Bump version for release. (#1564 )

Remove onnxruntime<=1.20.1 Windows pin (#1551 )
Add text/markdown to Accept header (#1554 )
2026-02-20 11:40:57 -08:00 · 2026-02-16 15:05:37 -08:00 · 2026-02-13 11:53:01 -08:00 · 2026-02-13 10:45:39 -08:00 · 2026-01-08 15:15:22 -08:00 · 2026-01-07 16:38:45 -08:00
23 changed files with 2647 additions and 34 deletions
@@ -1,2 +1,5 @@
 packages/markitdown/tests/test_files/** linguist-vendored
 packages/markitdown-sample-plugin/tests/test_files/** linguist-vendored
+
+# Treat PDF files as binary to prevent line ending conversion
+*.pdf binary
@@ -52,6 +52,7 @@ coverage.xml
 .hypothesis/
 .pytest_cache/
 cover/
+.test-logs/

 # Translations
 *.mo
@@ -30,30 +30,30 @@ dependencies = [
  "magika~=0.6.1",
  "charset-normalizer",
  "defusedxml",
-  "onnxruntime<=1.20.1; sys_platform == 'win32'",
 ]

 [project.optional-dependencies]
 all = [
  "python-pptx",
-  "mammoth~=1.10.0",
+  "mammoth~=1.11.0",
  "pandas",
  "openpyxl",
  "xlrd",
  "lxml",
-  "pdfminer.six",
+  "pdfminer.six>=20251230",
+  "pdfplumber>=0.11.9",
  "olefile",
  "pydub",
  "SpeechRecognition",
  "youtube-transcript-api~=1.0.0",
  "azure-ai-documentintelligence",
-  "azure-identity"
+  "azure-identity",
 ]
 pptx = ["python-pptx"]
-docx = ["mammoth", "lxml"]
+docx = ["mammoth~=1.11.0", "lxml"]
 xlsx = ["pandas", "openpyxl"]
 xls = ["pandas", "xlrd"]
-pdf = ["pdfminer.six"]
+pdf = ["pdfminer.six>=20251230", "pdfplumber>=0.11.9"]
 outlook = ["olefile"]
 audio-transcription = ["pydub", "SpeechRecognition"]
 youtube-transcription = ["youtube-transcript-api"]
@@ -1,4 +1,4 @@
 # SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
 #
 # SPDX-License-Identifier: MIT
-__version__ = "0.1.3"
+__version__ = "0.1.5"
@@ -107,6 +107,13 @@ class MarkItDown:
        requests_session = kwargs.get("requests_session")
        if requests_session is None:
            self._requests_session = requests.Session()
+            # Signal that we prefer markdown over HTML, etc. if the server supports it.
+            # e.g., https://blog.cloudflare.com/markdown-for-agents/
+            self._requests_session.headers.update(
+                {
+                    "Accept": "text/markdown, text/html;q=0.9, text/plain;q=0.8, */*;q=0.1"
+                }
+            )
        else:
            self._requests_session = requests_session

@@ -15,13 +15,6 @@ from .._exceptions import MissingDependencyException, MISSING_DEPENDENCY_MESSAGE
 _dependency_exc_info = None
 try:
    import mammoth
-    import mammoth.docx.files
-
-    def mammoth_files_open(self, uri):
-        warn("DOCX: processing of r:link resources (e.g., linked images) is disabled.")
-        return io.BytesIO(b"")
-
-    mammoth.docx.files.Files.open = mammoth_files_open

 except ImportError:
    # Preserve the error and stack trace for later
@@ -1,22 +1,69 @@
 import sys
 import io
-
+import re
 from typing import BinaryIO, Any

-
 from .._base_converter import DocumentConverter, DocumentConverterResult
 from .._stream_info import StreamInfo
 from .._exceptions import MissingDependencyException, MISSING_DEPENDENCY_MESSAGE

+# Pattern for MasterFormat-style partial numbering (e.g., ".1", ".2", ".10")
+PARTIAL_NUMBERING_PATTERN = re.compile(r"^\.\d+$")

-# Try loading optional (but in this case, required) dependencies
-# Save reporting of any exceptions for later
+
+def _merge_partial_numbering_lines(text: str) -> str:
+    """
+    Post-process extracted text to merge MasterFormat-style partial numbering
+    with the following text line.
+
+    MasterFormat documents use partial numbering like:
+        .1  The intent of this Request for Proposal...
+        .2  Available information relative to...
+
+    Some PDF extractors split these into separate lines:
+        .1
+        The intent of this Request for Proposal...
+
+    This function merges them back together.
+    """
+    lines = text.split("\n")
+    result_lines: list[str] = []
+    i = 0
+
+    while i < len(lines):
+        line = lines[i]
+        stripped = line.strip()
+
+        # Check if this line is ONLY a partial numbering
+        if PARTIAL_NUMBERING_PATTERN.match(stripped):
+            # Look for the next non-empty line to merge with
+            j = i + 1
+            while j < len(lines) and not lines[j].strip():
+                j += 1
+
+            if j < len(lines):
+                # Merge the partial numbering with the next line
+                next_line = lines[j].strip()
+                result_lines.append(f"{stripped} {next_line}")
+                i = j + 1  # Skip past the merged line
+            else:
+                # No next line to merge with, keep as is
+                result_lines.append(line)
+                i += 1
+        else:
+            result_lines.append(line)
+            i += 1
+
+    return "\n".join(result_lines)
+
+
+# Load dependencies
 _dependency_exc_info = None
 try:
    import pdfminer
    import pdfminer.high_level
+    import pdfplumber
 except ImportError:
-    # Preserve the error and stack trace for later
    _dependency_exc_info = sys.exc_info()


@@ -28,16 +75,435 @@ ACCEPTED_MIME_TYPE_PREFIXES = [
 ACCEPTED_FILE_EXTENSIONS = [".pdf"]


+def _to_markdown_table(table: list[list[str]], include_separator: bool = True) -> str:
+    """Convert a 2D list (rows/columns) into a nicely aligned Markdown table.
+
+    Args:
+        table: 2D list of cell values
+        include_separator: If True, include header separator row (standard markdown).
+                          If False, output simple pipe-separated rows.
+    """
+    if not table:
+        return ""
+
+    # Normalize None → ""
+    table = [[cell if cell is not None else "" for cell in row] for row in table]
+
+    # Filter out empty rows
+    table = [row for row in table if any(cell.strip() for cell in row)]
+
+    if not table:
+        return ""
+
+    # Column widths
+    col_widths = [max(len(str(cell)) for cell in col) for col in zip(*table)]
+
+    def fmt_row(row: list[str]) -> str:
+        return (
+            "|"
+            + "|".join(str(cell).ljust(width) for cell, width in zip(row, col_widths))
+            + "|"
+        )
+
+    if include_separator:
+        header, *rows = table
+        md = [fmt_row(header)]
+        md.append("|" + "|".join("-" * w for w in col_widths) + "|")
+        for row in rows:
+            md.append(fmt_row(row))
+    else:
+        md = [fmt_row(row) for row in table]
+
+    return "\n".join(md)
+
+
+def _extract_form_content_from_words(page: Any) -> str | None:
+    """
+    Extract form-style content from a PDF page by analyzing word positions.
+    This handles borderless forms/tables where words are aligned in columns.
+
+    Returns markdown with proper table formatting:
+    - Tables have pipe-separated columns with header separator rows
+    - Non-table content is rendered as plain text
+
+    Returns None if the page doesn't appear to be a form-style document,
+    indicating that pdfminer should be used instead for better text spacing.
+    """
+    words = page.extract_words(keep_blank_chars=True, x_tolerance=3, y_tolerance=3)
+    if not words:
+        return None
+
+    # Group words by their Y position (rows)
+    y_tolerance = 5
+    rows_by_y: dict[float, list[dict]] = {}
+    for word in words:
+        y_key = round(word["top"] / y_tolerance) * y_tolerance
+        if y_key not in rows_by_y:
+            rows_by_y[y_key] = []
+        rows_by_y[y_key].append(word)
+
+    # Sort rows by Y position
+    sorted_y_keys = sorted(rows_by_y.keys())
+    page_width = page.width if hasattr(page, "width") else 612
+
+    # First pass: analyze each row
+    row_info: list[dict] = []
+    for y_key in sorted_y_keys:
+        row_words = sorted(rows_by_y[y_key], key=lambda w: w["x0"])
+        if not row_words:
+            continue
+
+        first_x0 = row_words[0]["x0"]
+        last_x1 = row_words[-1]["x1"]
+        line_width = last_x1 - first_x0
+        combined_text = " ".join(w["text"] for w in row_words)
+
+        # Count distinct x-position groups (columns)
+        x_positions = [w["x0"] for w in row_words]
+        x_groups: list[float] = []
+        for x in sorted(x_positions):
+            if not x_groups or x - x_groups[-1] > 50:
+                x_groups.append(x)
+
+        # Determine row type
+        is_paragraph = line_width > page_width * 0.55 and len(combined_text) > 60
+
+        # Check for MasterFormat-style partial numbering (e.g., ".1", ".2")
+        # These should be treated as list items, not table rows
+        has_partial_numbering = False
+        if row_words:
+            first_word = row_words[0]["text"].strip()
+            if PARTIAL_NUMBERING_PATTERN.match(first_word):
+                has_partial_numbering = True
+
+        row_info.append(
+            {
+                "y_key": y_key,
+                "words": row_words,
+                "text": combined_text,
+                "x_groups": x_groups,
+                "is_paragraph": is_paragraph,
+                "num_columns": len(x_groups),
+                "has_partial_numbering": has_partial_numbering,
+            }
+        )
+
+    # Collect ALL x-positions from rows with 3+ columns (table-like rows)
+    # This gives us the global column structure
+    all_table_x_positions: list[float] = []
+    for info in row_info:
+        if info["num_columns"] >= 3 and not info["is_paragraph"]:
+            all_table_x_positions.extend(info["x_groups"])
+
+    if not all_table_x_positions:
+        return None
+
+    # Compute adaptive column clustering tolerance based on gap analysis
+    all_table_x_positions.sort()
+
+    # Calculate gaps between consecutive x-positions
+    gaps = []
+    for i in range(len(all_table_x_positions) - 1):
+        gap = all_table_x_positions[i + 1] - all_table_x_positions[i]
+        if gap > 5:  # Only significant gaps
+            gaps.append(gap)
+
+    # Determine optimal tolerance using statistical analysis
+    if gaps and len(gaps) >= 3:
+        # Use 70th percentile of gaps as threshold (balances precision/recall)
+        sorted_gaps = sorted(gaps)
+        percentile_70_idx = int(len(sorted_gaps) * 0.70)
+        adaptive_tolerance = sorted_gaps[percentile_70_idx]
+
+        # Clamp tolerance to reasonable range [25, 50]
+        adaptive_tolerance = max(25, min(50, adaptive_tolerance))
+    else:
+        # Fallback to conservative value
+        adaptive_tolerance = 35
+
+    # Compute global column boundaries using adaptive tolerance
+    global_columns: list[float] = []
+    for x in all_table_x_positions:
+        if not global_columns or x - global_columns[-1] > adaptive_tolerance:
+            global_columns.append(x)
+
+    # Adaptive max column check based on page characteristics
+    # Calculate average column width
+    if len(global_columns) > 1:
+        content_width = global_columns[-1] - global_columns[0]
+        avg_col_width = content_width / len(global_columns)
+
+        # Forms with very narrow columns (< 30px) are likely dense text
+        if avg_col_width < 30:
+            return None
+
+        # Compute adaptive max based on columns per inch
+        # Typical forms have 3-8 columns per inch
+        columns_per_inch = len(global_columns) / (content_width / 72)
+
+        # If density is too high (> 10 cols/inch), likely not a form
+        if columns_per_inch > 10:
+            return None
+
+        # Adaptive max: allow more columns for wider pages
+        # Standard letter is 612pt wide, so scale accordingly
+        adaptive_max_columns = int(20 * (page_width / 612))
+        adaptive_max_columns = max(15, adaptive_max_columns)  # At least 15
+
+        if len(global_columns) > adaptive_max_columns:
+            return None
+    else:
+        # Single column, not a form
+        return None
+
+    # Now classify each row as table row or not
+    # A row is a table row if it has words that align with 2+ of the global columns
+    for info in row_info:
+        if info["is_paragraph"]:
+            info["is_table_row"] = False
+            continue
+
+        # Rows with partial numbering (e.g., ".1", ".2") are list items, not table rows
+        if info["has_partial_numbering"]:
+            info["is_table_row"] = False
+            continue
+
+        # Count how many global columns this row's words align with
+        aligned_columns: set[int] = set()
+        for word in info["words"]:
+            word_x = word["x0"]
+            for col_idx, col_x in enumerate(global_columns):
+                if abs(word_x - col_x) < 40:
+                    aligned_columns.add(col_idx)
+                    break
+
+        # If row uses 2+ of the established columns, it's a table row
+        info["is_table_row"] = len(aligned_columns) >= 2
+
+    # Find table regions (consecutive table rows)
+    table_regions: list[tuple[int, int]] = []  # (start_idx, end_idx)
+    i = 0
+    while i < len(row_info):
+        if row_info[i]["is_table_row"]:
+            start_idx = i
+            while i < len(row_info) and row_info[i]["is_table_row"]:
+                i += 1
+            end_idx = i
+            table_regions.append((start_idx, end_idx))
+        else:
+            i += 1
+
+    # Check if enough rows are table rows (at least 20%)
+    total_table_rows = sum(end - start for start, end in table_regions)
+    if len(row_info) > 0 and total_table_rows / len(row_info) < 0.2:
+        return None
+
+    # Build output - collect table data first, then format with proper column widths
+    result_lines: list[str] = []
+    num_cols = len(global_columns)
+
+    # Helper function to extract cells from a row
+    def extract_cells(info: dict) -> list[str]:
+        cells: list[str] = ["" for _ in range(num_cols)]
+        for word in info["words"]:
+            word_x = word["x0"]
+            # Find the correct column using boundary ranges
+            assigned_col = num_cols - 1  # Default to last column
+            for col_idx in range(num_cols - 1):
+                col_end = global_columns[col_idx + 1]
+                if word_x < col_end - 20:
+                    assigned_col = col_idx
+                    break
+            if cells[assigned_col]:
+                cells[assigned_col] += " " + word["text"]
+            else:
+                cells[assigned_col] = word["text"]
+        return cells
+
+    # Process rows, collecting table data for proper formatting
+    idx = 0
+    while idx < len(row_info):
+        info = row_info[idx]
+
+        # Check if this row starts a table region
+        table_region = None
+        for start, end in table_regions:
+            if idx == start:
+                table_region = (start, end)
+                break
+
+        if table_region:
+            start, end = table_region
+            # Collect all rows in this table
+            table_data: list[list[str]] = []
+            for table_idx in range(start, end):
+                cells = extract_cells(row_info[table_idx])
+                table_data.append(cells)
+
+            # Calculate column widths for this table
+            if table_data:
+                col_widths = [
+                    max(len(row[col]) for row in table_data) for col in range(num_cols)
+                ]
+                # Ensure minimum width of 3 for separator dashes
+                col_widths = [max(w, 3) for w in col_widths]
+
+                # Format header row
+                header = table_data[0]
+                header_str = (
+                    "| "
+                    + " | ".join(
+                        cell.ljust(col_widths[i]) for i, cell in enumerate(header)
+                    )
+                    + " |"
+                )
+                result_lines.append(header_str)
+
+                # Format separator row
+                separator = (
+                    "| "
+                    + " | ".join("-" * col_widths[i] for i in range(num_cols))
+                    + " |"
+                )
+                result_lines.append(separator)
+
+                # Format data rows
+                for row in table_data[1:]:
+                    row_str = (
+                        "| "
+                        + " | ".join(
+                            cell.ljust(col_widths[i]) for i, cell in enumerate(row)
+                        )
+                        + " |"
+                    )
+                    result_lines.append(row_str)
+
+            idx = end  # Skip to end of table region
+        else:
+            # Check if we're inside a table region (not at start)
+            in_table = False
+            for start, end in table_regions:
+                if start < idx < end:
+                    in_table = True
+                    break
+
+            if not in_table:
+                # Non-table content
+                result_lines.append(info["text"])
+            idx += 1
+
+    return "\n".join(result_lines)
+
+
+def _extract_tables_from_words(page: Any) -> list[list[list[str]]]:
+    """
+    Extract tables from a PDF page by analyzing word positions.
+    This handles borderless tables where words are aligned in columns.
+
+    This function is designed for structured tabular data (like invoices),
+    not for multi-column text layouts in scientific documents.
+    """
+    words = page.extract_words(keep_blank_chars=True, x_tolerance=3, y_tolerance=3)
+    if not words:
+        return []
+
+    # Group words by their Y position (rows)
+    y_tolerance = 5
+    rows_by_y: dict[float, list[dict]] = {}
+    for word in words:
+        y_key = round(word["top"] / y_tolerance) * y_tolerance
+        if y_key not in rows_by_y:
+            rows_by_y[y_key] = []
+        rows_by_y[y_key].append(word)
+
+    # Sort rows by Y position
+    sorted_y_keys = sorted(rows_by_y.keys())
+
+    # Find potential column boundaries by analyzing x positions across all rows
+    all_x_positions = []
+    for words_in_row in rows_by_y.values():
+        for word in words_in_row:
+            all_x_positions.append(word["x0"])
+
+    if not all_x_positions:
+        return []
+
+    # Cluster x positions to find column starts
+    all_x_positions.sort()
+    x_tolerance_col = 20
+    column_starts: list[float] = []
+    for x in all_x_positions:
+        if not column_starts or x - column_starts[-1] > x_tolerance_col:
+            column_starts.append(x)
+
+    # Need at least 3 columns but not too many (likely text layout, not table)
+    if len(column_starts) < 3 or len(column_starts) > 10:
+        return []
+
+    # Find rows that span multiple columns (potential table rows)
+    table_rows = []
+    for y_key in sorted_y_keys:
+        words_in_row = sorted(rows_by_y[y_key], key=lambda w: w["x0"])
+
+        # Assign words to columns
+        row_data = [""] * len(column_starts)
+        for word in words_in_row:
+            # Find the closest column
+            best_col = 0
+            min_dist = float("inf")
+            for i, col_x in enumerate(column_starts):
+                dist = abs(word["x0"] - col_x)
+                if dist < min_dist:
+                    min_dist = dist
+                    best_col = i
+
+            if row_data[best_col]:
+                row_data[best_col] += " " + word["text"]
+            else:
+                row_data[best_col] = word["text"]
+
+        # Only include rows that have content in multiple columns
+        non_empty = sum(1 for cell in row_data if cell.strip())
+        if non_empty >= 2:
+            table_rows.append(row_data)
+
+    # Validate table quality - tables should have:
+    # 1. Enough rows (at least 3 including header)
+    # 2. Short cell content (tables have concise data, not paragraphs)
+    # 3. Consistent structure across rows
+    if len(table_rows) < 3:
+        return []
+
+    # Check if cells contain short, structured data (not long text)
+    long_cell_count = 0
+    total_cell_count = 0
+    for row in table_rows:
+        for cell in row:
+            if cell.strip():
+                total_cell_count += 1
+                # If cell has more than 30 chars, it's likely prose text
+                if len(cell.strip()) > 30:
+                    long_cell_count += 1
+
+    # If more than 30% of cells are long, this is probably not a table
+    if total_cell_count > 0 and long_cell_count / total_cell_count > 0.3:
+        return []
+
+    return [table_rows]
+
+
 class PdfConverter(DocumentConverter):
    """
-    Converts PDFs to Markdown. Most style information is ignored, so the results are essentially plain-text.
+    Converts PDFs to Markdown.
+    Supports extracting tables into aligned Markdown format (via pdfplumber).
+    Falls back to pdfminer if pdfplumber is missing or fails.
    """

    def accepts(
        self,
        file_stream: BinaryIO,
        stream_info: StreamInfo,
-        **kwargs: Any,  # Options to pass to the converter
+        **kwargs: Any,
    ) -> bool:
        mimetype = (stream_info.mimetype or "").lower()
        extension = (stream_info.extension or "").lower()
@@ -55,9 +521,8 @@ class PdfConverter(DocumentConverter):
        self,
        file_stream: BinaryIO,
        stream_info: StreamInfo,
-        **kwargs: Any,  # Options to pass to the converter
+        **kwargs: Any,
    ) -> DocumentConverterResult:
-        # Check the dependencies
        if _dependency_exc_info is not None:
            raise MissingDependencyException(
                MISSING_DEPENDENCY_MESSAGE.format(
@@ -65,13 +530,58 @@ class PdfConverter(DocumentConverter):
                    extension=".pdf",
                    feature="pdf",
                )
-            ) from _dependency_exc_info[
-                1
-            ].with_traceback(  # type: ignore[union-attr]
+            ) from _dependency_exc_info[1].with_traceback(
                _dependency_exc_info[2]
-            )
+            )  # type: ignore[union-attr]

-        assert isinstance(file_stream, io.IOBase)  # for mypy
-        return DocumentConverterResult(
-            markdown=pdfminer.high_level.extract_text(file_stream),
-        )
+        assert isinstance(file_stream, io.IOBase)
+
+        markdown_chunks: list[str] = []
+
+        # Read file stream into BytesIO for compatibility with pdfplumber
+        pdf_bytes = io.BytesIO(file_stream.read())
+
+        try:
+            # Track how many pages are form-style vs plain text
+            form_pages = 0
+            plain_pages = 0
+
+            with pdfplumber.open(pdf_bytes) as pdf:
+                for page in pdf.pages:
+                    # Try form-style word position extraction
+                    page_content = _extract_form_content_from_words(page)
+
+                    # If extraction returns None, this page is not form-style
+                    if page_content is None:
+                        plain_pages += 1
+                        # Extract text using pdfplumber's basic extraction for this page
+                        text = page.extract_text()
+                        if text and text.strip():
+                            markdown_chunks.append(text.strip())
+                    else:
+                        form_pages += 1
+                        if page_content.strip():
+                            markdown_chunks.append(page_content)
+
+            # If most pages are plain text, use pdfminer for better text handling
+            if plain_pages > form_pages and plain_pages > 0:
+                pdf_bytes.seek(0)
+                markdown = pdfminer.high_level.extract_text(pdf_bytes)
+            else:
+                # Build markdown from chunks
+                markdown = "\n\n".join(markdown_chunks).strip()
+
+        except Exception:
+            # Fallback if pdfplumber fails
+            pdf_bytes.seek(0)
+            markdown = pdfminer.high_level.extract_text(pdf_bytes)
+
+        # Fallback if still empty
+        if not markdown:
+            pdf_bytes.seek(0)
+            markdown = pdfminer.high_level.extract_text(pdf_bytes)
+
+        # Post-process to merge MasterFormat-style partial numbering with following text
+        markdown = _merge_partial_numbering_lines(markdown)
+
+        return DocumentConverterResult(markdown=markdown)
@@ -0,0 +1,97 @@
+%PDF-1.4
+%“Œ‹ž ReportLab Generated PDF document http://www.reportlab.com
+1 0 obj
+<<
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+TECHMART ELECTRONICS
+4567 Innovation Blvd
+San Francisco, CA 94103
+(415) 555-0199
+
+===================================
+
+Store #0342 - Downtown SF
+11/23/2024 14:32:18 PST
+TXN: TXN-98765-2024
+Cashier: Emily Rodriguez
+Register: POS-07
+
+-----------------------------------
+
+Wireless Noise-Cancelling
+Headphones - Premium Black
+AUDIO-5521 1 @ $349.99
+Member Discount $-50.00
+$299.99
+USB-C Hub 7-in-1 Adapter
+with HDMI & Ethernet
+ACC-8834 2 @ $79.99
+$159.98
+Portable SSD 2TB
+Thunderbolt 3 Compatible
+STOR-2241 1 @ $289.00
+Member Discount $-29.00
+$260.00
+Ergonomic Wireless Mouse
+Rechargeable Battery
+ACC-9012 1 @ $59.99
+$59.99
+Screen Cleaning Kit
+Professional Grade
+CARE-1156 3 @ $12.99
+$38.97
+HDMI 2.1 Cable 6ft
+8K Resolution Support
+CABLE-7789 2 @ $24.99
+Member Discount $-5.00
+$44.98
+-----------------------------------
+
+SUBTOTAL $863.91
+Member Discount (15%)-$84.00
+Sales Tax (8.5%) $66.23
+Rewards Applied -$25.00
+===================================
+TOTAL $821.14
+===================================
+
+PAYMENT METHOD
+Visa Card ending in 4782
+Auth: 847392
+Ref: REF-20241123-98765
+
+-----------------------------------
+
+REWARDS MEMBER
+Sarah Mitchell
+ID: TM-447821
+Points Earned: 821
+Total Points: 3,247
+Next Reward: $50 gift card
+at 5,000 pts (1,753 to go)
+
+-----------------------------------
+
+RETURN POLICY
+Returns within 30 days
+Receipt required
+Electronics must be unopened
+
+*TXN98765202411231432*
+
+Thank you for shopping!
+www.techmart.example.com
+
+===================================
+
@@ -0,0 +1,76 @@
+ZAVA AUTO REPAIR
+Certified Collision Repair
+123 Main Street, Redmond, WA 98052
+Phone: (425) 000-0000
+Preliminary Estimate (ID: EST-1008)
+| Customer Information |                     |     | Vehicle Information |                   |
+| -------------------- | ------------------- | --- | ------------------- | ----------------- |
+| Insured name         | Gabriel Diaz        |     | Year                | 2022              |
+| Claim #              | SF-1008             |     | Make                | Jeep              |
+| Policy #             | POL-2022-555        |     | Model               | Grand Cherokee    |
+| Phone                | (425) 111-1111      |     | Trim                | Limited           |
+| Email                | gabriel@contoso.com |     | VIN                 | 1C4RJFBG2NC123456 |
+|                      |                     |     | Color               | White             |
+|                      |                     |     | Odometer            | 9,800             |
+| Repair Order #       | RO-20221108         |     | Estimator           | Ellis Turner      |
+Estimate Totals
+|                  |     | Hours | Rate | Cost  |
+| ---------------- | --- | ----- | ---- | ----- |
+| Parts            |     |       |      | 2,100 |
+| Body Labor       |     | 2     | 150  | 300   |
+| Paint Labor      |     | 1.5   | 150  | 225   |
+| Mechanical Labor |     | -     | -    | -     |
+Supplies
+|               | Paint Supplies           |     |        | 60     |
+| ------------- | ------------------------ | --- | ------ | ------ |
+|               | Body Supplies            |     |        | 30     |
+| Other Charges |                          |     |        | 15     |
+| Subtotal      |                          |     |        | 2,730  |
+| Sales Tax     |                          |     | 10.20% | 278.46 |
+| GRAND TOTAL   |                          |     |        | 5,738  |
+| Note          | Minor rear bumper repair |     |        |        |
+This is a preliminary estimate for the visible damage of the vehicle. Additional damage / repairs / parts may be found
+after the vehicle has been disassembled and damaged parts have been removed. Suspension damages may be
+present, but can not be determined until an alignment on the vehicle has been done. Parts Prices may vary due to
+models and vehicle maker price updates. Please be advised if vehicle owner elects to have vehicle sent to service for
+any mechanical concerns, ALL service departments charge a vehicle diagnostic charge. If the mechanical concern is
+deemed not related to an insurance claim, vehicle owner will be reponsible for charges.
+
+ZAVA AUTO REPAIR
+Certified Collision Repair
+123 Main Street, Redmond, WA 98052
+Phone: (425) 000-0000
+Preliminary Estimate (ID: EST-1008)
+Customer Information Vehicle Information
+| Insured name   | Bruce Wayne                |     | Year      | 2025         |
+| -------------- | -------------------------- | --- | --------- | ------------ |
+| Claim #        |                            | 999 | Make      | Batman       |
+| Policy #       | IM-BATMAN                  |     | Model     | Batmobile    |
+| Phone          | (416) 555-1234             |     | Trim      | Limited      |
+| Email          | batman@wayneindustries.com |     | VIN       | XXX          |
+|                |                            |     | Color     | Black        |
+|                |                            |     | Odometer  | 1            |
+| Repair Order # | RO-20221108                |     | Estimator | Ellis Turner |
+Estimate Totals
+|                  |     | Hours | Rate | Cost   |
+| ---------------- | --- | ----- | ---- | ------ |
+| Parts            |     |       |      | 99,999 |
+| Body Labor       |     | 2     | 150  | 300    |
+| Paint Labor      |     | 1.5   | 150  | 225    |
+| Mechanical Labor |     | -     | -    | -      |
+Supplies
+|               | Paint Supplies           |     |        | 60        |
+| ------------- | ------------------------ | --- | ------ | --------- |
+|               | Body Supplies            |     |        | 30        |
+| Other Charges |                          |     |        | 15        |
+| Subtotal      |                          |     |        | 100,629   |
+| Sales Tax     |                          |     | 10.20% | 10264.158 |
+| GRAND TOTAL   |                          |     |        | 211,522   |
+| Note          | Minor rear bumper repair |     |        |           |
+
+This is a preliminary estimate for the visible damage of the vehicle. Additional damage / repairs / parts may be found
+after the vehicle has been disassembled and damaged parts have been removed. Suspension damages may be
+present, but can not be determined until an alignment on the vehicle has been done. Parts Prices may vary due to
+models and vehicle maker price updates. Please be advised if vehicle owner elects to have vehicle sent to service for
+any mechanical concerns, ALL service departments charge a vehicle diagnostic charge. If the mechanical concern is
+deemed not related to an insurance claim, vehicle owner will be reponsible for charges.
@@ -0,0 +1,44 @@
+INVENTORY RECONCILIATION REPORT
+Report ID: SPARSE-2024-INV-1234
+Warehouse: Distribution Center East
+Report Date: 2024-11-15
+Prepared By: Sarah Martinez
+| Product Code | Location | Expected | Actual | Variance | Status   |
+| ------------ | -------- | -------- | ------ | -------- | -------- |
+| SKU-8847     | A-12     | 450      |        |          |          |
+|              | B-07     |          | 289    | -23      |          |
+| SKU-9201     |          | 780      | 778    |          | OK       |
+|              | C-15     |          |        | +15      |          |
+| SKU-4563     | D-22     |          | 156    |          | CRITICAL |
+|              |          | 180      |        | -24      |          |
+| SKU-7728     | A-08     | 920      |        |          |          |
+|              |          |          | 935    | +15      | OK       |
+Variance Analysis:
+Summary Statistics:
+Total Variance Cost: $4,287.50
+Critical Items: 1
+Overall Accuracy: 97.2%
+Detailed Analysis by Category:
+The inventory reconciliation reveals several key findings. The primary variance driver is SKU-4563,
+which shows a -24 unit discrepancy requiring immediate investigation. Location B-07 handling of
+SKU-8847 also demonstrates significant variance. Cross-location verification protocols should be
+
+reviewed to prevent future discrepancies. The overall accuracy rate of 97.2% meets our target
+threshold, but critical items require expedited resolution to maintain operational efficiency.
+Extended Inventory Review:
+| Product Code | Category    | Unit Cost | Total Value | Last Audit | Notes      |
+| ------------ | ----------- | --------- | ----------- | ---------- | ---------- |
+| SKU-8847     | Electronics | $45.00    | $13,005.00  | 2024-10-15 |            |
+| SKU-9201     | Hardware    | $32.50    | $25,285.00  | 2024-10-22 | Verified   |
+| SKU-4563     | Software    | $120.00   | $18,720.00  |            | Critical   |
+| SKU-7728     | Accessories | $15.75    | $14,726.25  | 2024-11-01 |            |
+| SKU-3345     | Electronics | $67.00    | $22,445.00  | 2024-10-18 |            |
+| SKU-5512     | Hardware    | $89.00    | $31,150.00  |            | Pending    |
+| SKU-6678     | Software    | $200.00   | $42,000.00  | 2024-10-25 | High Value |
+| SKU-7789     | Accessories | $8.50     | $5,950.00   | 2024-11-05 |            |
+| SKU-2234     | Electronics | $125.00   | $35,000.00  |            |            |
+| SKU-1123     | Hardware    | $55.00    | $27,500.00  | 2024-10-30 | Verified   |
+Recommendations:
+1. Immediate review of SKU-4563 handling procedures. 2. Implement additional verification for critical
+items. 3. Schedule follow-up audit for high-value products (SKU-6678, SKU-2234).
+Approval:
@@ -0,0 +1,62 @@
+BOOKING ORDER
+Print Date 12/15/2024 14:30:22
+Page 1 of 1
+STARLIGHT CINEMAS
+Orders
+| Order / Rev: | 2024-12-5678   |     |     | Cinema:          |     | Downtown Multiplex |
+| ------------ | -------------- | --- | --- | ---------------- | --- | ------------------ |
+| Alt Order #: | SC-WINTER-2024 |     |     | Primary Contact: |     | Sarah Johnson      |
+Product Desc: Holiday Movie Marathon Package Location: NYC-01
+| Estimate:            | EST-456                 |     |     | Region: |     | NORTHEAST |
+| -------------------- | ----------------------- | --- | --- | ------- | --- | --------- |
+| Booking Dates:       | 12/20/2024 - 12/31/2024 |     |     |         |     |           |
+| Original Date / Rev: | 12/01/24 / 12/10/24     |     |     |         |     |           |
+| Order Type:          | Premium Package         |     |     |         |     |           |
+Booking Agency
+| Name:            | Premier Entertainment Group |     |     |                |     |           |
+| ---------------- | --------------------------- | --- | --- | -------------- | --- | --------- |
+|                  |                             |     |     | Billing Type:  |     | Net 30    |
+| Contact:         | Michael Chen                |     |     |                |     |           |
+|                  |                             |     |     | Payment Terms: |     | Corporate |
+| Billing Contact: | accounting@premierent.com   |     |     |                |     |           |
+|                  |                             |     |     | Commission:    |     | 10%       |
+555 Broadway Suite 1200
+New York, NY 10012
+Customer
+| Name:          | Universal Studios Distribution |     |     |     |     |     |
+| -------------- | ------------------------------ | --- | --- | --- | --- | --- |
+| Category:      | Film Distributor               |     |     |     |     |     |
+| Contact Email: | bookings@universalstudios.com  |     |     |     |     |     |
+| Customer ID:   | CUST-98765                     |     |     |     |     |     |
+| Revenue Code:  | FILM-PREMIUM                   |     |     |     |     |     |
+Booking Summary
+| Start Date | End Date | # Shows | Gross Amount | Net Amount |     |     |
+| ---------- | -------- | ------- | ------------ | ---------- | --- | --- |
+| 12/20/24   | 12/31/24 | 48      | $12,500.00   | $11,250.00 |     |     |
+Totals
+| Month         | # Shows | Gross Amount |     | Net Amount |     | Occupancy |
+| ------------- | ------- | ------------ | --- | ---------- | --- | --------- |
+| December 2024 | 48      | $12,500.00   |     | $11,250.00 |     | 85%       |
+| Totals        | 48      | $12,500.00   |     | $11,250.00 |     | 85%       |
+Account Representatives
+Representative Territory Region Start Date / End Date Commission %
+| Sarah Johnson | NYC Metro | NORTHEAST | 12/20/24 - 12/31/24 |     | 100% |     |
+| ------------- | --------- | --------- | ------------------- | --- | ---- | --- |
+Show Schedule Details
+Ln Screen Start End Movie Title Format Showtime Days Shows Rate Type Total
+1 SCR-1 12/20/24 12/25/24 Holiday Spectacular IMAX 3D 7:00 PM Daily 12 $250 PM $3,000
+(Runtime: 142 min); Holiday Season Premium
+2 SCR-2 12/20/24 12/31/24 Winter Wonderland Standard 4:30 PM Daily 24 $150 MT $3,600
+(Runtime: 98 min); Matinee Special
+3 SCR-1 12/26/24 12/31/24 New Year Mystery 4DX 9:30 PM Daily 12 $300 PM $3,600
+(Runtime: 116 min); Premium Experience
+Show Details
+| Show Screen | Date Range | Title | Showtime | Days Type | Rate | Revenue |
+| ----------- | ---------- | ----- | -------- | --------- | ---- | ------- |
+1 SCR-1 12/20-12/25 Holiday Spectacular 7:00 PM Daily PM $250 $3,000
+This booking order is subject to cinema availability and standard terms.
+2 SCR-2 12/20-12/31 Winter Wonderland 4:30 PM Daily MT $150 $3,600
+All showtimes are approximate and subject to change.
+3 SCR-1 12/26-12/31 New Year Mystery 9:30 PM Daily PM $300 $3,600
+| Total Revenue: |     |     |     |     |     | $12,500.00 |
+| -------------- | --- | --- | --- | --- | --- | ---------- |
@@ -0,0 +1,65 @@
+1
+
+Introduction
+
+Large language models (LLMs) are becoming a crucial building block in developing powerful agents
+that utilize LLMs for reasoning, tool usage, and adapting to new observations (Yao et al., 2022; Xi
+et al., 2023; Wang et al., 2023b) in many real-world tasks. Given the expanding tasks that could
+benefit from LLMs and the growing task complexity, an intuitive approach to scale up the power of
+agents is to use multiple agents that cooperate. Prior work suggests that multiple agents can help
+encourage divergent thinking (Liang et al., 2023), improve factuality and reasoning (Du et al., 2023),
+and provide validation (Wu et al., 2023). In light of the intuition and early evidence of promise, it is
+intriguing to ask the following question: how can we facilitate the development of LLM applications
+that could span a broad spectrum of domains and complexities based on the multi-agent approach?
+
+Our insight is to use multi-agent conversations to achieve it. There are at least three reasons con-
+firming its general feasibility and utility thanks to recent advances in LLMs: First, because chat-
+optimized LLMs (e.g., GPT-4) show the ability to incorporate feedback, LLM agents can cooperate
+through conversations with each other or human(s), e.g., a dialog where agents provide and seek rea-
+soning, observations, critiques, and validation. Second, because a single LLM can exhibit a broad
+range of capabilities (especially when configured with the correct prompt and inference settings),
+conversations between differently configured agents can help combine these broad LLM capabilities
+in a modular and complementary manner. Third, LLMs have demonstrated ability to solve complex
+tasks when the tasks are broken into simpler subtasks. Multi-agent conversations can enable this
+partitioning and integration in an intuitive manner. How can we leverage the above insights and
+support different applications with the common requirement of coordinating multiple agents, poten-
+tially backed by LLMs, humans, or tools exhibiting different capacities? We desire a multi-agent
+conversation framework with generic abstraction and effective implementation that has the flexibil-
+ity to satisfy different application needs. Achieving this requires addressing two critical questions:
+(1) How can we design individual agents that are capable, reusable, customizable, and effective in
+multi-agent collaboration? (2) How can we develop a straightforward, unified interface that can
+accommodate a wide range of agent conversation patterns? In practice, applications of varying
+complexities may need distinct sets of agents with specific capabilities, and may require different
+conversation patterns, such as single- or multi-turn dialogs, different human involvement modes, and
+static vs. dynamic conversation. Moreover, developers may prefer the flexibility to program agent
+interactions in natural language or code. Failing to adequately address these two questions would
+limit the framework’s scope of applicability and generality.
+While there is contemporaneous exploration of multi-agent approaches,3 we present AutoGen, a
+generalized multi-agent conversation framework (Figure 1), based on the following new concepts.
+1 Customizable and conversable agents. AutoGen uses a generic design of agents that can lever-
+age LLMs, human inputs, tools, or a combination of them. The result is that developers can
+easily and quickly create agents with different roles (e.g., agents to write code, execute code,
+wire in human feedback, validate outputs, etc.) by selecting and configuring a subset of built-in
+capabilities. The agent’s backend can also be readily extended to allow more custom behaviors.
+To make these agents suitable for multi-agent conversation, every agent is made conversable –
+they can receive, react, and respond to messages. When configured properly, an agent can hold
+multiple turns of conversations with other agents autonomously or solicit human inputs at cer-
+tain rounds, enabling human agency and automation. The conversable agent design leverages the
+strong capability of the most advanced LLMs in taking feedback and making progress via chat
+and also allows combining capabilities of LLMs in a modular fashion. (Section 2.1)
+
+2 Conversation programming. A fundamental insight of AutoGen is to simplify and unify com-
+plex LLM application workflows as multi-agent conversations. So AutoGen adopts a program-
+ming paradigm centered around these inter-agent conversations. We refer to this paradigm as
+conversation programming, which streamlines the development of intricate applications via two
+primary steps: (1) defining a set of conversable agents with specific capabilities and roles (as
+described above); (2) programming the interaction behavior between agents via conversation-
+centric computation and control. Both steps can be achieved via a fusion of natural and pro-
+gramming languages to build applications with a wide range of conversation patterns and agent
+behaviors. AutoGen provides ready-to-use implementations and also allows easy extension and
+experimentation for both steps. (Section 2.2)
+
+3We refer to Appendix A for a detailed discussion.
+
+2
+
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@@ -288,6 +288,47 @@ def test_input_as_strings() -> None:
    assert "# Test" in result.text_content


+def test_doc_rlink() -> None:
+    # Test for: CVE-2025-11849
+    markitdown = MarkItDown()
+
+    # Document with rlink
+    docx_file = os.path.join(TEST_FILES_DIR, "rlink.docx")
+
+    # Directory containing the target rlink file
+    rlink_tmp_dir = os.path.abspath(os.sep + "tmp")
+
+    # Ensure the tmp directory exists
+    if not os.path.exists(rlink_tmp_dir):
+        pytest.skip(f"Skipping rlink test; {rlink_tmp_dir} directory does not exist.")
+        return
+
+    rlink_file_path = os.path.join(rlink_tmp_dir, "test_rlink.txt")
+    rlink_content = "de658225-569e-4e3d-9ed2-cfb6abf927fc"
+    b64_prefix = (
+        "ZGU2NTgyMjUtNTY5ZS00ZTNkLTllZDItY2ZiNmFiZjk"  # base64 prefix of rlink_content
+    )
+
+    if os.path.exists(rlink_file_path):
+        with open(rlink_file_path, "r", encoding="utf-8") as f:
+            existing_content = f.read()
+            if existing_content != rlink_content:
+                raise ValueError(
+                    f"Existing {rlink_file_path} content does not match expected content."
+                )
+    else:
+        with open(rlink_file_path, "w", encoding="utf-8") as f:
+            f.write(rlink_content)
+
+    try:
+        result = markitdown.convert(docx_file, keep_data_uris=True).text_content
+        assert (
+            b64_prefix not in result
+        )  # Make sure the target file was NOT embedded in the output
+    finally:
+        os.remove(rlink_file_path)
+
+
@pytest.mark.skipif(
    skip_remote,
    reason="do not run tests that query external urls",
@@ -301,9 +342,9 @@ def test_markitdown_remote() -> None:
        assert test_string in result.text_content

    # Youtube
-    result = markitdown.convert(YOUTUBE_TEST_URL)
-    for test_string in YOUTUBE_TEST_STRINGS:
-        assert test_string in result.text_content
+    # result = markitdown.convert(YOUTUBE_TEST_URL)
+    # for test_string in YOUTUBE_TEST_STRINGS:
+    #    assert test_string in result.text_content


@pytest.mark.skipif(
@@ -452,6 +493,7 @@ if __name__ == "__main__":
        test_markitdown_remote,
        test_speech_transcription,
        test_exceptions,
+        test_doc_rlink,
        test_markitdown_exiftool,
        test_markitdown_llm_parameters,
        test_markitdown_llm,
@@ -0,0 +1,171 @@
+#!/usr/bin/env python3 -m pytest
+"""Tests for MasterFormat-style partial numbering in PDF conversion."""
+
+import os
+import re
+import pytest
+
+from markitdown import MarkItDown
+from markitdown.converters._pdf_converter import PARTIAL_NUMBERING_PATTERN
+
+TEST_FILES_DIR = os.path.join(os.path.dirname(__file__), "test_files")
+
+
+class TestMasterFormatPartialNumbering:
+    """Test handling of MasterFormat-style partial numbering (.1, .2, etc.)."""
+
+    def test_partial_numbering_pattern_regex(self):
+        """Test that the partial numbering regex pattern correctly matches."""
+
+        # Should match partial numbering patterns
+        assert PARTIAL_NUMBERING_PATTERN.match(".1") is not None
+        assert PARTIAL_NUMBERING_PATTERN.match(".2") is not None
+        assert PARTIAL_NUMBERING_PATTERN.match(".10") is not None
+        assert PARTIAL_NUMBERING_PATTERN.match(".99") is not None
+
+        # Should NOT match other patterns
+        assert PARTIAL_NUMBERING_PATTERN.match("1.") is None
+        assert PARTIAL_NUMBERING_PATTERN.match("1.2") is None
+        assert PARTIAL_NUMBERING_PATTERN.match(".1.2") is None
+        assert PARTIAL_NUMBERING_PATTERN.match("text") is None
+        assert PARTIAL_NUMBERING_PATTERN.match(".a") is None
+        assert PARTIAL_NUMBERING_PATTERN.match("") is None
+
+    def test_masterformat_partial_numbering_not_split(self):
+        """Test that MasterFormat partial numbering stays with associated text.
+
+        MasterFormat documents use partial numbering like:
+            .1  The intent of this Request for Proposal...
+            .2  Available information relative to...
+
+        These should NOT be split into separate table columns, but kept
+        as coherent text lines with the number followed by its description.
+        """
+        pdf_path = os.path.join(TEST_FILES_DIR, "masterformat_partial_numbering.pdf")
+
+        markitdown = MarkItDown()
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Partial numberings should NOT appear isolated on their own lines
+        # If they're isolated, it means the parser incorrectly split them from their text
+        lines = text_content.split("\n")
+        isolated_numberings = []
+        for line in lines:
+            stripped = line.strip()
+            # Check if line contains ONLY a partial numbering (with possible whitespace/pipes)
+            cleaned = stripped.replace("|", "").strip()
+            if cleaned in [".1", ".2", ".3", ".4", ".5", ".6", ".7", ".8", ".9", ".10"]:
+                isolated_numberings.append(stripped)
+
+        assert len(isolated_numberings) == 0, (
+            f"Partial numberings should not be isolated from their text. "
+            f"Found isolated: {isolated_numberings}"
+        )
+
+        # Verify that partial numberings appear WITH following text on the same line
+        # Look for patterns like ".1 The intent" or ".1  Some text"
+        partial_with_text = re.findall(r"\.\d+\s+\w+", text_content)
+        assert (
+            len(partial_with_text) > 0
+        ), "Expected to find partial numberings followed by text on the same line"
+
+    def test_masterformat_content_preserved(self):
+        """Test that MasterFormat document content is fully preserved."""
+        pdf_path = os.path.join(TEST_FILES_DIR, "masterformat_partial_numbering.pdf")
+
+        markitdown = MarkItDown()
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Verify key content from the MasterFormat document is preserved
+        expected_content = [
+            "RFP for Construction Management Services",
+            "Section 00 00 43",
+            "Instructions to Respondents",
+            "Ken Sargent House",
+            "INTENT",
+            "Request for Proposal",
+            "KEN SARGENT HOUSE",
+            "GRANDE PRAIRIE, ALBERTA",
+            "Section 00 00 45",
+        ]
+
+        for content in expected_content:
+            assert (
+                content in text_content
+            ), f"Expected content '{content}' not found in extracted text"
+
+        # Verify partial numbering is followed by text on the same line
+        # .1 should be followed by "The intent" on the same line
+        assert re.search(
+            r"\.1\s+The intent", text_content
+        ), "Partial numbering .1 should be followed by 'The intent' text"
+
+        # .2 should be followed by "Available information" on the same line
+        assert re.search(
+            r"\.2\s+Available information", text_content
+        ), "Partial numbering .2 should be followed by 'Available information' text"
+
+        # Ensure text content is not empty and has reasonable length
+        assert (
+            len(text_content.strip()) > 100
+        ), "MasterFormat document should have substantial text content"
+
+    def test_merge_partial_numbering_with_empty_lines_between(self):
+        """Test that partial numberings merge correctly even with empty lines between.
+
+        When PDF extractors produce output like:
+            .1
+
+            The intent of this Request...
+
+        The merge logic should still combine them properly.
+        """
+        pdf_path = os.path.join(TEST_FILES_DIR, "masterformat_partial_numbering.pdf")
+
+        markitdown = MarkItDown()
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # The merged result should have .1 and .2 followed by text
+        # Check that we don't have patterns like ".1\n\nThe intent" (unmerged)
+        lines = text_content.split("\n")
+
+        for i, line in enumerate(lines):
+            stripped = line.strip()
+            # If we find an isolated partial numbering, the merge failed
+            if stripped in [".1", ".2", ".3", ".4", ".5", ".6", ".7", ".8"]:
+                # Check if next non-empty line exists and wasn't merged
+                for j in range(i + 1, min(i + 3, len(lines))):
+                    if lines[j].strip():
+                        pytest.fail(
+                            f"Partial numbering '{stripped}' on line {i} was not "
+                            f"merged with following text '{lines[j].strip()[:30]}...'"
+                        )
+                        break
+
+    def test_multiple_partial_numberings_all_merged(self):
+        """Test that all partial numberings in a document are properly merged."""
+        pdf_path = os.path.join(TEST_FILES_DIR, "masterformat_partial_numbering.pdf")
+
+        markitdown = MarkItDown()
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Count occurrences of merged partial numberings (number followed by text)
+        merged_count = len(re.findall(r"\.\d+\s+[A-Za-z]", text_content))
+
+        # Count isolated partial numberings (number alone on a line)
+        isolated_count = 0
+        for line in text_content.split("\n"):
+            stripped = line.strip()
+            if re.match(r"^\.\d+$", stripped):
+                isolated_count += 1
+
+        assert (
+            merged_count >= 2
+        ), f"Expected at least 2 merged partial numberings, found {merged_count}"
+        assert (
+            isolated_count == 0
+        ), f"Found {isolated_count} isolated partial numberings that weren't merged"
Author	SHA1	Message	Date
afourney	4a5340f93b	Bump version for release. (#1564 )	2026-02-20 11:40:57 -08:00
Bas Nijholt	6b0fd15e60	Remove onnxruntime<=1.20.1 Windows pin (#1551 )	2026-02-16 15:05:37 -08:00
afourney	2b6ec9f315	Add text/markdown to Accept header (#1554 )	2026-02-13 11:53:01 -08:00
lesyk	c83de14a9c	[MS] Extend table support for wide tables (#1552 ) * feat: enhance PDF table extraction to support complex forms and add new test cases * feat: enhance PDF table extraction with adaptive column clustering and add comprehensive test cases * fix: correct formatting and improve assertions in PDF table tests	2026-02-13 10:45:39 -08:00
lesyk	7fdaefb724	Fix: PDF parsing doesn't support partially numbered lists (#1525 ) * Fix: PDF parsing doesn't support partially numbered lists * Refactor: Move import of PARTIAL_NUMBERING_PATTERN to the top of the test file * Refactor: Improve assertion formatting in partial numbering tests	2026-01-08 15:15:22 -08:00
lesyk	251dddcf0c	[MS] Update PDF table extraction to support aligned Markdown (#1499 ) * Added PDF table extraction feature with aligned Markdown (#1419) * Add PDF test files and enhance extraction tests - Added a medical report scan PDF for testing scanned PDF handling. - Included a retail purchase receipt PDF to validate receipt extraction functionality. - Introduced a multipage invoice PDF to test extraction of complex invoice structures. - Added a borderless table PDF for testing inventory reconciliation report extraction. - Implemented comprehensive tests for PDF table extraction, ensuring proper structure and data integrity. - Enhanced existing tests to validate the order and presence of extracted content across various PDF types. * fix: update dependencies for PDF processing and improve table extraction logic * Bumped version of pdfminer.six --------- Authored-by: Ashok <ashh010101@gmail.com>	2026-01-07 16:38:45 -08:00
afourney	dde250a456	Bump versions of mammoth and pdfminer.six (#1492 ) * Updated pyproject to require a minimum version of pdfminer.six to ensure CVE-2025-64512 is patched.	2025-12-01 10:11:24 -08:00
afourney	3d4fe3cdcc	Upgrade mammoth to 1.11.0 (#1452 )	2025-10-20 16:07:39 -07:00
afourney	447c047731	Test if mammoth resolves rlinks. (#1451 )	2025-10-20 15:54:05 -07:00