Document Library

Document Library

The library is Draggy's answer to "what does my lease say about pets". You point it at a folder, it indexes the contents locally, and from then on questions that look like they are about your own material get searched there before the web.

Nothing is uploaded. Indexing runs against your local Ollama, and the index lives in the same SQLite database as your chats.

Indexing a folder

Settings → Library → Add folder. Pick a directory and Draggy walks it, extracts text from what it recognises, splits it into passages, and computes an embedding for each one. Progress is shown per file.

Large folders take a while — this is a model running over every paragraph you own. It is a one-time cost per folder, and you can keep using Draggy while it runs.

You can add several folders. Each is listed with how many files and passages it contributed, and each can be removed on its own without rebuilding the rest.

The embedding model

Picked from your VRAM, the same way the talk model is — see Choosing a Model. Bigger cards get a model that embeds noticeably better, and the ladder can climb further per gigabyte than the chat or talk model does, because a passage is one forward pass through the encoder rather than one pass per generated word.

VRAM	Model
under 2 GB	All-MiniLM
2 GB	Nomic Embed Text
4 GB	MxBai Embed Large
8 GB	Qwen 3 Embedding 0.6B
16 GB	Qwen 3 Embedding 4B
24 GB and up	Qwen 3 Embedding 8B

The picker, in Settings → Personalization, works like the talk model's: Automatic at the top, then every embedding model you have installed. Pick one and it is remembered; delete it and Draggy quietly goes back to automatic rather than downloading it again behind your back.

If you do change it — by hand, or because automatic sized a different model to new hardware — the existing index becomes meaningless: embeddings from one model cannot be compared with embeddings from another. Re-index after switching, from Settings → Library.

How it gets used

When a question looks like it could be about your own files, the assistant calls search_library before search_web. It answers from the passages that come back and names the file each fact came from, so you can go and check.

If the library has nothing relevant it says so rather than inventing something, and offers to search the web instead.

You can also force it: ask "what do my notes say about X" and the intent is usually clear enough.

Getting better results

Structure helps. Documents with headings chunk into meaningful passages. A hundred-page PDF with no structure chunks into a hundred pages of soup.

Index less, not more. A folder of what you actually care about beats your entire home directory. Precision drops as the index grows, because there are simply more near-matches competing.

Check the file names in the answer. If it cites the wrong document repeatedly, the passages it is finding are probably too short to be distinctive.

Removing it

Settings → Library lists what is indexed, removes a single source, or clears everything. Clearing the index does not touch your actual files — Draggy only ever reads them.