— Document Chunking (14 Types)

Transform raw documents into semantically coherent chunks

14 document-type handlers: naive splitter, paper, book, manual, presentation, QA, table, resume, picture (OCR), audio (transcription), email, tag, one, laws.

Classes

Files

~N k

Lines

Key Metric

❓ What is this & why?

The app module contains 14 specialized document-type chunkers. Different document formats have different semantic boundaries: tables need structure preservation, academic papers need section hierarchy, books need chapter breaks, code needs logical units. This module exists to transform raw documents into semantically coherent chunks that can be retrieved and reasoned about as first-class units.

💡 Real-world analogy

Think of a newspaper archive. Articles (papers) need to be cut at section boundaries to preserve meaning. Tables need their grid structure intact. Books need chapters separated, not random paragraphs. A generic 'split by word count' chunker would destroy all this structure. Instead, each document type gets a specialized cutter that understands its layout.

🤔 Why Is It Designed This Way?

{{DESIGN_RATIONALE}} — 150+ words explaining the design choices: what pattern does this follow and why? What constraints shaped the implementation? What trade-offs were made and what was sacrificed?

Design Choice	What Was Chosen	What Was Rejected	Why
Example: data layout	Array of structs	Struct of arrays	Random access pattern dominates; cache locality for single items matters more than SIMD sweeps

Architecture

flowchart LR
    subgraph Input["Input Documents"]
        I1["PDF"]
        I2["Markdown"]
        I3["Table"]
        I4["Code"]
        I5["Other..."]
    end
    subgraph Detect["Type Detection"]
        D["Detect Format"]
    end
    subgraph Chunkers["14 Chunker Types"]
        C1["Naive Split"]
        C2["Paper"]
        C3["Book"]
        C4["Table"]
        C5["Others..."]
    end
    subgraph Output["Chunks + Metadata"]
        O["Semantic Chunks"]
    end
    Input --> D
    D -->|Strategy| Chunkers
    Chunkers --> O

Key Classes

Class / Function	File	Purpose
`ClassName`	file.h	Brief description

Data Structures

Type	Name	Description
enum	`EnumName`	Brief description

Interactions

Direction	Partner	Interface	Description
→	Other Module	`methodName()`	Brief description

Configuration

Knob / Parameter	Default	Description
`param_name`	value	What it controls

Directory Map

Source tree for app

submod_name/
├── file_a.ext                 ← Role: brief annotation
├── file_b.ext                 ← Role: brief annotation
├── file_c.ext                 ← Role: brief annotation
└── index.ext                  ← Role: entry point

📑 Annotated Code Walkthrough

The most important code in this sub-module, annotated with WHY each piece exists:

// Replace with actual code from the source
void key_function() {
    // ← WHY: Explain the purpose of this line
    // ← WHY: What constraint or requirement drives this?
}

Line-by-line:

Line N: What this does and WHY — what would break if removed
Line M: The design choice here — why this approach over the obvious alternative

⚠️ Edge Cases & Boundaries

Edge Case	What Happens	Where in Code	Risk Level
Empty input	How it's handled	function_name:line	🟢 Low
Concurrent access	How it's handled	function_name:line	🔴 High

Processing Workflow

sequenceDiagram
    participant User as User/API
    participant Detector as Type Detector
    participant Chunker as Specialized Chunker
    participant Metadata as Metadata Handler
    User->>Detector: Document submitted
    Detector->>Detector: Analyze format
    Detector->>Chunker: Route to handler
    Chunker->>Chunker: Parse content
    Chunker->>Metadata: Extract structure
    Metadata->>User: Return chunks + metadata

Code Examples

Example: Typical Usage

// Replace with actual code example
void example() {
    // ...
}