v0.5.0

Retrieval that needs no model at all, videos read from their subtitles, and a site that explains the whole thing.

Retrieval on its own

• POST /api/search returns the passages without writing an answer over them, so whatever called it can write instead. In lexical and exact, retrieval is pure SQLite: no model is involved, nothing to install, nothing called. hybrid and semantic still turn the question into a vector, which needs the embedding engine.
• Both local endpoints carry a text field holding the result ready to read, so a shortcut can show one value instead of walking an array. On /api/ask it is the answer with its sources listed underneath; on /api/search it is the passages themselves, each under its source and locator.

Videos

• A URL whose subtitles already exist is read from them instead of being downloaded and transcribed. An hour of video becomes text in seconds, and an author's own subtitles carry punctuation, which cuts into passages far better than a small transcription model.
• Subtitles a platform generated by machine are accepted only if you ask: the setting sits under Sources, off by default, because they carry no punctuation.
• Requests to the platform are retried with spaced out waits. A rate limit no longer fails the import.

Engines

• The embedding engine is a switch rather than a word to type. Leaving it reveals the address of your own server, prefilled.
• A curated embedding model that is not downloaded yet is now said plainly, with a button to install it, instead of failing when a source is queued against it.

Site and wiki

• A presentation site lives in docs/, in English and French, published at infinition.github.io/langolier. No CDN, no webfont, no analytics, and a strict content security policy.
• The wiki is part of it, generated from the markdown in wiki/ by scripts/build-wiki.py, so the pages and the repository never drift apart.
• The sidebar carries three links: the site, the source, and the tip jar.

The creature

• The mark in the sidebar is the Langolier itself. It breathes, follows the pointer, and swallows documents while sources are being read, transcribed or vectorised. Clicking the one at the top feeds it.

Assets

Installers for macOS (universal .dmg), Windows (.exe) and Linux (.deb, .rpm, .AppImage), plus chatbot-runners-*.zip holding the launchers used by exported chatbots.

macOS builds are ad hoc signed. On first launch, right click the app and pick Open.