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Overview

When pageChunks: true is passed to ToMarkdown() or ToText(), the return value is a JSON string containing an array of page objects — one per page — rather than a single concatenated string. Each object in the array follows the schema described on this page. PDF4LLM Chunk Schema Diagram Deserialise the JSON string with your preferred library to work with the chunks in C#: 
using Newtonsoft.Json.Linq;
using PDF4LLM;

string   json   = PdfExtractor.ToMarkdown("document.pdf", pageChunks: true);
JArray   chunks = JArray.Parse(json);

foreach (JObject chunk in chunks)
{
    foreach (var prop in chunk.Properties())
    {
        Console.WriteLine(prop.Name);
        Console.WriteLine("----");
        Console.WriteLine(prop.Value);
    }
}

​
Why use page chunks?

Page chunking is the recommended approach for any pipeline that needs to process, search, or embed a PDF’s content. Rather than working with one large string, you get a structured array where each page is a self-contained unit carrying both its text and the metadata needed to make that text useful. This matters most in RAG applications, where you need to attach source information — file path, page number, document title — to every embedded chunk so that retrieved passages can be traced back to their origin. The layout data in page_boxes adds another layer of utility: you can filter out headers, footers, and captions before embedding, or treat tables and body text differently depending on your retrieval strategy. Rather than post-processing a flat Markdown string and trying to guess where page boundaries or section headings fall, chunking gives you that structure directly from the PDF’s own layout engine. Example — extracting page numbers and first 100 characters of text from each chunk: 
using Newtonsoft.Json.Linq;
using PDF4LLM;

string json   = PdfExtractor.ToMarkdown("document.pdf", pageChunks: true);
JArray chunks = JArray.Parse(json);

foreach (JObject chunk in chunks)
{
    int    pageNumber = chunk["metadata"]!["page_number"]!.Value<int>();
    string text       = chunk["text"]!.Value<string>()!;

    Console.WriteLine($"{pageNumber}: {text[..Math.Min(100, text.Length)]}");
}
This is the recommended approach for RAG pipelines — it lets you attach rich metadata to each piece of content before embedding or indexing it.

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Chunk schema

Each item in the returned JSON array is an object with four top-level keys: 
{
    "metadata":   { ... },
    "toc_items":  [ ... ],
    "page_boxes": [ ... ],
    "text":       "..."
}

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metadata

Contains both document-level properties (consistent across all chunks) and page-level properties (unique per chunk). 
{
    "format":       "PDF 1.7",
    "title":        "My Document",
    "author":       "Jane Smith",
    "subject":      "",
    "keywords":     "",
    "creator":      "pdf-lib",
    "producer":     "pdf-lib",
    "creationDate": "D:20260206183204Z",
    "modDate":      "D:20260206183204Z",
    "trapped":      "",
    "encryption":   null,

    "file_path":    "document.pdf",
    "page_count":   19,
    "page_number":  1
}
​
format
string
The PDF version string, e.g. "PDF 1.7".
​
title
string
Document title from PDF metadata. Empty string if not set.
​
author
string
Document author from PDF metadata. Empty string if not set.
​
creator
string
The application that originally created the PDF.
​
producer
string
The application that produced or converted the PDF.
​
creationDate
string
PDF creation date string in D:YYYYMMDDHHmmSSZ format.
​
modDate
string
Date the PDF was last modified, in the same format as creationDate.
​
encryption
string | null
Encryption method if the document is encrypted, otherwise null.
​
file_path
string
The file path of the source document as provided to ToMarkdown().
​
page_count
integer
Total number of pages in the document.
​
page_number
integer
The 1-based page number this chunk represents.

​
Usage example

foreach (JObject chunk in chunks)
{
    var    meta      = chunk["metadata"]!;
    int    pageNum   = meta["page_number"]!.Value<int>();
    int    pageCount = meta["page_count"]!.Value<int>();
    string filePath  = meta["file_path"]!.Value<string>()!;

    Console.WriteLine($"Page {pageNum} of {pageCount} — {filePath}");
}

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toc_items

A list of Table of Contents entries that fall on this page. Each entry is an array in the format [level, title, page_number]. 
"toc_items": [
    [1, "Introduction",      3],
    [2, "Background",        3],
    [2, "Problem Statement", 3]
]
​
level
integer
Heading hierarchy depth. 1 = top-level chapter, 2 = section, 3 = subsection, etc.
​
title
string
The heading text as it appears in the Table of Contents.
​
page_number
integer
The page number the TOC entry points to (1-based).
toc_items is an empty array [] for pages that have no TOC entries, or for documents without a Table of Contents. Always check before iterating.

​
Usage example

foreach (JObject chunk in chunks)
{
    foreach (JArray entry in chunk["toc_items"]!)
    {
        int    level  = entry[0].Value<int>();
        string title  = entry[1].Value<string>()!;
        int    page   = entry[2].Value<int>();
        string indent = new string(' ', (level - 1) * 2);

        Console.WriteLine($"{indent}{title} (p.{page})");
    }
}

​
page_boxes

A list of layout elements detected on the page by the layout analysis engine. Each element describes a discrete visual block — a paragraph, heading, image, table, list item — along with its position on the page and its character offsets within the page’s text string. 
"page_boxes": [
    {
        "index": 0,
        "class": "section-header",
        "bbox":  [58, 55, 560, 108],
        "pos":   [0, 88]
    },
    {
        "index": 1,
        "class": "text",
        "bbox":  [36, 125, 574, 209],
        "pos":   [88, 524]
    }
]
​
index
integer
Zero-based position of this box in the page’s reading order (top to bottom).
​
class
string
The type of layout element detected. See the box classes table below.
​
bbox
[float, float, float, float]
Bounding box of the element in PDF page coordinates: [x0, y0, x1, y1]. Origin is the top-left of the page. Units are PDF points (1 pt = 1/72 inch).
​
pos
[int, int]
Character offsets into the page’s text string: [start, end]. Use these to slice the exact text that corresponds to this layout element.

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Box classes

ClassDescription
textBody paragraph or general prose
section-headerA heading or section title
list-itemA bullet or numbered list entry
tableA detected table
pictureAn image or figure
captionA caption beneath a figure or table
page-footerFooter content at the bottom of the page
page-headerHeader content at the top of the page

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Usage example — extract only headings

foreach (JObject chunk in chunks)
{
    string text  = chunk["text"]!.Value<string>()!;

    foreach (JObject box in chunk["page_boxes"]!)
    {
        if (box["class"]!.Value<string>() != "section-header") continue;

        int    start       = box["pos"]![0]!.Value<int>();
        int    end         = box["pos"]![1]!.Value<int>();
        string headingText = text[start..end].Trim();

        Console.WriteLine(headingText);
    }
}

​
Usage example — get bounding boxes for all images

foreach (JObject chunk in chunks)
{
    int page = chunk["metadata"]!["page_number"]!.Value<int>();

    foreach (JObject box in chunk["page_boxes"]!)
    {
        if (box["class"]!.Value<string>() != "picture") continue;

        var bbox = box["bbox"]!.ToObject<float[]>()!;
        Console.WriteLine($"Page {page}: image at [{string.Join(", ", bbox)}]");
    }
}

​
text

The full Markdown-formatted text content of the page as a single string. Headings, bold text, tables, and list items are represented using standard Markdown syntax. 
"text": "## Introduction\n\nWe highlight four promising research opportunities to improve\n_Large Language Model_ inference for datacenter AI...\n\n## **BACKGROUND**\n\n...\n"
​
text
string
Markdown string for the entire page. Newlines separate logical blocks. Images that cannot be extracted are replaced with a placeholder such as ==> picture [535 x 193] intentionally omitted <==.
The character offsets in each page_boxes[n]["pos"] correspond directly to positions within this string. Use them to precisely extract the text for any layout element without re-parsing the Markdown.

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Usage example — slice text by layout element

JObject chunk = (JObject)chunks[0];
string  text  = chunk["text"]!.Value<string>()!;

foreach (JObject box in chunk["page_boxes"]!)
{
    int    start   = box["pos"]![0]!.Value<int>();
    int    end     = box["pos"]![1]!.Value<int>();
    string cls     = box["class"]!.Value<string>()!;
    string snippet = text[start..end].Trim();

    if (snippet.Length > 80)
        snippet = snippet[..80];

    Console.WriteLine($"[{cls}] {snippet}");
}

​
Full iteration example

using Newtonsoft.Json.Linq;
using PDF4LLM;

string json   = PdfExtractor.ToMarkdown("document.pdf", pageChunks: true);
JArray chunks = JArray.Parse(json);

foreach (JObject chunk in chunks)
{
    var    meta      = chunk["metadata"]!;
    var    toc       = chunk["toc_items"]!;
    var    boxes     = chunk["page_boxes"]!;
    string text      = chunk["text"]!.Value<string>()!;

    int    pageNum   = meta["page_number"]!.Value<int>();
    int    pageCount = meta["page_count"]!.Value<int>();

    Console.WriteLine($"\n--- Page {pageNum} of {pageCount} ---");

    // TOC entries on this page
    foreach (JArray entry in toc)
    {
        int    level = entry[0].Value<int>();
        string title = entry[1].Value<string>()!;
        Console.WriteLine($"  TOC [{level}]: {title}");
    }

    // Layout elements
    foreach (JObject box in boxes)
    {
        int    start   = box["pos"]![0]!.Value<int>();
        int    end     = box["pos"]![1]!.Value<int>();
        string cls     = box["class"]!.Value<string>()!;
        string snippet = text[start..end].Trim().Replace("\n", " ");

        if (snippet.Length > 60)
            snippet = snippet[..60];

        Console.WriteLine($"  [{cls}] {snippet}");
    }
}
MethodDescription
ToMarkdown()Produces chunks when pageChunks: true
ToText()Plain text equivalent with pageChunks: true
ToJson()Alternative export with full bounding box and layout data
GetKeyValues()Extract form field data from a PDF

JSON Schema

Full schema reference for the JSON output, including text, image, table, and drawing blocks with bounding boxes.

Extract JSON guide

Working walkthrough with filtering and pipeline examples.

ToJson()

Full API reference for ToJson().

Tables guide

Best practices for extracting tables with layout data and converting to DataTables or CSV.