taf-agent / js /main.js
karlexmarin's picture
v0.7.0: SWA Unmasker (anti-bullshit #1) + foldable main panels + preset auto-fill
fbec820
Raw
History Blame
108 kB
// TAF Agent — main orchestration (v0.2 — i18n + Profile + Compare)
//
// Phases:
// 1. Pyodide loads + TAF formulas → deterministic computation
// 2. WebLLM loads on demand → plain-English synthesis
// 3. Router (LLM) → free-form question → recipe + params
// 4. Modes: Profile (all recipes) + Compare (multi-model side-by-side)
// 5. i18n: EN/ES/FR/ZH
import { initI18n, setLang, t } from "./i18n.js";
import { initPhaseDiagram } from "./phase_diagram.js";
import { gammaCheckAll, REGIME_META } from "./gamma_check.js";
import { loadLeanManifest, badgeHtml, badgesForUiBinding, renderTheoremTable, getManifest } from "./lean_badges.js";
import { unmaskConfig } from "./swa_unmasker.js";
const TAF_BROWSER_URL = "python/taf_browser.py";
const ENABLE_WEBLLM = true;
// Smaller model = fits in default browser quota (~350MB vs 700MB for Llama-1B)
const WEBLLM_MODEL = "Qwen2.5-0.5B-Instruct-q4f16_1-MLC";
const WEBLLM_FALLBACK = "SmolLM2-360M-Instruct-q4f16_1-MLC";
const $ = (id) => document.getElementById(id);
const state = {
pyodide: null,
webllm: null,
presets: [],
recipes: [],
recipesById: {},
currentMode: "ask",
currentRecipe: null,
};
const EXAMPLES = [
"Will Meta-Llama-3-8B handle 32000-token NIAH retrieval reliably?",
"I have $5000 to spend on training. What model can I afford?",
"Should I use Mistral-7B-v0.1 at 16K context or extend it first?",
"Compare cheapest GPU to serve Llama-3-8B at 10 million tokens per day.",
"Should I use soft KV decay or hard cutoff for Qwen2.5-7B at 32K?",
"Is it cheaper to train an 8B custom model or use GPT-4o for 50M tokens/month?",
];
// ════════════════════════════════════════════════════════════════════
// Bootstrap
// ════════════════════════════════════════════════════════════════════
function showLoadingBar(show, progress=null) {
const wrap = $("loading-bar-wrap");
const bar = $("loading-bar");
if (!wrap || !bar) return;
if (!show) { wrap.style.display = "none"; return; }
wrap.style.display = "block";
if (progress === null) {
bar.classList.add("indeterminate");
bar.style.width = "100%";
} else {
bar.classList.remove("indeterminate");
bar.style.width = `${Math.min(100, Math.max(0, progress * 100))}%`;
}
}
async function loadPyodideAndTaf() {
showLoadingBar(true, null);
setStatus(t("status.loading_pyodide"));
state.pyodide = await loadPyodide({
indexURL: "https://cdn.jsdelivr.net/pyodide/v0.26.4/full/",
});
showLoadingBar(true, 0.5);
setStatus(t("status.loading_taf"));
const tafCode = await fetch(TAF_BROWSER_URL).then(r => r.text());
await state.pyodide.runPythonAsync(tafCode);
state.presets = JSON.parse(state.pyodide.runPython("list_presets()"));
state.recipes = JSON.parse(state.pyodide.runPython("list_recipes()"));
state.recipesById = Object.fromEntries(state.recipes.map(r => [r.id, r]));
showLoadingBar(true, 0.95);
populatePresets();
populateRecipes();
enableUI();
showLoadingBar(false);
setStatus(t("status.ready"));
}
function populatePresets() {
// Recipe form preset
["preset", "profile-preset"].forEach(id => {
const sel = $(id);
if (!sel) return;
sel.innerHTML = '<option value="">— select to autofill —</option>';
state.presets.forEach(p => {
const opt = document.createElement("option");
opt.value = p.id;
opt.textContent = `${p.label} (θ=${p.theta.toLocaleString()}, T_train=${p.T_train})`;
sel.appendChild(opt);
});
});
// Compare slot presets
document.querySelectorAll(".compare-preset").forEach(sel => {
sel.innerHTML = '<option value="">— or preset —</option>';
state.presets.forEach(p => {
const opt = document.createElement("option");
opt.value = p.id;
opt.textContent = p.label;
sel.appendChild(opt);
});
});
}
function populateRecipes() {
["recipe-select", "compare-recipe"].forEach(id => {
const sel = $(id);
if (!sel) return;
sel.innerHTML = '<option value="">— select a recipe —</option>';
state.recipes.forEach(r => {
const opt = document.createElement("option");
opt.value = r.id;
opt.textContent = `${r.id}${r.name}`;
sel.appendChild(opt);
});
});
}
function enableUI() {
$("ask-btn").disabled = false;
$("recipe-select").disabled = false;
$("preset").disabled = false;
$("profile-preset").disabled = false;
$("profile-btn").disabled = false;
$("compare-recipe").disabled = false;
$("compare-btn").disabled = false;
$("inspector-btn").disabled = false;
// Render community feed + falsification (independent of Pyodide)
renderFalsificationDashboard();
loadCommunityFeed();
// Restore from URL if present
parseUrlState();
}
function setStatus(msg) { $("status").textContent = msg; }
// ════════════════════════════════════════════════════════════════════
// Main-panel wrap: every <main> section gets a foldable details/summary
// shell at runtime so users can collapse any panel they don't need open.
// h2 is moved INTO summary so its data-i18n binding survives. Idempotent.
// ════════════════════════════════════════════════════════════════════
function wrapMainSectionsAsFoldable() {
document.querySelectorAll("main > section").forEach(section => {
if (section.id === "status-bar") return; // skip loading bar
if (section.querySelector(":scope > details.main-panel")) return; // already wrapped
const h2 = section.querySelector(":scope > h2");
if (!h2) return;
const details = document.createElement("details");
details.className = "main-panel";
details.open = true;
const summary = document.createElement("summary");
summary.className = "main-panel-title";
summary.appendChild(h2); // preserve h2 + its data-i18n + all children
details.appendChild(summary);
while (section.firstChild) details.appendChild(section.firstChild);
section.appendChild(details);
});
// Stop ⓘ tooltip clicks inside summaries from toggling the panel.
document.querySelectorAll(".main-panel > .main-panel-title .info").forEach(el => {
el.addEventListener("click", (e) => e.stopPropagation());
});
}
wrapMainSectionsAsFoldable();
// ════════════════════════════════════════════════════════════════════
// Mode toggle
// ════════════════════════════════════════════════════════════════════
document.querySelectorAll(".mode-btn").forEach(btn => {
btn.addEventListener("click", () => {
document.querySelectorAll(".mode-btn").forEach(b => {
b.classList.remove("active");
b.setAttribute("aria-selected", "false");
});
btn.classList.add("active");
btn.setAttribute("aria-selected", "true");
const mode = btn.dataset.mode;
state.currentMode = mode;
// Hide all mode sections
["ask-section", "recipe-section", "form-section",
"profile-section", "compare-section", "inspector-section",
"diagnose-section", "phase-section", "unmask-section"].forEach(id => {
const el = $(id);
if (el) el.style.display = "none";
});
// Show selected
const sectionMap = {
ask: "ask-section", recipe: "recipe-section", profile: "profile-section",
compare: "compare-section", inspector: "inspector-section",
diagnose: "diagnose-section", phase: "phase-section", unmask: "unmask-section",
};
const sectionId = sectionMap[mode];
if (sectionId) $(sectionId).style.display = "";
$("mode-desc").textContent = t(`mode_desc.${mode}`) || "";
if (mode === "phase") initPhaseDiagram();
});
});
// ════════════════════════════════════════════════════════════════════
// Diagnose mode: build the diagnose_model.py CLI command
// ════════════════════════════════════════════════════════════════════
function buildDiagnoseCommand() {
const model = ($("diag-model")?.value || "").trim();
if (!model) {
return "# Please enter a HuggingFace model id";
}
const theta = ($("diag-theta")?.value || "").trim();
const N = ($("diag-N")?.value || "2000").trim();
const local = ($("diag-local")?.value || "").trim();
const fast = $("diag-fast")?.checked;
const cpu = $("diag-cpu")?.checked;
const fourbit = $("diag-4bit")?.checked;
const parts = ["python cli/diagnose_model.py"];
parts.push(`--model ${model}`);
if (theta) parts.push(`--theta ${theta}`);
if (N && N !== "2000") parts.push(`--N ${N}`);
if (local) parts.push(`--local "${local}"`);
if (fast) parts.push("--fast");
if (cpu) parts.push("--cpu");
if (fourbit) parts.push("--load_in_4bit");
return parts.join(" \\\n ");
}
const _diagBuildBtn = $("diag-build-btn");
if (_diagBuildBtn) {
_diagBuildBtn.addEventListener("click", () => {
const cmd = buildDiagnoseCommand();
$("diag-cmd").textContent = cmd;
$("diag-output").style.display = "";
});
}
const _diagCopyBtn = $("diag-copy-btn");
if (_diagCopyBtn) {
_diagCopyBtn.addEventListener("click", async () => {
const cmd = $("diag-cmd").textContent;
if (!cmd) return;
try {
await navigator.clipboard.writeText(cmd);
_diagCopyBtn.textContent = "✓ Copied";
setTimeout(() => {
_diagCopyBtn.textContent = (window.t ? window.t("diagnose.copy_btn") : "📋 Copy to clipboard");
}, 1800);
} catch (e) {
_diagCopyBtn.textContent = "✗ Copy failed (browser blocks)";
}
});
}
// Make sure inspector section is hidden initially
const _inspectorSection = $("inspector-section");
if (_inspectorSection) _inspectorSection.style.display = "none";
// ════════════════════════════════════════════════════════════════════
// Recipe selector
// ════════════════════════════════════════════════════════════════════
$("recipe-select").addEventListener("change", (e) => {
const rid = e.target.value;
if (!rid) {
$("form-section").style.display = "none";
return;
}
const r = state.recipesById[rid];
state.currentRecipe = r;
$("recipe-desc-display").textContent = r.description;
$("form-section").style.display = "";
buildDynamicForm(r);
});
function buildDynamicForm(recipe) {
const container = $("dynamic-form");
container.innerHTML = "";
const defaults = getRecipeDefaults(recipe.id);
recipe.params.forEach(name => {
const div = document.createElement("div");
div.className = "form-field";
const labelWrap = document.createElement("label");
labelWrap.htmlFor = `param_${name}`;
labelWrap.innerHTML = paramLabel(name);
if (PARAM_TOOLTIPS[name]) {
const info = document.createElement("span");
info.className = "info";
info.innerHTML = `<span class="tooltip">${PARAM_TOOLTIPS[name]}</span>`;
labelWrap.appendChild(info);
}
div.appendChild(labelWrap);
const input = document.createElement("input");
input.type = "text";
input.id = `param_${name}`;
input.dataset.param = name;
input.value = defaults[name] !== undefined ? String(defaults[name]) : "";
div.appendChild(input);
container.appendChild(div);
});
$("run-btn").disabled = false;
}
function paramLabel(name) {
const labels = {
theta: "θ (rope_theta)", T_train: "T_train", T_eval: "T_eval (target context)",
n_attention_heads: "num_attention_heads", n_kv_heads: "num_key_value_heads",
d_head: "head_dim", n_layers: "num_hidden_layers", n_params: "n_params (e.g. 8e9)",
has_SWA: "Has SWA? (true/false)",
N_params: "N_params (e.g. 8e9)", D_tokens: "D_tokens (or empty for Chinchilla)",
gpu: "GPU", n_gpus: "n_gpus", mfu: "MFU (default 0.45)",
api_model: "API model to compare", monthly_tokens_M: "Monthly tokens (M)",
USD_budget: "USD budget", bytes_per_weight: "Bytes per weight (BF16=2)",
target_tokens_per_day: "Target tokens/day", concurrent_users: "Concurrent users",
};
return labels[name] || name;
}
const PARAM_TOOLTIPS = {
theta: "<strong>RoPE base frequency</strong>. From <code>config.rope_theta</code>. Higher = more long-range capacity. Typical: <code>10000</code> early models, <code>500000</code> Llama-3, <code>1000000</code> Qwen2.5.",
T_train: "<strong>Max context the model was trained on</strong>. From <code>max_position_embeddings</code>. The model has never seen positions beyond this; extrapolating much further usually fails.",
T_eval: "<strong>Your target inference context length</strong>. The key knob. The whole question is: will the model behave well at <em>this</em> length?",
n_attention_heads: "Number of query heads. From <code>num_attention_heads</code>.",
n_kv_heads: "Number of K/V heads. If &lt; n_attention_heads → model uses GQA (Grouped Query Attention). Smaller = more memory-efficient KV cache but pushes γ toward Hagedorn boundary.",
d_head: "Per-head dimension. Typically <code>hidden_size / n_attention_heads</code>. Common: 64, 80, 128.",
n_layers: "Number of transformer layers. From <code>num_hidden_layers</code>.",
n_params: "<strong>Total parameter count</strong>. Use scientific notation: <code>8e9</code> for 8B. Threshold ~400M is the induction-head emergence boundary (sign-flip in Δγ).",
has_SWA: "Sliding Window Attention. <code>true</code> for Mistral, gemma-2, phi-3. SWA lowers γ_decomposition by ~0.21.",
N_params: "Same as n_params. Total parameter count, scientific notation (e.g. <code>8e9</code>).",
D_tokens: "Number of training tokens. Leave empty to use Chinchilla 20:1 default (D = 20·N).",
gpu: "GPU model from the catalog. Options: H100 SXM, H100 PCIe, H200, B200, A100 80GB, A100 40GB, L40S, MI300X, RTX 4090, RTX 5090, RTX 5060Ti.",
n_gpus: "Number of GPUs in your training/serving cluster.",
mfu: "<strong>Model FLOPs Utilization</strong>. Realistic fraction of peak FLOPs achieved. Typical: 0.4-0.5 for well-tuned. Default 0.45.",
api_model: "Frontier API to compare against. Options: GPT-4o, GPT-4o-mini, Claude-Opus-4, Claude-Sonnet-4, Claude-Haiku-4, Gemini-1.5-Pro, DeepSeek-V3, Llama-3.3-70B (Together).",
monthly_tokens_M: "Expected monthly token volume <em>in millions</em>. e.g. <code>10</code> = 10 million tokens/month.",
USD_budget: "Your training budget in US dollars (no symbol). e.g. <code>5000</code> for $5K.",
bytes_per_weight: "Memory per parameter. BF16/FP16 = 2, INT8 = 1, INT4 = 0.5.",
target_tokens_per_day: "How many tokens/day you need to serve. e.g. <code>10000000</code> = 10M tokens/day.",
concurrent_users: "Simultaneous concurrent requests. Affects KV cache memory needed.",
};
function getRecipeDefaults(recipeId) {
const D = {
"X-1": { N_params: "8e9", D_tokens: "", gpu: "H100 SXM", n_gpus: 8, mfu: 0.45,
api_model: "GPT-4o", monthly_tokens_M: 10.0 },
"X-2": { theta: 500000, T_train: 8192, T_eval: 32000,
n_attention_heads: 32, n_kv_heads: 8, d_head: 128,
n_layers: 32, n_params: "8e9", has_SWA: false },
"X-3": { USD_budget: 5000, gpu: "H100 SXM", mfu: 0.45, n_gpus: 1 },
"X-5": { N_params: "8e9", T_eval: 4096, n_layers: 32, n_kv_heads: 8, d_head: 128,
bytes_per_weight: 2.0, target_tokens_per_day: 10000000, concurrent_users: 1 },
"X-19": { theta: 500000, T_train: 8192, T_eval: 8192,
n_attention_heads: 32, n_kv_heads: 8, d_head: 128,
n_layers: 32, n_params: "8e9", has_SWA: false },
};
return D[recipeId] || {};
}
// ════════════════════════════════════════════════════════════════════
// Preset autofill (works in recipe mode)
// ════════════════════════════════════════════════════════════════════
$("preset").addEventListener("change", (e) => {
if (!e.target.value) return;
const modelId = e.target.value;
state.lastModelId = modelId; // remember for filename/hash
// Mirror behavior with profile-preset: also fill HF id input if present.
if ($("hf-id")) {
$("hf-id").value = modelId;
if ($("hf-status")) $("hf-status").textContent = tFmt("profile.preset_loaded", { id: modelId });
}
const proxy = state.pyodide.runPython(`get_preset(${JSON.stringify(modelId)})`);
const preset = proxy.toJs ? proxy.toJs({ dict_converter: Object.fromEntries }) : proxy;
if (!preset || Object.keys(preset).length === 0) return;
fillRecipeForm(preset);
});
function fillRecipeForm(p) {
// Fill any matching field in dynamic form
Object.entries(p).forEach(([k, v]) => {
const map = {
theta: "theta", T_train: "T_train",
n_attention_heads: "n_attention_heads", n_kv_heads: "n_kv_heads",
d_head: "d_head", n_layers: "n_layers", n_params: "n_params",
has_SWA: "has_SWA",
};
const formId = "param_" + (map[k] || k);
const el = $(formId);
if (el) el.value = (typeof v === "number" && (k === "n_params" || v > 1e6))
? v.toExponential(2) : String(v);
// Also fill N_params for cost recipes
if (k === "n_params") {
const np = $("param_N_params");
if (np) np.value = (typeof v === "number" ? v.toExponential(2) : String(v));
}
});
}
// ════════════════════════════════════════════════════════════════════
// HF Hub fetch (any model)
// ════════════════════════════════════════════════════════════════════
async function fetchHfConfig(modelId) {
const url = `https://huggingface.co/${modelId}/raw/main/config.json`;
const resp = await fetch(url);
if (!resp.ok) {
if (resp.status === 401 || resp.status === 403) {
throw new Error(`Model is gated (${resp.status}). Accept license on HF Hub first, or fill manually.`);
}
throw new Error(`HTTP ${resp.status} — config.json not found at ${url}`);
}
return await resp.json();
}
$("hf-fetch-btn").addEventListener("click", async () => {
const modelId = $("hf-id").value.trim();
if (!modelId) {
$("hf-status").textContent = "⚠ Enter a model id like 'Qwen/Qwen2.5-32B-Instruct'";
return;
}
$("hf-status").textContent = `⏳ Fetching config.json from HF Hub for ${modelId}...`;
$("hf-fetch-btn").disabled = true;
state.lastModelId = modelId; // remember for filename/hash
try {
const cfg = await fetchHfConfig(modelId);
const preset = configToPreset(cfg, modelId);
fillRecipeForm(preset);
$("hf-status").innerHTML = `✅ Config loaded for <strong>${modelId}</strong> (family: ${preset._family}). Verify values, click Analyze.`;
} catch (err) {
$("hf-status").textContent = `❌ ${err.message}`;
} finally {
$("hf-fetch-btn").disabled = false;
}
});
// ════════════════════════════════════════════════════════════════════
// 🪟 Unmask mode (v0.7.0 anti-bullshit pack #1)
// ════════════════════════════════════════════════════════════════════
// Tiny string-template helper: t(key) with {placeholder} substitution.
// Falls back to the raw key when the i18n entry is missing so dev sees the gap.
function tFmt(key, params = {}) {
let s = t(key) || key;
for (const [k, v] of Object.entries(params)) {
const fmtVal = v === null || v === undefined ? "—"
: (typeof v === "number" ? v.toLocaleString() : String(v));
s = s.replace(new RegExp(`\\{${k}\\}`, "g"), fmtVal);
}
return s;
}
const VERDICT_COLOR = {
honest: "#3fb950",
inflated: "#f1c40f",
severely_inflated: "#f85149",
yarn_extended: "#f1c40f",
unknown: "#8b949e",
};
function renderUnmaskCard(result, modelId = "") {
const color = VERDICT_COLOR[result.verdict] || VERDICT_COLOR.unknown;
const ratioPct = (result.ratio * 100).toFixed(1);
const f = result.flags;
const fmtN = (x) => x === null || x === undefined ? "—" : Number(x).toLocaleString();
const escapeHtml = (s) => String(s).replace(/[&<>"']/g, c =>
({"&":"&amp;","<":"&lt;",">":"&gt;",'"':"&quot;","'":"&#39;"}[c]));
const verdictLabel = t(`unmask.verdict.${result.verdict}`) || result.verdict;
const labelDeclared = t("unmask.label.declared") || "Declared context";
const labelEffective = t("unmask.label.effective") || "Effective (estimate)";
const labelRatio = t("unmask.label.ratio") || "Ratio";
const sectionFlags = t("unmask.section.flags") || "Architecture flags";
const sectionWarn = t("unmask.section.warnings")|| "Warnings";
const sectionReco = t("unmask.section.reco") || "Recommendation";
// Architecture flags row labels
const flagSwa = t("unmask.flag.swa") || "SWA";
const flagRope = t("unmask.flag.rope") || "RoPE scaling";
const flagGqa = t("unmask.flag.gqa") || "GQA";
const flagLayers = t("unmask.flag.layers") || "Layers";
const flagDhead = t("unmask.flag.dhead") || "d_head";
const flagTheta = t("unmask.flag.theta") || "RoPE θ";
const flagYes = t("unmask.flag.yes") || "yes";
const flagNo = t("unmask.flag.no") || "no";
const swaText = f.hasSWA
? `${flagYes} (window = ${fmtN(f.swaWindow)})`
: flagNo;
const ropeText = f.hasYaRN
? `${f.ropeScalingType} (factor = ${f.yarnFactor}, original = ${fmtN(f.yarnOriginal)})`
: flagNo;
const gqaText = f.hasGQA
? `${flagYes} (${f.n_kv_heads} kv / ${f.n_attn_heads} attn heads)`
: (t("unmask.flag.full_mha") || "no (full MHA, {n} heads)").replace("{n}", f.n_attn_heads ?? "?");
const warningsHtml = result.warnings.length
? `<details class="unmask-panel" open><summary class="unmask-panel-title">${sectionWarn}</summary><ul>${result.warnings.map(w =>
`<li>${tFmt("unmask.warn." + w.code, w.params)}</li>`).join("")}</ul></details>`
: "";
const recoHtml = result.recoCode
? `<details class="unmask-panel" open><summary class="unmask-panel-title">${sectionReco}</summary><p class="unmask-reco">${tFmt("unmask.reco." + result.recoCode, result.recoParams)}</p></details>`
: "";
return `
<div class="unmask-result">
<div class="unmask-hero" style="border-color: ${color};">
<div class="unmask-verdict" style="color: ${color};">${verdictLabel}</div>
${modelId ? `<div class="unmask-model"><code>${escapeHtml(modelId)}</code></div>` : ""}
<div class="unmask-numbers">
<div><span class="unmask-num-label">${labelDeclared}</span><span class="unmask-num-val">${fmtN(result.declaredContext)}</span></div>
<div><span class="unmask-num-label">${labelEffective}</span><span class="unmask-num-val">${fmtN(result.effectiveContext)}</span></div>
<div><span class="unmask-num-label">${labelRatio}</span><span class="unmask-num-val">${ratioPct}%</span></div>
</div>
</div>
<div class="unmask-details">
<details class="unmask-panel" open>
<summary class="unmask-panel-title">${sectionFlags}</summary>
<ul>
<li><strong>${flagSwa}:</strong> ${swaText}</li>
<li><strong>${flagRope}:</strong> ${ropeText}</li>
<li><strong>${flagGqa}:</strong> ${gqaText}</li>
<li><strong>${flagLayers}:</strong> ${fmtN(f.n_layers)} · <strong>${flagDhead}:</strong> ${fmtN(f.d_head)} · <strong>${flagTheta}:</strong> ${fmtN(f.rope_theta)}</li>
</ul>
</details>
${warningsHtml}
${recoHtml}
</div>
</div>
`;
}
async function runUnmaskFromId() {
const modelId = ($("unmask-id").value || "").trim();
if (!modelId) {
$("unmask-status").textContent = t("unmask.status.empty_id") || "⚠ Enter a model id.";
return;
}
$("unmask-status").textContent = tFmt("unmask.status.fetching", { modelId });
$("unmask-fetch-btn").disabled = true;
try {
const cfg = await fetchHfConfig(modelId);
const result = unmaskConfig(cfg);
$("unmask-output").innerHTML = renderUnmaskCard(result, modelId);
const verdictLocalized = t(`unmask.verdict.${result.verdict}`) || result.verdict;
$("unmask-status").textContent = tFmt("unmask.status.success", { modelId, verdict: verdictLocalized });
} catch (err) {
$("unmask-status").textContent = `❌ ${err.message}`;
$("unmask-output").innerHTML = "";
} finally {
$("unmask-fetch-btn").disabled = false;
}
}
function runUnmaskFromPaste() {
const raw = ($("unmask-paste").value || "").trim();
if (!raw) {
$("unmask-status").textContent = t("unmask.status.empty_paste") || "⚠ Paste a config.json first.";
return;
}
let cfg;
try {
cfg = JSON.parse(raw);
} catch (e) {
$("unmask-status").textContent = tFmt("unmask.status.invalid_json", { error: e.message });
return;
}
const result = unmaskConfig(cfg);
const pastedLabel = t("unmask.pasted_label") || "(pasted config)";
$("unmask-output").innerHTML = renderUnmaskCard(result, pastedLabel);
const verdictLocalized = t(`unmask.verdict.${result.verdict}`) || result.verdict;
$("unmask-status").textContent = tFmt("unmask.status.success_paste", { verdict: verdictLocalized });
}
$("unmask-fetch-btn")?.addEventListener("click", runUnmaskFromId);
$("unmask-paste-btn")?.addEventListener("click", runUnmaskFromPaste);
$("unmask-id")?.addEventListener("keydown", (e) => {
if (e.key === "Enter") { e.preventDefault(); runUnmaskFromId(); }
});
function configToPreset(cfg, modelId) {
const n_attn = cfg.num_attention_heads || cfg.n_head || 0;
const n_kv = cfg.num_key_value_heads || cfg.num_attention_heads || cfg.n_head || 0;
const hidden = cfg.hidden_size || cfg.d_model || cfg.n_embd || 0;
const d_head = cfg.head_dim || (n_attn > 0 ? Math.floor(hidden / n_attn) : 0);
const theta = cfg.rope_theta || cfg.rotary_emb_base ||
(cfg.alibi ? null : (cfg.position_embedding_type === "absolute" ? null : 10000));
const T_train = cfg.max_position_embeddings || cfg.max_sequence_length ||
cfg.n_positions || cfg.n_ctx || 0;
const n_layers = cfg.num_hidden_layers || cfg.n_layer || 0;
const has_SWA = !!(cfg.sliding_window || cfg.use_sliding_window);
let family = "rope-mha";
if (cfg.alibi) family = "alibi";
else if (cfg.model_type === "mamba" || cfg.model_type === "mamba2") family = "ssm";
else if (theta == null) family = "abspe";
else if (n_kv < n_attn) family = "rope-gqa";
const n_params_est = estimateParams(cfg);
return {
theta: theta || 10000, T_train: T_train || 2048,
n_attention_heads: n_attn, n_kv_heads: n_kv, d_head: d_head,
n_layers: n_layers, n_params: n_params_est, has_SWA: has_SWA,
_family: family, _model_id: modelId,
};
}
function estimateParams(cfg) {
const h = cfg.hidden_size || cfg.d_model || 0;
const L = cfg.num_hidden_layers || cfg.n_layer || 0;
const V = cfg.vocab_size || 32000;
return Math.round(12 * h * h * L + 2 * V * h);
}
// ════════════════════════════════════════════════════════════════════
// Run recipe (manual mode)
// ════════════════════════════════════════════════════════════════════
$("run-btn").addEventListener("click", async () => {
if (!state.currentRecipe) {
alert("Select a recipe first.");
return;
}
const rid = state.currentRecipe.id;
const params = collectParams(state.currentRecipe.params);
await runAndDisplay(rid, params);
});
function collectParams(paramNames) {
const p = {};
paramNames.forEach(name => {
const el = $("param_" + name);
if (!el || el.value === "") return;
let v = el.value;
if (v === "true" || v === "false") {
p[name] = (v === "true");
} else if (!isNaN(parseFloat(v)) && isFinite(v)) {
p[name] = parseFloat(v);
} else {
p[name] = v;
}
});
return p;
}
// ════════════════════════════════════════════════════════════════════
// Ask mode (free-form question via router)
// ════════════════════════════════════════════════════════════════════
$("ask-btn").addEventListener("click", async () => {
const q = $("question").value.trim();
if (!q) {
alert("Please type a question.");
return;
}
$("ask-btn").disabled = true;
setStatus("🤔 Asking the in-browser LLM to pick a recipe...");
try {
const route = await routeQuestion(q);
setStatus(`📋 Selected recipe ${route.recipe_id}. Running...`);
await runAndDisplay(route.recipe_id, route.params, q);
} catch (err) {
setStatus(`❌ Routing failed: ${err.message}`);
$("output-section").style.display = "block";
$("verdict-box").className = "verdict-no";
$("verdict-box").innerHTML = `<strong>Could not route question.</strong><br>${escapeHtml(err.message)}<br><br>Try the Recipe mode for full manual control.`;
} finally {
$("ask-btn").disabled = false;
}
});
$("example-btn").addEventListener("click", () => {
const ex = EXAMPLES[Math.floor(Math.random() * EXAMPLES.length)];
$("question").value = ex;
});
async function routeQuestion(question) {
const engine = await loadWebLLM();
const recipesDesc = state.recipes.map(r =>
` ${r.id}: ${r.name}${r.description}\n params: ${r.params.join(", ")}`
).join("\n");
const systemPrompt = `You are a routing function. Given a user's free-form question
about transformer LLM viability, you MUST output a single JSON object with two fields:
- recipe_id: one of [${state.recipes.map(r => r.id).join(", ")}]
- params: an object with parameter values inferred from the question
Available recipes:
${recipesDesc}
Common model facts you may use:
Meta-Llama-3-8B: theta=500000, T_train=8192, n_attention_heads=32, n_kv_heads=8, d_head=128, n_layers=32, n_params=8e9
Mistral-7B-v0.1: theta=10000, T_train=8192, n_attention_heads=32, n_kv_heads=8, d_head=128, n_layers=32, n_params=7e9, has_SWA=true
Qwen2.5-7B: theta=1000000, T_train=32768, n_attention_heads=28, n_kv_heads=4, d_head=128, n_layers=28, n_params=7.6e9
Llama-3.3-70B-Instruct: theta=500000, T_train=131072, n_attention_heads=64, n_kv_heads=8, d_head=128, n_layers=80, n_params=70e9
Respond with ONLY the JSON object. No prose, no markdown fences, no explanation.`;
const reply = await engine.chat.completions.create({
messages: [
{ role: "system", content: systemPrompt },
{ role: "user", content: question },
],
max_tokens: 400,
temperature: 0.0,
response_format: { type: "json_object" },
});
const raw = reply.choices[0].message.content.trim();
let parsed;
try {
parsed = JSON.parse(raw);
} catch (e) {
// Try extracting JSON from markdown fences
const m = raw.match(/\{[\s\S]*\}/);
if (!m) throw new Error(`LLM returned non-JSON: ${raw.slice(0, 200)}`);
parsed = JSON.parse(m[0]);
}
if (!parsed.recipe_id || !state.recipesById[parsed.recipe_id]) {
throw new Error(`Unknown recipe: ${parsed.recipe_id}`);
}
return parsed;
}
// ════════════════════════════════════════════════════════════════════
// Run + display + synthesize
// ════════════════════════════════════════════════════════════════════
async function runAndDisplay(recipeId, params, originalQuestion=null) {
setStatus("🧮 Computing TAF chain...");
state.pyodide.globals.set("__rid", recipeId);
state.pyodide.globals.set("__params", state.pyodide.toPy(params));
const resultJSON = state.pyodide.runPython(`
import json
result = run_recipe(__rid, **__params)
json.dumps(result)
`);
const result = JSON.parse(resultJSON);
result._original_question = originalQuestion;
renderResult(result);
$("output-section").style.display = "block";
$("profile-output").style.display = "none";
$("compare-output").style.display = "none";
state.lastResult = { type: "recipe", recipeId, params };
state.lastFullResult = result;
setStatus("✅ Done. Numbers below.");
if (ENABLE_WEBLLM) {
await synthesizeAnswer(result);
}
}
function renderResult(r) {
console.log("[TAF] renderResult called with:", r);
if (r.error) {
$("verdict-box").className = "verdict-no";
$("verdict-box").innerHTML = `<strong>Error</strong>: ${escapeHtml(r.error)}`;
$("chain-box").innerHTML = "";
return;
}
const vBox = $("verdict-box");
if (!vBox) {
console.error("[TAF] verdict-box element not found!");
return;
}
const verdictStr = String(r.verdict || "UNKNOWN");
let vClass = "";
if (verdictStr.startsWith("YES") || verdictStr === "GO" || verdictStr.startsWith("USE SOFT")) vClass = "verdict-yes";
else if (verdictStr.startsWith("NO") || verdictStr.startsWith("MEMORY") || verdictStr === "TINY-MODEL") vClass = "verdict-no";
else vClass = "verdict-degraded";
vBox.className = vClass;
const verdictEmoji = vClass === "verdict-yes" ? "✅" : (vClass === "verdict-no" ? "❌" : "⚠");
vBox.innerHTML = `
<div style="display:flex; justify-content:space-between; align-items:center; margin-bottom:0.75rem; gap:1rem; flex-wrap:wrap;">
<div style="font-size:1.6rem; font-weight:800;">${verdictEmoji} ${escapeHtml(verdictStr)}</div>
<div class="recipe-tag">${escapeHtml(r.recipe_id || "")}${escapeHtml(r.recipe_name || "")}</div>
</div>
<div style="margin-bottom:0.5rem;"><strong>Reason:</strong> ${escapeHtml(r.reason || "(none)")}</div>
${r.mitigation && r.mitigation !== "None required." && r.mitigation !== "None — proceed with Chinchilla-optimal recipe."
? `<div><strong>Action:</strong> ${escapeHtml(r.mitigation)}</div>`
: ""}
`;
console.log("[TAF] verdict-box populated with class:", vClass, "verdict:", verdictStr);
const cBox = $("chain-box");
cBox.innerHTML = "";
r.chain.forEach(step => {
const div = document.createElement("details");
div.className = "chain-step";
div.innerHTML = `
<summary>
<span><strong>Step ${step.step}</strong> — ${escapeHtml(step.name)}</span>
<span class="step-section">${escapeHtml(step.section)}</span>
</summary>
<div class="step-formula">${escapeHtml(step.formula)}</div>
<div><strong>Inputs:</strong> ${escapeHtml(JSON.stringify(step.inputs))}</div>
<div class="step-result"><strong>Result:</strong> ${formatResult(step.result)}</div>
${step.interpretation ? `<div class="step-interp">${escapeHtml(step.interpretation)}</div>` : ""}
`;
cBox.appendChild(div);
});
}
function formatResult(r) {
if (r === null || r === undefined) return "n/a (not applicable)";
if (typeof r === "number") return r.toLocaleString(undefined, { maximumFractionDigits: 4 });
if (typeof r === "object") return `<pre>${escapeHtml(JSON.stringify(r, null, 2))}</pre>`;
return String(r);
}
function escapeHtml(s) {
return String(s)
.replace(/&/g, "&amp;").replace(/</g, "&lt;").replace(/>/g, "&gt;")
.replace(/"/g, "&quot;").replace(/'/g, "&#39;");
}
// ════════════════════════════════════════════════════════════════════
// WebLLM (synthesis + router)
// ════════════════════════════════════════════════════════════════════
async function loadWebLLM() {
if (state.webllm) return state.webllm;
// Request persistent storage to avoid quota issues with cached model weights
if (navigator.storage && navigator.storage.persist) {
try {
const persistent = await navigator.storage.persist();
console.log(persistent ? "Persistent storage granted" : "Persistent storage denied");
} catch (e) {
console.warn("storage.persist() failed:", e);
}
}
setStatus(`⏳ Loading WebLLM library + ${WEBLLM_MODEL.split("-")[0]} (~350MB first time, cached after)...`);
const { CreateMLCEngine } = await import("https://esm.run/@mlc-ai/web-llm");
const tryLoad = async (modelId) => {
return await CreateMLCEngine(modelId, {
initProgressCallback: (info) => setStatus(`⏳ ${info.text || "Loading model..."}`),
});
};
try {
state.webllm = await tryLoad(WEBLLM_MODEL);
} catch (err) {
if (String(err).includes("QuotaExceeded") || String(err).includes("storage")) {
setStatus(`⚠ Quota exceeded for ${WEBLLM_MODEL}. Trying smaller fallback ${WEBLLM_FALLBACK}...`);
try {
state.webllm = await tryLoad(WEBLLM_FALLBACK);
} catch (err2) {
throw new Error(
`Both models failed. Browser storage too constrained. ` +
`Try: (1) Settings → Privacy → Site settings → allow more storage for this site, ` +
`(2) clear browser cache, (3) use Chrome/Edge in non-incognito mode. ` +
`Original error: ${err2.message || err2}`
);
}
} else {
throw err;
}
}
return state.webllm;
}
async function synthesizeAnswer(result) {
$("answer-header").style.display = "block";
$("answer-box").style.display = "block";
$("answer-box").innerHTML = '<em style="color:var(--fg-dim);">Generating plain-English summary...</em>';
let engine;
try {
engine = await loadWebLLM();
} catch (err) {
$("answer-box").innerHTML = `<em style="color:var(--warning);">⚠ WebLLM failed: ${escapeHtml(String(err))}<br>Numbers above are still correct.</em>`;
return;
}
const prompt = buildSynthesisPrompt(result);
let answer = "";
try {
const reply = await engine.chat.completions.create({
messages: [
{ role: "system", content: t("synthesis.system") },
{ role: "user", content: prompt },
],
max_tokens: 400,
temperature: 0.2,
});
answer = reply.choices[0].message.content;
} catch (err) {
$("answer-box").innerHTML = `<em style="color:var(--warning);">⚠ Synthesis failed: ${escapeHtml(String(err))}</em>`;
return;
}
$("answer-box").innerHTML = `
<div style="white-space:pre-wrap; line-height:1.7;">${escapeHtml(answer)}</div>
<div style="margin-top:0.75rem; font-size:0.85rem; color:var(--fg-dim);">
↑ Synthesised by Llama-3.2-1B in your browser. Numbers are deterministic Python.
</div>
`;
setStatus("✅ Done.");
}
function buildSynthesisPrompt(r) {
const numbersBlock = r.chain.map(s =>
`Step ${s.step} (${s.section}) ${s.name}: ${formatResultPlain(s.result)}${s.interpretation || ""}`
).join("\n");
return `Recipe: ${r.recipe_id}${r.recipe_name}
${r._original_question ? `User question: "${r._original_question}"\n` : ""}
Computed chain:
${numbersBlock}
Verdict: ${r.verdict}
Reason: ${r.reason}
Action: ${r.mitigation}
Summarize for non-technical user in 4-6 sentences. Cite section numbers (§X.Y). Mention verdict and most important action.`;
}
function formatResultPlain(r) {
if (r === null || r === undefined) return "n/a";
if (typeof r === "number") return r.toLocaleString(undefined, { maximumFractionDigits: 4 });
if (typeof r === "object") return JSON.stringify(r);
return String(r);
}
// ════════════════════════════════════════════════════════════════════
// INSPECTOR mode (paste raw config.json)
// ════════════════════════════════════════════════════════════════════
$("inspector-btn").addEventListener("click", async () => {
const raw = $("inspector-json").value.trim();
if (!raw) {
$("inspector-status").textContent = "⚠ Paste a config.json first";
return;
}
let cfg;
try {
cfg = JSON.parse(raw);
} catch (e) {
$("inspector-status").textContent = `❌ Invalid JSON: ${e.message}`;
return;
}
$("inspector-status").textContent = "⏳ Parsing + profiling...";
$("inspector-btn").disabled = true;
try {
const preset = configToPreset(cfg, cfg.model_type ? `<inspector:${cfg.model_type}>` : "<inspector>");
state.lastModelId = preset._model_id || "<inspected>";
const T_eval = parseInt($("inspector-T_eval").value) || preset.T_train;
const params = {
theta: preset.theta, T_train: preset.T_train, T_eval: T_eval,
n_attention_heads: preset.n_attention_heads,
n_kv_heads: preset.n_kv_heads,
d_head: preset.d_head, n_layers: preset.n_layers,
n_params: preset.n_params, has_SWA: preset.has_SWA,
};
state.pyodide.globals.set("__pp", state.pyodide.toPy(params));
const json = state.pyodide.runPython(`
import json
result = profile_model(**__pp)
json.dumps(result)
`);
const profile = JSON.parse(json);
renderProfile(profile, params);
state.lastResult = { type: "profile", params };
state.lastFullResult = profile;
$("inspector-status").innerHTML = `✅ Profiled: <strong>${preset._family}</strong> (${preset.n_params.toExponential(2)} params)`;
} catch (err) {
$("inspector-status").textContent = `❌ ${err.message}`;
console.error(err);
} finally {
$("inspector-btn").disabled = false;
}
});
// ════════════════════════════════════════════════════════════════════
// What-if T_eval slider — interactive exploration
// ════════════════════════════════════════════════════════════════════
function renderWhatIfSlider(profile, params, targetEl) {
if (!profile || !params) return;
const minL = 256;
const maxL = Math.max(params.T_eval * 4, 200000);
const initialL = params.T_eval;
targetEl.innerHTML = `
<h3 data-i18n="whatif.title">🎚 What-if: drag T_eval to see γ change live</h3>
<p class="subtle" data-i18n="whatif.desc">Pure JS recompute (no Pyodide call). Shows the geometric γ_Padé and d_horizon as you slide. The full chain re-runs on click.</p>
<input type="range" id="whatif-slider" class="whatif-slider"
min="${minL}" max="${maxL}" step="${Math.round(maxL/200)}" value="${initialL}" />
<div class="whatif-row"><span data-i18n="whatif.T_eval"><strong>T_eval</strong></span><span id="whatif-T_eval">${initialL.toLocaleString()}</span></div>
<div class="whatif-row"><span data-i18n="whatif.gamma_pade"><strong>γ_Padé</strong></span><span id="whatif-gamma">—</span></div>
<div class="whatif-row"><span data-i18n="whatif.d_horizon"><strong>d_horizon</strong></span><span id="whatif-dh">—</span></div>
<div class="whatif-row"><span data-i18n="whatif.l_niah"><strong>L_NIAH ceiling</strong></span><span id="whatif-niah">—</span></div>
<div class="whatif-row"><span data-i18n="whatif.predicted"><strong>Predicted geometric verdict</strong></span><span id="whatif-verdict" class="verdict-text">—</span></div>
<button id="whatif-rerun" class="secondary" type="button" style="margin-top:0.5rem;" data-i18n="whatif.rerun">↻ Recompute full chain at this T_eval</button>
`;
if (window.__taf_applyTranslations) window.__taf_applyTranslations();
const update = () => {
const T = parseInt($("whatif-slider").value);
const sqrt2 = Math.SQRT2;
const g_pade = (2 * params.theta - T * sqrt2) / (2 * params.theta + T * sqrt2);
// Apply same decomposition as Python
const g_corr = g_pade
+ (params.n_kv_heads < params.n_attention_heads ? 0.11 : 0)
+ (params.has_SWA ? -0.21 : 0)
+ (params.n_params >= 4e8 ? -0.15 : 0);
let dh = null, niah = null, verdict, vClass;
if (g_corr > 0 && g_corr < 1) {
dh = params.theta * (1 - g_corr) * sqrt2 / (1 + g_corr);
niah = 2 * dh;
if (T < dh) { verdict = `✅ YES (margin ${((1 - T / dh) * 100).toFixed(0)}%)`; vClass = "yes"; }
else if (T < niah) { verdict = `⚠ DEGRADED`; vClass = "deg"; }
else { verdict = `❌ NO (past NIAH ceiling)`; vClass = "no"; }
} else {
verdict = `❌ NO (Phase B)`; vClass = "no";
}
$("whatif-T_eval").textContent = T.toLocaleString();
$("whatif-gamma").textContent = g_pade.toFixed(4) + (g_corr !== g_pade ? ` → ${g_corr.toFixed(4)}` : "");
$("whatif-dh").textContent = dh !== null ? Math.round(dh).toLocaleString() : "n/a (Phase B)";
$("whatif-niah").textContent = niah !== null ? Math.round(niah).toLocaleString() : "n/a";
const vEl = $("whatif-verdict");
vEl.textContent = verdict;
vEl.className = "verdict-text " + vClass;
};
$("whatif-slider").addEventListener("input", update);
$("whatif-rerun").addEventListener("click", () => {
const T = parseInt($("whatif-slider").value);
// Update params and trigger full re-profile
$("profile-T_eval").value = T;
$("profile-btn").click();
});
update();
}
// ════════════════════════════════════════════════════════════════════
// FALSIFICATION dashboard inline
// ════════════════════════════════════════════════════════════════════
const FALSIFICATION_STATUS = [
{ id: "F1", claim: "γ_Padé MAE < 5% on non-anomalous Phase A models", status: "confirmed", evidence: "n=9, paper Tab. 4" },
{ id: "F2", claim: "d_horizon predicts NIAH collapse within 1% (pythia-70m)", status: "confirmed", evidence: "predicted 4078, observed 4096" },
{ id: "F3", claim: "Fisher info predicts forward-hook recovery within 0.2%", status: "confirmed", evidence: "12.5% predicted vs 12.3% observed" },
{ id: "F4", claim: "Layer asymmetry early/late ratio ≈ 13.5× (pythia-70m)", status: "confirmed", evidence: "F2 thermostat experiment" },
{ id: "F5", claim: "Area law S_γ = O(log N) for all γ > 0", status: "confirmed", evidence: "n=56, r=-0.954" },
{ id: "F6", claim: "KV truncation at D_f gives ΔPPL ≤ 0 in γ ∈ [0.65, 0.85]", status: "confirmed", evidence: "pythia-2.8b ΔPPL=-0.51" },
{ id: "F7", claim: "Linear pruning cost: ΔPPL ≈ 0.18 × %Q/K_pruned", status: "confirmed", evidence: "pythia-1b 0.17, 2.8b 0.18" },
{ id: "F8", claim: "Padé saturates at [1,1] in LLM regime z<<1", status: "confirmed", evidence: "sage round 4" },
{ id: "F9", claim: "RoPE attention is Euclidean fractional (d_eff=1/γ), not hyperbolic", status: "confirmed", evidence: "EXP-METRIC-RoPE sage" },
{ id: "F10", claim: "Δγ < -0.1 in models ≥ 400M ⇒ GQA / induction-head dominance", status: "confirmed", evidence: "n=20+ models" },
{ id: "F11", claim: "Δγ > +0.3 ⇒ alternating SWA (Gemma family signature)", status: "confirmed", evidence: "Gemma-2-9b Δγ=+0.51" },
{ id: "F12", claim: "Mamba L_crit = 45, α = 0.703", status: "confirmed", evidence: "3 seeds" },
{ id: "F13", claim: "Phase boundary at γ = 1 (Hagedorn)", status: "confirmed", evidence: "χ → ∞" },
{ id: "F14", claim: "RLHF Δγ shift ≤ 0.072 (recipe-specific)", status: "partial", evidence: "n=8 recipe-locked" },
{ id: "F15", claim: "R_c boundary at R_c★ ≈ 1.68", status: "refuted", evidence: "overlap zone [0.92, 3.08] n=9" },
{ id: "F16", claim: "Holographic pruning: alive bands in ℓ > L_crit ΔPPL ≈ 0", status: "refuted", evidence: "linear cost law instead" },
{ id: "F17", claim: "Soft d_horizon decay beats hard in regime d_h ≳ T_train/2", status: "partial", evidence: "n=2/3 (pythia-1b refuted)" },
{ id: "F18", claim: "Mittag-Leffler prefactor 1/Γ(1-γ) governs A_0", status: "refuted", evidence: "n=39, ratio 0.23" },
{ id: "F19", claim: "γ_Padé predicts γ_obs across-model variance", status: "partial", evidence: "centroid OK, ~0.1% var explained, see §sec:gamma_decomposition" },
{ id: "F20", claim: "β-flow exactly equivalent to logistic ODE", status: "confirmed", evidence: "sage symbolic check" },
{ id: "F21", claim: "tanh trajectory γ(t)~tanh(log step) on pythia-1b checkpoints", status: "refuted", evidence: "R²=0.15 on 4 checkpoints" },
{ id: "F22", claim: "χ(z*) = (5+√17)/4 closed form at Cayley fixed point", status: "confirmed", evidence: "sage symbolic, minimal poly 2y²-5y+1" },
{ id: "F23", claim: "T ↔ d_horizon involution: θ_design ∘ γ_Padé = id", status: "confirmed", evidence: "sage symbolic" },
];
function renderFalsificationDashboard() {
const target = $("falsification-table");
if (!target) return;
const counts = { confirmed: 0, partial: 0, refuted: 0, untested: 0 };
FALSIFICATION_STATUS.forEach(f => counts[f.status]++);
const summary = `<p class="subtle">
✅ <strong>${counts.confirmed}</strong> confirmed ·
⚠ <strong>${counts.partial}</strong> partial ·
❌ <strong>${counts.refuted}</strong> refuted ·
⏳ <strong>${counts.untested}</strong> untested
(out of ${FALSIFICATION_STATUS.length} total predictions)
</p>`;
let table = `<table class="falsification-table"><thead>
<tr><th>ID</th><th>Claim</th><th>Status</th><th>Evidence</th></tr>
</thead><tbody>`;
FALSIFICATION_STATUS.forEach(f => {
const icon = ({ confirmed: "✅", partial: "⚠", refuted: "❌", untested: "⏳" })[f.status];
table += `<tr>
<td><code>${f.id}</code></td>
<td>${escapeHtml(f.claim)}</td>
<td class="fal-status ${f.status}">${icon} ${f.status}</td>
<td class="subtle">${escapeHtml(f.evidence)}</td>
</tr>`;
});
table += "</tbody></table>";
target.innerHTML = summary + table;
}
// ════════════════════════════════════════════════════════════════════
// Browse community submissions (live from GitHub Issues API)
// ════════════════════════════════════════════════════════════════════
async function loadCommunityFeed() {
const target = $("community-feed");
if (!target) return;
try {
const resp = await fetch(`https://api.github.com/repos/${REGISTRY_REPO}/issues?state=open&per_page=15&sort=created&direction=desc`);
if (!resp.ok) {
if (resp.status === 404) {
target.innerHTML = `<em>The registry repo isn't created yet. Once <a href="https://github.com/${REGISTRY_REPO}" target="_blank"><code>${REGISTRY_REPO}</code></a> exists with submissions, they'll appear here live.</em>`;
return;
}
throw new Error(`HTTP ${resp.status}`);
}
const issues = await resp.json();
if (!issues || issues.length === 0) {
target.innerHTML = `<em>No submissions yet. Be the first — generate a Profile and click <strong>📤 Submit to registry</strong>.</em>`;
return;
}
const html = issues.map(issue => {
const verdict = extractVerdictFromTitle(issue.title);
const vClass = verdictClass(verdict);
const time = relativeTime(new Date(issue.created_at));
return `<div class="community-item">
<span class="verdict-badge ${vClass}">${escapeHtml(verdict)}</span>
<a href="${escapeHtml(issue.html_url)}" target="_blank">${escapeHtml(issue.title)}</a>
<span class="item-time">${time}</span>
</div>`;
}).join("");
target.innerHTML = html;
} catch (err) {
target.innerHTML = `<em>⚠ Couldn't load community feed: ${escapeHtml(err.message)}</em>`;
}
}
function extractVerdictFromTitle(title) {
const m = title.match(/→\s*(\S+)/);
if (m) return m[1];
if (title.includes("YES")) return "YES";
if (title.includes("NO")) return "NO";
if (title.includes("DEGRADED")) return "DEG";
if (title.includes("Profile")) return "📇";
if (title.includes("Compare")) return "🆚";
return "?";
}
function verdictClass(v) {
if (v.startsWith("YES") || v === "GO") return "yes";
if (v.startsWith("NO")) return "no";
if (v === "DEG" || v === "DEGRADED") return "deg";
return "";
}
function relativeTime(d) {
const sec = Math.floor((Date.now() - d.getTime()) / 1000);
if (sec < 60) return `${sec}s ago`;
if (sec < 3600) return `${Math.floor(sec / 60)}m ago`;
if (sec < 86400) return `${Math.floor(sec / 3600)}h ago`;
return `${Math.floor(sec / 86400)}d ago`;
}
// ════════════════════════════════════════════════════════════════════
// PROFILE mode
// ════════════════════════════════════════════════════════════════════
$("profile-preset").addEventListener("change", (e) => {
if (!e.target.value) return;
const modelId = e.target.value;
state.lastModelId = modelId; // remember for filename/hash
// Preset keys ARE valid HF model ids (e.g. "meta-llama/Llama-3.2-1B"). Auto-fill
// the HF id input so the user can also click 📥 Fetch to refresh from HF Hub
// without retyping. Status hint clarifies the dual source of truth.
if ($("profile-hf-id")) {
$("profile-hf-id").value = modelId;
if ($("profile-hf-status")) {
$("profile-hf-status").textContent = tFmt("profile.preset_loaded", { id: modelId });
}
}
const proxy = state.pyodide.runPython(`get_preset(${JSON.stringify(modelId)})`);
const p = proxy.toJs ? proxy.toJs({ dict_converter: Object.fromEntries }) : proxy;
if (!p || Object.keys(p).length === 0) return;
$("profile-theta").value = p.theta;
$("profile-T_train").value = p.T_train;
$("profile-n_attn").value = p.n_attention_heads;
$("profile-n_kv").value = p.n_kv_heads;
$("profile-d_head").value = p.d_head;
$("profile-n_layers").value = p.n_layers;
$("profile-n_params").value = p.n_params.toExponential(2);
$("profile-has_swa").value = String(p.has_SWA);
});
$("profile-fetch-btn").addEventListener("click", async () => {
const id = $("profile-hf-id").value.trim();
if (!id) { $("profile-hf-status").textContent = "⚠ Enter a model id"; return; }
$("profile-hf-status").textContent = `⏳ Fetching ${id}...`;
$("profile-fetch-btn").disabled = true;
state.lastModelId = id; // remember for filename/hash
try {
const cfg = await fetchHfConfig(id);
const p = configToPreset(cfg, id);
$("profile-theta").value = p.theta;
$("profile-T_train").value = p.T_train;
$("profile-n_attn").value = p.n_attention_heads;
$("profile-n_kv").value = p.n_kv_heads;
$("profile-d_head").value = p.d_head;
$("profile-n_layers").value = p.n_layers;
$("profile-n_params").value = p.n_params.toExponential(2);
$("profile-has_swa").value = String(p.has_SWA);
$("profile-hf-status").innerHTML = `✅ <strong>${id}</strong> (${p._family})`;
} catch (err) {
$("profile-hf-status").textContent = `❌ ${err.message}`;
} finally {
$("profile-fetch-btn").disabled = false;
}
});
$("profile-btn").addEventListener("click", async () => {
const params = {
theta: parseFloat($("profile-theta").value),
T_train: parseInt($("profile-T_train").value),
T_eval: parseInt($("profile-T_eval").value),
n_attention_heads: parseInt($("profile-n_attn").value),
n_kv_heads: parseInt($("profile-n_kv").value),
d_head: parseInt($("profile-d_head").value),
n_layers: parseInt($("profile-n_layers").value),
n_params: parseFloat($("profile-n_params").value),
has_SWA: $("profile-has_swa").value === "true",
};
setStatus("🧮 Profiling — running all 5 recipes...");
$("profile-btn").disabled = true;
try {
state.pyodide.globals.set("__pp", state.pyodide.toPy(params));
const json = state.pyodide.runPython(`
import json
result = profile_model(**__pp)
json.dumps(result)
`);
const profile = JSON.parse(json);
renderProfile(profile, params);
state.lastResult = { type: "profile", params };
state.lastFullResult = profile;
setStatus("✅ Profile ready.");
} catch (err) {
setStatus(`❌ ${err.message}`);
console.error(err);
} finally {
$("profile-btn").disabled = false;
}
});
function renderProfile(p, params) {
$("profile-output").style.display = "block";
// Hide other outputs
$("output-section").style.display = "none";
$("compare-output").style.display = "none";
const verdictClass = (v) => {
if (v.startsWith("YES") || v === "GO" || v.startsWith("USE SOFT")) return "v-yes";
if (v.startsWith("NO") || v.startsWith("MEMORY") || v === "TINY-MODEL") return "v-no";
return "v-deg";
};
const verdictEmoji = (v) => verdictClass(v) === "v-yes" ? "✅"
: verdictClass(v) === "v-no" ? "❌" : "⚠";
const ms = p.model_summary;
const kn = p.key_numbers;
const formatN = (x) => x === null || x === undefined ? "n/a"
: (typeof x === "number" ? x.toLocaleString(undefined, { maximumFractionDigits: 4 }) : String(x));
const recipesHtml = Object.entries(p.recipes).map(([rid, r]) => `
<div class="taf-recipe-tile ${verdictClass(r.verdict)}">
<div class="tile-header">
<span>${escapeHtml(rid)} — <span class="tile-name">${escapeHtml(r.name)}</span></span>
<span class="tile-verdict">${verdictEmoji(r.verdict)} ${escapeHtml(r.verdict)}</span>
</div>
<div class="tile-reason">${escapeHtml(r.reason || "")}</div>
${r.mitigation && r.mitigation !== "None required." && r.mitigation !== "None — proceed with Chinchilla-optimal recipe."
? `<div class="tile-reason" style="margin-top:0.4rem; color:var(--fg-dim);"><strong>Action:</strong> ${escapeHtml(r.mitigation)}</div>`
: ""}
</div>
`).join("");
// Reusable tooltip helper — keeps tooltip pattern uniform across the card
const ttip = (key, fallback) =>
`<span class="info"><span class="tooltip" data-i18n="${key}">${fallback}</span></span>`;
const numbersHtml = `
<div class="num-row"><span class="num-label">γ_Padé(T_eval) ${ttip("tooltip.gamma_pade", "Closed-form prediction (2−z)/(2+z), z = T√2/θ. Paper §sec:gamma_decomposition.")}</span><span class="num-value">${formatN(kn.gamma_pade)}</span></div>
<div class="num-row"><span class="num-label">γ_decomposed ${ttip("tooltip.gamma_decomposed", "γ from full architectural decomposition: Padé baseline + GQA shift + SWA shift + post-IH shift.")}</span><span class="num-value">${formatN(kn.gamma_decomposed)}</span></div>
<div class="num-row"><span class="num-label">d_horizon ${ttip("tooltip.d_horizon", "Effective attention horizon at T_eval. Beyond this, attention scores fall below the noise floor (paper §26).")}</span><span class="num-value">${formatN(kn.d_horizon)}</span></div>
<div class="num-row"><span class="num-label">L_NIAH ceiling ${ttip("tooltip.L_NIAH", "Predicted ceiling for needle-in-a-haystack retrieval reliability at the current d_horizon.")}</span><span class="num-value">${formatN(kn.L_NIAH_ceiling)}</span></div>
<div class="num-row"><span class="num-label">χ susceptibility ${ttip("tooltip.chi", "Susceptibility exponent χ = 1/(1−γ). Diverges at the Hagedorn line γ=1.")}</span><span class="num-value">${formatN(kn.chi_susceptibility)}</span></div>
<div class="num-row"><span class="num-label">KV memory @ T_eval (BF16) ${ttip("tooltip.kv_memory", "Per-request KV cache memory at T_eval in BF16 = 2 · n_layers · n_kv_heads · d_head · T_eval bytes.")}</span><span class="num-value">${formatN(kn.kv_memory_per_request_GB)} GB</span></div>
`;
const falsHtml = (p.falsification_status || []).map(f =>
`<div class="taf-falsification"><strong>${escapeHtml(f.id)}</strong> — ${escapeHtml(f.claim)}: ${escapeHtml(f.status)}</div>`
).join("");
// Per-verdict count breakdown — recipes test orthogonal axes (long-context,
// budget, hardware, custom-vs-API, KV-compression). Worst-of-N would conflate
// a "use API" recommendation with a long-context failure, so we show counts.
const verdictCounts = Object.values(p.recipes).reduce((acc, r) => {
const c = verdictClass(r.verdict);
acc[c] = (acc[c] || 0) + 1;
return acc;
}, {});
const nYes = verdictCounts["v-yes"] || 0;
const nDeg = verdictCounts["v-deg"] || 0;
const nNo = verdictCounts["v-no"] || 0;
const breakdownCls = nNo ? "v-no" : nDeg ? "v-deg" : "v-yes";
const gammaForPill = kn.gamma_decomposed ?? kn.gamma_pade;
const recipeCount = Object.keys(p.recipes).length;
$("profile-box").innerHTML = `
<div class="taf-card">
<div class="taf-hero">
<div class="hero-arch">${escapeHtml(ms.architecture_class)}</div>
<div class="hero-meta">
n_params=${formatN(ms.n_params)} ·
T_train=${ms.T_train} · T_eval=${ms.T_eval} ·
θ=${formatN(ms.rope_theta)} ·
${ms.has_GQA ? "GQA" : "MHA"}${ms.has_SWA ? " + SWA" : ""}
</div>
<div class="hero-row">
<span class="hero-pill ${breakdownCls}">✅ ${nYes} · ⚠ ${nDeg} · ❌ ${nNo} ${ttip("tooltip.verdict_breakdown", "Per-recipe breakdown across the orthogonal axes (long-context, budget, hardware, custom-vs-API, KV-compression). Recipes are independent decisions — a ❌ on X-1 means \"use API\" not \"model fails\". Open the Recipes section for per-axis verdict.")}</span>
${gammaForPill !== null && gammaForPill !== undefined
? `<span class="hero-pill">γ = ${formatN(gammaForPill)} ${ttip("tooltip.gamma_pill", "γ_decomposed (full architectural decomposition) or γ_Padé as fallback. Range (0,1) = Phase A (anti-Ising). γ ≥ 1 = Hagedorn / Phase B.")}</span>`
: ''}
${gammaForPill > 0 && gammaForPill < 1
? `<span class="hero-pill" style="background:rgba(110,80,200,0.15); border-color:rgba(110,80,200,0.45);"><span data-i18n="v05.antiising.badge">🧲 Anti-Ising (β=γ−1&lt;0, machine-verified)</span> ${ttip("tooltip.anti_ising", "Phase A class: β = γ−1 &lt; 0 (anti-Ising). Machine-verified by Sage Groebner basis + Lean Mathlib4. See §35 v0.5.")} ${badgesForUiBinding("anti_ising_pill")}</span>`
: ''}
</div>
</div>
<details class="taf-section" open>
<summary>
<span data-i18n="tafcard.recipes_title">📋 Recipes — verdict per dimension</span>
<span class="section-count">${recipeCount} ${t("tafcard.recipes_count_label", "dimensions")}</span>
</summary>
<div class="taf-section-body">
<div class="taf-recipes-grid">${recipesHtml}</div>
</div>
</details>
<details class="taf-section">
<summary>
<span data-i18n="tafcard.diag_title">🔬 Diagnostics — numbers + γ check + what-if</span>
</summary>
<div class="taf-section-body">
<h4 style="margin-top:0.3em;" data-i18n="tafcard.numbers_title">🔢 Key numbers (paper §26)</h4>
<div class="taf-key-numbers">${numbersHtml}</div>
<h4 style="margin-top:1.2em;" data-i18n="gamma_check.title">🔍 γ predicted vs observed</h4>
<div class="recipe-desc" data-i18n="gamma_check.desc">
Enter your empirically measured γ. Tool detects regime: fraud (θ inflated) / compressed / over-Padé / SWA-random / normal.
</div>
<div class="form-grid" style="margin:0.5em 0 0.6em;">
<div class="form-field">
<label><span data-i18n="gamma_check.gobs_label">γ_observed</span>
<span class="info"><span class="tooltip" data-i18n="gamma_check.gobs_tip">Empirically measured γ from your model's attention scores. Use the Diagnose CLI to obtain this from real weights.</span></span>
</label>
<input type="number" id="gc-gobs" step="0.0001" value="${formatN(kn.gamma_decomposed ?? kn.gamma_pade)}" />
</div>
<div class="form-field">
<label><span data-i18n="gamma_check.random_label">Random corpus?</span>
<span class="info"><span class="tooltip" data-i18n="gamma_check.random_tip">Tick if γ_observed was measured on random/unstructured tokens. Distinguishes SWA signature (γ_obs &gt; 1) from anomaly.</span></span>
</label>
<select id="gc-random">
<option value="false" selected data-i18n="common.no">No</option>
<option value="true" data-i18n="common.yes">Yes</option>
</select>
</div>
</div>
<div id="gamma-check-results"></div>
<h4 style="margin-top:1.2em;" data-i18n="tafcard.whatif_title">🎚️ What-if explorer</h4>
<div id="whatif-container" class="whatif-box"></div>
</div>
</details>
<details class="taf-section">
<summary>
<span data-i18n="tafcard.verify_title">✓ Verification — Lean + Sage + falsification</span>
</summary>
<div class="taf-section-body">
<h4 style="margin-top:0.3em;" data-i18n="lean.table.title">📑 Lean+Mathlib theorem table</h4>
<div style="margin-bottom: 0.6em; opacity: 0.85; font-size: 0.92em;" data-i18n="lean.table.desc">
Every entry below is machine-proven against Lean 4 + Mathlib4. Click any L# link to jump to the source line on GitHub. The table is grouped by topic; click a header to expand.
</div>
<div id="lean-table-host"></div>
<h4 style="margin-top:1.2em;" data-i18n="v05.consistency.title">🔬 Algebraic consistency (Sage + Lean v0.5)</h4>
<div style="margin-bottom: 0.6em; opacity: 0.85; font-size: 0.92em;" data-i18n="v05.consistency.desc">
Verifies 12 D-SAGE algebraic identities of TAF critical exponents (machine-proof Sage Groebner basis + Lean Mathlib4). Pass = framework intact. Fail = bf16 outlier / quantization artifact.
</div>
<div class="lean-badges-row">${badgesForUiBinding("algebraic_consistency_check")}</div>
<button class="secondary" id="verify-consistency-btn" data-i18n="v05.consistency.btn">
🔬 Verify algebraic consistency
</button>
<div id="consistency-result" style="margin-top: 0.8em;"></div>
<h4 style="margin-top:1.2em;" data-i18n="tafcard.fals_title">🔬 Falsification status (F1-F23)</h4>
${falsHtml || '<div class="subtle" data-i18n="tafcard.fals_none">No falsifications applicable.</div>'}
</div>
</details>
<details class="taf-section">
<summary>
<span data-i18n="tafcard.share_title">📂 Provenance & share</span>
</summary>
<div class="taf-section-body">
<details style="margin:0.4em 0 0.8em; padding:0.6em 0.8em; border:1px solid rgba(241,196,15,0.5); border-radius:6px; background:rgba(241,196,15,0.07); font-size:0.88em;">
<summary style="cursor:pointer; font-weight:600;" data-i18n="v053.calibration.title">🔬 v0.5.3 — Calibration audit (2026-05-02)</summary>
<div style="margin-top:0.5em; line-height:1.45;" data-i18n="v053.calibration.note"></div>
</details>
<div class="share-bar">
<button class="secondary" id="profile-share-btn" data-i18n="share.btn">🔗 Copy share link</button>
<button class="secondary" id="profile-download-btn" data-i18n="share.download">💾 Download JSON</button>
<button class="secondary" id="profile-download-md-btn" data-i18n="share.download_md">📝 Markdown</button>
<button class="secondary" id="profile-download-tex-btn" data-i18n="share.download_tex">📜 LaTeX</button>
<button class="secondary" id="profile-submit-btn" data-i18n="share.submit">📤 Submit to registry</button>
<span id="profile-share-status" class="subtle"></span>
</div>
</div>
</details>
</div>
`;
// Render the what-if slider for interactive exploration
renderWhatIfSlider(p, params, $("whatif-container"));
// Render Lean+Mathlib theorem table (graceful no-op if manifest missed).
// Loaded async at bootstrap; if Profile clicked before fetch resolves we
// wait once and then render.
const renderLeanTable = () => {
const host = $("lean-table-host");
if (!host) return;
if (getManifest()) {
host.innerHTML = renderTheoremTable();
if (window.__taf_applyTranslations) window.__taf_applyTranslations();
} else {
host.innerHTML = `<div class="subtle" data-i18n="lean.manifest.loading">Loading Lean manifest…</div>`;
loadLeanManifest()
.then(() => { host.innerHTML = renderTheoremTable(); if (window.__taf_applyTranslations) window.__taf_applyTranslations(); })
.catch(err => { host.innerHTML = `<div class="subtle" data-i18n="lean.manifest.error">Lean manifest unavailable: ${err.message}</div>`; });
}
};
renderLeanTable();
// Re-apply translations to dynamically inserted buttons
if (window.__taf_applyTranslations) window.__taf_applyTranslations();
// Wire share/download/submit buttons
$("profile-share-btn").addEventListener("click", () => copyShareLink("profile", params));
$("profile-download-btn").addEventListener("click", async () => {
const filename = await makeFilename("profile", p);
const data = await exportableData("profile", p);
downloadJSON(filename, data);
$("profile-share-status").textContent = `✅ Downloaded ${filename}`;
setTimeout(() => $("profile-share-status").textContent = "", 5000);
});
$("profile-download-md-btn").addEventListener("click", async () => {
const hash = await inputHash("profile", p);
const base = (await makeFilename("profile", p)).replace(/\.json$/, "");
downloadText(`${base}.md`, profileToMarkdown(p, hash), "text/markdown;charset=utf-8");
$("profile-share-status").textContent = `✅ Downloaded ${base}.md`;
setTimeout(() => $("profile-share-status").textContent = "", 5000);
});
$("profile-download-tex-btn").addEventListener("click", async () => {
const hash = await inputHash("profile", p);
const base = (await makeFilename("profile", p)).replace(/\.json$/, "");
downloadText(`${base}.tex`, profileToLatex(p, hash), "application/x-tex;charset=utf-8");
$("profile-share-status").textContent = `✅ Downloaded ${base}.tex`;
setTimeout(() => $("profile-share-status").textContent = "", 5000);
});
$("profile-submit-btn").addEventListener("click", async () => {
await submitToRegistry("profile", p, $("profile-share-status"));
setTimeout(() => $("profile-share-status").textContent = "", 8000);
});
// v0.6: γ predicted-vs-observed panel — interactive
const updateGammaCheck = () => {
const gObs = parseFloat($("gc-gobs").value);
const isRandom = $("gc-random").value === "true";
const r = gammaCheckAll({ theta: params.theta, T: params.T_eval, gObs, isRandom });
const meta = REGIME_META[r.regime] || REGIME_META.unknown;
const fmt = (x, d=4) => (x === null || x === undefined || Number.isNaN(x))
? "n/a"
: (!Number.isFinite(x) ? "∞" : Number(x).toLocaleString(undefined, { maximumFractionDigits: d }));
$("gamma-check-results").innerHTML = `
<div class="taf-key-numbers">
<div class="num-row"><span class="num-label">γ_Padé(T_eval) ${ttip("tooltip.gamma_pade", "Closed-form prediction (2−z)/(2+z), z = T√2/θ.")}</span><span class="num-value">${fmt(r.gammaPade)}</span></div>
<div class="num-row"><span class="num-label">θ_eff (observed) ${ttip("tooltip.theta_eff_obs", "Effective θ implied by your γ_observed: T√2 / (1 − γ_obs).")}</span><span class="num-value">${fmt(r.thetaEffObs, 1)}</span></div>
<div class="num-row"><span class="num-label">θ_eff (Padé) ${ttip("tooltip.theta_eff_pade", "Effective θ predicted by closed-form: θ + T/√2.")}</span><span class="num-value">${fmt(r.thetaEffPade, 1)}</span></div>
<div class="num-row"><span class="num-label">η = θ_eff_obs / θ_eff_Padé ${ttip("tooltip.efficiency", "Efficiency ratio. ≈1 = normal · &lt;0.01 = fraud · &lt;0.5 = compressed · &gt;1.5 = over-Padé.")}</span><span class="num-value">${fmt(r.efficiency)}</span></div>
<div class="num-row"><span class="num-label">ΔH_Cardy = log(θ_eff_obs / θ_nominal) ${ttip("tooltip.delta_h_cardy", "Cardy entropy shift. Negative = compression entropy. ~0 = nominal match.")}</span><span class="num-value">${fmt(r.deltaHCardy)}</span></div>
</div>
<div class="taf-recipe-tile ${meta.cls}" style="margin-top:0.6em;">
<div class="tile-header">
<span data-i18n="gamma_check.regime">Regime</span>
<span class="tile-verdict">${meta.emoji} <span data-i18n="gamma_check.regime.${r.regime}">${r.regime}</span></span>
</div>
<div class="tile-reason" data-i18n="gamma_check.regime.${r.regime}.desc"></div>
</div>
<details style="margin-top:0.6em;">
<summary style="cursor:pointer; font-weight:600;" data-i18n="gamma_check.glossary.title">ⓘ What do these mean?</summary>
<ul class="gc-glossary" style="margin:0.5em 0 0 1.2em; line-height:1.55;">
<li data-i18n="gamma_check.glossary.gamma_pade"></li>
<li data-i18n="gamma_check.glossary.gamma_obs"></li>
<li data-i18n="gamma_check.glossary.theta_eff_obs"></li>
<li data-i18n="gamma_check.glossary.theta_eff_pade"></li>
<li data-i18n="gamma_check.glossary.efficiency"></li>
<li data-i18n="gamma_check.glossary.delta_h"></li>
<li data-i18n="gamma_check.glossary.regime"></li>
</ul>
</details>
`;
if (window.__taf_applyTranslations) window.__taf_applyTranslations();
};
$("gc-gobs").addEventListener("input", updateGammaCheck);
$("gc-random").addEventListener("change", updateGammaCheck);
updateGammaCheck();
// v0.5.1: Algebraic consistency check button
$("verify-consistency-btn").addEventListener("click", () => {
const gammaVal = kn.gamma_decomposed ?? kn.gamma_pade;
if (gammaVal === null || gammaVal === undefined) {
$("consistency-result").innerHTML = `<div class="subtle">⚠ No γ value available for verification.</div>`;
return;
}
if (gammaVal <= 0 || gammaVal >= 1) {
$("consistency-result").innerHTML = `
<div style="padding:0.6em; border-left:3px solid #d29922; background:rgba(210,153,34,0.08);">
⚠ <strong>γ = ${gammaVal.toFixed(4)} out of Phase A</strong> — verification requires γ ∈ (0, 1).
${gammaVal >= 1 ? "Hagedorn boundary reached." : "Phase B / negative regime."}
</div>`;
return;
}
try {
const json = state.pyodide.runPython(`
import json
result = verify_algebraic_consistency(${gammaVal})
json.dumps(result)
`);
const r = JSON.parse(json);
const passed = r.n_checks_passed;
const total = r.n_checks_total;
const allOk = r.all_consistent;
const tooltipText = (id) => {
const key = `v05.tooltip.${id.replace(/[^a-zA-Z0-9]/g, '_')}`;
const tip = t(key);
return (tip === key) ? '' : tip;
};
const checksRows = Object.entries(r.checks).map(([id, c]) => {
const tip = tooltipText(id);
return `<div class="num-row" style="padding:0.25em 0;" ${tip ? `title="${escapeHtml(tip)}"` : ''}>
<span class="num-label" style="font-family:monospace;font-size:0.85em;${tip ? 'cursor:help;border-bottom:1px dotted rgba(110,180,255,0.5);' : ''}">${escapeHtml(id)}: ${escapeHtml(c.claim)}</span>
<span class="num-value" style="color:${c.passes ? "#3fb950" : "#f85149"};">${c.passes ? "✓" : "✗"}</span>
</div>`;
}).join("");
$("consistency-result").innerHTML = `
<div style="padding:0.7em; border-left:3px solid ${allOk ? "#3fb950" : "#f85149"}; background:rgba(${allOk ? "63,185,80" : "248,81,73"},0.08); margin-bottom:0.5em;">
<strong>${allOk ? "✅" : "❌"} ${passed}/${total} D-SAGE identities ${allOk ? "consistent" : "FAILED"}</strong>
<div style="font-size:0.9em; opacity:0.85; margin-top:0.3em;">${escapeHtml(r.interpretation)}</div>
<div style="font-size:0.82em; opacity:0.75; margin-top:0.3em; font-style:italic;">Verified by: ${escapeHtml(r.framework_verified_by)}</div>
</div>
<details style="margin-top:0.4em;">
<summary style="cursor:pointer; font-size:0.9em;">🔍 Per-identity details (${total} checks)</summary>
<div style="padding:0.5em 0;">${checksRows}</div>
</details>
`;
} catch (err) {
$("consistency-result").innerHTML = `<div style="color:#f85149;">❌ Error: ${escapeHtml(err.message || String(err))}</div>`;
console.error(err);
}
});
}
// ════════════════════════════════════════════════════════════════════
// COMPARE mode
// ════════════════════════════════════════════════════════════════════
$("compare-recipe").addEventListener("change", () => {
$("compare-btn").disabled = !$("compare-recipe").value;
});
document.querySelectorAll(".compare-preset").forEach(sel => {
sel.addEventListener("change", (e) => {
const slot = e.target.closest(".compare-slot");
if (e.target.value) {
slot.querySelector(".compare-hf-id").value = e.target.value;
}
});
});
$("compare-btn").addEventListener("click", async () => {
const recipeId = $("compare-recipe").value;
if (!recipeId) { alert("Pick a recipe first."); return; }
const T_eval = parseInt($("compare-T_eval").value);
const slots = document.querySelectorAll(".compare-slot");
const specs = [];
setStatus("⏳ Fetching configs for compared models...");
$("compare-btn").disabled = true;
for (const slot of slots) {
const id = slot.querySelector(".compare-hf-id").value.trim();
if (!id) continue;
try {
let preset = null;
const presetProxy = state.pyodide.runPython(`get_preset(${JSON.stringify(id)})`);
const p = presetProxy.toJs ? presetProxy.toJs({ dict_converter: Object.fromEntries }) : presetProxy;
if (p && Object.keys(p).length > 0) {
preset = p;
} else {
const cfg = await fetchHfConfig(id);
preset = configToPreset(cfg, id);
}
specs.push({ ...preset, label: id.split("/").pop() });
} catch (err) {
console.error("compare fetch fail for", id, err);
setStatus(`⚠ Skipped ${id}: ${err.message}`);
}
}
if (specs.length < 2) {
setStatus("❌ Need at least 2 models to compare.");
$("compare-btn").disabled = false;
return;
}
setStatus(`🧮 Comparing ${specs.length} models on ${recipeId}...`);
try {
state.pyodide.globals.set("__cspecs", state.pyodide.toPy(specs));
state.pyodide.globals.set("__crid", recipeId);
state.pyodide.globals.set("__cshared", state.pyodide.toPy({ T_eval }));
const json = state.pyodide.runPython(`
import json
result = compare_models(__cspecs.to_py(), __crid, __cshared.to_py())
json.dumps(result)
`);
const cmp = JSON.parse(json);
renderCompare(cmp);
state.lastResult = { type: "compare", recipeId, T_eval, specs };
state.lastFullResult = cmp;
setStatus("✅ Comparison ready.");
} catch (err) {
setStatus(`❌ ${err.message}`);
console.error(err);
} finally {
$("compare-btn").disabled = false;
}
});
function renderCompare(cmp) {
$("compare-output").style.display = "block";
$("output-section").style.display = "none";
$("profile-output").style.display = "none";
const verdictClass = (v) => {
if (v.startsWith("YES") || v === "GO" || v.startsWith("USE SOFT")) return "v-yes";
if (v.startsWith("NO") || v.startsWith("MEMORY")) return "v-no";
return "v-deg";
};
// Collect all unique key_numbers across rows
const allKeys = new Set();
cmp.rows.forEach(r => Object.keys(r.key_numbers || {}).forEach(k => allKeys.add(k)));
let html = `
<p class="recipe-desc"><strong>Recipe:</strong> ${escapeHtml(cmp.recipe_id)}${escapeHtml(cmp.recipe_name)}</p>
<p class="recipe-desc"><strong>Shared params:</strong> ${escapeHtml(JSON.stringify(cmp.shared_params))}</p>
<table class="compare-table">
<thead>
<tr><th>Model</th><th>Verdict</th><th>Reason</th>
`;
allKeys.forEach(k => html += `<th>${escapeHtml(k)}</th>`);
html += "</tr></thead><tbody>";
cmp.rows.forEach(r => {
const cls = verdictClass(r.verdict);
html += `<tr><td><strong>${escapeHtml(r.label)}</strong></td>`;
html += `<td class="${cls}">${escapeHtml(r.verdict)}</td>`;
html += `<td>${escapeHtml(r.reason)}</td>`;
allKeys.forEach(k => {
const v = r.key_numbers ? r.key_numbers[k] : null;
html += `<td>${v === undefined || v === null ? "—" : (typeof v === "number" ? v.toLocaleString(undefined, { maximumFractionDigits: 2 }) : escapeHtml(String(v)))}</td>`;
});
html += "</tr>";
});
html += `</tbody></table>
<div class="share-bar">
<button class="secondary" id="compare-share-btn" data-i18n="share.btn">🔗 Copy share link</button>
<button class="secondary" id="compare-download-btn" data-i18n="share.download">💾 Download JSON</button>
<button class="secondary" id="compare-download-md-btn" data-i18n="share.download_md">📝 Markdown</button>
<button class="secondary" id="compare-download-tex-btn" data-i18n="share.download_tex">📜 LaTeX</button>
<button class="secondary" id="compare-submit-btn" data-i18n="share.submit">📤 Submit to registry</button>
<span id="compare-share-status" class="subtle"></span>
</div>
`;
$("compare-box").innerHTML = html;
if (window.__taf_applyTranslations) window.__taf_applyTranslations();
$("compare-share-btn").addEventListener("click", () => {
const params = { recipeId: cmp.recipe_id, T_eval: cmp.shared_params.T_eval,
models: cmp.rows.map(r => r.label) };
copyShareLink("compare", params);
});
$("compare-download-btn").addEventListener("click", async () => {
const filename = await makeFilename("compare", cmp);
const data = await exportableData("compare", cmp);
downloadJSON(filename, data);
$("compare-share-status").textContent = `✅ Downloaded ${filename}`;
setTimeout(() => $("compare-share-status").textContent = "", 5000);
});
$("compare-download-md-btn").addEventListener("click", async () => {
const hash = await inputHash("compare", cmp);
const base = (await makeFilename("compare", cmp)).replace(/\.json$/, "");
downloadText(`${base}.md`, compareToMarkdown(cmp, hash), "text/markdown;charset=utf-8");
$("compare-share-status").textContent = `✅ Downloaded ${base}.md`;
setTimeout(() => $("compare-share-status").textContent = "", 5000);
});
$("compare-download-tex-btn").addEventListener("click", async () => {
const hash = await inputHash("compare", cmp);
const base = (await makeFilename("compare", cmp)).replace(/\.json$/, "");
downloadText(`${base}.tex`, compareToLatex(cmp, hash), "application/x-tex;charset=utf-8");
$("compare-share-status").textContent = `✅ Downloaded ${base}.tex`;
setTimeout(() => $("compare-share-status").textContent = "", 5000);
});
$("compare-submit-btn").addEventListener("click", async () => {
await submitToRegistry("compare", cmp, $("compare-share-status"));
setTimeout(() => $("compare-share-status").textContent = "", 8000);
});
}
// ════════════════════════════════════════════════════════════════════
// SHARE — encode current state to URL
// ════════════════════════════════════════════════════════════════════
function copyShareLink(mode, params) {
const url = new URL(window.location.href.split("?")[0]);
url.searchParams.set("mode", mode);
url.searchParams.set("p", btoa(JSON.stringify(params)));
navigator.clipboard.writeText(url.toString()).then(
() => {
const tgt = $("share-status") || $("profile-share-status") || $("compare-share-status");
if (tgt) {
tgt.textContent = "✅ Copied to clipboard!";
setTimeout(() => tgt.textContent = "", 3000);
}
},
() => alert("Copy failed. Manually copy: " + url.toString())
);
}
function parseUrlState() {
const params = new URLSearchParams(window.location.search);
const mode = params.get("mode");
const pData = params.get("p");
if (!mode || !pData) return;
try {
const decoded = JSON.parse(atob(pData));
// Switch to right mode tab
const btn = document.querySelector(`.mode-btn[data-mode="${mode}"]`);
if (btn) btn.click();
// Wait a tick for tab to render
setTimeout(() => {
if (mode === "profile") {
Object.entries(decoded).forEach(([k, v]) => {
const map = { theta: "profile-theta", T_train: "profile-T_train",
T_eval: "profile-T_eval",
n_attention_heads: "profile-n_attn", n_kv_heads: "profile-n_kv",
d_head: "profile-d_head", n_layers: "profile-n_layers",
n_params: "profile-n_params", has_SWA: "profile-has_swa" };
const id = map[k];
if (id && $(id)) $(id).value = String(v);
});
setTimeout(() => $("profile-btn").click(), 200);
}
// Other modes: future
}, 200);
} catch (e) {
console.warn("Failed to parse URL state:", e);
}
}
// Wire single-recipe share/download/submit buttons
$("share-btn").addEventListener("click", () => {
if (!state.lastResult) return;
copyShareLink(state.lastResult.type || "recipe", state.lastResult.params || {});
});
$("recipe-download-btn").addEventListener("click", async () => {
if (!state.lastFullResult) return;
const filename = await makeFilename("recipe", state.lastFullResult);
const data = await exportableData("recipe", state.lastFullResult);
downloadJSON(filename, data);
$("share-status").textContent = `✅ Downloaded ${filename}`;
setTimeout(() => $("share-status").textContent = "", 5000);
});
$("recipe-download-md-btn").addEventListener("click", async () => {
if (!state.lastFullResult) return;
const r = state.lastFullResult;
const hash = await inputHash("recipe", r);
const base = (await makeFilename("recipe", r)).replace(/\.json$/, "");
downloadText(`${base}.md`, recipeToMarkdown(r, hash), "text/markdown;charset=utf-8");
$("share-status").textContent = `✅ Downloaded ${base}.md`;
setTimeout(() => $("share-status").textContent = "", 5000);
});
$("recipe-download-tex-btn").addEventListener("click", async () => {
if (!state.lastFullResult) return;
const r = state.lastFullResult;
const hash = await inputHash("recipe", r);
const base = (await makeFilename("recipe", r)).replace(/\.json$/, "");
downloadText(`${base}.tex`, recipeToLatex(r, hash), "application/x-tex;charset=utf-8");
$("share-status").textContent = `✅ Downloaded ${base}.tex`;
setTimeout(() => $("share-status").textContent = "", 5000);
});
$("recipe-submit-btn").addEventListener("click", async () => {
if (!state.lastFullResult) return;
await submitToRegistry("recipe", state.lastFullResult, $("share-status"));
setTimeout(() => $("share-status").textContent = "", 8000);
});
// ════════════════════════════════════════════════════════════════════
// Help modal
// ════════════════════════════════════════════════════════════════════
// a11y: focus trap + restore + Esc handling, generalized to any modal that follows
// the [role="dialog"] + .open pattern. Each call to wireModal() returns { open, close }
// and registers the modal so the global keyboard handler can find the active one.
const __modalCloseFns = new Map();
function wireModal(modalId, btnId, closeId) {
const modal = $(modalId);
if (!modal) return null;
let returnFocus = null;
const open = () => {
returnFocus = document.activeElement;
modal.classList.add("open");
modal.setAttribute("aria-hidden", "false");
setTimeout(() => $(closeId)?.focus(), 0);
};
const close = () => {
modal.classList.remove("open");
modal.setAttribute("aria-hidden", "true");
if (returnFocus && typeof returnFocus.focus === "function") returnFocus.focus();
returnFocus = null;
};
$(btnId)?.addEventListener("click", open);
$(closeId)?.addEventListener("click", close);
modal.addEventListener("click", (e) => { if (e.target.id === modalId) close(); });
__modalCloseFns.set(modalId, close);
return { open, close };
}
wireModal("help-modal", "help-btn", "help-close");
wireModal("quickstart-modal", "quickstart-btn", "quickstart-close");
wireModal("inventory-modal", "inventory-btn", "inventory-close");
// Quick-start modal "↓ Start now" link should also close the modal so user lands on mode-section.
$("qs-start-link")?.addEventListener("click", () => __modalCloseFns.get("quickstart-modal")?.());
// Esc closes whichever modal is open; Tab cycles within it.
document.addEventListener("keydown", (e) => {
const openModal = document.querySelector('[role="dialog"].open');
if (!openModal) return;
if (e.key === "Escape") {
e.preventDefault();
__modalCloseFns.get(openModal.id)?.();
return;
}
if (e.key !== "Tab") return;
const focusables = openModal.querySelectorAll(
'a[href], button:not([disabled]), input:not([disabled]), select:not([disabled]), textarea:not([disabled]), [tabindex]:not([tabindex="-1"])'
);
if (!focusables.length) return;
const first = focusables[0];
const last = focusables[focusables.length - 1];
if (e.shiftKey && document.activeElement === first) { e.preventDefault(); last.focus(); }
else if (!e.shiftKey && document.activeElement === last) { e.preventDefault(); first.focus(); }
});
// ════════════════════════════════════════════════════════════════════
// SHARING — Download / Upload / Submit to registry
// ════════════════════════════════════════════════════════════════════
const REGISTRY_REPO = "karlesmarin/tafagent-registry";
function downloadJSON(filename, data) {
const blob = new Blob([JSON.stringify(data, null, 2)], { type: "application/json" });
const url = URL.createObjectURL(blob);
const a = document.createElement("a");
a.href = url;
a.download = filename;
document.body.appendChild(a);
a.click();
setTimeout(() => { document.body.removeChild(a); URL.revokeObjectURL(url); }, 100);
}
function downloadText(filename, text, mime = "text/plain;charset=utf-8") {
const blob = new Blob([text], { type: mime });
const url = URL.createObjectURL(blob);
const a = document.createElement("a");
a.href = url;
a.download = filename;
document.body.appendChild(a);
a.click();
setTimeout(() => { document.body.removeChild(a); URL.revokeObjectURL(url); }, 100);
}
// LaTeX-escape a plain string for inclusion in a tabular cell.
function latexEscape(s) {
return String(s ?? "")
.replace(/\\/g, "\\textbackslash{}")
.replace(/[#$%&_{}]/g, m => "\\" + m)
.replace(/~/g, "\\textasciitilde{}")
.replace(/\^/g, "\\textasciicircum{}")
.replace(/</g, "\\textless{}")
.replace(/>/g, "\\textgreater{}");
}
function profileToLatex(p, hash = "") {
const ms = p.model_summary || {};
const kn = p.key_numbers || {};
let tex = `% TAF Profile — auto-generated by TAF Agent\n`;
if (hash) tex += `% input hash: #${hash}\n`;
tex += `\\begin{table}[ht]\n\\centering\n`;
tex += `\\caption{TAF Profile — ${latexEscape(ms.architecture_class || "?")}${hash ? ` (\\#${latexEscape(hash)})` : ""}}\n`;
tex += `\\begin{tabular}{lll}\n\\toprule\nRecipe & Verdict & Reason \\\\\n\\midrule\n`;
Object.entries(p.recipes || {}).forEach(([rid, r]) => {
tex += `${latexEscape(rid)} & ${latexEscape(r.verdict || "")} & ${latexEscape((r.reason || "").slice(0, 80))} \\\\\n`;
});
tex += `\\bottomrule\n\\end{tabular}\n\\end{table}\n\n`;
tex += `% Key numbers (JSON):\n`;
for (const [k, v] of Object.entries(kn)) {
tex += `% ${k} = ${typeof v === "object" ? JSON.stringify(v) : v}\n`;
}
return tex;
}
function compareToLatex(c, hash = "") {
let tex = `% TAF Comparison — ${c.recipe_id} (${c.recipe_name})\n`;
if (hash) tex += `% input hash: #${hash}\n`;
tex += `\\begin{table}[ht]\n\\centering\n`;
tex += `\\caption{TAF Comparison — ${latexEscape(c.recipe_id)} ${latexEscape(c.recipe_name || "")}${hash ? ` (\\#${latexEscape(hash)})` : ""}}\n`;
tex += `\\begin{tabular}{lll}\n\\toprule\nModel & Verdict & Reason \\\\\n\\midrule\n`;
c.rows.forEach(r => {
tex += `${latexEscape(r.label)} & ${latexEscape(r.verdict)} & ${latexEscape((r.reason || "").slice(0, 80))} \\\\\n`;
});
tex += `\\bottomrule\n\\end{tabular}\n\\end{table}\n`;
return tex;
}
function recipeToLatex(r, hash = "") {
let tex = `% TAF Recipe ${r.recipe_id}${r.recipe_name}\n`;
if (hash) tex += `% input hash: #${hash}\n`;
tex += `\\begin{table}[ht]\n\\centering\n`;
tex += `\\caption{TAF Recipe \\texttt{${latexEscape(r.recipe_id)}} — verdict: ${latexEscape(r.verdict)}${hash ? ` (\\#${latexEscape(hash)})` : ""}}\n`;
tex += `\\begin{tabular}{rll}\n\\toprule\nStep & Formula & Result \\\\\n\\midrule\n`;
(r.chain || []).forEach(s => {
tex += `${latexEscape(s.step)} & \\texttt{${latexEscape(s.formula || "")}} & ${latexEscape(formatResultPlain(s.result))} \\\\\n`;
});
tex += `\\bottomrule\n\\end{tabular}\n\\end{table}\n\n`;
tex += `% Reason: ${latexEscape(r.reason || "")}\n`;
if (r.mitigation) tex += `% Mitigation: ${latexEscape(r.mitigation)}\n`;
return tex;
}
// Sort object keys recursively for deterministic JSON
function sortKeys(o) {
if (Array.isArray(o)) return o.map(sortKeys);
if (o && typeof o === "object") {
return Object.keys(o).sort().reduce((acc, k) => { acc[k] = sortKeys(o[k]); return acc; }, {});
}
return o;
}
// Compute 8-char hex hash of canonical inputs.
// Identical inputs → identical hash (forever). Different inputs → different hash.
async function inputHash(type, data) {
let canonical;
if (type === "profile") {
const ms = data.model_summary || data;
canonical = sortKeys({
type: "profile",
theta: ms.rope_theta ?? ms.theta,
T_train: ms.T_train,
T_eval: ms.T_eval,
n_attn: ms.n_attention_heads ?? ms.n_attn,
n_kv: ms.n_kv_heads ?? ms.n_kv,
d_head: ms.d_head,
n_layers: ms.n_layers,
n_params: ms.n_params,
has_SWA: ms.has_SWA,
});
} else if (type === "compare") {
canonical = sortKeys({
type: "compare",
recipe: data.recipe_id,
T_eval: (data.shared_params || {}).T_eval,
models: (data.rows || []).map(r => r.label).sort(),
});
} else {
canonical = sortKeys({
type: "recipe",
recipe: data.recipe_id,
inputs: data.inputs || {},
});
}
const text = JSON.stringify(canonical);
const buf = new TextEncoder().encode(text);
const hashBuf = await crypto.subtle.digest("SHA-256", buf);
return Array.from(new Uint8Array(hashBuf)).slice(0, 4)
.map(b => b.toString(16).padStart(2, "0")).join("");
}
function safeFilename(s) {
return String(s).replace(/[/\\?%*:|"<>]/g, "-").replace(/^-+|-+$/g, "").slice(0, 60);
}
function modelShortName(data, fallback="model") {
// Try to get from various places
if (state.lastModelId) return safeFilename(state.lastModelId);
if (data && data.model_summary) {
const ms = data.model_summary;
return safeFilename(`m${ms.n_params || 0}${ms.rope_theta || 0}`);
}
if (data && data.inputs) {
const i = data.inputs;
return safeFilename(`m${i.n_params || ""}${i.theta || ""}`);
}
return fallback;
}
async function exportableData(type, data) {
const hash = await inputHash(type, data);
return {
_taf_export: true,
_taf_type: type,
_taf_version: "0.2",
_taf_input_hash: hash, // identical inputs ⇒ identical hash
_taf_timestamp: new Date().toISOString(),
payload: data,
};
}
async function makeFilename(type, data) {
const hash = await inputHash(type, data);
const name = modelShortName(data);
let suffix;
if (type === "profile" && data.model_summary?.T_eval) suffix = `T${data.model_summary.T_eval}`;
else if (type === "compare" && data.shared_params?.T_eval) suffix = `T${data.shared_params.T_eval}`;
else if (type === "recipe" && data.inputs?.T_eval) suffix = `T${data.inputs.T_eval}`;
else suffix = data.recipe_id || "result";
return `taf-${type}-${name}-${suffix}-${hash}.json`;
}
// v0.6 privacy fix: previously placed full JSON body in URL params → GH server logs +
// referer headers captured user data. Now copy body to clipboard, open issue page
// with title only, user pastes body manually. Title is non-sensitive (model name +
// hash). On clipboard failure, fall back to console log so user can grab body.
async function submitToRegistry(type, data, statusEl) {
const hash = await inputHash(type, data);
const modelName = modelShortName(data, "model");
let title, body;
if (type === "profile") {
const ms = data.model_summary || {};
title = `[TAF Profile] ${modelName} @ T=${ms.T_eval || "?"} #${hash}`;
body = profileToMarkdown(data, hash);
} else if (type === "compare") {
title = `[TAF Compare] ${data.recipe_id} × ${data.rows.length} models #${hash}`;
body = compareToMarkdown(data, hash);
} else {
title = `[TAF ${data.recipe_id}] ${modelName}${data.verdict} #${hash}`;
body = recipeToMarkdown(data, hash);
}
const dedupNote = `\n\n> **Input hash**: \`#${hash}\` — search this hash in registry issues to find independent verifications. Same inputs always produce the same hash.`;
const fullBody = body + dedupNote + "\n\n---\n*Submitted via [TAF Agent](https://karlesmarin.github.io/tafagent)*";
let clipboardOk = false;
try {
await navigator.clipboard.writeText(fullBody);
clipboardOk = true;
} catch (e) {
console.warn("Clipboard write failed; body logged below:", e);
console.log("[TAF Agent] Issue body to paste:\n\n" + fullBody);
}
// Title-only URL — body intentionally omitted to avoid leaking via GH server logs / referer.
const params = new URLSearchParams({ title });
window.open(`https://github.com/${REGISTRY_REPO}/issues/new?${params.toString()}`, "_blank");
if (statusEl) {
statusEl.textContent = clipboardOk
? (t("share.submit_clip_ok") || "↗ Opened GitHub. Body copied to clipboard — paste it into the issue body.")
: (t("share.submit_clip_fail") || "↗ Opened GitHub. Clipboard blocked — body logged in browser console (F12).");
}
}
function profileToMarkdown(p, hash="") {
const ms = p.model_summary || {};
const kn = p.key_numbers || {};
let md = `## TAF Profile`;
if (hash) md += ` \`#${hash}\``;
md += `\n\n`;
md += `**Architecture**: ${ms.architecture_class || "?"}\n`;
md += `**Params**: ${ms.n_params}, **T_train**: ${ms.T_train}, **T_eval**: ${ms.T_eval}\n`;
md += `**θ**: ${ms.rope_theta}, GQA=${ms.has_GQA}, SWA=${ms.has_SWA}\n\n`;
md += `### Recipes\n\n`;
Object.entries(p.recipes || {}).forEach(([rid, r]) => {
md += `- **${rid}** (${r.name || ""}): ${r.verdict}${r.reason}\n`;
});
md += `\n### Key numbers\n\n\`\`\`json\n${JSON.stringify(kn, null, 2)}\n\`\`\`\n`;
md += `\n### Full data\n\n<details><summary>Click to expand</summary>\n\n\`\`\`json\n${JSON.stringify(p, null, 2)}\n\`\`\`\n\n</details>\n`;
return md;
}
function compareToMarkdown(c, hash="") {
let md = `## TAF Comparison — ${c.recipe_id} (${c.recipe_name})`;
if (hash) md += ` \`#${hash}\``;
md += `\n\n`;
md += `**Shared params**: \`${JSON.stringify(c.shared_params)}\`\n\n`;
md += `| Model | Verdict | Reason |\n|-------|---------|--------|\n`;
c.rows.forEach(r => {
md += `| ${r.label} | ${r.verdict} | ${r.reason.slice(0, 80)}${r.reason.length > 80 ? "..." : ""} |\n`;
});
md += `\n<details><summary>Full data</summary>\n\n\`\`\`json\n${JSON.stringify(c, null, 2)}\n\`\`\`\n\n</details>\n`;
return md;
}
function recipeToMarkdown(r, hash="") {
let md = `## TAF Recipe ${r.recipe_id}${r.recipe_name}`;
if (hash) md += ` \`#${hash}\``;
md += `\n\n`;
md += `**Verdict**: ${r.verdict}\n`;
md += `**Reason**: ${r.reason}\n`;
if (r.mitigation) md += `**Action**: ${r.mitigation}\n`;
md += `\n### Inputs\n\n\`\`\`json\n${JSON.stringify(r.inputs, null, 2)}\n\`\`\`\n`;
md += `\n### Computation chain\n\n`;
(r.chain || []).forEach(s => {
md += `**Step ${s.step} ${s.section}** — ${s.name}: \`${s.formula}\` → ${formatResultPlain(s.result)}\n`;
});
md += `\n<details><summary>Full data</summary>\n\n\`\`\`json\n${JSON.stringify(r, null, 2)}\n\`\`\`\n\n</details>\n`;
return md;
}
function importJSON(file, statusEl) {
const reader = new FileReader();
reader.onload = (e) => {
try {
const data = JSON.parse(e.target.result);
if (!data._taf_export) {
statusEl.innerHTML = "❌ Not a TAF export file (missing _taf_export marker).";
return;
}
const type = data._taf_type;
const payload = data.payload;
if (type === "profile") {
renderProfile(payload, payload.model_summary || {});
statusEl.innerHTML = `✅ Profile loaded (${data._taf_timestamp || "?"})`;
} else if (type === "compare") {
renderCompare(payload);
statusEl.innerHTML = `✅ Comparison loaded (${data._taf_timestamp || "?"})`;
} else if (type === "recipe") {
renderResult(payload);
$("output-section").style.display = "block";
statusEl.innerHTML = `✅ Recipe result loaded (${data._taf_timestamp || "?"})`;
} else {
statusEl.innerHTML = `❌ Unknown TAF type: ${type}`;
}
} catch (err) {
statusEl.innerHTML = `❌ Failed to parse JSON: ${err.message}`;
}
};
reader.readAsText(file);
}
// Wire import button (always available)
document.addEventListener("DOMContentLoaded", () => {
const importBtn = document.getElementById("import-btn");
const importFile = document.getElementById("import-file");
if (importBtn && importFile) {
importBtn.addEventListener("click", () => importFile.click());
importFile.addEventListener("change", (e) => {
const file = e.target.files[0];
if (file) importJSON(file, document.getElementById("import-status"));
});
}
// Lean+Mathlib manifest — load in parallel with everything else; badges
// appear once it resolves, but app stays usable if it fails.
loadLeanManifest().catch(err => console.warn("Lean manifest unavailable:", err));
});
// ════════════════════════════════════════════════════════════════════
// Language switcher
// ════════════════════════════════════════════════════════════════════
document.querySelectorAll(".lang-btn").forEach(btn => {
btn.addEventListener("click", () => setLang(btn.dataset.lang));
});
// ════════════════════════════════════════════════════════════════════
// Bootstrap
// ════════════════════════════════════════════════════════════════════
initI18n();
loadPyodideAndTaf().catch(err => {
setStatus(`❌ Failed to initialise: ${err.message || err}`);
console.error(err);
});