{% extends "base.html" %}
{% set nav = 'train' %}
{% block title %}New run — NanoDex{% endblock %}
{% block body %}

<div style="margin-bottom:24px">
  <span class="eyebrow">New training run</span>
  <h1 style="font-size:28px;margin-top:5px">Build a model from nothing</h1>
</div>

<div class="steps">
  <div class="stp on" data-s="1"><div class="n">Step 1</div><div class="t">Size</div></div>
  <div class="stp" data-s="2"><div class="n">Step 2</div><div class="t">Tokens</div></div>
  <div class="stp" data-s="3"><div class="n">Step 3</div><div class="t">Name</div></div>
  <div class="stp" data-s="4"><div class="n">Step 4</div><div class="t">Review</div></div>
</div>

<!-- STEP 1 ---------------------------------------------------------------->
<div class="panelstep on" data-p="1">
  <h2 style="font-size:19px">How big should it be?</h2>
  <p class="sub" style="margin:6px 0 20px">Every tier is the same architecture —
    a <span class="mono">LlamaForCausalLM</span> decoder-only transformer with
    SiLU MLPs, RMSNorm, rotary embeddings and grouped-query attention — scaled
    down in width and depth. The parameter counts below are totals, embeddings
    included.</p>

  <div class="picks">
    {% for t in tiers %}
    <button type="button" class="pick {{ 'on' if t.key == '1m' }}" data-tier="{{ t.key }}"
            data-params="{{ t.params }}" data-label="{{ t.label }}">
      <b>{{ t.label }}</b>
      <div class="p-n">{{ "{:,}".format(t.params) }} params</div>
      <div class="p-d">
        {{ t.layers }} layers · {{ t.hidden }} hidden<br>
        {{ t.heads }} heads ({{ t.kv_heads }} KV)<br>
        FFN {{ t.ffn }} · ctx {{ seq_len }}
      </div>
    </button>
    {% endfor %}
  </div>

  <div style="display:flex;justify-content:flex-end;margin-top:24px">
    <button class="btn primary" data-go="2">Continue &nbsp;→</button>
  </div>
</div>

<!-- STEP 2 ---------------------------------------------------------------->
<div class="panelstep" data-p="2">
  <h2 style="font-size:19px">How much should it read?</h2>
  <p class="sub" style="margin:6px 0 24px">Training data is
    <a href="https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu" target="_blank"
       rel="noopener" style="color:var(--accent)">fineweb-edu</a> — filtered
    educational web text. More tokens means a sharper model and a longer wait.</p>

  <div class="card pad-lg">
    <div style="display:flex;justify-content:space-between;align-items:baseline;margin-bottom:16px">
      <label class="fl" style="margin:0">Token budget</label>
      <div class="mono" style="font-size:26px;font-weight:680;color:var(--accent)"
           id="tokLabel">500M</div>
    </div>
    <input type="range" id="tok" min="0" max="{{ stops|length - 1 }}"
           value="4" step="1">
    <div class="mono muted"
         style="display:flex;justify-content:space-between;margin-top:9px;font-size:12px">
      <span>200M</span><span>500M</span><span>1B</span><span>1.5B</span>
    </div>
    <div class="quickpick">
      {% for m in [200, 500, 1000, 1500] %}
      <button type="button" class="btn sm" data-tokens="{{ m }}">
        {{ (m / 1000)|round(1)|string|replace('.0','') ~ 'B' if m >= 1000
           else (m|string ~ 'M') }}</button>
      {% endfor %}
    </div>
  </div>

  <div class="grid g4" style="margin-top:16px">
    <div class="stat"><span>Parameters</span><b id="e-params">—</b><small id="e-tier">&nbsp;</small></div>
    <div class="stat"><span>Optimizer steps</span><b id="e-steps">—</b><small>gradient updates</small></div>
    <div class="stat"><span>Estimated time</span><b id="e-eta">—</b><small id="e-cal">&nbsp;</small></div>
    <div class="stat"><span>Tokens / param</span><b id="e-ratio">—</b><small id="e-chin">&nbsp;</small></div>
  </div>

  <p class="hint" id="scaleNote"></p>

  <div style="display:flex;justify-content:space-between;margin-top:24px">
    <button class="btn ghost" data-go="1">← Back</button>
    <button class="btn primary" data-go="3">Continue &nbsp;→</button>
  </div>
</div>

<!-- STEP 3 ---------------------------------------------------------------->
<div class="panelstep" data-p="3">
  <h2 style="font-size:19px">Give it a name</h2>
  <p class="sub" style="margin:6px 0 20px">This is what you'll see in your model
    list, and the default repository name when you publish it.</p>

  <div class="card pad-lg" style="max-width:560px">
    <label class="fl" for="name">Model name</label>
    <input type="text" id="name" placeholder="my-first-lm" maxlength="80" autocomplete="off">
    <p class="hint">Letters, numbers, <span class="mono">-</span>,
      <span class="mono">_</span> and <span class="mono">.</span>. Leave it blank
      and we'll name it after the size and token budget.</p>
    <p class="hint" style="margin-top:14px">Will publish to
      <span class="mono" style="color:var(--fg-2)">{{ user.username }}/<span id="namePreview">…</span></span></p>
  </div>

  <div style="display:flex;justify-content:space-between;margin-top:24px">
    <button class="btn ghost" data-go="2">← Back</button>
    <button class="btn primary" data-go="4">Review &nbsp;→</button>
  </div>
</div>

<!-- STEP 4 ---------------------------------------------------------------->
<div class="panelstep" data-p="4">
  <h2 style="font-size:19px">Ready to launch</h2>
  <p class="sub" style="margin:6px 0 20px">Your run joins the shared queue. You
    can watch it — or close the tab and come back; it keeps going either way.</p>

  <div class="grid g2">
    <div class="card pad-lg">
      <span class="eyebrow">Model</span>
      <div style="margin-top:12px">
        <div class="kv"><span>Name</span><b id="r-name">—</b></div>
        <div class="kv"><span>Size</span><b id="r-tier">—</b></div>
        <div class="kv"><span>Parameters</span><b id="r-params">—</b></div>
        <div class="kv"><span>Architecture</span><b id="r-arch">—</b></div>
        <div class="kv"><span>Vocabulary</span><b>{{ "{:,}".format(vocab) }} BPE</b></div>
        <div class="kv"><span>Context</span><b>{{ seq_len }} tokens</b></div>
      </div>
    </div>
    <div class="card pad-lg">
      <span class="eyebrow">Training</span>
      <div style="margin-top:12px">
        <div class="kv"><span>Dataset</span><b>fineweb-edu</b></div>
        <div class="kv"><span>Token budget</span><b id="r-tok">—</b></div>
        <div class="kv"><span>Optimizer steps</span><b id="r-steps">—</b></div>
        <div class="kv"><span>Optimizer</span><b>AdamW · cosine</b></div>
        <div class="kv"><span>Estimated time</span><b id="r-eta">—</b></div>
        <div class="kv"><span>Queue limit</span><b>{{ max_active }} runs per person</b></div>
      </div>
    </div>
  </div>

  <div style="display:flex;justify-content:space-between;margin-top:24px;gap:12px;flex-wrap:wrap">
    <button class="btn ghost" data-go="3">← Back</button>
    <button class="btn primary lg" id="launch">Queue this run &nbsp;→</button>
  </div>
</div>

{% endblock %}
{% block scripts %}
<script>
const STOPS = {{ stops | tojson }};
const state = { tier:'1m', tokens:500, name:'' };

function labelTokens(m){
  return m >= 1000 ? String(m/1000).replace(/\.0$/,'') + 'B' : m + 'M';
}
let est = null;

function showStep(n){
  document.querySelectorAll('.panelstep').forEach(p =>
    p.classList.toggle('on', p.dataset.p === String(n)));
  document.querySelectorAll('.stp').forEach(s => {
    const i = Number(s.dataset.s);
    s.classList.toggle('on', i === n);
    s.classList.toggle('ok', i < n);
  });
  window.scrollTo({top:0, behavior:'smooth'});
  if(n === 4) fillReview();
}

document.querySelectorAll('[data-go]').forEach(b =>
  b.addEventListener('click', () => showStep(Number(b.dataset.go))));
document.querySelectorAll('.stp').forEach(s =>
  s.addEventListener('click', () => showStep(Number(s.dataset.s))));

document.querySelectorAll('.pick[data-tier]').forEach(p =>
  p.addEventListener('click', () => {
    document.querySelectorAll('.pick[data-tier]').forEach(q => q.classList.remove('on'));
    p.classList.add('on');
    state.tier = p.dataset.tier;
    updateEstimate();
  }));

const tok = document.getElementById('tok');
function setTokens(m){
  const i = STOPS.indexOf(m);
  state.tokens = m;
  if(i >= 0) tok.value = i;
  document.getElementById('tokLabel').textContent = labelTokens(m);
  updateEstimate();
}
tok.addEventListener('input', () => setTokens(STOPS[Number(tok.value)]));
document.querySelectorAll('[data-tokens]').forEach(b =>
  b.addEventListener('click', () => setTokens(Number(b.dataset.tokens))));

const nameEl = document.getElementById('name');
nameEl.addEventListener('input', () => {
  state.name = nameEl.value;
  document.getElementById('namePreview').textContent = defaultName();
});

function defaultName(){
  const s = state.name.trim().replace(/[^A-Za-z0-9._-]+/g,'-').replace(/^[-._]+|[-._]+$/g,'');
  if(s) return s.slice(0,80);
  const sel = document.querySelector('.pick.on[data-tier]');
  return (sel ? sel.dataset.label.toLowerCase() : 'nanodex')
         + '-' + labelTokens(state.tokens).toLowerCase();
}

let estTimer;
function updateEstimate(){
  clearTimeout(estTimer);
  estTimer = setTimeout(async () => {
    try{
      est = await NX.get(`/api/estimate?tier=${state.tier}&tokens=${state.tokens*1e6}`);
    }catch(e){ return; }
    const sel = document.querySelector('.pick.on[data-tier]');
    document.getElementById('e-params').textContent = Number(est.n_params).toLocaleString();
    document.getElementById('e-tier').textContent = sel ? sel.dataset.label : '';
    document.getElementById('e-steps').textContent = Number(est.steps).toLocaleString();
    document.getElementById('e-eta').textContent = est.eta_human;
    document.getElementById('e-cal').textContent = est.calibrated
      ? 'from real runs here' : 'prior — self-calibrates';
    document.getElementById('e-ratio').textContent = Math.round(est.ratio) + ':1';
    document.getElementById('e-chin').textContent =
      est.chinchilla_x.toFixed(1) + '× Chinchilla';

    const r = est.ratio;
    document.getElementById('scaleNote').textContent = r < 60
      ? 'Under ~60 tokens per parameter this model never uses the capacity it has. Either raise the budget or pick a smaller size.'
      : (r < 150
        ? 'Workable, but on the thin side for this size — 300:1 or more is where these models get interesting.'
        : (r > 2000
          ? 'Very deep into the over-trained regime. Still improves, but the last few hundred million tokens buy little — a larger size would use them better.'
          : 'A good range for this size: well past compute-optimal, and it still finishes in reasonable time.'));
    document.getElementById('namePreview').textContent = defaultName();
  }, 140);
}

function fillReview(){
  const sel = document.querySelector('.pick.on[data-tier]');
  document.getElementById('r-name').textContent = defaultName();
  document.getElementById('r-tier').textContent = sel ? sel.dataset.label : '—';
  document.getElementById('r-params').textContent =
    sel ? Number(sel.dataset.params).toLocaleString() : '—';
  const d = sel ? sel.querySelector('.p-d').textContent.trim().split('·') : [];
  document.getElementById('r-arch').textContent = 'LlamaForCausalLM';
  document.getElementById('r-tok').textContent = labelTokens(state.tokens) + ' tokens';
  document.getElementById('r-steps').textContent =
    est ? Number(est.steps).toLocaleString() : '—';
  document.getElementById('r-eta').textContent = est ? est.eta_human : '—';
}

document.getElementById('launch').addEventListener('click', async (ev) => {
  const b = ev.currentTarget;
  b.disabled = true; b.textContent = 'Queueing…';
  try{
    const r = await NX.post('/api/jobs', {
      tier: state.tier, tokens: state.tokens * 1e6, name: state.name
    });
    location.href = '/models/' + r.id;
  }catch(e){
    NX.toast(NX.esc(e.message), 'err');
    b.disabled = false; b.innerHTML = 'Queue this run &nbsp;→';
  }
});

setTokens(state.tokens);
document.getElementById('namePreview').textContent = defaultName();
</script>
{% endblock %}