Ships

Local AI: two-pass turns, prompt budgeting, moods, activation memory, and a bridge for a second AI

Local AI: a Tools tab, an alarm, a calendar, and an installer that installs

Local AI download button: correct the installer size in the comments

Local AI: stop packaging previous builds inside the app

Local AI: she notices your goals instead of you filling in a form

Local AI: tell her what she is, and stop the loop erasing her context

Local AI: a loop, so she can speak without being spoken to

Local AI: speak the first sentence immediately, accept the risk of a gap

Local AI: measure the real synthesis speed, and size pieces to it

Local AI: speak the reply while it is still being synthesised

Gate the Local AI installer download behind login + a per-IP quota

Local AI: gate the download, fix cut-off replies, and fix speech on long text

Local AI: a working suite on first launch — voice in, voice out, personas, memory

Local AI: a Hearing tab — manage the speech-to-text models, like Models does for LLMs

Local AI: a voice button that can't act now says why, instead of sitting there disabled

Local AI: ignore the release-next build folder (built when the app is running and locks release/)

Local AI: refuse to package over a running install instead of destroying it

Local AI: make "add a voice" the recording workflow, not a WAV-and-type-it-yourself form

Local AI: voice models were downloading to the system drive, ignoring the Model cache folder

Local AI: make voice setup actually installable — two dependency traps that both exit 0

Local AI: build a reference voice from any recording, and split video IPC out of main.ts

Local AI: a repeat tool for single probes, and one shape for reading results

Local AI: Voices tab — load and test speech models, starting with NeuTTS Air

Local AI: stop a battery at the first fatal model error instead of failing 8 probes

Ship the Local AI download fix that the previous deploy skipped

Local AI: fix the download 403, ship a current build, update public copy

Local-harness: ignore release-ship/ (distribution build output, same as release/)

Local AI download: fix the 403, ship a current build, and update the public copy

Local AI: Models + System tabs, a permanent test ledger, and a working video backend

Chat avatar: fix unnatural head tilt while floor-sitting — replace a ±25° single-sine head roll (metronome wobble) with subtle breathing + a gentle multi-frequency sway (~±3°)

Reframe Local AI + assistant everywhere: /ai-probe page (harness-first), llms.txt, chat-systems.md (chat-first, room/VR opt-in, companion->assistant), CLAUDE.md North Star, changelog label -> CommsLink Local AI

AI Probe API: expose capability probe suite (navigation/reasoning/knowledge/reflection/instruction/tool-use) via /exam?type= + /grade; single-source generators into shared recallBench lib

AI Probe: local analysis suite (9 probes, hub, capability matrix) + /ai-probe page reframe with desktop-tool download

AI Memory Probe: auto-generate a unique exam every request. New services/web/lib/recallBench/generate.ts — a seeded, deterministic generator builds a long conversation (~480 turns / ~42 questions at the default level) of randomized, un-guessable facts (invented names/numbers/places), with mid-convo updates and same-category distractors so binding is hard. GET /exam mints a random id and returns turns+questions (key withheld); POST /grade REGENERATES the identical exam from that id to score — stateless, nothing stored, no exam reusable. Replaces the fixed 8-question demo. Levels 1/2/3 scale length+density. Page shows a small generated preview. +5 generator tests; 887 pass

AI Probe: fix /recall-bench redirect — use a next.config 308 (real Location header) instead of a page-level redirect() that prerendered into a broken cached 307. Add /ai-probe to the no-store list so the live-iterated tool isn't cached for a year

Rebrand Recall Bench -> CommsLink AI Probe (the AI Memory Probe). It's now API-first: a self-diagnostic an AI runs on itself, not a human playground. Page /ai-probe leads with API access (mint key + pastable instructions) and shows a sample exam below; removed the memory-strategy picker + reference-strategy runs. Route /recall-bench 301-redirects to /ai-probe. API paths renamed to /api/v1/ai-probe/* with /api/v1/recall-bench/* kept as aliases (earlier keys still work) via a route factory. Landing card, llms.txt, changelog classifier updated; 885 tests pass

Recall Bench: attach the session token to authed calls. The API-key panel now gates on useSession().isLoggedIn (not a bare 401), and both key management and the real-model Run send Authorization: Bearer <token> — signed-in users can mint keys and run models instead of seeing the sign-in prompt / a 401

Recall Bench: sign-in link carries returnUrl=/recall-bench so login sends you back here instead of the 'which app?' picker

Recall Bench API — external AIs can take the memory test themselves. Sign in at /recall-bench, mint a clb_ key (reuses the user_pat store with a new recall:run scope — no migration, kept separate from Bench), and copy a pastable instruction block for any AI with web access. New endpoints: POST/GET/DELETE /api/v1/recall-bench/keys (session), GET /api/v1/recall-bench/exam + POST /api/v1/recall-bench/grade (session or key). The exam serves the conversation + questions with the answer key WITHHELD; grading is deterministic (no LLM, no credits — the AI brings its own compute). core/actions/recallBench/{patsAction,examAction}; ApiAccess component; llms.txt documents the endpoints; +3 tests

Recall Bench (/recall-bench): live conversational-memory benchmark on the landing page. An AI overhears a scripted conversation one line at a time, then is quizzed on planted facts at increasing distance; grading is deterministic exact-match, so no AI judges an AI. Free reference strategies (perfect/none/fixed-window) run in-browser; real models (Grok/Claude) run server-side via POST /api/v1/recall-bench/run and cost credits. Pure engine in services/web/lib/recallBench shared by the page + api (COPYd into the api image like lib/bench); recall-vs-distance curve + static/update/distractor sub-scores. Adds classifier PATH_RULE, llms.txt entry, landing card, and tests