title	emoji	colorFrom	colorTo	sdk	sdk_version	python_version	command	app_file	hf_oauth	oauth_scopes	hf_oauth_scopes	license	pinned	short_description	models	tags	owner	version	readme	requires-python
parser2md - PDF & HTML parser to markdown	📚	yellow	purple	gradio	5.44.1	3.12	python main.py	main.py	true	read-access	inference-api	mit	true	PDF & HTML parser to markdown	meta-llama/Llama-4-Maverick-17B-128E-Instruct openai/gpt-oss-120b, openai/gpt-oss-20b vikp/surya_det3 vikp/surya_rec2 vikp/surya_tablerec datalab-to/surya_layout datalab-to/surya_tablerec datalab-to/texify datalab-to/ocr_error_detection datalab-to/inline_math_det0 datalab-to/line_detector0 xiaoyao9184/surya_text_detection xiaoyao9184/surya_text_recognition xiaoyao9184/surya_table_recognition xiaoyao9184/surya_texify xiaoyao9184/surya_layout xiaoyao9184/surya_ocr_error_detection xiaoyao9184/surya_inline_math_detection]	markdown PDF parser converter extractor	research-semmyk	0.1.0	README.md	>=3.12

parserPDF

[Pipeline for (in-progress) integrated RAG-KG platform]

---

A Gradio-based web application for converting PDF, HTML and Word documents to Markdown format. Powered by the Marker library (a pipeline of deep learning models for document parsing) and optional LLM integration for enhanced processing. Supports batch processing of files and directories via an intuitive UI.

Features

• PDF to Markdown: Extract text, tables, and images from PDFs, HTMLs and Word documents using Marker.
• HTML to Markdown: Convert HTML files to clean Markdown. #Deprecated
• Batch Processing: Upload multiple files or entire directories.
• LLM Integration: Optional use of Hugging Face or OpenAI models for advanced conversion (e.g., via Llama or GPT models).
• Customizable Settings: Adjust model parameters, output formats (Markdown/HTML), page ranges, and more via the UI.
• Output Management: Generated Markdown files saved to a configurable output directory, with logs and download links.

Project Structure

parserpdf/
├── README.md                   # Project documentation
├── requirements.txt            # Python dependencies
├── main.py                     # Entry point – launches the Gradio UI
├── pyproject.toml              # Project configuration
├── .env                        # Environment variables (e.g., API tokens)
├── .gitignore                  # Git ignore rules
├── converters/                 # Conversion logic
│   ├── __init__.py
│   ├── extraction_converter.py # Document extraction utilities
│   ├── pdf_to_md.py            # Marker-based PDF, HTML, Word → Markdown
│   ├── html_to_md.py           # HTML → Markdown  #Deprecated
│   └── md_to_pdf.py            # Markdown → PDF (pending full implementation)
├── file_handler/               # File handling utilities
│   ├── __init__.py
│   └── file_utils.py           # Helpers for files, directories, and paths
├── llm/                        # LLM client integrations
│   ├── __init__.py
│   ├── hf_client.py            # Hugging Face client wrapper  ##PutOnHold
│   ├── openai_client.py        # Marker OpenAI client         ##NotFullyImplemented
│   ├── llm_login.py            # Authentication handlers
│   └── provider_validator.py   # Provider validation
├── ui/                         # Gradio UI components
│   ├── __init__.py
│   └── gradio_ui.py            # UI layout, event handlers and coordination
├── utils/                      # Utility modules
│   ├── __init__.py
│   ├── config.py               # Configuration constants
│   ├── config.ini              # config file for settings
│   ├── logger.py               # Logging wrapper
│   ├── lib_loader.py           # loads weasyprint lib dependencies to environ
│   ├── get_config.py           # helper for getting configurations
│   ├── get_arg_name.py         # helper for getting argument names
│   └── utils.py                # General utilities and helpers
├── data/                       # Sample data and outputs (gitignored)
│   ├── output_dir/             # Output directory
│   ├── pdf/                    # Sample PDFs
├── logs/                       # Log files (gitignored)
├── tests/                      # Unit tests   ##ToBeUpdated
│   ├── tests_converter.py          # tests for converters
└── scrapyard/                  # Development scraps


[Projected]
├── transformers/
│   ├── __init__.py
│   ├── marker.py           # Marker class
│   └── marker_utils.py     # helpers for Marker class

Installation

1. Clone the repository:

   git clone <repo-url>
   cd parserpdf
   

2. Create a virtual environment and install dependencies:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   pip install -r requirements.txt
   

3. Set up environment variables (optional for LLM features):

   • Create a .env file with your API tokens, e.g.:

     HF_TOKEN=hf_xxx
     OPENAI_API_KEY=sk-xxx
     

   • HuggingFace login (oauth) integrated with Gradio:

4. Install Marker (if not in requirements.txt):

   pip install marker-pdf[full]
   

Usage

1. Run the application:

   python main.py
   

2. Open the provided local URL (e.g., http://127.0.0.1:7860) in your browser.

3. In the UI:

   • Upload PDF/HTML/Word files or directories via the "PDF, HTML & Word ➜ Markdown" tab.
   • Configure LLM/Marker settings in the accordions (e.g., select provider, model, tokens).
   • Click "Process All Uploaded Files" to convert.
   • View logs, JSON output, and download generated Markdown files.

Example Workflow

• Upload a PDF directory.
• Set model to meta-llama/Llama-4-Maverick-17B-128E-Instruct (Hugging Face).
• Enable LLM if needed, set page range (e.g., "1-10").
• Process: Outputs Markdown files with extracted text/images to output_dir.

Configuration

• Edit utils/config.ini or utils/config.py for defaults (e.g., model ID, output dir).
• On windows, set weasyprint's GTK path: e.g. "C:\Dat\dev\gtk3-runtime\bin" or "C:\msys64\mingw64\bin"
• UI overrides: Adjust sliders for max tokens, temperature, workers, etc.

LLM Providers

• Hugging Face: Supports inference providers like Fireworks AI, Together AI.
• OpenAI: Compatible via router (default: https://router.huggingface.co/v1).
• Login via UI or CLI: huggingface-cli login.

Output

• Markdown files saved to output_dir (default: ./output_dir).
• Images extracted as JPEGs alongside Markdown.
• Logs in logs/ and UI textbox.

Limitations & TODO

• Markdown → PDF is pending full implementation.
• HTML tab is deprecated; use main tab for mixed uploads.
• Large files/directories may require increased max_workers and higher processing power.
• No JSON/chunks output yet (flagged for future).

Contributing

Fork the repo, create a branch, and submit a PR.

• GitHub
• HuggingFace Space Community

Ensure tests pass: - verify the application's functionality. ##TardyOutdated

pytest tests/

Test Structure

• tests/test_converters.py: Tests PDF/HTML/Markdown converters, including init, conversion, batch processing, and error handling.
• tests/test_file_handler.py: Tests file collection utilities (PDF/HTML/MD paths), data processing, and output directory creation.
• tests/test_utils.py: Tests logging setup, config loading, utility functions like is_dict/is_list_of_dicts, and configuration access.
• tests/test_llm.py: Tests LLM login, provider validation, Hugging Face/OpenAI client initialization, and API interactions.
• tests/test_main_ui.py: Tests main application logic, UI building, batch conversion, file accumulation, and ProcessPoolExecutor integration.

Roadmap (No concrete timeline for now)

1. Q4 2025: Document viewer pre-processing and processed document view post-processing
2. Q4 2025: Integration with RAG-KG (knowledge graph)
3. MCP server and Faster conversion rate
4. Integrated research platform for document realist-based analysis

License

MIT License. See LICENSE for details.

Acknowledgments

• Built with Gradio for the UI.
• PDF parsing via Marker.
• LLM integrations using Hugging Face Transformers and OpenAI APIs.
• HuggingFace Spaces Configuration Reference HF Spaces Configuration Reference
• IBM Research: HF Spaces Guide