---

name: marker description: Convert documents (PDF, EPUB, PPTX, DOCX, XLSX, HTML, images) to Markdown/JSON/HTML using marker-pdf with Claude Haiku LLM enhancement for accurate table, math, and form extraction. Use when user needs to extract content from documents, convert PDFs to markdown, or process document files.

Marker Document Converter

Convert PDF, EPUB, PPTX, DOCX, XLSX, HTML, and image files to clean Markdown/JSON/HTML format using the marker-pdf tool with multimodal LLM enhancement.

Prerequisites

# Install marker-pdf with full document support
uv tool install marker-pdf[full]

Requires Python 3.10+ and PyTorch.

Basic Usage

marker_single "<file_path>" \
  --output_format markdown \
  --output_dir "<output_directory>" \
  --use_llm \
  --llm_service marker.services.claude.ClaudeService \
  --claude_model_name claude-haiku-4-5 \
  --claude_api_key $ANTHROPIC_API_KEY \
  --disable_image_extraction

Note: --disable_image_extraction generates plain text output. Remove this flag if images need to be preserved.

Output Formats

Format	Description	Use Case
markdown	Formatted text with tables, LaTeX equations ($$-fenced), code blocks, image links	General document conversion
html	Semantic HTML with <img>, <math>, <pre> tags	Web display
json	Hierarchical structure with block types, bounding boxes, section hierarchy	Programmatic processing
chunks	Flattened JSON optimized for RAG	Vector database ingestion

CLI Options

Core Options

• --output_format: markdown (default), html, json, chunks
• --output_dir: Directory for output files
• --page_range: Specific pages, e.g., "0,5-10,20"

LLM Enhancement

• --use_llm: Enable LLM for improved accuracy (tables, forms, math, handwriting)
• --llm_service: LLM service class (see LLM Services below)
• --block_correction_prompt: Custom prompt for output refinement

OCR & Processing

• --force_ocr: Force OCR on entire document, converts inline math to LaTeX
• --strip_existing_ocr: Remove existing OCR and re-process
• --redo_inline_math: Highest quality inline math conversion (use with --use_llm)

Image & Output Control

• --disable_image_extraction: Skip image extraction (plain text only)
• --paginate_output: Add page separators to output
• --extract_images: Enable image extraction (default: true)

Advanced

• --config_json: Load configuration from JSON file
• --debug: Enable diagnostic logging
• --force_layout_block: Force layout type, e.g., Table
• --converter_cls: Custom converter class

LLM Services

Claude (Default)

marker_single document.pdf \
  --use_llm \
  --llm_service marker.services.claude.ClaudeService \
  --claude_api_key $ANTHROPIC_API_KEY \
  --claude_model_name claude-haiku-4-5

OpenAI

marker_single document.pdf \
  --use_llm \
  --llm_service marker.services.openai.OpenAIService \
  --openai_api_key $OPENAI_API_KEY \
  --openai_model gpt-4o

Ollama (Local)

marker_single document.pdf \
  --use_llm \
  --llm_service marker.services.ollama.OllamaService \
  --ollama_base_url "http://localhost:11434" \
  --ollama_model llama3.2-vision

Google Gemini (Default if no service specified)

export GOOGLE_API_KEY="your-api-key"
marker_single document.pdf --use_llm

Examples

Convert PDF to Markdown (Plain Text)

marker_single "./docs/report.pdf" \
  --output_format markdown \
  --output_dir "./docs/" \
  --use_llm \
  --llm_service marker.services.claude.ClaudeService \
  --claude_model_name claude-haiku-4-5 \
  --claude_api_key $ANTHROPIC_API_KEY \
  --disable_image_extraction

Convert with Images Preserved

marker_single "./docs/report.pdf" \
  --output_format markdown \
  --output_dir "./docs/" \
  --use_llm \
  --llm_service marker.services.claude.ClaudeService \
  --claude_model_name claude-haiku-4-5 \
  --claude_api_key $ANTHROPIC_API_KEY

Extract Tables Only

marker_single "./docs/spreadsheet.pdf" \
  --use_llm \
  --force_layout_block Table \
  --converter_cls marker.converters.table.TableConverter \
  --output_format json

Batch Convert Multiple Files

marker /path/to/input/folder --workers 4

Using JSON Config File

cat > config.json << EOF
{
  "force_ocr": true,
  "use_llm": true,
  "output_format": "markdown",
  "disable_image_extraction": true,
  "strip_existing_ocr": true,
  "redo_inline_math": true
}
EOF

marker_single document.pdf --config_json config.json

Output Structure

Markdown Output

• Image links: ![](image_name.png)
• Tables: Formatted as markdown tables
• Equations: Fenced with $$...$$
• Code: Fenced with ```language
• Headings: # for sections

JSON Output

{
  "pages": [
    {
      "id": "page_0",
      "polygon": [[x1,y1], [x2,y2], ...],
      "children": [
        {
          "id": "block_0",
          "block_type": "Text|Table|Image|...",
          "html": "<p>content</p>",
          "polygon": [...],
          "section_hierarchy": {...}
        }
      ]
    }
  ],
  "metadata": {
    "table_of_contents": [...],
    "page_stats": [...]
  }
}

Instructions

1. Confirm the input file path exists

2. Determine output directory (default: same as input file)

3. Use AskUserQuestion tool to ask user preferences (ask both questions together):

   Question 1 - Image Extraction:

   • Header: "Images"
   • Question: "是否需要提取文档中的图片？"
   • Options:
     • "No (Recommended)": 仅提取文本，生成纯 Markdown 文件
     • "Yes": 提取图片并保存，Markdown 中包含图片链接

   Question 2 - LLM Service:

   • Header: "LLM"
   • Question: "使用哪个 LLM 来识别图片和表格内容？"
   • Options:
     • "Claude Haiku (Recommended)": 快速、经济，需要 ANTHROPIC_API_KEY
     • "Claude Sonnet": 更高质量，需要 ANTHROPIC_API_KEY
     • "GPT-4o": OpenAI 模型，需要 OPENAI_API_KEY
     • "Ollama (Local)": 本地运行，无需 API Key

4. Based on user's answers, construct the command:

   • If "No" for images: add --disable_image_extraction
   • Set LLM service parameters according to selection:
     • Claude Haiku: --llm_service marker.services.claude.ClaudeService --claude_model_name claude-haiku-4-5 --claude_api_key $ANTHROPIC_API_KEY
     • Claude Sonnet: --llm_service marker.services.claude.ClaudeService --claude_model_name claude-sonnet-4-20250514 --claude_api_key $ANTHROPIC_API_KEY
     • GPT-4o: --llm_service marker.services.openai.OpenAIService --openai_api_key $OPENAI_API_KEY --openai_model gpt-4o
     • Ollama: --llm_service marker.services.ollama.OllamaService --ollama_base_url "http://localhost:11434" --ollama_model llama3.2-vision

5. Run the marker_single command with chosen options

6. Report the output file location and any extraction notes