v1.1.0
4
Commits
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 JesseMarkowitzandClaude Opus 5
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144406cd48 |
M11: what the server will actually read
The release-validation milestone, and the thing it had to settle first was whether any of the earlier evidence meant what it said. M8 measured a deployment enforcing a 4,096-token input window while the application budgeted 16,384. Every request returned 200. What Ollama does with the excess is drop the oldest tokens, and the oldest tokens here are the system block — the narrator's rules and the campaign canon. A hundred-turn certification against that server would have looked perfect and proved nothing, which is why this milestone could not begin with a hundred turns. So the application asks now. Ollama's window is a property of how a model was loaded rather than of the request — sending num_ctx is accepted, ignored, and worse, reloads the model at the server's own default — so the only honest move is to find out and then tell the truth about it. /api/ps reports what a resident model is being served with, /api/show what an unloaded one will load with, both on the same host inference already uses, through the same endpoint policy and the same TLS trust store. A verified window is a ceiling on the budget; an unverified one leaves the budget alone and is recorded as unverified in the turn's own provenance, so an old turn can be asked afterwards whether it was built against a checked window. There is no third behaviour, and in particular no hard-coded 4,096: a number the server did not say would be right on one machine and wrong on the next. The proof that this is doing something is a campaign whose canon sits at the front of the prompt, 120 turns of history, and a 4,096-token window. The canon is still there afterwards and the oldest history is gone. The same campaign built the old way produces a prompt more than twice the window — the defect, reproduced, so the fix is measured against it rather than asserted. Two defects the validation found on its own, and they are the same defect twice: something was true and nobody was told. A manual state correction of four changes with one bad reference applied three, returned 201, and said nothing — while recording the refusal on the audit row nobody reads. It came to light because the identity diagnostic's own fixture was refused that way and the whole run proceeded on a campaign with no scene, which would have read as a model failure. And the narration-length setting moved no number: brief, medium and long each became one English sentence, while the numeric hint the model actually reads was derived from the global reply cap and said the same thing for all three. Both now say what they did. The other two post-M8 findings are closed as well. The tab said AI D&D, which no document had ever claimed it did not; it says Interactive Story now, with the open campaign first, and the name is the owner's decision rather than a find-and-replace to something narrower than the engine. After an Undo the reader could not tell where they had landed; the control row now ends with "Moment 11 · later story ahead", from the server's own answer, in the word the transcript already uses, with none of head, branch or depth anywhere near it. The identity diagnostic exists and the root cause does not. That campaign was destroyed, so no cause can be established — what M11 owes the finding is something that can classify the next occurrence, and a diagnostic that makes only the judgements a program can honestly make: duplicate keys, shared names, protagonist drift, state and context disagreeing. Whether prose misattributed a line is left to a person reading it beside its prompt, because a regex cannot read dialogue and one that pretended to would produce exactly the confident wrong answer this finding is about. Its detectors are proved to fire against a planted second Alice. Two entities may still share a display name. That was checked first, as the finding asked, and left permitted: a mother and a daughter, or a stranger giving a false name, are ordinary fiction, and refusing them to guard against a model mistake would refuse the wrong thing. What was missing was that it happened silently. It is reported now. Evidence, not inference: a hundred accepted turns against a real narrator with genuine process restarts; a real browser against the built SPA; a container with no network at all; a campaign moved into a data directory that never existed. Each was discarded and re-run whenever the product changed under it, and the runs that were thrown away are listed in the report with the reason, along with ten defects in the harnesses themselves — because a harness that has only ever agreed with itself is not evidence, and two of M8's five harness defects were masking real ones. No dependency was added, removed or upgraded. No acceptance test was retired, relaxed or reclassified. M11 is implemented and verified; it is not accepted, and there is no release tag. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Qyn3oRd4D6pi72nKBG725B |
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JesseMarkowitzandClaude Opus 5
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c1a73b3d77 |
M1: make the first story turn work with no Internet
Phase 0B ran the upstream application on a network with no route out and the first turn died in tiktoken, which downloads its BPE table the first time anything counts a token. The browser separately fetched three font families from Google on every page load. Neither is visible on a machine that has been online once, which is why both now have tests. The tokenizer table is vendored at backend/app/context/vendor/cl100k_base.tiktoken and backend/app/context/encoding.py builds the encoding from it directly, verifying its SHA-256 against the digest tiktoken itself pins for that URL. No code path in the tokenizer can reach the network any more — not a warm cache, not an environment variable a deployment could forget. The encoding was checked token for token against tiktoken's own. The three font families are self-hosted as variable fonts under frontend/public/fonts/ (343 KiB, Latin and Latin Extended), declared in frontend/src/styles/fonts.css, and re-vendored by frontend/tools/vendor_fonts.py. Their OFL licences ship beside them. With no remote asset left, the CSP drops both Google hosts and gains object-src, base-uri and form-action; woff2 also gets its real media type, which Python's table lacks on a slim image. A trusted-LAN Ollama turned out not to work at all over HTTPS. httpx verifies against the certifi bundle, so an endpoint whose certificate comes from a CA the user installed on their own machines — a StartOS server's Ollama, for one — was refused with CERTIFICATE_VERIFY_FAILED while curl and the browser on the same host accepted it. app/tlstrust.py builds one context that unions the platform CA store with certifi's, and all four outbound clients use it. A union rather than a swap, so an image with an empty system store cannot start failing on endpoints that worked before. Verification itself is untouched: CERT_REQUIRED, hostname checking on, and no insecure escape hatch. The storyteller listener is now loopback by explicit statement rather than by inheriting uvicorn's default: start.sh, start.ps1, and docker-compose.yml, which publishes to 127.0.0.1 rather than every interface. Reaching an Ollama on another machine is outbound and needs none of that inbound exposure. backend/requirements.lock pins the exact tested closure; requirements.txt keeps the ranges. DEVELOPMENT.md covers setup, the same-host and trusted-LAN Ollama configurations, and how to re-run the offline proof. PROVENANCE.md records the upstream commit, the MIT terms, and both vendored assets. Verified, not just compiled. On an --internal Docker network with 1.1.1.1 unreachable and no name resolving, a campaign was created and played for six turns through same-host Ollama, restarted, and resumed. A second run played ten turns through Ollama on a separate physical machine on the LAN over verified HTTPS, summaries and embeddings included, with the storyteller's default route deleted so the LAN was reachable and the Internet was not. Its capture: 893 packets to the approved host, 730 loopback, zero anywhere else, and zero DNS queries. Two induced model failures left the accepted story bit-identical. The inherited SPA was opened in a browser and a campaign read back from it. Evidence is in planning/reports/M1-BASELINE-REPORT.md, along with the findings that did not belong in this change. 648 backend tests pass, up from the inherited 632; frontend lint and build are clean; the image builds. No M2 work is included: the hosted, cloud, analytics, Postgres and scripting surfaces are untouched. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_017foPNqFjAJa2Ngebf5mEfL |
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Claude
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544c599a5a |
Keep the composer above the on-screen keyboard on the first tap
Both composers are position:sticky;bottom:0, which pins them to the bottom of the *layout* viewport. A phone keyboard does not shrink that viewport -- it only covers it -- so the first tap on the input left the box sitting behind the keyboard. Tapping back and focusing again appeared to work only because the page had been scrolled during the first attempt, so the browser's scroll-into-view landed somewhere else. Two engines, two halves: - Chromium honours interactive-widget=resizes-content on the viewport meta, which makes the layout viewport shrink when the keyboard opens, so 100dvh and sticky bottoms account for it on their own. - iOS Safari ignores that flag and only shrinks the visual viewport, so measure the covered height from visualViewport and publish it as --kb-inset; the composers offset their sticky bottom by it. On browsers that already resized the layout viewport the measurement is ~0, so the same rule is a no-op there instead of a double lift. The pages also gain a matching bottom margin so the last beat can still be scrolled clear of a lifted composer. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_011BC7Dsg4gSQm3NLcZcG5SK |
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parththakkar106andClaude Fable 5
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db9f904222 |
Initial commit: AI Dungeon clone (FastAPI backend + React frontend)
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01KFsGHju9szibJJa2YJcdbg |