$", s)
+ if not m_close:
+ raise ValueError("invalid closing tag format")
+ name = m_close.group(1)
+ try:
+ IDocTagsToken(name)
+ except ValueError:
+ raise ValueError(f"unknown token '{name}'")
+ return s
-class IDocTagsToken(str, Enum):
- """IDocTagsToken."""
+ # Extract tag name from an opening tag while dropping attributes
+ m = re.match(r"^<\s*([a-zA-Z_][\w\-]*)\b[^>]*?(/?)\s*>$", s)
+ if not m:
+ raise ValueError("invalid opening tag format")
- _LOC_PREFIX = "loc_"
- _SECTION_HEADER_PREFIX = "section_header_level_"
+ name, trailing_slash = m.group(1), m.group(2)
- DOCUMENT = "doctag"
- VERSION = "version"
+ # Validate the tag name against known tokens
+ try:
+ tok_enum = IDocTagsToken(name)
+ except ValueError:
+ raise ValueError(f"unknown token '{name}'")
- OTSL = "otsl"
- ORDERED_LIST = "ordered_list"
- UNORDERED_LIST = "unordered_list"
+ # Disallow explicit self-closing markup or inherently self-closing tokens
+ if trailing_slash == "/":
+ raise ValueError(f"token '{name}' is self-closing; no closing tag")
+ if cls.IS_SELFCLOSING.get(tok_enum, False):
+ raise ValueError(f"token '{name}' is self-closing; no closing tag")
- PAGE_BREAK = "page_break"
+ return f""
- CAPTION = "caption"
- FOOTNOTE = "footnote"
- FORMULA = "formula"
- LIST_ITEM = "list_item"
- PAGE_FOOTER = "page_footer"
- PAGE_HEADER = "page_header"
- PICTURE = "picture"
- SECTION_HEADER = "section_header"
- TABLE = "table"
- TEXT = "text"
- TITLE = "title"
- DOCUMENT_INDEX = "document_index"
- CODE = "code"
- CHECKBOX_SELECTED = "checkbox_selected"
- CHECKBOX_UNSELECTED = "checkbox_unselected"
- FORM = "form"
- EMPTY_VALUE = "empty_value" # used for empty value fields in fillable forms
+ @classmethod
+ def create_doctag_root(
+ cls, *, version: str = DOCTAGS_VERSION, closing: bool = False
+ ) -> str:
+ """Create the document root tag.
+
+ - When `closing` is True, returns the closing root tag.
+ - When a `version` is provided, includes it as an attribute.
+ - Otherwise returns a bare opening root tag.
+ """
+ if closing:
+ return f""
+ elif version:
+ return f'<{IDocTagsToken.DOCUMENT.value} {IDocTagsAttributeKey.VERSION.value}="{version}">'
+ else:
+ # Version attribute is optional; emit bare root tag when not provided
+ return f"<{IDocTagsToken.DOCUMENT.value}>"
+
+ @classmethod
+ def create_threading_token(cls, *, id: str, horizontal: bool = False) -> str:
+ """Create a continuation threading token.
+
+ Emits `` or `` depending on
+ the `horizontal` flag. Validates required attributes against the
+ class schema and basic value sanity.
+ """
+ token = IDocTagsToken.H_THREAD if horizontal else IDocTagsToken.THREAD
+ # Ensure the required attribute is declared for this token
+ assert IDocTagsAttributeKey.ID in cls.ALLOWED_ATTRIBUTES.get(token, set())
+
+ # Validate id length if a range is specified
+ lo, hi = cls.ALLOWED_ATTRIBUTE_RANGE[token][IDocTagsAttributeKey.ID]
+ length = len(id)
+ if not (lo <= length <= hi):
+ raise ValueError(f"id length must be in [{lo}, {hi}]")
+
+ return f'<{token.value} {IDocTagsAttributeKey.ID.value}="{id}"/>'
+
+ @classmethod
+ def create_floating_group_token(
+ cls, *, value: IDocTagsAttributeValue, closing: bool = False
+ ) -> str:
+ """Create a floating group tag.
+
+ - When `closing` is True, returns the closing tag.
+ - Otherwise returns an opening tag with a class attribute derived from `value`.
+ """
+ if closing:
+ return f""
+ else:
+ return f'<{IDocTagsToken.FLOATING_GROUP.value} {IDocTagsAttributeKey.CLASS.value}="{value.value}">'
+
+ @classmethod
+ def create_list_token(cls, *, ordered: bool, closing: bool = False) -> str:
+ """Create a list tag.
+
+ - When `closing` is True, returns the closing tag.
+ - Otherwise returns an opening tag with an `ordered` boolean attribute.
+ """
+ if closing:
+ return f""
+ elif ordered:
+ return (
+ f"<{IDocTagsToken.LIST.value} "
+ f'{IDocTagsAttributeKey.ORDERED.value}="{IDocTagsAttributeValue.TRUE.value}">'
+ )
+ else:
+ return (
+ f"<{IDocTagsToken.LIST.value} "
+ f'{IDocTagsAttributeKey.ORDERED.value}="{IDocTagsAttributeValue.FALSE.value}">'
+ )
+
+ @classmethod
+ def create_heading_token(cls, *, level: int, closing: bool = False) -> str:
+ """Create a heading tag with validated level.
+
+ When `closing` is False, emits an opening tag with level attribute.
+ When `closing` is True, emits the corresponding closing tag.
+ """
+ lo, hi = cls.ALLOWED_ATTRIBUTE_RANGE[IDocTagsToken.HEADING][
+ IDocTagsAttributeKey.LEVEL
+ ]
+ if not (lo <= level <= hi):
+ raise ValueError(f"level must be in [{lo}, {hi}]")
+
+ if closing:
+ return f""
+ return f'<{IDocTagsToken.HEADING.value} {IDocTagsAttributeKey.LEVEL.value}="{level}">'
+
+ @classmethod
+ def create_location_token(
+ cls, *, value: int, resolution: int = DOCTAGS_RESOLUTION
+ ) -> str:
+ """Create a location token with value and resolution.
+
+ Validates both attributes using the configured ranges and ensures
+ `value` lies within [0, resolution]. Always emits the resolution
+ attribute for explicitness.
+ """
+ range_map = cls.ALLOWED_ATTRIBUTE_RANGE[IDocTagsToken.LOCATION]
+ # Validate resolution if a constraint exists
+ r_lo, r_hi = range_map.get(
+ IDocTagsAttributeKey.RESOLUTION, (resolution, resolution)
+ )
+ if not (r_lo <= resolution <= r_hi):
+ raise ValueError(f"resolution: {resolution} must be in [{r_lo}, {r_hi}]")
+
+ v_lo, v_hi = range_map[IDocTagsAttributeKey.VALUE]
+ if not (v_lo <= value <= v_hi):
+ raise ValueError(f"value: {value} must be in [{v_lo}, {v_hi}]")
+ if not (0 <= value <= resolution):
+ raise ValueError(f"value: {value} must be in [0, {resolution}]")
+
+ return (
+ f"<{IDocTagsToken.LOCATION.value} "
+ f'{IDocTagsAttributeKey.VALUE.value}="{value}" '
+ f'{IDocTagsAttributeKey.RESOLUTION.value}="{resolution}"/>'
+ )
@classmethod
def get_special_tokens(
cls,
*,
- page_dimension: Tuple[int, int] = (500, 500),
include_location_tokens: bool = True,
- include_code_class: bool = False,
- include_picture_class: bool = False,
- ):
- """Function to get all special document tokens."""
+ include_temporal_tokens: bool = True,
+ ) -> list[str]:
+ """Return all DocTags special tokens.
+
+ Rules:
+ - If a token has attributes, do not emit a bare opening tag without attributes.
+ - Respect `include_location_tokens` and `include_temporal_tokens` to limit
+ generation of location and time-related tokens.
+ - Emit self-closing tokens as `` when they have no attributes.
+ - Emit non-self-closing tokens as paired `` and `` when they
+ have no attributes.
+ """
special_tokens: list[str] = []
- for token in cls:
- if not token.value.endswith("_"):
- special_tokens.append(f"<{token.value}>")
- special_tokens.append(f"")
-
- for i in range(6):
- special_tokens += [
- f"<{IDocTagsToken._SECTION_HEADER_PREFIX.value}{i}>",
- f"",
- ]
- special_tokens.extend(IDocTagsTableToken.get_special_tokens())
+ temporal_tokens = {
+ IDocTagsToken.HOUR,
+ IDocTagsToken.MINUTE,
+ IDocTagsToken.SECOND,
+ IDocTagsToken.CENTISECOND,
+ }
- if include_picture_class:
- special_tokens.extend([t.value for t in _PictureClassificationToken])
+ for token in IDocTagsToken:
+ # Optional gating for location/temporal tokens
+ if not include_location_tokens and token is IDocTagsToken.LOCATION:
+ continue
+ if not include_temporal_tokens and token in temporal_tokens:
+ continue
- if include_code_class:
- special_tokens.extend([t.value for t in _CodeLanguageToken])
+ name = token.value
+ is_selfclosing = bool(cls.IS_SELFCLOSING.get(token, False))
+
+ # Attribute-aware emission
+ attrs = cls.ALLOWED_ATTRIBUTES.get(token, set())
+ if attrs:
+ # Enumerated attribute values
+ enum_map = cls.ALLOWED_ATTRIBUTE_VALUES.get(token, {})
+ for attr_name, allowed_vals in enum_map.items():
+ for v in sorted(allowed_vals, key=lambda x: x.value):
+ if is_selfclosing:
+ special_tokens.append(
+ f'<{name} {attr_name.value}="{v.value}"/>'
+ )
+ else:
+ special_tokens.append(
+ f'<{name} {attr_name.value}="{v.value}">'
+ )
+ special_tokens.append(f"")
+
+ # Ranged attribute values (emit a conservative, complete range)
+ range_map = cls.ALLOWED_ATTRIBUTE_RANGE.get(token, {})
+ for attr_name, (lo, hi) in range_map.items():
+ # Keep the list size reasonable by skipping optional resolution enumeration
+ if (
+ token is IDocTagsToken.LOCATION
+ and attr_name is IDocTagsAttributeKey.RESOLUTION
+ ):
+ continue
+ for n in range(lo, hi + 1):
+ if is_selfclosing:
+ special_tokens.append(f'<{name} {attr_name.value}="{n}"/>')
+ else:
+ special_tokens.append(f'<{name} {attr_name.value}="{n}">')
+ special_tokens.append(f"")
+ # Do not emit a bare tag for attribute-bearing tokens
+ continue
- if include_location_tokens:
- # Adding dynamically generated location-tokens
- for i in range(0, max(page_dimension[0], page_dimension[1])):
- special_tokens.append(f"<{IDocTagsToken._LOC_PREFIX.value}{i}/>")
+ # Tokens without attributes
+ if is_selfclosing:
+ special_tokens.append(f"<{name}/>")
+ else:
+ special_tokens.append(f"<{name}>")
+ special_tokens.append(f"")
return special_tokens
@classmethod
- def create_token_name_from_doc_item_label(cls, label: str, level: int = 1) -> str:
- """Get token corresponding to passed doc item label."""
- doc_token_by_item_label = {
- DocItemLabel.CAPTION: IDocTagsToken.CAPTION,
- DocItemLabel.FOOTNOTE: IDocTagsToken.FOOTNOTE,
- DocItemLabel.FORMULA: IDocTagsToken.FORMULA,
- DocItemLabel.LIST_ITEM: IDocTagsToken.LIST_ITEM,
- DocItemLabel.PAGE_FOOTER: IDocTagsToken.PAGE_FOOTER,
- DocItemLabel.PAGE_HEADER: IDocTagsToken.PAGE_HEADER,
- DocItemLabel.PICTURE: IDocTagsToken.PICTURE,
- DocItemLabel.TABLE: IDocTagsToken.TABLE,
- DocItemLabel.TEXT: IDocTagsToken.TEXT,
- DocItemLabel.TITLE: IDocTagsToken.TITLE,
- DocItemLabel.DOCUMENT_INDEX: IDocTagsToken.DOCUMENT_INDEX,
- DocItemLabel.CODE: IDocTagsToken.CODE,
- DocItemLabel.CHECKBOX_SELECTED: IDocTagsToken.CHECKBOX_SELECTED,
- DocItemLabel.CHECKBOX_UNSELECTED: IDocTagsToken.CHECKBOX_UNSELECTED,
- DocItemLabel.FORM: IDocTagsToken.FORM,
- # Fallback mappings for labels without dedicated tokens in IDocTagsToken
- DocItemLabel.KEY_VALUE_REGION: IDocTagsToken.TEXT,
- DocItemLabel.PARAGRAPH: IDocTagsToken.TEXT,
- DocItemLabel.REFERENCE: IDocTagsToken.TEXT,
- DocItemLabel.CHART: IDocTagsToken.PICTURE,
- }
+ def create_selfclosing_token(
+ cls,
+ *,
+ token: IDocTagsToken,
+ attrs: Optional[dict["IDocTagsAttributeKey", Any]] = None,
+ ) -> str:
+ """Create a self-closing token with optional attributes (default None).
+
+ - Validates the token is declared self-closing.
+ - Validates provided attributes against ``ALLOWED_ATTRIBUTES`` and
+ ``ALLOWED_ATTRIBUTE_VALUES`` or ``ALLOWED_ATTRIBUTE_RANGE`` when present.
+ """
+ if not cls.IS_SELFCLOSING.get(token, False):
+ raise ValueError(f"token '{token.value}' is not self-closing")
+
+ # No attributes requested
+ if not attrs:
+ return f"<{token.value}/>"
+
+ # Validate attribute keys
+ allowed_keys = cls.ALLOWED_ATTRIBUTES.get(token, set())
+ for k in attrs.keys():
+ if k not in allowed_keys:
+ raise ValueError(
+ f"attribute '{getattr(k, 'value', str(k))}' not allowed on '{token.value}'"
+ )
- res: str
- if label == DocItemLabel.SECTION_HEADER:
- res = f"{IDocTagsToken._SECTION_HEADER_PREFIX}{level}"
- else:
- try:
- res = doc_token_by_item_label[DocItemLabel(label)].value
- except KeyError as e:
- raise RuntimeError(f"Unexpected DocItemLabel: {label}") from e
- return res
+ # Validate values either via enumerations or numeric ranges
+ enum_map = cls.ALLOWED_ATTRIBUTE_VALUES.get(token, {})
+ range_map = cls.ALLOWED_ATTRIBUTE_RANGE.get(token, {})
+
+ def _coerce_value(val: Any) -> str:
+ # Accept enums or native scalars; stringify for emission
+ if isinstance(val, Enum):
+ return val.value # type: ignore[attr-defined]
+ return str(val)
+
+ parts: list[str] = []
+ for k, v in attrs.items():
+ # Enumerated allowed values
+ if k in enum_map:
+ allowed = enum_map[k]
+ # Accept either the enum or its string representation
+ v_norm = v.value if isinstance(v, Enum) else str(v)
+ allowed_strs = {a.value for a in allowed}
+ if v_norm not in allowed_strs:
+ raise ValueError(
+ f"invalid value '{v_norm}' for '{k.value}' on '{token.value}'"
+ )
+ parts.append(f'{k.value}="{v_norm}"')
+ continue
+
+ # Ranged numeric values
+ if k in range_map:
+ lo, hi = range_map[k]
+ try:
+ v_num = int(v)
+ except Exception:
+ raise ValueError(
+ f"attribute '{k.value}' on '{token.value}' must be an integer"
+ )
+ if not (lo <= v_num <= hi):
+ raise ValueError(
+ f"attribute '{k.value}' must be in [{lo}, {hi}] for '{token.value}'"
+ )
+ parts.append(f'{k.value}="{v_num}"')
+ continue
+
+ # Free-form attribute without specific constraints
+ parts.append(f'{k.value}="{_coerce_value(v)}"')
+
+ # Assemble tag
+ attrs_text = " ".join(parts)
+ return f"<{token.value} {attrs_text}/>"
-class IDocTagsParams(DocTagsParams):
- """DocTags-specific serialization parameters."""
+class IDocTagsSerializationMode(str, Enum):
+ """Serialization mode for IDocTags output."""
+ HUMAN_FRIENDLY = "human_friendly"
+ LLM_FRIENDLY = "llm_friendly"
+
+
+class IDocTagsParams(CommonParams):
+ """IDocTags-specific serialization parameters independent of DocTags."""
+
+ # Geometry & content controls (aligned with DocTags defaults)
+ xsize: int = DOCTAGS_RESOLUTION
+ ysize: int = DOCTAGS_RESOLUTION
+ add_location: bool = True
+ add_caption: bool = True
+ add_content: bool = True
+ add_table_cell_location: bool = False
+ add_page_break: bool = True
+
+ mode: IDocTagsSerializationMode = IDocTagsSerializationMode.HUMAN_FRIENDLY
+
+ # IDocTags formatting
do_self_closing: bool = True
pretty_indentation: Optional[str] = 2 * " "
+ # Expand self-closing forms of non-self-closing tokens after pretty-printing
+ preserve_empty_non_selfclosing: bool = True
+
+
+def _get_delim(*, params: IDocTagsParams) -> str:
+ """Return record delimiter based on IDocTagsSerializationMode."""
+ if params.mode == IDocTagsSerializationMode.HUMAN_FRIENDLY:
+ return "\n"
+ if params.mode == IDocTagsSerializationMode.LLM_FRIENDLY:
+ return ""
+ raise RuntimeError(f"Unknown IDocTags mode: {params.mode}")
class IDocTagsListSerializer(BaseModel, BaseListSerializer):
@@ -217,8 +888,9 @@ def serialize(
This emits list containers (````/````) and
serializes children explicitly. Nested ``ListGroup`` items are emitted as
- siblings without an enclosing ```` wrapper, while structural
- wrappers are still preserved even when content is suppressed.
+ siblings, and individual list items are not wrapped here. The text
+ serializer is responsible for wrapping list item content (as
+ ````), so this serializer remains agnostic of item types.
Args:
item: The list group to serialize.
@@ -236,13 +908,13 @@ def serialize(
params = IDocTagsParams(**kwargs)
# Build list children explicitly. Requirements:
- # 1) / can be children of lists.
- # 2) Do NOT wrap nested lists into , even if they are
+ # 1)
can be children of lists.
+ # 2) Do NOT wrap nested lists into , even if they are
# children of a ListItem in the logical structure.
# 3) Still ensure structural wrappers are preserved even when
# content is suppressed (e.g., add_content=False).
item_results: list[SerializationResult] = []
- child_results_wrapped: list[str] = []
+ child_texts: list[str] = []
excluded = doc_serializer.get_excluded_refs(**kwargs)
for child_ref in item.children:
@@ -262,7 +934,7 @@ def serialize(
**kwargs,
)
if sub_res.text:
- child_results_wrapped.append(sub_res.text)
+ child_texts.append(sub_res.text)
item_results.append(sub_res)
continue
@@ -274,7 +946,8 @@ def serialize(
my_visited.add(child.self_ref)
- # Serialize the list item content (DocTagsTextSerializer will not wrap it)
+ # Serialize the list item content; wrapping is handled by the text
+ # serializer (as ), not here.
child_res = doc_serializer.serialize(
item=child,
list_level=list_level + 1,
@@ -283,15 +956,11 @@ def serialize(
**kwargs,
)
item_results.append(child_res)
- # Wrap the content into , without any nested list content.
- child_text_wrapped = _wrap(
- text=f"{child_res.text}",
- wrap_tag=IDocTagsToken.LIST_ITEM.value,
- )
- child_results_wrapped.append(child_text_wrapped)
+ if child_res.text:
+ child_texts.append(child_res.text)
- # After the , append any nested lists (children of this ListItem)
- # as siblings at the same level (not wrapped in ).
+ # After the , append any nested lists (children of this ListItem)
+ # as siblings at the same level (not wrapped in ).
for subref in child.children:
sub = subref.resolve(doc)
if (
@@ -308,24 +977,138 @@ def serialize(
**kwargs,
)
if sub_res.text:
- child_results_wrapped.append(sub_res.text)
+ child_texts.append(sub_res.text)
item_results.append(sub_res)
delim = _get_delim(params=params)
- if child_results_wrapped:
- text_res = delim.join(child_results_wrapped)
+ if child_texts:
+ text_res = delim.join(child_texts)
text_res = f"{text_res}{delim}"
- wrap_tag = (
- IDocTagsToken.ORDERED_LIST.value
+ open_token = (
+ IDocTagsVocabulary.create_list_token(ordered=True)
if item.first_item_is_enumerated(doc)
- else IDocTagsToken.UNORDERED_LIST.value
+ else IDocTagsVocabulary.create_list_token(ordered=False)
)
- text_res = _wrap(text=text_res, wrap_tag=wrap_tag)
+ text_res = _wrap_token(text=text_res, open_token=open_token)
else:
text_res = ""
return create_ser_result(text=text_res, span_source=item_results)
+class IDocTagsTextSerializer(BaseModel, BaseTextSerializer):
+ """IDocTags-specific text item serializer using `` tokens."""
+
+ @override
+ def serialize(
+ self,
+ *,
+ item: "TextItem",
+ doc_serializer: BaseDocSerializer,
+ doc: DoclingDocument,
+ visited: Optional[set[str]] = None,
+ **kwargs: Any,
+ ) -> SerializationResult:
+ """Serialize a ``TextItem`` into IDocTags markup.
+
+ Depending on parameters, emits meta blocks, location tokens, and the
+ item's textual content (prefixing code language for ``CodeItem``). For
+ floating items, captions may be appended. The result can be wrapped in a
+ tag derived from the item's label when applicable.
+
+ Args:
+ item: The text-like item to serialize.
+ doc_serializer: The document-level serializer for delegating nested items.
+ doc: The document used to resolve references and children.
+ visited: Set of already visited item refs to avoid cycles.
+ **kwargs: Additional serializer parameters forwarded to ``IDocTagsParams``.
+
+ Returns:
+ A ``SerializationResult`` with the serialized text and span source.
+ """
+ my_visited = visited if visited is not None else set()
+ params = IDocTagsParams(**kwargs)
+
+ # Determine wrapper open-token for this item using IDocTags vocabulary.
+ # - SectionHeaderItem: use ... .
+ # - Other text-like items: map the label to an IDocTagsToken; for
+ # list items, this maps to and keeps the text serializer
+ # free of type-based special casing.
+ wrap_open_token: Optional[str]
+ if isinstance(item, SectionHeaderItem):
+ wrap_open_token = IDocTagsVocabulary.create_heading_token(level=item.level)
+ elif isinstance(item, ListItem):
+ tok = IDocTagsToken.LIST_TEXT
+ wrap_open_token = f"<{tok.value}>"
+ else:
+ label_value = str(item.label)
+ try:
+ tok = IDocTagsToken(label_value)
+ wrap_open_token = f"<{tok.value}>"
+ except ValueError:
+ raise ValueError(
+ f"Unsupported IDocTags token for label '{label_value}'"
+ )
+
+ parts: list[str] = []
+
+ if item.meta:
+ meta_res = doc_serializer.serialize_meta(item=item, **kwargs)
+ if meta_res.text:
+ parts.append(meta_res.text)
+
+ if params.add_location:
+ # Use IDocTags `` tokens instead of ``
+ loc = _create_location_tokens_for_item(item=item, doc=doc)
+ if loc:
+ parts.append(loc)
+
+ if params.add_content:
+ if (
+ item.text == ""
+ and len(item.children) == 1
+ and isinstance(
+ (child_group := item.children[0].resolve(doc)), InlineGroup
+ )
+ ):
+ ser_res = doc_serializer.serialize(item=child_group, visited=my_visited)
+ text_part = ser_res.text
+ else:
+ text_part = doc_serializer.post_process(
+ text=item.text,
+ formatting=item.formatting,
+ hyperlink=item.hyperlink,
+ )
+
+ # For code blocks, preserve language using a lightweight facets marker
+ # e.g., language=python before the code content.
+ if isinstance(item, CodeItem):
+ lang = getattr(item.code_language, "value", str(item.code_language))
+ if lang:
+ parts.append(
+ _wrap(
+ text=f"language={lang.lower()}",
+ wrap_tag=IDocTagsToken.FACETS.value,
+ )
+ )
+ # Keep the textual code content as-is
+ text_part = text_part
+ else:
+ text_part = text_part.strip()
+
+ if text_part:
+ parts.append(text_part)
+
+ if params.add_caption and isinstance(item, FloatingItem):
+ cap_text = doc_serializer.serialize_captions(item=item, **kwargs).text
+ if cap_text:
+ parts.append(cap_text)
+
+ text_res = "".join(parts)
+ if wrap_open_token is not None:
+ text_res = _wrap_token(text=text_res, open_token=wrap_open_token)
+ return create_ser_result(text=text_res, span_source=item)
+
+
class IDocTagsMetaSerializer(BaseModel, BaseMetaSerializer):
"""DocTags-specific meta serializer."""
@@ -401,7 +1184,7 @@ def _serialize_meta_field(self, meta: BaseMeta, name: str) -> Optional[str]:
return None
-class IDocTagsPictureSerializer(DocTagsPictureSerializer):
+class IDocTagsPictureSerializer(BasePictureSerializer):
"""DocTags-specific picture item serializer."""
@override
@@ -414,25 +1197,36 @@ def serialize(
**kwargs: Any,
) -> SerializationResult:
"""Serializes the passed item."""
- params = DocTagsParams(**kwargs)
+ params = IDocTagsParams(**kwargs)
+
+ open_token: str = IDocTagsVocabulary.create_floating_group_token(
+ value=IDocTagsAttributeValue.PICTURE
+ )
+ close_token: str = IDocTagsVocabulary.create_floating_group_token(
+ value=IDocTagsAttributeValue.PICTURE, closing=True
+ )
+
+ # Build caption (as a sibling of the picture within the floating_group)
res_parts: list[SerializationResult] = []
- is_chart = False
+ caption_text = ""
+ if params.add_caption:
+ cap_res = doc_serializer.serialize_captions(item=item, **kwargs)
+ if cap_res.text:
+ caption_text = cap_res.text
+ res_parts.append(cap_res)
+ # Build picture inner content (meta + body) that will go inside ...
+ picture_inner_parts: list[str] = []
if item.self_ref not in doc_serializer.get_excluded_refs(**kwargs):
-
if item.meta:
meta_res = doc_serializer.serialize_meta(item=item, **kwargs)
if meta_res.text:
+ picture_inner_parts.append(meta_res.text)
res_parts.append(meta_res)
body = ""
if params.add_location:
- body += item.get_location_tokens(
- doc=doc,
- xsize=params.xsize,
- ysize=params.ysize,
- self_closing=params.do_self_closing,
- )
+ body += _create_location_tokens_for_item(item=item, doc=doc)
# handle tabular chart data
chart_data: Optional[TableData] = None
@@ -441,50 +1235,421 @@ def serialize(
if chart_data and chart_data.table_cells:
temp_doc = DoclingDocument(name="temp")
temp_table = temp_doc.add_table(data=chart_data)
- otsl_content = temp_table.export_to_otsl(
- temp_doc,
- add_cell_location=False,
- # Suppress chart cell text if global content is off
- add_cell_text=params.add_content,
- self_closing=params.do_self_closing,
- table_token=IDocTagsTableToken,
+ # Reuse the IDocTags table emission for chart data
+ params_chart = IDocTagsParams(
+ **{
+ **params.model_dump(),
+ "add_table_cell_location": False,
+ }
+ )
+ otsl_content = IDocTagsTableSerializer()._emit_otsl(
+ item=temp_table, # type: ignore[arg-type]
+ doc_serializer=doc_serializer,
+ doc=temp_doc,
+ params=params_chart,
+ **kwargs,
)
body += otsl_content
- res_parts.append(create_ser_result(text=body, span_source=item))
+ if body:
+ picture_inner_parts.append(body)
+ res_parts.append(create_ser_result(text=body, span_source=item))
+
+ picture_text = "".join(picture_inner_parts)
+ if picture_text:
+ picture_text = _wrap(
+ text=picture_text, wrap_tag=IDocTagsToken.PICTURE.value
+ )
+
+ # Compose final structure for picture group:
+ # [] ...
+ composed_inner = f"{caption_text}{picture_text}"
+ text_res = ""
+ if composed_inner:
+ text_res = f"{open_token}{composed_inner}{close_token}"
+
+ return create_ser_result(text=text_res, span_source=res_parts)
+
+
+class IDocTagsTableSerializer(BaseTableSerializer):
+ """DocTags-specific table item serializer."""
+
+ # _get_table_token no longer needed; OTSL tokens are emitted via vocabulary
+
+ def _emit_otsl(
+ self,
+ *,
+ item: TableItem,
+ doc_serializer: BaseDocSerializer,
+ doc: DoclingDocument,
+ params: "IDocTagsParams",
+ **kwargs: Any,
+ ) -> str:
+ """Emit OTSL payload using IDocTags tokens and location semantics.
+
+ Raises ValueError when per-cell location is requested but the
+ document/page context is unavailable.
+ """
+ if not item.data or not item.data.table_cells:
+ return ""
+
+ nrows, ncols = item.data.num_rows, item.data.num_cols
+
+ # If per-cell location is requested and any cell has a bbox, we
+ # require page context from the table provenance and document pages.
+ need_cell_loc = params.add_table_cell_location and any(
+ (c.bbox is not None) for row in item.data.grid for c in row
+ )
+
+ if params.add_table_cell_location and (not need_cell_loc):
+ raise ValueError("Missing cell-locations in the table-grid.")
+
+ page_no = 0
+ if need_cell_loc:
+ if not item.prov:
+ raise ValueError(
+ "Per-cell location requested but table has no provenance (page_no)."
+ )
+ page_no = item.prov[0].page_no
+ if not doc.pages or page_no not in doc.pages:
+ raise ValueError(
+ f"Per-cell location requested but no page info for page {page_no}."
+ )
+ page_w, page_h = doc.pages[page_no].size.as_tuple()
+ if page_w <= 0 or page_h <= 0:
+ raise ValueError(
+ f"Invalid page size ({page_w}, {page_h}) for page {page_no}."
+ )
+ else:
+ # Defaults will not be used unless a bbox is present and
+ # add_table_cell_location is true
+ page_w, page_h = (1.0, 1.0)
+
+ parts: list[str] = []
+ for i in range(nrows):
+ for j in range(ncols):
+ cell = item.data.grid[i][j]
+ content = cell._get_text(
+ doc=doc, doc_serializer=doc_serializer, **kwargs
+ ).strip()
+
+ rowspan, rowstart = cell.row_span, cell.start_row_offset_idx
+ colspan, colstart = cell.col_span, cell.start_col_offset_idx
+
+ # Optional per-cell location
+ cell_loc = ""
+ if params.add_table_cell_location:
+
+ if cell.bbox is None:
+ raise ValueError("Missing cell-bbox in the table-grid.")
+
+ bbox = cell.bbox.to_top_left_origin(page_h).as_tuple()
+ cell_loc = _create_location_tokens_for_bbox(
+ bbox=bbox,
+ page_w=page_w,
+ page_h=page_h,
+ xres=params.xsize,
+ yres=params.ysize,
+ )
+
+ if rowstart == i and colstart == j:
+ if content:
+ if cell.column_header:
+ parts.append(
+ IDocTagsVocabulary.create_selfclosing_token(
+ token=IDocTagsToken.CHED
+ )
+ )
+ elif cell.row_header:
+ parts.append(
+ IDocTagsVocabulary.create_selfclosing_token(
+ token=IDocTagsToken.RHED
+ )
+ )
+ elif cell.row_section:
+ parts.append(
+ IDocTagsVocabulary.create_selfclosing_token(
+ token=IDocTagsToken.SROW
+ )
+ )
+ else:
+ parts.append(
+ IDocTagsVocabulary.create_selfclosing_token(
+ token=IDocTagsToken.FCEL
+ )
+ )
+
+ if params.add_table_cell_location:
+ parts.append(cell_loc)
+ if params.add_content:
+ parts.append(content)
+ else:
+ parts.append(
+ IDocTagsVocabulary.create_selfclosing_token(
+ token=IDocTagsToken.ECEL
+ )
+ )
+ elif rowstart != i and colspan == 1:
+ parts.append(
+ IDocTagsVocabulary.create_selfclosing_token(
+ token=IDocTagsToken.UCEL
+ )
+ )
+ elif colstart != j and rowspan == 1:
+ parts.append(
+ IDocTagsVocabulary.create_selfclosing_token(
+ token=IDocTagsToken.LCEL
+ )
+ )
+ else:
+ parts.append(
+ IDocTagsVocabulary.create_selfclosing_token(
+ token=IDocTagsToken.XCEL
+ )
+ )
+
+ parts.append(
+ IDocTagsVocabulary.create_selfclosing_token(token=IDocTagsToken.NL)
+ )
+
+ return "".join(parts)
+
+ @override
+ def serialize(
+ self,
+ *,
+ item: TableItem,
+ doc_serializer: BaseDocSerializer,
+ doc: DoclingDocument,
+ visited: Optional[set[str]] = None,
+ **kwargs: Any,
+ ) -> SerializationResult:
+ """Serializes the passed item."""
+ params = IDocTagsParams(**kwargs)
+
+ # FIXME: we might need to check the label to distinguish between TABLE and DOCUMENT_INDEX label
+ open_token: str = IDocTagsVocabulary.create_floating_group_token(
+ value=IDocTagsAttributeValue.TABLE
+ )
+ close_token: str = IDocTagsVocabulary.create_floating_group_token(
+ value=IDocTagsAttributeValue.TABLE, closing=True
+ )
+
+ res_parts: list[SerializationResult] = []
+
+ # Caption as sibling of the OTSL payload within the floating group
+ caption_text = ""
if params.add_caption:
cap_res = doc_serializer.serialize_captions(item=item, **kwargs)
if cap_res.text:
+ caption_text = cap_res.text
res_parts.append(cap_res)
- text_res = "".join([r.text for r in res_parts])
- if text_res:
- token = IDocTagsToken.create_token_name_from_doc_item_label(
- label=DocItemLabel.CHART if is_chart else DocItemLabel.PICTURE,
+ # Build table payload: location (if any) + OTSL content inside ...
+ otsl_payload = ""
+ if item.self_ref not in doc_serializer.get_excluded_refs(**kwargs):
+ body = ""
+ if params.add_location:
+ body += _create_location_tokens_for_item(
+ item=item, doc=doc, xres=params.xsize, yres=params.ysize
+ )
+
+ otsl_text = self._emit_otsl(
+ item=item,
+ doc_serializer=doc_serializer,
+ doc=doc,
+ params=params,
+ visited=visited,
+ **kwargs,
)
- text_res = _wrap(text=text_res, wrap_tag=token)
+ body += otsl_text
+ if body:
+ otsl_payload = _wrap(text=body, wrap_tag=IDocTagsToken.OTSL.value)
+ res_parts.append(create_ser_result(text=body, span_source=item))
+
+ composed_inner = f"{caption_text}{otsl_payload}"
+ text_res = ""
+ if composed_inner:
+ text_res = f"{open_token}{composed_inner}{close_token}"
+
return create_ser_result(text=text_res, span_source=res_parts)
-class IDocTagsTableSerializer(DocTagsTableSerializer):
- """DocTags-specific table item serializer."""
+class IDocTagsInlineSerializer(BaseInlineSerializer):
+ """Inline serializer emitting IDocTags `` and `` tokens."""
+
+ @override
+ def serialize(
+ self,
+ *,
+ item: InlineGroup,
+ doc_serializer: BaseDocSerializer,
+ doc: DoclingDocument,
+ list_level: int = 0,
+ visited: Optional[set[str]] = None,
+ **kwargs: Any,
+ ) -> SerializationResult:
+ """Serialize inline content with optional location into IDocTags text."""
+ my_visited = visited if visited is not None else set()
+ params = IDocTagsParams(**kwargs)
+ parts: list[SerializationResult] = []
+ if params.add_location:
+ # Create a single enclosing bbox over inline children
+ boxes: list[tuple[float, float, float, float]] = []
+ prov_page_w_h: Optional[tuple[float, float, int]] = None
+ for it, _ in doc.iterate_items(root=item):
+ if isinstance(it, DocItem) and it.prov:
+ for prov in it.prov:
+ page_w, page_h = doc.pages[prov.page_no].size.as_tuple()
+ boxes.append(prov.bbox.to_top_left_origin(page_h).as_tuple())
+ prov_page_w_h = (page_w, page_h, prov.page_no)
+ if boxes and prov_page_w_h is not None:
+ x0 = min(b[0] for b in boxes)
+ y0 = min(b[1] for b in boxes)
+ x1 = max(b[2] for b in boxes)
+ y1 = max(b[3] for b in boxes)
+ page_w, page_h, _ = prov_page_w_h
+ loc_str = _create_location_tokens_for_bbox(
+ bbox=(x0, y0, x1, y1),
+ page_w=page_w,
+ page_h=page_h,
+ xres=params.xsize,
+ yres=params.ysize,
+ )
+ parts.append(create_ser_result(text=loc_str))
+ params.add_location = False
+ parts.extend(
+ doc_serializer.get_parts(
+ item=item,
+ list_level=list_level,
+ is_inline_scope=True,
+ visited=my_visited,
+ **{**kwargs, **params.model_dump()},
+ )
+ )
+ delim = _get_delim(params=params)
+ text_res = delim.join([p.text for p in parts if p.text])
+ if text_res:
+ text_res = f"{text_res}{delim}"
+ text_res = _wrap(text=text_res, wrap_tag=IDocTagsToken.INLINE.value)
+ return create_ser_result(text=text_res, span_source=parts)
+
+
+class IDocTagsFallbackSerializer(BaseFallbackSerializer):
+ """Fallback serializer concatenating text for list/inline groups."""
+
+ @override
+ def serialize(
+ self,
+ *,
+ item: NodeItem,
+ doc_serializer: BaseDocSerializer,
+ doc: DoclingDocument,
+ **kwargs: Any,
+ ) -> SerializationResult:
+ """Serialize unsupported nodes by concatenating their textual parts."""
+ if isinstance(item, (ListGroup, InlineGroup)):
+ parts = doc_serializer.get_parts(item=item, **kwargs)
+ text_res = "\n".join([p.text for p in parts if p.text])
+ return create_ser_result(text=text_res, span_source=parts)
+ return create_ser_result()
- def _get_table_token(self) -> Any:
- return IDocTagsTableToken
+class IDocTagsKeyValueSerializer(BaseKeyValueSerializer):
+ """No-op serializer for key/value items in IDocTags."""
+
+ @override
+ def serialize(
+ self,
+ *,
+ item: KeyValueItem,
+ doc_serializer: BaseDocSerializer,
+ doc: DoclingDocument,
+ **kwargs: Any,
+ ) -> SerializationResult:
+ """Return an empty result for key/value items."""
+ return create_ser_result()
-class IDocTagsDocSerializer(DocTagsDocSerializer):
- """DocTags document serializer."""
+class IDocTagsFormSerializer(BaseFormSerializer):
+ """No-op serializer for form items in IDocTags."""
+
+ @override
+ def serialize(
+ self,
+ *,
+ item: FormItem,
+ doc_serializer: BaseDocSerializer,
+ doc: DoclingDocument,
+ **kwargs: Any,
+ ) -> SerializationResult:
+ """Return an empty result for form items."""
+ return create_ser_result()
+
+
+class IDocTagsAnnotationSerializer(BaseAnnotationSerializer):
+ """No-op annotation serializer; IDocTags relies on meta instead."""
+
+ @override
+ def serialize(
+ self,
+ *,
+ item: DocItem,
+ doc: DoclingDocument,
+ **kwargs: Any,
+ ) -> SerializationResult:
+ """Return an empty result; annotations are handled via meta."""
+ return create_ser_result()
+
+
+class IDocTagsDocSerializer(DocSerializer):
+ """IDocTags document serializer."""
+
+ text_serializer: BaseTextSerializer = IDocTagsTextSerializer()
+ table_serializer: BaseTableSerializer = IDocTagsTableSerializer()
picture_serializer: BasePictureSerializer = IDocTagsPictureSerializer()
+ key_value_serializer: BaseKeyValueSerializer = IDocTagsKeyValueSerializer()
+ form_serializer: BaseFormSerializer = IDocTagsFormSerializer()
+ fallback_serializer: BaseFallbackSerializer = IDocTagsFallbackSerializer()
+
+ list_serializer: BaseListSerializer = IDocTagsListSerializer()
+ inline_serializer: BaseInlineSerializer = IDocTagsInlineSerializer()
+
meta_serializer: BaseMetaSerializer = IDocTagsMetaSerializer()
- table_serializer: BaseTableSerializer = IDocTagsTableSerializer()
+ annotation_serializer: BaseAnnotationSerializer = IDocTagsAnnotationSerializer()
+
params: IDocTagsParams = IDocTagsParams()
@override
def _meta_is_wrapped(self) -> bool:
return True
+ @override
+ def serialize_captions(
+ self,
+ item: FloatingItem,
+ **kwargs: Any,
+ ) -> SerializationResult:
+ """Serialize the item's captions with IDocTags location tokens."""
+ params = IDocTagsParams(**kwargs)
+ results: list[SerializationResult] = []
+ if item.captions:
+ cap_res = super().serialize_captions(item, **kwargs)
+ if cap_res.text and params.add_location:
+ for caption in item.captions:
+ if caption.cref not in self.get_excluded_refs(**kwargs):
+ if isinstance(cap := caption.resolve(self.doc), DocItem):
+ loc_txt = _create_location_tokens_for_item(
+ item=cap, doc=self.doc
+ )
+ results.append(create_ser_result(text=loc_txt))
+ if cap_res.text and params.add_content:
+ results.append(cap_res)
+ text_res = "".join([r.text for r in results])
+ if text_res:
+ text_res = _wrap(text=text_res, wrap_tag=IDocTagsToken.CAPTION.value)
+ return create_ser_result(text=text_res, span_source=results)
+
@override
def serialize_doc(
self,
@@ -492,28 +1657,597 @@ def serialize_doc(
parts: list[SerializationResult],
**kwargs: Any,
) -> SerializationResult:
- """DocTags-specific document serializer."""
+ """Doc-level serialization with IDocTags root wrapper."""
delim = _get_delim(params=self.params)
+
+ open_token: str = IDocTagsVocabulary.create_doctag_root()
+ close_token: str = IDocTagsVocabulary.create_doctag_root(closing=True)
+
text_res = delim.join([p.text for p in parts if p.text])
if self.params.add_page_break:
- page_sep = f"<{IDocTagsToken.PAGE_BREAK.value}{'/' if self.params.do_self_closing else ''}>"
+ # Always emit well‑formed page breaks using the vocabulary
+ page_sep = IDocTagsVocabulary.create_selfclosing_token(
+ token=IDocTagsToken.PAGE_BREAK
+ )
for full_match, _, _ in self._get_page_breaks(text=text_res):
text_res = text_res.replace(full_match, page_sep)
- tmp = f"<{IDocTagsToken.DOCUMENT.value}>"
- tmp += f"<{IDocTagsToken.VERSION.value}>{DOCTAGS_VERSION}"
- tmp += f"{text_res}"
- tmp += f""
-
- text_res = tmp
+ text_res = f"{open_token}{text_res}{close_token}"
if self.params.pretty_indentation and (
my_root := parseString(text_res).documentElement
):
+ # Pretty-print using minidom. This may collapse empty elements
+ # into self-closing tags. We optionally expand back non-self-closing
+ # tokens to preserve the IDocTags contract.
text_res = my_root.toprettyxml(indent=self.params.pretty_indentation)
text_res = "\n".join(
[line for line in text_res.split("\n") if line.strip()]
)
+ if self.params.preserve_empty_non_selfclosing:
+ # Expand self-closing forms for tokens that are not allowed
+ # to be self-closing according to the vocabulary.
+ # Example: ->
+ non_selfclosing = [
+ tok
+ for tok in IDocTagsToken
+ if not IDocTagsVocabulary.IS_SELFCLOSING.get(tok, False)
+ ]
+
+ def _expand_tag(text: str, name: str) -> str:
+ # Match or
+ pattern = rf"<\s*{name}(\s[^>]*)?/\s*>"
+ return re.sub(pattern, rf"<{name}\1>", text)
+
+ for tok in non_selfclosing:
+ text_res = _expand_tag(text_res, tok.value)
+
return create_ser_result(text=text_res, span_source=parts)
+
+ @override
+ def requires_page_break(self):
+ """Return whether page breaks should be emitted for the document."""
+ return self.params.add_page_break
+
+
+class IDocTagsDocDeserializer(BaseModel):
+ """IDocTags document deserializer."""
+
+ # Internal state used while walking the tree
+ _page_no: int = 0
+ _default_resolution: int = DOCTAGS_RESOLUTION
+
+ def deserialize(
+ self,
+ *,
+ doctags: str,
+ ) -> DoclingDocument:
+ """Deserialize DocTags XML into a DoclingDocument.
+
+ Args:
+ doctags: DocTags XML string to parse.
+
+ Returns:
+ A populated `DoclingDocument` parsed from the input.
+ """
+ root_node = parseString(doctags).documentElement
+ if root_node is None:
+ raise ValueError("Invalid DocTags XML: missing documentElement")
+ root: Element = cast(Element, root_node)
+ if root.tagName != IDocTagsToken.DOCUMENT.value:
+ candidates = root.getElementsByTagName(IDocTagsToken.DOCUMENT.value)
+ if candidates:
+ root = cast(Element, candidates[0])
+
+ doc = DoclingDocument(name="Document")
+ # Initialize with a default page so location tokens can be re‑emitted
+ self._page_no = 0
+ self._default_resolution = DOCTAGS_RESOLUTION
+ self._ensure_page_exists(
+ doc=doc, page_no=self._page_no, resolution=self._default_resolution
+ )
+ self._parse_document_root(doc=doc, root=root)
+ return doc
+
+ # ------------- Core walkers -------------
+ def _parse_document_root(self, *, doc: DoclingDocument, root) -> None:
+ for node in root.childNodes:
+ if getattr(node, "nodeType", None) == node.ELEMENT_NODE:
+ self._dispatch_element(doc=doc, el=node, parent=None)
+
+ def _dispatch_element(self, *, doc: DoclingDocument, el, parent) -> None:
+ name = el.tagName
+ if name in {
+ IDocTagsToken.TITLE.value,
+ IDocTagsToken.TEXT.value,
+ IDocTagsToken.CAPTION.value,
+ IDocTagsToken.FOOTNOTE.value,
+ IDocTagsToken.PAGE_HEADER.value,
+ IDocTagsToken.PAGE_FOOTER.value,
+ IDocTagsToken.CODE.value,
+ IDocTagsToken.FORMULA.value,
+ }:
+ self._parse_text_like(doc=doc, el=el, parent=parent)
+ elif name == IDocTagsToken.PAGE_BREAK.value:
+ # Start a new page; keep a default square page using the configured resolution
+ self._page_no += 1
+ self._ensure_page_exists(
+ doc=doc, page_no=self._page_no, resolution=self._default_resolution
+ )
+ elif name == IDocTagsToken.HEADING.value:
+ self._parse_heading(doc=doc, el=el, parent=parent)
+ elif name == IDocTagsToken.LIST.value:
+ self._parse_list(doc=doc, el=el, parent=parent)
+ elif name == IDocTagsToken.FLOATING_GROUP.value:
+ self._parse_floating_group(doc=doc, el=el, parent=parent)
+ else:
+ self._walk_children(doc=doc, el=el, parent=parent)
+
+ def _walk_children(self, *, doc: DoclingDocument, el, parent) -> None:
+ for node in el.childNodes:
+ if getattr(node, "nodeType", None) == node.ELEMENT_NODE:
+ # Ignore geometry/meta containers at this level; pass through page breaks
+ if node.tagName in {
+ IDocTagsToken.HEAD.value,
+ IDocTagsToken.META.value,
+ IDocTagsToken.LOCATION.value,
+ }:
+ continue
+ self._dispatch_element(doc=doc, el=node, parent=parent)
+
+ # ------------- Text blocks -------------
+ def _parse_text_like(self, *, doc: DoclingDocument, el, parent) -> None:
+ """Parse text-like tokens (title, text, caption, footnotes, code, formula)."""
+ prov_list = self._extract_provenance(doc=doc, el=el)
+ text = self._get_text(el).strip()
+ if not text:
+ return
+
+ nm = el.tagName
+
+ # Handle code separately (language + content extraction)
+ if nm == IDocTagsToken.CODE.value:
+ code_text, lang_label = self._extract_code_content_and_language(el)
+ if not code_text.strip():
+ return
+ item = doc.add_code(
+ text=code_text,
+ code_language=lang_label,
+ parent=parent,
+ prov=(prov_list[0] if prov_list else None),
+ )
+ for p in prov_list[1:]:
+ item.prov.append(p)
+ return
+
+ # Map text-like tokens to text item labels
+ text_label_map = {
+ IDocTagsToken.TEXT.value: DocItemLabel.TEXT,
+ IDocTagsToken.CAPTION.value: DocItemLabel.CAPTION,
+ IDocTagsToken.FOOTNOTE.value: DocItemLabel.FOOTNOTE,
+ IDocTagsToken.PAGE_HEADER.value: DocItemLabel.PAGE_HEADER,
+ IDocTagsToken.PAGE_FOOTER.value: DocItemLabel.PAGE_FOOTER,
+ }
+
+ if nm in text_label_map:
+ item = doc.add_text(
+ label=text_label_map[nm],
+ text=text,
+ parent=parent,
+ prov=(prov_list[0] if prov_list else None),
+ )
+ for p in prov_list[1:]:
+ item.prov.append(p)
+ return
+
+ if nm == IDocTagsToken.TITLE.value:
+ item = doc.add_title(
+ text=text,
+ parent=parent,
+ prov=(prov_list[0] if prov_list else None),
+ )
+ for p in prov_list[1:]:
+ item.prov.append(p)
+ return
+
+ if nm == IDocTagsToken.FORMULA.value:
+ item = doc.add_formula(
+ text=text,
+ parent=parent,
+ prov=(prov_list[0] if prov_list else None),
+ )
+ for p in prov_list[1:]:
+ item.prov.append(p)
+ return
+
+ def _extract_code_content_and_language(self, el) -> tuple[str, CodeLanguageLabel]:
+ """Extract code content and language from a element."""
+ lang_label = CodeLanguageLabel.UNKNOWN
+ parts: list[str] = []
+ for node in el.childNodes:
+ if getattr(node, "nodeType", None) == node.TEXT_NODE:
+ if node.data.strip():
+ parts.append(node.data)
+ elif getattr(node, "nodeType", None) == node.ELEMENT_NODE:
+ nm_child = node.tagName
+ if nm_child == IDocTagsToken.FACETS.value:
+ facets_text = self._get_text(node).strip()
+ if "=" in facets_text:
+ key, val = facets_text.split("=", 1)
+ if key.strip().lower() == "language":
+ val_norm = val.strip().lower()
+ try:
+ lang_label = next(
+ lbl
+ for lbl in CodeLanguageLabel
+ if lbl.value.lower() == val_norm
+ )
+ except StopIteration:
+ lang_label = CodeLanguageLabel.UNKNOWN
+ continue
+ if nm_child == IDocTagsToken.LOCATION.value:
+ continue
+ if nm_child == IDocTagsToken.BR.value:
+ parts.append("\n")
+ else:
+ parts.append(self._get_text(node))
+
+ return "".join(parts), lang_label
+
+ def _parse_heading(self, *, doc: DoclingDocument, el, parent) -> None:
+ lvl_txt = el.getAttribute(IDocTagsAttributeKey.LEVEL.value) or "1"
+ try:
+ level = int(lvl_txt)
+ except Exception:
+ level = 1
+ # Extract provenance from heading token (if any)
+ prov_list = self._extract_provenance(doc=doc, el=el)
+ text = self._get_text(el)
+ text_stripped = text.strip()
+ if text_stripped:
+ item = doc.add_heading(
+ text=text_stripped,
+ level=level,
+ parent=parent,
+ prov=(prov_list[0] if prov_list else None),
+ )
+ for p in prov_list[1:]:
+ item.prov.append(p)
+
+ def _parse_list(self, *, doc: DoclingDocument, el, parent) -> None:
+ ordered = (
+ el.getAttribute(IDocTagsAttributeKey.ORDERED.value)
+ == IDocTagsAttributeValue.TRUE.value
+ )
+ group = doc.add_list_group(parent=parent)
+ for node in el.childNodes:
+ if getattr(node, "nodeType", None) != node.ELEMENT_NODE:
+ continue
+ if node.tagName == IDocTagsToken.LIST_TEXT.value:
+ # Collect provenance from the wrapper
+ prov_list = self._extract_provenance(doc=doc, el=node)
+ text = self._get_text(node).strip()
+ if text:
+ item = doc.add_list_item(
+ text=text,
+ parent=group,
+ enumerated=ordered,
+ prov=(prov_list[0] if prov_list else None),
+ )
+ for p in prov_list[1:]:
+ item.prov.append(p)
+
+ # ------------- Floating groups -------------
+ def _parse_floating_group(self, *, doc: DoclingDocument, el, parent) -> None:
+ cls_val = el.getAttribute(IDocTagsAttributeKey.CLASS.value)
+ if cls_val == IDocTagsAttributeValue.TABLE.value:
+ self._parse_table_group(doc=doc, el=el, parent=parent)
+ elif cls_val == IDocTagsAttributeValue.PICTURE.value:
+ self._parse_picture_group(doc=doc, el=el, parent=parent)
+ else:
+ self._walk_children(doc=doc, el=el, parent=parent)
+
+ def _parse_table_group(self, *, doc: DoclingDocument, el, parent) -> None:
+ caption = self._extract_caption(doc=doc, el=el)
+ otsl_el = self._first_child(el, IDocTagsToken.OTSL.value)
+ if otsl_el is None:
+ doc.add_table(data=TableData(), caption=caption, parent=parent)
+ return
+ # Extract table provenance from leading tokens
+ tbl_provs = self._extract_provenance(doc=doc, el=otsl_el)
+ inner = self._inner_xml(otsl_el)
+ # Remove any location tokens from the OTSL content before parsing
+ inner = re.sub(r"<\s*location\b[^>]*/\s*>", "", inner)
+ td = self._parse_otsl_table_content(f"{inner}")
+ tbl = doc.add_table(
+ data=td,
+ caption=caption,
+ parent=parent,
+ prov=(tbl_provs[0] if tbl_provs else None),
+ )
+ for p in tbl_provs[1:]:
+ tbl.prov.append(p)
+
+ def _parse_picture_group(self, *, doc: DoclingDocument, el, parent) -> None:
+ # Extract caption from the floating group
+ caption = self._extract_caption(doc=doc, el=el)
+
+ # Extract provenance from the block (locations appear inside it)
+ prov_list: list[ProvenanceItem] = []
+ picture_el = self._first_child(el, IDocTagsToken.PICTURE.value)
+ if picture_el is not None:
+ prov_list = self._extract_provenance(doc=doc, el=picture_el)
+
+ # Create the picture item first, attach caption and provenance
+ pic = doc.add_picture(
+ caption=caption,
+ parent=parent,
+ prov=(prov_list[0] if prov_list else None),
+ )
+ for p in prov_list[1:]:
+ pic.prov.append(p)
+
+ # If there is a child and it contains an ,
+ # parse it as TabularChartMetaField and attach to picture.meta
+ if picture_el is not None:
+ otsl_el = self._first_child(picture_el, IDocTagsToken.OTSL.value)
+ if otsl_el is not None:
+ inner = self._inner_xml(otsl_el)
+ td = self._parse_otsl_table_content(f"{inner}")
+ if pic.meta is None:
+ pic.meta = PictureMeta()
+ pic.meta.tabular_chart = TabularChartMetaField(chart_data=td)
+
+ # ------------- Helpers -------------
+ def _extract_caption(self, *, doc: DoclingDocument, el) -> Optional[TextItem]:
+ cap_el = self._first_child(el, IDocTagsToken.CAPTION.value)
+ if cap_el is None:
+ return None
+ text = self._get_text(cap_el).strip()
+ if not text:
+ return None
+ prov_list = self._extract_provenance(doc=doc, el=cap_el)
+ item = doc.add_text(
+ label=DocItemLabel.CAPTION,
+ text=text,
+ prov=(prov_list[0] if prov_list else None),
+ )
+ for p in prov_list[1:]:
+ item.prov.append(p)
+ return item
+
+ def _first_child(self, el, tag_name: str):
+ for node in el.childNodes:
+ if (
+ getattr(node, "nodeType", None) == node.ELEMENT_NODE
+ and node.tagName == tag_name
+ ):
+ return node
+ return None
+
+ def _inner_xml(self, el) -> str:
+ parts: list[str] = []
+ for node in el.childNodes:
+ if getattr(node, "nodeType", None) == node.TEXT_NODE:
+ parts.append(node.data)
+ elif node.nodeType == node.ELEMENT_NODE:
+ parts.append(node.toxml())
+ return "".join(parts)
+
+ # --------- OTSL table parsing (inlined) ---------
+ def _otsl_extract_tokens_and_text(self, s: str) -> tuple[list[str], list[str]]:
+ """Extract OTSL structural tokens and interleaved text.
+
+ Strips the outer wrapper and ignores location tokens (expected
+ to be removed before).
+ """
+ pattern = r"(<[^>]+>)"
+ tokens = re.findall(pattern, s)
+ # Drop the wrapper tags
+ tokens = [
+ t
+ for t in tokens
+ if t
+ not in [
+ f"<{IDocTagsToken.OTSL.value}>",
+ f"",
+ ]
+ ]
+
+ parts = re.split(pattern, s)
+ parts = [
+ p
+ for p in parts
+ if p.strip()
+ and p
+ not in [
+ f"<{IDocTagsToken.OTSL.value}>",
+ f"",
+ ]
+ ]
+ return tokens, parts
+
+ def _otsl_parse_texts(
+ self, texts: list[str], tokens: list[str]
+ ) -> tuple[list[TableCell], list[list[str]]]:
+ """Parse OTSL interleaved texts+tokens into TableCell list and row tokens."""
+ # Token strings used in the stream (normalized to )
+
+ fcel = IDocTagsVocabulary.create_selfclosing_token(token=IDocTagsToken.FCEL)
+ ecel = IDocTagsVocabulary.create_selfclosing_token(token=IDocTagsToken.ECEL)
+ lcel = IDocTagsVocabulary.create_selfclosing_token(token=IDocTagsToken.LCEL)
+ ucel = IDocTagsVocabulary.create_selfclosing_token(token=IDocTagsToken.UCEL)
+ xcel = IDocTagsVocabulary.create_selfclosing_token(token=IDocTagsToken.XCEL)
+ nl = IDocTagsVocabulary.create_selfclosing_token(token=IDocTagsToken.NL)
+ ched = IDocTagsVocabulary.create_selfclosing_token(token=IDocTagsToken.CHED)
+ rhed = IDocTagsVocabulary.create_selfclosing_token(token=IDocTagsToken.RHED)
+ srow = IDocTagsVocabulary.create_selfclosing_token(token=IDocTagsToken.SROW)
+
+ # Clean tokens to only structural OTSL markers
+ clean_tokens: list[str] = []
+ for t in tokens:
+ if t in [ecel, fcel, lcel, ucel, xcel, nl, ched, rhed, srow]:
+ clean_tokens.append(t)
+ tokens = clean_tokens
+
+ # Split into rows by NL markers while keeping segments
+ split_row_tokens = [
+ list(group)
+ for is_sep, group in groupby(tokens, key=lambda z: z == nl)
+ if not is_sep
+ ]
+
+ table_cells: list[TableCell] = []
+ r_idx = 0
+ c_idx = 0
+
+ def count_right(rows: list[list[str]], c: int, r: int, which: list[str]) -> int:
+ span = 0
+ j = c
+ while j < len(rows[r]) and rows[r][j] in which:
+ j += 1
+ span += 1
+ return span
+
+ def count_down(rows: list[list[str]], c: int, r: int, which: list[str]) -> int:
+ span = 0
+ i = r
+ while i < len(rows) and c < len(rows[i]) and rows[i][c] in which:
+ i += 1
+ span += 1
+ return span
+
+ for i, t in enumerate(texts):
+ cell_text = ""
+ if t in [fcel, ecel, ched, rhed, srow]:
+ row_span = 1
+ col_span = 1
+ right_offset = 1
+ if t != ecel and (i + 1) < len(texts):
+ cell_text = texts[i + 1]
+ right_offset = 2
+
+ next_right = (
+ texts[i + right_offset] if i + right_offset < len(texts) else ""
+ )
+ next_bottom = (
+ split_row_tokens[r_idx + 1][c_idx]
+ if (r_idx + 1) < len(split_row_tokens)
+ and c_idx < len(split_row_tokens[r_idx + 1])
+ else ""
+ )
+
+ if next_right in [lcel, xcel]:
+ col_span += count_right(
+ split_row_tokens, c_idx + 1, r_idx, [lcel, xcel]
+ )
+ if next_bottom in [ucel, xcel]:
+ row_span += count_down(
+ split_row_tokens, c_idx, r_idx + 1, [ucel, xcel]
+ )
+
+ table_cells.append(
+ TableCell(
+ text=cell_text.strip(),
+ row_span=row_span,
+ col_span=col_span,
+ start_row_offset_idx=r_idx,
+ end_row_offset_idx=r_idx + row_span,
+ start_col_offset_idx=c_idx,
+ end_col_offset_idx=c_idx + col_span,
+ )
+ )
+
+ if t in [fcel, ecel, ched, rhed, srow, lcel, ucel, xcel]:
+ c_idx += 1
+ if t == nl:
+ r_idx += 1
+ c_idx = 0
+
+ return table_cells, split_row_tokens
+
+ def _parse_otsl_table_content(self, otsl_content: str) -> TableData:
+ """Parse OTSL content into TableData (inlined from utils)."""
+ tokens, mixed = self._otsl_extract_tokens_and_text(otsl_content)
+ table_cells, split_rows = self._otsl_parse_texts(mixed, tokens)
+ return TableData(
+ num_rows=len(split_rows),
+ num_cols=(max(len(r) for r in split_rows) if split_rows else 0),
+ table_cells=table_cells,
+ )
+
+ def _get_text(self, el) -> str:
+ out: list[str] = []
+ for node in el.childNodes:
+ if getattr(node, "nodeType", None) == node.TEXT_NODE:
+ # Skip pure indentation/pretty-print whitespace
+ if node.data.strip():
+ out.append(node.data)
+ elif node.nodeType == node.ELEMENT_NODE:
+ nm = node.tagName
+ if nm in {IDocTagsToken.LOCATION.value}:
+ continue
+ if nm == IDocTagsToken.BR.value:
+ out.append("\n")
+ else:
+ out.append(self._get_text(node))
+ return "".join(out)
+
+ # --------- Location helpers ---------
+ def _ensure_page_exists(
+ self, *, doc: DoclingDocument, page_no: int, resolution: int
+ ) -> None:
+ # If the page already exists, do nothing; otherwise add with a square size based on resolution
+ if page_no not in doc.pages:
+ doc.add_page(
+ page_no=page_no, size=Size(width=resolution, height=resolution)
+ )
+
+ def _extract_provenance(self, *, doc: DoclingDocument, el) -> list[ProvenanceItem]:
+ # Collect immediate child tokens in groups of 4
+ values: list[int] = []
+ res_for_group: Optional[int] = None
+ provs: list[ProvenanceItem] = []
+
+ for node in el.childNodes:
+ if getattr(node, "nodeType", None) != node.ELEMENT_NODE:
+ continue
+ if node.tagName != IDocTagsToken.LOCATION.value:
+ continue
+ try:
+ v = int(node.getAttribute(IDocTagsAttributeKey.VALUE.value) or "0")
+ except Exception:
+ v = 0
+ try:
+ r = int(
+ node.getAttribute(IDocTagsAttributeKey.RESOLUTION.value)
+ or str(self._default_resolution)
+ )
+ except Exception:
+ r = self._default_resolution
+ values.append(v)
+ # For a group, remember the last seen resolution
+ res_for_group = r
+ if len(values) == 4:
+ # Ensure page exists (and set consistent default size for this page)
+ self._ensure_page_exists(
+ doc=doc,
+ page_no=self._page_no,
+ resolution=res_for_group or self._default_resolution,
+ )
+ l = float(min(values[0], values[2]))
+ t = float(min(values[1], values[3]))
+ rgt = float(max(values[0], values[2]))
+ btm = float(max(values[1], values[3]))
+ bbox = BoundingBox.from_tuple(
+ (l, t, rgt, btm), origin=CoordOrigin.TOPLEFT
+ )
+ provs.append(
+ ProvenanceItem(page_no=self._page_no, bbox=bbox, charspan=(0, 0))
+ )
+ values = []
+ res_for_group = None
+
+ return provs
diff --git a/examples/convert_to_idoctags.py b/examples/convert_to_idoctags.py
new file mode 100644
index 00000000..64749223
--- /dev/null
+++ b/examples/convert_to_idoctags.py
@@ -0,0 +1,430 @@
+import os
+import json
+import glob
+import argparse
+from pathlib import Path
+from typing import Sequence, Dict, Any, Optional
+from collections import Counter
+from io import BytesIO
+
+from PIL import Image as PILImage
+
+from datasets import load_dataset
+from tqdm import tqdm
+from transformers import (
+ AutoTokenizer,
+ PreTrainedTokenizerBase,
+)
+from docling_core.types.doc import DoclingDocument, ImageRef
+from docling_core.types.doc.base import ImageRefMode
+from docling_core.experimental.idoctags import (
+ IDocTagsSerializationMode,
+ IDocTagsParams,
+ IDocTagsVocabulary,
+ IDocTagsDocSerializer,
+)
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+# In order to download **before** the datasets library, run
+#
+# HF_HUB_DISABLE_XET=1 hf download --repo-type dataset "docling-project/canva-set-a"
+#
+
+def update_tokenizer(tokenizer: PreTrainedTokenizerBase, verbose: bool = False) -> PreTrainedTokenizerBase:
+ """Extend tokenizer with IDocTags special tokens.
+
+ Parameters
+ - tokenizer: base tokenizer to extend
+ - verbose: print added tokens if True
+ """
+ special_tokens = IDocTagsVocabulary.get_special_tokens()
+ if verbose:
+ for i, tok in enumerate(special_tokens):
+ print(i, "\t", tok)
+ tokenizer.add_tokens(special_tokens)
+ if verbose:
+ print(f"New vocab size: {tokenizer.vocab_size}")
+ return tokenizer
+
+def run_dump(cfg: Dict[str, Any]) -> int:
+ """Dump/serialize documents from a dataset to IDocTags strings/files.
+
+ Config keys (with defaults):
+ - dataset_name: str ("docling-project/doclaynet-set-a")
+ - dataset_subset: str ("pdf_train")
+ - dataset_split: str ("train")
+ - output_dir: str ("./scratch/idoctags")
+ - failed_dir: str ("./scratch/idoctags_failed") — where to dump HTML+JSON when serialization fails
+ - write_outputs: bool (True) — write serialized outputs if True
+ - variants: list of serialization variants; each item:
+ {"add_content": bool, "mode": "LLM_FRIENDLY"|"HUMAN_FRIENDLY", "suffix": str}
+ Defaults to three variants mirroring prior behavior.
+ """
+ dataset_name = cfg.get("dataset_name", "docling-project/doclaynet-set-a")
+ dataset_subset = cfg.get("dataset_subset", "train")
+ dataset_split = cfg.get("dataset_split", "train")
+ output_dir = Path(cfg.get("output_dir", "./scratch/idoctags"))
+ failed_dir = Path(cfg.get("failed_dir", "./scratch/idoctags_failed"))
+ pngs_dir = Path(cfg.get("pngs_dir", "./scratch/pngs_dir"))
+ write_outputs: bool = bool(cfg.get("write_outputs", True))
+
+ default_variants = [
+ {"add_content": False, "mode": "LLM_FRIENDLY", "suffix": "_without"},
+ {"add_content": True, "mode": "LLM_FRIENDLY", "suffix": "_with"},
+ {"add_content": True, "mode": "HUMAN_FRIENDLY", "suffix": "_with_h"},
+ ]
+ variants = cfg.get("variants", default_variants)
+
+ if write_outputs:
+ output_dir.mkdir(parents=True, exist_ok=True)
+ # Create failed dir proactively; also created again on demand in the exception path
+ failed_dir.mkdir(parents=True, exist_ok=True)
+
+ ds = load_dataset(dataset_name, dataset_subset)
+ split = ds[dataset_split]
+ total = len(split)
+
+ errors: list[str] = []
+ ok = 0
+
+ for idx, row in tqdm(enumerate(split), total=total, ncols=128):
+ text = row.get("GroundTruthDocument", "")
+ try:
+ doc = DoclingDocument.model_validate_json(text)
+ page_images = [
+ __ for __ in row["GroundTruthPageImages"]
+ ]
+ # page_images[0].show()
+
+ except Exception as exc:
+ errors.append(
+ f"Parse error: {exc} for {dataset_name}/{dataset_subset}/{dataset_split} idx={idx}"
+ )
+ continue
+
+ for i, __ in enumerate(page_images, start=1):
+ doc.pages[i].image = ImageRef.from_pil(__, dpi=140)
+ # png_path = pngs_dir / f"{idx}_{i}.png"
+ # __.save(png_path)
+
+ try:
+ for var in variants:
+ params = IDocTagsParams()
+ params.add_content = bool(var.get("add_content", True))
+ mode_str = str(var.get("mode", "LLM_FRIENDLY"))
+ params.mode = (
+ IDocTagsSerializationMode.LLM_FRIENDLY
+ if mode_str == "LLM_FRIENDLY"
+ else IDocTagsSerializationMode.HUMAN_FRIENDLY
+ )
+
+ iser = IDocTagsDocSerializer(doc=doc, params=params)
+ serialized = iser.serialize().text
+
+ if write_outputs:
+ suffix = var.get("suffix", "")
+ out_path = output_dir / f"{idx}{suffix}.idoctags"
+ with open(out_path, "w", encoding="utf-8") as fw:
+ fw.write(serialized)
+ ok += 1
+ except Exception as exc:
+ print(f"exc: {exc}")
+ # page_images[0].show()
+
+ failed_dir.mkdir(parents=True, exist_ok=True)
+ # JSON dump of the parsed DoclingDocument
+ json_path = failed_dir / f"{idx}.json"
+ print(f"\n\n -> writing {json_path}")
+ with open(json_path, "w", encoding="utf-8") as fj:
+ fj.write(doc.model_dump_json(indent=2))
+
+ try:
+ # Split-page HTML with layout/images; avoid single-column variant
+ html_path = failed_dir / f"{idx}_split.html"
+ print(f"\n\n -> writing {html_path}")
+ doc.save_as_html(
+ filename=html_path,
+ image_mode=ImageRefMode.EMBEDDED,
+ split_page_view=True,
+ include_annotations=True,
+ )
+ except Exception as exc2:
+ print(f"exception: {exc2}")
+
+ print(f"Serialized OK: {ok} / {total}")
+ if errors:
+ print("Errors:")
+ for e in errors:
+ print(" -", e)
+ return 0 if ok > 0 and not errors else (0 if ok == total else 1)
+
+
+def run_analyse(cfg: Dict[str, Any]) -> int:
+ """Analyse token lengths and special-token usage from IDocTags files.
+
+ Config keys (with defaults):
+ - tokenizer_name: str ("ibm-granite/granite-docling-258M")
+ - input_glob: str ("./scratch/idoctags/*_with_h.idoctags")
+ - pair_replace: dict with {"from": "_h", "to": ""} to locate paired files (optional)
+ - show_plots: bool (True)
+ - verbose: bool (False)
+ """
+ tokenizer_name = cfg.get("tokenizer_name", "ibm-granite/granite-docling-258M")
+ input_glob_pat = cfg.get("input_glob", "./scratch/idoctags/*_with_h.idoctags")
+ pair_replace = cfg.get("pair_replace", {"from": "_h", "to": ""})
+ show_plots = bool(cfg.get("show_plots", True))
+ verbose = bool(cfg.get("verbose", False))
+
+ base_tokenizer: PreTrainedTokenizerBase = AutoTokenizer.from_pretrained(tokenizer_name)
+ ext_tokenizer: PreTrainedTokenizerBase = AutoTokenizer.from_pretrained(tokenizer_name)
+ ext_tokenizer = update_tokenizer(tokenizer=ext_tokenizer, verbose=verbose)
+
+ filenames = sorted(glob.glob(input_glob_pat))
+ if not filenames:
+ print(f"No files matched pattern: {input_glob_pat}")
+ return 1
+
+ base_lengths: list[int] = []
+ ext_lengths: list[int] = []
+ special_counts: Counter[int] = Counter()
+
+ # Map special tokens to IDs in the extended tokenizer
+ special_tokens = IDocTagsVocabulary.get_special_tokens()
+ special_token_ids = {ext_tokenizer.convert_tokens_to_ids(tok) for tok in special_tokens}
+
+ for filename in tqdm(filenames, desc="Analyse", ncols=128):
+ with open(filename, "r", encoding="utf-8") as fr:
+ text_h = fr.read()
+
+ paired_name: Optional[str] = None
+ if isinstance(pair_replace, dict) and pair_replace.get("from") is not None:
+ paired_name = filename.replace(str(pair_replace.get("from")), str(pair_replace.get("to", "")))
+
+ text_plain = None
+ if paired_name and os.path.exists(paired_name):
+ with open(paired_name, "r", encoding="utf-8") as fr:
+ text_plain = fr.read()
+
+ # Tokenize and collect lengths
+ base_tokens_h = base_tokenizer.encode(text_h, add_special_tokens=True)
+ ext_tokens_h = ext_tokenizer.encode(text_h, add_special_tokens=True)
+ base_lengths.append(len(base_tokens_h))
+ ext_lengths.append(len(ext_tokens_h))
+
+ # Special token usage on the extended-tokenized sequence of the HF/H text
+ for tid in ext_tokens_h:
+ if tid in special_token_ids:
+ special_counts[tid] += 1
+
+ # Optionally also include the paired non-human-friendly text lengths
+ if text_plain is not None:
+ _ = base_tokenizer.encode(text_plain, add_special_tokens=True)
+ _e = ext_tokenizer.encode(text_plain, add_special_tokens=True)
+ base_lengths.append(len(_))
+ ext_lengths.append(len(_e))
+ for tid in _e:
+ if tid in special_token_ids:
+ special_counts[tid] += 1
+
+ # Report summary
+ print(f"Files analysed: {len(filenames)}")
+ print(f"Sequences tokenized (including pairs when available): {len(ext_lengths)}")
+ if ext_lengths:
+ arr = np.asarray(ext_lengths)
+ print(
+ f"Extended tokenizer lengths — min: {arr.min()}, p50: {np.median(arr)}, p95: {np.percentile(arr,95)}, max: {arr.max()}, mean: {arr.mean():.1f}"
+ )
+
+ # Map special IDs back to tokens and show top-k
+ if special_counts:
+ id_to_token = {i: ext_tokenizer.convert_ids_to_tokens([i])[0] for i in special_counts.keys()}
+ total_special = sum(special_counts.values())
+ print("Special token usage (top 30):")
+ for tid, cnt in special_counts.most_common(30):
+ tok = id_to_token.get(tid, str(tid))
+ pct = 100.0 * cnt / total_special if total_special else 0.0
+ print(f" - {tok}: {cnt} ({pct:.2f}%)")
+
+ if show_plots:
+ # Bar chart of top-N special tokens
+ items = special_counts.most_common(30)
+ labels = [id_to_token.get(tid, str(tid)) for tid, _ in items]
+ values = [v for _, v in items]
+ plt.figure(figsize=(12, 5))
+ plt.bar(labels, values, color="#4C78A8")
+ plt.xticks(rotation=90)
+ plt.title("Top Special Tokens (by frequency)")
+ plt.tight_layout()
+ plt.show()
+
+ # Visualizations for lengths
+ if show_plots and base_lengths and ext_lengths:
+ plot_token_histograms(base_lengths, ext_lengths)
+ plot_token_scatter_with_regression(base_lengths, ext_lengths)
+
+ return 0
+
+
+def plot_token_histograms(
+ original_num_tokens: Sequence[int] | np.ndarray,
+ optimal_num_tokens: Sequence[int] | np.ndarray,
+ *,
+ bins: int = 50,
+ density: bool = False,
+) -> None:
+ """Plot overlapping histograms for original and optimal token counts.
+
+ Parameters
+ - original_num_tokens: sequence of counts before optimization
+ - optimal_num_tokens: sequence of counts after optimization
+ - bins: number of histogram bins
+ - density: normalize histograms if True
+ """
+ x = np.asarray(original_num_tokens)
+ y = np.asarray(optimal_num_tokens)
+
+ plt.figure(figsize=(10, 6))
+ plt.hist(
+ x,
+ bins=bins,
+ alpha=0.5,
+ label="Original",
+ color="#4C78A8",
+ edgecolor="black",
+ density=density,
+ )
+ plt.hist(
+ y,
+ bins=bins,
+ alpha=0.5,
+ label="Optimal",
+ color="#F58518",
+ edgecolor="black",
+ density=density,
+ )
+ plt.xlabel("Number of tokens")
+ plt.ylabel("Density" if density else "Frequency")
+ plt.title("Token Count Distributions")
+ plt.legend()
+ plt.grid(axis="y", alpha=0.3)
+ plt.tight_layout()
+ plt.show()
+
+
+def plot_token_scatter_with_regression(
+ original_num_tokens: Sequence[int] | np.ndarray,
+ optimal_num_tokens: Sequence[int] | np.ndarray,
+) -> None:
+ """Scatter plot of original vs optimal tokens with a linear regression line.
+
+ Parameters
+ - original_num_tokens: x-values
+ - optimal_num_tokens: y-values
+ """
+ x = np.asarray(original_num_tokens, dtype=float)
+ y = np.asarray(optimal_num_tokens, dtype=float)
+
+ if x.size == 0 or y.size == 0:
+ print("No data to plot.")
+ return
+
+ # Linear regression with numpy polyfit (degree 1)
+ slope, intercept = np.polyfit(x, y, 1)
+ y_pred = slope * x + intercept
+ # Compute R^2
+ ss_res = np.sum((y - y_pred) ** 2)
+ ss_tot = np.sum((y - np.mean(y)) ** 2)
+ r2 = 1 - ss_res / ss_tot if ss_tot > 0 else float("nan")
+
+ # Prepare line for full x-range
+ x_line = np.linspace(x.min(), x.max(), 100)
+ y_line = slope * x_line + intercept
+
+ plt.figure(figsize=(8, 8))
+ plt.scatter(x, y, alpha=0.6, color="#4C78A8", label="Documents")
+ plt.plot(x_line, y_line, color="#E45756", linewidth=2,
+ label=f"y = {slope:.3f}x + {intercept:.3f} (R²={r2:.3f})")
+ plt.xlabel("Original tokens")
+ plt.ylabel("Optimal tokens")
+ plt.title("Original vs Optimal Tokens with Linear Fit")
+ plt.grid(alpha=0.3)
+ plt.legend()
+ plt.tight_layout()
+ plt.show()
+
+def default_config(mode: str) -> Dict[str, Any]:
+ if mode == "dump":
+ return {
+ "dataset_name": "docling-project/doclaynet-set-a",
+ "dataset_subset": "pdf_train",
+ "dataset_split": "train",
+ "output_dir": "./scratch/idoctags",
+ "failed_dir": "./scratch/idoctags_failed",
+ "write_outputs": True,
+ "variants": [
+ {"add_content": False, "mode": "LLM_FRIENDLY", "suffix": "_without"},
+ {"add_content": True, "mode": "LLM_FRIENDLY", "suffix": "_with"},
+ {"add_content": True, "mode": "HUMAN_FRIENDLY", "suffix": "_with_h"},
+ ],
+ }
+ elif mode == "analyse":
+ return {
+ "tokenizer_name": "ibm-granite/granite-docling-258M",
+ "input_glob": "./scratch/idoctags/*_with_h.idoctags",
+ "pair_replace": {"from": "_h", "to": ""},
+ "show_plots": True,
+ "verbose": False,
+ }
+ else:
+ raise ValueError(f"Unknown mode for default config: {mode}")
+
+
+def main(argv: Optional[Sequence[str]] = None) -> int:
+ parser = argparse.ArgumentParser(description="Convert and analyse IDocTags data")
+ parser.add_argument(
+ "--mode",
+ choices=["dump", "analyse"],
+ required=True,
+ help="Mode: dump dataset to idoctags or analyse token stats",
+ )
+ parser.add_argument(
+ "--config",
+ type=Path,
+ default=None,
+ help="Path to JSON config. If omitted, a default config is created for the chosen mode.",
+ )
+ parser.add_argument(
+ "--write-default-config",
+ action="store_true",
+ help="Only write the default config for the selected mode and exit.",
+ )
+ args = parser.parse_args(list(argv) if argv is not None else None)
+
+ cfg_path: Optional[Path] = args.config
+ cfg: Dict[str, Any]
+
+ if cfg_path is None:
+ cfg = default_config(args.mode)
+ out_name = Path(f"idoctags_{args.mode}_config.json")
+ with open(out_name, "w", encoding="utf-8") as fw:
+ json.dump(cfg, fw, indent=2)
+ print(f"Wrote default config to: {out_name.resolve()}")
+ if args.write_default_config:
+ return 0
+ # proceed using the freshly created config in-memory
+ else:
+ with open(cfg_path, "r", encoding="utf-8") as fr:
+ cfg = json.load(fr)
+
+ if args.mode == "dump":
+ return run_dump(cfg)
+ elif args.mode == "analyse":
+ return run_analyse(cfg)
+ else:
+ raise AssertionError("unreachable")
+
+
+if __name__ == "__main__":
+ raise SystemExit(main())
diff --git a/pyproject.toml b/pyproject.toml
index 7c78cd18..caab0684 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -91,7 +91,10 @@ chunking-openai = [
# specific:
'tiktoken (>=0.9.0,<0.13.0)',
]
-
+examples = [
+ "datasets>=4.0.0",
+ "matplotlib>=3.7.0",
+]
[dependency-groups]
dev = [
"pre-commit~=3.7",
diff --git a/test/data/doc/ddoc_0.v0.gt.idt b/test/data/doc/ddoc_0.v0.gt.idt
new file mode 100644
index 00000000..ba2dc6d6
--- /dev/null
+++ b/test/data/doc/ddoc_0.v0.gt.idt
@@ -0,0 +1,250 @@
+
+
+
+
+
+
+ ndbinfo_select_all - Select From ndbinfo Tables
+
+
+
+
+
+
+
+
+ Default Value
+
+ 1
+
+
+ Minimum Value
+
+ 0
+
+
+ Maximum Value
+
+ MAX_INT
+
+
+
+
+
+
+
+
+ This option sets the number of times to execute the select. Use --delay to set the time between loops.
+
+
+
+
+
+
+
+ • --ndb-connectstring
+
+
+
+
+
+
+
+
+
+ Command-Line Format
+
+ --ndb-connectstring=connection-string
+
+
+ Type
+
+ String
+
+
+ Default Value
+
+ [none]
+
+
+
+
+
+
+
+
+ Set connect string for connecting to ndb_mgmd. Syntax: "[nodeid=id;][host=]hostname[:port]". Overrides entries in NDB_CONNECTSTRING and my.cnf.
+
+
+
+
+
+
+
+ • --ndb-mgmd-host
+
+
+
+
+
+
+
+
+
+ Command-Line Format
+
+ --ndb-mgmd-host=connection-string
+
+
+ Type
+
+ String
+
+
+ Default Value
+
+ [none]
+
+
+
+
+
+
+
+
+ Same as --ndb-connectstring .
+
+
+
+
+
+
+
+ • --ndb-nodeid
+
+
+
+
+
+
+
+
+
+ Command-Line Format
+
+ --ndb-nodeid=#
+
+
+ Type
+
+ Integer
+
+
+ Default Value
+
+ [none]
+
+
+
+
+
+
+
+
+ Set node ID for this node, overriding any ID set by --ndb-connectstring.
+
+
+
+
+
+
+
+ • --ndb-optimized-node-selection
+
+
+
+
+
+
+
+
+
+ Command-Line Format
+
+ --ndb-optimized-node-selection
+
+
+
+
+
+
+
+
+ Enable optimizations for selection of nodes for transactions. Enabled by default; use --skip-ndb- optimized-node-selection to disable.
+
+
+
+
+
+
+
+ • --no-defaults
+
+
+
+
+
+
+
+
+
+ Command-Line Format
+
+ --no-defaults
+
+
+
+
+
+
+
+
+ Do not read default options from any option file other than login file.
+
+
+
+
+
+
+
+ • --print-defaults
+
+
+
+
+
+
+
+
+
+ Command-Line Format
+
+ --print-defaults
+
+
+
+
+
+
+
+
+ Print program argument list and exit.
+
+
+
+
+
+
+ 4253
+
+
diff --git a/test/data/doc/ddoc_0.v1.gt.idt b/test/data/doc/ddoc_0.v1.gt.idt
new file mode 100644
index 00000000..e7832056
--- /dev/null
+++ b/test/data/doc/ddoc_0.v1.gt.idt
@@ -0,0 +1,205 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/test/data/doc/ddoc_0.v2.gt.idt b/test/data/doc/ddoc_0.v2.gt.idt
new file mode 100644
index 00000000..753602fa
--- /dev/null
+++ b/test/data/doc/ddoc_0.v2.gt.idt
@@ -0,0 +1 @@
+
diff --git a/test/data/doc/dummy_doc_with_meta.gt.idt.xml b/test/data/doc/dummy_doc_with_meta.gt.idt.xml
index 2d6b544b..d40943b9 100644
--- a/test/data/doc/dummy_doc_with_meta.gt.idt.xml
+++ b/test/data/doc/dummy_doc_with_meta.gt.idt.xml
@@ -1,39 +1,42 @@
-
- 1.0.0
+
<meta>
<summary>This is a title.</summary>
<my_corp__foo>More stuff here.</my_corp__foo>
</meta>
- <loc_42/>
- <loc_26/>
- <loc_406/>
- <loc_46/>
+ <location value="43" resolution="512"/>
+ <location value="26" resolution="512"/>
+ <location value="415" resolution="512"/>
+ <location value="47" resolution="512"/>
DocLayNet: A Large Human-Annotated Dataset for Document-Layout Analysis
-
-
- ...
- Bar chart
- CC1=NNC(C2=CN3C=CN=C3C(CC3=CC(F)=CC(F)=C3)=N2)=N1
- {'myanalysis': {'prediction': 'abc'}, 'something_else': {'text': 'aaa'}}
-
-
-
-
-
+
-
-
-
-
+
+
+
+
Figure 1: Four examples of complex page layouts across different document categories
-
-
-
-
-
-
-
+
+
+ ...
+ Bar chart
+ CC1=NNC(C2=CN3C=CN=C3C(CC3=CC(F)=CC(F)=C3)=N2)=N1
+ {'myanalysis': {'prediction': 'abc'}, 'something_else': {'text': 'aaa'}}
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/test/test_deserializer_idoctags.py b/test/test_deserializer_idoctags.py
new file mode 100644
index 00000000..6f014781
--- /dev/null
+++ b/test/test_deserializer_idoctags.py
@@ -0,0 +1,537 @@
+from docling_core.experimental.idoctags import (
+ IDocTagsDocDeserializer,
+ IDocTagsDocSerializer,
+ IDocTagsParams,
+)
+from docling_core.types.doc import (
+ BoundingBox,
+ DocItemLabel,
+ DoclingDocument,
+ ProvenanceItem,
+ Size,
+ TableCell,
+ TableData,
+)
+from docling_core.types.doc.labels import CodeLanguageLabel
+
+DO_PRINT: bool = False
+
+
+def _serialize(
+ doc: DoclingDocument,
+ add_location: bool = True,
+ add_content: bool = True,
+ add_table_cell_location: bool = False,
+ add_table_cell_text: bool = True,
+) -> str:
+ ser = IDocTagsDocSerializer(
+ doc=doc,
+ params=IDocTagsParams(
+ add_location=add_location,
+ add_content=add_content,
+ add_table_cell_location=add_table_cell_location,
+ add_table_cell_text=add_table_cell_text,
+ ),
+ )
+ return ser.serialize().text
+
+
+def _deserialize(text: str) -> DoclingDocument:
+ return IDocTagsDocDeserializer().deserialize(doctags=text)
+
+
+def _add_default_page(doc: DoclingDocument):
+ doc.add_page(page_no=0, size=Size(width=1000, height=1000))
+
+
+def _default_prov() -> ProvenanceItem:
+ return ProvenanceItem(
+ page_no=0,
+ bbox=BoundingBox(l=100, t=100, r=300, b=200),
+ charspan=(0, 0),
+ )
+
+
+def test_roundtrip_text():
+ doc = DoclingDocument(name="t")
+ doc.add_text(label=DocItemLabel.TEXT, text="Hello world")
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ assert doc2.texts[0].label == DocItemLabel.TEXT
+ assert doc2.texts[0].text == "Hello world"
+
+
+def test_roundtrip_title():
+ doc = DoclingDocument(name="t")
+ doc.add_title(text="My Title")
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ assert doc2.texts[0].label == DocItemLabel.TITLE
+ assert doc2.texts[0].text == "My Title"
+
+
+def test_roundtrip_heading():
+ doc = DoclingDocument(name="t")
+ doc.add_heading(text="Section A", level=2)
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ h = doc2.texts[0]
+ assert h.label == DocItemLabel.SECTION_HEADER and getattr(h, "level", 0) == 2
+ assert h.text == "Section A"
+
+
+def test_roundtrip_caption():
+ doc = DoclingDocument(name="t")
+ doc.add_text(label=DocItemLabel.CAPTION, text="Cap text")
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ assert doc2.texts[0].label == DocItemLabel.CAPTION
+ assert doc2.texts[0].text == "Cap text"
+
+
+def test_roundtrip_footnote():
+ doc = DoclingDocument(name="t")
+ doc.add_text(label=DocItemLabel.FOOTNOTE, text="Foot note")
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ assert doc2.texts[0].label == DocItemLabel.FOOTNOTE
+ assert doc2.texts[0].text == "Foot note"
+
+
+def test_roundtrip_page_header():
+ doc = DoclingDocument(name="t")
+ doc.add_text(label=DocItemLabel.PAGE_HEADER, text="Header")
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ assert doc2.texts[0].label == DocItemLabel.PAGE_HEADER
+ assert doc2.texts[0].text == "Header"
+
+
+def test_roundtrip_page_footer():
+ doc = DoclingDocument(name="t")
+ doc.add_text(label=DocItemLabel.PAGE_FOOTER, text="Footer")
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ assert doc2.texts[0].label == DocItemLabel.PAGE_FOOTER
+ assert doc2.texts[0].text == "Footer"
+
+
+def test_roundtrip_code():
+ doc = DoclingDocument(name="t")
+ doc.add_code(text="print('hi')", code_language=CodeLanguageLabel.PYTHON)
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ assert doc2.texts[0].label == DocItemLabel.CODE
+ assert doc2.texts[0].text.strip() == "print('hi')"
+ assert getattr(doc2.texts[0], "code_language", None) == CodeLanguageLabel.PYTHON
+
+
+def test_roundtrip_formula():
+ doc = DoclingDocument(name="t")
+ doc.add_formula(text="E=mc^2")
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ assert doc2.texts[0].label == DocItemLabel.FORMULA
+ assert doc2.texts[0].text == "E=mc^2"
+
+
+def test_roundtrip_list_unordered():
+ doc = DoclingDocument(name="t")
+ lg = doc.add_list_group()
+ doc.add_list_item("A", parent=lg, enumerated=False)
+ doc.add_list_item("B", parent=lg, enumerated=False)
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ # Ensure group created and items present
+ assert len(doc2.groups) == 1
+ assert len(doc2.texts) == 2
+ assert [it.text for it in doc2.texts] == ["A", "B"]
+
+
+def test_roundtrip_list_ordered():
+ doc = DoclingDocument(name="t")
+ lg = doc.add_list_group()
+ doc.add_list_item("1", parent=lg, enumerated=True)
+ doc.add_list_item("2", parent=lg, enumerated=True)
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.groups) == 1
+ assert len(doc2.texts) == 2
+ assert [it.text for it in doc2.texts] == ["1", "2"]
+
+
+def test_roundtrip_picture_with_caption():
+ doc = DoclingDocument(name="t")
+ cap = doc.add_text(label=DocItemLabel.CAPTION, text="Fig 1")
+ doc.add_picture(caption=cap)
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.pictures) == 1
+ # Caption added as a separate text item referenced by the picture
+ assert len(doc2.texts) >= 1
+ cap_texts = [t for t in doc2.texts if t.label == DocItemLabel.CAPTION]
+ assert len(cap_texts) == 1 and cap_texts[0].text == "Fig 1"
+
+
+def test_roundtrip_table_simple():
+ doc = DoclingDocument(name="t")
+ td = TableData(num_rows=0, num_cols=2)
+ td.add_row(["H1", "H2"]) # header row semantics not required here
+ td.add_row(["C1", "C2"]) # data row
+ doc.add_table(data=td)
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.tables) == 1
+ t2 = doc2.tables[0].data
+ assert t2.num_rows == 2 and t2.num_cols == 2
+ grid_texts = [[cell.text for cell in row] for row in t2.grid]
+ assert grid_texts == [["H1", "H2"], ["C1", "C2"]]
+
+
+def test_roundtrip_table_with_caption():
+ doc = DoclingDocument(name="t")
+ # Create a caption and a simple 2x2 table
+ cap = doc.add_text(label=DocItemLabel.CAPTION, text="Tbl 1")
+ td = TableData(num_rows=0, num_cols=2)
+ td.add_row(["H1", "H2"]) # header row
+ td.add_row(["C1", "C2"]) # data row
+ doc.add_table(data=td, caption=cap)
+
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print(dt)
+ doc2 = _deserialize(dt)
+
+ # One table reconstructed with same grid
+ assert len(doc2.tables) == 1
+ t2 = doc2.tables[0]
+ assert t2.data.num_rows == 2 and t2.data.num_cols == 2
+ grid_texts = [[cell.text for cell in row] for row in t2.data.grid]
+ assert grid_texts == [["H1", "H2"], ["C1", "C2"]]
+
+ # Caption preserved and linked to the table
+ assert len(t2.captions) == 1
+ cap_item = t2.captions[0].resolve(doc2)
+ assert cap_item.label == DocItemLabel.CAPTION and cap_item.text == "Tbl 1"
+
+
+def test_roundtrip_text_prov():
+ doc = DoclingDocument(name="t")
+ _add_default_page(doc)
+ doc.add_text(label=DocItemLabel.TEXT, text="Hello world", prov=_default_prov())
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ dt2 = _serialize(doc2)
+ if DO_PRINT:
+ print("\n", dt2)
+ print(f"`{doc2.texts[0].text}`")
+ assert len(doc2.texts) == 1
+ assert doc2.texts[0].label == DocItemLabel.TEXT
+ assert doc2.texts[0].text == "Hello world"
+
+
+def test_roundtrip_title_prov():
+ doc = DoclingDocument(name="t")
+ _add_default_page(doc)
+ doc.add_title(text="My Title", prov=_default_prov())
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ assert doc2.texts[0].label == DocItemLabel.TITLE
+ assert doc2.texts[0].text == "My Title"
+
+
+def test_roundtrip_heading_prov():
+ doc = DoclingDocument(name="t")
+ _add_default_page(doc)
+ doc.add_heading(text="Section A", level=2, prov=_default_prov())
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ h = doc2.texts[0]
+ assert h.label == DocItemLabel.SECTION_HEADER and getattr(h, "level", 0) == 2
+ assert h.text == "Section A"
+
+
+def test_roundtrip_caption_prov():
+ doc = DoclingDocument(name="t")
+ _add_default_page(doc)
+ doc.add_text(label=DocItemLabel.CAPTION, text="Cap text", prov=_default_prov())
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ assert doc2.texts[0].label == DocItemLabel.CAPTION
+ assert doc2.texts[0].text == "Cap text"
+
+
+def test_roundtrip_footnote_prov():
+ doc = DoclingDocument(name="t")
+ _add_default_page(doc)
+ doc.add_text(label=DocItemLabel.FOOTNOTE, text="Foot note", prov=_default_prov())
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ assert doc2.texts[0].label == DocItemLabel.FOOTNOTE
+ assert doc2.texts[0].text == "Foot note"
+
+
+def test_roundtrip_page_header_prov():
+ doc = DoclingDocument(name="t")
+ _add_default_page(doc)
+ doc.add_text(label=DocItemLabel.PAGE_HEADER, text="Header", prov=_default_prov())
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ assert doc2.texts[0].label == DocItemLabel.PAGE_HEADER
+ assert doc2.texts[0].text == "Header"
+
+
+def test_roundtrip_page_footer_prov():
+ doc = DoclingDocument(name="t")
+ _add_default_page(doc)
+ doc.add_text(label=DocItemLabel.PAGE_FOOTER, text="Footer", prov=_default_prov())
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ assert doc2.texts[0].label == DocItemLabel.PAGE_FOOTER
+ assert doc2.texts[0].text == "Footer"
+
+
+def test_roundtrip_code_prov():
+ doc = DoclingDocument(name="t")
+ _add_default_page(doc)
+ doc.add_code(
+ text="print('hi')", code_language=CodeLanguageLabel.PYTHON, prov=_default_prov()
+ )
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ assert doc2.texts[0].label == DocItemLabel.CODE
+ assert doc2.texts[0].text.strip() == "print('hi')"
+ assert getattr(doc2.texts[0], "code_language", None) == CodeLanguageLabel.PYTHON
+
+
+def test_roundtrip_formula_prov():
+ doc = DoclingDocument(name="t")
+ _add_default_page(doc)
+ doc.add_formula(text="E=mc^2", prov=_default_prov())
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.texts) == 1
+ assert doc2.texts[0].label == DocItemLabel.FORMULA
+ assert doc2.texts[0].text == "E=mc^2"
+
+
+def test_roundtrip_list_unordered_prov():
+ doc = DoclingDocument(name="t")
+ _add_default_page(doc)
+ lg = doc.add_list_group()
+ prov = _default_prov()
+ doc.add_list_item("A", parent=lg, enumerated=False, prov=prov)
+ doc.add_list_item("B", parent=lg, enumerated=False, prov=prov)
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.groups) == 1
+ assert len(doc2.texts) == 2
+ assert [it.text for it in doc2.texts] == ["A", "B"]
+
+
+def test_roundtrip_list_ordered_prov():
+ doc = DoclingDocument(name="t")
+ _add_default_page(doc)
+ lg = doc.add_list_group()
+ prov = _default_prov()
+ doc.add_list_item("1", parent=lg, enumerated=True, prov=prov)
+ doc.add_list_item("2", parent=lg, enumerated=True, prov=prov)
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.groups) == 1
+ assert len(doc2.texts) == 2
+ assert [it.text for it in doc2.texts] == ["1", "2"]
+
+
+def test_roundtrip_picture_with_caption_prov():
+ doc = DoclingDocument(name="t")
+ _add_default_page(doc)
+ cap = doc.add_text(label=DocItemLabel.CAPTION, text="Fig 1", prov=_default_prov())
+ doc.add_picture(caption=cap, prov=_default_prov())
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.pictures) == 1
+ assert len(doc2.texts) >= 1
+ cap_texts = [t for t in doc2.texts if t.label == DocItemLabel.CAPTION]
+ assert len(cap_texts) == 1 and cap_texts[0].text == "Fig 1"
+
+
+def test_roundtrip_table_simple_prov():
+ doc = DoclingDocument(name="t")
+ _add_default_page(doc)
+ td = TableData(num_rows=0, num_cols=2)
+ td.add_row(["H1", "H2"]) # header row semantics not required here
+ td.add_row(["C1", "C2"]) # data row
+ doc.add_table(data=td, prov=_default_prov())
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print("\n", dt)
+ doc2 = _deserialize(dt)
+ assert len(doc2.tables) == 1
+ t2 = doc2.tables[0].data
+ assert t2.num_rows == 2 and t2.num_cols == 2
+ grid_texts = [[cell.text for cell in row] for row in t2.grid]
+ assert grid_texts == [["H1", "H2"], ["C1", "C2"]]
+
+
+def test_roundtrip_table_with_caption_prov():
+ doc = DoclingDocument(name="t")
+ _add_default_page(doc)
+ cap = doc.add_text(label=DocItemLabel.CAPTION, text="Tbl 1", prov=_default_prov())
+ td = TableData(num_rows=0, num_cols=2)
+ td.add_row(["H1", "H2"]) # header row
+ td.add_row(["C1", "C2"]) # data row
+ doc.add_table(data=td, caption=cap, prov=_default_prov())
+
+ dt = _serialize(doc)
+ if DO_PRINT:
+ print(dt)
+ doc2 = _deserialize(dt)
+
+ assert len(doc2.tables) == 1
+ t2 = doc2.tables[0]
+ assert t2.data.num_rows == 2 and t2.data.num_cols == 2
+ grid_texts = [[cell.text for cell in row] for row in t2.data.grid]
+ assert grid_texts == [["H1", "H2"], ["C1", "C2"]]
+
+ assert len(t2.captions) == 1
+ cap_item = t2.captions[0].resolve(doc2)
+ assert cap_item.label == DocItemLabel.CAPTION and cap_item.text == "Tbl 1"
+
+
+def test_roundtrip_complex_table_with_caption_prov():
+ doc = DoclingDocument(name="t")
+ _add_default_page(doc)
+ cap = doc.add_text(label=DocItemLabel.CAPTION, text="Tbl 1", prov=_default_prov())
+ td = TableData(num_rows=3, num_cols=4)
+
+ cell_0_0 = TableCell(
+ row_span=1,
+ col_span=1,
+ start_row_offset_idx=0,
+ end_row_offset_idx=1,
+ start_col_offset_idx=0,
+ end_col_offset_idx=1,
+ text="H 0-0",
+ )
+ td.table_cells.append(cell_0_0)
+
+ cell_0_1 = TableCell(
+ row_span=1,
+ col_span=3,
+ start_row_offset_idx=0,
+ end_row_offset_idx=1,
+ start_col_offset_idx=1,
+ end_col_offset_idx=4,
+ text="H 1-4",
+ )
+ td.table_cells.append(cell_0_1)
+
+ cell_1_0 = TableCell(
+ row_span=2,
+ col_span=1,
+ start_row_offset_idx=1,
+ end_row_offset_idx=3,
+ start_col_offset_idx=0,
+ end_col_offset_idx=1,
+ text="R 1-3",
+ )
+ td.table_cells.append(cell_1_0)
+
+ cell_1_1 = TableCell(
+ row_span=2,
+ col_span=3,
+ start_row_offset_idx=1,
+ end_row_offset_idx=3,
+ start_col_offset_idx=1,
+ end_col_offset_idx=4,
+ text="R 2-2",
+ )
+ td.table_cells.append(cell_1_1)
+
+ doc.add_table(data=td, caption=cap, prov=_default_prov())
+
+ dt = _serialize(doc, add_table_cell_text=True, add_content=True)
+ if DO_PRINT:
+ print(dt)
+ doc2 = _deserialize(dt)
+
+ assert len(doc2.tables) == 1
+ t2 = doc2.tables[0]
+ assert t2.data.num_rows == 3 and t2.data.num_cols == 4
+ grid_texts = [[cell.text for cell in row] for row in t2.data.grid]
+ assert grid_texts == [
+ ["H 0-0", "H 1-4", "H 1-4", "H 1-4"],
+ ["R 1-3", "R 2-2", "R 2-2", "R 2-2"],
+ ["R 1-3", "R 2-2", "R 2-2", "R 2-2"],
+ ]
+
+ assert len(t2.captions) == 1
+ cap_item = t2.captions[0].resolve(doc2)
+ assert cap_item.label == DocItemLabel.CAPTION and cap_item.text == "Tbl 1"
diff --git a/test/test_serialization.py b/test/test_serialization.py
index a783c410..dd629130 100644
--- a/test/test_serialization.py
+++ b/test/test_serialization.py
@@ -4,12 +4,7 @@
import pytest
-from docling_core.experimental.idoctags import IDocTagsDocSerializer, IDocTagsParams
from docling_core.transforms.serializer.common import _DEFAULT_LABELS
-from docling_core.transforms.serializer.doctags import (
- DocTagsDocSerializer,
- DocTagsParams,
-)
from docling_core.transforms.serializer.html import (
HTMLDocSerializer,
HTMLOutputStyle,
@@ -43,7 +38,7 @@ def verify(exp_file: Path, actual: str):
# Normalize platform-dependent quote escaping for DocTags outputs
name = exp_file.name
- if name.endswith(".dt") or name.endswith(".idt.xml"):
+ if name.endswith(".dt") or name.endswith(".idt") or name.endswith(".idt.xml"):
def _normalize_quotes(s: str) -> str:
return s.replace(""", '"').replace(""", '"')
@@ -51,7 +46,7 @@ def _normalize_quotes(s: str) -> str:
expected = _normalize_quotes(expected)
actual = _normalize_quotes(actual)
- assert expected == actual
+ assert actual == expected
# ===============================
@@ -559,94 +554,3 @@ def test_html_inline_and_formatting():
ser = HTMLDocSerializer(doc=doc)
actual = ser.serialize().text
verify(exp_file=src.with_suffix(".gt.html"), actual=actual)
-
-
-# ===============================
-# DocTags tests
-# ===============================
-
-
-def test_doctags_inline_loc_tags():
- src = Path("./test/data/doc/2408.09869v3_enriched.json")
- doc = DoclingDocument.load_from_json(src)
-
- ser = DocTagsDocSerializer(doc=doc)
- actual = ser.serialize().text
- verify(exp_file=src.with_suffix(".out.dt"), actual=actual)
-
-
-def test_doctags_rich_table(rich_table_doc):
- exp_file = Path("./test/data/doc/rich_table.out.dt")
-
- ser = DocTagsDocSerializer(doc=rich_table_doc)
- actual = ser.serialize().text
- verify(exp_file=exp_file, actual=actual)
-
-
-def test_doctags_inline_and_formatting():
- src = Path("./test/data/doc/inline_and_formatting.yaml")
- doc = DoclingDocument.load_from_yaml(src)
-
- ser = DocTagsDocSerializer(doc=doc)
- actual = ser.serialize().text
- verify(exp_file=src.with_suffix(".gt.dt"), actual=actual)
-
-
-def test_doctags_meta():
- src = Path("./test/data/doc/dummy_doc_with_meta.yaml")
- doc = DoclingDocument.load_from_yaml(src)
-
- ser = DocTagsDocSerializer(doc=doc)
- actual = ser.serialize().text
- verify(exp_file=src.with_suffix(".gt.dt"), actual=actual)
-
-
-# ===============================
-# IDocTags tests
-# ===============================
-
-
-def test_idoctags():
- src = Path("./test/data/doc/ddoc_0.json")
- doc = DoclingDocument.load_from_json(src)
-
- if True:
- # Human readable, indented and with content
- params = IDocTagsParams()
- params.add_content = True
-
- ser = IDocTagsDocSerializer(doc=doc, params=params)
- actual = ser.serialize().text
-
- verify(exp_file=src.with_suffix(".v0.gt.dt"), actual=actual)
-
- if True:
- # Human readable, indented but without content
- params = IDocTagsParams()
- params.add_content = False
-
- ser = IDocTagsDocSerializer(doc=doc, params=params)
- actual = ser.serialize().text
-
- verify(exp_file=src.with_suffix(".v1.gt.dt"), actual=actual)
-
- if True:
- # Machine readable, not indented and without content
- params = IDocTagsParams()
- params.pretty_indentation = ""
- params.add_content = False
- params.mode = DocTagsParams.Mode.MINIFIED
-
- ser = IDocTagsDocSerializer(doc=doc, params=params)
- actual = ser.serialize().text
-
- verify(exp_file=src.with_suffix(".v2.gt.dt"), actual=actual)
-
-
-def test_idoctags_meta():
- src = Path("./test/data/doc/dummy_doc_with_meta.yaml")
- doc = DoclingDocument.load_from_yaml(src)
-
- ser = IDocTagsDocSerializer(doc=doc)
- actual = ser.serialize().text
- verify(exp_file=src.with_suffix(".gt.idt.xml"), actual=actual)
diff --git a/test/test_doctags_content_suppression.py b/test/test_serialization_doctag.py
similarity index 60%
rename from test/test_doctags_content_suppression.py
rename to test/test_serialization_doctag.py
index 1a6cf4b2..45d0c983 100644
--- a/test/test_doctags_content_suppression.py
+++ b/test/test_serialization_doctag.py
@@ -1,10 +1,21 @@
+"""Test serialization."""
+
+from pathlib import Path
+
from docling_core.transforms.serializer.doctags import (
DocTagsDocSerializer,
DocTagsParams,
)
+from docling_core.types.doc import DoclingDocument
from docling_core.types.doc.document import DoclingDocument, TableData
from docling_core.types.doc.labels import DocItemLabel
+from .test_serialization import verify
+
+# ===============================
+# DocTags tests
+# ===============================
+
def serialize_doctags(doc: DoclingDocument, **param_overrides) -> str:
params = DocTagsParams(**param_overrides)
@@ -53,10 +64,10 @@ def test_list_items_not_double_wrapped_when_no_content():
doc.add_list_item("Item B", parent=lst)
txt = serialize_doctags(doc, add_content=True)
- print(f"txt with content:\n{txt}")
+ # print(f"txt with content:\n{txt}")
txt = serialize_doctags(doc, add_content=False)
- print(f"txt without content:\n{txt}")
+ # print(f"txt without content:\n{txt}")
# No nested
assert "" not in txt
@@ -64,3 +75,38 @@ def test_list_items_not_double_wrapped_when_no_content():
# Should still have exactly two opening list_item wrappers (for the two items)
# Note: other occurrences could appear in location tokens etc., so be conservative
assert txt.count("") >= 2
+
+
+def test_doctags_inline_loc_tags():
+ src = Path("./test/data/doc/2408.09869v3_enriched.json")
+ doc = DoclingDocument.load_from_json(src)
+
+ ser = DocTagsDocSerializer(doc=doc)
+ actual = ser.serialize().text
+ verify(exp_file=src.with_suffix(".out.dt"), actual=actual)
+
+
+def test_doctags_rich_table(rich_table_doc):
+ exp_file = Path("./test/data/doc/rich_table.out.dt")
+
+ ser = DocTagsDocSerializer(doc=rich_table_doc)
+ actual = ser.serialize().text
+ verify(exp_file=exp_file, actual=actual)
+
+
+def test_doctags_inline_and_formatting():
+ src = Path("./test/data/doc/inline_and_formatting.yaml")
+ doc = DoclingDocument.load_from_yaml(src)
+
+ ser = DocTagsDocSerializer(doc=doc)
+ actual = ser.serialize().text
+ verify(exp_file=src.with_suffix(".gt.dt"), actual=actual)
+
+
+def test_doctags_meta():
+ src = Path("./test/data/doc/dummy_doc_with_meta.yaml")
+ doc = DoclingDocument.load_from_yaml(src)
+
+ ser = DocTagsDocSerializer(doc=doc)
+ actual = ser.serialize().text
+ verify(exp_file=src.with_suffix(".gt.dt"), actual=actual)
diff --git a/test/test_serialization_idoctag.py b/test/test_serialization_idoctag.py
new file mode 100644
index 00000000..645881f3
--- /dev/null
+++ b/test/test_serialization_idoctag.py
@@ -0,0 +1,180 @@
+"""Unit tests for IDocTags create_closing_token helper."""
+
+from pathlib import Path
+
+import pytest
+
+from docling_core.experimental.idoctags import (
+ IDocTagsDocSerializer,
+ IDocTagsParams,
+ IDocTagsSerializationMode,
+ IDocTagsVocabulary,
+)
+from docling_core.types.doc import DocItemLabel, DoclingDocument, TableData
+
+from .test_serialization import verify
+
+# ===============================
+# IDocTags unit-tests
+# ===============================
+
+
+def test_create_closing_token_from_opening_tag_simple():
+ assert IDocTagsVocabulary.create_closing_token(token="") == ""
+ assert (
+ IDocTagsVocabulary.create_closing_token(token='\n ')
+ == ""
+ )
+ assert (
+ IDocTagsVocabulary.create_closing_token(token=' ')
+ == "
"
+ )
+ # Inline with attribute
+ assert (
+ IDocTagsVocabulary.create_closing_token(token=' ')
+ == ""
+ )
+
+
+def test_create_closing_token_returns_existing_closing():
+ assert IDocTagsVocabulary.create_closing_token(token="") == ""
+
+
+@pytest.mark.parametrize(
+ "bad",
+ [
+ "
",
+ '',
+ '',
+ '',
+ ],
+)
+def test_create_closing_token_rejects_self_closing(bad):
+ with pytest.raises(ValueError):
+ IDocTagsVocabulary.create_closing_token(token=bad)
+
+
+@pytest.mark.parametrize(
+ "bad",
+ [
+ "text", # not a tag
+ "", # self-closing form of non-self-closing token
+ "", # malformed closing
+ "", # unknown token
+ ],
+)
+def test_create_closing_token_invalid_inputs(bad):
+ with pytest.raises(ValueError):
+ IDocTagsVocabulary.create_closing_token(token=bad)
+
+
+# ===============================
+# IDocTags tests
+# ===============================
+
+
+def serialize_idoctags(doc: DoclingDocument, **param_overrides) -> str:
+ params = IDocTagsParams(**param_overrides)
+ ser = IDocTagsDocSerializer(doc=doc, params=params)
+ return ser.serialize().text
+
+
+def test_no_content_suppresses_caption_and_table_cell_text():
+ doc = DoclingDocument(name="t")
+
+ # Add a caption text item
+ cap = doc.add_text(label=DocItemLabel.CAPTION, text="Table Caption Text")
+
+ # Build a 2x2 table with header row and data row
+ td = TableData(num_rows=0, num_cols=2)
+ td.add_row(["H1", "H2"]) # header
+ td.add_row(["C1", "C2"]) # data
+ doc.add_table(data=td, caption=cap)
+
+ txt = serialize_idoctags(doc, add_content=False)
+
+ # Caption text suppressed
+ assert "Table Caption Text" not in txt
+
+ # No table cell text
+ for cell_text in ["H1", "H2", "C1", "C2"]:
+ assert cell_text not in txt
+
+ # OTSL structural tokens should remain
+ assert "" in txt and "" in txt
+
+
+def test_no_content_suppresses_figure_caption_text():
+ doc = DoclingDocument(name="t")
+ cap = doc.add_text(label=DocItemLabel.CAPTION, text="Figure Caption Text")
+ doc.add_picture(caption=cap)
+
+ txt = serialize_idoctags(doc, add_content=False)
+ assert "Figure Caption Text" not in txt
+
+
+def test_list_items_not_double_wrapped_when_no_content():
+ doc = DoclingDocument(name="t")
+ lst = doc.add_list_group()
+ doc.add_list_item("Item A", parent=lst)
+ doc.add_list_item("Item B", parent=lst)
+
+ txt = serialize_idoctags(doc, add_content=True)
+ # print(f"txt with content:\n{txt}")
+
+ txt = serialize_idoctags(doc, add_content=False)
+ # print(f"txt without content:\n{txt}")
+
+ # No nested
+ assert "" not in txt
+
+ # Should still have exactly two opening list_text wrappers (for the two items)
+ # Note: other occurrences could appear in location tokens etc., so be conservative
+ assert txt.count("") >= 2
+
+
+def test_idoctags():
+ src = Path("./test/data/doc/ddoc_0.json")
+ doc = DoclingDocument.load_from_json(src)
+
+ if True:
+ # Human readable, indented and with content
+ params = IDocTagsParams()
+ params.add_content = True
+
+ ser = IDocTagsDocSerializer(doc=doc, params=params)
+ actual = ser.serialize().text
+
+ verify(exp_file=src.with_suffix(".v0.gt.idt"), actual=actual)
+
+ if True:
+ # Human readable, indented but without content
+ params = IDocTagsParams()
+ params.add_content = False
+
+ ser = IDocTagsDocSerializer(doc=doc, params=params)
+ actual = ser.serialize().text
+
+ verify(exp_file=src.with_suffix(".v1.gt.idt"), actual=actual)
+
+ if True:
+ # Machine readable, not indented and without content
+ params = IDocTagsParams()
+ params.pretty_indentation = ""
+ params.add_content = False
+ params.mode = IDocTagsSerializationMode.LLM_FRIENDLY
+
+ ser = IDocTagsDocSerializer(doc=doc, params=params)
+ actual = ser.serialize().text
+
+ verify(exp_file=src.with_suffix(".v2.gt.idt"), actual=actual)
+
+
+def test_idoctags_meta():
+ src = Path("./test/data/doc/dummy_doc_with_meta.yaml")
+ doc = DoclingDocument.load_from_yaml(src)
+
+ ser = IDocTagsDocSerializer(doc=doc)
+ actual = ser.serialize().text
+ verify(exp_file=src.with_suffix(".gt.idt.xml"), actual=actual)
diff --git a/uv.lock b/uv.lock
index 30f766a2..eab3d3d5 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,5 +1,5 @@
version = 1
-revision = 3
+revision = 2
requires-python = ">=3.9, <4.0"
resolution-markers = [
"python_full_version >= '3.12'",
@@ -8,6 +8,165 @@ resolution-markers = [
"python_full_version < '3.10'",
]
+[[package]]
+name = "aiohappyeyeballs"
+version = "2.6.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760, upload-time = "2025-03-12T01:42:48.764Z" }
+wheels = [
+ { url = "https://files.pythonhosted.org/packages/0f/15/5bf3b99495fb160b63f95972b81750f18f7f4e02ad051373b669d17d44f2/aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8", size = 15265, upload-time = "2025-03-12T01:42:47.083Z" },
+]
+
+[[package]]
+name = "aiohttp"
+version = "3.13.2"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+ { name = "aiohappyeyeballs" },
+ { name = "aiosignal" },
+ { name = "async-timeout", marker = "python_full_version < '3.11'" },
+ { name = "attrs" },
+ { name = "frozenlist" },
+ { name = "multidict" },
+ { name = "propcache" },
+ { name = "yarl" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/1c/ce/3b83ebba6b3207a7135e5fcaba49706f8a4b6008153b4e30540c982fae26/aiohttp-3.13.2.tar.gz", hash = "sha256:40176a52c186aefef6eb3cad2cdd30cd06e3afbe88fe8ab2af9c0b90f228daca", size = 7837994, upload-time = "2025-10-28T20:59:39.937Z" }
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