diff --git a/README.md b/README.md index d87c144..a10b830 100644 --- a/README.md +++ b/README.md @@ -7,10 +7,16 @@ siehe Architektur-Plan (`docs/` bzw. der genehmigte Plan). Mission Control 2.0 (FastAPI + React/shadcn) · Hermes Agent + hermes-webui · Shared Memory (SQLite via MCP). Jede Schicht hinter stabilem Vertrag austauschbar. -## Status: Phase 0 (Gerüst) +## Status: Phase 1 (Engine + Routing) ✅ -- `backend/` — FastAPI: `GET /api/health`, `GET /api/models` (read-only aus llama-swap config). -- `frontend/` — Vite + React + Tailwind v4 + shadcn-Style, App-Shell mit Cmd+K, Dark-default. +Fortschritt & Resume-Guide: siehe [`docs/STATUS.md`](docs/STATUS.md). + +- **Phase 0** — FastAPI-Skeleton + React/shadcn-Shell (Cmd+K, Dark, PWA). +- **Phase 1** — Compute-Module (fit/caps/sources, portiert), **Discover** (live HF + Fit + Caps), + **Engine-Write** (register + `groups`/Ko-Residenz), **LiteLLM-Gateway** (Config + Service, + `model: auto` + Fallbacks), Frontend **Modelle & Routing** (Caps-Chips, Fit, Discover, Routing-View). + +API: `health · models · discover · fit · models/register · groups · routing` (Details in `docs/STATUS.md`). ## Entwickeln diff --git a/backend/app.py b/backend/app.py index 220621a..97ea59b 100644 --- a/backend/app.py +++ b/backend/app.py @@ -13,7 +13,7 @@ from fastapi.staticfiles import StaticFiles from starlette.requests import Request from config import FRONTEND_DIST, VERSION -from routers import health, models +from routers import health, models, routing app = FastAPI(title="Mission Control 2.0", version=VERSION) @@ -36,6 +36,7 @@ async def no_cache(request: Request, call_next): app.include_router(health.router) app.include_router(models.router) +app.include_router(routing.router) # Prod: gebautes Frontend ausliefern (falls vorhanden). SPA-Fallback auf index.html. diff --git a/backend/config.py b/backend/config.py index 6679038..1f7ce0a 100644 --- a/backend/config.py +++ b/backend/config.py @@ -15,9 +15,26 @@ from ruamel.yaml import YAML LLAMA_SWAP_URL = os.environ.get("MC_LLAMA_SWAP_URL", "http://127.0.0.1:8080").rstrip("/") CONFIG_PATH = Path(os.environ.get("MC_CONFIG_PATH", "/etc/llama-swap/config.yaml")) MODELS_DIR = Path(os.environ.get("MC_MODELS_DIR", "/srv/models")) +# Cache der Modell-Entdeckung ("aktuell beste Modelle", live von HuggingFace). +# Persistent neben den Modellen (übersteht Deploys). TTL = Frische-Fenster. +DISCOVER_CACHE_PATH = Path(os.environ.get("MC_DISCOVER_CACHE", str(MODELS_DIR / "mc2-discover.json"))) +DISCOVER_TTL = int(os.environ.get("MC_DISCOVER_TTL", "43200")) # 12 h +# Befehl-Vorlage für llama-swap: {model}=GGUF-Pfad, {ctx}=Kontext, ${PORT} bleibt stehen. +_DEFAULT_CMD_TEMPLATE = ( + "llama-server -m {model} --host 127.0.0.1 --port ${PORT} " + "-c {ctx} -ngl 999 -fa 1 --no-mmap" +) +CMD_TEMPLATE = os.environ.get("MC_CMD_TEMPLATE", _DEFAULT_CMD_TEMPLATE) +if "{model}" not in CMD_TEMPLATE: + CMD_TEMPLATE = _DEFAULT_CMD_TEMPLATE +DEFAULT_TTL = int(os.environ.get("MC_DEFAULT_TTL", "300")) +# Env für HuggingFace-Downloads: XET deaktivieren (Hänger bei ~6 MB, siehe v1-Gotcha). +HF_DOWNLOAD_ENV = {"HF_HUB_DISABLE_XET": "1"} # --- Routing-Gateway (LiteLLM, model: auto) ---------------------------------- GATEWAY_URL = os.environ.get("MC_GATEWAY_URL", "http://127.0.0.1:4000").rstrip("/") +GATEWAY_CONFIG_PATH = Path(os.environ.get( + "MC_GATEWAY_CONFIG", str(Path(__file__).resolve().parent.parent / "gateway" / "config.yaml"))) # --- Server ------------------------------------------------------------------ HOST = os.environ.get("MC_HOST", "0.0.0.0") @@ -27,7 +44,7 @@ PORT = int(os.environ.get("MC_PORT", "9000")) FRONTEND_DIST = Path(os.environ.get("MC_FRONTEND_DIST", str(Path(__file__).resolve().parent.parent / "frontend" / "dist"))) # Version (Phase 0 — Greenfield-Skeleton). -VERSION = "2.0.0-phase0" +VERSION = "2.0.0-phase1" # Gemeinsame YAML-Instanz (preserve_quotes hält Kommentare/Quotes in config.yaml). yaml = YAML() diff --git a/backend/requirements.txt b/backend/requirements.txt index f67f08e..dbc1314 100644 --- a/backend/requirements.txt +++ b/backend/requirements.txt @@ -2,3 +2,4 @@ fastapi>=0.115 uvicorn[standard]>=0.30 httpx>=0.27 ruamel.yaml>=0.18 +psutil>=5.9 diff --git a/backend/routers/health.py b/backend/routers/health.py index 3af5376..5fa3043 100644 --- a/backend/routers/health.py +++ b/backend/routers/health.py @@ -3,7 +3,7 @@ from fastapi import APIRouter from config import VERSION -from services import llamaswap +from services import gateway, llamaswap router = APIRouter(prefix="/api") @@ -14,4 +14,5 @@ def health() -> dict: "status": "ok", "version": VERSION, "engine_reachable": llamaswap.engine_reachable(), + "gateway_reachable": gateway.gateway_reachable(), } diff --git a/backend/routers/models.py b/backend/routers/models.py index 896e555..66ce527 100644 --- a/backend/routers/models.py +++ b/backend/routers/models.py @@ -1,13 +1,81 @@ -"""Modelle-Endpoint (Phase 0: read-only Liste aus der llama-swap config.yaml).""" +"""Modelle-Endpoints: Liste (mit Caps), Discover, Fit, Register, Groups.""" -from fastapi import APIRouter +import psutil +from fastapi import APIRouter, HTTPException +from pydantic import BaseModel -from services import llamaswap +from services import discover, llamaswap +from services.fit import evaluate_fit, max_ctx_for router = APIRouter(prefix="/api") +def _ram_gb() -> float: + return psutil.virtual_memory().total / (1024 ** 3) + + @router.get("/models") def models() -> dict: items = llamaswap.list_models() return {"models": items, "count": len(items)} + + +@router.get("/discover") +def discover_models(force: bool = False) -> dict: + ram = _ram_gb() + data = discover.refresh_discover(ram) if force else discover.safe_discover(ram) + if not data: + raise HTTPException(502, "Modell-Quellen gerade nicht erreichbar — später erneut.") + return {**data, "sys_ram_gb": round(ram, 1)} + + +@router.get("/fit") +def fit(params_b: float, quant: str = "Q4_K_M", ctx: int = 8192, name: str = "") -> dict: + ram = _ram_gb() + return { + "fit": evaluate_fit(params_b, quant, ctx, ram, name=name), + "optimal_ctx": max_ctx_for(params_b, quant, ram), + "sys_ram_gb": round(ram, 1), + } + + +class RegisterReq(BaseModel): + model_path: str + role: str | None = None + ctx: int = 8192 + ttl: int | None = None + mmproj_path: str | None = None + jinja: bool = False + + +@router.post("/models/register") +def register(req: RegisterReq) -> dict: + try: + model_id = llamaswap.register_model( + req.model_path, role=req.role, ctx=req.ctx, ttl=req.ttl, + mmproj_path=req.mmproj_path, jinja=req.jinja, + ) + except PermissionError as exc: + raise HTTPException(500, str(exc)) + return {"ok": True, "model_id": model_id} + + +@router.get("/groups") +def groups() -> dict: + return {"groups": llamaswap.list_groups()} + + +class GroupReq(BaseModel): + group: str + members: list[str] + swap: bool = False + persist: bool = False + + +@router.put("/groups") +def set_group(req: GroupReq) -> dict: + try: + llamaswap.set_group(req.group, req.members, swap=req.swap, persist=req.persist) + except PermissionError as exc: + raise HTTPException(500, str(exc)) + return {"ok": True} diff --git a/backend/routers/routing.py b/backend/routers/routing.py new file mode 100644 index 0000000..b7defe7 --- /dev/null +++ b/backend/routers/routing.py @@ -0,0 +1,28 @@ +"""Routing-Endpoints: Gateway-Übersicht (welcher Alias = fast/heavy/…) + Mapping setzen.""" + +from fastapi import APIRouter, HTTPException +from pydantic import BaseModel + +from services import gateway + +router = APIRouter(prefix="/api") + + +@router.get("/routing") +def routing() -> dict: + return {**gateway.routing_summary(), "gateway_reachable": gateway.gateway_reachable()} + + +class RouteReq(BaseModel): + name: str # Gateway-Modellname, z.B. "fast" / "heavy" / "vision" / "coder" + target_alias: str # llama-swap-Alias, der bedient wird + api_base: str = "http://127.0.0.1:8080/v1" + + +@router.put("/routing/route") +def set_route(req: RouteReq) -> dict: + try: + gateway.set_route(req.name, req.target_alias, api_base=req.api_base) + except Exception as exc: # noqa: BLE001 + raise HTTPException(500, str(exc)) + return {"ok": True} diff --git a/backend/services/caps.py b/backend/services/caps.py new file mode 100644 index 0000000..9064bd0 --- /dev/null +++ b/backend/services/caps.py @@ -0,0 +1,131 @@ +""" +Modell-Capabilities — EINE Quelle der Wahrheit für Modell-Eigenschaften +(MoE / Tools / Vision / Coder / Reasoning / Embedding / Kontext). +Portiert aus Mission Control v1 (model_caps.py). + +Quellen, geschichtet: GGUF-Header (offline, authoritativ) → cmd-Flags +(--jinja/--mmproj) → HF-Block (tags + chat_template) → Familien-Fallback. +Tool-Fähigkeit dreistufig: yes (bestätigt) | likely (Familie) | no. +""" + +import re +import struct + +from services.fit import extract_active_params_b, extract_params_b + +_GGUF_FIXED = {0: 1, 1: 1, 2: 2, 3: 2, 4: 4, 5: 4, 6: 4, 7: 1, 10: 8, 11: 8, 12: 8} + + +def _read_gguf_meta(path: str) -> dict: + """Liest nur den GGUF-Metadaten-Header (architecture/context_length/expert_count/ + parameter_count). Bricht vor dem Tokenizer-Array ab → schnell, lädt NICHT das Modell.""" + out: dict = {} + try: + with open(path, "rb") as f: + if f.read(4) != b"GGUF": + return {} + struct.unpack(" int: return struct.unpack(" int: return struct.unpack(" str: return f.read(ru64()).decode("utf-8", "replace") + + def rval(t: int): + if t == 8: return rstr() + if t == 0: return struct.unpack(" dict: + """Capability-Tag-Set für ein Modell. Alle Quellen optional — nutzt, was da ist.""" + low = (name or "").lower() + cmdl = (cmd or "").lower() + hf = hf or {} + + meta = _read_gguf_meta(gguf_path) if gguf_path else {} + arch = str(meta.get("architecture") or hf.get("architecture") or "").lower() + tags = [str(t).lower() for t in (hf.get("tags") or [])] + chat_tpl = str(hf.get("chat_template") or "") + + expert_count = int(meta.get("expert_count") or 0) + moe = ( + expert_count > 1 + or any(a in arch for a in _MOE_ARCH) + or bool(re.search(r"\d+x\d+\.?\d*b", low)) + or bool(re.search(r"a\d+\.?\d*b", low)) + ) + active_b = extract_active_params_b(name) + + pcount = int(meta.get("parameter_count") or 0) + params_b = round(pcount / 1e9, 1) if pcount else extract_params_b(name) + ctx = meta.get("context_length") + if not ctx: + m = re.search(r"-(?:c|-ctx-size)\s+(\d+)", cmdl) + ctx = int(m.group(1)) if m else None + + tool_confirmed = "--jinja" in cmdl or "tool_call" in chat_tpl or "" in chat_tpl + tool_family = any(fam in low for fam in _TOOL_FAMILIES) or "function-calling" in tags + tools = "yes" if tool_confirmed else ("likely" if tool_family else "no") + + vision = "--mmproj" in cmdl or "vl" in arch or "clip" in arch or any(k in low for k in _VISION_KW) + coder = any(k in low for k in _CODE_KW) + reasoning = any(k in low for k in _REASON_KW) or "reasoning" in tags + embedding = "bert" in arch or any(k in low for k in _EMBED_KW) + + return { + "moe": moe, "active_b": active_b, "tools": tools, "vision": vision, + "coder": coder, "reasoning": reasoning, "embedding": embedding, + "ctx": ctx, "params_b": params_b or None, "arch": arch or None, + } diff --git a/backend/services/discover.py b/backend/services/discover.py new file mode 100644 index 0000000..4d10921 --- /dev/null +++ b/backend/services/discover.py @@ -0,0 +1,133 @@ +""" +Automatische Modell-Entdeckung ("aktuell beste Modelle"): fragt vertrauenswürdige +HF-Orgs live ab, kategorisiert per Stichwort, rankt nach Hardware-Fit + Beliebtheit +und cached. Portiert aus Mission Control v1 (cookbook.py-Discover). + +Wichtig (Greenfield-Fix gegen v1): EIN gemeinsamer Ranking-Helfer `rank_runnable` +ist die Quelle der Wahrheit — sowohl die „beste Empfehlung" je Kategorie als auch +spätere Auto-Setups nutzen ihn, damit sie nie auseinanderlaufen. +""" + +import json +import os +import time + +import httpx + +from config import DISCOVER_CACHE_PATH, DISCOVER_TTL +from services.caps import capabilities +from services.fit import evaluate_fit, extract_params_b, max_ctx_for +from services.sources import CATEGORIES, SKIP_TOKENS, TRUSTED_AUTHORS + +_FIT_ORDER = {"perfect": 0, "marginal": 1, "too_tight": 2} + + +def _categorize(repo_id: str) -> str: + low = repo_id.lower() + for cat in CATEGORIES: + if any(k in low for k in cat["kw"]): + return cat["role"] + return "scout" + + +def _fetch_author_models(author: str) -> list: + url = (f"https://huggingface.co/api/models?author={author}" + f"&filter=gguf&sort=downloads&direction=-1&limit=40") + try: + with httpx.Client(timeout=12.0) as c: + data = c.get(url).json() + return data if isinstance(data, list) else [] + except Exception: + return [] + + +def rank_runnable(models: list[dict]) -> list[dict]: + """EINE Quelle der Wahrheit fürs Ranking lauffähiger Modelle: + bestes Fit-Level zuerst (perfect < marginal), bei Gleichstand meistgeladen. + Zu große Modelle (too_tight) fliegen raus.""" + return sorted( + [m for m in models if m["fit"]["level"] != "too_tight"], + key=lambda m: (_FIT_ORDER[m["fit"]["level"]], -int(m.get("downloads") or 0)), + ) + + +def refresh_discover(ram_gb: float) -> dict: + """Quellen live abfragen, kategorisieren, ranken, cachen. Wirft nur, wenn KEINE + Quelle erreichbar war.""" + raw, seen, ok = [], set(), 0 + for author in TRUSTED_AUTHORS: + models = _fetch_author_models(author) + if models: + ok += 1 + for m in models: + rid = m.get("id") + if not rid or rid in seen: + continue + seen.add(rid) + raw.append(m) + if ok == 0: + raise RuntimeError("Keine Quelle erreichbar.") + + by_cat: dict[str, list] = {c["role"]: [] for c in CATEGORIES} + for m in raw: + rid = m["id"] + low = rid.lower() + if any(tok in low for tok in SKIP_TOKENS): + continue + role = _categorize(rid) + params_b = extract_params_b(rid) + quant = "Q4_K_M" # Referenz-Quant für die Fit-Einschätzung + fit = evaluate_fit(params_b, quant, 8192, ram_gb, name=rid) + tags = [str(t) for t in (m.get("tags") or [])] + by_cat[role].append({ + "name": rid.split("/")[-1], "author": rid.split("/")[0], "repo": rid, + "role": role, "params_b": params_b, "quant": quant, "tags": tags, + "downloads": int(m.get("downloads") or 0), "likes": int(m.get("likes") or 0), + "lastModified": m.get("lastModified"), + "fit": fit, "optimal_ctx": max_ctx_for(params_b, quant, ram_gb), + "caps": capabilities(name=rid, hf={"tags": tags}), + }) + + cats = [] + for c in CATEGORIES: + items = by_cat[c["role"]] + ranked = rank_runnable(items) + # Top 4 je Kategorie (für die Anzeige) — gerankt, dann nach Downloads aufgefüllt. + items.sort(key=lambda x: (x["fit"]["level"] != "too_tight", x["downloads"]), reverse=True) + top = items[:4] + if top: + cats.append({ + "role": c["role"], "title": c["title"], "icon": c["icon"], + "models": top, + "recommended": ranked[0]["repo"] if ranked else None, + }) + + data = {"updated": time.time(), "categories": cats} + try: + DISCOVER_CACHE_PATH.parent.mkdir(parents=True, exist_ok=True) + tmp = DISCOVER_CACHE_PATH.with_name(DISCOVER_CACHE_PATH.name + ".tmp") + tmp.write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") + os.replace(tmp, DISCOVER_CACHE_PATH) + except Exception: + pass # Cache ist nur Beschleunigung + return data + + +def load_discover() -> dict | None: + try: + if DISCOVER_CACHE_PATH.exists(): + return json.loads(DISCOVER_CACHE_PATH.read_text(encoding="utf-8")) + except Exception: + pass + return None + + +def safe_discover(ram_gb: float) -> dict | None: + """Aus Cache (wenn frisch) oder live; wirft nie — None wenn nichts da.""" + cached = load_discover() + if cached and (time.time() - cached.get("updated", 0) < DISCOVER_TTL): + return cached + try: + return refresh_discover(ram_gb) + except Exception: + return cached diff --git a/backend/services/fit.py b/backend/services/fit.py new file mode 100644 index 0000000..e508b06 --- /dev/null +++ b/backend/services/fit.py @@ -0,0 +1,92 @@ +""" +Hardware-Fit-Mathe (VRAM/RAM, tps-Schätzung) für APUs mit Unified Memory +(Bosgame M5 / Strix Halo). Portiert aus Mission Control v1 (hw_math.py). +""" + +import re + +# Bytes pro Parameter je GGUF-Quant (Annahme). +QUANT_BYTES_PER_PARAM = { + "Q2_K": 0.35, "Q3_K_S": 0.38, "Q3_K_M": 0.42, "Q3_K_L": 0.45, + "Q4_0": 0.50, "Q4_1": 0.55, "Q4_K_S": 0.50, "Q4_K_M": 0.55, + "Q5_0": 0.62, "Q5_1": 0.68, "Q5_K_S": 0.62, "Q5_K_M": 0.65, + "Q6_K": 0.75, "Q8_0": 1.00, "F16": 2.00, "BF16": 2.00, +} + + +def estimate_memory_gb(params_b: float, quant: str, ctx: int) -> float: + """Geschätzter Speicherbedarf in GB (Gewichte + Kontext-KV).""" + bpp = QUANT_BYTES_PER_PARAM.get(quant.upper(), 0.65) + weights = params_b * bpp + context_vram = (ctx / 8192) * (max(params_b, 7) / 7) * 0.8 + return weights + context_vram + + +def extract_active_params_b(name: str) -> float | None: + """Aktive Parameter bei MoE ('30B-A3B' → 3.0). None bei Dense.""" + m = re.search(r"(? float: + """Geschätzte t/s anhand der ~273 GB/s Bandbreite der APU. + moe_active_ratio = aktive/gesamt Params; < 1 bei MoE.""" + bw = 273 if sys_ram_gb > 8 else 70 + if req_gb <= 0: + return 0.0 + raw_tps = (bw / req_gb) * 0.55 + if moe_active_ratio < 0.8: + raw_tps *= (1.0 / moe_active_ratio) ** 0.5 + return raw_tps + + +def evaluate_fit(params_b: float, quant: str, ctx: int, sys_ram_gb: float, name: str = "") -> dict: + """Fit für ein Shared-Memory-System (APU). name → MoE-Erkennung (optional).""" + req_gb = estimate_memory_gb(params_b, quant, ctx) + active_b = extract_active_params_b(name) if name else None + moe_ratio = (active_b / params_b) if (active_b and params_b > 0) else 1.0 + tps = estimate_speed(req_gb, sys_ram_gb, moe_ratio) + usable_ram = max(sys_ram_gb - 4.0, 0) + if req_gb > usable_ram: + fit_level, text = "too_tight", "Zu groß (OOM)" + elif req_gb > usable_ram * 0.8: + fit_level, text = "marginal", "Könnte knapp werden" + else: + fit_level, text = "perfect", "Passt perfekt" + return {"level": fit_level, "text": text, "req_gb": round(req_gb, 1), "tps": round(tps, 0)} + + +def extract_params_b(name: str) -> float: + """Parametergröße (Mrd.) aus Repo-/Dateiname. 8x7B (MoE) → 56.""" + moe = re.search(r"(\d+)x(\d+(?:\.\d+)?)[bB]", name) + if moe: + return float(moe.group(1)) * float(moe.group(2)) + m = re.search(r"(\d+(?:\.\d+)?)[bB](?![a-zA-Z])", name) + return float(m.group(1)) if m else 7.0 + + +_NICE_CTX = [2048, 4096, 8192, 16384, 32768, 49152, 65536, 98304, 131072] + + +def max_ctx_for(params_b: float, quant: str, sys_ram_gb: float) -> int: + """Größter 'schöner' Kontext, der komfortabel passt (80 % des nutzbaren RAM).""" + bpp = QUANT_BYTES_PER_PARAM.get(quant.upper(), 0.65) + weights = params_b * bpp + usable = max(sys_ram_gb - 4.0, 0) * 0.8 + ctx_budget = usable - weights + if ctx_budget <= 0: + return 2048 + per_8k = (max(params_b, 7) / 7) * 0.8 + raw_ctx = (ctx_budget / per_8k) * 8192 + best = _NICE_CTX[0] + for c in _NICE_CTX: + if c <= raw_ctx: + best = c + return best + + +def recommend_ctx(params_b: float, quant: str, sys_ram_gb: float) -> dict: + ctx = max_ctx_for(params_b, quant, sys_ram_gb) + k = ctx // 1024 + return {"ctx": ctx, "k": k, + "note": f"Bis ~{k}k Kontext passt komfortabel auf deine Hardware ({round(sys_ram_gb)} GB)."} diff --git a/backend/services/gateway.py b/backend/services/gateway.py new file mode 100644 index 0000000..dae9627 --- /dev/null +++ b/backend/services/gateway.py @@ -0,0 +1,69 @@ +""" +Routing-Gateway-Service: liest/schreibt die LiteLLM-Config und prüft die +Erreichbarkeit. MC verwaltet damit die Modell-Zuordnung (welcher llama-swap-Alias +ist fast/heavy/vision/coder) und die Routing-Regeln. +""" + +import httpx + +from config import GATEWAY_CONFIG_PATH, GATEWAY_URL, yaml + + +def read_gateway_config() -> dict: + if not GATEWAY_CONFIG_PATH.exists(): + return {"model_list": [], "litellm_settings": {}, "router_settings": {}} + with GATEWAY_CONFIG_PATH.open("r", encoding="utf-8") as f: + return yaml.load(f) or {} + + +def write_gateway_config(cfg: dict) -> None: + import os + GATEWAY_CONFIG_PATH.parent.mkdir(parents=True, exist_ok=True) + tmp = GATEWAY_CONFIG_PATH.with_name(GATEWAY_CONFIG_PATH.name + ".tmp") + with tmp.open("w", encoding="utf-8") as f: + yaml.dump(cfg, f) + os.replace(tmp, GATEWAY_CONFIG_PATH) + + +def routing_summary() -> dict: + """Kompakte Sicht für die UI: welcher Backend-Alias steckt hinter welchem + Gateway-Modellnamen + die Fallback-Ketten.""" + cfg = read_gateway_config() + routes = [] + for entry in cfg.get("model_list") or []: + params = entry.get("litellm_params") or {} + routes.append({ + "name": entry.get("model_name"), + "target": str(params.get("model", "")), + "api_base": params.get("api_base"), + }) + settings = cfg.get("litellm_settings") or {} + return { + "routes": routes, + "fallbacks": settings.get("fallbacks") or [], + "context_window_fallbacks": settings.get("context_window_fallbacks") or [], + } + + +def set_route(name: str, target_alias: str, api_base: str = "http://127.0.0.1:8080/v1") -> None: + """Einen Gateway-Modellnamen (z.B. 'fast') auf einen llama-swap-Alias mappen.""" + cfg = read_gateway_config() + ml = cfg.setdefault("model_list", []) + params = {"model": f"openai/{target_alias}", "api_base": api_base, "api_key": "sk-noauth"} + for entry in ml: + if entry.get("model_name") == name: + entry["litellm_params"] = params + break + else: + ml.append({"model_name": name, "litellm_params": params}) + write_gateway_config(cfg) + + +def gateway_reachable() -> bool: + try: + with httpx.Client(timeout=3.0) as c: + # LiteLLM hat /health/liveliness; /v1/models tut's auch. + r = c.get(f"{GATEWAY_URL}/v1/models") + return r.status_code in (200, 401) + except Exception: + return False diff --git a/backend/services/llamaswap.py b/backend/services/llamaswap.py index 1dbb5d7..3888aec 100644 --- a/backend/services/llamaswap.py +++ b/backend/services/llamaswap.py @@ -1,21 +1,20 @@ """ -Engine-Service: liest die llama-swap config.yaml (read-only in Phase 0) und -spricht die llama-swap-API (/v1/models, /running). Schreiblogik (Modelle -installieren, Gruppen/Routing verwalten) kommt in Phase 1. +Engine-Service: liest/schreibt die llama-swap config.yaml und spricht die +llama-swap-API. Portiert & erweitert aus Mission Control v1. -Logik portiert aus Mission Control v1 (llamaswap.py + routers/models.py), -auf das Nötigste reduziert. +NEU in 2.0: `groups` für Ko-Residenz (schnell + schwer gleichzeitig geladen, +`swap:false`) → Multi-Model-Delegation ohne Nachlade-Latenz. """ import os import re import httpx +from ruamel.yaml.scalarstring import LiteralScalarString -from config import CONFIG_PATH, LLAMA_SWAP_URL, yaml +from config import CMD_TEMPLATE, CONFIG_PATH, DEFAULT_TTL, LLAMA_SWAP_URL, yaml # Kanonische Rollen (vereinheitlicht ggü. v1: kein manager/reviewer mehr). -# Eine Quelle der Wahrheit — Capability-Erkennung läuft separat über model_caps (Phase 1). ROLE_IDS = {"vision", "coder", "reasoning", "agent", "scout"} _CTX_RE = re.compile(r"-(?:c|-ctx-size)\s+(\d+)") @@ -23,9 +22,8 @@ _PATH_RE = re.compile(r"-(?:m|-model)\s+([^\s]+)") _QUANT_RE = re.compile(r"(Q\d_[A-Z0-9_]+|IQ\d_[A-Z0-9_]+|fp16|bf16)\.gguf", re.IGNORECASE) +# --- Lesen ------------------------------------------------------------------- def read_config() -> dict: - """llama-swap config.yaml laden. Existiert sie nicht (z.B. lokaler Dev-PC - ohne Engine), wird ein leeres Modell-Set zurückgegeben statt zu werfen.""" if not CONFIG_PATH.exists(): return {"models": {}} with CONFIG_PATH.open("r", encoding="utf-8") as f: @@ -36,17 +34,11 @@ def read_config() -> dict: def _parse_model(name: str, spec: dict) -> dict: - """Ein config.yaml-Modell in ein flaches UI-Objekt übersetzen.""" spec = spec or {} cmd = str(spec.get("cmd", "")).strip() + ctx = int(m.group(1)) if (m := _CTX_RE.search(cmd)) else None - ctx = None - if (m := _CTX_RE.search(cmd)): - ctx = int(m.group(1)) - - path = "" - filename = "" - quant = "" + path = filename = quant = "" size_bytes = None if (m := _PATH_RE.search(cmd)): path = m.group(1).replace("'", "").replace('"', "") @@ -60,9 +52,9 @@ def _parse_model(name: str, spec: dict) -> dict: if isinstance(aliases, str): aliases = [aliases] aliases = [str(a) for a in aliases] - # Rolle = erster Alias; Legacy-Fallback: Key selbst ist eine Rolle. role = aliases[0].lower() if aliases else (name.lower() if name.lower() in ROLE_IDS else None) + from services.caps import capabilities return { "name": name, "role": role, @@ -71,24 +63,122 @@ def _parse_model(name: str, spec: dict) -> dict: "ctx": ctx, "ttl": spec.get("ttl"), "cmd": cmd, + "gguf_path": path, "filename": filename, "quant": quant, "size_bytes": size_bytes, - # "incomplete" = Eintrag ohne hinterlegtes Modell (-m), z.B. Platzhalter. "incomplete": not path, + "capabilities": capabilities( + name=filename or name, cmd=cmd, + gguf_path=(path if (path and os.path.exists(path)) else ""), + ), } def list_models() -> list[dict]: - """Alle in der config.yaml konfigurierten Modelle (read-only).""" cfg = read_config() return [_parse_model(name, spec) for name, spec in (cfg.get("models") or {}).items()] def engine_reachable() -> bool: - """Ist die llama-swap-API erreichbar?""" try: with httpx.Client(timeout=3.0) as c: return c.get(f"{LLAMA_SWAP_URL}/v1/models").status_code == 200 except Exception: return False + + +# --- Schreiben --------------------------------------------------------------- +def model_id_from_path(model_path: str) -> str: + """Sprechende Modell-ID (= API-Name) aus dem GGUF-Pfad: Repo-Ordnername ohne + '-GGUF'. Fallback: Dateiname ohne Quant-Suffix.""" + d = os.path.basename(os.path.dirname(model_path)) + name = re.sub(r"[-_]?GGUF$", "", d, flags=re.I).strip("-_") + if not name: + fn = re.sub(r"\.gguf$", "", os.path.basename(model_path), flags=re.I) + fn = re.sub(r"-\d+-of-\d+$", "", fn) + name = re.sub(r"[-_](Q\d[\w]*|IQ\d[\w]*|F16|BF16|FP16|F32)$", "", fn, flags=re.I) + return name or "modell" + + +def set_role_alias(cfg: dict, model_id: str, role: str | None) -> None: + """Rolle als eindeutigen llama-swap-`aliases`-Eintrag setzen (vorher bei allen + anderen Modellen entfernen). role=None/leer entfernt den Alias.""" + models = cfg.get("models") or {} + role = (role or "").strip().lower() + if role: + for mid, spec in models.items(): + if mid == model_id or not isinstance(spec, dict): + continue + al = [a for a in (spec.get("aliases") or []) if str(a).lower() != role] + if al: + spec["aliases"] = al + else: + spec.pop("aliases", None) + spec = models.get(model_id) + if isinstance(spec, dict): + if role and role != model_id.lower(): + spec["aliases"] = [role] + else: + spec.pop("aliases", None) + + +def _augment_vision(cmd: str, model_path: str, mmproj_path: str | None) -> str: + """Vision-Modelle brauchen --mmproj und --jinja.""" + if mmproj_path: + if "--mmproj" not in cmd: + cmd += f" --mmproj {mmproj_path}" + if "--jinja" not in cmd: + cmd += " --jinja" + return cmd + + +def write_config(cfg: dict) -> None: + """Atomar schreiben (tmp + os.replace), damit llama-swap mit -watch-config nie + eine halbe Datei sieht. Fehlende Schreibrechte → klare Meldung.""" + try: + CONFIG_PATH.parent.mkdir(parents=True, exist_ok=True) + tmp = CONFIG_PATH.with_name(CONFIG_PATH.name + ".tmp") + with tmp.open("w", encoding="utf-8") as f: + yaml.dump(cfg, f) + os.replace(tmp, CONFIG_PATH) + except PermissionError as exc: + raise PermissionError( + f"Mission Control darf '{CONFIG_PATH}' nicht schreiben. " + f"Einmalig: sudo chown -R hitonabi:hitonabi {CONFIG_PATH.parent}" + ) from exc + + +def register_model(model_path: str, role: str | None = None, ctx: int = 8192, + ttl: int | None = None, mmproj_path: str | None = None, + jinja: bool = False) -> str: + """Ein GGUF als llama-swap-Modell eintragen (cmd + Rolle-Alias). Gibt die + Modell-ID zurück. jinja=True erzwingt --jinja (Tool-Calling, z.B. fürs Agent-Hirn).""" + cfg = read_config() + model_id = model_id_from_path(model_path) + cmd = CMD_TEMPLATE.replace("{model}", model_path).replace("{ctx}", str(ctx)) + cmd = _augment_vision(cmd, model_path, mmproj_path) + if jinja and "--jinja" not in cmd: + cmd += " --jinja" + cfg.setdefault("models", {})[model_id] = { + "cmd": LiteralScalarString(cmd + "\n"), + "ttl": ttl if ttl is not None else DEFAULT_TTL, + } + set_role_alias(cfg, model_id, role) + write_config(cfg) + return model_id + + +# --- Groups (Ko-Residenz) ---------------------------------------------------- +def set_group(group: str, members: list[str], swap: bool = False, persist: bool = False) -> None: + """llama-swap-`groups`-Eintrag setzen. swap=False → alle Mitglieder dürfen + GLEICHZEITIG laufen (Ko-Residenz, keine Nachlade-Latenz). persist=True → + Mitglieder werden nie automatisch entladen.""" + cfg = read_config() + groups = cfg.setdefault("groups", {}) + groups[group] = {"swap": swap, "persist": persist, "members": list(members)} + write_config(cfg) + + +def list_groups() -> dict: + return read_config().get("groups") or {} diff --git a/backend/services/sources.py b/backend/services/sources.py new file mode 100644 index 0000000..5c2274c --- /dev/null +++ b/backend/services/sources.py @@ -0,0 +1,27 @@ +""" +Vertrauenswürdige Quellen + Kategorien für die automatische Modell-Entdeckung. +Portiert aus Mission Control v1 (sources.py). Rollen sind die EINE Quelle der +Wahrheit (vereinheitlicht): vision · coder · reasoning · agent · scout. +""" + +# HF-Orgs, die zuverlässig aktuelle, hochwertige GGUF-Quants veröffentlichen. +TRUSTED_AUTHORS = ["unsloth", "bartowski", "ggml-org", "lmstudio-community"] + +# Kategorien (Reihenfolge = Anzeige + Zuordnungs-Priorität). Ein Modell wird der +# ERSTEN Kategorie zugeordnet, deren Stichwort im Repo-Namen vorkommt; sonst „scout". +# Die `role` ist zugleich der Alias-Vorschlag und gehört zu ROLE_IDS. +CATEGORIES = [ + {"role": "vision", "title": "Bilder verstehen", "icon": "eye", + "kw": ["-vl-", "-vl", "vision", "llava", "multimodal", "-mm-", "pixtral"]}, + {"role": "coder", "title": "Coden & Programmieren", "icon": "code", + "kw": ["coder", "-code-", "code-", "codestral", "starcoder"]}, + {"role": "reasoning", "title": "Nachdenken & Logik", "icon": "pulse", + "kw": ["-r1", "deepseek-r1", "reasoning", "qwq", "magistral", "-think", "thinking", "-o1"]}, + {"role": "agent", "title": "Agenten & Tool-Use", "icon": "layers", + "kw": ["hermes", "-tool", "command-r", "watt", "-fc-", "function"]}, + {"role": "scout", "title": "Allrounder & Chat", "icon": "compass", + "kw": []}, # Fallback: instruct/chat-Modelle +] + +# Repo-Namensteile, die bei der Entdeckung übersprungen werden (Roh-/Spezialformate). +SKIP_TOKENS = ["-base", "-bnb-", "-gptq", "-awq", "-fp8", "draft", "tokenizer"] diff --git a/docs/STATUS.md b/docs/STATUS.md new file mode 100644 index 0000000..efcc839 --- /dev/null +++ b/docs/STATUS.md @@ -0,0 +1,46 @@ +# Mission Control 2.0 — Status & Resume-Guide + +> So machst du jederzeit nahtlos weiter. Der vollständige Architektur-Plan liegt in +> `C:\Users\TobisPC\.claude\plans\piped-cuddling-sloth.md` (genehmigt). + +## Wo das Projekt lebt +- **Code:** `F:\Coding Stuff\mission-control-2` (Windows-Dev-PC) + Gitea-Remote + `https://git.tobisniceshomelab.ddnsfree.com/Hitonabi/mission-control-v2` (Branch `main`). +- **v1** (`F:\Coding Stuff\mission-control`) bleibt unangetastet bis zum Cutover. +- **Box** (Bosgame, `192.168.178.151`): noch **nicht** deployt (Phase 0 step 5 offen). + +## Phasen-Fortschritt +- [x] **Phase 0 — Gerüst:** FastAPI (`/api/health`,`/api/models`) + React/shadcn-Shell (Cmd+K, Dark, PWA). Verifiziert. +- [x] **Phase 1 — Engine + Routing:** Compute-Module (fit/caps/sources), Discover (live HF), Engine-Write + (register + groups/Ko-Residenz), LiteLLM-Gateway-Config + Service, Frontend Modelle&Routing + (Caps-Chips, Fit, Discover-Tab, Routing-View). Lokal verifiziert (Backend-Smoke + Frontend-Build + Browser). +- [ ] **Phase 2 — System/OS + Connect** (Metriken, Dienste, Update/Self-Update, Connect-Snippets). +- [ ] **Phase 3 — Memory + MCP** (Governance-UI, mcp_memory.py portiert, mcp_mc.py neu). +- [ ] **Phase 4 — Hermes-Schicht** (hermes-webui Dienst, Brain=auto, Tools/MCP verdrahten). **Braucht Box.** +- [ ] **Phase 5 — Betrieb/Observability/Politur** (Backup, LiteLLM-Traces, Health). +- [ ] **Phase 6 — Cutover** (/opt → v2, v1 aus). **Braucht Box.** +- Offen aus Phase 0/1: **Box-Deploy** (Gitea-Repo da; Box-Setup als systemd-USER-Dienst noch offen), + LiteLLM **Complexity-Auto-Router** gegen installierte Version verifizieren. + +## Lokal entwickeln/verifizieren +```bash +# Backend +cd backend && .venv/Scripts/python -m uvicorn app:app --port 9000 +# Frontend (Dev) +cd frontend && npm run dev # http://localhost:5173 (proxyt /api → :9000) +# Frontend (Build → wird vom Backend ausgeliefert, committet) +cd frontend && npm run build +``` + +## API (Stand Phase 1) +- `GET /api/health` — Status + engine/gateway reachable +- `GET /api/models` — installierte Modelle inkl. `capabilities` +- `GET /api/discover[?force=1]` — beste Modelle je Kategorie (live HF, Fit, Caps, ⭐recommended) +- `GET /api/fit?params_b=&quant=&ctx=&name=` — Hardware-Fit-Schätzung +- `POST /api/models/register` — GGUF als llama-swap-Modell eintragen (cmd + Rolle-Alias, optional jinja) +- `GET/PUT /api/groups` — llama-swap-`groups` (Ko-Residenz `swap:false`) +- `GET /api/routing`, `PUT /api/routing/route` — LiteLLM-Gateway-Mapping + +## Nächster sinnvoller Schritt +Phase 2 (System/OS + Connect) lokal bauen — **oder** Box-Deploy einrichten (systemd-USER-Dienst, +sudo-frei). 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var(--tw-invert,) var(--tw-saturate,) var(--tw-sepia,) var(--tw-drop-shadow,)}.grayscale{--tw-grayscale:grayscale(100%);filter:var(--tw-blur,) var(--tw-brightness,) var(--tw-contrast,) var(--tw-grayscale,) var(--tw-hue-rotate,) var(--tw-invert,) var(--tw-saturate,) var(--tw-sepia,) var(--tw-drop-shadow,)}.invert{--tw-invert:invert(100%);filter:var(--tw-blur,) var(--tw-brightness,) var(--tw-contrast,) var(--tw-grayscale,) var(--tw-hue-rotate,) var(--tw-invert,) var(--tw-saturate,) var(--tw-sepia,) var(--tw-drop-shadow,)}.sepia{--tw-sepia:sepia(100%);filter:var(--tw-blur,) var(--tw-brightness,) var(--tw-contrast,) var(--tw-grayscale,) var(--tw-hue-rotate,) var(--tw-invert,) var(--tw-saturate,) var(--tw-sepia,) var(--tw-drop-shadow,)}.backdrop-blur{--tw-backdrop-blur:blur(8px);-webkit-backdrop-filter:var(--tw-backdrop-blur,) var(--tw-backdrop-brightness,) var(--tw-backdrop-contrast,) var(--tw-backdrop-grayscale,) var(--tw-backdrop-hue-rotate,) var(--tw-backdrop-invert,) var(--tw-backdrop-opacity,) var(--tw-backdrop-saturate,) var(--tw-backdrop-sepia,);backdrop-filter:var(--tw-backdrop-blur,) var(--tw-backdrop-brightness,) var(--tw-backdrop-contrast,) var(--tw-backdrop-grayscale,) var(--tw-backdrop-hue-rotate,) var(--tw-backdrop-invert,) var(--tw-backdrop-opacity,) var(--tw-backdrop-saturate,) var(--tw-backdrop-sepia,)}.backdrop-grayscale{--tw-backdrop-grayscale:grayscale(100%);-webkit-backdrop-filter:var(--tw-backdrop-blur,) var(--tw-backdrop-brightness,) var(--tw-backdrop-contrast,) var(--tw-backdrop-grayscale,) var(--tw-backdrop-hue-rotate,) var(--tw-backdrop-invert,) var(--tw-backdrop-opacity,) var(--tw-backdrop-saturate,) var(--tw-backdrop-sepia,);backdrop-filter:var(--tw-backdrop-blur,) var(--tw-backdrop-brightness,) var(--tw-backdrop-contrast,) var(--tw-backdrop-grayscale,) var(--tw-backdrop-hue-rotate,) var(--tw-backdrop-invert,) var(--tw-backdrop-opacity,) var(--tw-backdrop-saturate,) var(--tw-backdrop-sepia,)}.backdrop-invert{--tw-backdrop-invert:invert(100%);-webkit-backdrop-filter:var(--tw-backdrop-blur,) var(--tw-backdrop-brightness,) var(--tw-backdrop-contrast,) var(--tw-backdrop-grayscale,) var(--tw-backdrop-hue-rotate,) var(--tw-backdrop-invert,) var(--tw-backdrop-opacity,) var(--tw-backdrop-saturate,) var(--tw-backdrop-sepia,);backdrop-filter:var(--tw-backdrop-blur,) var(--tw-backdrop-brightness,) var(--tw-backdrop-contrast,) var(--tw-backdrop-grayscale,) var(--tw-backdrop-hue-rotate,) var(--tw-backdrop-invert,) var(--tw-backdrop-opacity,) var(--tw-backdrop-saturate,) var(--tw-backdrop-sepia,)}.backdrop-sepia{--tw-backdrop-sepia:sepia(100%);-webkit-backdrop-filter:var(--tw-backdrop-blur,) var(--tw-backdrop-brightness,) var(--tw-backdrop-contrast,) var(--tw-backdrop-grayscale,) var(--tw-backdrop-hue-rotate,) var(--tw-backdrop-invert,) var(--tw-backdrop-opacity,) var(--tw-backdrop-saturate,) var(--tw-backdrop-sepia,);backdrop-filter:var(--tw-backdrop-blur,) var(--tw-backdrop-brightness,) var(--tw-backdrop-contrast,) var(--tw-backdrop-grayscale,) var(--tw-backdrop-hue-rotate,) var(--tw-backdrop-invert,) var(--tw-backdrop-opacity,) var(--tw-backdrop-saturate,) var(--tw-backdrop-sepia,)}.backdrop-filter{-webkit-backdrop-filter:var(--tw-backdrop-blur,) var(--tw-backdrop-brightness,) var(--tw-backdrop-contrast,) var(--tw-backdrop-grayscale,) var(--tw-backdrop-hue-rotate,) var(--tw-backdrop-invert,) var(--tw-backdrop-opacity,) var(--tw-backdrop-saturate,) var(--tw-backdrop-sepia,);backdrop-filter:var(--tw-backdrop-blur,) var(--tw-backdrop-brightness,) var(--tw-backdrop-contrast,) var(--tw-backdrop-grayscale,) var(--tw-backdrop-hue-rotate,) var(--tw-backdrop-invert,) var(--tw-backdrop-opacity,) var(--tw-backdrop-saturate,) var(--tw-backdrop-sepia,)}.transition{transition-property:color,background-color,border-color,outline-color,text-decoration-color,fill,stroke,--tw-gradient-from,--tw-gradient-via,--tw-gradient-to,opacity,box-shadow,transform,translate,scale,rotate,filter,-webkit-backdrop-filter,backdrop-filter,display,content-visibility,overlay,pointer-events;transition-timing-function:var(--tw-ease,var(--default-transition-timing-function));transition-duration:var(--tw-duration,var(--default-transition-duration))}.transition\!{transition-property:color,background-color,border-color,outline-color,text-decoration-color,fill,stroke,--tw-gradient-from,--tw-gradient-via,--tw-gradient-to,opacity,box-shadow,transform,translate,scale,rotate,filter,-webkit-backdrop-filter,backdrop-filter,display,content-visibility,overlay,pointer-events!important;transition-timing-function:var(--tw-ease,var(--default-transition-timing-function))!important;transition-duration:var(--tw-duration,var(--default-transition-duration))!important}.transition-colors{transition-property:color,background-color,border-color,outline-color,text-decoration-color,fill,stroke,--tw-gradient-from,--tw-gradient-via,--tw-gradient-to;transition-timing-function:var(--tw-ease,var(--default-transition-timing-function));transition-duration:var(--tw-duration,var(--default-transition-duration))}.outline-none{--tw-outline-style:none;outline-style:none}:where(.divide-x-reverse>:not(:last-child)){--tw-divide-x-reverse:1}.ring-inset{--tw-ring-inset:inset}.placeholder\:text-muted-foreground::placeholder{color:hsl(var(--muted-foreground))}.last\:border-0:last-child{border-style:var(--tw-border-style);border-width:0}@media(hover:hover){.hover\:bg-accent:hover{background-color:hsl(var(--accent))}.hover\:text-accent-foreground:hover{color:hsl(var(--accent-foreground))}.hover\:text-foreground:hover{color:hsl(var(--foreground))}.hover\:opacity-90:hover{opacity:.9}}.focus-visible\:ring-2:focus-visible{--tw-ring-shadow:var(--tw-ring-inset,) 0 0 0 calc(2px + var(--tw-ring-offset-width)) var(--tw-ring-color,currentcolor);box-shadow:var(--tw-inset-shadow),var(--tw-inset-ring-shadow),var(--tw-ring-offset-shadow),var(--tw-ring-shadow),var(--tw-shadow)}.focus-visible\:ring-ring:focus-visible{--tw-ring-color:hsl(var(--ring))}.focus-visible\:outline-none:focus-visible{--tw-outline-style:none;outline-style:none}.disabled\:opacity-50:disabled{opacity:.5}.aria-selected\:bg-accent[aria-selected=true]{background-color:hsl(var(--accent))}.aria-selected\:text-accent-foreground[aria-selected=true]{color:hsl(var(--accent-foreground))}@media(min-width:40rem){.sm\:grid-cols-2{grid-template-columns:repeat(2,minmax(0,1fr))}}}:root{--background:0 0% 100%;--foreground:222 22% 12%;--card:0 0% 100%;--card-foreground:222 22% 12%;--popover:0 0% 100%;--popover-foreground:222 22% 12%;--primary:172 70% 38%;--primary-foreground:0 0% 100%;--muted:220 14% 95%;--muted-foreground:220 9% 42%;--accent:220 14% 94%;--accent-foreground:222 22% 12%;--border:220 13% 88%;--input:220 13% 88%;--ring:172 66% 50%;--radius:.65rem}.dark{--background:222 24% 7%;--foreground:210 20% 92%;--card:222 22% 10%;--card-foreground:210 20% 92%;--popover:222 24% 9%;--popover-foreground:210 20% 92%;--primary:172 66% 50%;--primary-foreground:222 47% 8%;--muted:220 14% 15%;--muted-foreground:215 14% 62%;--accent:220 14% 17%;--accent-foreground:210 20% 92%;--border:220 14% 19%;--input:220 14% 19%;--ring:172 66% 50%}*{border-color:hsl(var(--border))}html,body,#root{height:100%}body{background-color:hsl(var(--background));color:hsl(var(--foreground));-webkit-font-smoothing:antialiased;margin:0;font-family:ui-sans-serif,system-ui,-apple-system,Segoe UI,Roboto,sans-serif}@property --tw-rotate-x{syntax:"*";inherits:false}@property --tw-rotate-y{syntax:"*";inherits:false}@property --tw-rotate-z{syntax:"*";inherits:false}@property --tw-skew-x{syntax:"*";inherits:false}@property --tw-skew-y{syntax:"*";inherits:false}@property --tw-pan-x{syntax:"*";inherits:false}@property --tw-pan-y{syntax:"*";inherits:false}@property --tw-pinch-zoom{syntax:"*";inherits:false}@property --tw-space-y-reverse{syntax:"*";inherits:false;initial-value:0}@property --tw-space-x-reverse{syntax:"*";inherits:false;initial-value:0}@property --tw-divide-x-reverse{syntax:"*";inherits:false;initial-value:0}@property --tw-border-style{syntax:"*";inherits:false;initial-value:solid}@property --tw-divide-y-reverse{syntax:"*";inherits:false;initial-value:0}@property --tw-leading{syntax:"*";inherits:false}@property --tw-font-weight{syntax:"*";inherits:false}@property --tw-ordinal{syntax:"*";inherits:false}@property --tw-slashed-zero{syntax:"*";inherits:false}@property --tw-numeric-figure{syntax:"*";inherits:false}@property --tw-numeric-spacing{syntax:"*";inherits:false}@property --tw-numeric-fraction{syntax:"*";inherits:false}@property --tw-shadow{syntax:"*";inherits:false;initial-value:0 0 #0000}@property --tw-shadow-color{syntax:"*";inherits:false}@property --tw-shadow-alpha{syntax:"";inherits:false;initial-value:100%}@property --tw-inset-shadow{syntax:"*";inherits:false;initial-value:0 0 #0000}@property --tw-inset-shadow-color{syntax:"*";inherits:false}@property --tw-inset-shadow-alpha{syntax:"";inherits:false;initial-value:100%}@property --tw-ring-color{syntax:"*";inherits:false}@property --tw-ring-shadow{syntax:"*";inherits:false;initial-value:0 0 #0000}@property --tw-inset-ring-color{syntax:"*";inherits:false}@property --tw-inset-ring-shadow{syntax:"*";inherits:false;initial-value:0 0 #0000}@property --tw-ring-inset{syntax:"*";inherits:false}@property --tw-ring-offset-width{syntax:"";inherits:false;initial-value:0}@property --tw-ring-offset-color{syntax:"*";inherits:false;initial-value:#fff}@property --tw-ring-offset-shadow{syntax:"*";inherits:false;initial-value:0 0 #0000}@property --tw-outline-style{syntax:"*";inherits:false;initial-value:solid}@property --tw-blur{syntax:"*";inherits:false}@property --tw-brightness{syntax:"*";inherits:false}@property --tw-contrast{syntax:"*";inherits:false}@property --tw-grayscale{syntax:"*";inherits:false}@property --tw-hue-rotate{syntax:"*";inherits:false}@property --tw-invert{syntax:"*";inherits:false}@property --tw-opacity{syntax:"*";inherits:false}@property --tw-saturate{syntax:"*";inherits:false}@property --tw-sepia{syntax:"*";inherits:false}@property --tw-drop-shadow{syntax:"*";inherits:false}@property --tw-drop-shadow-color{syntax:"*";inherits:false}@property --tw-drop-shadow-alpha{syntax:"";inherits:false;initial-value:100%}@property --tw-drop-shadow-size{syntax:"*";inherits:false}@property --tw-backdrop-blur{syntax:"*";inherits:false}@property --tw-backdrop-brightness{syntax:"*";inherits:false}@property --tw-backdrop-contrast{syntax:"*";inherits:false}@property --tw-backdrop-grayscale{syntax:"*";inherits:false}@property --tw-backdrop-hue-rotate{syntax:"*";inherits:false}@property --tw-backdrop-invert{syntax:"*";inherits:false}@property --tw-backdrop-opacity{syntax:"*";inherits:false}@property --tw-backdrop-saturate{syntax:"*";inherits:false}@property --tw-backdrop-sepia{syntax:"*";inherits:false} diff --git a/frontend/dist/index.html b/frontend/dist/index.html index 2abd19d..f732964 100644 --- a/frontend/dist/index.html +++ b/frontend/dist/index.html @@ -6,8 +6,8 @@ Mission Control 2.0 - - + +
diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx index dcd6e4c..d06ee66 100644 --- a/frontend/src/App.tsx +++ b/frontend/src/App.tsx @@ -3,6 +3,7 @@ import { Command as CommandIcon } from "lucide-react" import { NAV, type ViewId } from "@/nav" import { CommandPalette } from "@/components/CommandPalette" import { ModelsView } from "@/views/ModelsView" +import { RoutingView } from "@/views/RoutingView" import { Placeholder } from "@/views/Placeholder" import { api, type Health } from "@/lib/api" import { cn } from "@/lib/utils" @@ -88,7 +89,10 @@ export default function App() {
{view === "models" && } - {view !== "models" && } + {view === "routing" && } + {view !== "models" && view !== "routing" && ( + + )}
diff --git a/frontend/src/components/CapsChips.tsx b/frontend/src/components/CapsChips.tsx new file mode 100644 index 0000000..44b5440 --- /dev/null +++ b/frontend/src/components/CapsChips.tsx @@ -0,0 +1,27 @@ +import type { Capabilities } from "@/lib/api" + +function Chip({ children, tone = "muted" }: { children: React.ReactNode; tone?: "muted" | "primary" | "warn" }) { + const tones = { + muted: "bg-muted text-muted-foreground", + primary: "bg-primary/15 text-primary", + warn: "bg-amber-500/15 text-amber-500", + } + return ( + {children} + ) +} + +export function CapsChips({ caps }: { caps?: Capabilities }) { + if (!caps) return null + return ( + + {caps.coder && 💻 Code} + {caps.vision && 👁 Bild} + {caps.reasoning && 🧠 Reason} + {caps.moe && 🧩 MoE{caps.active_b ? `·${caps.active_b}b` : ""}} + {caps.tools === "yes" && 🛠 Tools} + {caps.tools === "likely" && 🛠 Tools?} + {caps.embedding && 🔢 Embed} + + ) +} diff --git a/frontend/src/lib/api.ts b/frontend/src/lib/api.ts index 10c457d..e784d6e 100644 --- a/frontend/src/lib/api.ts +++ b/frontend/src/lib/api.ts @@ -9,6 +9,26 @@ export async function api(path: string, init?: RequestInit): Promis return res.json() as Promise } +export interface Capabilities { + moe: boolean + active_b: number | null + tools: "yes" | "likely" | "no" + vision: boolean + coder: boolean + reasoning: boolean + embedding: boolean + ctx: number | null + params_b: number | null + arch: string | null +} + +export interface Fit { + level: "perfect" | "marginal" | "too_tight" + text: string + req_gb: number + tps: number +} + export interface ModelInfo { name: string role: string | null @@ -17,14 +37,52 @@ export interface ModelInfo { ctx: number | null ttl: number | null cmd: string + gguf_path: string filename: string quant: string size_bytes: number | null incomplete: boolean + capabilities: Capabilities +} + +export interface DiscoverModel { + name: string + author: string + repo: string + role: string + params_b: number + quant: string + tags: string[] + downloads: number + fit: Fit + optimal_ctx: number + caps: Capabilities +} + +export interface DiscoverCategory { + role: string + title: string + icon: string + models: DiscoverModel[] + recommended: string | null +} + +export interface DiscoverResp { + updated: number + categories: DiscoverCategory[] + sys_ram_gb: number +} + +export interface RoutingResp { + routes: { name: string; target: string; api_base: string | null }[] + fallbacks: Record[] + context_window_fallbacks: Record[] + gateway_reachable: boolean } export interface Health { status: string version: string engine_reachable: boolean + gateway_reachable: boolean } diff --git a/frontend/src/views/ModelsView.tsx b/frontend/src/views/ModelsView.tsx index 90a1c70..7662b1b 100644 --- a/frontend/src/views/ModelsView.tsx +++ b/frontend/src/views/ModelsView.tsx @@ -1,18 +1,31 @@ import { useEffect, useState } from "react" -import { api, type ModelInfo } from "@/lib/api" +import { api, type DiscoverResp, type Fit, type ModelInfo } from "@/lib/api" +import { CapsChips } from "@/components/CapsChips" +import { cn } from "@/lib/utils" function fmtSize(b: number | null) { if (!b) return "—" const gb = b / 1024 ** 3 return gb >= 1 ? `${gb.toFixed(1)} GB` : `${(b / 1024 ** 2).toFixed(0)} MB` } - function fmtCtx(c: number | null) { - if (!c) return "—" - return `${Math.round(c / 1024)}k` + return c ? `${Math.round(c / 1024)}k` : "—" } -export function ModelsView() { +function FitBadge({ fit }: { fit: Fit }) { + const tone = { + perfect: "bg-emerald-500/15 text-emerald-500", + marginal: "bg-amber-500/15 text-amber-500", + too_tight: "bg-red-500/15 text-red-500", + }[fit.level] + return ( + + {fit.text} · ~{fit.req_gb} GB + + ) +} + +function Installed() { const [models, setModels] = useState([]) const [error, setError] = useState("") const [loading, setLoading] = useState(true) @@ -24,71 +37,133 @@ export function ModelsView() { .finally(() => setLoading(false)) }, []) + if (loading) return
Lade…
+ if (error) + return ( +
+ Engine nicht erreichbar oder keine Config gefunden ({error}). +
+ ) + + return ( +
+ + + + + + + + + + + + {models.length === 0 && ( + + + + )} + {models.map((m) => ( + + + + + + + + ))} + +
ModellRolleFähigkeitenKontextGröße
+ Keine Modelle konfiguriert. +
{m.name} + {m.role ? ( + {m.role} + ) : ( + — + )} + + + {fmtCtx(m.ctx)}{fmtSize(m.size_bytes)}
+
+ ) +} + +function Discover() { + const [data, setData] = useState(null) + const [error, setError] = useState("") + const [loading, setLoading] = useState(true) + + useEffect(() => { + api("/api/discover") + .then(setData) + .catch((e) => setError(String(e))) + .finally(() => setLoading(false)) + }, []) + + if (loading) return
Suche aktuelle Modelle…
+ if (error || !data) + return ( +
+ Modell-Quellen gerade nicht erreichbar ({error}). +
+ ) + + return ( +
+
+ Live von HuggingFace · Hardware-Fit für ~{data.sys_ram_gb} GB · ⭐ = beste Wahl je Kategorie +
+ {data.categories.map((cat) => ( +
+

{cat.title}

+
+ {cat.models.map((m) => ( +
+
+ {cat.recommended === m.repo && ⭐} + {m.name} +
+
{m.author}
+
+ + +
+
+ ))} +
+
+ ))} +
+ ) +} + +export function ModelsView() { + const [tab, setTab] = useState<"installed" | "discover">("installed") return (

Modelle & Routing

- In llama-swap konfigurierte Modelle (Phase 0: read-only). Installieren, Gruppen & - Auto-Routing folgen in Phase 1. + Installierte Modelle (mit Fähigkeiten) und aktuell beste Modelle für deine Hardware.

- {loading &&
Lade…
} - {error && ( -
- Engine nicht erreichbar oder keine Config gefunden ({error}). -
- )} +
+ {(["installed", "discover"] as const).map((t) => ( + + ))} +
- {!loading && !error && ( -
- - - - - - - - - - - - {models.length === 0 && ( - - - - )} - {models.map((m) => ( - - - - - - - - ))} - -
ModellRolleKontextQuantGröße
- Keine Modelle konfiguriert. -
- {m.name} - {m.incomplete && ( - - unvollständig - - )} - - {m.role ? ( - - {m.role} - - ) : ( - — - )} - {fmtCtx(m.ctx)}{m.quant || "—"}{fmtSize(m.size_bytes)}
-
- )} + {tab === "installed" ? : }
) } diff --git a/frontend/src/views/RoutingView.tsx b/frontend/src/views/RoutingView.tsx new file mode 100644 index 0000000..41aa455 --- /dev/null +++ b/frontend/src/views/RoutingView.tsx @@ -0,0 +1,79 @@ +import { useEffect, useState } from "react" +import { api, type RoutingResp } from "@/lib/api" +import { cn } from "@/lib/utils" + +export function RoutingView() { + const [data, setData] = useState(null) + const [error, setError] = useState("") + + useEffect(() => { + api("/api/routing").then(setData).catch((e) => setError(String(e))) + }, []) + + return ( +
+
+

Routing

+

+ Der LiteLLM-Gateway bündelt alle Modelle zu einem Endpunkt. auto = schnell im + Alltag, eskaliert bei Bedarf auf heavy. Gilt für Hermes und Vibe Coding. +

+
+ + {error && ( +
+ Gateway-Config nicht lesbar ({error}). +
+ )} + + {data && ( + <> +
+ + Gateway {data.gateway_reachable ? "online" : "offline (Config wird trotzdem angezeigt)"} +
+ +
+ + + + + + + + + {data.routes.map((r) => ( + + + + + ))} + +
Gateway-Modell→ Backend (llama-swap)
{r.name}{r.target}
+
+ + {data.fallbacks.length > 0 && ( +
+
Eskalation (Fallbacks)
+
    + {data.fallbacks.map((f, i) => { + const [k, v] = Object.entries(f)[0] + return ( +
  • + {k} → {v.join(", ")} +
    • + ) + })} +
+
+ )} + + )} +
+ ) +} diff --git a/gateway/config.yaml b/gateway/config.yaml new file mode 100644 index 0000000..00f3170 --- /dev/null +++ b/gateway/config.yaml @@ -0,0 +1,65 @@ +# LiteLLM-Gateway-Config für Mission Control 2.0 +# ---------------------------------------------------------------------------- +# EIN OpenAI-Endpunkt für ALLE Konsumenten (Hermes + Vibe-Coding-IDEs). +# Hinter dem Gateway sitzt llama-swap (:8080), das die llama-swap-Rollen-Aliase +# (fast/heavy/vision/coder) bei Bedarf lädt — fast+heavy sind via llama-swap +# `groups` (swap:false) ko-resident, daher Delegation ohne Nachlade-Latenz. +# +# Wird von Mission Control verwaltet (services/gateway.py). Start auf der Box: +# litellm --config /opt/mission-control-2/gateway/config.yaml --port 4000 +# +# HINWEIS (auf der Box verifizieren): Der KOMPLEXITÄTS-Auto-Router ("model: auto" +# wählt pro Anfrage schnell↔schwer nach Schwierigkeit) ist LiteLLM-versionsabhängig. +# Baseline unten: "auto" == fast, eskaliert per Fallback auf heavy (bei Fehler/ +# Kontext-Overflow). Den echten Complexity-Router (docs.litellm.ai/docs/proxy/ +# auto_routing) in Phase „Routing-Feinschliff" gegen die installierte Version setzen. + +model_list: + # Schnelles Alltags-Hirn (llama-swap-Alias "fast") + - model_name: fast + litellm_params: + model: openai/fast + api_base: http://127.0.0.1:8080/v1 + api_key: sk-noauth + + # Schweres Reasoning-Hirn (llama-swap-Alias "heavy") + - model_name: heavy + litellm_params: + model: openai/heavy + api_base: http://127.0.0.1:8080/v1 + api_key: sk-noauth + + # Vision (llama-swap-Alias "vision") + - model_name: vision + litellm_params: + model: openai/vision + api_base: http://127.0.0.1:8080/v1 + api_key: sk-noauth + + # Coder (llama-swap-Alias "coder") + - model_name: coder + litellm_params: + model: openai/coder + api_base: http://127.0.0.1:8080/v1 + api_key: sk-noauth + + # "auto" — Baseline: == fast, eskaliert per Fallback auf heavy. + - model_name: auto + litellm_params: + model: openai/fast + api_base: http://127.0.0.1:8080/v1 + api_key: sk-noauth + +litellm_settings: + # Bei Fehler/Kontext-Overflow von "auto"/"fast" auf "heavy" eskalieren. + fallbacks: + - auto: ["heavy"] + - fast: ["heavy"] + context_window_fallbacks: + - auto: ["heavy"] + - fast: ["heavy"] + num_retries: 1 + request_timeout: 600 + +router_settings: + routing_strategy: simple-shuffle