Notolog is an open-source Markdown editor built with Python and PySide6, featuring AI-powered assistance and local-first privacy.

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pip install notolog
notolog  # Launch the app

pip install "notolog[llama]"

conda install notolog -c conda-forge

git clone https://github.com/notolog/notolog-editor.git
cd notolog-editor
python3 -m venv notolog_env && source notolog_env/bin/activate
pip install .
python -m notolog.app

• Markdown Editor - Real-time syntax highlighting in edit mode (implemented specifically for Notolog), live preview, adaptive line numbers, code blocks
• AI Assistant - Supports: OpenAI API, ONNX Runtime GenAI (local), and llama.cpp (local, GGUF models)
• File Encryption - PBKDF2HMAC key derivation with Fernet (AES-128 CBC mode) for optional file encryption
• Multi-Language - 19 languages supported
• Customizable - 6 built-in themes
• Cross-Platform - Windows, macOS, Linux

See the User Guide for complete feature documentation.

• Python 3.10+ (python.org)
• 4 GB RAM minimum (8+ GB for local AI models)

Using a virtual environment is recommended:

python3 -m venv notolog_env
source notolog_env/bin/activate  # Linux/macOS
notolog_env\Scripts\activate     # Windows
pip install notolog

For detailed instructions including conda and Debian packages, see Getting Started.

Notolog supports three AI backends:

• OpenAI API - Cloud-based inference via OpenAI-compatible endpoints
• On-Device LLM - Local inference using ONNX Runtime GenAI (e.g. Phi-3, Llama)
• Module llama.cpp - Local inference with GGUF quantized models (e.g. Llama, Mistral, Qwen)

See the AI Assistant Guide for setup instructions.

git clone https://github.com/notolog/notolog-editor.git
cd notolog-editor
pip install -e .
python -m notolog.app

Run tests:

python dev_install.py test
pytest

See CONTRIBUTING.md for guidelines.

Notolog is open-source software licensed under the MIT License.

This project uses third-party libraries, each subject to its own license. See ThirdPartyNotices.md for details.

Notolog prioritizes data protection and user privacy:

• Encryption: File encryption (optional) uses PBKDF2HMAC key derivation with Fernet (AES-128 CBC mode).
• Auto-Save: Changes are saved automatically to prevent data loss.
• Privacy: No telemetry or tracking. Local-only AI inference options available.

For vulnerability reporting, see SECURITY.md.

This project integrates third-party AI services and libraries:

• OpenAI API: Users are required to supply their own API keys and adhere to OpenAI's applicable terms, policies, and API documentation.
• ONNX Runtime GenAI: Used for local ONNX model inference. More info: onnxruntime-genai
• llama.cpp: Used for local GGUF model inference via llama-cpp-python.

Notolog is developed independently and is not affiliated with these organizations or projects.

• Compliance: Users are responsible for ensuring their use complies with applicable laws and regulations.
• Liability: The developers disclaim liability for misuse or non-compliance with legal or regulatory requirements.
• Trademarks: All trademarks and brand names are the property of their respective owners and are used for identification purposes only.

⭐ If you find Notolog useful, please consider giving it a star on GitHub!

This README.md file has been crafted and edited using Notolog Editor.