karti-ai
408ce4a525
The site does no live inference. Rollouts are captured once against spark-1 and replayed at their recorded wall-clock — a public demo with no auth cannot hold an API key, and a recorded run can be scrubbed, permalinked, blind-compared and verified in ways a live one cannot. What stops it being a video is that the browser re-derives every number from the recorded moves. verify_fixtures.py is the Python half of that: it replays every committed fixture through the engine and reproduces its own rewards. All 16 land at delta 0.0. A fixture that cannot be regenerated is a claim with no receipt. First real measurement, thinking off, 8 seeds: solved 0/8. The model repeats guesses it has already played, invents words (trape, slith, postt, boomy), and contradicts its own feedback — consistency 0.09 to 0.17. That is the published failure taxonomy showing up in our own data on the first run, and it is why `consistency` is a reward component rather than a footnote. A capture failure is recorded as a turn with a null reply, never dropped. A capture that silently discarded failed turns would be reporting a better model than the one that ran. CI gates both halves and four things that fail silently in production: the word lists must rebuild byte-identically, the prerendered routes must carry their own baked og tags (crawlers do not run JS, so without them every shared link previews as the homepage), no blob: URL may reach the bundle (the site's CSP has no worker-src, so it falls back to default-src 'self' and a blob worker is blocked with no error), and the conformance digest must match across languages. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_019mt6sHQHEnEYrJZvoMCJSB
84 lines
1.9 KiB
JSON
84 lines
1.9 KiB
JSON
{
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"runId": "solver-s4",
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"seed": 4,
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"model": "entropy-solver",
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"capturedAt": "2026-08-28",
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"rewards": {
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"solved": 1.0,
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"economy": 1.0,
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"consistency": 1.0
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},
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"metrics": {
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"guesses_used": 4.0,
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"rejected_replies": 0.0,
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"reference_depth": 4.0,
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"turns_granted": 6.0,
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"inconsistent_guesses": 0.0
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},
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"truncated": false,
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"outcome": "solved",
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"answer": "divot",
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"turns": [
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{
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"reply": "[tares]",
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"reasoning": null,
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"call": {
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"promptTokens": null,
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"completionTokens": null,
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"reasoningTokens": null,
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"durationMs": null,
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"finishReason": "generated"
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},
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"info": {
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"guess": "tares",
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"observation": "T A R E S\nY X X X X\n\nYou have 5 guesses left."
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}
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},
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{
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"reply": "[count]",
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"reasoning": null,
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"call": {
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"promptTokens": null,
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"completionTokens": null,
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"reasoningTokens": null,
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"durationMs": null,
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"finishReason": "generated"
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},
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"info": {
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"guess": "count",
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"observation": "C O U N T\nX Y X X G\n\nYou have 4 guesses left."
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}
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},
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{
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"reply": "[pivot]",
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"reasoning": null,
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"call": {
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"promptTokens": null,
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"completionTokens": null,
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"reasoningTokens": null,
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"durationMs": null,
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"finishReason": "generated"
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},
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"info": {
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"guess": "pivot",
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"observation": "P I V O T\nX G G G G\n\nYou have 3 guesses left."
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}
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},
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{
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"reply": "[divot]",
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"reasoning": null,
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"call": {
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"promptTokens": null,
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"completionTokens": null,
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"reasoningTokens": null,
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"durationMs": null,
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"finishReason": "generated"
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},
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"info": {
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"guess": "divot",
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"observation": "D I V O T\nG G G G G\n\nYou have 2 guesses left."
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}
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}
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]
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}
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