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Is there a memory book for humans?
LLMs (AI) have limited context windows which makes it challenging to include all necessary context in the prompt. A common solution is a memory book.
The memory book stores arbitrarily large amounts of text (typically past conversations as well as reference material like wikipedia articles), segmented in some way (sentence, paragraph, etc). When you type in a prompt, it uses a dumb text similarity metric (like cosine similarity) to retrieve the most relevant snippets and attaches them to your prompt for the AI's benefit. Cosine similarity has low precision but decent recall, so while not all passages it finds will be relevant, if there is something relevant it will end up as a hit, and the AI can sort them out on its own when doing more sophisticated processing of the prompt.
This sounds like a very useful thing when writing notes, even without an AI. Is there any program intended for human use (GUI or CLI) which can scan my notes, build a database, and retrieve relevant passages easily based on some rough text similarity measure? (not just keywords - eg. cosine can deal with synonyms)
Inspired by https://rpg.codidact.com/posts/285850
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Not a real answer, but may be interesting: Silly Tavern includes a memory book
Of course, Silly Tavern is a frontend for talking to AIs. So passages from the memory book will be shown to the AI, not you. There are various ways you could see them anyway (view full prompt, ask AI to repeat them) but I wouldn't call it user-friendly unless you intend to use AI for your note taking.
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The following users marked this post as Works for me:
| User | Comment | Date |
|---|---|---|
| matthewsnyder | (no comment) | Mar 17, 2024 at 18:14 |
There are many vector search libraries and engines for use in machine learning, apis, databases, and programs. https://github.com/currentslab/awesome-vector-search has a list of some of them.
For example, Semantra seems to fit your requirements. It is a command line tool with a local web server. You can run it to index your text and pdf files and search your documents with the web interface, "by meaning rather than just text" as they claim.
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