57fd6e5087f9b7ff9ee896dc60e71d73771fa3df
4 Commits
| Author | SHA1 | Message | Date | |
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MechaCat02
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9ab5aba6b3 |
feat(sync): protocol 2 — hydration, a counter not a clock, no silent shrinking
The reworked bundle's PORT.md makes row-level last-write-wins conditional
on three gates, each learned by losing real data. The port's sync broke
all three, and had four more ways to lose or stall work. Both ends change,
so this is one protocol version, refused by the other side if mismatched.
Gate 1, hydration. A device now pulls every page the server holds before
it may push anything; it used to push first. The 14 Sep laptop — a
week-old copy re-stamped at boot and pushed over a week of phone work —
is now a test, and the phone's week survives it. Boot writes nothing
syncable either: the lesson opens with the app's own words (the artifact's
seeded turn) and waits for Start, instead of stamping a reply and a
progress edit before a server can even be configured.
Gate 2, a counter. Every row remembers the change_seq it last agreed with
(base_seq). The server applies a write only if that still matches —
compare-and-swap under an advisory lock — and otherwise returns its copy
as a conflict. No clock is compared anywhere: a device an hour fast used
to win every conflict for an hour, and a slow one's newer edit was
silently dropped with HTTP 200. dirty and rev replace the timestamp
watermark, which lost edits whenever a clock moved backwards.
Gate 3, no silent shrinking. A conflict is settled by what each copy
holds (sync/resolve.ts): more reviews, more evidence, a finished unit, the
further roadmap position, the union of learned grammar. A deliberate
shrink is explicit: a reset or a cleared lesson raises a marker every
device obeys, including its own unsynced edits, so a reset is not undone
by a device that had not heard of it. Trimming the transcript is local
and tombstones nothing — it used to delete the other device's turns.
Also fixed on the way:
· keys travel as JSON arrays — a space in 몇 명 used to stop every
device's pull at that row, permanently;
· pulls take a shared lock against pushes, so a change_seq committed
out of order can no longer be skipped;
· study_log and peek are per device and summed, so two devices' reviews
of one day both count;
· each user's data has an epoch; a server that lost it is detected,
and the device re-hydrates and offers its data back;
· a protocol-1 client is refused with 426 rather than half-understood.
Migration 9 adds the columns, re-keys the counters and tombstones; the
server drops protocol-1 rows once (none were deployed). Verified: 14
two-device scenarios against a real Postgres, and two browser profiles
syncing a lesson through the UI.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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MechaCat02
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074f602494 |
feat(server): an OpenAI-compatible backend, so the model is yours to pick
HANKAN_TUTOR_BACKEND=openai talks to anything serving /chat/completions -- LM Studio, Ollama, llama.cpp, vLLM, LiteLLM, OpenRouter, OpenAI. The TutorBackend seam already existed for this, so the model becomes a config line rather than a code change. Written against fetch rather than the openai package. The Anthropic SDK alone is 14MB in the image, this backend uses one endpoint with no tools and no retries, and local servers are the ones most likely to deviate from an SDK's expectations. The real risk in hand-rolling it is SSE reassembly, so that is where the tests are: a JSON payload split across two TCP reads, an event whose blank-line terminator lands in the next read, heartbeat comments, CRLF framing, and a stream that ends without [DONE]. The two split cases both fail against a naive per-read parser, which is what makes them worth having. <think> blocks are stripped from the stream, tags split across chunks included. Reasoning models served locally often emit chain-of-thought inline in `content` rather than in a separate field, and left in it lands in the lesson transcript where the block parser reads it as prose. WHAT THIS COSTS: prompt caching. The Anthropic backend marks the ~12k character gate as a cached prefix, so every turn after the first reads it at a fraction of the input price. There is no portable equivalent, so against a paid hosted endpoint the system prompt is re-billed every turn -- the biggest cost lever in the design, gone. Against a local model it costs nothing, and the shape still pays: llama.cpp and LM Studio reuse their KV cache for an unchanged prefix. Measured on a 6,948-character prompt against gpt-oss-20b, first token 1,563ms cold and 324ms warm, so the system prompt goes first and stays put here too. Verified against LM Studio running openai/gpt-oss-20b, not only a fake: a turn streams from the browser through this server to the model and back, rendered in the chat, no page errors. Also makes test/server/http.test.ts backend-agnostic. It asserted the echo backend's wording and so failed the moment the server was pointed at a real model -- precisely the case a transport test should survive. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> |
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MechaCat02
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b48a5f8fb1 |
fix(server): CORS, without which the phone could never reach the Pi
The Android build always talks to the Pi cross-origin -- a Capacitor webview serves the app from http://localhost, not from your domain -- so the browser sends a preflight OPTIONS first. It is not permitted to attach an Authorization header to that. Auth ran before anything else, so the preflight came back 401 and the real request was never attempted. There were no Access-Control-Allow-* headers either, so even a successful preflight would not have helped. Verified from an actual page before the fix: GET /api/sync and POST /api/tutor both "Failed to fetch" -- an opaque network error that points at the network rather than at middleware order. CORS now runs first and answers OPTIONS itself. Any origin is allowed by default, which is not a hole: the gate is a bearer token rather than a cookie, so a hostile page gains nothing from being allowed to send a request it cannot authenticate. HANKAN_ALLOWED_ORIGINS narrows it. backends/echo.ts is a keyless backend that reflects the request back in chunks. Deploying involves a container, a reverse proxy, a token, CORS and an SSE stream that has to survive compression -- five things that break independently, none of which involve Anthropic. HANKAN_TUTOR_BACKEND=echo proves all five from the phone before a key exists and before anything is billed. CI now runs the server that way, so the tutor endpoint is exercised over real HTTP rather than only against an injected mock. test/server/http.test.ts covers the preflight, the allow-origin header on real responses, Vary: Origin, that a bad token is still refused, and that the SSE stream parses and terminates with a done event. Verified end to end in a browser: the Pi configured through the settings panel, sync pushing 2 rows and a second sync moving 0 (the pushedAt watermark holding), the header switching from "local stand-in" to "connected", and a turn streaming back over SSE with the 8,859-character system prompt intact. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> |
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MechaCat02
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66f92247d2 |
feat(tutor): the real endpoint, streamed, with the system prompt cached
POST /api/tutor takes the assembled system prompt, the transcript the
client owns, and the new message, and streams tokens back. It holds
nothing between requests, so a dropped connection costs one turn rather
than the conversation.
The seam moved first: Sample took the assembled prompt as messages[0] with
role user. It now has an explicit system field, which is what lets the
backend put it in the API's system parameter as a cached block. The gate
is ~12k characters and is byte-identical for as long as the learner stays
in one unit, so every turn after the first reads the prefix at a fraction
of the input price. That is the single biggest cost lever in the design,
and it was unreachable through the old shape.
prompt/tutor-system.md still ships unchanged; only where the string is
placed changed.
SSE has three rules that are silent when broken, and all three are
handled: every event ends with a blank line, payloads are JSON-encoded
because a raw newline in Korean text would break the framing, and a `:`
heartbeat every 15s keeps intermediaries from timing the stream out.
Cache-Control is set on the returned Response rather than inside
streamSSE, which writes its own and would overwrite it; `no-transform` is
there because compression, not buffering, is what usually makes SSE look
like it hangs behind a proxy.
The client uses fetch + getReader, not EventSource — EventSource cannot
POST, and the body is {system, history, message}. Aborting closes the
connection, the server aborts upstream, and a cancelled turn stops
billing. With no server configured the app falls back to the stub, so the
offline build is untouched.
backends/anthropic.ts is the default. backends/agent-sdk.ts is deliberately
unimplemented and documents why the plain API was chosen over PORT.md's
Agent SDK — chiefly that its prompt accepts only user-role messages, so
the transcript would have to be flattened into a single turn.
The endpoint's own tests use a mock backend and need no API key.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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