I started building AI for notes to help me chat with my library of notes. The result of that exploration is org-ai—my one of one software that helps me remember what I’ve previously written, summarize information. Under the hood it uses vector-based similarity search and LLMs to extract useful information from my zettelkasten in a chat-based interface.
See also:
- Context is needed for practical LLM applications
- How langchain works
- Why vector databases are important to AI
Links to this note
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It’s useful to think about the underlying utilities that go into running one’s life and business with the same rigor used to build something significant. Afterall, the things we rely on every day can have an outsized impact on our own performance so why not treat it that way?
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I built org-ai using Python which exposes a chat interface through a simple CLI. This makes it a bit clunky when using it from Emacs—I would need to open up an instance of a terminal, activate the virtual environment, and execute the program to start the chat.
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I would guess that a significant amount of software is written for one person and we should celebrate it more.