How I Built a Local AI Assistant for Obsidian

A naukri.com initiative

New

How I Buil...

Medium

314

Image Credit: Medium

Obsidian has become a popular tool for managing knowledge in a local-first manner.
Many existing AI integrations with Obsidian require API keys and rely on cloud services, compromising privacy and control.
To address this, a local AI assistant was developed, focusing on privacy, control, and offline usability.
The project aimed to create a fast, offline AI assistant for note-based workflows without cloud dependencies.
The assistant is implemented as a Python CLI tool that loads a local model and executes queries locally.
Installation is straightforward, requiring only Python 3.6+ and pip, with no need for internet connectivity post-setup.
Use cases include local note summarization, semantic search, writing assistance, and offline research support.
The assistant respects privacy, operates instantly, is hackable, and works in air-gapped environments.
Challenges in development included managing model size, memory execution, antivirus concerns, and balancing simplicity with functionality.
Future plans include adding features like ChromaDB-powered search, model flexibility, prompt templates, an Obsidian plugin bridge, and a GUI launcher.

Read Full Article

18 Likes

For uninterrupted reading, download the app