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

.github/workflows/pre-commit.yml

@@ -5,7 +5,7 @@ jobs:
   pre-commit:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - name: Set up Python
         uses: actions/setup-python@v5
         with:

.github/workflows/tests.yml

@@ -5,7 +5,7 @@ jobs:
   tests:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - uses: actions/setup-python@v5
         with:
           python-version: |

.gitignore

@@ -52,6 +52,7 @@ coverage.xml
 .hypothesis/
 .pytest_cache/
 cover/
+.test-logs/
 
 # Translations
 *.mo

README.md

@@ -15,7 +15,7 @@
 
 MarkItDown is a lightweight Python utility for converting various files to Markdown for use with LLMs and related text analysis pipelines. To this end, it is most comparable to [textract](https://github.com/deanmalmgren/textract), but with a focus on preserving important document structure and content as Markdown (including: headings, lists, tables, links, etc.) While the output is often reasonably presentable and human-friendly, it is meant to be consumed by text analysis tools -- and may not be the best option for high-fidelity document conversions for human consumption.
 
-At present, MarkItDown supports:
+MarkItDown currently supports the conversion from:
 
 - PDF
 - PowerPoint
@@ -164,14 +164,14 @@ result = md.convert("test.pdf")
 print(result.text_content)
 ```
 
-To use Large Language Models for image descriptions, provide `llm_client` and `llm_model`:
+To use Large Language Models for image descriptions (currently only for pptx and image files), provide `llm_client` and `llm_model`:
 
 ```python
 from markitdown import MarkItDown
 from openai import OpenAI
 
 client = OpenAI()
-md = MarkItDown(llm_client=client, llm_model="gpt-4o")
+md = MarkItDown(llm_client=client, llm_model="gpt-4o", llm_prompt="optional custom prompt")
 result = md.convert("example.jpg")
 print(result.text_content)
 ```
@@ -199,7 +199,7 @@ contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additio
 
 ### How to Contribute
 
-You can help by looking at issues or helping review PRs. Any issue or PR is welcome, but we have also marked some as 'open for contribution' and 'open for reviewing' to help facilitate community contributions. These are ofcourse just suggestions and you are welcome to contribute in any way you like.
+You can help by looking at issues or helping review PRs. Any issue or PR is welcome, but we have also marked some as 'open for contribution' and 'open for reviewing' to help facilitate community contributions. These are of course just suggestions and you are welcome to contribute in any way you like.
 
 <div align="center">
 

packages/markitdown-mcp/Dockerfile

@@ -3,8 +3,10 @@ FROM python:3.13-slim-bullseye
 ENV DEBIAN_FRONTEND=noninteractive
 ENV EXIFTOOL_PATH=/usr/bin/exiftool
 ENV FFMPEG_PATH=/usr/bin/ffmpeg
+ENV MARKITDOWN_ENABLE_PLUGINS=True
 
 # Runtime dependency
+# NOTE: Add any additional MarkItDown plugins here
 RUN apt-get update && apt-get install -y --no-install-recommends \
     ffmpeg \
     exiftool

packages/markitdown-mcp/README.md

@@ -54,7 +54,7 @@ Once mounted, all files under data will be accessible under `/workdir` in the co
 
 It is recommended to use the Docker image when running the MCP server for Claude Desktop.
 
-Follow [these instrutions](https://modelcontextprotocol.io/quickstart/user#for-claude-desktop-users) to access Claude's `claude_desktop_config.json` file.
+Follow [these instructions](https://modelcontextprotocol.io/quickstart/user#for-claude-desktop-users) to access Claude's `claude_desktop_config.json` file.
 
 Edit it to include the following JSON entry:
 
@@ -102,7 +102,7 @@ To debug the MCP server you can use the `mcpinspector` tool.
 npx @modelcontextprotocol/inspector
 ```
 
-You can then connect to the insepctor through the specified host and port (e.g., `http://localhost:5173/`).
+You can then connect to the inspector through the specified host and port (e.g., `http://localhost:5173/`).
 
 If using STDIO:
 * select `STDIO` as the transport type,
@@ -127,8 +127,7 @@ Finally:
 
 ## Security Considerations
 
-The server does not support authentication, and runs with the privileges if the user running it. For this reason, when running in SSE or Streamable HTTP mode, it is recommended to run the server bound to `localhost` (default).
-
+The server does not support authentication, and runs with the privileges of the user running it. For this reason, when running in SSE or Streamable HTTP mode, it is recommended to run the server bound to `localhost` (default).
 
 ## Trademarks
 

packages/markitdown-mcp/src/markitdown_mcp/__main__.py

@@ -1,5 +1,6 @@
 import contextlib
 import sys
+import os
 from collections.abc import AsyncIterator
 from mcp.server.fastmcp import FastMCP
 from starlette.applications import Starlette
@@ -19,7 +20,15 @@ mcp = FastMCP("markitdown")
 @mcp.tool()
 async def convert_to_markdown(uri: str) -> str:
     """Convert a resource described by an http:, https:, file: or data: URI to markdown"""
-    return MarkItDown().convert_uri(uri).markdown
+    return MarkItDown(enable_plugins=check_plugins_enabled()).convert_uri(uri).markdown
+
+
+def check_plugins_enabled() -> bool:
+    return os.getenv("MARKITDOWN_ENABLE_PLUGINS", "false").strip().lower() in (
+        "true",
+        "1",
+        "yes",
+    )
 
 
 def create_starlette_app(mcp_server: Server, *, debug: bool = False) -> Starlette:

packages/markitdown/pyproject.toml

@@ -30,29 +30,31 @@ dependencies = [
   "magika~=0.6.1",
   "charset-normalizer",
   "defusedxml",
+  "onnxruntime<=1.20.1; sys_platform == 'win32'",
 ]
 
 [project.optional-dependencies]
 all = [
   "python-pptx",
-  "mammoth",
+  "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"]

packages/markitdown/src/markitdown/__about__.py

@@ -1,4 +1,4 @@
 # SPDX-FileCopyrightText: 2024-present Adam Fourney <adamfo@microsoft.com>
 #
 # SPDX-License-Identifier: MIT
-__version__ = "0.1.2"
+__version__ = "0.1.5b1"

packages/markitdown/src/markitdown/_base_converter.py

@@ -69,7 +69,7 @@ class DocumentConverter:
         data = file_stream.read(100) # ... peek at the first 100 bytes, etc.
         file_stream.seek(cur_pos)    # Reset the position to the original position
 
-        Prameters:
+        Parameters:
         - file_stream: The file-like object to convert. Must support seek(), tell(), and read() methods.
         - stream_info: The StreamInfo object containing metadata about the file (mimetype, extension, charset, set)
         - kwargs: Additional keyword arguments for the converter.
@@ -90,7 +90,7 @@ class DocumentConverter:
         """
         Convert a document to Markdown text.
 
-        Prameters:
+        Parameters:
         - file_stream: The file-like object to convert. Must support seek(), tell(), and read() methods.
         - stream_info: The StreamInfo object containing metadata about the file (mimetype, extension, charset, set)
         - kwargs: Additional keyword arguments for the converter.

packages/markitdown/src/markitdown/_markitdown.py

@@ -115,6 +115,7 @@ class MarkItDown:
         # TODO - remove these (see enable_builtins)
         self._llm_client: Any = None
         self._llm_model: Union[str | None] = None
+        self._llm_prompt: Union[str | None] = None
         self._exiftool_path: Union[str | None] = None
         self._style_map: Union[str | None] = None
 
@@ -139,6 +140,7 @@ class MarkItDown:
             # TODO: Move these into converter constructors
             self._llm_client = kwargs.get("llm_client")
             self._llm_model = kwargs.get("llm_model")
+            self._llm_prompt = kwargs.get("llm_prompt")
             self._exiftool_path = kwargs.get("exiftool_path")
             self._style_map = kwargs.get("style_map")
 
@@ -559,6 +561,9 @@ class MarkItDown:
                 if "llm_model" not in _kwargs and self._llm_model is not None:
                     _kwargs["llm_model"] = self._llm_model
 
+                if "llm_prompt" not in _kwargs and self._llm_prompt is not None:
+                    _kwargs["llm_prompt"] = self._llm_prompt
+
                 if "style_map" not in _kwargs and self._style_map is not None:
                     _kwargs["style_map"] = self._style_map
 

packages/markitdown/src/markitdown/converters/_doc_intel_converter.py

@@ -84,6 +84,9 @@ def _get_mime_type_prefixes(types: List[DocumentIntelligenceFileType]) -> List[s
             prefixes.append(
                 "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
             )
+        elif type_ == DocumentIntelligenceFileType.HTML:
+            prefixes.append("text/html")
+            prefixes.append("application/xhtml+xml")
         elif type_ == DocumentIntelligenceFileType.PDF:
             prefixes.append("application/pdf")
             prefixes.append("application/x-pdf")
@@ -119,6 +122,8 @@ def _get_file_extensions(types: List[DocumentIntelligenceFileType]) -> List[str]
             extensions.append(".bmp")
         elif type_ == DocumentIntelligenceFileType.TIFF:
             extensions.append(".tiff")
+        elif type_ == DocumentIntelligenceFileType.HTML:
+            extensions.append(".html")
     return extensions
 
 

packages/markitdown/src/markitdown/converters/_docx_converter.py

@@ -1,4 +1,6 @@
 import sys
+import io
+from warnings import warn
 
 from typing import BinaryIO, Any
 
@@ -13,6 +15,7 @@ from .._exceptions import MissingDependencyException, MISSING_DEPENDENCY_MESSAGE
 _dependency_exc_info = None
 try:
     import mammoth
+
 except ImportError:
     # Preserve the error and stack trace for later
     _dependency_exc_info = sys.exc_info()

packages/markitdown/src/markitdown/converters/_exiftool.py

@@ -1,7 +1,11 @@
 import json
-import subprocess
 import locale
-from typing import BinaryIO, Any, Union
+import subprocess
+from typing import Any, BinaryIO, Union
+
+
+def _parse_version(version: str) -> tuple:
+    return tuple(map(int, (version.split("."))))
 
 
 def exiftool_metadata(
@@ -13,6 +17,24 @@ def exiftool_metadata(
     if not exiftool_path:
         return {}
 
+    # Verify exiftool version
+    try:
+        version_output = subprocess.run(
+            [exiftool_path, "-ver"],
+            capture_output=True,
+            text=True,
+            check=True,
+        ).stdout.strip()
+        version = _parse_version(version_output)
+        min_version = (12, 24)
+        if version < min_version:
+            raise RuntimeError(
+                f"ExifTool version {version_output} is vulnerable to CVE-2021-22204. "
+                "Please upgrade to version 12.24 or later."
+            )
+    except (subprocess.CalledProcessError, ValueError) as e:
+        raise RuntimeError("Failed to verify ExifTool version.") from e
+
     # Run exiftool
     cur_pos = file_stream.tell()
     try:

packages/markitdown/src/markitdown/converters/_markdownify.py

@@ -92,9 +92,11 @@ class _CustomMarkdownify(markdownify.MarkdownConverter):
         """Same as usual converter, but removes data URIs"""
 
         alt = el.attrs.get("alt", None) or ""
-        src = el.attrs.get("src", None) or ""
+        src = el.attrs.get("src", None) or el.attrs.get("data-src", None) or ""
         title = el.attrs.get("title", None) or ""
         title_part = ' "%s"' % title.replace('"', r"\"") if title else ""
+        # Remove all line breaks from alt
+        alt = alt.replace("\n", " ")
         if (
             convert_as_inline
             and el.parent.name not in self.options["keep_inline_images_in"]
@@ -107,5 +109,18 @@ class _CustomMarkdownify(markdownify.MarkdownConverter):
 
         return "![%s](%s%s)" % (alt, src, title_part)
 
+    def convert_input(
+        self,
+        el: Any,
+        text: str,
+        convert_as_inline: Optional[bool] = False,
+        **kwargs,
+    ) -> str:
+        """Convert checkboxes to Markdown [x]/[ ] syntax."""
+
+        if el.get("type") == "checkbox":
+            return "[x] " if el.has_attr("checked") else "[ ] "
+        return ""
+
     def convert_soup(self, soup: Any) -> str:
         return super().convert_soup(soup)  # type: ignore

packages/markitdown/src/markitdown/converters/_pdf_converter.py

@@ -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 +75,388 @@ 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 global column boundaries
+    all_table_x_positions.sort()
+    global_columns: list[float] = []
+    for x in all_table_x_positions:
+        if not global_columns or x - global_columns[-1] > 30:
+            global_columns.append(x)
+
+    # Too many columns suggests dense text, not a form
+    if len(global_columns) > 8:
+        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 +474,8 @@ 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 +483,58 @@ 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)

packages/markitdown/src/markitdown/converters/_pptx_converter.py

@@ -168,11 +168,23 @@ class PptxConverter(DocumentConverter):
 
                 # Group Shapes
                 if shape.shape_type == pptx.enum.shapes.MSO_SHAPE_TYPE.GROUP:
-                    sorted_shapes = sorted(shape.shapes, key=attrgetter("top", "left"))
+                    sorted_shapes = sorted(
+                        shape.shapes,
+                        key=lambda x: (
+                            float("-inf") if not x.top else x.top,
+                            float("-inf") if not x.left else x.left,
+                        ),
+                    )
                     for subshape in sorted_shapes:
                         get_shape_content(subshape, **kwargs)
 
-            sorted_shapes = sorted(slide.shapes, key=attrgetter("top", "left"))
+            sorted_shapes = sorted(
+                slide.shapes,
+                key=lambda x: (
+                    float("-inf") if not x.top else x.top,
+                    float("-inf") if not x.left else x.left,
+                ),
+            )
             for shape in sorted_shapes:
                 get_shape_content(shape, **kwargs)
 

packages/markitdown/tests/test_docintel_html.py

@@ -0,0 +1,26 @@
+import io
+from markitdown.converters._doc_intel_converter import (
+    DocumentIntelligenceConverter,
+    DocumentIntelligenceFileType,
+)
+from markitdown._stream_info import StreamInfo
+
+
+def _make_converter(file_types):
+    conv = DocumentIntelligenceConverter.__new__(DocumentIntelligenceConverter)
+    conv._file_types = file_types
+    return conv
+
+
+def test_docintel_accepts_html_extension():
+    conv = _make_converter([DocumentIntelligenceFileType.HTML])
+    stream_info = StreamInfo(mimetype=None, extension=".html")
+    assert conv.accepts(io.BytesIO(b""), stream_info)
+
+
+def test_docintel_accepts_html_mimetype():
+    conv = _make_converter([DocumentIntelligenceFileType.HTML])
+    stream_info = StreamInfo(mimetype="text/html", extension=None)
+    assert conv.accepts(io.BytesIO(b""), stream_info)
+    stream_info = StreamInfo(mimetype="application/xhtml+xml", extension=None)
+    assert conv.accepts(io.BytesIO(b""), stream_info)

packages/markitdown/tests/test_files/RECEIPT-2024-TXN-98765_retail_purchase.pdf

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packages/markitdown/tests/test_files/masterformat_partial_numbering.pdf

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packages/markitdown/tests/test_module_misc.py

@@ -4,6 +4,7 @@ import os
 import re
 import shutil
 import pytest
+from unittest.mock import MagicMock
 
 from markitdown._uri_utils import parse_data_uri, file_uri_to_path
 
@@ -287,6 +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",
@@ -300,9 +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(
@@ -370,6 +412,50 @@ def test_markitdown_exiftool() -> None:
         assert target in result.text_content
 
 
+def test_markitdown_llm_parameters() -> None:
+    """Test that LLM parameters are correctly passed to the client."""
+    mock_client = MagicMock()
+    mock_response = MagicMock()
+    mock_response.choices = [
+        MagicMock(
+            message=MagicMock(
+                content="Test caption with red circle and blue square 5bda1dd6"
+            )
+        )
+    ]
+    mock_client.chat.completions.create.return_value = mock_response
+
+    test_prompt = "You are a professional test prompt."
+    markitdown = MarkItDown(
+        llm_client=mock_client, llm_model="gpt-4o", llm_prompt=test_prompt
+    )
+
+    # Test image file
+    markitdown.convert(os.path.join(TEST_FILES_DIR, "test_llm.jpg"))
+
+    # Verify the prompt was passed to the OpenAI API
+    assert mock_client.chat.completions.create.called
+    call_args = mock_client.chat.completions.create.call_args
+    messages = call_args[1]["messages"]
+    assert len(messages) == 1
+    assert messages[0]["content"][0]["text"] == test_prompt
+
+    # Reset the mock for the next test
+    mock_client.chat.completions.create.reset_mock()
+
+    # TODO: may only use one test after the llm caption method duplicate has been removed:
+    # https://github.com/microsoft/markitdown/pull/1254
+    # Test PPTX file
+    markitdown.convert(os.path.join(TEST_FILES_DIR, "test.pptx"))
+
+    # Verify the prompt was passed to the OpenAI API for PPTX images too
+    assert mock_client.chat.completions.create.called
+    call_args = mock_client.chat.completions.create.call_args
+    messages = call_args[1]["messages"]
+    assert len(messages) == 1
+    assert messages[0]["content"][0]["text"] == test_prompt
+
+
 @pytest.mark.skipif(
     skip_llm,
     reason="do not run llm tests without a key",
@@ -407,7 +493,9 @@ if __name__ == "__main__":
         test_markitdown_remote,
         test_speech_transcription,
         test_exceptions,
+        test_doc_rlink,
         test_markitdown_exiftool,
+        test_markitdown_llm_parameters,
         test_markitdown_llm,
     ]:
         print(f"Running {test.__name__}...", end="")

packages/markitdown/tests/test_pdf_masterformat.py

@@ -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"

packages/markitdown/tests/test_pdf_tables.py

@@ -0,0 +1,871 @@
+#!/usr/bin/env python3 -m pytest
+"""Tests for PDF table extraction functionality."""
+import os
+import re
+import pytest
+
+from markitdown import MarkItDown
+
+TEST_FILES_DIR = os.path.join(os.path.dirname(__file__), "test_files")
+
+
+# --- Helper Functions ---
+def validate_strings(result, expected_strings, exclude_strings=None):
+    """Validate presence or absence of specific strings."""
+    text_content = result.text_content.replace("\\", "")
+    for string in expected_strings:
+        assert string in text_content, f"Expected string not found: {string}"
+    if exclude_strings:
+        for string in exclude_strings:
+            assert string not in text_content, f"Excluded string found: {string}"
+
+
+def validate_markdown_table(result, expected_headers, expected_data_samples):
+    """Validate that a markdown table exists with expected headers and data."""
+    text_content = result.text_content
+
+    # Check for markdown table structure (| header | header |)
+    assert "|" in text_content, "No markdown table markers found"
+
+    # Check headers are present
+    for header in expected_headers:
+        assert header in text_content, f"Expected table header not found: {header}"
+
+    # Check some data values are present
+    for data in expected_data_samples:
+        assert data in text_content, f"Expected table data not found: {data}"
+
+
+def extract_markdown_tables(text_content):
+    """
+    Extract all markdown tables from text content.
+    Returns a list of tables, where each table is a list of rows,
+    and each row is a list of cell values.
+    """
+    tables = []
+    lines = text_content.split("\n")
+    current_table = []
+    in_table = False
+
+    for line in lines:
+        line = line.strip()
+        if line.startswith("|") and line.endswith("|"):
+            # Skip separator rows (contain only dashes and pipes)
+            if re.match(r"^\|[\s\-|]+\|$", line):
+                continue
+            # Parse cells from the row
+            cells = [cell.strip() for cell in line.split("|")[1:-1]]
+            current_table.append(cells)
+            in_table = True
+        else:
+            if in_table and current_table:
+                tables.append(current_table)
+                current_table = []
+            in_table = False
+
+    # Don't forget the last table
+    if current_table:
+        tables.append(current_table)
+
+    return tables
+
+
+def validate_table_structure(table):
+    """
+    Validate that a table has consistent structure:
+    - All rows have the same number of columns
+    - Has at least a header row and one data row
+    """
+    if not table:
+        return False, "Table is empty"
+
+    if len(table) < 2:
+        return False, "Table should have at least header and one data row"
+
+    num_cols = len(table[0])
+    if num_cols < 2:
+        return False, f"Table should have at least 2 columns, found {num_cols}"
+
+    for i, row in enumerate(table):
+        if len(row) != num_cols:
+            return False, f"Row {i} has {len(row)} columns, expected {num_cols}"
+
+    return True, "Table structure is valid"
+
+
+class TestPdfTableExtraction:
+    """Test PDF table extraction with various PDF types."""
+
+    @pytest.fixture
+    def markitdown(self):
+        """Create MarkItDown instance."""
+        return MarkItDown()
+
+    def test_borderless_table_extraction(self, markitdown):
+        """Test extraction of borderless tables from SPARSE inventory PDF.
+
+        Expected output structure:
+        - Header: INVENTORY RECONCILIATION REPORT with Report ID, Warehouse, Date, Prepared By
+        - Pipe-separated rows with inventory data
+        - Text section: Variance Analysis with Summary Statistics
+        - More pipe-separated rows with extended inventory review
+        - Footer: Recommendations section
+        """
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "SPARSE-2024-INV-1234_borderless_table.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Validate document header content
+        expected_strings = [
+            "INVENTORY RECONCILIATION REPORT",
+            "Report ID: SPARSE-2024-INV-1234",
+            "Warehouse: Distribution Center East",
+            "Report Date: 2024-11-15",
+            "Prepared By: Sarah Martinez",
+        ]
+        validate_strings(result, expected_strings)
+
+        # Validate pipe-separated format is used
+        assert "|" in text_content, "Should have pipe separators for form-style data"
+
+        # --- Validate First Table Data (Inventory Variance) ---
+        # Validate table headers are present
+        first_table_headers = [
+            "Product Code",
+            "Location",
+            "Expected",
+            "Actual",
+            "Variance",
+            "Status",
+        ]
+        for header in first_table_headers:
+            assert header in text_content, f"Should contain header '{header}'"
+
+        # Validate first table has all expected SKUs
+        first_table_skus = ["SKU-8847", "SKU-9201", "SKU-4563", "SKU-7728"]
+        for sku in first_table_skus:
+            assert sku in text_content, f"Should contain {sku}"
+
+        # Validate first table has correct status values
+        expected_statuses = ["OK", "CRITICAL"]
+        for status in expected_statuses:
+            assert status in text_content, f"Should contain status '{status}'"
+
+        # Validate first table has location codes
+        expected_locations = ["A-12", "B-07", "C-15", "D-22", "A-08"]
+        for loc in expected_locations:
+            assert loc in text_content, f"Should contain location '{loc}'"
+
+        # --- Validate Second Table Data (Extended Inventory Review) ---
+        # Validate second table headers
+        second_table_headers = [
+            "Category",
+            "Unit Cost",
+            "Total Value",
+            "Last Audit",
+            "Notes",
+        ]
+        for header in second_table_headers:
+            assert header in text_content, f"Should contain header '{header}'"
+
+        # Validate second table has all expected SKUs (10 products)
+        second_table_skus = [
+            "SKU-8847",
+            "SKU-9201",
+            "SKU-4563",
+            "SKU-7728",
+            "SKU-3345",
+            "SKU-5512",
+            "SKU-6678",
+            "SKU-7789",
+            "SKU-2234",
+            "SKU-1123",
+        ]
+        for sku in second_table_skus:
+            assert sku in text_content, f"Should contain {sku}"
+
+        # Validate second table has categories
+        expected_categories = ["Electronics", "Hardware", "Software", "Accessories"]
+        for category in expected_categories:
+            assert category in text_content, f"Should contain category '{category}'"
+
+        # Validate second table has cost values (spot check)
+        expected_costs = ["$45.00", "$32.50", "$120.00", "$15.75"]
+        for cost in expected_costs:
+            assert cost in text_content, f"Should contain cost '{cost}'"
+
+        # Validate second table has note values
+        expected_notes = ["Verified", "Critical", "Pending"]
+        for note in expected_notes:
+            assert note in text_content, f"Should contain note '{note}'"
+
+        # --- Validate Analysis Text Section ---
+        analysis_strings = [
+            "Variance Analysis:",
+            "Summary Statistics:",
+            "Total Variance Cost: $4,287.50",
+            "Critical Items: 1",
+            "Overall Accuracy: 97.2%",
+            "Recommendations:",
+        ]
+        validate_strings(result, analysis_strings)
+
+        # --- Validate Document Structure Order ---
+        # Verify sections appear in correct order
+        # Note: Using flexible patterns since column merging may occur based on gap detection
+        import re
+
+        header_pos = text_content.find("INVENTORY RECONCILIATION REPORT")
+        # Look for Product Code header - may be in same column as Location or separate
+        first_table_match = re.search(r"\|\s*Product Code", text_content)
+        variance_pos = text_content.find("Variance Analysis:")
+        extended_review_pos = text_content.find("Extended Inventory Review:")
+        # Second table - look for SKU entries after extended review section
+        # The table may not have pipes on every row due to paragraph detection
+        second_table_pos = -1
+        if extended_review_pos != -1:
+            # Look for either "| Product Code" or "Product Code" as table header
+            second_table_match = re.search(
+                r"Product Code.*Category", text_content[extended_review_pos:]
+            )
+            if second_table_match:
+                # Adjust position to be relative to full text
+                second_table_pos = extended_review_pos + second_table_match.start()
+        recommendations_pos = text_content.find("Recommendations:")
+
+        positions = {
+            "header": header_pos,
+            "first_table": first_table_match.start() if first_table_match else -1,
+            "variance_analysis": variance_pos,
+            "extended_review": extended_review_pos,
+            "second_table": second_table_pos,
+            "recommendations": recommendations_pos,
+        }
+
+        # All sections should be found
+        for name, pos in positions.items():
+            assert pos != -1, f"Section '{name}' not found in output"
+
+        # Verify correct order
+        assert (
+            positions["header"] < positions["first_table"]
+        ), "Header should come before first table"
+        assert (
+            positions["first_table"] < positions["variance_analysis"]
+        ), "First table should come before Variance Analysis"
+        assert (
+            positions["variance_analysis"] < positions["extended_review"]
+        ), "Variance Analysis should come before Extended Review"
+        assert (
+            positions["extended_review"] < positions["second_table"]
+        ), "Extended Review should come before second table"
+        assert (
+            positions["second_table"] < positions["recommendations"]
+        ), "Second table should come before Recommendations"
+
+    def test_borderless_table_no_duplication(self, markitdown):
+        """Test that borderless table content is not duplicated excessively."""
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "SPARSE-2024-INV-1234_borderless_table.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Count occurrences of unique table data - should not be excessively duplicated
+        # SKU-8847 appears in both tables, plus possibly once in summary text
+        sku_count = text_content.count("SKU-8847")
+        # Should appear at most 4 times (2 tables + minor text references), not more
+        assert (
+            sku_count <= 4
+        ), f"SKU-8847 appears too many times ({sku_count}), suggests duplication issue"
+
+    def test_borderless_table_correct_position(self, markitdown):
+        """Test that tables appear in correct positions relative to text."""
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "SPARSE-2024-INV-1234_borderless_table.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Verify content order - header should come before table content, which should come before analysis
+        header_pos = text_content.find("Prepared By: Sarah Martinez")
+        # Look for Product Code in any pipe-separated format
+        product_code_pos = text_content.find("Product Code")
+        variance_pos = text_content.find("Variance Analysis:")
+
+        assert header_pos != -1, "Header should be found"
+        assert product_code_pos != -1, "Product Code should be found"
+        assert variance_pos != -1, "Variance Analysis should be found"
+
+        assert (
+            header_pos < product_code_pos < variance_pos
+        ), "Product data should appear between header and Variance Analysis"
+
+        # Second table content should appear after "Extended Inventory Review"
+        extended_review_pos = text_content.find("Extended Inventory Review:")
+        # Look for Category header which is in second table
+        category_pos = text_content.find("Category")
+        recommendations_pos = text_content.find("Recommendations:")
+
+        if (
+            extended_review_pos != -1
+            and category_pos != -1
+            and recommendations_pos != -1
+        ):
+            # Find Category position after Extended Inventory Review
+            category_after_review = text_content.find("Category", extended_review_pos)
+            if category_after_review != -1:
+                assert (
+                    extended_review_pos < category_after_review < recommendations_pos
+                ), "Extended review table should appear between Extended Inventory Review and Recommendations"
+
+    def test_receipt_pdf_extraction(self, markitdown):
+        """Test extraction of receipt PDF (no tables, formatted text).
+
+        Expected output structure:
+        - Store header: TECHMART ELECTRONICS with address
+        - Transaction info: Store #, date, TXN, Cashier, Register
+        - Line items: 6 products with prices and member discounts
+        - Totals: Subtotal, Member Discount, Sales Tax, Rewards, TOTAL
+        - Payment info: Visa Card, Auth, Ref
+        - Rewards member info: Name, ID, Points
+        - Return policy and footer
+        """
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "RECEIPT-2024-TXN-98765_retail_purchase.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # --- Validate Store Header ---
+        store_header = [
+            "TECHMART ELECTRONICS",
+            "4567 Innovation Blvd",
+            "San Francisco, CA 94103",
+            "(415) 555-0199",
+        ]
+        validate_strings(result, store_header)
+
+        # --- Validate Transaction Info ---
+        transaction_info = [
+            "Store #0342 - Downtown SF",
+            "11/23/2024",
+            "TXN: TXN-98765-2024",
+            "Cashier: Emily Rodriguez",
+            "Register: POS-07",
+        ]
+        validate_strings(result, transaction_info)
+
+        # --- Validate Line Items (6 products) ---
+        line_items = [
+            # Product 1: Headphones
+            "Wireless Noise-Cancelling",
+            "Headphones - Premium Black",
+            "AUDIO-5521",
+            "$349.99",
+            "$299.99",
+            # Product 2: USB-C Hub
+            "USB-C Hub 7-in-1 Adapter",
+            "ACC-8834",
+            "$79.99",
+            "$159.98",
+            # Product 3: Portable SSD
+            "Portable SSD 2TB",
+            "STOR-2241",
+            "$289.00",
+            "$260.00",
+            # Product 4: Wireless Mouse
+            "Ergonomic Wireless Mouse",
+            "ACC-9012",
+            "$59.99",
+            # Product 5: Screen Cleaning Kit
+            "Screen Cleaning Kit",
+            "CARE-1156",
+            "$12.99",
+            "$38.97",
+            # Product 6: HDMI Cable
+            "HDMI 2.1 Cable 6ft",
+            "CABLE-7789",
+            "$24.99",
+            "$44.98",
+        ]
+        validate_strings(result, line_items)
+
+        # --- Validate Totals ---
+        totals = [
+            "SUBTOTAL",
+            "$863.91",
+            "Member Discount",
+            "Sales Tax (8.5%)",
+            "$66.23",
+            "Rewards Applied",
+            "-$25.00",
+            "TOTAL",
+            "$821.14",
+        ]
+        validate_strings(result, totals)
+
+        # --- Validate Payment Info ---
+        payment_info = [
+            "PAYMENT METHOD",
+            "Visa Card ending in 4782",
+            "Auth: 847392",
+            "REF-20241123-98765",
+        ]
+        validate_strings(result, payment_info)
+
+        # --- Validate Rewards Member Info ---
+        rewards_info = [
+            "REWARDS MEMBER",
+            "Sarah Mitchell",
+            "ID: TM-447821",
+            "Points Earned: 821",
+            "Total Points: 3,247",
+        ]
+        validate_strings(result, rewards_info)
+
+        # --- Validate Return Policy & Footer ---
+        footer_info = [
+            "RETURN POLICY",
+            "Returns within 30 days",
+            "Receipt required",
+            "Thank you for shopping!",
+            "www.techmart.example.com",
+        ]
+        validate_strings(result, footer_info)
+
+        # --- Validate Document Structure Order ---
+        positions = {
+            "store_header": text_content.find("TECHMART ELECTRONICS"),
+            "transaction": text_content.find("TXN: TXN-98765-2024"),
+            "first_item": text_content.find("Wireless Noise-Cancelling"),
+            "subtotal": text_content.find("SUBTOTAL"),
+            "total": text_content.find("TOTAL"),
+            "payment": text_content.find("PAYMENT METHOD"),
+            "rewards": text_content.find("REWARDS MEMBER"),
+            "return_policy": text_content.find("RETURN POLICY"),
+        }
+
+        # All sections should be found
+        for name, pos in positions.items():
+            assert pos != -1, f"Section '{name}' not found in output"
+
+        # Verify correct order
+        assert (
+            positions["store_header"] < positions["transaction"]
+        ), "Store header should come before transaction"
+        assert (
+            positions["transaction"] < positions["first_item"]
+        ), "Transaction should come before items"
+        assert (
+            positions["first_item"] < positions["subtotal"]
+        ), "Items should come before subtotal"
+        assert (
+            positions["subtotal"] < positions["total"]
+        ), "Subtotal should come before total"
+        assert (
+            positions["total"] < positions["payment"]
+        ), "Total should come before payment"
+        assert (
+            positions["payment"] < positions["rewards"]
+        ), "Payment should come before rewards"
+        assert (
+            positions["rewards"] < positions["return_policy"]
+        ), "Rewards should come before return policy"
+
+    def test_multipage_invoice_extraction(self, markitdown):
+        """Test extraction of multipage invoice PDF with form-style layout.
+
+        Expected output: Pipe-separated format with clear cell boundaries.
+        Form data should be extracted with pipes indicating column separations.
+        """
+        pdf_path = os.path.join(TEST_FILES_DIR, "REPAIR-2022-INV-001_multipage.pdf")
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Validate basic content is extracted
+        expected_strings = [
+            "ZAVA AUTO REPAIR",
+            "Collision Repair",
+            "Redmond, WA",
+            "Gabriel Diaz",
+            "Jeep",
+            "Grand Cherokee",
+            "Parts",
+            "Body Labor",
+            "Paint Labor",
+            "GRAND TOTAL",
+            # Second page content
+            "Bruce Wayne",
+            "Batmobile",
+        ]
+        validate_strings(result, expected_strings)
+
+        # Validate pipe-separated table format
+        # Form-style documents should use pipes to separate cells
+        assert "|" in text_content, "Form-style PDF should contain pipe separators"
+
+        # Validate key form fields are properly separated
+        # These patterns check that label and value are in separate cells
+        # Note: cells may have padding spaces for column alignment
+        import re
+
+        assert re.search(
+            r"\| Insured name\s*\|", text_content
+        ), "Insured name should be in its own cell"
+        assert re.search(
+            r"\| Gabriel Diaz\s*\|", text_content
+        ), "Gabriel Diaz should be in its own cell"
+        assert re.search(
+            r"\| Year\s*\|", text_content
+        ), "Year label should be in its own cell"
+        assert re.search(
+            r"\| 2022\s*\|", text_content
+        ), "Year value should be in its own cell"
+
+        # Validate table structure for estimate totals
+        assert (
+            re.search(r"\| Hours\s*\|", text_content) or "Hours |" in text_content
+        ), "Hours column header should be present"
+        assert (
+            re.search(r"\| Rate\s*\|", text_content) or "Rate |" in text_content
+        ), "Rate column header should be present"
+        assert (
+            re.search(r"\| Cost\s*\|", text_content) or "Cost |" in text_content
+        ), "Cost column header should be present"
+
+        # Validate numeric values are extracted
+        assert "2,100" in text_content, "Parts cost should be extracted"
+        assert "300" in text_content, "Body labor cost should be extracted"
+        assert "225" in text_content, "Paint labor cost should be extracted"
+        assert "5,738" in text_content, "Grand total should be extracted"
+
+        # Validate second page content (Bruce Wayne invoice)
+        assert "Bruce Wayne" in text_content, "Second page customer name"
+        assert "Batmobile" in text_content, "Second page vehicle model"
+        assert "211,522" in text_content, "Second page grand total"
+
+        # Validate disclaimer text is NOT in table format (long paragraph)
+        # The disclaimer should be extracted as plain text, not pipe-separated
+        assert (
+            "preliminary estimate" in text_content.lower()
+        ), "Disclaimer text should be present"
+
+    def test_academic_pdf_extraction(self, markitdown):
+        """Test extraction of academic paper PDF (scientific document).
+
+        Expected output: Plain text without tables or pipe characters.
+        Scientific documents should be extracted as flowing text with proper spacing,
+        not misinterpreted as tables.
+        """
+        pdf_path = os.path.join(TEST_FILES_DIR, "test.pdf")
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Validate academic paper content with proper spacing
+        expected_strings = [
+            "Introduction",
+            "Large language models",  # Should have proper spacing, not "Largelanguagemodels"
+            "agents",
+            "multi-agent",  # Should be properly hyphenated
+        ]
+        validate_strings(result, expected_strings)
+
+        # Validate proper text formatting (words separated by spaces)
+        assert "LLMs" in text_content, "Should contain 'LLMs' acronym"
+        assert "reasoning" in text_content, "Should contain 'reasoning'"
+        assert "observations" in text_content, "Should contain 'observations'"
+
+        # Ensure content is not empty and has proper length
+        assert len(text_content) > 1000, "Academic PDF should have substantial content"
+
+        # Scientific documents should NOT have tables or pipe characters
+        assert (
+            "|" not in text_content
+        ), "Scientific document should not contain pipe characters (no tables)"
+
+        # Verify no markdown tables were extracted
+        tables = extract_markdown_tables(text_content)
+        assert (
+            len(tables) == 0
+        ), f"Scientific document should have no tables, found {len(tables)}"
+
+        # Verify text is properly formatted with spaces between words
+        # Check that common phrases are NOT joined together (which would indicate bad extraction)
+        assert (
+            "Largelanguagemodels" not in text_content
+        ), "Text should have proper spacing, not joined words"
+        assert (
+            "multiagentconversations" not in text_content.lower()
+        ), "Text should have proper spacing between words"
+
+    def test_scanned_pdf_handling(self, markitdown):
+        """Test handling of scanned/image-based PDF (no text layer).
+
+        Expected output: Empty - scanned PDFs without OCR have no text layer.
+        """
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "MEDRPT-2024-PAT-3847_medical_report_scan.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+
+        # Scanned PDFs without OCR have no text layer, so extraction should be empty
+        assert (
+            result is not None
+        ), "Converter should return a result even for scanned PDFs"
+        assert result.text_content is not None, "text_content should not be None"
+
+        # Verify extraction is empty (no text layer in scanned PDF)
+        assert (
+            result.text_content.strip() == ""
+        ), f"Scanned PDF should have empty extraction, got: '{result.text_content[:100]}...'"
+
+
+class TestPdfTableMarkdownFormat:
+    """Test that extracted tables have proper markdown formatting."""
+
+    @pytest.fixture
+    def markitdown(self):
+        """Create MarkItDown instance."""
+        return MarkItDown()
+
+    def test_markdown_table_has_pipe_format(self, markitdown):
+        """Test that form-style PDFs have pipe-separated format."""
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "SPARSE-2024-INV-1234_borderless_table.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Find rows with pipes
+        lines = text_content.split("\n")
+        pipe_rows = [
+            line for line in lines if line.startswith("|") and line.endswith("|")
+        ]
+
+        assert len(pipe_rows) > 0, "Should have pipe-separated rows"
+
+        # Check that Product Code appears in a pipe-separated row
+        product_code_found = any("Product Code" in row for row in pipe_rows)
+        assert product_code_found, "Product Code should be in pipe-separated format"
+
+    def test_markdown_table_columns_have_pipes(self, markitdown):
+        """Test that form-style PDF columns are separated with pipes."""
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "SPARSE-2024-INV-1234_borderless_table.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Find table rows and verify column structure
+        lines = text_content.split("\n")
+        table_rows = [
+            line for line in lines if line.startswith("|") and line.endswith("|")
+        ]
+
+        assert len(table_rows) > 0, "Should have markdown table rows"
+
+        # Check that at least some rows have multiple columns (pipes)
+        multi_col_rows = [row for row in table_rows if row.count("|") >= 3]
+        assert (
+            len(multi_col_rows) > 5
+        ), f"Should have rows with multiple columns, found {len(multi_col_rows)}"
+
+
+class TestPdfTableStructureConsistency:
+    """Test that extracted tables have consistent structure across all PDF types."""
+
+    @pytest.fixture
+    def markitdown(self):
+        """Create MarkItDown instance."""
+        return MarkItDown()
+
+    def test_borderless_table_structure(self, markitdown):
+        """Test that borderless table PDF has pipe-separated structure."""
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "SPARSE-2024-INV-1234_borderless_table.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Should have pipe-separated content
+        assert "|" in text_content, "Borderless table PDF should have pipe separators"
+
+        # Check that key content is present
+        assert "Product Code" in text_content, "Should contain Product Code"
+        assert "SKU-8847" in text_content, "Should contain first SKU"
+        assert "SKU-9201" in text_content, "Should contain second SKU"
+
+    def test_multipage_invoice_table_structure(self, markitdown):
+        """Test that multipage invoice PDF has pipe-separated format."""
+        pdf_path = os.path.join(TEST_FILES_DIR, "REPAIR-2022-INV-001_multipage.pdf")
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        text_content = result.text_content
+
+        # Should have pipe-separated content
+        assert "|" in text_content, "Invoice PDF should have pipe separators"
+
+        # Find rows with pipes
+        lines = text_content.split("\n")
+        pipe_rows = [
+            line for line in lines if line.startswith("|") and line.endswith("|")
+        ]
+
+        assert (
+            len(pipe_rows) > 10
+        ), f"Should have multiple pipe-separated rows, found {len(pipe_rows)}"
+
+        # Check that some rows have multiple columns
+        multi_col_rows = [row for row in pipe_rows if row.count("|") >= 4]
+        assert len(multi_col_rows) > 5, "Should have rows with 3+ columns"
+
+    def test_receipt_has_no_tables(self, markitdown):
+        """Test that receipt PDF doesn't incorrectly extract tables from formatted text."""
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "RECEIPT-2024-TXN-98765_retail_purchase.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        tables = extract_markdown_tables(result.text_content)
+
+        # Receipt should not have markdown tables extracted
+        # (it's formatted text, not tabular data)
+        # If tables are extracted, they should be minimal/empty
+        total_table_rows = sum(len(t) for t in tables)
+        assert (
+            total_table_rows < 5
+        ), f"Receipt should not have significant tables, found {total_table_rows} rows"
+
+    def test_scanned_pdf_no_tables(self, markitdown):
+        """Test that scanned PDF has empty extraction and no tables."""
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "MEDRPT-2024-PAT-3847_medical_report_scan.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+
+        # Scanned PDF with no text layer should have empty extraction
+        assert (
+            result.text_content.strip() == ""
+        ), "Scanned PDF should have empty extraction"
+
+        tables = extract_markdown_tables(result.text_content)
+
+        # Scanned PDF with no text layer should have no tables
+        assert len(tables) == 0, "Scanned PDF should have no extracted tables"
+
+    def test_all_pdfs_table_rows_consistent(self, markitdown):
+        """Test that all PDF tables have rows with pipe-separated content.
+
+        Note: With gap-based column detection, rows may have different column counts
+        depending on how content is spaced in the PDF. What's important is that each
+        row has pipe separators and the content is readable.
+        """
+        pdf_files = [
+            "SPARSE-2024-INV-1234_borderless_table.pdf",
+            "REPAIR-2022-INV-001_multipage.pdf",
+            "RECEIPT-2024-TXN-98765_retail_purchase.pdf",
+            "test.pdf",
+        ]
+
+        for pdf_file in pdf_files:
+            pdf_path = os.path.join(TEST_FILES_DIR, pdf_file)
+            if not os.path.exists(pdf_path):
+                continue
+
+            result = markitdown.convert(pdf_path)
+            tables = extract_markdown_tables(result.text_content)
+
+            for table_idx, table in enumerate(tables):
+                if not table:
+                    continue
+
+                # Verify each row has at least one column (pipe-separated content)
+                for row_idx, row in enumerate(table):
+                    assert (
+                        len(row) >= 1
+                    ), f"{pdf_file}: Table {table_idx}, row {row_idx} has no columns"
+
+                    # Verify the row has non-empty content
+                    row_content = " ".join(cell.strip() for cell in row)
+                    assert (
+                        len(row_content.strip()) > 0
+                    ), f"{pdf_file}: Table {table_idx}, row {row_idx} is empty"
+
+    def test_borderless_table_data_integrity(self, markitdown):
+        """Test that borderless table extraction preserves data integrity."""
+        pdf_path = os.path.join(
+            TEST_FILES_DIR, "SPARSE-2024-INV-1234_borderless_table.pdf"
+        )
+
+        if not os.path.exists(pdf_path):
+            pytest.skip(f"Test file not found: {pdf_path}")
+
+        result = markitdown.convert(pdf_path)
+        tables = extract_markdown_tables(result.text_content)
+
+        assert len(tables) >= 2, "Should have at least 2 tables"
+
+        # Check first table has expected SKU data
+        first_table = tables[0]
+        table_text = str(first_table)
+        assert "SKU-8847" in table_text, "First table should contain SKU-8847"
+        assert "SKU-9201" in table_text, "First table should contain SKU-9201"
+
+        # Check second table has expected category data
+        second_table = tables[1]
+        table_text = str(second_table)
+        assert "Electronics" in table_text, "Second table should contain Electronics"
+        assert "Hardware" in table_text, "Second table should contain Hardware"