diff --git a/bridge/aria_bridge.py b/bridge/aria_bridge.py index a2d816c..95b95de 100644 --- a/bridge/aria_bridge.py +++ b/bridge/aria_bridge.py @@ -3544,12 +3544,17 @@ class ARIABridge: iid = (payload.get("instanceId") or "").strip() if iid: prev = self._workers.get(iid, {}) + _models = payload.get("models") self._workers[iid] = { "instanceId": iid, "service": payload.get("service") or "", "node": payload.get("node") or "", "gpus": payload.get("gpus") or "", "model": payload.get("model") or "", + # models: welche Modelle die Box fahren kann (llm/llama-swap). + # Fallback auf [model] fuer alte Adapter ohne models-Feld. + "models": [m for m in _models if m] if isinstance(_models, list) + else ([payload.get("model")] if payload.get("model") else []), "busy": bool(prev.get("busy", False)), "last_seen": time.time(), } @@ -4006,9 +4011,10 @@ class ARIABridge: req_payload["tools"] = tools if model: req_payload["model"] = model - # Redundanz/Multitasking: freie llm-Instanz gezielt adressieren; None - # → Broadcast wie bisher. Mehrere Instanzen → parallele Turns. - llm_target = self._pick_worker("llm") + # Redundanz/Multitasking: freie llm-Instanz gezielt adressieren, die + # das gewaehlte Modell fahren kann; None → Broadcast wie bisher. + # Mehrere Boxen mit demselben Modell → Round-Robin (pro Projekt verteilt). + llm_target = self._pick_worker("llm", model=model or None) if llm_target: req_payload["targetInstance"] = llm_target logger.info("[rvs] llm_request → llm-adapter (id=%s, msgs=%d, max_tokens=%d, tools=%d, model=%s, target=%s)", @@ -4767,29 +4773,39 @@ class ARIABridge: out.append({ "instanceId": w["instanceId"], "service": w.get("service") or "", "node": w.get("node") or "", "gpus": w.get("gpus") or "", - "model": w.get("model") or "", "busy": bool(w.get("busy")), + "model": w.get("model") or "", "models": w.get("models") or [], + "busy": bool(w.get("busy")), "online": (now - w.get("last_seen", 0)) < self.WORKER_OFFLINE_S, }) return out - def _pick_worker(self, service: str) -> Optional[str]: + def _pick_worker(self, service: str, model: Optional[str] = None) -> Optional[str]: """Waehlt eine online, moeglichst freie Instanz des Diensts (Round-Robin - ueber die freien). Gibt die instanceId oder None (keine online). Fuer - Stage-3-Routing (targetInstance).""" + ueber die freien). Gibt die instanceId oder None. Fuer Stage-3-Routing + (targetInstance). + + model: wenn gesetzt (nur llm sinnvoll), kommen nur Boxen in Frage, die das + Modell fahren koennen (models-Liste oder legacy model-Feld). Meldet KEINE + Box das Modell → None (nachsichtig: Aufrufer faellt auf Broadcast zurueck).""" now = time.time() online = [w for w in self._workers.values() if w.get("service") == service and (now - w.get("last_seen", 0)) < self.WORKER_OFFLINE_S] + if model: + online = [w for w in online + if model in (w.get("models") or []) + or w.get("model") == model] if not online: return None free = [w for w in online if not w.get("busy")] pool = free or online # alle busy → trotzdem eine nehmen (least-bad) - # Round-Robin: rotierender Zeiger pro Dienst. + # Round-Robin: rotierender Zeiger pro Dienst(+Modell). + rr_key = f"{service}:{model}" if model else service rr = getattr(self, "_worker_rr", None) if rr is None: rr = self._worker_rr = {} - idx = rr.get(service, 0) % len(pool) - rr[service] = idx + 1 + idx = rr.get(rr_key, 0) % len(pool) + rr[rr_key] = idx + 1 chosen = pool[idx] chosen["busy"] = True # optimistisch, bis der naechste Ping korrigiert return chosen["instanceId"] diff --git a/diagnostic/index.html b/diagnostic/index.html index 81c374e..61d269c 100644 --- a/diagnostic/index.html +++ b/diagnostic/index.html @@ -602,9 +602,13 @@
Beim ersten Wechsel zu einem Modell lädt die AI-Box das GGUF (mehrere GB) — die erste Antwort dauert dann länger, danach ist es gecacht. - Liste kommt aus /shared/config/local_models.json (Keys = xtts/llama-swap/config.yaml). + Verfügbare Modelle kommen live von den angemeldeten LLM-Boxen; + Namen aus /shared/config/local_models.json.
+ +
+
@@ -2006,7 +2010,7 @@ } if (msg.type === 'sat_update') { satellites = msg.satellites || []; renderSatellites(); return; } - if (msg.type === 'worker_update') { workers = msg.workers || []; renderWorkers(); return; } + if (msg.type === 'worker_update') { workers = msg.workers || []; renderWorkers(); if (typeof refreshLocalLlmModelChoices === 'function') refreshLocalLlmModelChoices(); return; } if (msg.type === 'sat_devices') { if (msg.satellite) { satDevices[msg.satellite] = { devices: msg.devices || [], location: msg.location, ts: Date.now() }; } satScanning = null; @@ -4265,10 +4269,13 @@ const meta = WORKER_SVC_META[w.service] || { icon: '⚙️', label: w.service }; const dot = !w.online ? '#666' : (w.busy ? '#FFB020' : '#3FFF3F'); const stat = !w.online ? 'offline' : (w.busy ? 'beschaeftigt' : 'frei'); + // llm-Boxen koennen mehrere Modelle fahren (llama-swap) → Liste zeigen. + const modelText = (w.service === 'llm' && Array.isArray(w.models) && w.models.length) + ? w.models.join(', ') : (w.model || ''); return '
' + '' + '' + meta.icon + ' ' + escapeHtml(meta.label) + '' + - '' + escapeHtml(w.model || '') + '' + + '' + escapeHtml(modelText) + '' + (w.gpus ? 'GPU ' + escapeHtml(w.gpus) + '' : '') + '' + stat + '' + '
'; @@ -6825,18 +6832,66 @@ el.textContent = m && m.description ? m.description : ''; } async function loadLocalModelList() { + // Kuratierte Namen/Beschreibungen laden; die tatsaechliche Verfuegbarkeit + // kommt live aus der Flotte (refreshLocalLlmModelChoices). try { const r = await fetch('/api/local-models-list'); const j = await r.json(); _localModelsCache = (j && j.models) || []; } catch (e) { _localModelsCache = []; } - const sel = document.getElementById('local-llm-model'); - if (sel) { - sel.innerHTML = _localModelsCache.map(m => - ``).join('') || ''; - if (_localModelsCache.some(m => m.id === _currentLocalModel)) sel.value = _currentLocalModel; - updateLocalModelDesc(); + refreshLocalLlmModelChoices(); + } + // Zaehlt pro Modell die online LLM-Boxen, die es fahren koennen. + function fleetLlmModelCounts() { + const counts = {}; + for (const w of workers) { + if (w.service !== 'llm' || !w.online) continue; + const list = (Array.isArray(w.models) && w.models.length) ? w.models : (w.model ? [w.model] : []); + for (const id of list) counts[id] = (counts[id] || 0) + 1; } + return counts; + } + // Baut das Modell-Dropdown aus der Vereinigung von live-Flotte + kuratierter + // Liste; zeigt pro Modell "· N Box(en)" bzw. "· offline". Auswahl bleibt + // erhalten (auch wenn das gewaehlte Modell gerade keine online Box hat). + function refreshLocalLlmModelChoices() { + const sel = document.getElementById('local-llm-model'); + if (!sel) return; + const counts = fleetLlmModelCounts(); + const nameOf = id => { const m = _localModelsCache.find(x => x.id === id); return (m && m.display_name) || id; }; + const ids = new Set(); + Object.keys(counts).forEach(id => ids.add(id)); + _localModelsCache.forEach(m => ids.add(m.id)); + if (_currentLocalModel) ids.add(_currentLocalModel); + const order = Array.from(ids).sort(); + sel.innerHTML = order.map(id => { + const n = counts[id] || 0; + const avail = n > 0 ? ` · ${n} Box${n > 1 ? 'en' : ''}` : ' · offline'; + return ``; + }).join('') || ''; + if (order.includes(_currentLocalModel)) sel.value = _currentLocalModel; + updateLocalModelDesc(); + renderLocalLlmFleet(); + } + // Kompakte Box-Liste unter dem Dropdown: Node → Modelle → Health. + function renderLocalLlmFleet() { + const box = document.getElementById('local-llm-fleet'); + if (!box) return; + const llm = workers.filter(w => w.service === 'llm'); + if (!llm.length) { box.innerHTML = 'Keine LLM-Box angemeldet. Starte eine Box mit COMPOSE_PROFILES=llm.'; return; } + const byNode = {}; + for (const w of llm) { (byNode[w.node || '?'] = byNode[w.node || '?'] || []).push(w); } + box.innerHTML = '
LLM-Boxen:
' + Object.keys(byNode).sort().map(node => { + return byNode[node].map(w => { + const dot = !w.online ? '#666' : (w.busy ? '#FFB020' : '#3FFF3F'); + const models = (Array.isArray(w.models) && w.models.length) ? w.models.join(', ') : (w.model || '—'); + return '
' + + '' + + '🖥️ ' + escapeHtml(node) + '' + + '' + escapeHtml(models) + '' + + '
'; + }).join(''); + }).join(''); } async function loadLocalLlmConfig() { try { @@ -6849,11 +6904,8 @@ if (ol) ol.checked = !!c.localOnly; if (tv) tv.value = (c.toolVariant === 'full') ? 'full' : 'slim'; _currentLocalModel = c.localLlmModel || 'qwen3-8b'; - const sel = document.getElementById('local-llm-model'); - if (sel && _localModelsCache.some(m => m.id === _currentLocalModel)) { - sel.value = _currentLocalModel; - updateLocalModelDesc(); - } + // Dropdown neu aufbauen (Flotte+kuratiert) und die gespeicherte Auswahl setzen. + refreshLocalLlmModelChoices(); setLocalLlmStatus(c); } catch (e) { /* still */ } } diff --git a/diagnostic/server.js b/diagnostic/server.js index 1ca7722..8e05e3d 100644 --- a/diagnostic/server.js +++ b/diagnostic/server.js @@ -499,7 +499,7 @@ function workerList() { const now = Date.now(); return Array.from(workers.values()).map(w => ({ instanceId: w.instanceId, service: w.service, node: w.node, - gpus: w.gpus, model: w.model, busy: !!w.busy, + gpus: w.gpus, model: w.model, models: w.models || [], busy: !!w.busy, online: (now - (w.last_seen || 0)) < WORKER_OFFLINE_MS, })); } @@ -1019,6 +1019,7 @@ function connectRVS(forcePlain) { workers.set(p.instanceId, { instanceId: p.instanceId, service: p.service || "", node: p.node || "", gpus: p.gpus || "", model: p.model || "", + models: Array.isArray(p.models) ? p.models : (p.model ? [p.model] : []), busy: !!prev.busy, last_seen: Date.now(), }); broadcastWorkers(); @@ -1032,7 +1033,7 @@ function connectRVS(forcePlain) { let w = workers.get(p.instanceId); if (!w) { const svc = String(p.instanceId).split("@")[0]; - w = { instanceId: p.instanceId, service: svc, node: "", gpus: "", model: "", busy: false, last_seen: 0 }; + w = { instanceId: p.instanceId, service: svc, node: "", gpus: "", model: "", models: [], busy: false, last_seen: 0 }; workers.set(p.instanceId, w); } w.busy = !!p.busy; diff --git a/xtts/llm-adapter/adapter.py b/xtts/llm-adapter/adapter.py index a1ec4ee..3728a79 100644 --- a/xtts/llm-adapter/adapter.py +++ b/xtts/llm-adapter/adapter.py @@ -133,14 +133,33 @@ async def _emit_llm_status(ws, state: str, model: str, **extra) -> None: {"service": "llm", "state": state, "model": model, **extra}) +async def _fetch_available_models() -> list: + """Fragt llama-swap ab, welche Modelle diese Box fahren kann (GET /v1/models, + OpenAI-kompatibel → {data:[{id},...]}). Das sind die config.yaml-Keys. + Defensiv: bei Fehler Fallback auf [LLM_MODEL].""" + try: + async with httpx.AsyncClient(timeout=10) as client: + r = await client.get(f"{LLAMA_URL}/v1/models") + r.raise_for_status() + data = r.json() + ids = [m.get("id") for m in (data.get("data") or []) if m.get("id")] + return ids or [LLM_MODEL] + except Exception as e: + logger.warning("llama-swap /v1/models nicht abfragbar (%s) — Fallback [%s]", e, LLM_MODEL) + return [LLM_MODEL] + + async def _worker_register(ws) -> None: """Meldet diesen Worker bei der aria-bridge an (worker_hello) und haelt die Flotten-Registry per periodischem worker_ping (mit busy-Status) frisch.""" try: + models = await _fetch_available_models() await _send(ws, "worker_hello", { "instanceId": INSTANCE_ID, "service": WORKER_SERVICE, "node": NODE_NAME, "gpus": GPU_IDS, "model": LLM_MODEL, + "models": models, # welche Modelle diese Box fahren kann (llama-swap-Keys) }) + logger.info("worker_hello: models=%s", models) while True: await asyncio.sleep(WORKER_PING_INTERVAL_S) await _send(ws, "worker_ping",