feat(demo): illustrative aroma-descriptor preview

training/app.py

@@ -189,6 +189,57 @@ def api_suggest(qs: str = ""):
     return {"items": items}
 
 
+# --- Aroma PREVIEW (illustrative, NOT a trained model) -------------------------
+# Well-known odor characters for a handful of famous flavor molecules, so the demo can
+# SHOW what an unlocked aroma read looks like. These are common-knowledge descriptors
+# used as an illustration — the real model trains on a customer's expert-labeled odor
+# data (see docs/AROMA.md). Clearly flagged "preview" in the UI; never passed off as live.
+_AROMA_PREVIEW_RAW = [
+    ("O=Cc1ccc(O)c(OC)c1", [("vanilla", 0.95), ("sweet", 0.6), ("creamy", 0.4), ("woody", 0.25)]),
+    ("CC1=CCC(CC1)C(C)=C", [("citrus", 0.9), ("orange", 0.7), ("fresh", 0.5), ("terpene", 0.3)]),
+    ("CC(C)C1CCC(C)CC1O", [("minty", 0.9), ("cooling", 0.7), ("fresh", 0.5), ("herbal", 0.3)]),
+    ("C=CCc1ccc(O)c(OC)c1", [("clove", 0.9), ("spicy", 0.7), ("woody", 0.4), ("sweet", 0.3)]),
+    ("O=Cc1ccccc1", [("almond", 0.95), ("cherry", 0.5), ("sweet", 0.4)]),
+    ("O=C/C=C/c1ccccc1", [("cinnamon", 0.95), ("spicy", 0.6), ("sweet", 0.4), ("warm", 0.3)]),
+    ("CC(C)=CCCC(C)(O)C=C", [("floral", 0.85), ("lavender", 0.6), ("citrus", 0.4), ("woody", 0.25)]),
+    ("CCCC(=O)OCC", [("fruity", 0.9), ("pineapple", 0.7), ("sweet", 0.5)]),
+    ("CC(=O)C(C)=O", [("buttery", 0.95), ("creamy", 0.6)]),
+    ("CC(C)=CCC/C(C)=C/CO", [("rose", 0.85), ("floral", 0.7), ("citrus", 0.3)]),
+    ("CCOC(C)=O", [("solvent", 0.6), ("fruity", 0.5), ("sweet", 0.3)]),
+    ("O=Cc1ccco1", [("almond", 0.7), ("bready", 0.6), ("caramel", 0.5), ("sweet", 0.3)]),
+    ("Cc1ccc(C(C)C)cc1O", [("thyme", 0.85), ("herbal", 0.7), ("medicinal", 0.4), ("spicy", 0.3)]),
+    ("COc1ccccc1O", [("smoky", 0.85), ("medicinal", 0.6), ("woody", 0.5), ("spicy", 0.3)]),
+    ("C/C=C/c1ccc(OC)cc1", [("anise", 0.9), ("licorice", 0.7), ("sweet", 0.5)]),
+    ("CC(=O)CCc1ccc(O)cc1", [("raspberry", 0.9), ("jammy", 0.6), ("sweet", 0.5)]),
+]
+
+
+def _aroma_index():
+    out = {}
+    for smi, descs in _AROMA_PREVIEW_RAW:
+        m = Chem.MolFromSmiles(smi)
+        if m is not None:
+            out[Chem.MolToInchiKey(m).split("-")[0]] = descs
+    return out
+
+
+_AROMA_PREVIEW = _aroma_index()
+
+
+@app.post("/api/aroma")
+def api_aroma(q: Query):
+    """ILLUSTRATIVE aroma preview for a few well-known molecules — NOT a live model."""
+    smi = _resolve(q.smiles)
+    mol = Chem.MolFromSmiles(smi) if smi else None
+    if mol is None:
+        return {"available": False}
+    descs = _AROMA_PREVIEW.get(Chem.MolToInchiKey(mol).split("-")[0])
+    if not descs:
+        return {"available": False}
+    return {"available": True, "preview": True,
+            "descriptors": [{"odor": n, "score": s} for n, s in descs]}
+
+
 @app.get("/", response_class=HTMLResponse)
 def home():
     return Path("workbench.html").read_text()

training/workbench.html

@@ -74,6 +74,13 @@
   .aroma-lead b{color:var(--aroma)}
   .aroma-note{font-size:13px;color:var(--muted);margin:0;line-height:1.55;max-width:760px}
   .aroma-note b{color:var(--ink)}
+  .aroma-prev-tag{font-size:11px;font-weight:650;text-transform:uppercase;letter-spacing:.05em;color:var(--aroma);margin:0 0 10px}
+  .ameter{margin:8px 0}
+  .arow{display:flex;justify-content:space-between;align-items:baseline;margin-bottom:4px}
+  .aname{font-weight:600;font-size:13px;text-transform:capitalize}
+  .aval{font-family:var(--mono);font-size:12px;color:var(--muted)}
+  .atrack{height:8px;background:#EDEFEC;border-radius:5px;overflow:hidden}
+  .afill{height:100%;background:var(--aroma);border-radius:5px;transition:width .5s ease}
   .kv{display:grid;grid-template-columns:auto 1fr;gap:6px 16px;margin-bottom:10px}
   .kv .k{font-weight:600;font-size:13px}
   .kv .v{font-family:var(--mono);font-size:13px;color:var(--muted)}
@@ -166,6 +173,7 @@ <h2>Behavior &amp; safety</h2>
 
   <div class="card aroma-card" id="aromaCard" style="display:none">
     <h2>Aroma</h2>
+    <div id="aromaPreview" style="display:none;margin-bottom:14px"></div>
     <div class="aroma-lead">Aroma prediction unlocks with <b>your</b> data.</div>
     <p class="aroma-note">The public demo predicts <b>taste</b> from open data. A useful
     aroma model needs expert-labeled odor data — so we train it <b>on-premise, on your
@@ -217,14 +225,16 @@ <h2>Aroma</h2>
   go.disabled = true; go.textContent = 'Reading…';
   $('err').style.display='none';
   try{
-    const [p, n, s, nm] = await Promise.all([
+    const [p, n, s, nm, ar] = await Promise.all([
       post('/api/predict',{smiles:text}),
       post('/api/neighbors',{smiles:text, k:8}),
       post('/api/structure',{smiles:text}),
-      post('/api/names',{smiles:text})
+      post('/api/names',{smiles:text}),
+      post('/api/aroma',{smiles:text})
     ]);
     if(p.error){ throw new Error(p.error); }
     render(p, n.neighbors||[], (s&&s.svg)||null, nm||{});
+    renderAroma(ar||{});
   }catch(e){
     $('results').style.display='none'; $('behaviorCard').style.display='none'; $('aromaCard').style.display='none'; $('footnote').style.display='none';
     $('err').textContent = e.message; $('err').style.display='block';
@@ -340,6 +350,15 @@ <h2>Aroma</h2>
   $('behavior').innerHTML = html;
 }
 
+function renderAroma(ar){
+  const box=$('aromaPreview');
+  if(ar && ar.available && (ar.descriptors||[]).length){
+    box.innerHTML='<div class="aroma-prev-tag">▸ preview — illustrative of the unlocked read (not a live prediction)</div>'+
+      ar.descriptors.map(d=>{ const pct=Math.round(d.score*100); return `<div class="ameter"><div class="arow"><span class="aname">${d.odor}</span><span class="aval">${pct}%</span></div><div class="atrack"><div class="afill" style="width:${pct}%"></div></div></div>`; }).join('');
+    box.style.display='block';
+  } else { box.style.display='none'; }
+}
+
 function chip(key, on, color, label){
   const style = on && color ? `style="background:${color}"` : '';
   return `<span class="chip ${on?'on':''}" ${style}>${label}</span>`;