🌐 Language | English · Português 🇧🇷
Every PDF tool you need — 100% local, 100% private.
Features • Usage • Contributing • License
LocalPDF.io is a self-hosted web app for PDF and document manipulation. Every file is processed on your own machine — nothing is uploaded to any server.
No accounts. No cloud. No data leaving your computer.
- 🖼️ PDF → Imagens - Extraia cada página como imagem PNG
- 📝 PDF → Word - Converta PDF em documento DOCX editável
- 📊 PDF → Excel - Extraia tabelas para planilhas XLSX
- 📄 PDF → Texto - Extraia todo o texto em arquivo TXT
- 🔒 PDF → PDF/A - Converta para o padrão de arquivamento (PDF/A-1b)
- 🔍 OCR em PDF - Extraia texto de PDFs e imagens escaneadas com Tesseract OCR (português e inglês)
- 🖼️ PDF → Images — Extract each page as a PNG image
- 📝 PDF → Word — Convert PDF into an editable DOCX document
- 📊 PDF → Excel — Extract tables into an XLSX spreadsheet
- 📄 PDF → Text — Extract all text into a TXT file
- 🔒 PDF → PDF/A — Convert to archival standard (PDF/A-1b)
- 🔗 Merge PDFs — Combine multiple PDFs into one document
- ✂️ Split PDF — Separate each page into individual files
- 📦 Compress PDF — Reduce file size while preserving quality
docker run -p 5000:5000 ghcr.io/virgiliojr94/localpdf.io:latestgit clone https://github.com/virgiliojr94/localpdf.io.git
cd localpdf.io
docker build -t localpdf .
docker run -p 5000:5000 localpdfOpen: http://localhost:5000
git clone https://github.com/virgiliojr94/localpdf.io.git
cd localpdf.io
pip install -r requirements.txt
# Instale o Ghostscript e Tesseract no sistema
# Debian/Ubuntu:
apt-get install ghostscript tesseract-ocr tesseract-ocr-por tesseract-ocr-eng
python app.pyOpen: http://localhost:5000
- Flask - Framework web Python
- PyMuPDF - Manipulação de PDFs
- Pillow - Processamento de imagens
- python-docx - Manipulação de arquivos Word
- ReportLab - Geração de PDFs
- OpenPyXL - Manipulação de planilhas Excel
- PDF2Docx - Conversor de PDF para Docx
- Tesseract OCR - Reconhecimento óptico de caracteres
All files are processed locally on your machine. No data is sent to external servers — ever.
Contributions are welcome! See the contribution guide to get started.
Thanks to everyone who has contributed to this project! ✨
MIT License — free to use and modify.
⭐ If this project was useful to you, consider giving it a star on GitHub!