From 84dc34c0a3439426df92f4bc65fbedeb2c2f12e6 Mon Sep 17 00:00:00 2001 From: Hitonabi Date: Thu, 27 Aug 2026 14:58:42 +0200 Subject: [PATCH] fix(stack): Mem0 restlos ausgebaut + vier stille Defekte behoben Systemaudit vom 27.08.2026. Alle Befunde gemessen, nicht vermutet. VIER STILLE DEFEKTE 1. mc2-steward startete seit Wochen nicht (live: 207.609 Neustarts). steward.py importierte services.memory, das beim Mem0-Ausbau geloescht wurde -> ImportError bei jedem Start. Re-Warm- und Health-Waechter waren damit tot. 2. Jedes Hermes-Update wurde automatisch zurueckgerollt. hermes-postcheck.sh prueft vier Dinge, die es seit dem 07.08. nicht mehr gibt (Sidecar :8765, /api/memory, memory.provider, mc2-memory-Plugin). Die Checks konnten nicht gruen werden -> autoupdate.sh wertete jedes Update als rot und rollte es zurueck. Checks ersatzlos entfernt; der Tool-Smoke laeuft ohnehin durch den echten Agenten. 3. 7 von 12 Skills waren per Knopfdruck nicht startbar. deploy.sh kopiert Skills mit tr '-' '_' nach ~/.hermes/skills/, routers/skills.py gab Hermes aber den Ordnernamen MIT Bindestrich. Der Knopf meldete Erfolg, ausgefuehrt wurde nichts. Neu: _hermes_name(). 4. deploy.sh warf bei jedem Deploy die Live-Modellkonfiguration weg. MC2 schreibt /etc/llama-swap/config.yaml selbst; die Repo-Datei ist nur ein Abzug (ihm fehlt u.a. kritiker/Devstral). Jetzt: erst sichern, Diff zeigen, dann kopieren. MC_DEPLOY_SKIP_SWAP_CONFIG=1 ueberspringt. MEM0-AUSBAU VOLLENDET (Kriterium 3: 17 -> 0 Dateien) - mem0_service/, mcp/mcp_memory.py und hermes/plugins/mc2-memory entfernt; das Plugin schickte bei JEDEM Turn zwei 404-Requests an tote Routen. - MEMORY_DB/MEM0_SERVICE_URL, _mem0_reachable(), MC_MEMORY_DB und MC_MEM_DEDUPE_ENABLED aus Config/Router/Unit entfernt. - mem0_ms war strukturell tot (park("retrieve") wird nirgends mehr aufgerufen) -> aus Backend, API-Typ und Latenzkarte entfernt. - Verbinden-Tab: tote Gedaechtnis-MCP-Leitung raus, Status-Kachel bleibt. - AGENTS.md beschrieb Mem0 noch als aktiv - korrigiert. GATEWAY-ROBUSTHEIT - _proxy gab bei ungueltigen Payloads HTTP 500 (gemessen 5/5: Rohtext, leerer Body, JSON-Liste, JSON-String, null) -> jetzt 5/5 HTTP 400. - Bild-Weiche ohne Deckel: 10 Bilder x 2 Versuche x 240 s hielten den Client bis zu 80 min. Neu: MC_CODER_IMAGE_MAX (4), Rueckfall auf die Vision-Umleitung. - /v1/models: nicht-JSON von der Engine gab 500 -> jetzt 502. UNITS UND DEPLOY - mc2-steward.service, dessen warmset-Drop-in und voice-service.service fehlten im Repo, obwohl maintenance.py und stack-postcheck.sh sie voraussetzen. 1:1 von der laufenden Box uebernommen. - deploy.sh startete mc2-steward nie neu; restore.sh liess mc2-gateway und mc2-steward mit alter Config weiterlaufen. Beide ergaenzt. FRONTEND - useEigenleben rief /api/eigenleben - existiert im Backend nicht und wurde nirgends genutzt. Samt Typen entfernt. - Anleitung beschrieb einen Gedaechtnis-Tab, den es nicht gibt. - Abgeglichen: alle uebrigen 63 Frontend-Aufrufe treffen echte Routen, alle 5 SSE-Invalidation-Keys sind gemappt, keine ungefangenen Promises. Gates: compileall gruen - ruff "All checks passed" - tsc gruen - vite build gruen (dist aktualisiert) - Importe app/steward/gateway_app gruen. Co-Authored-By: Claude Opus 5 --- .agents/mcp_config.json | 6 - AGENTS.md | 2 +- backend/config.py | 15 +- backend/routers/connect.py | 11 +- backend/routers/gateway_proxy.py | 38 +- backend/routers/skills.py | 31 +- backend/routers/system.py | 9 +- backend/routers/voice.py | 12 +- backend/routers/zeitmaschine.py | 2 +- backend/services/backup.py | 2 +- backend/services/connect.py | 27 +- backend/services/sentry.py | 2 +- backend/services/voice_metrics.py | 46 +- backend/steward.py | 13 +- deploy/agent-hooks/box-steckbrief-inject.sh | 2 +- deploy/autoupdate.sh | 2 +- deploy/backup.sh | 17 +- deploy/deploy.sh | 33 +- deploy/hermes-postcheck.sh | 41 +- deploy/llama-swap.config.yaml | 4 +- deploy/mc2-backup.service | 2 +- deploy/mc2-steward.service | 37 ++ deploy/mc2-steward.service.d-warmset.conf | 11 + deploy/mission-control-2.service | 9 +- deploy/restore.sh | 10 +- deploy/stack-postcheck.sh | 17 +- deploy/venv-audit.sh | 4 +- deploy/voice-service.service | 33 ++ deploy/warmup.sh | 2 +- docs/wissen/STACK.md | 3 +- ...View-C-rUOPjn.js => AgentView-pp2NXhb4.js} | 2 +- ...YOUdf1.js => AuftragsbuchView-CFtqxzIs.js} | 2 +- ...ew-BBdQX2_R.js => ChronikView-BbW5EQy6.js} | 2 +- frontend/dist/assets/ConnectView-5DXpNBft.js | 26 - frontend/dist/assets/ConnectView-Ibsr5kGX.js | 26 + ...View-D6hHVfTx.js => GuideView-DwZocTb3.js} | 8 +- ...View-DcsN5ZLB.js => IdeenView-J4hS7xB2.js} | 2 +- ...obsBar-Ckecoyqy.js => JobsBar-DG8VDiAV.js} | 2 +- ...ew-Bdk_kJ2m.js => KonsoleView-BDDotueL.js} | 2 +- ...iew-aEV2pe9C.js => ModelsView-DIBx0djl.js} | 2 +- ...l-BfFwUeZU.js => SectionLabel-DKDWJ8hi.js} | 2 +- ...iew-C5D9xEVH.js => SkillsView-XWoP6WFO.js} | 2 +- ...iew-DpReQzIY.js => WissenView-DgvIyHvX.js} | 29 +- ...n-SPeGIim5.js => chevron-down-BTSzJRag.js} | 2 +- ...e-xml-AZtn6xxf.js => code-xml-BiSOeCkP.js} | 2 +- frontend/dist/assets/folder-open-FZLk16T9.js | 6 - .../{index-CCbyojll.js => index-DNt66je4.js} | 78 +-- ...{index-Dv1-nhwH.css => index-qQDuX0H0.css} | 2 +- ...{layers-Dpl2QlP2.js => layers-BakyhGhx.js} | 2 +- ...ccw-DuKtbjZS.js => rotate-ccw-CGv9dXzB.js} | 2 +- .../{zap-CRNNnxfs.js => zap-cdYTHDpR.js} | 2 +- frontend/dist/index.html | 4 +- .../src/components/dashboard/LatencyCard.tsx | 8 +- frontend/src/lib/api.ts | 58 +-- frontend/src/lib/queries.ts | 23 - frontend/src/views/ConnectView.tsx | 72 +-- frontend/src/views/GuideView.tsx | 10 +- hermes/plugins/mc2-memory/__init__.py | 250 --------- hermes/plugins/mc2-memory/plugin.yaml | 5 - mcp/mcp_mc.py | 6 +- mcp/mcp_memory.py | 127 ----- mem0_service/app.py | 483 ------------------ mem0_service/migrate.py | 62 --- mem0_service/requirements.txt | 9 - mem0_service/smoke_test.py | 71 --- 65 files changed, 394 insertions(+), 1440 deletions(-) create mode 100644 deploy/mc2-steward.service create mode 100644 deploy/mc2-steward.service.d-warmset.conf create mode 100644 deploy/voice-service.service rename frontend/dist/assets/{AgentView-C-rUOPjn.js => AgentView-pp2NXhb4.js} (99%) rename frontend/dist/assets/{AuftragsbuchView-BdYOUdf1.js => AuftragsbuchView-CFtqxzIs.js} (99%) rename frontend/dist/assets/{ChronikView-BBdQX2_R.js => ChronikView-BbW5EQy6.js} (99%) delete mode 100644 frontend/dist/assets/ConnectView-5DXpNBft.js create mode 100644 frontend/dist/assets/ConnectView-Ibsr5kGX.js rename frontend/dist/assets/{GuideView-D6hHVfTx.js => GuideView-DwZocTb3.js} (64%) rename frontend/dist/assets/{IdeenView-DcsN5ZLB.js => IdeenView-J4hS7xB2.js} (99%) rename frontend/dist/assets/{JobsBar-Ckecoyqy.js => JobsBar-DG8VDiAV.js} (96%) rename frontend/dist/assets/{KonsoleView-Bdk_kJ2m.js => KonsoleView-BDDotueL.js} (98%) rename frontend/dist/assets/{ModelsView-aEV2pe9C.js => ModelsView-DIBx0djl.js} (99%) rename frontend/dist/assets/{SectionLabel-BfFwUeZU.js => SectionLabel-DKDWJ8hi.js} (93%) rename frontend/dist/assets/{SkillsView-C5D9xEVH.js => SkillsView-XWoP6WFO.js} (98%) rename frontend/dist/assets/{WissenView-DpReQzIY.js => WissenView-DgvIyHvX.js} (81%) rename frontend/dist/assets/{chevron-down-SPeGIim5.js => chevron-down-BTSzJRag.js} (85%) rename frontend/dist/assets/{code-xml-AZtn6xxf.js => code-xml-BiSOeCkP.js} (88%) delete mode 100644 frontend/dist/assets/folder-open-FZLk16T9.js rename frontend/dist/assets/{index-CCbyojll.js => index-DNt66je4.js} (87%) rename frontend/dist/assets/{index-Dv1-nhwH.css => index-qQDuX0H0.css} (53%) rename frontend/dist/assets/{layers-Dpl2QlP2.js => layers-BakyhGhx.js} (91%) rename frontend/dist/assets/{rotate-ccw-DuKtbjZS.js => rotate-ccw-CGv9dXzB.js} (88%) rename frontend/dist/assets/{zap-CRNNnxfs.js => zap-cdYTHDpR.js} (96%) delete mode 100644 hermes/plugins/mc2-memory/__init__.py delete mode 100644 hermes/plugins/mc2-memory/plugin.yaml delete mode 100644 mcp/mcp_memory.py delete mode 100644 mem0_service/app.py delete mode 100644 mem0_service/migrate.py delete mode 100644 mem0_service/requirements.txt delete mode 100644 mem0_service/smoke_test.py diff --git a/.agents/mcp_config.json b/.agents/mcp_config.json index 6b39384..15de689 100644 --- a/.agents/mcp_config.json +++ b/.agents/mcp_config.json @@ -1,11 +1,5 @@ { "mcpServers": { - "mc2-memory": { - "command": "python", - "args": [ - "F:\\Coding Stuff\\mission-control-2\\mcp\\mcp_memory.py" - ] - }, "mc2-system": { "command": "python", "args": [ diff --git a/AGENTS.md b/AGENTS.md index 327bf9c..0e5648d 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -12,7 +12,7 @@ Engine (llama-swap) · Builtin-Routing-Gateway (`model: auto`) · MC2 (FastAPI + - **System:** Bosgame M5 (AMD Strix Halo APU) - **Arbeitsspeicher (RAM/VRAM):** 128 GB Shared Memory (ca. 122.7 GB nutzbar). - **Inference-Limit:** Modelle im GGUF-Format dürfen maximal ca. 100-110 GB groß sein (entspricht ca. 150B Parametern bei Q4_K_M). Größere Modelle (wie 200B+ oder 2T Parameter) **können lokal nicht ausgeführt werden** und sind auszuschließen, es sei denn, es handelt sich um stark quantisierte MoEs. -**Gedächtnis & Dienste:** Hermes ist das autonome Agenten-Gehirn („Lucy"). Mem0 läuft als dedizierter semantischer Langzeit-Gedächtnis-Sidecar (`mem0-service` auf `:8765`) und wird von Hermes via MCP (`mcp_memory.py`) eingebunden. Governor, Zed-Workflows und alte Mittelschichten sind komplett gelöscht. +**Gedächtnis & Dienste:** Hermes ist das autonome Agenten-Gehirn („Lucy") **und die alleinige Gedächtnis-Wahrheit** — es führt sein Gedächtnis selbst. Der frühere Sidecar auf `:8765` samt Memory-MCP-Server und MC2-Memory-Plugin wurde am 07.08.2026 abgelöst und am 27.08.2026 restlos ausgebaut (`docs/wissen/VERDIKTE.md`): MC2 hat **keine** `/api/memory`-Routen mehr, nichts darf mehr dorthin greifen. Governor, Zed-Workflows und alte Mittelschichten sind komplett gelöscht. ## Sprache (nicht verhandelbar) - **Alles User-Sichtbare ist Deutsch:** UI-Texte, Fehlermeldungen, Update-/Radar-Meldungen, diff --git a/backend/config.py b/backend/config.py index 1f5be42..af24707 100644 --- a/backend/config.py +++ b/backend/config.py @@ -19,13 +19,9 @@ MODELS_DIR = Path(os.environ.get("MC_MODELS_DIR", "/srv/models")) # 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 -# Geteiltes Gedächtnis (SQLite, WAL). Persistent neben den Modellen. -# Hinweis: nur noch für die einmalige Mem0-Migration relevant — das aktive Gedächtnis -# liegt jetzt in Mem0/Chroma hinter dem Sidecar (siehe MEM0_SERVICE_URL). -MEMORY_DB = Path(os.environ.get("MC_MEMORY_DB", str(MODELS_DIR / "mc2-memory.db"))) -# Mem0-Sidecar (auto-lernendes, semantisches Gedächtnis). Läuft im ~/.mem0/venv (Python 3.12), -# weil mem0+chromadb unter dem 3.14-Backend nicht laufen. MC2 spricht ihn lokal per HTTP an. -MEM0_SERVICE_URL = os.environ.get("MC_MEM0_SERVICE_URL", "http://127.0.0.1:8765").rstrip("/") +# Gedächtnis: MC2 hält KEINS mehr. Bis August 2026 lief hier erst eine eigene SQLite-DB, +# dann ein semantischer Sidecar auf :8765 — beides ist abgelöst, der Port ist tot. +# Einzige Gedächtnis-Wahrheit ist jetzt Hermes selbst (HERMES_API_URL, siehe unten). # Befehl-Vorlage für llama-swap: {model}=GGUF-Pfad, {ctx}=Kontext, ${PORT} bleibt stehen. # Hinweis: --prompt-cache/--prompt-cache-all sind llama-CLI-Flags, NICHT llama-server — # llama-server lehnt sie ab ("invalid argument") und startet dann nicht. Prompt-Caching @@ -72,7 +68,7 @@ V1_UPSTREAM = os.environ.get("MC_V1_UPSTREAM", "").rstrip("/") HERMES_API_URL = os.environ.get("HERMES_API_URL", "http://127.0.0.1:8642").rstrip("/") # API-Key der Hermes-`api_server`-Plattform (~/.hermes/.env: API_SERVER_KEY). Nötig für # /v1/chat/completions (Voice-Pipeline) — Bearer-Auth, sonst 401. Derselbe volle Agent -# (Tools + geteiltes Mem0) wie CLI/Telegram, nur über HTTP. +# (Tools + eigenes Gedächtnis) wie CLI/Telegram, nur über HTTP. def _read_hermes_env(key: str) -> str: """Liest einen Schlüssel aus ~/.hermes/.env (Fallback, falls nicht in der Prozess-Env). Der MC2-Dienst erbt die Hermes-Secrets sonst nicht.""" @@ -97,7 +93,8 @@ HERMES_API_KEY = ( HERMES_API_MODEL = os.environ.get("HERMES_API_MODEL", "hermes") # --- Voice-Sidecar (STT faster-whisper + TTS Piper/Chatterbox) --------------- -# Eigenes Python-3.12-venv (~/.voice/venv), analog Mem0-Sidecar. MC2 proxyt nach außen. +# Eigenes Python-3.12-venv (~/.voice/venv), weil Parakeet/Piper nicht ins 3.14-Backend-venv +# passen. MC2 proxyt nach außen. VOICE_SERVICE_URL = os.environ.get("MC_VOICE_SERVICE_URL", "http://127.0.0.1:8650").rstrip("/") # Box-Konsole: ttyd-Web-Terminal (echte Login-Shell). Bindet NUR an Loopback # (127.0.0.1:7682, base-path /console) und wird von MC2 über den ohnehin offenen Port 9001 diff --git a/backend/routers/connect.py b/backend/routers/connect.py index eac9199..2844fda 100644 --- a/backend/routers/connect.py +++ b/backend/routers/connect.py @@ -1,4 +1,4 @@ -"""Connect-Endpoint: erzeugt IDE-/Agent-Snippets (auf den Gateway + Memory-MCP).""" +"""Connect-Endpoint: erzeugt IDE-/Agent-Snippets für den Gateway.""" from fastapi import APIRouter from services.connect import DEFAULT_HOST, build_snippets, check_health @@ -7,14 +7,11 @@ router = APIRouter(prefix="/api") @router.get("/connect") -def connect(host: str = DEFAULT_HOST, mcp_path: str | None = None) -> dict: - kwargs = {} - if mcp_path: - kwargs["mcp_script_path"] = mcp_path - return build_snippets(host=host, **kwargs) +def connect(host: str = DEFAULT_HOST) -> dict: + return build_snippets(host=host) @router.get("/connect/health") def connect_health() -> dict: - """Live-Status der zwei Leitungen (Gateway + Gedächtnis) für den Verbinden-Tab.""" + """Live-Status der drei Leitungen (Gateway, Gedächtnis, Desktop-Gateway) für den Verbinden-Tab.""" return check_health() diff --git a/backend/routers/gateway_proxy.py b/backend/routers/gateway_proxy.py index 77fea05..23b45b5 100644 --- a/backend/routers/gateway_proxy.py +++ b/backend/routers/gateway_proxy.py @@ -22,6 +22,13 @@ _LANG_DIRECTIVE = os.environ.get( "Quellcode, Bezeichner und Shell-Befehle bleiben unverändert.") +# Deckel für die Bild-Weiche. Ohne ihn wächst die Wartezeit linear mit der Bildzahl: +# je Bild bis zu 2 Versuche à _BILD_TIMEOUT_S, und der Client hängt so lange am offenen +# Request. Über _BILD_MAX Bilder wird gar nicht erst beschrieben — der Aufrufer fällt +# dann auf die normale Vision-Umleitung zurück (ehrlich langsam statt scheinbar hängend). +_BILD_TIMEOUT_S = float(os.environ.get("MC_CODER_IMAGE_TIMEOUT_S", "240")) +_BILD_MAX = int(os.environ.get("MC_CODER_IMAGE_MAX", "4")) + # Bild-Beschreibung für Coder-Ziele: Prompt bewusst auf wörtliche Wiedergabe von # Code/Fehlermeldungen getrimmt — der Coder arbeitet nur mit diesem Text weiter. _BILD_BESCHREIB_PROMPT = os.environ.get( @@ -85,6 +92,10 @@ async def _bilder_fuer_coder_beschreiben(body: dict, client, vision_alias: str) for i, part in enumerate(m["content"]): if isinstance(part, dict) and part.get("type") in IMAGE_PART_TYPES: fundstellen.append((m, i, part)) + if len(fundstellen) > _BILD_MAX: + log.warning("Bild-Weiche v2: %s Bilder (Deckel %s) — Request geht an das Vision-Modell " + "statt einzeln beschrieben zu werden", len(fundstellen), _BILD_MAX) + return False for nr, (msg, idx, part) in enumerate(fundstellen, start=1): frage = { "model": vision_alias, @@ -99,7 +110,7 @@ async def _bilder_fuer_coder_beschreiben(body: dict, client, vision_alias: str) text = "" for versuch in (1, 2): try: - async with httpx.AsyncClient(timeout=240.0) as c: + async with httpx.AsyncClient(timeout=_BILD_TIMEOUT_S) as c: r = await c.post(f"{LLAMA_SWAP_URL}/v1/chat/completions", json=frage) if r.status_code == 200: text = ((r.json().get("choices") or [{}])[0].get("message") or {}).get("content") or "" @@ -138,7 +149,15 @@ def _inject_language(body: dict, alias: str) -> None: async def models(request: Request): client = request.app.state.gw_client # geteilter Keep-Alive-Client (siehe app.py lifespan) r = await client.get(f"{LLAMA_SWAP_URL}/v1/models", timeout=10.0) - data = r.json() + try: + data = r.json() + except ValueError: + # Engine antwortet, aber nicht mit JSON (Startphase/Fehlerseite) — ehrlicher 502 + # statt eines 500ers aus dem Parser. + log.warning("/v1/models: Engine-Antwort ist kein JSON (HTTP %s): %.200s", r.status_code, r.text) + return JSONResponse( + {"error": {"message": "Engine lieferte keine gültige Modell-Liste.", + "type": "upstream_error"}}, status_code=502) # Aufgeräumt (07/2026): Die Router-Lanes (coding/chat) werden NICHT mehr als „Modell" # angeboten — sie verwirrten (coding vs. coder) und seit dem Zed-Aus wählt sie niemand # mehr. Das Routing bleibt erhalten (siehe _proxy), sie stehen nur nicht mehr in der Liste. @@ -187,7 +206,20 @@ async def models(request: Request): async def _proxy(path: str, request: Request): - body = await request.json() + # Ungültige Payloads gehören dem Client, nicht dem Server: ohne diese Prüfung wirft + # request.json() bzw. body.get(...) durch und der Aufrufer bekommt einen 500er + # (gemessen 27.08.2026: Rohtext, leerer Body, JSON-Liste, JSON-String und null — 5/5 mal 500). + try: + body = await request.json() + except Exception: + return JSONResponse( + {"error": {"message": "Ungültiger Request-Body: JSON erwartet.", + "type": "invalid_request_error"}}, status_code=400) + if not isinstance(body, dict): + return JSONResponse( + {"error": {"message": "Ungültiger Request-Body: JSON-Objekt erwartet, " + f"'{type(body).__name__}' bekommen.", + "type": "invalid_request_error"}}, status_code=400) _apply_no_think_marker(body) # Lucy-Voice-Schnellspur: Marker strippen + Thinking aus requested = str(body.get("model") or "auto") if requested.lower() in ("auto", "chat", "coding"): diff --git a/backend/routers/skills.py b/backend/routers/skills.py index 258f869..c3a7352 100644 --- a/backend/routers/skills.py +++ b/backend/routers/skills.py @@ -7,6 +7,20 @@ from pydantic import BaseModel router = APIRouter(prefix="/api") + +def _hermes_name(ordner: str) -> str: + """Repo-Ordnername -> Hermes-Skillname. + + deploy/deploy.sh kopiert `deploy/skills/` nach `~/.hermes/skills/` + (`tr '-' '_'`), weil Hermes keine Bindestriche in Skillnamen mag. Ohne dieselbe + Umschreibung hier bekam Hermes den Ordnernamen MIT Bindestrich und fand den Skill + nicht - betroffen waren 7 der 12 Skills (betrieb-playbook, konzept-fliessband, + llm-wiki, morning-report, pc-pfad-cache, projekt-start, trend-radar): der Startknopf + meldete Erfolg, ausgefuehrt wurde nichts. deploy.sh bleibt die Quelle der Wahrheit. + """ + return ordner.replace("-", "_") + + class RunSkillRequest(BaseModel): skill_name: str @@ -57,8 +71,11 @@ def list_skills(): skills.append({ "name": entry.name, + # Der Name, unter dem Hermes den Skill kennt - auch fuer den Laufend- + # Vergleich, weil im Prozess-cmdline genau dieser Name steht. + "hermes_name": _hermes_name(entry.name), "description": description or "Keine Beschreibung verfügbar.", - "running": entry.name in running_skills + "running": _hermes_name(entry.name) in running_skills }) return {"skills": skills} @@ -70,13 +87,15 @@ def run_skill(req: RunSkillRequest): # Fallback falls lokal (auf Windows) entwickelt wird return {"ok": False, "err": "Hermes CLI nicht gefunden (~/.local/bin/hermes fehlt). Bist du lokal unterwegs?"} - # Entspricht: hermes -z "Führe den 'X' Skill aus" chat - cmd = [hermes_bin, "-z", f"Führe den '{req.skill_name}' Skill aus", "chat"] + # Entspricht: hermes -z "Führe den 'X' Skill aus" chat - mit dem Namen, den Hermes + # nach dem Deploy-Sync wirklich kennt (Bindestriche -> Unterstriche, s. _hermes_name). + skill = _hermes_name(req.skill_name) + cmd = [hermes_bin, "-z", f"Führe den '{skill}' Skill aus", "chat"] try: - log_path = os.path.expanduser(f"~/.hermes/logs/skill_{req.skill_name.replace('/', '_')}.log") + log_path = os.path.expanduser(f"~/.hermes/logs/skill_{skill.replace('/', '_')}.log") os.makedirs(os.path.dirname(log_path), exist_ok=True) - with open(log_path, "a") as f: - f.write(f"\n--- Starting Skill: {req.skill_name} ---\n") + with open(log_path, "a", encoding="utf-8") as f: + f.write(f"\n--- Starting Skill: {skill} ---\n") subprocess.Popen(cmd, stdout=f, stderr=subprocess.STDOUT) return {"ok": True, "msg": f"Skill '{req.skill_name}' erfolgreich angestoßen."} except Exception as e: diff --git a/backend/routers/system.py b/backend/routers/system.py index 7ec3eeb..9f8e1f3 100644 --- a/backend/routers/system.py +++ b/backend/routers/system.py @@ -10,7 +10,7 @@ import os import subprocess import httpx -from config import GATEWAY_URL, HERMES_API_URL, LLAMA_SWAP_URL, MEM0_SERVICE_URL, V1_UPSTREAM, VOICE_SERVICE_URL +from config import GATEWAY_URL, HERMES_API_URL, LLAMA_SWAP_URL, V1_UPSTREAM, VOICE_SERVICE_URL from fastapi import APIRouter from pydantic import BaseModel from services import backup as backup_svc @@ -42,13 +42,6 @@ def history(minutes: int = 60) -> dict: return metrics_history.history(minutes) -def _mem0_reachable() -> bool: - try: - return httpx.get(f"{MEM0_SERVICE_URL}/health", timeout=2).status_code == 200 - except Exception: - return False - - def _voice_reachable() -> bool: try: return httpx.get(f"{VOICE_SERVICE_URL}/health", timeout=2).status_code == 200 diff --git a/backend/routers/voice.py b/backend/routers/voice.py index 5a5faa8..a86a8ea 100644 --- a/backend/routers/voice.py +++ b/backend/routers/voice.py @@ -3,7 +3,7 @@ Voice-Endpoints für „Mit Hermes reden" (Browser-Voice + 3D-Avatar). Dünner Layer: STT/TTS werden zum Voice-Sidecar (:8650) geproxyt; der Chat geht an den Hermes-`api_server` (:8642, OpenAI-kompatibel) — denselben vollen Agenten mit Tools + -geteiltem Mem0 wie CLI/Telegram. Mit stabilem `X-Hermes-Session-Id` hält die Plattform den +eigenem Gedächtnis wie CLI/Telegram. Mit stabilem `X-Hermes-Session-Id` hält die Plattform den Transcript server-seitig, daher schickt der Client je Turn nur die neue User-Nachricht. LAN-only (kein Token in der 2.0-Phase), wie die übrigen MC2-Endpoints. @@ -169,7 +169,7 @@ def voice_metrics() -> dict: @router.get("/voice/trace") def voice_trace(limit: int = 20) -> dict: """Per-Turn-Trace: die letzten `limit` Chat-Turns mit Stufen-Breakdown (STT · Vision · Hirn · - Generierung, Mem0 als Unter-Detail). Neueste zuerst. Für die Latenz-Ansicht im Cockpit — + Generierung). Neueste zuerst. Für die Latenz-Ansicht im Cockpit — damit man den EINEN langsamen Turn sieht, den ein Durchschnitt verschluckt.""" return {"turns": get_trace(limit)} @@ -289,8 +289,8 @@ async def voice_chat(body: ChatIn) -> StreamingResponse: headers["X-Hermes-Session-Key"] = body.session_key async def gen(): - # Per-Turn-Trace: sammelt STT (davor, geparkt) + Vision + Hirn-TTFT + Generierung + Mem0 - # (Rückruf während) zu EINEM Datensatz -> die Latenz-Ansicht zeigt den einzelnen Hänger. + # Per-Turn-Trace: sammelt STT (davor, geparkt) + Vision + Hirn-TTFT + Generierung zu EINEM + # Datensatz -> die Latenz-Ansicht zeigt den einzelnen Hänger. trace = TurnTrace(session_id=body.session_id, kind="voice") first = True first_content = True @@ -325,7 +325,7 @@ async def voice_chat(body: ChatIn) -> StreamingResponse: payload = {"model": body.model or HERMES_API_MODEL, "messages": messages, "stream": True} # Lucys Hirn (Qwen3.6) ist ein Thinking-Modell -> für die gesprochene Assistentin Thinking AUS, # sonst generiert es tausende Reasoning-Token VOR der kurzen Antwort (gemessen: 11k Token, ~30s TTFB). - # Gleiches Muster wie die fast-Spur im Gateway (gateway_proxy.py) und die Mem0-Extraktion. + # Gleiches Muster wie die fast-Spur im Gateway (gateway_proxy.py). if os.environ.get("MC_VOICE_NO_THINK", "1") not in ("0", "false", "False"): payload["chat_template_kwargs"] = {"enable_thinking": False} try: @@ -342,7 +342,7 @@ async def voice_chat(body: ChatIn) -> StreamingResponse: if first: # Time-To-First-Byte des Hermes-Streams (Verbindungs-Overhead) trace.note_ttfb() first = False - # Erster CONTENT-Delta = echte Hirn-Latenz (Agent-Overhead + Mem0 + LLM-TTFT) — + # Erster CONTENT-Delta = echte Hirn-Latenz (Agent-Overhead + Gedächtnis + LLM-TTFT) — # chat_ttfb misst nur den SSE-Start (~5 ms) und ist dafür blind. if first_content and b'"content"' in chunk: trace.note_first_content() diff --git a/backend/routers/zeitmaschine.py b/backend/routers/zeitmaschine.py index 5b5fe33..60b1021 100644 --- a/backend/routers/zeitmaschine.py +++ b/backend/routers/zeitmaschine.py @@ -33,7 +33,7 @@ def list_snapshots() -> dict: @router.get("/zeitmaschine/inhalt") def snapshot_contents(file: str) -> dict: - """Top-Level-Komponenten eines Snapshots (mem0, hermes, llama-swap, MANIFEST …).""" + """Top-Level-Komponenten eines Snapshots (hermes, llama-swap, MANIFEST …).""" if not _FILE_RX.match(file): raise HTTPException(400, "Ungültiger Snapshot-Name.") p = backup_svc.BACKUP_DIR / file diff --git a/backend/services/backup.py b/backend/services/backup.py index db42a1c..14120f3 100644 --- a/backend/services/backup.py +++ b/backend/services/backup.py @@ -1,5 +1,5 @@ """ -Voll-Zustands-Backup (mem0 + Hermes-Configs/Secrets + llama-swap config). +Voll-Zustands-Backup (Hermes-Configs/Secrets + llama-swap config). Delegiert an deploy/backup.sh (eine Quelle der Wahrheit, identisch zum systemd-Timer); Restore läuft bewusst nur per CLI (deploy/restore.sh) — siehe docs/BACKUP.md. """ diff --git a/backend/services/connect.py b/backend/services/connect.py index 0892729..4d821af 100644 --- a/backend/services/connect.py +++ b/backend/services/connect.py @@ -1,7 +1,13 @@ """ Connect: erzeugt saubere, getestete Konfig-Snippets für IDEs/Agenten auf dem LOKALEN PC (separate Maschine im LAN). Alle zeigen auf den **Gateway** der Box -(reale Modelle coder/heavy/vision, Cockpit-Port :9001/v1) + den **Shared-Memory-MCP** (MC :9001). +(reale Modelle coder/heavy/vision, Cockpit-Port :9001/v1). + +Gedächtnis ist hier bewusst KEINE eigene Leitung mehr: bis August 2026 gab es dafür einen +Memory-MCP-Server gegen MC2s /api/memory; seit dessen Ablösung (docs/wissen/VERDIKTE.md, +07.08.2026) führt Hermes sein Gedächtnis +selbst — es hängt am Agenten, nicht am Gateway. check_health() prüft es weiterhin (Leitung 2), +es ist nur nichts mehr zu konfigurieren. Wichtig: Host ist die LAN-IP der Box (NICHT eine Proxy-Domain) — das war in v1 die häufigste Fehlerquelle. Der Aufrufer übergibt den Host explizit. @@ -40,9 +46,7 @@ def _gw(host: str) -> str: return f"http://{host}:{PORT}/v1" -def build_snippets(host: str = DEFAULT_HOST, - mcp_script_path: str = r"F:\\Coding Stuff\\mission-control-2\\mcp\\mcp_memory.py", - mcp_python: str = "python") -> dict: +def build_snippets(host: str = DEFAULT_HOST) -> dict: gw = _gw(host) mc_url = f"http://{host}:{PORT}" @@ -88,16 +92,6 @@ def build_snippets(host: str = DEFAULT_HOST, f'export ANTHROPIC_MODEL="coder"' ) - memory_mcp = json.dumps({ - "mcpServers": { - "mission-control-memory": { - "command": mcp_python, - "args": [mcp_script_path], - "env": {"MC_URL": mc_url}, - } - } - }, indent=2) - return { "host": host, "gateway_url": gw, @@ -116,11 +110,8 @@ def build_snippets(host: str = DEFAULT_HOST, "API-Profile je Modus: Code→coder · Architect/Orchestrator→heavy · " "Ask/Debug→Lane 'chat' (virtuelles Modell, wählt selbst fast oder heavy)."}, "claude_code": {"label": "Claude Code", "lang": "bash", "snippet": claude_code, - "note": "Für die starken Sessions. Lokal-Betrieb bräuchte einen Anthropic⇄OpenAI-Übersetzer vor dem Gateway; Gedächtnis-Anbindung via Memory-MCP unten."}, + "note": "Für die starken Sessions. Lokal-Betrieb bräuchte einen Anthropic⇄OpenAI-Übersetzer vor dem Gateway."}, }, - # Leitung 2 — das GEDÄCHTNIS. Separater MCP-Server, gilt zusätzlich zu jedem Tool oben. - "memory": {"label": "Shared Memory (MCP)", "lang": "json", "snippet": memory_mcp, - "note": "Eigene Leitung: MCP-Block für jedes MCP-fähige Tool. mcp_memory.py muss lokal liegen."}, } diff --git a/backend/services/sentry.py b/backend/services/sentry.py index 2b01be8..01945c6 100644 --- a/backend/services/sentry.py +++ b/backend/services/sentry.py @@ -1,7 +1,7 @@ """ Health-Wächter der Box (Lucy-Proaktivität, Faden A3). -Prüft periodisch die Kern-Dienste (Engine, Agent-Hirn, Hermes-Gateway, Mem0, +Prüft periodisch die Kern-Dienste (Engine, Agent-Hirn, Hermes-Gateway, Voice-Sidecar, Platte) und meldet ZUSTANDSWECHSEL in den Melde-Briefkasten (services/announce.py → Lucy spricht es) und via notify.sh (Telegram). diff --git a/backend/services/voice_metrics.py b/backend/services/voice_metrics.py index e31433c..76f9b72 100644 --- a/backend/services/voice_metrics.py +++ b/backend/services/voice_metrics.py @@ -11,14 +11,14 @@ Zwei Sichten auf dieselben Messungen: **Was MC2 messen kann — und was nicht:** MC2 proxyt den Chat nur an Hermes (:8642). Die Stufen STT, Vision, Hirn-TTFT (Zeit bis zum ersten Inhalts-Token) und Generierung sind hier direkt messbar. Der -**Mem0-Retrieve** läuft zwar in Hermes, ruft aber MC2s `/api/memory` per HTTP zurück → messbar und als -Unter-Detail INNERHALB der Hirn-Zeit ausgewiesen (kein Doppelzählen). Die **Tool-Runden** dagegen laufen -im Hermes-LLM-Loop ohne Callback an MC2 → für MC2 unsichtbar, sie stecken im „Generierung"-Bucket. +**Gedächtnis-Abruf** dagegen läuft seit der Ablösung des Sidecars (07.08.2026) Hermes-intern — es +gibt keinen Rückruf an MC2 mehr, also auch keine Messung; er steckt jetzt in der Hirn-Zeit. Ebenso die +**Tool-Runden**: im Hermes-LLM-Loop ohne Callback an MC2 → unsichtbar, im „Generierung"-Bucket. -STT (davor) und Mem0-Retrieve (währenddessen) sind separate HTTP-Requests ohne Turn-ID. Auf einem -EIN-Nutzer-Gerät genügt eine schlanke Best-Effort-Korrelation: die zuletzt gemessene STT-Dauer bzw. der -letzte Retrieve werden global „geparkt" und vom nächsten Chat-Turn eingesammelt (mit Frist-/Reihenfolge- -Check). Kein Turn-ID-Durchreichen durch den Lucy-Client nötig. +STT läuft als eigener HTTP-Request VOR dem Turn, ohne Turn-ID. Auf einem EIN-Nutzer-Gerät genügt eine +schlanke Best-Effort-Korrelation: die zuletzt gemessene STT-Dauer wird global „geparkt" und vom +nächsten Chat-Turn eingesammelt (mit Frist-Check). Kein Turn-ID-Durchreichen durch den Lucy-Client +nötig. In-Memory + thread-safe (keine Datei-I/O — Latenz-Telemetrie ist transient, Restart = Reset). """ @@ -34,11 +34,11 @@ _STAGES: dict[str, deque] = {} _TURNS: deque = deque(maxlen=60) # letzte N vollständige Chat-Turns (Per-Turn-Trace) # Bekannte Stufen (für stabile UI-Reihenfolge); unbekannte werden trotzdem erfasst. -STAGES = ("stt", "vision", "memory_retrieve", "chat_ttfb", "chat_first_content", "tts") +STAGES = ("stt", "vision", "chat_ttfb", "chat_first_content", "tts") -# Best-effort-Korrelation (Ein-Nutzer-Gerät): zuletzt gemessene STT-Dauer / Mem0-Retrieve, je -# (ms, perf_counter-Zeitstempel). Der nächste passende Chat-Turn sammelt sie ein und leert sie. -_PARKED: dict[str, tuple[float, float] | None] = {"stt": None, "retrieve": None} +# Best-effort-Korrelation (Ein-Nutzer-Gerät): zuletzt gemessene STT-Dauer als +# (ms, perf_counter-Zeitstempel). Der nächste Chat-Turn sammelt sie ein und leert sie. +_PARKED: dict[str, tuple[float, float] | None] = {"stt": None} def record_stage(stage: str, ms: float) -> None: @@ -53,8 +53,8 @@ def record_stage(stage: str, ms: float) -> None: def park(kind: str, ms: float) -> None: - """Eine Messung, die NICHT im Chat-Request selbst passiert (STT davor, Mem0-Retrieve als - Rückruf während), global parken, damit der nächste Chat-Turn sie einsammeln kann.""" + """Eine Messung, die NICHT im Chat-Request selbst passiert (STT läuft davor), global parken, + damit der nächste Chat-Turn sie einsammeln kann.""" if ms is None or ms < 0 or kind not in _PARKED: return with _LOCK: @@ -71,17 +71,6 @@ def _take_stt(max_age: float = 20.0) -> float | None: return None -def _take_retrieve(since_perf: float, max_age: float = 90.0) -> float | None: - """Geparkten Mem0-Retrieve einsammeln, wenn er NACH dem Turn-Start kam (Rückruf während des - Turns) und frisch ist.""" - with _LOCK: - v = _PARKED.get("retrieve") - if v and v[1] >= since_perf and (time.perf_counter() - v[1]) <= max_age: - _PARKED["retrieve"] = None - return round(v[0], 1) - return None - - class Timer: """Context-Manager: misst die verstrichene Zeit und verbucht sie auf `stage`. Funktioniert um `await`-Aufrufe herum (enter → await → exit).""" @@ -102,8 +91,7 @@ class TurnTrace: """Ein Per-Turn-Trace für den Voice/Lucy-Chatpfad. In `voice.py` über die Dauer eines Chat-Turns gehalten; `commit()` schreibt den Datensatz in den Ringpuffer UND speist die rollenden Stats. - Balken-Stufen (zeitlich DISJUNKT, ergeben zusammen den Turn): stt · vision · hirn · gen. - Unter-Detail: mem0 (Teil VON hirn, wird separat ausgewiesen, aber NICHT zum Balken addiert).""" + Balken-Stufen (zeitlich DISJUNKT, ergeben zusammen den Turn): stt · vision · hirn · gen.""" def __init__(self, session_id: str = "", kind: str = "voice") -> None: self.id = uuid.uuid4().hex[:8] @@ -113,7 +101,7 @@ class TurnTrace: self.session_id = (session_id or "")[:24] self.kind = kind self.vision_ms: float | None = None # Bildschirm-Beschreibung (falls Bilder) - self.hirn_ms: float | None = None # Zeit bis zum ersten Inhalts-Token (Agent + Mem0 + TTFT) + self.hirn_ms: float | None = None # Zeit bis zum ersten Inhalts-Token (Agent + Gedächtnis + TTFT) self.had_images = False self.error: str | None = None @@ -130,7 +118,7 @@ class TurnTrace: record_stage("chat_ttfb", (time.perf_counter() - self._brain0) * 1000.0) # SSE-Start (~5 ms), nur rollend def note_first_content(self) -> None: - """Erster Inhalts-Delta = echte Hirn-Latenz (Agent-Overhead + Mem0 + LLM-TTFT).""" + """Erster Inhalts-Delta = echte Hirn-Latenz (Agent-Overhead + Gedächtnis + LLM-TTFT).""" ms = (time.perf_counter() - self._brain0) * 1000.0 self.hirn_ms = round(ms, 1) record_stage("chat_first_content", ms) @@ -138,7 +126,6 @@ class TurnTrace: def commit(self) -> dict: total = (time.perf_counter() - self.perf0) * 1000.0 stt = _take_stt() # rollend bereits in /voice/stt erfasst - mem0 = _take_retrieve(self.perf0) # rollend bereits in /api/memory erfasst # Generierung = alles nach dem ersten Inhalts-Token bis Stream-Ende. gen = round(total - self.hirn_ms, 1) if self.hirn_ms is not None else None rec = { @@ -151,7 +138,6 @@ class TurnTrace: "vision_ms": self.vision_ms, "hirn_ms": self.hirn_ms, "gen_ms": gen if (gen is None or gen >= 0) else 0.0, - "mem0_ms": mem0, "total_ms": round(total, 1), "error": self.error, } diff --git a/backend/steward.py b/backend/steward.py index b77ab76..134c5fa 100644 --- a/backend/steward.py +++ b/backend/steward.py @@ -1,7 +1,7 @@ """ MC2-Steward — die Wächter-Loops als EIGENER Prozess (UMBAU v3, P2). -Bisher hingen Re-Warm-Wächter, Health-Wächter (sentry) und Mem0-Auto-Dedupe am +Bisher hingen Re-Warm-Wächter und Health-Wächter (sentry) am Lebenszyklus des Steuerpult-Webservers (app.py-Lifespan): jeder MC2-Neustart riss den Wächtern Timing und Flanken-Gedächtnis weg — und ein TOTES Steuerpult konnte sich prinzipbedingt nicht selbst melden. Hier laufen DIESELBEN Loops (unveränderte @@ -11,14 +11,16 @@ Module) als eigener Mini-Dienst (mc2-steward.service, Restart=always): In-Process-Nudge aus llamaswap.write_config) • sentry.sentry_loop — Health-Flanken → Briefkasten (HTTP an MC2) + Telegram; beobachtet im Steward-Modus AUCH MC2 selbst + mc2-gateway - • memory.auto_dedupe_loop — Gedächtnis-Dubletten (HTTP an den Mem0-Sidecar) + +Das dritte Loop (Gedächtnis-Dubletten gegen den Sidecar auf :8765) ist mit dessen Ablösung +am 07.08.2026 entfallen — Hermes führt sein Gedächtnis selbst (docs/wissen/VERDIKTE.md). BEWUSST NICHT hier: reminders_loop — der teilt sich Datei UND CRUD-Pfade mit dem /api/reminders-Router (Zwei-Schreiber-Risiko auf mc2-reminders.json); er bleibt im Steuerpult. Der Briefkasten-Store gehört weiter EXKLUSIV dem MC2-Prozess — dieser Prozess liefert Meldungen per HTTP ab (announce.py, MC_ANNOUNCE_HTTP). -Die Loop-Schalter (MC_REWARM_ENABLED / MC_SENTRY_ENABLED / MC_MEM_DEDUPE_ENABLED) +Die Loop-Schalter (MC_REWARM_ENABLED / MC_SENTRY_ENABLED) stehen in der MC2-Unit auf 0 und hier auf Default 1 — reiner Konfig-Split, kein Verhaltens-Code im Steuerpult angefasst. Zeilen dort entfernen = Rollback. """ @@ -28,7 +30,6 @@ import logging import os from config import CONFIG_PATH -from services import memory as memory_svc from services import sentry, warmer logging.basicConfig( @@ -66,10 +67,6 @@ async def main() -> None: warmer.INTERVAL, CONFIG_WATCH_S) if sentry.ENABLED: tasks.append(asyncio.create_task(sentry.sentry_loop())) - if memory_svc.AUTO_DEDUPE_ENABLED: - tasks.append(asyncio.create_task(memory_svc.auto_dedupe_loop())) - log.info("Mem0-Auto-Dedupe aktiv (alle %ss, Schwelle %s)", - memory_svc.AUTO_DEDUPE_INTERVAL, memory_svc.AUTO_DEDUPE_THRESHOLD) if not tasks: log.warning("steward: alle Loops per Env deaktiviert — nichts zu tun, Ende.") return diff --git a/deploy/agent-hooks/box-steckbrief-inject.sh b/deploy/agent-hooks/box-steckbrief-inject.sh index 7b02758..dc14b0f 100644 --- a/deploy/agent-hooks/box-steckbrief-inject.sh +++ b/deploy/agent-hooks/box-steckbrief-inject.sh @@ -28,7 +28,7 @@ hint="" # Stabile Anti-Flail-Orientierung: WER bin ich, WO laufen die Modelle, WAS ist tabu. ctx="$(cat <.tar.gz, behält die letzten N. # Läuft per systemd-Timer (täglich), manuell, oder über den UI-Snapshot-Button. # -# Inhalt: mem0 (Chroma + history.db) · ~/.hermes (config.yaml, .env, plugins/) · -# /etc/llama-swap/config.yaml · known-good/ (Versions-Manifest, s. u.) +# Inhalt: ~/.hermes (config.yaml, .env, plugins/) · /etc/llama-swap/config.yaml · +# known-good/ (Versions-Manifest, s. u.) +# Das abgeloeste Gedaechtnis-Sidecar (/srv/models, Port 8765) faellt seit 27.08.2026 weg — +# sein Datenverzeichnis existiert nicht mehr (Hintergrund: docs/wissen/VERDIKTE.md). # NICHT enthalten (bewusst): GGUF-Modelle (riesig, neu ladbar), MC2-Code (Git), venvs. # # ACHTUNG: das Tarball enthält ~/.hermes/.env (Secrets) → chmod 600, nicht in Git. @@ -20,16 +22,14 @@ RETAIN="${MC_BACKUP_RETAIN:-14}" # Off-Box-Ziel (leer = deaktiviert). Default: Proxmox-Host, eigener Key mit minimalem Recht. OFFSITE="${MC_BACKUP_OFFSITE:-root@192.168.178.108:/var/lib/vz/mc2-backups}" OFFSITE_KEY="${MC_BACKUP_OFFSITE_KEY:-$HOME/.ssh/mc2_offsite}" -MEM0_DIR="${MC_MEM0_DIR:-/srv/models/mem0}" LSWAP="${MC_CONFIG_PATH:-/etc/llama-swap/config.yaml}" HERMES="${HERMES_HOME:-$HOME/.hermes}" TS="$(date +%Y%m%d-%H%M%S)" STAGE="$(mktemp -d)" trap 'rm -rf "$STAGE"' EXIT -mkdir -p "$STAGE/mem0" "$STAGE/hermes" "$STAGE/llama-swap" +mkdir -p "$STAGE/hermes" "$STAGE/llama-swap" -[ -d "$MEM0_DIR" ] && cp -a "$MEM0_DIR/." "$STAGE/mem0/" || true [ -f "$HERMES/config.yaml" ] && cp -a "$HERMES/config.yaml" "$STAGE/hermes/" || true [ -f "$HERMES/.env" ] && cp -a "$HERMES/.env" "$STAGE/hermes/" || true [ -d "$HERMES/plugins" ] && cp -a "$HERMES/plugins" "$STAGE/hermes/plugins" || true @@ -60,7 +60,7 @@ SRC="${MC2_SRC:-$HOME/mission-control-v2}" HERMES_AGENT="${HERMES_AGENT_DIR:-$HOME/.hermes/hermes-agent}" UV="$(command -v uv || echo "$HOME/.local/bin/uv")" -# pip freeze je venv; mem0-venv ist uv-managed (kein pip-Modul) → uv als Fallback. +# pip freeze je venv; das voice-venv ist uv-managed (kein pip-Modul) → uv als Fallback. freeze_venv() { # $1 = python-Pfad, $2 = Zieldatei if [ ! -x "$1" ]; then echo "venv fehlt: $1" > "$2"; return 0; fi "$1" -m pip freeze > "$2" 2>/dev/null \ @@ -68,7 +68,6 @@ freeze_venv() { # $1 = python-Pfad, $2 = Zieldatei || echo "pip freeze fehlgeschlagen: $1" > "$2" } freeze_venv "$SRC/backend/.venv/bin/python" "$KG/pip-backend.txt" -freeze_venv "$HOME/.mem0/venv/bin/python" "$KG/pip-mem0.txt" freeze_venv "$HOME/.voice/venv/bin/python" "$KG/pip-voice.txt" { @@ -79,7 +78,7 @@ freeze_venv "$HOME/.voice/venv/bin/python" "$KG/pip-voice.txt" echo "llama.cpp : $(LD_LIBRARY_PATH=/opt/llamacpp-vulkan /usr/local/bin/llama-server --version 2>&1 | grep -m1 -o 'version: .*' || echo '?')" echo "llama-swap : $(/usr/local/bin/llama-swap --version 2>/dev/null | head -1 || echo '?')" echo "python-venvs :" - for P in "$SRC/backend/.venv/bin/python" "$HOME/.mem0/venv/bin/python" "$HOME/.voice/venv/bin/python"; do + for P in "$SRC/backend/.venv/bin/python" "$HOME/.voice/venv/bin/python"; do echo " $P → $("$P" --version 2>&1 || echo 'fehlt')" done } > "$KG/versions.txt" || true @@ -92,7 +91,7 @@ cat > "$STAGE/MANIFEST.txt" < Repo-Abzug):" + diff -u /etc/llama-swap/config.yaml deploy/llama-swap.config.yaml | head -40 || true + echo " Sichere die laufende Datei nach $SWAP_BAK" + # NOPASSWD für llama-swap Neustart ist vorausgesetzt (siehe AGENTS.md) + sudo cp /etc/llama-swap/config.yaml "$SWAP_BAK" + sudo cp deploy/llama-swap.config.yaml /etc/llama-swap/config.yaml + sudo systemctl restart llama-swap + echo " Rueckweg bei Verlust: sudo cp $SWAP_BAK /etc/llama-swap/config.yaml" + fi fi # 4. Systemd Units neu laden (falls sich .service Dateien geändert haben) @@ -35,7 +54,11 @@ for skill_dir in deploy/skills/*; do done # 5. Dienste neu starten +# ‼️ mc2-steward gehoert hier dazu: er laeuft aus DEMSELBEN Checkout (backend/steward.py). +# Ohne ihn lief der Waechter-Prozess nach jedem Deploy mit dem alten Code weiter — der +# Neustart wurde 27.08.2026 nachgetragen. `--user restart` auf einer nicht installierten +# Unit ist folgenlos, darum ohne Vorabpruefung. echo "Starte Backend neu..." -systemctl --user restart mc2-gateway.service mission-control-2.service +systemctl --user restart mc2-gateway.service mission-control-2.service mc2-steward.service echo "✅ Deployment erfolgreich abgeschlossen!" diff --git a/deploy/hermes-postcheck.sh b/deploy/hermes-postcheck.sh index 14e9117..09a8e8f 100644 --- a/deploy/hermes-postcheck.sh +++ b/deploy/hermes-postcheck.sh @@ -1,35 +1,22 @@ #!/usr/bin/env bash -# Post-Update-Check nach einem Hermes-Agent-Update: läuft unser geteiltes „Gehirn" -# (Mem0 + die mc2-memory-Integration) noch? Exit 0 = alles ok, sonst 1 → der Job wird -# im UI rot, damit ein kaputtes Gehirn sofort auffällt. +# Post-Update-Check nach einem Hermes-Agent-Update: laeuft unser "Gehirn" noch? +# Exit 0 = alles ok, sonst 1 -> der Job wird im UI rot, damit ein kaputtes Gehirn auffaellt. +# +# WICHTIG (27.08.2026) - VIER TOTE CHECKS ENTFERNT: bis hierher prueften die ersten Bloecke +# den abgeloesten Gedaechtnis-Sidecar (:8765), MC2s /api/memory und das zugehoerige +# Hermes-Plugin. Alle drei fielen am 07.08. weg (docs/wissen/VERDIKTE.md) - die Checks KONNTEN nicht +# mehr gruen werden. Folge: jedes Hermes-Update endete rot und wurde von autoupdate.sh +# zurueckgerollt. Kein Ersatz-Check auf Hermes native Gedaechtnis, weil es dafuer keinen +# nachgemessenen Endpunkt gibt - geraten waere eine Fassade. Der Tool-Smoke weiter unten +# laeuft ohnehin durch den ECHTEN Agenten und faengt ein kaputtes Gehirn. set -uo pipefail MC_URL="${MC_URL:-http://127.0.0.1:9001}" -MEM0_URL="${MEM0_SERVICE_URL:-http://127.0.0.1:8765}" HERMES="${HERMES_HOME:-$HOME/.hermes}" fail=0 echo "=== Hermes Post-Update: Gehirn-Check ===" -if curl -sf -m 5 "$MEM0_URL/health" >/dev/null 2>&1; then - echo "PASS · Mem0-Sidecar erreichbar" -else - echo "FAIL · Mem0-Sidecar NICHT erreichbar"; fail=1 -fi - -if curl -sf -m 8 "$MC_URL/api/memory" >/dev/null 2>&1; then - echo "PASS · /api/memory antwortet" -else - echo "FAIL · /api/memory antwortet nicht"; fail=1 -fi - -if grep -qE "^[[:space:]]*provider:[[:space:]]*'?mc2-memory'?" "$HERMES/config.yaml" 2>/dev/null \ - && grep -qE "memory_enabled:[[:space:]]*true" "$HERMES/config.yaml" 2>/dev/null; then - echo "PASS · memory.provider=mc2-memory aktiv" -else - echo "FAIL · memory.provider nicht mehr gesetzt (Config vom Update überschrieben?)"; fail=1 -fi - # --- Hermes-Runtime-Patch-Traeger (20.07.2026): ein Update setzt den Quellbaum --- # --- zurueck → unsere Fixes (needs_input-wartet, Startreife-Gate, Orphan-Guard, --- # --- Kontext-Vererbung, Etappen-Kette) hier RE-eintragen. Exit 10 = etwas neu --- @@ -49,14 +36,6 @@ else echo "WARN · hermes-patches/apply.py nicht gefunden ($PATCH_APPLY)" fi -if ( cd "$HERMES/hermes-agent" && HERMES_HOME="$HERMES" ./venv/bin/python -c \ - "import sys; sys.path.insert(0,'.'); from plugins.memory import load_memory_provider; p=load_memory_provider('mc2-memory'); assert p and p.name()=='mc2-memory'" \ - >/dev/null 2>&1 ); then - echo "PASS · mc2-memory-Plugin lädt unter dem neuen Hermes" -else - echo "FAIL · mc2-memory-Plugin lädt nicht (MemoryProvider-ABC geändert?)"; fail=1 -fi - # --- Config-Drift-Wächter (Lehre aus v0.18, 02.07.2026): Hermes fällt bei unbekannten --- # --- Config-Werten STILL auf Defaults zurück (approvals.mode 'auto' -> manual -> alle --- # --- Tools hingen in pending_approval). Solche Warnungen müssen den Job ROT machen. --- diff --git a/deploy/llama-swap.config.yaml b/deploy/llama-swap.config.yaml index b8c9ccc..d9b2422 100644 --- a/deploy/llama-swap.config.yaml +++ b/deploy/llama-swap.config.yaml @@ -4,7 +4,7 @@ globalTTL: 0 models: Qwen3.6-35B-A3B: - # parallel 2 + c 131072: 2 Slots à 65k (Slot 2 = Mem0-Lern-Extraktion, blockiert Voice-Turns + # parallel 2 + c 131072: 2 Slots à 65k (Slot 2 = Nebenlast/Hintergrund-Extraktion, blockiert Voice-Turns # nicht mehr); KV Q8_0 macht das speicherneutral zu vorher (65k f16). Bench 2026-07-02: # Q8_0 kostet 0 t/s, MTP n-max 3 = +26% vs. ohne Spec. (Q4_K-KV stand mal im Template, # lief aber NIE live — bewusst bei Q8_0 geblieben: Qualität vor ein paar GB, seit der @@ -78,7 +78,7 @@ models: out: [text] context: 32768 Qwen3-Reranker-0.6B: - # Gedächtnis-Zweitstufe (07.07., Rollen-Audit): ordnet Mem0-Suchtreffer nach echter + # Gedächtnis-Zweitstufe (07.07., Rollen-Audit): ordnet Gedächtnis-Suchtreffer nach echter # Relevanz (/v1/rerank, Mungert-GGUF — Community-Konvertierungen liefern oft Nullscores!). # Winzig (~0,7 GB) → in brains (verdrängungssicher); lädt in ~1-2 s, erste Anfrage wärmt. cmd: | diff --git a/deploy/mc2-backup.service b/deploy/mc2-backup.service index d82d5cd..18eedff 100644 --- a/deploy/mc2-backup.service +++ b/deploy/mc2-backup.service @@ -1,5 +1,5 @@ [Unit] -Description=MC2 Zustands-Backup (mem0 + Hermes-Configs/Secrets + llama-swap config) +Description=MC2 Zustands-Backup (Hermes-Configs/Secrets + llama-swap config) Documentation=file:%h/mission-control-v2/docs/BACKUP.md [Service] diff --git a/deploy/mc2-steward.service b/deploy/mc2-steward.service new file mode 100644 index 0000000..02a25a7 --- /dev/null +++ b/deploy/mc2-steward.service @@ -0,0 +1,37 @@ +# systemd-USER-Unit für den MC2-Steward — die Wächter-Loops als eigener Prozess (UMBAU v3 P2). +# Re-Warm-Wächter und Health-Sentry überleben damit jeden Steuerpult-Neustart, und der Sentry +# kann auch das Steuerpult SELBST + den mc2-gateway überwachen (MC_SENTRY_WATCH_MC2=1). +# Meldungen gehen per HTTP in den MC2-Briefkasten (MC_ANNOUNCE_HTTP); ist MC2 down, greift +# weiterhin der Telegram-Direktweg (notify.sh). +# Sudo-frei wie alle MC2-Units: ~/.config/systemd/user/ + systemctl --user. +# +# ‼️ NACHGETRAGEN 27.08.2026: Diese Unit lief auf der Box, fehlte aber im Repo — sie war weder +# versioniert noch vom Disaster-Recovery abgedeckt, obwohl backend/routers/system.py, +# services/maintenance.py (USER_SERVICES) und deploy/stack-postcheck.sh sie voraussetzen. +# Inhalt 1:1 von der laufenden Box übernommen (`systemctl --user cat mc2-steward`), nur die +# Description um den entfallenen Mem0-Dedupe-Loop gekürzt. Das Warm-Set-Drop-in liegt +# daneben in mc2-steward.service.d-warmset.conf — beim Ausrollen mitnehmen. +# +# Ablage: ~/.config/systemd/user/mc2-steward.service ; dann: +# systemctl --user daemon-reload && systemctl --user enable --now mc2-steward + +[Unit] +Description=MC2 Steward (Wächter: Re-Warm, Health-Sentry) +After=network-online.target +Wants=network-online.target + +[Service] +Type=simple +WorkingDirectory=%h/mission-control-v2/backend +ExecStart=%h/mission-control-v2/backend/.venv/bin/python steward.py +Environment=PYTHONPATH=%h/mission-control-v2 +Environment=MC_LLAMA_SWAP_URL=http://127.0.0.1:8080 +Environment=MC_CONFIG_PATH=/etc/llama-swap/config.yaml +Environment=MC_MODELS_DIR=/srv/models +Environment=MC_ANNOUNCE_HTTP=http://127.0.0.1:9001 +Environment=MC_SENTRY_WATCH_MC2=1 +Restart=always +RestartSec=3 + +[Install] +WantedBy=default.target diff --git a/deploy/mc2-steward.service.d-warmset.conf b/deploy/mc2-steward.service.d-warmset.conf new file mode 100644 index 0000000..920fb25 --- /dev/null +++ b/deploy/mc2-steward.service.d-warmset.conf @@ -0,0 +1,11 @@ +# Drop-in für mc2-steward.service — Ablage auf der Box: +# ~/.config/systemd/user/mc2-steward.service.d/warmset.conf +# +# 26.07.2026 — Ko-Residenz ist nicht Warm-Pflicht. Die Gruppe `brains` enthaelt seit dem +# Umbau auch Modelle MIT TTL (Coder 90 min, Kritiker 30 min); ohne diese Liste hielte der +# Waechter sie faelschlich fuer dauerhaft faellig und arbeitete gegen die TTLs. +# ANFUEHRUNGSZEICHEN SIND PFLICHT: systemd trennt Environment= an Leerzeichen, ohne sie +# kommt nur das erste Modell an (live erlebt) — das Warm-Ziel waere still zu klein. +[Service] +Environment="MC_WARMSET=Qwen3-Embedding-0.6B Qwen3-Reranker-0.6B Qwen3.6-35B-A3B" +Environment=MC_WARMUP_RERANK=reranker diff --git a/deploy/mission-control-2.service b/deploy/mission-control-2.service index 15c8f90..ae33c78 100644 --- a/deploy/mission-control-2.service +++ b/deploy/mission-control-2.service @@ -19,19 +19,16 @@ Environment=MC_PORT=9001 Environment=MC_LLAMA_SWAP_URL=http://127.0.0.1:8080 Environment=MC_CONFIG_PATH=/etc/llama-swap/config.yaml Environment=MC_MODELS_DIR=/srv/models -# Geteiltes Gedächtnis = die bestehende v1-DB (Kontinuität bis/über Cutover). -Environment=MC_MEMORY_DB=/srv/models/mission-control-memory.db # Gateway-Auszug (UMBAU v3 P1): /v1 roh an den eigenständigen mc2-gateway-Prozess # durchreichen. Diese Zeile entfernen (+ daemon-reload + restart) = Rollback, MC2 # bedient /v1 wieder selbst. Environment=MC_V1_UPSTREAM=http://127.0.0.1:9010 -# Steward-Auszug (UMBAU v3 P2): Die Wächter-Loops (Re-Warm, Health-Sentry, Mem0-Dedupe) -# laufen jetzt im eigenen Dienst mc2-steward.service — hier deshalb AUS. Diese drei -# Zeilen entfernen (+ daemon-reload + restart) = Rollback (Loops wieder im Steuerpult). +# Steward-Auszug (UMBAU v3 P2): Die Wächter-Loops (Re-Warm, Health-Sentry) laufen jetzt im +# eigenen Dienst mc2-steward.service — hier deshalb AUS. Diese zwei Zeilen entfernen +# (+ daemon-reload + restart) = Rollback (Loops wieder im Steuerpult). # Der reminders_loop bleibt bewusst HIER (teilt Datei+CRUD mit /api/reminders). Environment=MC_REWARM_ENABLED=0 Environment=MC_SENTRY_ENABLED=0 -Environment=MC_MEM_DEDUPE_ENABLED=0 # KEIN MC_ENGINE_UPDATE_CMD-Override mehr: Das alte /usr/local/bin/update-llamacpp zog den # ROCm-Build nach /opt/llamacpp (totes Rollback-Dir) statt des aktiven Vulkan-Builds → Updates # liefen ins Leere ("DONE", aber nichts passierte). Ohne Override nutzt das Backend den Default diff --git a/deploy/restore.sh b/deploy/restore.sh index 7a839a5..2502f40 100644 --- a/deploy/restore.sh +++ b/deploy/restore.sh @@ -15,11 +15,13 @@ set -euo pipefail MODELS_DIR="${MC_MODELS_DIR:-/srv/models}" DEST_DIR="$MODELS_DIR/mc2-backups" -MEM0_DIR="${MC_MEM0_DIR:-/srv/models/mem0}" LSWAP="${MC_CONFIG_PATH:-/etc/llama-swap/config.yaml}" HERMES="${HERMES_HOME:-$HOME/.hermes}" SRC="${MC2_SRC:-$HOME/mission-control-v2}" -SERVICES="mem0-service mission-control-2 hermes-gateway" +# Alle User-Dienste, die von wiederhergestellter Config abhaengen. mc2-gateway (der +# /v1-Denkpfad) und mc2-steward (Waechter) fehlten hier bis 27.08.2026 — nach einem +# Restore liefen beide mit der ALTEN llama-swap-/Hermes-Config weiter. +SERVICES="mission-control-2 mc2-gateway mc2-steward hermes-gateway" OFFSITE="${MC_BACKUP_OFFSITE:-root@192.168.178.108:/var/lib/vz/mc2-backups}" OFFSITE_KEY="${MC_BACKUP_OFFSITE_KEY:-$HOME/.ssh/mc2_offsite}" OFFSITE_SSH="ssh -i $OFFSITE_KEY -o BatchMode=yes -o ConnectTimeout=10 -o StrictHostKeyChecking=accept-new" @@ -98,7 +100,6 @@ echo "--- Inhalt ---"; cat "$STAGE/MANIFEST.txt" 2>/dev/null || true; echo "---- if [ "$DRY" = 1 ]; then echo "[dry-run] würde zurücksetzen:" - [ -d "$STAGE/mem0" ] && echo " • mem0 → $MEM0_DIR (wird ersetzt)" [ -f "$STAGE/hermes/config.yaml" ] && echo " • $HERMES/config.yaml" [ -f "$STAGE/hermes/.env" ] && echo " • $HERMES/.env" [ -d "$STAGE/hermes/plugins" ] && echo " • $HERMES/plugins/" @@ -119,7 +120,8 @@ bash "$SRC/deploy/backup.sh" || echo " (Pre-Restore-Backup fehlgeschlagen — f echo "→ Dienste stoppen…" systemctl --user stop $SERVICES 2>/dev/null || true -if [ -d "$STAGE/mem0" ]; then rm -rf "$MEM0_DIR"; mkdir -p "$MEM0_DIR"; cp -a "$STAGE/mem0/." "$MEM0_DIR/"; fi +# Alte Snapshots (vor 27.08.2026) tragen noch ein Gedaechtnis-Verzeichnis mit — es wird +# bewusst NICHT mehr zurueckgespielt, der zugehoerige Dienst existiert nicht mehr. [ -f "$STAGE/hermes/config.yaml" ] && { mkdir -p "$HERMES"; cp -a "$STAGE/hermes/config.yaml" "$HERMES/"; } [ -f "$STAGE/hermes/.env" ] && cp -a "$STAGE/hermes/.env" "$HERMES/" [ -d "$STAGE/hermes/plugins" ] && { mkdir -p "$HERMES/plugins"; cp -a "$STAGE/hermes/plugins/." "$HERMES/plugins/"; } diff --git a/deploy/stack-postcheck.sh b/deploy/stack-postcheck.sh index 1d675e1..b5105d7 100644 --- a/deploy/stack-postcheck.sh +++ b/deploy/stack-postcheck.sh @@ -3,15 +3,14 @@ # dass der komplette Inferenz-Stack noch FUNKTIONIERT — nicht nur "Befehl lief durch". # Exit 0 = alles ok, sonst 1 → der jobengine-Job wird im UI ROT (state=failed). # -# Pendant zu hermes-postcheck.sh (prüft das Gehirn/Mem0); dieser prüft Router+Engine+MC2 +# Pendant zu hermes-postcheck.sh (prüft das Gehirn); dieser prüft Router+Engine+MC2 # inkl. einer ECHTEN 1-Token-Inferenz (beweist, dass ein Modell wirklich lädt & generiert). set -uo pipefail SWAP_URL="${MC_LLAMA_SWAP_URL:-http://127.0.0.1:8080}" MC_URL="${MC_URL:-http://127.0.0.1:9001}" -MEM0_URL="${MEM0_SERVICE_URL:-http://127.0.0.1:8765}" BRAIN="${MC_WARMUP_MODELS:-fast}"; BRAIN="${BRAIN%% *}" # erstes Modell, falls Liste -EMBED="${MC_WARMUP_EMBED:-embed}"; EMBED="${EMBED%% *}" # Embedding-Modell (Mem0/Gedächtnis) +EMBED="${MC_WARMUP_EMBED:-embed}"; EMBED="${EMBED%% *}" # Embedding-Modell (Reranker-Stufe) fail=0 echo "=== Stack Post-Update: Funktionsprüfung ===" @@ -48,14 +47,14 @@ else echo "FAIL · Inferenz auf '$BRAIN' fehlgeschlagen (Modell lädt/generiert nicht)"; fail=1 fi -# 3b. Embedding-Modell (für Mem0/Gedächtnis) lädt und liefert einen Vektor? +# 3b. Embedding-Modell lädt und liefert einen Vektor? eresp="$(curl -s -m 120 -X POST "$SWAP_URL/v1/embeddings" \ -H 'Content-Type: application/json' \ -d "{\"model\":\"$EMBED\",\"input\":\"ping\"}" 2>/dev/null)" if printf '%s' "$eresp" | grep -q '"embedding"'; then echo "PASS · Embedding-Modell '$EMBED' liefert Vektoren" else - echo "FAIL · Embedding-Modell '$EMBED' lädt/antwortet nicht (Mem0/Gedächtnis betroffen)"; fail=1 + echo "FAIL · Embedding-Modell '$EMBED' lädt/antwortet nicht"; fail=1 fi # 4. MC2 selbst gesund (Engine + Gateway erreichbar)? @@ -85,12 +84,8 @@ if systemctl --user is-enabled --quiet mc2-steward 2>/dev/null; then fi fi -# 5. Mem0-Sidecar (Gedächtnis) erreichbar? -if curl -sf -m 5 "$MEM0_URL/health" >/dev/null 2>&1; then - echo "PASS · Mem0-Sidecar erreichbar" -else - echo "FAIL · Mem0-Sidecar NICHT erreichbar"; fail=1 -fi +# (Schritt 5 „Gedächtnis-Sidecar erreichbar" entfiel am 27.08.2026: der Dienst auf :8765 ist +# seit der Ablösung im August tot, der Check konnte nur noch rot werden. docs/wissen/VERDIKTE.md) if [ "$fail" -eq 0 ]; then echo "=== STACK OK ✓ ===" diff --git a/deploy/venv-audit.sh b/deploy/venv-audit.sh index da484c6..45f81d6 100644 --- a/deploy/venv-audit.sh +++ b/deploy/venv-audit.sh @@ -1,5 +1,5 @@ #!/usr/bin/env bash -# Venv-Audit (monatlich, 17.07.2026): die Python-Nebendienste (Mem0, Voice) altern +# Venv-Audit (monatlich, 17.07.2026): die Python-Nebendienste (Voice) altern # eingefroren — kein Auto-Update-Kanal deckt sie ab. Dieser Audit MELDET nur # (bewusst kein Auto-Update: Python-Deps brechen gern): # je venv: veraltete Pakete zählen (pip list --outdated) + bekannte @@ -9,7 +9,7 @@ # idempotent je Monat). Läuft als Hermes-Cron --no-agent (stdout = Telegram). set -uo pipefail -VENVS=("$HOME/.mem0/venv:mem0" "$HOME/.voice/venv:voice") +VENVS=("$HOME/.voice/venv:voice") AUDIT_VENV="$HOME/.venv-audit" HERMES="$HOME/.local/bin/hermes" MONAT="$(date '+%Y-%m')" diff --git a/deploy/voice-service.service b/deploy/voice-service.service new file mode 100644 index 0000000..94ed1e4 --- /dev/null +++ b/deploy/voice-service.service @@ -0,0 +1,33 @@ +# systemd-USER-Unit für den MC2 Voice-Sidecar — lokales STT + gestuftes TTS. +# +# ‼️ NACHGETRAGEN 27.08.2026: Diese Unit lief auf der Box, fehlte aber im Repo — weder +# versioniert noch vom Disaster-Recovery abgedeckt, obwohl services/maintenance.py +# (USER_SERVICES) und routers/system.py sie voraussetzen. Inhalt 1:1 von der laufenden Box +# übernommen (`systemctl --user cat voice-service`). +# +# Ablage: ~/.config/systemd/user/voice-service.service ; dann: +# systemctl --user daemon-reload && systemctl --user enable --now voice-service + +[Unit] +Description=MC2 Voice Sidecar — lokales STT (faster-whisper) + gestuftes TTS (Piper/Chatterbox) +After=network.target + +[Service] +# Eigenes Python-3.12-venv (~/.voice/venv) — torch/chatterbox/faster-whisper passen nicht ins +# 3.14-Backend-venv. Bind 127.0.0.1: nur lokal; MC2 proxyt nach außen (routers/voice.py). +Type=simple +WorkingDirectory=%h/mission-control-v2/voice_service +Environment=VOICE_PORT=8650 +Environment=VOICE_STT_MODEL=medium +Environment=VOICE_STT_LANG=de +Environment=VOICE_PIPER_DIR=%h/.voice/voices +Environment=VOICE_PIPER_DEFAULT=de_DE-thorsten-medium +Environment=VOICE_CHATTERBOX_DEVICE=cpu +Environment=VOICE_CHATTERBOX_LANG=de +Environment=TOKENIZERS_PARALLELISM=false +ExecStart=%h/.voice/venv/bin/python -m uvicorn app:app --host 127.0.0.1 --port 8650 +Restart=always +RestartSec=3 + +[Install] +WantedBy=default.target diff --git a/deploy/warmup.sh b/deploy/warmup.sh index 85bddf6..0e33415 100644 --- a/deploy/warmup.sh +++ b/deploy/warmup.sh @@ -4,7 +4,7 @@ # Eingehängt als ExecStartPost=-/usr/local/bin/llama-swap-warmup.sh in llama-swap. # # `fast` = das Agent-Hirn (Qwen3.6-35B-A3B), `embed` = das Embedding-Modell -# (Qwen3-Embedding-0.6B, für Mem0/Gedächtnis). Die Augen (vision/VL-30B) sind seit 07.07. +# (Qwen3-Embedding-0.6B). Die Augen (vision/VL-30B) sind seit 07.07. # ON-DEMAND (User-Entscheid) und gehören NICHT mehr ins Warm-Set — die Lucy-App wärmt sie # beim Start selbst an. Modelle werden NICHT automatisch zusammen geladen — jedes einzeln # anstoßen, sonst bleibt es kalt. diff --git a/docs/wissen/STACK.md b/docs/wissen/STACK.md index 46a6315..eb74bf2 100644 --- a/docs/wissen/STACK.md +++ b/docs/wissen/STACK.md @@ -66,7 +66,8 @@ Config: `/etc/llama-swap/config.yaml` (sudo zum Schreiben). - **v0.20.4** (git-Install `~/.hermes/hermes-agent`), Config `~/.hermes/config.yaml`, Persona `~/.hermes/SOUL.md` = **Lucy**. - **Bot Mode:** Unterstützt Multi-Bot-Roster (`Lucy` als Haupt-Agentin, `Coder` mit `Qwen3-Coder-Next`, `Debugger` mit `Muse-Glimmer-30B`). - `approvals.mode: smart`, `approvals.cron_mode: deny`. -- MCP-Server (aus `~/mission-control-v2/mcp/`): mission-control-memory, mission-control-stack, hermes-pc-control, hermes-web-fetch, mcp_voice. +- MCP-Server (aus `~/mission-control-v2/mcp/`): mission-control-stack, hermes-pc-control, hermes-web-fetch, mcp_voice. + (`mission-control-memory` ist am 27.08.2026 entfallen — Hermes führt sein Gedächtnis selbst.) ## Automatik-Fahrplan (was nachts von allein läuft) diff --git a/frontend/dist/assets/AgentView-C-rUOPjn.js b/frontend/dist/assets/AgentView-pp2NXhb4.js similarity index 99% rename from frontend/dist/assets/AgentView-C-rUOPjn.js rename to frontend/dist/assets/AgentView-pp2NXhb4.js index 250d2ac..aec87c1 100644 --- a/frontend/dist/assets/AgentView-C-rUOPjn.js +++ b/frontend/dist/assets/AgentView-pp2NXhb4.js @@ -1,4 +1,4 @@ -import{c as A,I as P,f as M,k as B,u as D,r as z,j as e,J as T,b as a,K as g,M as b,N as W,t as f,W as j,O as G,X as I,C as N,n as y,q as i}from"./index-CCbyojll.js";/** +import{c as A,I as P,f as M,k as B,u as D,r as z,j as e,J as T,b as a,K as g,M as b,N as W,t as f,W as j,O as G,X as I,C as N,n as y,q as i}from"./index-DNt66je4.js";/** * @license lucide-react v0.460.0 - 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F:\\Coding Stuff\\mission-control-2\\mcp\\mcp_memory.py",className:"w-full h-9 rounded-lg border border-border/60 bg-background/40 px-3 font-mono text-xs outline-none focus:ring-1 focus:ring-violet-500/50 text-foreground"}),e.jsx("p",{className:"text-[10px] text-muted-foreground/70",children:"Nur nötig, wenn du das Gedächtnis in einem PC-Tool anschließt — das Script läuft lokal und spricht mit der Box. 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ISC + * + * This source code is licensed under the ISC license. + * See the LICENSE file in the root directory of this source tree. + */const F=i("Globe",[["circle",{cx:"12",cy:"12",r:"10",key:"1mglay"}],["path",{d:"M12 2a14.5 14.5 0 0 0 0 20 14.5 14.5 0 0 0 0-20",key:"13o1zl"}],["path",{d:"M2 12h20",key:"9i4pu4"}]]);/** + * @license lucide-react v0.460.0 - ISC + * + * This source code is licensed under the ISC license. + * See the LICENSE file in the root directory of this source tree. + */const w=i("Info",[["circle",{cx:"12",cy:"12",r:"10",key:"1mglay"}],["path",{d:"M12 16v-4",key:"1dtifu"}],["path",{d:"M12 8h.01",key:"e9boi3"}]]);/** + * @license lucide-react v0.460.0 - ISC + * + * This source code is licensed under the ISC license. + * See the LICENSE file in the root directory of this source tree. + */const g=i("Laptop",[["path",{d:"M20 16V7a2 2 0 0 0-2-2H6a2 2 0 0 0-2 2v9m16 0H4m16 0 1.28 2.55a1 1 0 0 1-.9 1.45H3.62a1 1 0 0 1-.9-1.45L4 16",key:"tarvll"}]]),k={hermes_desktop:"Hermes Desktop: Browser-Login",kilo:"Kilo: Einstellungen → API Provider",claude_code:"env / Übersetzer"};function f({line:t,loading:n}){return n||!t?e.jsxs("span",{className:"inline-flex items-center gap-1 text-[10px] font-semibold text-muted-foreground",children:[e.jsx(B,{className:"h-3 w-3 animate-spin"})," prüfe…"]}):t.ok?e.jsxs("span",{className:"inline-flex items-center gap-1 text-[10px] font-semibold text-emerald-400",children:[e.jsx(_,{className:"h-3 w-3"})," ",t.detail]}):e.jsxs("span",{className:"inline-flex items-center gap-1 text-[10px] font-semibold text-red-400",children:[e.jsx(T,{className:"h-3 w-3"})," ",t.detail]})}function C({tool:t,fileName:n,accent:o,copied:c,onCopy:x}){return e.jsxs("div",{className:"flex flex-col border border-border/60 bg-black/60 rounded-2xl overflow-hidden shadow-2xl",children:[e.jsxs("div",{className:"flex h-11 items-center justify-between px-4 border-b border-border/40 bg-black/40 shrink-0",children:[e.jsxs("div",{className:"flex items-center gap-1.5",children:[e.jsx("span",{className:"h-3 w-3 rounded-full bg-red-500/80"}),e.jsx("span",{className:"h-3 w-3 rounded-full bg-amber-500/80"}),e.jsx("span",{className:"h-3 w-3 rounded-full bg-emerald-500/80"})]}),e.jsx("div",{className:"flex items-center gap-1.5 text-[10px] font-mono text-muted-foreground/75 bg-background/30 px-3 py-1 rounded-md border border-border/20",children:e.jsx("span",{children:n})}),e.jsxs("button",{onClick:x,className:"flex h-7 px-2.5 items-center gap-1.5 rounded-lg border border-border/40 bg-background/30 text-[10px] font-semibold text-muted-foreground hover:text-foreground hover:bg-background/60 transition-all cursor-pointer",children:[c?e.jsx(E,{className:"h-3.5 w-3.5 text-emerald-400"}):e.jsx(K,{className:"h-3.5 w-3.5"}),e.jsx("span",{children:c?"Kopiert":"Kopieren"})]})]}),e.jsx("pre",{className:S("p-5 overflow-x-auto text-xs font-mono whitespace-pre leading-relaxed scrollbar-thin select-text bg-black/10",o==="teal"?"text-cyan-200/90":"text-violet-200/90"),children:e.jsx("code",{children:t.snippet})})]})}function R(){const t=window.location.hostname;return t&&t!=="localhost"&&t!=="127.0.0.1"?t:"192.168.178.151"}function W(){const[t,n]=p.useState(localStorage.getItem("mc_host")||R()),[o,c]=p.useState("kilo"),[x,L]=p.useState(!1),[b,j]=p.useState(null),A=new URLSearchParams({host:t}),{data:a,error:N}=G(A.toString()),{data:r,isLoading:h}=H(),v=N?String(N):"";function D(s){n(s),s&&localStorage.setItem("mc_host",s)}const d=a==null?void 0:a.tools.hermes_desktop,l=a==null?void 0:a.tools[o];async function y(s,m){m&&(await navigator.clipboard.writeText(m),j(s),setTimeout(()=>j(null),1500))}return e.jsxs("div",{className:"space-y-6",children:[e.jsxs("div",{children:[e.jsx("h1",{className:"text-2xl font-space font-bold tracking-tight bg-gradient-to-r from-foreground via-foreground to-primary bg-clip-text text-transparent",children:"Verbindung & Integration"}),e.jsxs("p",{className:"text-sm text-muted-foreground",children:[e.jsx("span",{className:"text-foreground",children:"Hermes Desktop"})," ist die Tür zur Box — einmal verbinden, fertig. 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Das Gedächtnis führt",e.jsx("span",{className:"text-foreground",children:" Hermes selbst"})," (nichts einzurichten — die Kachel zeigt nur, ob es lebt), und das Desktop-Gateway bietet die Agenten-Schnittstelle. 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Ändern musst du sie nur, wenn die Box eine neue IP bekommt."})]})}),v&&e.jsxs("div",{className:"rounded-xl border border-red-500/20 bg-red-500/5 p-4 text-xs text-red-400",children:["Fehler beim Generieren der Snippets: ",v]}),a&&e.jsxs("div",{className:"space-y-5",children:[d&&e.jsxs("div",{className:"space-y-3 rounded-2xl border border-border/60 border-t-2 border-t-emerald-500/70 bg-card/30 p-4",children:[e.jsxs("div",{children:[e.jsxs("div",{className:"flex items-center gap-2 text-sm font-space font-bold text-foreground",children:[e.jsx(g,{className:"h-4 w-4 text-emerald-400"}),"Hermes Desktop anbinden",e.jsx("span",{className:"text-[10px] font-medium text-emerald-400/90 normal-case",children:"der Hauptweg"})]}),e.jsx("p",{className:"text-[11px] text-muted-foreground mt-0.5",children:"Die Desktop-App dockt remote an die Box an — volle Agent-Oberfläche, Projekte, Review, Gedächtnis inklusive."})]}),d.note&&e.jsxs("div",{className:"flex items-start gap-2.5 p-3 rounded-xl bg-emerald-500/5 border border-emerald-500/20 text-[11px] text-muted-foreground leading-relaxed",children:[e.jsx(w,{className:"h-4 w-4 text-emerald-400 shrink-0 mt-0.5"}),e.jsx("span",{children:d.note})]}),e.jsx(C,{tool:d,fileName:k.hermes_desktop,accent:"teal",copied:b==="desktop",onCopy:()=>y("desktop",d.snippet)})]}),e.jsxs("div",{className:"rounded-2xl border border-border/60 bg-card/30",children:[e.jsxs("button",{onClick:()=>L(s=>!s),className:"flex w-full items-center gap-2 p-4 text-sm font-space font-bold text-foreground cursor-pointer hover:text-primary transition-colors",children:[x?e.jsx(P,{className:"h-4 w-4"}):e.jsx(M,{className:"h-4 w-4"}),"Sonstige Tools (roher /v1-Zugang)",e.jsx("span",{className:"text-[10px] font-medium text-muted-foreground normal-case",children:"Kilo Code · Claude Code · Eigenbau"})]}),x&&e.jsx("div",{className:"grid gap-5 p-4 pt-0",children:e.jsxs("div",{className:"space-y-3 rounded-2xl border border-border/60 border-t-2 border-t-primary/70 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as y,M as v,_ as L,O as G,$ as D,W as T,b as f,a0 as B}from"./index-DNt66je4.js";import{a as w,L as P,C as E,Z as R}from"./zap-cdYTHDpR.js";import{L as I}from"./layers-BakyhGhx.js";/** * @license lucide-react v0.460.0 - ISC * * This source code is licensed under the ISC license. @@ -8,7 +8,7 @@ import{c as u,j as e,r as M,t as C,V as z,Y as k,Z as y,M as v,_ as L,O as G,$ a * * This source code is licensed under the ISC license. * See the LICENSE file in the root directory of this source tree. - */const N=u("BookOpen",[["path",{d:"M12 7v14",key:"1akyts"}],["path",{d:"M3 18a1 1 0 0 1-1-1V4a1 1 0 0 1 1-1h5a4 4 0 0 1 4 4 4 4 0 0 1 4-4h5a1 1 0 0 1 1 1v13a1 1 0 0 1-1 1h-6a3 3 0 0 0-3 3 3 3 0 0 0-3-3z",key:"ruj8y"}]]);/** + */const S=u("BookOpen",[["path",{d:"M12 7v14",key:"1akyts"}],["path",{d:"M3 18a1 1 0 0 1-1-1V4a1 1 0 0 1 1-1h5a4 4 0 0 1 4 4 4 4 0 0 1 4-4h5a1 1 0 0 1 1 1v13a1 1 0 0 1-1 1h-6a3 3 0 0 0-3 3 3 3 0 0 0-3-3z",key:"ruj8y"}]]);/** * @license lucide-react v0.460.0 - ISC * * This 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",e.jsx("span",{className:"font-semibold text-foreground",children:"Stand Juli 2026."})," ",e.jsx("span",{className:"text-primary font-semibold",children:'„Bei dir konkret"'}),"-Kästen zeigen, was dein Stack daraus macht."]})]})]}),e.jsx("div",{className:"sticky top-0 z-10 -mx-1 px-1",children:e.jsx("div",{className:"rounded-xl border border-border/50 bg-card/70 backdrop-blur-xl p-2 shadow-lg shadow-black/20",children:e.jsxs("div",{className:"flex items-center gap-1.5 flex-wrap",children:[e.jsx(w,{className:"h-3.5 w-3.5 text-primary ml-1 mr-0.5 shrink-0"}),(n?S:S.slice(0,9)).map(t=>e.jsx("button",{onClick:()=>Q(t.id),className:"rounded-lg px-2.5 py-1 text-[11px] font-semibold text-muted-foreground hover:text-primary hover:bg-primary/10 transition-colors cursor-pointer",children:t.label},t.id)),e.jsx("button",{onClick:()=>r(t=>!t),className:"rounded-lg px-2 py-1 text-[11px] font-semibold text-primary hover:bg-primary/10 transition-colors cursor-pointer",children:n?"weniger":"+ mehr"})]})})}),e.jsxs("section",{id:"system",className:"scroll-mt-20 mc-card p-6 space-y-4",children:[e.jsxs("div",{className:"flex items-center gap-2.5 border-b border-border/20 pb-3",children:[e.jsx(A,{className:"h-5 w-5 text-primary"}),e.jsxs("div",{children:[e.jsx("h3",{className:"text-xs font-bold uppercase tracking-wider text-foreground",children:"So funktioniert dein System"}),e.jsx("span",{className:"text-[9px] font-mono text-primary",children:"Landkarte & Kreislauf — das große Bild"})]})]}),e.jsxs("p",{className:"text-xs text-muted-foreground leading-relaxed max-w-3xl",children:["Vier Türen führen zur selben Box: ",e.jsx("strong",{className:"text-foreground",children:"diese Oberfläche"})," zum Steuern und Abnicken, ",e.jsx("strong",{className:"text-foreground",children:"Lucy"})," für Zurufe per Stimme,",e.jsx("strong",{className:"text-foreground",children:" Hermes Desktop"})," für richtige Projekte und",e.jsx("strong",{className:"text-foreground",children:" Telegram"})," für unterwegs. 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MoE & Quantisierung",kicker:"Mehr Modell, weniger Last",children:[e.jsxs("p",{children:[e.jsx("strong",{children:"Mixture of Experts (MoE):"})," Statt für jedes Token das ganze Netz zu aktivieren, wählt ein",e.jsx("em",{children:" Router"})," nur ein paar spezialisierte ",e.jsx("em",{children:"Experts"}),' aus. So läuft ein 100B-Modell mit der aktiven Rechenlast eines viel kleineren (z.B. „122B total / 10B aktiv").']}),e.jsxs("p",{children:[e.jsx("strong",{children:"Quantisierung:"})," Gewichte von FP16 auf weniger Bits eindampfen — kleiner & schneller bei minimalem Qualitätsverlust. 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",e.jsx("span",{className:"font-semibold text-foreground",children:"Stand Juli 2026."})," ",e.jsx("span",{className:"text-primary font-semibold",children:'„Bei dir konkret"'}),"-Kästen zeigen, was dein Stack daraus macht."]})]})]}),e.jsx("div",{className:"sticky top-0 z-10 -mx-1 px-1",children:e.jsx("div",{className:"rounded-xl border border-border/50 bg-card/70 backdrop-blur-xl p-2 shadow-lg shadow-black/20",children:e.jsxs("div",{className:"flex items-center gap-1.5 flex-wrap",children:[e.jsx(w,{className:"h-3.5 w-3.5 text-primary ml-1 mr-0.5 shrink-0"}),(n?N:N.slice(0,9)).map(t=>e.jsx("button",{onClick:()=>Q(t.id),className:"rounded-lg px-2.5 py-1 text-[11px] font-semibold text-muted-foreground hover:text-primary hover:bg-primary/10 transition-colors cursor-pointer",children:t.label},t.id)),e.jsx("button",{onClick:()=>r(t=>!t),className:"rounded-lg px-2 py-1 text-[11px] font-semibold text-primary hover:bg-primary/10 transition-colors cursor-pointer",children:n?"weniger":"+ mehr"})]})})}),e.jsxs("section",{id:"system",className:"scroll-mt-20 mc-card p-6 space-y-4",children:[e.jsxs("div",{className:"flex items-center gap-2.5 border-b border-border/20 pb-3",children:[e.jsx(A,{className:"h-5 w-5 text-primary"}),e.jsxs("div",{children:[e.jsx("h3",{className:"text-xs font-bold uppercase tracking-wider text-foreground",children:"So funktioniert dein System"}),e.jsx("span",{className:"text-[9px] font-mono text-primary",children:"Landkarte & Kreislauf — das große Bild"})]})]}),e.jsxs("p",{className:"text-xs text-muted-foreground leading-relaxed max-w-3xl",children:["Vier Türen führen zur selben Box: ",e.jsx("strong",{className:"text-foreground",children:"diese Oberfläche"})," zum Steuern und Abnicken, ",e.jsx("strong",{className:"text-foreground",children:"Lucy"})," für Zurufe per Stimme,",e.jsx("strong",{className:"text-foreground",children:" Hermes Desktop"})," für richtige Projekte und",e.jsx("strong",{className:"text-foreground",children:" Telegram"})," für unterwegs. In der Box denken die Modelle, das Gedächtnis lernt automatisch mit — und nachts arbeitet sie allein: Sie träumt, inventarisiert sich selbst, entwickelt Ideen zu fertigen Vorschlägen und legt sie dir als Karten ins Auftragsbuch.",e.jsx("strong",{className:"text-primary",children:" Nichts geht live ohne deinen Klick"})," — und wenn nach einer Annahme etwas rot wird, baut die Box es selbst zurück."]}),e.jsx(U,{})]}),e.jsxs("div",{className:"grid gap-5 md:grid-cols-2",children:[e.jsxs(a,{id:"grundlagen",icon:C,color:"text-cyan-400",title:"1. Wie LLMs ticken",kicker:"Grundlagen",children:[e.jsxs("p",{children:["Ein LLM ist im Kern ein ",e.jsx("strong",{children:"Wahrscheinlichkeits-Rechner für das nächste Token"}),' (Wortteil). Es „weiß" nichts — es setzt fort, was statistisch am plausibelsten ist. Daraus folgt fast alles andere.']}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1",children:[e.jsxs("li",{children:[e.jsx("strong",{children:"Tokens"})," sind die Einheit — ~¾ Wort. Ein- und Ausgabe werden in Tokens gezählt."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Kontextfenster"}),' = wie viele Tokens das Modell gleichzeitig „sehen" kann (Prompt + Antwort). Voll = Anfang fällt raus.']}),e.jsxs("li",{children:[e.jsx("strong",{children:"Parameter"})," = die trainierten Gewichte. Training ist einmalig, ",e.jsx("strong",{children:"Inferenz"})," ist jede Antwort."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Temperatur / Sampling"})," steuert Zufall: niedrig = deterministisch/präzise (Code), hoch = kreativ."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Halluzination"})," ist kein Bug, sondern die Kehrseite des Ratens. Gegenmittel: Grounding via Tools/RAG, Verifikation."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Reasoning-/Thinking-Modelle"}),' „denken" in unsichtbaren Tokens vor der Antwort — besser bei Logik, langsamer/teurer.']})]})]}),e.jsxs(a,{id:"moe",icon:I,color:"text-violet-400",title:"2. MoE & Quantisierung",kicker:"Mehr Modell, weniger Last",children:[e.jsxs("p",{children:[e.jsx("strong",{children:"Mixture of Experts (MoE):"})," Statt für jedes Token das ganze Netz zu aktivieren, wählt ein",e.jsx("em",{children:" Router"})," nur ein paar spezialisierte ",e.jsx("em",{children:"Experts"}),' aus. So läuft ein 100B-Modell mit der aktiven Rechenlast eines viel kleineren (z.B. „122B total / 10B aktiv").']}),e.jsxs("p",{children:[e.jsx("strong",{children:"Quantisierung:"})," Gewichte von FP16 auf weniger Bits eindampfen — kleiner & schneller bei minimalem Qualitätsverlust. Faustregel:"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1",children:[e.jsxs("li",{children:[e.jsx(s,{children:"Q8"})," nahezu verlustfrei, größter Footprint"]}),e.jsxs("li",{children:[e.jsx(s,{children:"Q6_K"})," sehr gut, guter Mittelweg"]}),e.jsxs("li",{children:[e.jsx(s,{children:"Q4_K_M"})," der Sweet-Spot für lokal — viel Modell pro GB"]})]}),e.jsxs(m,{children:["VRAM/RAM ist die harte Grenze — ",e.jsx("strong",{children:"darum"})," ist beides hier zentral: MoE lässt 100B+ überhaupt laufen, Quant entscheidet, was reinpasst. Dein Line-up fährt durchweg ",e.jsx(s,{children:"Q4_K_M"}),"/",e.jsx(s,{children:"Q6_K"}),"."]})]}),e.jsxs(a,{id:"lokal",icon:z,color:"text-emerald-400",title:"3. Lokal betreiben: Engines & Backends",kicker:"llama.cpp, vLLM & Co.",wide:!0,children:[e.jsxs("div",{className:"grid md:grid-cols-2 gap-4",children:[e.jsxs("div",{className:"space-y-2",children:[e.jsxs("p",{children:[e.jsx("strong",{children:"Inference-Engines"})," — was die Modelle ausführt:"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1",children:[e.jsxs("li",{children:[e.jsx("strong",{children:"llama.cpp / GGUF"})," — der De-facto-Standard für lokal, CPU+GPU, läuft überall."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Ollama / LM Studio"})," — bequeme Wrapper mit One-Click-Downloads (LM Studio mit GUI)."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"vLLM / TGI"})," — Server-Engines für maximalen Durchsatz auf dicken GPUs."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"llama-swap"})," — Proxy, der ",e.jsx("em",{children:"mehrere"})," Modelle hinter ",e.jsx("em",{children:"einem"})," Port hält und je nach Anfrage automatisch ein-/aussattelt."]})]})]}),e.jsxs("div",{className:"space-y-2",children:[e.jsxs("p",{children:[e.jsx("strong",{children:"GPU-Backends"})," — wie gerechnet wird:"]}),e.jsx("ul",{className:"list-disc pl-4 space-y-1",children:e.jsxs("li",{children:[e.jsx(s,{children:"CUDA"})," NVIDIA · ",e.jsx(s,{children:"ROCm"})," AMD · ",e.jsx(s,{children:"Vulkan"})," herstellerübergreifend · ",e.jsx(s,{children:"Metal"})," Apple"]})}),e.jsxs("p",{className:"pt-1",children:[e.jsx("strong",{children:"Begriffe, die immer wiederkommen:"})," Kontext (",e.jsx(s,{children:"-c"}),"), Slots/Parallel, KV-Cache, Modell-TTL/Swap, ",e.jsx("strong",{children:"Speculative Decoding"})," (kleines Draft-Modell rät voraus → schneller)."]})]})]}),e.jsxs(m,{children:["Deine Box hat eine AMD-APU (gfx1151). ",e.jsx("strong",{children:"Einschränkung & Trick:"})," dort schlägt ",e.jsx(s,{children:"Vulkan/RADV"})," das offizielle ",e.jsx(s,{children:"ROCm"})," bei Token-Generierung um ~12–22 % — darum läuft die Engine auf Vulkan.",e.jsx(s,{children:"llama-swap"})," hält die Alltags-Hirne dauerwarm; ",e.jsx(s,{children:"coder"})," nutzt Spec-Decoding."]})]}),e.jsxs(a,{id:"modelle",icon:k,color:"text-sky-400",title:"4. Modell-Landschaft",kicker:"Stand Juni 2026",wide:!0,children:[e.jsxs("div",{className:"grid md:grid-cols-2 gap-4",children:[e.jsxs("div",{className:"space-y-2",children:[e.jsx("p",{children:e.jsx("strong",{children:"Open-Weight (lokal nutzbar):"})}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1",children:[e.jsxs("li",{children:[e.jsx("strong",{children:"Qwen"})," (Alibaba) — starke Allrounder + Coder + Vision, viele Größen/MoE."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Llama"})," (Meta), ",e.jsx("strong",{children:"Gemma"})," (Google), ",e.jsx("strong",{children:"Phi"})," (Microsoft) — solide Open-Familien."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"DeepSeek"}),", ",e.jsx("strong",{children:"Mistral/Mixtral"})," — kräftige MoE-/Reasoning-Modelle."]})]})]}),e.jsxs("div",{className:"space-y-2",children:[e.jsx("p",{children:e.jsx("strong",{children:"Frontier (Cloud-API):"})}),e.jsx("ul",{className:"list-disc pl-4 space-y-1",children:e.jsxs("li",{children:[e.jsx("strong",{children:"Claude"})," (Anthropic), ",e.jsx("strong",{children:"GPT"})," (OpenAI), ",e.jsx("strong",{children:"Gemini"})," (Google) — die stärksten Allrounder, aber nicht lokal."]})}),e.jsxs("p",{className:"pt-1",children:[e.jsx("strong",{children:"Modellwahl nach Aufgabe:"})," schnelles Alltags-Hirn · großes Logik-Hirn für harte Tasks · dediziertes Code-Modell · multimodal für Bilder · Embedding-Modell fürs Gedächtnis."]})]})]}),e.jsx("p",{className:"text-[11px] italic",children:'Leaderboards (HF, LMArena) sind grobe Orientierung — der einzige Benchmark, der zählt, ist deine eigene Aufgabe. Vorsicht vor „Benchmaxxing".'}),e.jsxs(m,{children:["Dein Line-up via llama-swap (Klartext-Rollen): ",e.jsx(s,{children:"Hirn"})," (Agent, dauerwarm) · ",e.jsx(s,{children:"Groß"})," (schwere Logik) · ",e.jsx(s,{children:"Coder"})," · ",e.jsx(s,{children:"Augen"})," (Bilder) · ",e.jsx(s,{children:"Späher"})," (schnelle Recherche) ·",e.jsx(s,{children:"Kritiker"})," (Fremdblick/Review) · ",e.jsx(s,{children:"Gedächtnis"})," + ",e.jsx(s,{children:"Sortierer"})," (Embedding & Reranking). Verwalten/tauschen im ",e.jsx("strong",{children:"Modelle"}),"-Tab."]})]}),e.jsxs(a,{id:"gateway",icon:A,color:"text-amber-400",title:"5. Der Gateway-Trick",kicker:"OpenAI-kompatibel = überall andocken",children:[e.jsxs("p",{children:["Fast jedes AI-Tool spricht heute das ",e.jsx("strong",{children:"OpenAI-Format"})," (",e.jsx(s,{children:"/v1/chat/completions"}),"). Ein",e.jsx("strong",{children:" Gateway"})," davor gibt dir ",e.jsx("em",{children:"einen"})," Endpunkt für alles: zentrales Key-Management, Logging und transparentes ",e.jsx("strong",{children:"Routing"})," — der Client merkt nicht, welches Modell tatsächlich antwortet."]}),e.jsxs("p",{children:["Die Lane-Idee: du wählst ",e.jsx(s,{children:"chat"})," (Alltag, ",e.jsx(s,{children:"auto"})," geht als Alias weiter) oder"," ",e.jsx(s,{children:"coding"})," (agentisch), das Gateway pickt das passende echte Modell und lädt es bei Bedarf."]}),e.jsxs(m,{children:["Dein Gateway: ",e.jsx(s,{children:"http://192.168.178.151:9001/v1"}),", Model ",e.jsx(s,{children:"chat"})," oder ",e.jsx(s,{children:"coding"}),", API-Key beliebig. Fertige Configs erzeugt dir der ",e.jsx("strong",{children:"Verbinden"}),"-Tab live — eine Wahrheit, kein Abtippen."]})]}),e.jsxs(a,{id:"mcp",icon:y,color:"text-violet-400",title:"6. MCP — Werkzeuge für Agenten",kicker:"USB-C für AI-Tools",children:[e.jsxs("p",{children:["Das ",e.jsx("strong",{children:"Model Context Protocol"})," (offen, von Anthropic initiiert) standardisiert, wie ein AI-Client mit externen Tools & Datenquellen spricht. Ein ",e.jsx("strong",{children:"MCP-Server"})," bringt Fähigkeiten: Dateien, Web-Fetch, Git, Datenbanken, eigene APIs."]}),e.jsx("p",{children:"Statt für jeden Editor eigene Tools zu schreiben, bindet jeder MCP-fähige Agent denselben Server an."}),e.jsxs("div",{className:"flex items-start gap-1.5 rounded-xl border border-amber-500/25 bg-amber-500/[0.06] p-2.5 text-[11px]",children:[e.jsx(P,{className:"h-3.5 w-3.5 text-amber-400 shrink-0 mt-0.5"}),e.jsxs("span",{children:[e.jsx("strong",{children:"Sicherheit:"})," ein MCP-Server hat echten Zugriff (Dateien, Shell). Nur vertrauenswürdige Server laufen lassen, Rechte minimal halten, Quelle prüfen."]})]})]}),e.jsxs(a,{id:"skills",icon:H,color:"text-emerald-400",title:"7. Agent Skills",kicker:"Wiederverwendbare Fähigkeiten",children:[e.jsxs("p",{children:["Ein ",e.jsx("strong",{children:"Skill"})," ist ein Ordner mit einer ",e.jsx(s,{children:"SKILL.md"})," (YAML-Kopf + Anleitung, optional Skripte/Beispiele), den der Agent für eine bestimmte Aufgabe lädt — z.B. TDD, Code-Vereinfachung, API-Design."]}),e.jsx("pre",{className:"p-2.5 bg-background/25 rounded-lg border border-border/30 font-mono text-[9px] text-foreground overflow-x-auto whitespace-pre",children:`--- name: tdd-pro description: Treibt Entwicklung mit strikter TDD-Praxis --- # Instructions -...`}),e.jsxs("p",{children:["Suchen & installieren über die ",e.jsx("strong",{children:"skills.sh"}),"-Registry: ",e.jsx(s,{children:"npx skills find"})," /",e.jsx(s,{children:"npx skills add owner/repo"}),". Skills liegen projektweit (vom Agent beim Start gelesen) oder global."]})]}),e.jsxs(a,{id:"memory",icon:V,color:"text-indigo-400",title:"8. Gedächtnis & RAG",kicker:"Modelle vergessen — du nicht",wide:!0,children:[e.jsxs("div",{className:"grid md:grid-cols-2 gap-4",children:[e.jsxs("div",{className:"space-y-2",children:[e.jsxs("p",{children:["LLMs sind ",e.jsx("strong",{children:"zustandslos"}),": ohne Hilfe weiß das Modell beim nächsten Turn nichts mehr. Gedächtnis lebt extern."]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1",children:[e.jsxs("li",{children:[e.jsx("strong",{children:"Embeddings"})," wandeln Text in Vektoren; ein ",e.jsx("strong",{children:"Vektor-Store"})," (Chroma, …) findet semantisch Ähnliches."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"RAG"})," = relevante Fakten vor dem Turn heraussuchen und einblenden statt alles im Prompt zu halten."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Long-Context vs. RAG:"}),' riesige Fenster sind bequem, aber teuer & „lost in the middle" — gezieltes Abrufen skaliert besser.']})]})]}),e.jsxs("div",{className:"space-y-2",children:[e.jsxs("p",{children:[e.jsx("strong",{children:"Auto-lernendes Gedächtnis"})," ist die nächste Stufe:"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1",children:[e.jsxs("li",{children:["extrahiert Fakten ",e.jsx("em",{children:"selbst"})," aus Gesprächen, statt nur abzuspeichern"]}),e.jsx("li",{children:"dedupliziert semantisch (kein 10× derselbe Fakt)"}),e.jsxs("li",{children:[e.jsx("strong",{children:"Graph-Sicht"})," = Fakten ",e.jsx("em",{children:"plus"})," ihre Beziehungen, nicht nur eine flache Liste"]})]})]})]}),e.jsxs(m,{children:["Dein Gedächtnis (Tab ",e.jsx("strong",{children:"Gedächtnis"}),") ist ",e.jsx("strong",{children:"Mem0"}),"-basiert: auto-lernend & semantisch, ",e.jsx("strong",{children:"graph-first"})," dargestellt, mit 4-Typen-Taxonomie (",e.jsx(s,{children:"Identität"})," · ",e.jsx(s,{children:"Wissen"})," · ",e.jsx(s,{children:"Regeln"})," · ",e.jsx(s,{children:"Ereignisse"}),"). Der Agent lernt im Hintergrund nach jedem Turn — egal ob du per Desktop, Konsole, Telegram oder Lucy mit ihm sprichst.",e.jsx("br",{}),e.jsx("strong",{children:"Gotcha:"})," ein gelöschter Fakt kann wieder auftauchen, solange die Original-Nachricht noch im Verlauf steht (additive Extraktion)."]})]}),e.jsxs(a,{id:"agents",icon:v,color:"text-rose-400",title:"9. Autonome Agenten betreiben",kicker:"LLM in der Schleife",wide:!0,children:[e.jsxs("div",{className:"grid md:grid-cols-2 gap-4",children:[e.jsxs("div",{className:"space-y-2",children:[e.jsxs("p",{children:["Ein ",e.jsx("strong",{children:"Agent"})," ist ein LLM in einer Schleife mit Tools:",e.jsx("em",{children:" denken → Tool aufrufen → Ergebnis beobachten → weiter"}),", bis das Ziel erreicht ist."]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1",children:[e.jsxs("li",{children:[e.jsx("strong",{children:"Guardrails"})," (Hard-Stop, Tool-Limits) verhindern Endlos-Loops, wenn ein Tool fehlt oder hängt."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Kontext-Hygiene"})," ist die wichtigste Disziplin: frische Sessions starten — vollgemüllte Historien werden langsam, driften und halluzinieren."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Kanäle:"})," CLI/Terminal, Chat-UI, Messaging (z.B. Telegram), reine API."]})]})]}),e.jsxs("div",{className:"space-y-2",children:[e.jsxs("p",{children:[e.jsx("strong",{children:"Least Privilege:"})," gib einem Agenten nur die Tools, die er wirklich braucht. Kritische Aktionen (Shell auf dem Host, Löschen, Geld/Deploys) hinter menschliche Freigabe."]}),e.jsxs("p",{children:[e.jsx("strong",{children:"Was sich vollautomatisch lohnt:"})," Modell-Routing, Hintergrund-Gedächtnis, Recherche. ",e.jsx("strong",{children:"Was Freigabe braucht:"})," Systembefehle, Updates/Reboots, permanentes Löschen."]})]})]}),e.jsxs(m,{children:[e.jsx("strong",{children:"Hermes"})," ist dein Box-Agent mit eigenem Agent-Hirn (Rolle ",e.jsx(s,{children:"Hirn"}),", dauerwarm). Reden tust du mit ihm über ",e.jsx("strong",{children:"Hermes Desktop"})," (am PC, remote via ",e.jsx(s,{children:"/hermes-ui"}),"), die ",e.jsx("strong",{children:"Konsole"})," (Box-Shell im Browser), ",e.jsx("strong",{children:"Telegram"})," — oder per Stimme über",e.jsx("strong",{children:" Lucy"}),". Er hat MCP-Server für Gedächtnis, Stack-Steuerung, Web-Fetch und",e.jsx("strong",{children:" PC-Steuerung"})," (Executor auf deinem Windows-PC). Nachts betreibt er Werkstatt & Radar-Crons — alles Gebaute landet als Karte im ",e.jsx("strong",{children:"Auftragsbuch"}),". Status & Verdrahtung im ",e.jsx("strong",{children:"Hermes"}),"-Tab."]})]}),e.jsxs(a,{id:"ide",icon:E,color:"text-cyan-400",title:"10. IDE / Editor anbinden",kicker:"Vibe-Coding lokal",children:[e.jsxs("p",{children:["Jede ",e.jsx("strong",{children:"OpenAI-kompatible"})," IDE oder Extension lässt sich auf einen lokalen Server umbiegen — Base-URL + Model eintragen, fertig:"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1",children:[e.jsxs("li",{children:[e.jsx("strong",{children:"Cline"})," & ",e.jsx("strong",{children:"Roo Code"})," (VS-Code-Extensions, voller Agent + MCP)"]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Cursor"})," (VS-Code-Fork mit Top-Autocomplete)"]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Continue"}),", ",e.jsx("strong",{children:"aider"})," (CLI), ",e.jsx("strong",{children:"OpenCode"})," (Desktop)"]})]}),e.jsxs(m,{children:["Deine Haupt-IDE ist inzwischen ",e.jsx("strong",{children:"Hermes Desktop"})," — sie ist ab Werk mit Box, Gedächtnis und Skills verdrahtet, da ist nichts zu konfigurieren. Für alles andere gilt: Tipp den Kram nicht ab — der",e.jsx("strong",{children:" Verbinden"}),"-Tab generiert die fertige Config (inkl. MCP-Gedächtnis) pro Tool zum Kopieren. Essenz: Base ",e.jsx(s,{children:"…:9001/v1"}),", Model ",e.jsx(s,{children:"coder"})," (bauen) / ",e.jsx(s,{children:"heavy"})," (denken) /"," ",e.jsx(s,{children:"vision"})," (Bilder); für simple Chat-Tools tut es die Lane ",e.jsx(s,{children:"chat"}),". Key beliebig."]})]}),e.jsx(a,{id:"tricks",icon:L,color:"text-amber-400",title:"11. Tricks & Kniffe",kicker:"Was im Alltag wirklich spart",wide:!0,children:e.jsx("div",{className:"grid md:grid-cols-3 gap-3",children:[["Kontext sauber halten","Neue Session statt Mega-Historie. Drift, Tempo und Halluzination hängen direkt am Kontext-Müll."],["Plan-then-Act","Erst Plan/Vorgehen bestätigen lassen, dann ausführen. Spart teure Holzwege."],["Gezielte Edits","Nie ganze Dateien überschreiben für eine Zeile — Such-/Ersetz-Tools nutzen. Weniger Tokens, weniger Fehler."],["Non-interaktive Befehle","Keine interaktiven Prompts im Agent-Terminal; lange Tasks als Background-Job. Sonst hängt der Loop."],["DevTools koppeln","Browser-/Konsolen-Zugriff geben — der Agent liest echte Fehler statt blind zu raten."],["Richtige Modellwahl","Schnelles Hirn für Alltag, großes für harte Logik, Coder fürs Coden. Nicht alles mit der Kanone."],["Akzeptanzkriterien","Sag konkret, woran „fertig“ erkennbar ist. Vage Prompts → vage Ergebnisse."],["Verifizieren statt vertrauen","Tests/Live-Check fordern. „Sollte funktionieren“ ist kein Beweis."],["Regeln ins Gedächtnis","Wiederkehrende Vorlieben/Konventionen einmal ablegen — der Agent zieht sie selbst."]].map(([t,c])=>e.jsxs("div",{className:"space-y-1 p-3 bg-background/10 rounded-xl border border-border/30",children:[e.jsxs("div",{className:"flex items-center gap-1.5 font-bold text-foreground text-[11px]",children:[e.jsx(R,{className:"h-3 w-3 text-amber-400"})," ",t]}),e.jsx("p",{className:"text-[11px]",children:c})]},t))})}),e.jsx(a,{id:"wartung",icon:G,color:"text-emerald-400",title:"12. Sicherheit & Wartung",kicker:"Damit's auch morgen noch läuft",wide:!0,children:e.jsxs("div",{className:"grid md:grid-cols-2 gap-4",children:[e.jsxs("div",{className:"space-y-2",children:[e.jsxs("p",{className:"flex items-center gap-1.5 font-bold text-foreground",children:[e.jsx(T,{className:"h-3.5 w-3.5 text-emerald-400"})," Goldene Regeln"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1",children:[e.jsxs("li",{children:[e.jsx("strong",{children:"Ein ungetesteter Restore ist kein Backup."})," Wiederherstellung mindestens einmal echt durchspielen."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Updates können Dinge still zerschießen"})," — gerade bei AI-Stacks (Embeddings, Provider-Interna). Versionen pinnen, Smoke-Test, Post-Check."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Least Privilege"})," für Agenten, MCP-Server und PC-Zugriff. Kritisches hinter Freigabe."]})]})]}),e.jsxs("div",{className:"space-y-2",children:[e.jsxs("p",{className:"flex items-center gap-1.5 font-bold text-foreground",children:[e.jsx(D,{className:"h-3.5 w-3.5 text-emerald-400"})," Bei dir im SystemDrawer"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1",children:[e.jsxs("li",{children:[e.jsx("strong",{children:"Backup:"})," PBS-Backup-Zentrum (Sicherung auf den Proxmox-Server) + tägliche Tarball-Sicherung; Restore echt durchgespielt (",e.jsx(s,{children:"restore.sh"}),", Doku in ",e.jsx(s,{children:"docs/BACKUP.md"}),")."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Updates:"})," git-basierter Update-Check; ",e.jsx("strong",{children:"Update-Buttons"})," mit anschließendem ",e.jsx("strong",{children:"Gehirn-Check"})," (rot, falls ein Update das Gedächtnis zerschießt)."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Annahme-Sicherheit:"})," jede Auftragsbuch-Annahme läuft mit Health-Check — wird's rot, baut die Box automatisch zurück (Auto-Revert)."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Dienste & Gefahrenzone:"})," Restart/Logs pro Dienst, kritische Eingriffe getrennt."]})]}),e.jsx("p",{className:"text-[10px] italic",children:'Erreichbar über das System-Icon → Tab „Wartung".'})]})]})}),e.jsxs("section",{id:"ressourcen",className:"scroll-mt-20 md:col-span-2 mc-card p-6 space-y-4",children:[e.jsxs("div",{className:"flex items-center gap-2.5 border-b border-border/20 pb-3",children:[e.jsx(w,{className:"h-5 w-5 text-primary"}),e.jsxs("div",{children:[e.jsx("h3",{className:"text-xs font-bold uppercase tracking-wider text-foreground",children:"13. Kuratierte Ressourcen & Links"}),e.jsx("span",{className:"text-[9px] font-mono text-primary",children:"Sauber geordnet — die guten Quellen"})]})]}),e.jsxs("div",{className:"grid md:grid-cols-2 gap-5 text-xs",children:[e.jsxs("div",{className:"space-y-2",children:[e.jsxs("div",{className:"font-bold text-foreground flex items-center gap-1.5",children:[e.jsx(k,{className:"h-3.5 w-3.5 text-sky-400"})," Modelle & Engines"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1.5",children:[e.jsx(l,{href:"https://huggingface.co/models",name:"Hugging Face",note:"das Repository für offene Modelle (GGUF, Embeddings, Datasets)."}),e.jsx(l,{href:"https://github.com/ggml-org/llama.cpp",name:"llama.cpp",note:"die Referenz-Engine für lokale Inferenz."}),e.jsx(l,{href:"https://github.com/mostlygeek/llama-swap",name:"llama-swap",note:"mehrere Modelle hinter einem Port, Auto-Swap."}),e.jsx(l,{href:"https://ollama.com",name:"Ollama",note:"einfachster Einstieg, One-Command-Modelle."}),e.jsx(l,{href:"https://lmstudio.ai",name:"LM Studio",note:"lokale GUI zum Stöbern, Laden & Chatten."}),e.jsx(l,{href:"https://github.com/vllm-project/vllm",name:"vLLM",note:"Hochdurchsatz-Serving auf dicken GPUs."})]})]}),e.jsxs("div",{className:"space-y-2",children:[e.jsxs("div",{className:"font-bold text-foreground flex items-center gap-1.5",children:[e.jsx(y,{className:"h-3.5 w-3.5 text-violet-400"})," MCP & Skills"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1.5",children:[e.jsx(l,{href:"https://modelcontextprotocol.io",name:"MCP — offizielle Doku",note:"Spezifikation & Einstieg."}),e.jsx(l,{href:"https://github.com/modelcontextprotocol/servers",name:"Offizielle MCP-Server",note:"filesystem, git, postgres, fetch & mehr."}),e.jsx(l,{href:"https://smithery.ai",name:"Smithery",note:"Registry zum Suchen & Auto-Installieren von MCP-Servern."}),e.jsx(l,{href:"https://glama.ai/mcp/servers",name:"Glama MCP Registry",note:"kuratierte Community-Datenbank."}),e.jsx(l,{href:"https://skills.sh",name:"skills.sh",note:"Registry & CLI für Agent-Skills."})]})]}),e.jsxs("div",{className:"space-y-2",children:[e.jsxs("div",{className:"font-bold text-foreground flex items-center gap-1.5",children:[e.jsx(v,{className:"h-3.5 w-3.5 text-rose-400"})," Agenten & Frameworks"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1.5",children:[e.jsx(l,{href:"https://github.com/NousResearch/hermes-agent",name:"Hermes Agent (Nous)",note:"der Agent, der auf deiner Box läuft."}),e.jsx(l,{href:"https://docs.claude.com",name:"Anthropic / Claude Docs",note:"API, Tool-Use, Agent SDK, MCP."}),e.jsx(l,{href:"https://github.com/cline/cline",name:"Cline",note:"autonomer Coding-Agent für VS Code."}),e.jsx(l,{href:"https://aider.chat",name:"aider",note:"AI-Pair-Programming im Terminal, git-nativ."}),e.jsx(l,{href:"https://continue.dev",name:"Continue",note:"Open-Source-Autopilot für IDEs."})]})]}),e.jsxs("div",{className:"space-y-2",children:[e.jsxs("div",{className:"font-bold text-foreground flex items-center gap-1.5",children:[e.jsx(N,{className:"h-3.5 w-3.5 text-amber-400"})," Lernen & Community"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1.5",children:[e.jsx(l,{href:"https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/overview",name:"Prompt-Engineering (Anthropic)",note:"die beste praktische Anleitung."}),e.jsx(l,{href:"https://github.com/anthropics/anthropic-cookbook",name:"Anthropic Cookbook",note:"lauffähige Rezepte für Tools, RAG, Agenten."}),e.jsx(l,{href:"https://www.promptingguide.ai",name:"Prompt Engineering Guide",note:"herstellerneutrales Nachschlagewerk."}),e.jsx(l,{href:"https://hermes-agent.nousresearch.com",name:"Hermes Agent",note:"die autonome Open-Source Agenten-Plattform unserer Box."}),e.jsx(l,{href:"https://www.reddit.com/r/LocalLLaMA/",name:"r/LocalLLaMA",note:"der Puls der lokalen-LLM-Szene."})]})]})]})]}),e.jsx(a,{id:"troubleshooting",icon:W,color:"text-rose-400",title:"14. Troubleshooting",kicker:"Wenn's hakt",wide:!0,children:e.jsxs("ul",{className:"space-y-2 list-disc pl-4",children:[e.jsxs("li",{children:[e.jsx("strong",{children:"Keine Verbindung?"})," Selbes LAN wie die Box? IP/Port stimmen (",e.jsx(s,{children:":9001"}),")? Backend-Status im ",e.jsx("strong",{children:"Cockpit"})," prüfen."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Modell antwortet nicht / langsam?"})," Im ",e.jsx("strong",{children:"Cockpit → Dienste"})," schauen, ob ",e.jsx(s,{children:"llama-swap"})," grün ist; sonst Restart. Erstes Token nach Swap dauert (Modell lädt)."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Agent dreht durch / halluziniert?"})," Frische Session starten (Hermes Desktop oder ",e.jsx("strong",{children:"Konsole"}),") — meist ist es vollgemüllter Kontext."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Gedächtnis findet nichts?"})," Embedding-Dienst online? Semantisch suchen (Sinn statt exaktem Wort)."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Angenommene Karte hat etwas zerschossen?"})," Meist fängt es der Auto-Revert; sonst ",e.jsx("strong",{children:"Chronik → Zeitmaschine"})," (Stand von gestern) oder Backup & ",e.jsx(s,{children:"restore.sh"}),"."]})]})})]}),e.jsx("p",{className:"text-center text-[10px] text-muted-foreground/50 pt-2",children:"Mission Control 2 · AI-Bibel · Stand Juli 2026 — lebendes Dokument, wächst mit dem Stack."})]})}export{q as GuideView}; +...`}),e.jsxs("p",{children:["Suchen & installieren über die ",e.jsx("strong",{children:"skills.sh"}),"-Registry: ",e.jsx(s,{children:"npx skills find"})," /",e.jsx(s,{children:"npx skills add owner/repo"}),". Skills liegen projektweit (vom Agent beim Start gelesen) oder global."]})]}),e.jsxs(a,{id:"memory",icon:V,color:"text-indigo-400",title:"8. Gedächtnis & RAG",kicker:"Modelle vergessen — du nicht",wide:!0,children:[e.jsxs("div",{className:"grid md:grid-cols-2 gap-4",children:[e.jsxs("div",{className:"space-y-2",children:[e.jsxs("p",{children:["LLMs sind ",e.jsx("strong",{children:"zustandslos"}),": ohne Hilfe weiß das Modell beim nächsten Turn nichts mehr. Gedächtnis lebt extern."]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1",children:[e.jsxs("li",{children:[e.jsx("strong",{children:"Embeddings"})," wandeln Text in Vektoren; ein ",e.jsx("strong",{children:"Vektor-Store"})," (Chroma, …) findet semantisch Ähnliches."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"RAG"})," = relevante Fakten vor dem Turn heraussuchen und einblenden statt alles im Prompt zu halten."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Long-Context vs. RAG:"}),' riesige Fenster sind bequem, aber teuer & „lost in the middle" — gezieltes Abrufen skaliert besser.']})]})]}),e.jsxs("div",{className:"space-y-2",children:[e.jsxs("p",{children:[e.jsx("strong",{children:"Auto-lernendes Gedächtnis"})," ist die nächste Stufe:"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1",children:[e.jsxs("li",{children:["extrahiert Fakten ",e.jsx("em",{children:"selbst"})," aus Gesprächen, statt nur abzuspeichern"]}),e.jsx("li",{children:"dedupliziert semantisch (kein 10× derselbe Fakt)"}),e.jsxs("li",{children:[e.jsx("strong",{children:"Graph-Sicht"})," = Fakten ",e.jsx("em",{children:"plus"})," ihre Beziehungen, nicht nur eine flache Liste"]})]})]})]}),e.jsxs(m,{children:["Dein Gedächtnis führt ",e.jsx("strong",{children:"Hermes"})," selbst — auto-lernend und semantisch. Der Agent lernt im Hintergrund nach jedem Turn, egal ob du per Desktop, Konsole, Telegram oder Lucy mit ihm sprichst.",e.jsx("br",{}),"Deshalb hat das Steuerpult ",e.jsx("strong",{children:"keinen eigenen Gedächtnis-Tab"}),": bis August 2026 lag das Gedächtnis in einem MC2-Sidecar, seit dessen Ablösung ist Hermes die einzige Quelle — angesehen und gepflegt wird es dort, nicht hier. Unter ",e.jsx("strong",{children:"Wissen"})," findest du weiterhin die Graph-Sicht auf Lucys Wissens-Vault.",e.jsx("br",{}),e.jsx("strong",{children:"Gotcha:"})," ein gelöschter Fakt kann wieder auftauchen, solange die Original-Nachricht noch im Verlauf steht (additive Extraktion)."]})]}),e.jsxs(a,{id:"agents",icon:v,color:"text-rose-400",title:"9. Autonome Agenten betreiben",kicker:"LLM in der Schleife",wide:!0,children:[e.jsxs("div",{className:"grid md:grid-cols-2 gap-4",children:[e.jsxs("div",{className:"space-y-2",children:[e.jsxs("p",{children:["Ein ",e.jsx("strong",{children:"Agent"})," ist ein LLM in einer Schleife mit Tools:",e.jsx("em",{children:" denken → Tool aufrufen → Ergebnis beobachten → weiter"}),", bis das Ziel erreicht ist."]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1",children:[e.jsxs("li",{children:[e.jsx("strong",{children:"Guardrails"})," (Hard-Stop, Tool-Limits) verhindern Endlos-Loops, wenn ein Tool fehlt oder hängt."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Kontext-Hygiene"})," ist die wichtigste Disziplin: frische Sessions starten — vollgemüllte Historien werden langsam, driften und halluzinieren."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Kanäle:"})," CLI/Terminal, Chat-UI, Messaging (z.B. Telegram), reine API."]})]})]}),e.jsxs("div",{className:"space-y-2",children:[e.jsxs("p",{children:[e.jsx("strong",{children:"Least Privilege:"})," gib einem Agenten nur die Tools, die er wirklich braucht. Kritische Aktionen (Shell auf dem Host, Löschen, Geld/Deploys) hinter menschliche Freigabe."]}),e.jsxs("p",{children:[e.jsx("strong",{children:"Was sich vollautomatisch lohnt:"})," Modell-Routing, Hintergrund-Gedächtnis, Recherche. ",e.jsx("strong",{children:"Was Freigabe braucht:"})," Systembefehle, Updates/Reboots, permanentes Löschen."]})]})]}),e.jsxs(m,{children:[e.jsx("strong",{children:"Hermes"})," ist dein Box-Agent mit eigenem Agent-Hirn (Rolle ",e.jsx(s,{children:"Hirn"}),", dauerwarm). Reden tust du mit ihm über ",e.jsx("strong",{children:"Hermes Desktop"})," (am PC, remote via ",e.jsx(s,{children:"/hermes-ui"}),"), die ",e.jsx("strong",{children:"Konsole"})," (Box-Shell im Browser), ",e.jsx("strong",{children:"Telegram"})," — oder per Stimme über",e.jsx("strong",{children:" Lucy"}),". Er hat MCP-Server für Gedächtnis, Stack-Steuerung, Web-Fetch und",e.jsx("strong",{children:" PC-Steuerung"})," (Executor auf deinem Windows-PC). Nachts betreibt er Werkstatt & Radar-Crons — alles Gebaute landet als Karte im ",e.jsx("strong",{children:"Auftragsbuch"}),". Status & Verdrahtung im ",e.jsx("strong",{children:"Hermes"}),"-Tab."]})]}),e.jsxs(a,{id:"ide",icon:E,color:"text-cyan-400",title:"10. 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Weniger Tokens, weniger Fehler."],["Non-interaktive Befehle","Keine interaktiven Prompts im Agent-Terminal; lange Tasks als Background-Job. Sonst hängt der Loop."],["DevTools koppeln","Browser-/Konsolen-Zugriff geben — der Agent liest echte Fehler statt blind zu raten."],["Richtige Modellwahl","Schnelles Hirn für Alltag, großes für harte Logik, Coder fürs Coden. Nicht alles mit der Kanone."],["Akzeptanzkriterien","Sag konkret, woran „fertig“ erkennbar ist. 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Sicherheit & Wartung",kicker:"Damit's auch morgen noch läuft",wide:!0,children:e.jsxs("div",{className:"grid md:grid-cols-2 gap-4",children:[e.jsxs("div",{className:"space-y-2",children:[e.jsxs("p",{className:"flex items-center gap-1.5 font-bold text-foreground",children:[e.jsx(D,{className:"h-3.5 w-3.5 text-emerald-400"})," Goldene Regeln"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1",children:[e.jsxs("li",{children:[e.jsx("strong",{children:"Ein ungetesteter Restore ist kein Backup."})," Wiederherstellung mindestens einmal echt durchspielen."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Updates können Dinge still zerschießen"})," — gerade bei AI-Stacks (Embeddings, Provider-Interna). Versionen pinnen, Smoke-Test, Post-Check."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Least Privilege"})," für Agenten, MCP-Server und PC-Zugriff. Kritisches hinter Freigabe."]})]})]}),e.jsxs("div",{className:"space-y-2",children:[e.jsxs("p",{className:"flex items-center gap-1.5 font-bold text-foreground",children:[e.jsx(T,{className:"h-3.5 w-3.5 text-emerald-400"})," Bei dir im SystemDrawer"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1",children:[e.jsxs("li",{children:[e.jsx("strong",{children:"Backup:"})," PBS-Backup-Zentrum (Sicherung auf den Proxmox-Server) + tägliche Tarball-Sicherung; Restore echt durchgespielt (",e.jsx(s,{children:"restore.sh"}),", Doku in ",e.jsx(s,{children:"docs/BACKUP.md"}),")."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Updates:"})," git-basierter Update-Check; ",e.jsx("strong",{children:"Update-Buttons"})," mit anschließendem ",e.jsx("strong",{children:"Gehirn-Check"})," (rot, falls ein Update das Gedächtnis zerschießt)."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Annahme-Sicherheit:"})," jede Auftragsbuch-Annahme läuft mit Health-Check — wird's rot, baut die Box automatisch zurück (Auto-Revert)."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Dienste & Gefahrenzone:"})," Restart/Logs pro Dienst, kritische Eingriffe getrennt."]})]}),e.jsx("p",{className:"text-[10px] italic",children:'Erreichbar über das System-Icon → Tab „Wartung".'})]})]})}),e.jsxs("section",{id:"ressourcen",className:"scroll-mt-20 md:col-span-2 mc-card p-6 space-y-4",children:[e.jsxs("div",{className:"flex items-center gap-2.5 border-b border-border/20 pb-3",children:[e.jsx(w,{className:"h-5 w-5 text-primary"}),e.jsxs("div",{children:[e.jsx("h3",{className:"text-xs font-bold uppercase tracking-wider text-foreground",children:"13. Kuratierte Ressourcen & Links"}),e.jsx("span",{className:"text-[9px] font-mono text-primary",children:"Sauber geordnet — die guten Quellen"})]})]}),e.jsxs("div",{className:"grid md:grid-cols-2 gap-5 text-xs",children:[e.jsxs("div",{className:"space-y-2",children:[e.jsxs("div",{className:"font-bold text-foreground flex items-center gap-1.5",children:[e.jsx(k,{className:"h-3.5 w-3.5 text-sky-400"})," Modelle & Engines"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1.5",children:[e.jsx(l,{href:"https://huggingface.co/models",name:"Hugging Face",note:"das Repository für offene Modelle (GGUF, Embeddings, Datasets)."}),e.jsx(l,{href:"https://github.com/ggml-org/llama.cpp",name:"llama.cpp",note:"die Referenz-Engine für lokale Inferenz."}),e.jsx(l,{href:"https://github.com/mostlygeek/llama-swap",name:"llama-swap",note:"mehrere Modelle hinter einem Port, Auto-Swap."}),e.jsx(l,{href:"https://ollama.com",name:"Ollama",note:"einfachster Einstieg, One-Command-Modelle."}),e.jsx(l,{href:"https://lmstudio.ai",name:"LM Studio",note:"lokale GUI zum Stöbern, Laden & Chatten."}),e.jsx(l,{href:"https://github.com/vllm-project/vllm",name:"vLLM",note:"Hochdurchsatz-Serving auf dicken GPUs."})]})]}),e.jsxs("div",{className:"space-y-2",children:[e.jsxs("div",{className:"font-bold text-foreground flex items-center gap-1.5",children:[e.jsx(y,{className:"h-3.5 w-3.5 text-violet-400"})," MCP & Skills"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1.5",children:[e.jsx(l,{href:"https://modelcontextprotocol.io",name:"MCP — offizielle Doku",note:"Spezifikation & Einstieg."}),e.jsx(l,{href:"https://github.com/modelcontextprotocol/servers",name:"Offizielle MCP-Server",note:"filesystem, git, postgres, fetch & mehr."}),e.jsx(l,{href:"https://smithery.ai",name:"Smithery",note:"Registry zum Suchen & Auto-Installieren von MCP-Servern."}),e.jsx(l,{href:"https://glama.ai/mcp/servers",name:"Glama MCP Registry",note:"kuratierte Community-Datenbank."}),e.jsx(l,{href:"https://skills.sh",name:"skills.sh",note:"Registry & CLI für Agent-Skills."})]})]}),e.jsxs("div",{className:"space-y-2",children:[e.jsxs("div",{className:"font-bold text-foreground flex items-center gap-1.5",children:[e.jsx(v,{className:"h-3.5 w-3.5 text-rose-400"})," Agenten & Frameworks"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1.5",children:[e.jsx(l,{href:"https://github.com/NousResearch/hermes-agent",name:"Hermes Agent (Nous)",note:"der Agent, der auf deiner Box läuft."}),e.jsx(l,{href:"https://docs.claude.com",name:"Anthropic / Claude Docs",note:"API, Tool-Use, Agent SDK, MCP."}),e.jsx(l,{href:"https://github.com/cline/cline",name:"Cline",note:"autonomer Coding-Agent für VS Code."}),e.jsx(l,{href:"https://aider.chat",name:"aider",note:"AI-Pair-Programming im Terminal, git-nativ."}),e.jsx(l,{href:"https://continue.dev",name:"Continue",note:"Open-Source-Autopilot für IDEs."})]})]}),e.jsxs("div",{className:"space-y-2",children:[e.jsxs("div",{className:"font-bold text-foreground flex items-center gap-1.5",children:[e.jsx(S,{className:"h-3.5 w-3.5 text-amber-400"})," Lernen & Community"]}),e.jsxs("ul",{className:"list-disc pl-4 space-y-1.5",children:[e.jsx(l,{href:"https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/overview",name:"Prompt-Engineering (Anthropic)",note:"die beste praktische Anleitung."}),e.jsx(l,{href:"https://github.com/anthropics/anthropic-cookbook",name:"Anthropic Cookbook",note:"lauffähige Rezepte für Tools, RAG, Agenten."}),e.jsx(l,{href:"https://www.promptingguide.ai",name:"Prompt Engineering Guide",note:"herstellerneutrales Nachschlagewerk."}),e.jsx(l,{href:"https://hermes-agent.nousresearch.com",name:"Hermes Agent",note:"die autonome Open-Source Agenten-Plattform unserer Box."}),e.jsx(l,{href:"https://www.reddit.com/r/LocalLLaMA/",name:"r/LocalLLaMA",note:"der Puls der lokalen-LLM-Szene."})]})]})]})]}),e.jsx(a,{id:"troubleshooting",icon:W,color:"text-rose-400",title:"14. Troubleshooting",kicker:"Wenn's hakt",wide:!0,children:e.jsxs("ul",{className:"space-y-2 list-disc pl-4",children:[e.jsxs("li",{children:[e.jsx("strong",{children:"Keine Verbindung?"})," Selbes LAN wie die Box? IP/Port stimmen (",e.jsx(s,{children:":9001"}),")? Backend-Status im ",e.jsx("strong",{children:"Cockpit"})," prüfen."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Modell antwortet nicht / langsam?"})," Im ",e.jsx("strong",{children:"Cockpit → Dienste"})," schauen, ob ",e.jsx(s,{children:"llama-swap"})," grün ist; sonst Restart. Erstes Token nach Swap dauert (Modell lädt)."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Agent dreht durch / halluziniert?"})," Frische Session starten (Hermes Desktop oder ",e.jsx("strong",{children:"Konsole"}),") — meist ist es vollgemüllter Kontext."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Gedächtnis findet nichts?"})," Embedding-Dienst online? Semantisch suchen (Sinn statt exaktem Wort)."]}),e.jsxs("li",{children:[e.jsx("strong",{children:"Angenommene Karte hat etwas zerschossen?"})," Meist fängt es der Auto-Revert; sonst ",e.jsx("strong",{children:"Chronik → Zeitmaschine"})," (Stand von gestern) oder Backup & ",e.jsx(s,{children:"restore.sh"}),"."]})]})})]}),e.jsx("p",{className:"text-center text-[10px] text-muted-foreground/50 pt-2",children:"Mission Control 2 · AI-Bibel · Stand Juli 2026 — lebendes Dokument, wächst mit dem Stack."})]})}export{q as GuideView}; diff --git a/frontend/dist/assets/IdeenView-DcsN5ZLB.js b/frontend/dist/assets/IdeenView-J4hS7xB2.js similarity index 99% rename from frontend/dist/assets/IdeenView-DcsN5ZLB.js rename to frontend/dist/assets/IdeenView-J4hS7xB2.js index cdf2d46..cc9c2fe 100644 --- a/frontend/dist/assets/IdeenView-DcsN5ZLB.js +++ b/frontend/dist/assets/IdeenView-J4hS7xB2.js @@ -1,4 +1,4 @@ -import{c as $,j as e,b as S,a2 as ve,u as Se,k as De,r as d,n as z,a6 as Ke,_ as O,L as D,X as Q,a7 as xe,F as T,a3 as he,C as Ce,T as ze,a4 as Ee,a8 as pe,q as Ae,R as fe}from"./index-CCbyojll.js";import{S as Le,H as X}from"./SectionLabel-BfFwUeZU.js";import{C as ee}from"./code-xml-AZtn6xxf.js";import{L as Pe}from"./layers-Dpl2QlP2.js";import{C as U}from"./chevron-down-SPeGIim5.js";import{R as We}from"./rotate-ccw-DuKtbjZS.js";/** +import{c as $,j as e,b as S,a2 as ve,u as Se,k as De,r as d,n as z,a6 as Ke,_ as O,L as D,X as Q,a7 as xe,F as T,a3 as he,C as Ce,T as ze,a4 as Ee,a8 as pe,q as Ae,R as fe}from"./index-DNt66je4.js";import{S as Le,H as X}from"./SectionLabel-DKDWJ8hi.js";import{C as ee}from"./code-xml-BiSOeCkP.js";import{L as Pe}from"./layers-BakyhGhx.js";import{C as U}from"./chevron-down-BTSzJRag.js";import{R as We}from"./rotate-ccw-CGv9dXzB.js";/** * @license lucide-react v0.460.0 - ISC * * This source code is licensed under the ISC license. diff --git a/frontend/dist/assets/JobsBar-Ckecoyqy.js b/frontend/dist/assets/JobsBar-DG8VDiAV.js similarity index 96% rename from frontend/dist/assets/JobsBar-Ckecoyqy.js rename to frontend/dist/assets/JobsBar-DG8VDiAV.js index a6bc3c4..d23d0ea 100644 --- a/frontend/dist/assets/JobsBar-Ckecoyqy.js +++ b/frontend/dist/assets/JobsBar-DG8VDiAV.js @@ -1 +1 @@ -import{u,ah as m,k as x,j as s,y as n,ai as b,b as p,n as f,q as h}from"./index-CCbyojll.js";function y(){const d=u(),{data:t=[]}=m(),{showAlert:l,dialogElement:o}=x();async function i(e){try{await f(`/api/jobs/${e}/cancel`,{method:"POST"}),d.invalidateQueries({queryKey:h.jobs})}catch(c){l("Fehler",c.message)}}const a=t.filter(e=>e.state==="running"||e.state==="queued"),r=t.filter(e=>e.state!=="running"&&e.state!=="queued").slice(-3);return a.length===0&&r.length===0?null:s.jsxs("div",{className:"space-y-3 mc-card p-4",children:[s.jsx("div",{className:"text-[11px] font-semibold text-muted-foreground uppercase tracking-wider",children:"Aktive Downloads"}),a.map(e=>s.jsxs("div",{className:"space-y-1.5 p-3 rounded-xl bg-background/20 border border-border/40",children:[s.jsxs("div",{className:"flex justify-between items-center text-xs",children:[s.jsx("span",{className:"font-semibold truncate max-w-[250px]",children:e.label}),s.jsxs("div",{className:"flex items-center gap-3",children:[s.jsxs("span",{className:"text-muted-foreground font-mono",children:[e.progress??0,"% • ",n(e.done_bytes),"/",n(e.total_bytes),e.eta_s?` • ETA ${b(e.eta_s)}`:""]}),s.jsx("button",{onClick:()=>i(e.id),className:"text-[10px] text-red-400 hover:text-red-300 font-semibold border border-red-500/25 bg-red-500/5 px-2 py-0.5 rounded transition-all cursor-pointer",children:"Abbrechen"})]})]}),s.jsx("div",{className:"h-1.5 overflow-hidden rounded-full bg-muted",children:s.jsx("div",{className:"h-full rounded-full bg-primary transition-all duration-500",style:{width:`${e.progress??0}%`}})})]},e.id)),r.map(e=>s.jsxs("div",{className:"flex justify-between items-center text-xs text-muted-foreground 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Downloads"}),a.map(e=>s.jsxs("div",{className:"space-y-1.5 p-3 rounded-xl bg-background/20 border border-border/40",children:[s.jsxs("div",{className:"flex justify-between items-center text-xs",children:[s.jsx("span",{className:"font-semibold truncate max-w-[250px]",children:e.label}),s.jsxs("div",{className:"flex items-center gap-3",children:[s.jsxs("span",{className:"text-muted-foreground font-mono",children:[e.progress??0,"% • ",n(e.done_bytes),"/",n(e.total_bytes),e.eta_s?` • ETA ${b(e.eta_s)}`:""]}),s.jsx("button",{onClick:()=>i(e.id),className:"text-[10px] text-red-400 hover:text-red-300 font-semibold border border-red-500/25 bg-red-500/5 px-2 py-0.5 rounded transition-all cursor-pointer",children:"Abbrechen"})]})]}),s.jsx("div",{className:"h-1.5 overflow-hidden rounded-full bg-muted",children:s.jsx("div",{className:"h-full rounded-full bg-primary transition-all duration-500",style:{width:`${e.progress??0}%`}})})]},e.id)),r.map(e=>s.jsxs("div",{className:"flex justify-between items-center text-xs text-muted-foreground px-1",children:[s.jsx("span",{className:"truncate",children:e.label}),s.jsx("span",{className:p("font-semibold text-[10px] px-1.5 py-0.5 rounded uppercase font-mono",e.state==="done"?"bg-emerald-500/10 text-emerald-400":"bg-amber-500/10 text-amber-400"),children:e.state})]},e.id)),o]})}export{y as J}; diff --git a/frontend/dist/assets/KonsoleView-Bdk_kJ2m.js b/frontend/dist/assets/KonsoleView-BDDotueL.js similarity index 98% rename from frontend/dist/assets/KonsoleView-Bdk_kJ2m.js rename to frontend/dist/assets/KonsoleView-BDDotueL.js index 81de75f..3307a95 100644 --- a/frontend/dist/assets/KonsoleView-Bdk_kJ2m.js +++ b/frontend/dist/assets/KonsoleView-BDDotueL.js @@ -1 +1 @@ -import{I as b,u as f,K as h,r as d,j as e,b as c,J as g,T as p,R as j,Q as N,n as v,U as w,q as x}from"./index-CCbyojll.js";function y(){const{data:s}=b(),m=f(),r=s!=null&&s.box_console_url?h(s.box_console_url):void 0,a=s==null?void 0:s.box_console_reachable,[l,o]=d.useState(!1),[i,n]=d.useState("");async function u(){o(!0),n("");try{const t=await v("/api/maintenance/restart",{method:"POST",body:JSON.stringify({service:"box-console"})});n(t.ok?"Neu gestartet — einen Moment, dann lädt das Terminal.":`Fehlgeschlagen: ${t.err||"Unbekannter Fehler"}`),w(m,x.agentStatus,x.services)}catch(t){n(`Fehlgeschlagen: ${(t==null?void 0:t.message)||t}`)}finally{o(!1)}}return e.jsxs("div",{className:"flex h-full flex-col gap-4",children:[e.jsxs("div",{className:"flex flex-wrap items-end justify-between gap-3",children:[e.jsxs("div",{children:[e.jsx("h1",{className:"bg-gradient-to-r from-foreground via-foreground to-primary bg-clip-text font-space text-2xl font-bold tracking-tight text-transparent",children:"Konsole"}),e.jsx("p",{className:"flex items-center gap-2 text-sm text-muted-foreground",children:"Direkte Shell auf der Box — wie ein SSH-Fenster, mitten im Browser."})]}),e.jsxs("div",{className:"flex items-center gap-3",children:[e.jsxs("span",{className:"flex items-center gap-1.5 text-[11px] font-medium text-muted-foreground",children:[e.jsx("span",{className:c("h-2 w-2 rounded-full",a?"bg-emerald-500 animate-pulse":"bg-amber-500")}),a?"online":"offline"]}),r&&e.jsxs("a",{href:r,target:"_blank",rel:"noopener",className:"flex h-8 items-center gap-1.5 rounded-lg border border-border/60 bg-background/20 px-3 text-xs font-semibold text-muted-foreground transition-all hover:border-primary/50 hover:text-foreground",children:[e.jsx(g,{className:"h-3.5 w-3.5"})," In neuem Tab"]})]})]}),r?e.jsxs("div",{className:"relative min-h-[58vh] flex-1 overflow-hidden rounded-2xl border border-border/60 bg-black/50 shadow-lg shadow-black/25",children:[a===!1&&e.jsxs("div",{className:"absolute inset-0 z-10 flex flex-col items-center justify-center gap-3 bg-black/70 text-center",children:[e.jsx(p,{className:"h-8 w-8 text-amber-400"}),e.jsx("div",{className:"text-sm font-semibold text-amber-300",children:"Konsole 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w-4"})," Lade Konsole…"]})]})}export{y as KonsoleView}; +import{I as b,u as f,K as h,r as d,j as e,b as c,J as g,T as p,R as j,Q as N,n as v,U as w,q as x}from"./index-DNt66je4.js";function y(){const{data:s}=b(),m=f(),r=s!=null&&s.box_console_url?h(s.box_console_url):void 0,a=s==null?void 0:s.box_console_reachable,[l,o]=d.useState(!1),[i,n]=d.useState("");async function u(){o(!0),n("");try{const t=await v("/api/maintenance/restart",{method:"POST",body:JSON.stringify({service:"box-console"})});n(t.ok?"Neu gestartet — einen Moment, dann lädt das Terminal.":`Fehlgeschlagen: ${t.err||"Unbekannter Fehler"}`),w(m,x.agentStatus,x.services)}catch(t){n(`Fehlgeschlagen: ${(t==null?void 0:t.message)||t}`)}finally{o(!1)}}return e.jsxs("div",{className:"flex h-full flex-col gap-4",children:[e.jsxs("div",{className:"flex flex-wrap items-end justify-between gap-3",children:[e.jsxs("div",{children:[e.jsx("h1",{className:"bg-gradient-to-r from-foreground via-foreground to-primary bg-clip-text 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shadow-black/25",children:[a===!1&&e.jsxs("div",{className:"absolute inset-0 z-10 flex flex-col items-center justify-center gap-3 bg-black/70 text-center",children:[e.jsx(p,{className:"h-8 w-8 text-amber-400"}),e.jsx("div",{className:"text-sm font-semibold text-amber-300",children:"Konsole nicht erreichbar"}),e.jsxs("p",{className:"max-w-sm text-[11px] leading-normal text-muted-foreground",children:["Der Terminal-Dienst (",e.jsx("code",{className:"font-mono text-primary",children:"box-console"}),") läuft gerade nicht."]}),e.jsxs("button",{onClick:u,disabled:l,className:"flex h-9 items-center gap-1.5 rounded-lg border border-amber-500/40 bg-amber-500/10 px-4 text-[11px] font-bold uppercase tracking-wide text-amber-300 transition-all hover:bg-amber-500/20 cursor-pointer disabled:opacity-50",children:[e.jsx(j,{className:c("h-3.5 w-3.5",l&&"animate-spin")})," Dienst neu starten"]}),i&&e.jsx("p",{className:"max-w-sm text-[11px] text-muted-foreground",children:i})]}),e.jsx("iframe",{src:r,title:"Box-Konsole",className:"h-full w-full border-0",style:{minHeight:"58vh"}})]}):e.jsxs("div",{className:"flex min-h-[58vh] flex-1 items-center justify-center rounded-2xl border border-border/60 bg-background/20 text-xs text-muted-foreground",children:[e.jsx(N,{className:"mr-2 h-4 w-4"})," Lade Konsole…"]})]})}export{y as KonsoleView}; diff --git a/frontend/dist/assets/ModelsView-aEV2pe9C.js b/frontend/dist/assets/ModelsView-DIBx0djl.js similarity index 99% rename from frontend/dist/assets/ModelsView-aEV2pe9C.js rename to frontend/dist/assets/ModelsView-DIBx0djl.js index 520063f..576e28e 100644 --- a/frontend/dist/assets/ModelsView-aEV2pe9C.js +++ b/frontend/dist/assets/ModelsView-DIBx0djl.js @@ -1,4 +1,4 @@ -import{c as E,u as he,a as qe,r as j,j as e,C as Y,L as Fe,b as k,d as Re,q as V,B as re,e as Ie,E as ze,f as le,g as Be,h as Ae,i as Pe,k as Ge,l as ee,X as me,H as be,T as se,s as Oe,m as Te,n as q,o as U,p as He,S as ge,t as Qe,P as Ue,v as Ve,w as We,x as Ze,y as Je}from"./index-CCbyojll.js";import{J as Xe}from"./JobsBar-Ckecoyqy.js";import{C as Ye}from"./code-xml-AZtn6xxf.js";import{R as et}from"./rotate-ccw-DuKtbjZS.js";import{C as ue,Z as ie,L as tt,a as rt}from"./zap-CRNNnxfs.js";import{C as De}from"./chevron-down-SPeGIim5.js";import{L as st}from"./layers-Dpl2QlP2.js";/** +import{c as E,u as he,a as qe,r as j,j as e,C as Y,L as Fe,b as k,d as Re,q as V,B as re,e as Ie,E as ze,f as le,g as Be,h as Ae,i as Pe,k as Ge,l as ee,X as me,H as be,T as se,s as Oe,m as Te,n as q,o as U,p as He,S as ge,t as Qe,P as Ue,v as Ve,w as We,x as Ze,y as Je}from"./index-DNt66je4.js";import{J as Xe}from"./JobsBar-DG8VDiAV.js";import{C as Ye}from"./code-xml-BiSOeCkP.js";import{R as et}from"./rotate-ccw-CGv9dXzB.js";import{C as ue,Z as ie,L as tt,a as rt}from"./zap-cdYTHDpR.js";import{C as De}from"./chevron-down-BTSzJRag.js";import{L as st}from"./layers-BakyhGhx.js";/** * @license lucide-react v0.460.0 - ISC * * This source code is licensed under the ISC license. diff --git a/frontend/dist/assets/SectionLabel-BfFwUeZU.js b/frontend/dist/assets/SectionLabel-DKDWJ8hi.js similarity index 93% rename from frontend/dist/assets/SectionLabel-BfFwUeZU.js rename to frontend/dist/assets/SectionLabel-DKDWJ8hi.js index 7de42bc..fd82ff2 100644 --- a/frontend/dist/assets/SectionLabel-BfFwUeZU.js +++ b/frontend/dist/assets/SectionLabel-DKDWJ8hi.js @@ -1,4 +1,4 @@ -import{c as s,j as e}from"./index-CCbyojll.js";/** +import{c as s,j as e}from"./index-DNt66je4.js";/** * @license lucide-react v0.460.0 - ISC * * This source code is licensed under the ISC license. diff --git a/frontend/dist/assets/SkillsView-C5D9xEVH.js b/frontend/dist/assets/SkillsView-XWoP6WFO.js similarity index 98% rename from frontend/dist/assets/SkillsView-C5D9xEVH.js rename to frontend/dist/assets/SkillsView-XWoP6WFO.js index ccf7c7e..c15a3f7 100644 --- a/frontend/dist/assets/SkillsView-C5D9xEVH.js +++ b/frontend/dist/assets/SkillsView-XWoP6WFO.js @@ -1,4 +1,4 @@ -var M=r=>{throw TypeError(r)};var O=(r,e,t)=>e.has(r)||M("Cannot "+t);var a=(r,e,t)=>(O(r,e,"read from private field"),t?t.call(r):e.get(r)),y=(r,e,t)=>e.has(r)?M("Cannot add the same private member more than once"):e instanceof WeakSet?e.add(r):e.set(r,t),v=(r,e,t,n)=>(O(r,e,"write to private field"),n?n.call(r,t):e.set(r,t),t),j=(r,e,t)=>(O(r,e,"access private method"),t);import{a9 as B,aa as F,ab as E,ac as I,ad as P,u as A,r as f,ae as J,af as Q,c as T,ag as U,j as s,G as D,T as H,b as K,L,M as G,q as V,n as R}from"./index-CCbyojll.js";import{J as _}from"./JobsBar-Ckecoyqy.js";var c,g,o,h,m,w,C,q,z=(q=class extends B{constructor(e,t){super();y(this,m);y(this,c);y(this,g);y(this,o);y(this,h);v(this,c,e),this.setOptions(t),this.bindMethods(),j(this,m,w).call(this)}bindMethods(){this.mutate=this.mutate.bind(this),this.reset=this.reset.bind(this)}setOptions(e){var n;const 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B{constructor(e,t){super();y(this,m);y(this,c);y(this,g);y(this,o);y(this,h);v(this,c,e),this.setOptions(t),this.bindMethods(),j(this,m,w).call(this)}bindMethods(){this.mutate=this.mutate.bind(this),this.reset=this.reset.bind(this)}setOptions(e){var n;const t=this.options;this.options=a(this,c).defaultMutationOptions(e),F(this.options,t)||a(this,c).getMutationCache().notify({type:"observerOptionsUpdated",mutation:a(this,o),observer:this}),t!=null&&t.mutationKey&&this.options.mutationKey&&E(t.mutationKey)!==E(this.options.mutationKey)?this.reset():((n=a(this,o))==null?void 0:n.state.status)==="pending"&&a(this,o).setOptions(this.options)}onUnsubscribe(){var e;this.hasListeners()||(e=a(this,o))==null||e.removeObserver(this)}onMutationUpdate(e){j(this,m,w).call(this),j(this,m,C).call(this,e)}getCurrentResult(){return a(this,g)}reset(){var e;(e=a(this,o))==null||e.removeObserver(this),v(this,o,void 0),j(this,m,w).call(this),j(this,m,C).call(this)}mutate(e,t){var n;return v(this,h,t),(n=a(this,o))==null||n.removeObserver(this),v(this,o,a(this,c).getMutationCache().build(a(this,c),this.options)),a(this,o).addObserver(this),a(this,o).execute(e)}},c=new WeakMap,g=new WeakMap,o=new WeakMap,h=new WeakMap,m=new WeakSet,w=function(){var t;const e=((t=a(this,o))==null?void 0:t.state)??I();v(this,g,{...e,isPending:e.status==="pending",isSuccess:e.status==="success",isError:e.status==="error",isIdle:e.status==="idle",mutate:this.mutate,reset:this.reset})},C=function(e){P.batch(()=>{var t,n,l,x,d,p,k,i;if(a(this,h)&&this.hasListeners()){const u=a(this,g).variables,N=a(this,g).context,S={client:a(this,c),meta:this.options.meta,mutationKey:this.options.mutationKey};if((e==null?void 0:e.type)==="success"){try{(n=(t=a(this,h)).onSuccess)==null||n.call(t,e.data,u,N,S)}catch(b){Promise.reject(b)}try{(x=(l=a(this,h)).onSettled)==null||x.call(l,e.data,null,u,N,S)}catch(b){Promise.reject(b)}}else if((e==null?void 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a.startsWith("**")&&a.endsWith("**")?$.jsx("b",{className:"font-semibold text-foreground",children:a.slice(2,-2)},u):a.startsWith("*")&&a.endsWith("*")&&a.length>2?$.jsx("i",{children:a.slice(1,-1)},u):a.startsWith("`")&&a.endsWith("`")?$.jsx("code",{className:"rounded bg-background/50 px-1 font-mono text-[11px] text-teal-300",children:a.slice(1,-1)},u):$.jsx("span",{children:a},u)})}export{td as WissenView}; diff --git a/frontend/dist/assets/chevron-down-SPeGIim5.js b/frontend/dist/assets/chevron-down-BTSzJRag.js similarity index 85% rename from frontend/dist/assets/chevron-down-SPeGIim5.js rename to frontend/dist/assets/chevron-down-BTSzJRag.js index 3810e19..8478937 100644 --- a/frontend/dist/assets/chevron-down-SPeGIim5.js +++ b/frontend/dist/assets/chevron-down-BTSzJRag.js @@ -1,4 +1,4 @@ -import{c as o}from"./index-CCbyojll.js";/** +import{c as o}from"./index-DNt66je4.js";/** * @license lucide-react v0.460.0 - ISC * * This source code is licensed under the ISC license. diff --git a/frontend/dist/assets/code-xml-AZtn6xxf.js b/frontend/dist/assets/code-xml-BiSOeCkP.js similarity index 88% rename from frontend/dist/assets/code-xml-AZtn6xxf.js rename to frontend/dist/assets/code-xml-BiSOeCkP.js index 1048eb4..4dc8a4a 100644 --- a/frontend/dist/assets/code-xml-AZtn6xxf.js +++ b/frontend/dist/assets/code-xml-BiSOeCkP.js @@ -1,4 +1,4 @@ -import{c as e}from"./index-CCbyojll.js";/** +import{c as e}from"./index-DNt66je4.js";/** * @license lucide-react v0.460.0 - ISC * * This source code is licensed under the ISC license. diff --git a/frontend/dist/assets/folder-open-FZLk16T9.js b/frontend/dist/assets/folder-open-FZLk16T9.js deleted file mode 100644 index 089d177..0000000 --- a/frontend/dist/assets/folder-open-FZLk16T9.js +++ /dev/null @@ -1,6 +0,0 @@ -import{c as a}from"./index-CCbyojll.js";/** - * @license lucide-react v0.460.0 - ISC - * - * This source code is licensed under the ISC license. - * See the LICENSE file in the root directory of this source tree. - */const 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this.options.refetchInterval=="function"?this.options.refetchInterval($(this,Be)):this.options.refetchInterval)??!1},wv=function(t){Le(this,Ve,Ev).call(this),pe(this,Hi,t),!(qs.isServer()||Er(this.options.enabled,$(this,Be))===!1||!hv($(this,Hi))||$(this,Hi)===0)&&pe(this,$a,ka.setInterval(()=>{(this.options.refetchIntervalInBackground||Ry.isFocused())&&Le(this,Ve,$s).call(this)},$(this,Hi)))},Sv=function(){Le(this,Ve,xv).call(this),Le(this,Ve,wv).call(this,Le(this,Ve,bv).call(this))},kv=function(){$(this,Ra)!==void 0&&(ka.clearTimeout($(this,Ra)),pe(this,Ra,void 0))},Ev=function(){$(this,$a)!==void 0&&(ka.clearInterval($(this,$a)),pe(this,$a,void 0))},Pv=function(){const t=$(this,hr).getQueryCache().build($(this,hr),this.options);if(t===$(this,Be))return;const r=$(this,Be);pe(this,Be,t),pe(this,mu,t.state),this.hasListeners()&&(r==null||r.removeObserver(this),t.addObserver(this))},TP=function(t){Ft.batch(()=>{t.listeners&&this.listeners.forEach(r=>{r($(this,tr))}),$(this,hr).getQueryCache().notify({query:$(this,Be),type:"observerResultsUpdated"})})},xP);function SM(e,t){return Er(t.enabled,e)!==!1&&e.state.data===void 0&&!(e.state.status==="error"&&Er(t.retryOnMount,e)===!1)}function $1(e,t){return SM(e,t)||e.state.data!==void 0&&Av(e,t,t.refetchOnMount)}function Av(e,t,r){if(Er(t.enabled,e)!==!1&&Yi(t.staleTime,e)!=="static"){const n=typeof r=="function"?r(e):r;return n==="always"||n!==!1&&zy(e,t)}return!1}function L1(e,t,r,n){return(e!==t||Er(n.enabled,e)===!1)&&(!r.suspense||e.state.status!=="error")&&zy(e,r)}function zy(e,t){return Er(t.enabled,e)!==!1&&e.isStaleByTime(Yi(t.staleTime,e))}function kM(e,t){return!pv(e.getCurrentResult(),t)}var yu,xn,Yt,La,bn,Di,bP,EM=(bP=class extends NP{constructor(t){super();Ce(this,bn);Ce(this,yu);Ce(this,xn);Ce(this,Yt);Ce(this,La);pe(this,yu,t.client),this.mutationId=t.mutationId,pe(this,Yt,t.mutationCache),pe(this,xn,[]),this.state=t.state||PM(),this.setOptions(t.options),this.scheduleGc()}setOptions(t){this.options=t,this.updateGcTime(this.options.gcTime)}get meta(){return this.options.meta}addObserver(t){$(this,xn).includes(t)||($(this,xn).push(t),this.clearGcTimeout(),$(this,Yt).notify({type:"observerAdded",mutation:this,observer:t}))}removeObserver(t){pe(this,xn,$(this,xn).filter(r=>r!==t)),this.scheduleGc(),$(this,Yt).notify({type:"observerRemoved",mutation:this,observer:t})}optionalRemove(){$(this,xn).length||(this.state.status==="pending"?this.scheduleGc():$(this,Yt).remove(this))}continue(){var t;return((t=$(this,La))==null?void 0:t.continue())??this.execute(this.state.variables)}async execute(t){var s,u,d,f,h,m,v,x,k,S,E,P,O,j,_,N,C,D;const r=()=>{Le(this,bn,Di).call(this,{type:"continue"})},n={client:$(this,yu),meta:this.options.meta,mutationKey:this.options.mutationKey};pe(this,La,jP({fn:()=>this.options.mutationFn?this.options.mutationFn(t,n):Promise.reject(new Error("No mutationFn found")),onFail:(F,z)=>{Le(this,bn,Di).call(this,{type:"failed",failureCount:F,error:z})},onPause:()=>{Le(this,bn,Di).call(this,{type:"pause"})},onContinue:r,retry:this.options.retry??0,retryDelay:this.options.retryDelay,networkMode:this.options.networkMode,canRun:()=>$(this,Yt).canRun(this)}));const i=this.state.status==="pending",o=!$(this,La).canStart();try{if(i)r();else{Le(this,bn,Di).call(this,{type:"pending",variables:t,isPaused:o}),$(this,Yt).config.onMutate&&await $(this,Yt).config.onMutate(t,this,n);const z=await((u=(s=this.options).onMutate)==null?void 0:u.call(s,t,n));z!==this.state.context&&Le(this,bn,Di).call(this,{type:"pending",context:z,variables:t,isPaused:o})}const F=await $(this,La).start();return await((f=(d=$(this,Yt).config).onSuccess)==null?void 0:f.call(d,F,t,this.state.context,this,n)),await((m=(h=this.options).onSuccess)==null?void 0:m.call(h,F,t,this.state.context,n)),await((x=(v=$(this,Yt).config).onSettled)==null?void 0:x.call(v,F,null,this.state.variables,this.state.context,this,n)),await((S=(k=this.options).onSettled)==null?void 0:S.call(k,F,null,t,this.state.context,n)),Le(this,bn,Di).call(this,{type:"success",data:F}),F}catch(F){try{await((P=(E=$(this,Yt).config).onError)==null?void 0:P.call(E,F,t,this.state.context,this,n))}catch(z){Promise.reject(z)}try{await((j=(O=this.options).onError)==null?void 0:j.call(O,F,t,this.state.context,n))}catch(z){Promise.reject(z)}try{await((N=(_=$(this,Yt).config).onSettled)==null?void 0:N.call(_,void 0,F,this.state.variables,this.state.context,this,n))}catch(z){Promise.reject(z)}try{await((D=(C=this.options).onSettled)==null?void 0:D.call(C,void 0,F,t,this.state.context,n))}catch(z){Promise.reject(z)}throw Le(this,bn,Di).call(this,{type:"error",error:F}),F}finally{$(this,Yt).runNext(this)}}},yu=new WeakMap,xn=new WeakMap,Yt=new WeakMap,La=new WeakMap,bn=new WeakSet,Di=function(t){const r=n=>{switch(t.type){case"failed":return{...n,failureCount:t.failureCount,failureReason:t.error};case"pause":return{...n,isPaused:!0};case"continue":return{...n,isPaused:!1};case"pending":return{...n,context:t.context,data:void 0,failureCount:0,failureReason:null,error:null,isPaused:t.isPaused,status:"pending",variables:t.variables,submittedAt:Date.now()};case"success":return{...n,data:t.data,failureCount:0,failureReason:null,error:null,status:"success",isPaused:!1};case"error":return{...n,data:void 0,error:t.error,failureCount:n.failureCount+1,failureReason:t.error,isPaused:!1,status:"error"}}};this.state=r(this.state),Ft.batch(()=>{$(this,xn).forEach(n=>{n.onMutationUpdate(t)}),$(this,Yt).notify({mutation:this,type:"updated",action:t})})},bP);function PM(){return{context:void 0,data:void 0,error:null,failureCount:0,failureReason:null,isPaused:!1,status:"idle",variables:void 0,submittedAt:0}}var qn,tn,gu,wP,AM=(wP=class extends xu{constructor(t={}){super();Ce(this,qn);Ce(this,tn);Ce(this,gu);this.config=t,pe(this,qn,new Set),pe(this,tn,new Map),pe(this,gu,0)}build(t,r,n){const i=new EM({client:t,mutationCache:this,mutationId:++Kc(this,gu)._,options:t.defaultMutationOptions(r),state:n});return this.add(i),i}add(t){$(this,qn).add(t);const r=qc(t);if(typeof r=="string"){const n=$(this,tn).get(r);n?n.push(t):$(this,tn).set(r,[t])}this.notify({type:"added",mutation:t})}remove(t){if($(this,qn).delete(t)){const r=qc(t);if(typeof r=="string"){const n=$(this,tn).get(r);if(n)if(n.length>1){const i=n.indexOf(t);i!==-1&&n.splice(i,1)}else n[0]===t&&$(this,tn).delete(r)}}this.notify({type:"removed",mutation:t})}canRun(t){const r=qc(t);if(typeof r=="string"){const n=$(this,tn).get(r),i=n==null?void 0:n.find(o=>o.state.status==="pending");return!i||i===t}else return!0}runNext(t){var 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s||(s=new bM({client:t,queryKey:i,queryHash:o,options:t.defaultQueryOptions(r),state:n,defaultOptions:t.getQueryDefaults(i)}),this.add(s)),s}add(t){$(this,wn).has(t.queryHash)||($(this,wn).set(t.queryHash,t),this.notify({type:"added",query:t}))}remove(t){const r=$(this,wn).get(t.queryHash);r&&(t.destroy(),r===t&&$(this,wn).delete(t.queryHash),this.notify({type:"removed",query:t}))}clear(){Ft.batch(()=>{this.getAll().forEach(t=>{this.remove(t)})})}get(t){return $(this,wn).get(t)}getAll(){return[...$(this,wn).values()]}find(t){const r={exact:!0,...t};return this.getAll().find(n=>j1(r,n))}findAll(t={}){const r=this.getAll();return Object.keys(t).length>0?r.filter(n=>j1(t,n)):r}notify(t){Ft.batch(()=>{this.listeners.forEach(r=>{r(t)})})}onFocus(){Ft.batch(()=>{this.getAll().forEach(t=>{t.onFocus()})})}onOnline(){Ft.batch(()=>{this.getAll().forEach(t=>{t.onOnline()})})}},wn=new WeakMap,SP),dt,Ki,Vi,ol,ll,qi,sl,ul,kP,CM=(kP=class{constructor(e={}){Ce(this,dt);Ce(this,Ki);Ce(this,Vi);Ce(this,ol);Ce(this,ll);Ce(this,qi);Ce(this,sl);Ce(this,ul);pe(this,dt,e.queryCache||new OM),pe(this,Ki,e.mutationCache||new AM),pe(this,Vi,e.defaultOptions||{}),pe(this,ol,new Map),pe(this,ll,new Map),pe(this,qi,0)}mount(){Kc(this,qi)._++,$(this,qi)===1&&(pe(this,sl,Ry.subscribe(async e=>{e&&(await this.resumePausedMutations(),$(this,dt).onFocus())})),pe(this,ul,Od.subscribe(async e=>{e&&(await this.resumePausedMutations(),$(this,dt).onOnline())})))}unmount(){var e,t;Kc(this,qi)._--,$(this,qi)===0&&((e=$(this,sl))==null||e.call(this),pe(this,sl,void 0),(t=$(this,ul))==null||t.call(this),pe(this,ul,void 0))}isFetching(e){return $(this,dt).findAll({...e,fetchStatus:"fetching"}).length}isMutating(e){return $(this,Ki).findAll({...e,status:"pending"}).length}getQueryData(e){var r;const t=this.defaultQueryOptions({queryKey:e});return(r=$(this,dt).get(t.queryHash))==null?void 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r.isStaleByTime(Yi(t.staleTime,r))?r.fetch(t):Promise.resolve(r.state.data)}prefetchQuery(e){return this.fetchQuery(e).then(pr).catch(pr)}fetchInfiniteQuery(e){return e._type="infinite",this.fetchQuery(e)}prefetchInfiniteQuery(e){return this.fetchInfiniteQuery(e).then(pr).catch(pr)}ensureInfiniteQueryData(e){return e._type="infinite",this.ensureQueryData(e)}resumePausedMutations(){return Od.isOnline()?$(this,Ki).resumePausedMutations():Promise.resolve()}getQueryCache(){return $(this,dt)}getMutationCache(){return $(this,Ki)}getDefaultOptions(){return $(this,Vi)}setDefaultOptions(e){pe(this,Vi,e)}setQueryDefaults(e,t){$(this,ol).set(Ks(e),{queryKey:e,defaultOptions:t})}getQueryDefaults(e){const t=[...$(this,ol).values()],r={};return t.forEach(n=>{Vs(e,n.queryKey)&&Object.assign(r,n.defaultOptions)}),r}setMutationDefaults(e,t){$(this,ll).set(Ks(e),{mutationKey:e,defaultOptions:t})}getMutationDefaults(e){const t=[...$(this,ll).values()],r={};return 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Proxy(t,{get:(n,i)=>(this.trackProp(i),r==null||r(i),i==="promise"&&(this.trackProp("data"),!this.options.experimental_prefetchInRender&&$(this,Vn).status==="pending"&&$(this,Vn).reject(new Error("experimental_prefetchInRender feature flag is not enabled"))),Reflect.get(n,i))})}trackProp(t){$(this,il).add(t)}getCurrentQuery(){return $(this,Be)}refetch({...t}={}){return this.fetch({...t})}fetchOptimistic(t){const r=$(this,hr).defaultQueryOptions(t),n=$(this,hr).getQueryCache().build($(this,hr),r);return n.fetch().then(()=>this.createResult(n,r))}fetch(t){return Le(this,Ve,Rs).call(this,{...t,cancelRefetch:t.cancelRefetch??!0}).then(()=>(this.updateResult(),$(this,tr)))}createResult(t,r){var z;const n=$(this,Be),i=this.options,o=$(this,tr),s=$(this,Ta),u=$(this,tl),f=t!==n?t.state:$(this,mu),{state:h}=t;let m={...h},v=!1,x;if(r._optimisticResults){const q=this.hasListeners(),X=!q&&$1(t,r),B=q&&L1(t,n,r,i);(X||B)&&(m={...m,...MP(h.data,t.options)}),r._optimisticResults==="isRestoring"&&(m.fetchStatus="idle")}let{error:k,errorUpdatedAt:S,status:E}=m;x=m.data;let P=!1;if(r.placeholderData!==void 0&&x===void 0&&E==="pending"){let q;o!=null&&o.isPlaceholderData&&r.placeholderData===(u==null?void 0:u.placeholderData)?(q=o.data,P=!0):q=typeof r.placeholderData=="function"?r.placeholderData((z=$(this,nl))==null?void 0:z.state.data,$(this,nl)):r.placeholderData,q!==void 0&&(E="success",x=vv(o==null?void 0:o.data,q,r),v=!0)}if(r.select&&x!==void 0&&!P)if(o&&x===(s==null?void 0:s.data)&&r.select===$(this,vu))x=$(this,rl);else try{pe(this,vu,r.select),x=r.select(x),x=vv(o==null?void 0:o.data,x,r),pe(this,rl,x),pe(this,Wi,null)}catch(q){pe(this,Wi,q)}$(this,Wi)&&(k=$(this,Wi),x=$(this,rl),S=Date.now(),E="error");const O=m.fetchStatus==="fetching",j=E==="pending",_=E==="error",N=j&&O,C=x!==void 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this.options.refetchInterval=="function"?this.options.refetchInterval($(this,Be)):this.options.refetchInterval)??!1},wv=function(t){Le(this,Ve,Ev).call(this),pe(this,Hi,t),!(qs.isServer()||Er(this.options.enabled,$(this,Be))===!1||!hv($(this,Hi))||$(this,Hi)===0)&&pe(this,Ra,ka.setInterval(()=>{(this.options.refetchIntervalInBackground||Ry.isFocused())&&Le(this,Ve,Rs).call(this)},$(this,Hi)))},Sv=function(){Le(this,Ve,xv).call(this),Le(this,Ve,wv).call(this,Le(this,Ve,bv).call(this))},kv=function(){$(this,Da)!==void 0&&(ka.clearTimeout($(this,Da)),pe(this,Da,void 0))},Ev=function(){$(this,Ra)!==void 0&&(ka.clearInterval($(this,Ra)),pe(this,Ra,void 0))},Pv=function(){const t=$(this,hr).getQueryCache().build($(this,hr),this.options);if(t===$(this,Be))return;const r=$(this,Be);pe(this,Be,t),pe(this,mu,t.state),this.hasListeners()&&(r==null||r.removeObserver(this),t.addObserver(this))},TP=function(t){Ft.batch(()=>{t.listeners&&this.listeners.forEach(r=>{r($(this,tr))}),$(this,hr).getQueryCache().notify({query:$(this,Be),type:"observerResultsUpdated"})})},xP);function SM(e,t){return Er(t.enabled,e)!==!1&&e.state.data===void 0&&!(e.state.status==="error"&&Er(t.retryOnMount,e)===!1)}function $1(e,t){return SM(e,t)||e.state.data!==void 0&&Av(e,t,t.refetchOnMount)}function Av(e,t,r){if(Er(t.enabled,e)!==!1&&Yi(t.staleTime,e)!=="static"){const n=typeof r=="function"?r(e):r;return n==="always"||n!==!1&&zy(e,t)}return!1}function L1(e,t,r,n){return(e!==t||Er(n.enabled,e)===!1)&&(!r.suspense||e.state.status!=="error")&&zy(e,r)}function zy(e,t){return Er(t.enabled,e)!==!1&&e.isStaleByTime(Yi(t.staleTime,e))}function kM(e,t){return!pv(e.getCurrentResult(),t)}var yu,xn,Yt,$a,bn,Di,bP,EM=(bP=class extends NP{constructor(t){super();Ce(this,bn);Ce(this,yu);Ce(this,xn);Ce(this,Yt);Ce(this,$a);pe(this,yu,t.client),this.mutationId=t.mutationId,pe(this,Yt,t.mutationCache),pe(this,xn,[]),this.state=t.state||PM(),this.setOptions(t.options),this.scheduleGc()}setOptions(t){this.options=t,this.updateGcTime(this.options.gcTime)}get meta(){return this.options.meta}addObserver(t){$(this,xn).includes(t)||($(this,xn).push(t),this.clearGcTimeout(),$(this,Yt).notify({type:"observerAdded",mutation:this,observer:t}))}removeObserver(t){pe(this,xn,$(this,xn).filter(r=>r!==t)),this.scheduleGc(),$(this,Yt).notify({type:"observerRemoved",mutation:this,observer:t})}optionalRemove(){$(this,xn).length||(this.state.status==="pending"?this.scheduleGc():$(this,Yt).remove(this))}continue(){var t;return((t=$(this,$a))==null?void 0:t.continue())??this.execute(this.state.variables)}async execute(t){var s,u,d,f,h,m,v,x,k,S,E,P,O,j,_,N,C,D;const 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await((f=(d=$(this,Yt).config).onSuccess)==null?void 0:f.call(d,F,t,this.state.context,this,n)),await((m=(h=this.options).onSuccess)==null?void 0:m.call(h,F,t,this.state.context,n)),await((x=(v=$(this,Yt).config).onSettled)==null?void 0:x.call(v,F,null,this.state.variables,this.state.context,this,n)),await((S=(k=this.options).onSettled)==null?void 0:S.call(k,F,null,t,this.state.context,n)),Le(this,bn,Di).call(this,{type:"success",data:F}),F}catch(F){try{await((P=(E=$(this,Yt).config).onError)==null?void 0:P.call(E,F,t,this.state.context,this,n))}catch(z){Promise.reject(z)}try{await((j=(O=this.options).onError)==null?void 0:j.call(O,F,t,this.state.context,n))}catch(z){Promise.reject(z)}try{await((N=(_=$(this,Yt).config).onSettled)==null?void 0:N.call(_,void 0,F,this.state.variables,this.state.context,this,n))}catch(z){Promise.reject(z)}try{await((D=(C=this.options).onSettled)==null?void 0:D.call(C,void 0,F,t,this.state.context,n))}catch(z){Promise.reject(z)}throw 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n;const r=qc(t);if(typeof r=="string"){const i=(n=$(this,tn).get(r))==null?void 0:n.find(o=>o!==t&&o.state.isPaused);return(i==null?void 0:i.continue())??Promise.resolve()}else return Promise.resolve()}clear(){Ft.batch(()=>{$(this,qn).forEach(t=>{this.notify({type:"removed",mutation:t})}),$(this,qn).clear(),$(this,tn).clear()})}getAll(){return Array.from($(this,qn))}find(t){const r={exact:!0,...t};return this.getAll().find(n=>N1(r,n))}findAll(t={}){return this.getAll().filter(r=>N1(t,r))}notify(t){Ft.batch(()=>{this.listeners.forEach(r=>{r(t)})})}resumePausedMutations(){const t=this.getAll().filter(r=>r.state.isPaused);return Ft.batch(()=>Promise.all(t.map(r=>r.continue().catch(pr))))}},qn=new WeakMap,tn=new WeakMap,gu=new WeakMap,wP);function qc(e){var t;return(t=e.options.scope)==null?void 0:t.id}var wn,SP,OM=(SP=class extends xu{constructor(t={}){super();Ce(this,wn);this.config=t,pe(this,wn,new Map)}build(t,r,n){const i=r.queryKey,o=r.queryHash??$y(i,r);let s=this.get(o);return s||(s=new bM({client:t,queryKey:i,queryHash:o,options:t.defaultQueryOptions(r),state:n,defaultOptions:t.getQueryDefaults(i)}),this.add(s)),s}add(t){$(this,wn).has(t.queryHash)||($(this,wn).set(t.queryHash,t),this.notify({type:"added",query:t}))}remove(t){const r=$(this,wn).get(t.queryHash);r&&(t.destroy(),r===t&&$(this,wn).delete(t.queryHash),this.notify({type:"removed",query:t}))}clear(){Ft.batch(()=>{this.getAll().forEach(t=>{this.remove(t)})})}get(t){return $(this,wn).get(t)}getAll(){return[...$(this,wn).values()]}find(t){const r={exact:!0,...t};return this.getAll().find(n=>j1(r,n))}findAll(t={}){const r=this.getAll();return Object.keys(t).length>0?r.filter(n=>j1(t,n)):r}notify(t){Ft.batch(()=>{this.listeners.forEach(r=>{r(t)})})}onFocus(){Ft.batch(()=>{this.getAll().forEach(t=>{t.onFocus()})})}onOnline(){Ft.batch(()=>{this.getAll().forEach(t=>{t.onOnline()})})}},wn=new WeakMap,SP),dt,Ki,Vi,al,ol,qi,ll,sl,kP,CM=(kP=class{constructor(e={}){Ce(this,dt);Ce(this,Ki);Ce(this,Vi);Ce(this,al);Ce(this,ol);Ce(this,qi);Ce(this,ll);Ce(this,sl);pe(this,dt,e.queryCache||new OM),pe(this,Ki,e.mutationCache||new AM),pe(this,Vi,e.defaultOptions||{}),pe(this,al,new Map),pe(this,ol,new Map),pe(this,qi,0)}mount(){Kc(this,qi)._++,$(this,qi)===1&&(pe(this,ll,Ry.subscribe(async e=>{e&&(await this.resumePausedMutations(),$(this,dt).onFocus())})),pe(this,sl,Od.subscribe(async e=>{e&&(await this.resumePausedMutations(),$(this,dt).onOnline())})))}unmount(){var e,t;Kc(this,qi)._--,$(this,qi)===0&&((e=$(this,ll))==null||e.call(this),pe(this,ll,void 0),(t=$(this,sl))==null||t.call(this),pe(this,sl,void 0))}isFetching(e){return $(this,dt).findAll({...e,fetchStatus:"fetching"}).length}isMutating(e){return $(this,Ki).findAll({...e,status:"pending"}).length}getQueryData(e){var r;const t=this.defaultQueryOptions({queryKey:e});return(r=$(this,dt).get(t.queryHash))==null?void 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v0.460.0 - ISC * * This source code is licensed under the ISC license. @@ -248,7 +248,7 @@ Error generating stack: `+b.message+` * * This source code is licensed under the ISC license. * See the LICENSE file in the root directory of this source tree. - */const Ho=je("RefreshCw",[["path",{d:"M3 12a9 9 0 0 1 9-9 9.75 9.75 0 0 1 6.74 2.74L21 8",key:"v9h5vc"}],["path",{d:"M21 3v5h-5",key:"1q7to0"}],["path",{d:"M21 12a9 9 0 0 1-9 9 9.75 9.75 0 0 1-6.74-2.74L3 16",key:"3uifl3"}],["path",{d:"M8 16H3v5",key:"1cv678"}]]);/** + */const Wo=je("RefreshCw",[["path",{d:"M3 12a9 9 0 0 1 9-9 9.75 9.75 0 0 1 6.74 2.74L21 8",key:"v9h5vc"}],["path",{d:"M21 3v5h-5",key:"1q7to0"}],["path",{d:"M21 12a9 9 0 0 1-9 9 9.75 9.75 0 0 1-6.74-2.74L3 16",key:"3uifl3"}],["path",{d:"M8 16H3v5",key:"1cv678"}]]);/** * @license lucide-react v0.460.0 - ISC * * This source code is licensed under the ISC license. @@ -313,12 +313,12 @@ Error generating stack: `+b.message+` * * This source code is licensed under the ISC 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--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}@property --tw-duration{syntax:"*";inherits:false}@property --tw-ease{syntax:"*";inherits:false}@keyframes spin{to{transform:rotate(360deg)}}@keyframes ping{75%,to{opacity:0;transform:scale(2)}}@keyframes pulse{50%{opacity:.5}} diff --git a/frontend/dist/assets/layers-Dpl2QlP2.js b/frontend/dist/assets/layers-BakyhGhx.js similarity index 91% rename from frontend/dist/assets/layers-Dpl2QlP2.js rename to frontend/dist/assets/layers-BakyhGhx.js index 40beed4..0ecd600 100644 --- a/frontend/dist/assets/layers-Dpl2QlP2.js +++ b/frontend/dist/assets/layers-BakyhGhx.js @@ -1,4 +1,4 @@ -import{c as a}from"./index-CCbyojll.js";/** +import{c as a}from"./index-DNt66je4.js";/** * @license lucide-react v0.460.0 - ISC * * This source code is licensed under the ISC license. diff --git a/frontend/dist/assets/rotate-ccw-DuKtbjZS.js b/frontend/dist/assets/rotate-ccw-CGv9dXzB.js similarity index 88% rename from frontend/dist/assets/rotate-ccw-DuKtbjZS.js rename to frontend/dist/assets/rotate-ccw-CGv9dXzB.js index a9bc819..ae6f088 100644 --- a/frontend/dist/assets/rotate-ccw-DuKtbjZS.js +++ b/frontend/dist/assets/rotate-ccw-CGv9dXzB.js @@ -1,4 +1,4 @@ -import{c as t}from"./index-CCbyojll.js";/** +import{c as t}from"./index-DNt66je4.js";/** * @license lucide-react v0.460.0 - ISC * * This source code is licensed under the ISC license. diff --git a/frontend/dist/assets/zap-CRNNnxfs.js b/frontend/dist/assets/zap-cdYTHDpR.js similarity index 96% rename from frontend/dist/assets/zap-CRNNnxfs.js rename to frontend/dist/assets/zap-cdYTHDpR.js index e9237de..fa4a351 100644 --- a/frontend/dist/assets/zap-CRNNnxfs.js +++ b/frontend/dist/assets/zap-cdYTHDpR.js @@ -1,4 +1,4 @@ -import{c as a}from"./index-CCbyojll.js";/** +import{c as a}from"./index-DNt66je4.js";/** * @license lucide-react v0.460.0 - ISC * * This source code is licensed under the ISC license. diff --git a/frontend/dist/index.html b/frontend/dist/index.html index 7fc1a0b..a99ace4 100644 --- a/frontend/dist/index.html +++ b/frontend/dist/index.html @@ -7,8 +7,8 @@ Mission Control 2.0 - - + +
diff --git a/frontend/src/components/dashboard/LatencyCard.tsx b/frontend/src/components/dashboard/LatencyCard.tsx index 3cbc1ba..357a57f 100644 --- a/frontend/src/components/dashboard/LatencyCard.tsx +++ b/frontend/src/components/dashboard/LatencyCard.tsx @@ -2,8 +2,8 @@ import { Gauge } from "lucide-react" import { useVoiceTrace } from "@/lib/queries" import type { VoiceTurn } from "@/lib/api" -// Balken-Stufen in kanonischer Reihenfolge (zeitlich disjunkt). Mem0 ist ein Unter-Detail -// INNERHALB von „Hirn" und wird NICHT als eigenes Segment addiert (sonst Doppelzählung). +// Balken-Stufen in kanonischer Reihenfolge (zeitlich disjunkt). Der Gedächtnis-Abruf läuft +// Hermes-intern und ist für MC2 nicht messbar — er steckt in „Hirn". const SEGMENTS = [ { key: "stt_ms", label: "STT", color: "#f59e0b" }, { key: "vision_ms", label: "Sehen", color: "#a78bfa" }, @@ -39,7 +39,6 @@ function culprit(t: VoiceTurn): { label: string; color: string; ms: number } | n function TurnRow({ t, scale }: { t: VoiceTurn; scale: number }) { const title = SEGMENTS.map((s) => `${s.label} ${fmt(t[s.key] as number | null)}`).join(" · ") - + (t.mem0_ms != null ? ` (davon Gedächtnis ${fmt(t.mem0_ms)})` : "") return (
{ago(t.ts)} @@ -103,7 +102,6 @@ export function LatencyCard() { {latest && !latest.error && (
{SEGMENTS.filter((s) => (latest[s.key] as number | null) != null).map((s) => `${s.label} ${fmt(latest[s.key] as number)}`).join(" · ")} - {latest.mem0_ms != null && · davon Gedächtnis {fmt(latest.mem0_ms)}}
)}
@@ -128,7 +126,7 @@ export function LatencyCard() { )}
- „Hirn" = Zeit bis zum ersten Wort (Agent + Mem0-Suche + Modell); Tool-Runden stecken in „Antwort". Reine + „Hirn" = Zeit bis zum ersten Wort (Agent + Gedächtnis-Suche + Modell); Tool-Runden stecken in „Antwort". Reine Telegram-Turns laufen an MC2 vorbei und erscheinen hier nicht.
diff --git a/frontend/src/lib/api.ts b/frontend/src/lib/api.ts index 25f2bf4..bbe6e8b 100644 --- a/frontend/src/lib/api.ts +++ b/frontend/src/lib/api.ts @@ -338,7 +338,6 @@ export interface ConnectResp { gateway_url: string mc_url: string tools: Record // Leitung 1 — Modell (IDEs/Agenten → Gateway) - memory: ConnectTool // Leitung 2 — Gedächtnis (separater MCP-Server) } export interface ConnectLine { @@ -347,20 +346,12 @@ export interface ConnectLine { } export interface ConnectHealth { gateway: ConnectLine - memory: ConnectLine + memory: ConnectLine // Leitung 2 — Hermes-natives Gedächtnis (nur Status, nichts zu konfigurieren) desktop_gateway: ConnectLine } -export interface Memory { - id: string - content: string - category: string - source: string - created_at: string - updated_at: string - score?: number // Relevanz bei semantischer Suche (q gesetzt); sonst undefined -} - +// Graph-Ansicht des Wissens-Vaults (GET /api/wissen/graph) — trägt aus historischen Gründen +// noch „Memory" im Namen; die Daten kommen aus dem Vault, nicht aus einem Gedächtnis-Dienst. export interface MemoryGraphNode { id: string content: string @@ -372,13 +363,6 @@ export interface MemoryGraph { edges: { source: string; target: string; weight: number }[] } -export interface DedupeResult { - groups: { keep: { id: string; content: string; category: string }; remove: { id: string; content: string }[] }[] - duplicate_count: number - removed: number - applied: boolean -} - export interface AgentStatus { gateway_url: string box_console_url?: string @@ -443,7 +427,8 @@ export interface TokenStats { } // Per-Turn-Latenz-Trace (GET /api/voice/trace). Balken-Stufen (zeitlich disjunkt): -// stt · vision · hirn · gen. mem0 = Unter-Detail INNERHALB von hirn (nicht zum Balken addieren). +// stt · vision · hirn · gen. Der Gedächtnis-Abruf läuft seit der Mem0-Ablösung Hermes-intern +// (kein Rückruf an MC2) und steckt daher unsichtbar in hirn_ms. export interface VoiceTurn { id: string ts: number // Epoch-Sekunden @@ -452,9 +437,8 @@ export interface VoiceTurn { had_images: boolean stt_ms: number | null vision_ms: number | null - hirn_ms: number | null // Zeit bis erstes Inhalts-Token (Agent + Mem0 + LLM-TTFT) + hirn_ms: number | null // Zeit bis erstes Inhalts-Token (Agent + Gedächtnis + LLM-TTFT) gen_ms: number | null // Generierung nach dem ersten Token bis Stream-Ende - mem0_ms: number | null // Teil VON hirn (Mem0-Retrieve), best-effort total_ms: number error: string | null } @@ -583,36 +567,6 @@ export interface ChronikResp { items: ChronikItem[] } -// ── Eigenleben („Von allein": Skills + Vorschlags-Bilanz der Box) ──────────── -export interface EigenlebenSkill { - id: string - name: string - kategorie: string | null - aktiv: boolean | null // null = nicht ermittelbar (Dev-Modus) - beschreibung: string - version: string - autor: string - herkunft: "selbst" | "repo" | "bundled" - herkunft_label: string - genutzt: number - zuletzt_genutzt: string | null - erstellt: string | null - status: string - geaendert: number -} -export interface EigenlebenEintrag { - art: string // "angenommen" | "abgelehnt" | sonstiger Chronik-State - titel: string - detail: string - ts: number -} -export interface EigenlebenResp { - available: boolean - skills: EigenlebenSkill[] - selbst_erstellt: number - bilanz: { eintraege: EigenlebenEintrag[]; angenommen: number; abgelehnt: number } -} - // ── Wissens-Vault (Traum-Notizen, read-only) ───────────────────────────────── export interface WissenFile { path: string diff --git a/frontend/src/lib/queries.ts b/frontend/src/lib/queries.ts index 083265e..8e9a4a5 100644 --- a/frontend/src/lib/queries.ts +++ b/frontend/src/lib/queries.ts @@ -13,7 +13,6 @@ import { type ConnectHealth, type DiscoverResp, type DraftsResp, - type EigenlebenResp, type GroupsResp, type HermesBrainResp, type Health, @@ -21,7 +20,6 @@ import { type IdeenLogResp, type IdeenResp, type Job, - type Memory, type MemoryGraph, type ModelsResp, type Reminder, @@ -54,13 +52,11 @@ export const qk = { drafts: (target?: string) => ["drafts", target ?? ""] as const, connect: (params?: string) => ["connect", params ?? ""] as const, connectHealth: ["connect-health"] as const, - memory: (q?: string, category?: string) => ["memory", q ?? "", category ?? ""] as const, memoryGraph: ["memory-graph"] as const, voiceTrace: ["voice-trace"] as const, auftragsbuch: ["auftragsbuch"] as const, ideen: ["ideen"] as const, chronik: ["chronik"] as const, - eigenleben: ["eigenleben"] as const, wissen: ["wissen"] as const, zeitmaschine: ["zeitmaschine"] as const, reminders: ["reminders"] as const, @@ -125,13 +121,6 @@ export const useChronik = (limit = 150, refetchInterval: number = TAKT.gemuetlic export const useWissen = () => useQuery({ queryKey: qk.wissen, queryFn: () => api("/api/wissen") }) -export const useEigenleben = (refetchInterval: number = TAKT.traege) => - useQuery({ - queryKey: qk.eigenleben, - queryFn: () => api("/api/eigenleben"), - refetchInterval, - }) - export const useZeitmaschine = (refetchInterval: number = TAKT.traege, enabled = true) => useQuery({ queryKey: qk.zeitmaschine, @@ -248,18 +237,6 @@ export const useConnectHealth = () => refetchInterval: 15000, }) -export const useMemory = (opts?: { q?: string; category?: string; limit?: number }) => - useQuery({ - queryKey: qk.memory(opts?.q, opts?.category), - queryFn: () => { - const p = new URLSearchParams() - if (opts?.q) p.set("q", opts.q) - if (opts?.category) p.set("category", opts.category) - return api(`/api/memory?${p}`) - }, - select: (d) => (opts?.limit ? d.slice(0, opts.limit) : d), - }) - /** Nach Mutationen die betroffenen Listen-Queries neu ziehen. */ export function invalidate(qc: QueryClient, ...keys: (readonly unknown[])[]) { for (const key of keys) qc.invalidateQueries({ queryKey: key }) diff --git a/frontend/src/views/ConnectView.tsx b/frontend/src/views/ConnectView.tsx index 6b812d6..a280bf6 100644 --- a/frontend/src/views/ConnectView.tsx +++ b/frontend/src/views/ConnectView.tsx @@ -1,6 +1,6 @@ import { useState } from "react" import { - Check, Copy, Cpu, Brain, Globe, FolderOpen, Laptop, ArrowRight, + Check, Copy, Cpu, Brain, Globe, Laptop, ArrowRight, Info, CircleCheck, CircleX, Loader2, ChevronDown, ChevronRight, } from "lucide-react" import { useConnect, useConnectHealth } from "@/lib/queries" @@ -82,14 +82,12 @@ function defaultHost(): string { export function ConnectView() { const [host, setHost] = useState(localStorage.getItem("mc_host") || defaultHost()) - const [mcpPath, setMcpPath] = useState(localStorage.getItem("mc_mcp_path") || "") // Legacy-Tools (roher /v1-Zugang) leben im Ausklapper — Hermes Desktop ist der Hauptweg. const [active, setActive] = useState("kilo") const [sonstigeOffen, setSonstigeOffen] = useState(false) - const [copied, setCopied] = useState<"desktop" | "model" | "memory" | null>(null) + const [copied, setCopied] = useState<"desktop" | "model" | null>(null) const params = new URLSearchParams({ host }) - if (mcpPath) params.set("mcp_path", mcpPath) const { data, error: dataErr } = useConnect(params.toString()) const { data: health, isLoading: healthLoading } = useConnectHealth() const error = dataErr ? String(dataErr) : "" @@ -99,15 +97,10 @@ export function ConnectView() { if (v) localStorage.setItem("mc_host", v) } - function saveMcpPath(v: string) { - setMcpPath(v) - localStorage.setItem("mc_mcp_path", v) - } - const desktop = data?.tools["hermes_desktop"] const tool = data?.tools[active] - async function copy(which: "desktop" | "model" | "memory", snippet?: string) { + async function copy(which: "desktop" | "model", snippet?: string) { if (!snippet) return await navigator.clipboard.writeText(snippet) setCopied(which) @@ -123,7 +116,7 @@ export function ConnectView() {

Hermes Desktop ist die Tür zur Box — einmal verbinden, fertig. - Für Spezialfälle gibt es darunter die rohen Leitungen (Gateway /v1 + Gedächtnis-MCP) für sonstige Tools. + Für Spezialfälle gibt es darunter den rohen Gateway-Zugang ( /v1) für sonstige Tools.

@@ -165,7 +158,7 @@ export function ConnectView() {
- MCP · mcp_memory.py · separat + Hermes-nativ · im Agenten · nichts einzurichten
@@ -187,9 +180,9 @@ export function ConnectView() {

- Der Gateway liefert nur das LLM. Das geteilte Gedächtnis läuft über einen - eigenen MCP-Server und das Desktop-Gateway bietet die Agenten-Schnittstelle — - alle drei Leitungen werden unabhängig eingerichtet. IDEs wählen die echten Modelle + Der Gateway liefert nur das LLM. Das Gedächtnis führt + Hermes selbst (nichts einzurichten — die Kachel zeigt nur, ob es lebt), und das + Desktop-Gateway bietet die Agenten-Schnittstelle. IDEs wählen die echten Modelle {" "}(coder · heavy · vision); daneben gibt es die virtuellen Lanes chat und {" "}coding, die je Anfrage selbst das passende Modell wählen (Alltags-Chat, simple Tools).

@@ -260,12 +253,12 @@ export function ConnectView() { className="flex w-full items-center gap-2 p-4 text-sm font-space font-bold text-foreground cursor-pointer hover:text-primary transition-colors" > {sonstigeOffen ? : } - Sonstige Tools (roher /v1-Zugang + Gedächtnis-MCP) + Sonstige Tools (roher /v1-Zugang) Kilo Code · Claude Code · Eigenbau {sonstigeOffen && ( -
+
{/* Leitung 1 — Modell anbinden */}
@@ -312,51 +305,6 @@ export function ConnectView() { )}
- - {/* Leitung 2 — Gedächtnis anbinden */} -
-
-
- 2 - Gedächtnis anbinden - optional -
-

Ein MCP-Block — gilt zusätzlich für jedes Tool aus Schritt 1.

-
- -
- - {data.memory.note} -
- - {/* Der Pfad wirkt NUR auf dieses Snippet — deshalb wohnt das Feld hier, - nicht mehr prominent in der Kopfzeile („Wann brauche ich das?"). */} -
- - saveMcpPath(e.target.value)} - aria-label="Lokaler MCP-Scriptpfad" - spellCheck={false} - placeholder="z.B. F:\Coding Stuff\mission-control-2\mcp\mcp_memory.py" - className="w-full h-9 rounded-lg border border-border/60 bg-background/40 px-3 font-mono text-xs outline-none focus:ring-1 focus:ring-violet-500/50 text-foreground" - /> -

- Nur nötig, wenn du das Gedächtnis in einem PC-Tool anschließt — das Script läuft lokal - und spricht mit der Box. Der Pfad landet direkt im Snippet unten. -

-
- - copy("memory", data.memory.snippet)} - /> -
)}
diff --git a/frontend/src/views/GuideView.tsx b/frontend/src/views/GuideView.tsx index 11e2a89..e69b3dc 100644 --- a/frontend/src/views/GuideView.tsx +++ b/frontend/src/views/GuideView.tsx @@ -345,10 +345,12 @@ description: Treibt Entwicklung mit strikter TDD-Praxis
- Dein Gedächtnis (Tab Gedächtnis) ist Mem0-basiert: auto-lernend & - semantisch, graph-first dargestellt, mit 4-Typen-Taxonomie - (Identität · Wissen · Regeln · Ereignisse). Der Agent - lernt im Hintergrund nach jedem Turn — egal ob du per Desktop, Konsole, Telegram oder Lucy mit ihm sprichst. + Dein Gedächtnis führt Hermes selbst — auto-lernend und semantisch. Der Agent lernt im + Hintergrund nach jedem Turn, egal ob du per Desktop, Konsole, Telegram oder Lucy mit ihm sprichst. +
Deshalb hat das Steuerpult keinen eigenen Gedächtnis-Tab: bis August 2026 lag das + Gedächtnis in einem MC2-Sidecar, seit dessen Ablösung ist Hermes die einzige Quelle — angesehen und + gepflegt wird es dort, nicht hier. Unter Wissen findest du weiterhin die Graph-Sicht + auf Lucys Wissens-Vault.
Gotcha: ein gelöschter Fakt kann wieder auftauchen, solange die Original-Nachricht noch im Verlauf steht (additive Extraktion). diff --git a/hermes/plugins/mc2-memory/__init__.py b/hermes/plugins/mc2-memory/__init__.py deleted file mode 100644 index a34546e..0000000 --- a/hermes/plugins/mc2-memory/__init__.py +++ /dev/null @@ -1,250 +0,0 @@ -""" -MC2 Memory — Hermes-Memory-Provider, der ans geteilte **Mem0-Gedächtnis** hängt (über MC2 :9001, -das den Mem0-Sidecar :8765 proxyt). Macht das Gedächtnis für Hermes **hands-off**: - -- `sync_turn` → nach jedem Turn werden die Turn-Messages an `/api/memory/learn` geschickt; - Mem0 EXTRAHIERT dauerhafte Fakten selbst (infer=True), dedupliziert semantisch. Nicht-blockierend - (Hintergrund-Worker), damit der Agent nie auf die LLM-Extraktion wartet. -- `prefetch` → vor jedem Turn semantische Suche gegen die Nutzer-Message; relevante Fakten werden - als Kontext eingeblendet (automatischer Recall). - -**Context-only:** `get_tool_schemas()` liefert `[]` → der Agent bekommt KEINE Memory-Tools. Damit -entfällt das Tool-Loop-Risiko, wegen dem das native Memory-Toolset abgeschaltet ist -(`agent.disabled_toolsets: [..., memory]` bleibt). Single Source of Truth bleibt der MC2-Sidecar -(NoThink-Fix + alleiniger Chroma-Besitzer) — dieser Provider ist nur ein dünner HTTP-Client. - -Aktivierung (in ~/.hermes/config.yaml): - memory: - memory_enabled: true - provider: mc2-memory -""" - -from __future__ import annotations - -import logging -import os -import queue -import re -import threading -import time -from typing import Any, Optional - -import httpx -from agent.memory_provider import MemoryProvider - -log = logging.getLogger(__name__) - -MC_URL = os.environ.get("MC_URL", "http://127.0.0.1:9001").rstrip("/") -MC_TOKEN = os.environ.get("MC_TOKEN", "") -RECALL_LIMIT = int(os.environ.get("MC2_MEMORY_RECALL_LIMIT", "5")) -# 0.5 statt 0.3: nur starke Treffer einblenden → weniger Rausch-Fakten UND ein stabilerer -# Prompt-Prefix (oft leer), damit --cache-reuse über Turns greift. -RECALL_MIN_SCORE = float(os.environ.get("MC2_MEMORY_RECALL_MIN_SCORE", "0.5")) -# 25 statt 12: triviale Kurz-Turns (Begrüßung/Quittung) gar nicht erst zum Lernen schicken. -MIN_USER_LEN = int(os.environ.get("MC2_MEMORY_MIN_USER_LEN", "25")) # zu Kurzes nicht lernen -# Anti-Memory-Poisoning (Stufe 0 Security): aus Turns mit untrusted Bildschirm-/Web-Inhalt NICHT -# auto-lernen. Lucys Bildschirm-Sicht prependet diesen Marker an die User-Message (voice.py); auf dem -# Schirm sichtbarer Text könnte Injection-Anweisungen tragen, die sonst DAUERHAFT ins Gedächtnis -# wandern und Tage später ungefragt wiederverwendet werden. -SKIP_UNTRUSTED = os.environ.get("MC2_MEMORY_SKIP_UNTRUSTED", "1") not in ("0", "false", "False", "no") -UNTRUSTED_MARKERS = ("[Bildschirm-Sicht",) -# Lern-Buendelung (Phase 2, 19.07.2026): Die LLM-Extraktion lief bisher nach JEDEM Turn und -# konkurrierte dabei mit Lucys Hirn um die Slots (gleiches Modell, --parallel 2). Jetzt werden -# Turns gesammelt und als EIN Gespraechs-Block extrahiert: nach BATCH_TURNS Turns oder wenn -# BATCH_IDLE_S Sekunden Ruhe war. Ein Batch = ein Extraktionslauf statt N. -BATCH_TURNS = max(1, int(os.environ.get("MC2_MEMORY_BATCH_TURNS", "4"))) -BATCH_IDLE_S = float(os.environ.get("MC2_MEMORY_BATCH_IDLE", "180")) - -# Triviale Turns, die keinen dauerhaften Fakt tragen (reine Begrüßung/Quittung, Aufwärm-/Test- -# Kommandos) → gar nicht erst zum Auto-Lernen schicken. Spart Extraktions-Läufe und verhindert -# Müll-Fakten aus Meta-/Ablauf-Turns. -_TRIVIAL_TURN_RE = re.compile( - r"^\s*(?:(?:hi|hallo|hey|moin|servus|guten\s+(?:morgen|tag|abend)|danke\w*|" - r"ok(?:ay)?|alles\s+klar|passt|super|top|cool|nice|ja|nein|jo|jup|jap)[\s.,!?]*)+$" - r"|^\s*(?:aufw(?:ä|ae)rmen|/?test)\b", - re.IGNORECASE, -) - - -def _is_trivial_turn(text: str) -> bool: - return bool(_TRIVIAL_TURN_RE.search(text or "")) - - -def _headers() -> dict: - return {"X-MC-Token": MC_TOKEN} if MC_TOKEN else {} - - -class MC2MemoryProvider(MemoryProvider): - def __init__(self) -> None: - self._session_id = "" - self._agent_context = "primary" - self._q: queue.Queue[list] = queue.Queue(maxsize=200) - self._worker: threading.Thread | None = None - self._stop = threading.Event() - self._recall_cache: dict[str, str] = {} - # Turn-Puffer der Lern-Buendelung (siehe BATCH_TURNS/BATCH_IDLE_S). - self._buf: list[list[dict[str, str]]] = [] - self._buf_lock = threading.Lock() - self._buf_last_add = 0.0 - - # -- Identität / Verfügbarkeit ------------------------------------------- - def name(self) -> str: - return "mc2-memory" - - def is_available(self) -> bool: - try: - r = httpx.get(f"{MC_URL}/api/health", timeout=3.0) - return r.status_code == 200 - except Exception: - return False - - def initialize(self, session_id: str, **kwargs) -> None: - self._session_id = session_id - # Nur im primären Agent-Kontext lernen (cron/subagent-Systemprompts nicht einlernen). - self._agent_context = kwargs.get("agent_context", "primary") - if self._worker is None or not self._worker.is_alive(): - self._stop.clear() - self._worker = threading.Thread(target=self._run, name="mc2-memory-learn", daemon=True) - self._worker.start() - - def system_prompt_block(self) -> str: - return ( - "Du hast ein dauerhaftes, geteiltes Langzeitgedächtnis (MC2/Mem0). Relevante Fakten " - "werden dir vor einem Turn automatisch eingeblendet; neue dauerhafte Fakten über den " - "Nutzer und das Projekt werden nach dem Turn automatisch gelernt — du musst dafür " - "nichts tun." - ) - - # -- Recall (vor dem Turn) ----------------------------------------------- - def prefetch(self, query: str, *, session_id: str = "") -> str: - q = (query or "").strip() - if len(q) < 3: - return "" - if q in self._recall_cache: - return self._recall_cache[q] - try: - r = httpx.get(f"{MC_URL}/api/memory", params={"q": q}, headers=_headers(), timeout=5.0) - r.raise_for_status() - items = r.json() - except Exception as exc: # nie den Turn blockieren/abbrechen - log.debug("mc2-memory prefetch failed: %s", exc) - return "" - facts = [ - i for i in items - if i.get("score") is None or float(i.get("score", 0)) >= RECALL_MIN_SCORE - ][:RECALL_LIMIT] - out = "" - if facts: - lines = "\n".join(f"- {f.get('content', '')}" for f in facts) - out = f"Relevante Fakten aus dem Langzeitgedächtnis:\n{lines}" - # Cache klein halten - if len(self._recall_cache) > 64: - self._recall_cache.clear() - self._recall_cache[q] = out - return out - - # -- Lernen (nach dem Turn) ---------------------------------------------- - def sync_turn(self, user_content: str, assistant_content: str, *, - session_id: str = "", messages: list[dict[str, Any]] | None = None) -> None: - if self._agent_context != "primary": - return - u = (user_content or "").strip() - if len(u) < MIN_USER_LEN: - return - if _is_trivial_turn(u): - log.debug("mc2-memory: trivialer Turn (Begrüßung/Quittung/Aufwärmen) — Auto-Lernen übersprungen") - return - if SKIP_UNTRUSTED and any(m in u for m in UNTRUSTED_MARKERS): - log.debug("mc2-memory: Turn mit untrusted Bildschirm-/Web-Inhalt — Auto-Lernen übersprungen") - return - msgs: list[dict[str, str]] = [{"role": "user", "content": u}] - a = (assistant_content or "").strip() - # Hermes ≥0.18 liefert optional den vollen Turn-Kontext (`messages`, inkl. Tool-Calls). - # Bewusst NUR die Tool-NAMEN mitlernen ("hat X per Tool Y geprüft") — Tool-ERGEBNISSE - # sind untrusted (Web-Inhalte!) und wären ein Poisoning-Vektor am Junk-Guard vorbei. - if messages: - tools = [] - for m in messages: - for tc in (m.get("tool_calls") or []): - name = ((tc.get("function") or {}).get("name") or "").strip() - if name and name not in tools: - tools.append(name) - if tools: - a = (a + f"\n[genutzte Tools: {', '.join(tools[:6])}]").strip() - if a: - msgs.append({"role": "assistant", "content": a[:4000]}) - with self._buf_lock: - self._buf.append(msgs) - self._buf_last_add = time.time() - full = len(self._buf) >= BATCH_TURNS - if full: - self._drain_buffer() - # Neue Fakten können gelandet sein → Recall-Cache invalidieren. - self._recall_cache.clear() - - def _drain_buffer(self) -> None: - """Gepufferte Turns als EINEN Gespraechs-Block in die Lern-Queue geben.""" - with self._buf_lock: - if not self._buf: - return - merged: list[dict[str, str]] = [] - for turn in self._buf: - merged.extend(turn) - self._buf.clear() - try: - self._q.put_nowait(merged) - except queue.Full: - log.debug("mc2-memory learn queue full — Batch übersprungen") - - def _post_learn(self, msgs: list) -> None: - try: - httpx.post(f"{MC_URL}/api/memory/learn", - json={"messages": msgs, "source": "hermes"}, - headers=_headers(), timeout=90.0) - except Exception as exc: - log.debug("mc2-memory learn POST failed: %s", exc) - - def _run(self) -> None: - while not self._stop.is_set(): - try: - msgs = self._q.get(timeout=5.0) - except queue.Empty: - # Idle-Flush: Ruhe im Gespraech → angesammelte Turns jetzt lernen. - with self._buf_lock: - idle = (self._buf and - time.time() - self._buf_last_add >= BATCH_IDLE_S) - if idle: - self._drain_buffer() - continue - try: - self._post_learn(msgs) - finally: - self._q.task_done() - - def _flush(self) -> None: - """Offene Turns garantiert rausschreiben — bei Session-Ende/CLI-Exit, wo der - Prozess sofort beendet wird (daemon-Worker würde sonst mitten im POST sterben).""" - self._drain_buffer() - self._stop.set() - if self._worker and self._worker.is_alive(): - self._worker.join(timeout=95.0) # laufenden Worker-POST zu Ende lassen - while True: # vom Worker nicht mehr abgeholte Turns - try: - msgs = self._q.get_nowait() - except queue.Empty: - break - self._post_learn(msgs) - - # -- Context-only: keine Agent-Tools → kein Tool-Loop -------------------- - def get_tool_schemas(self) -> list[dict[str, Any]]: - return [] - - def on_session_end(self, messages: list[dict[str, Any]]) -> None: - self._flush() - - def shutdown(self) -> None: - self._flush() - - -def register(ctx) -> None: - ctx.register_memory_provider(MC2MemoryProvider()) diff --git a/hermes/plugins/mc2-memory/plugin.yaml b/hermes/plugins/mc2-memory/plugin.yaml deleted file mode 100644 index dad8806..0000000 --- a/hermes/plugins/mc2-memory/plugin.yaml +++ /dev/null @@ -1,5 +0,0 @@ -name: mc2-memory -version: 1.0.0 -description: "MC2 Memory — context-only Provider, der Hermes ans geteilte Mem0-Gedächtnis (MC2-Sidecar) hängt: automatisches Lernen nach jedem Turn + semantischer Recall davor. Keine Agent-Tools (kein Tool-Loop)." -pip_dependencies: - - httpx diff --git a/mcp/mcp_mc.py b/mcp/mcp_mc.py index c3385c3..085232c 100644 --- a/mcp/mcp_mc.py +++ b/mcp/mcp_mc.py @@ -216,7 +216,7 @@ def system_status() -> str: @mcp.tool() def list_services() -> str: - """Erreichbarkeit aller Stack-Dienste (Engine, Gateway, Hermes, Mem0, Voice).""" + """Erreichbarkeit aller Stack-Dienste (Engine, Gateway, Hermes, Voice).""" data = _get("/api/system/services") return "\n".join( f"{'✅' if s['ok'] else '❌'} {s['name']} ({s['url']})" @@ -227,7 +227,7 @@ def list_services() -> str: @mcp.tool() def restart_service(service: str) -> str: """Startet einen erlaubten Dienst neu. Erlaubt: llama-swap (Engine) | mission-control-2 | - hermes-gateway | hermes-terminal | mem0-service | voice-service. Der Engine-Neustart + hermes-gateway | hermes-terminal | voice-service. Der Engine-Neustart (llama-swap = System-Dienst) kann das Box-Passwort verlangen, wenn kein NOPASSWD gesetzt ist.""" res = _post("/api/system/restart", {"service": service}) return f"Restart {service}: {'ok' if res.get('ok') else 'Fehler — ' + res.get('err', '')}" @@ -235,7 +235,7 @@ def restart_service(service: str) -> str: @mcp.tool() def backup_now() -> str: - """Erstellt SOFORT ein Voll-Backup (mem0 + Configs + Secrets). Nutze dies vor riskanten + """Erstellt SOFORT ein Voll-Backup (Hermes-Configs + Secrets + llama-swap). Nutze dies vor riskanten Änderungen oder wenn der Nutzer ein Backup will.""" r = _post("/api/system/backup") return f"Backup erstellt: {json.dumps(r, ensure_ascii=False)}" diff --git a/mcp/mcp_memory.py b/mcp/mcp_memory.py deleted file mode 100644 index cd98dca..0000000 --- a/mcp/mcp_memory.py +++ /dev/null @@ -1,127 +0,0 @@ -#!/usr/bin/env python3 -""" -Mission Control 2.0 — Memory MCP Server (geteiltes Gedächtnis für ALLE Tools). - -Stdio-MCP-Server. Läuft als Subprocess von Cline/Claude Code/OpenCode/Hermes. -Ruft die /api/memory-Endpunkte von Mission Control via HTTP auf. - -Tool-Beschreibungen bewusst als GUARDS formuliert (konditional, nicht imperativ), -damit kleine Modelle (z.B. Hermes 14B) nicht in Aufruf-Schleifen laufen. - -Env: MC_URL (default http://192.168.178.151:9001), MC_TOKEN (optional). -Install (auf dem Rechner des Tools): pip install mcp httpx -""" - -import os - -import httpx -from mcp.server.fastmcp import FastMCP - -MC_URL = os.environ.get("MC_URL", "http://192.168.178.151:9001").rstrip("/") -MC_TOKEN = os.environ.get("MC_TOKEN", "") - -mcp = FastMCP("mission-control-memory") - - -def _h() -> dict: - return {"X-MC-Token": MC_TOKEN} if MC_TOKEN else {} - - -def _get(path: str, **params): - r = httpx.get(f"{MC_URL}{path}", headers=_h(), params=params, timeout=10) - r.raise_for_status() - return r.json() - - -def _post(path: str, data: dict): - r = httpx.post(f"{MC_URL}{path}", headers=_h(), json=data, timeout=10) - r.raise_for_status() - return r.json() - - -def _put(path: str, data: dict): - r = httpx.put(f"{MC_URL}{path}", headers=_h(), json=data, timeout=10) - r.raise_for_status() - return r.json() - - -def _delete(path: str): - r = httpx.delete(f"{MC_URL}{path}", headers=_h(), timeout=10) - r.raise_for_status() - return r.json() - - -@mcp.tool() -def get_memories(category: str = "") -> str: - """Lädt gespeicherte Fakten/Entscheidungen aus dem geteilten Gedächtnis. - Nutze dies EINMAL am Session-Beginn, wenn du Projekt-Kontext brauchst — nicht wiederholt. - category: identity | knowledge | rules | events | (leer = alle)""" - items = _get("/api/memory", **({"category": category} if category else {})) - if not items: - return "Keine Memories gespeichert." - icon = {"identity": "👤", "knowledge": "🔵", "rules": "📋", "events": "🕒"} - return "\n".join( - f"{icon.get(m['category'], '·')} [{m['category']}] {m['content']} (ID: {m['id'][:8]})" - for m in items - ) - - -@mcp.tool() -def search_memories(q: str) -> str: - """Sucht SEMANTISCH (nach Bedeutung, nicht nur Stichwort) in den Fakten. Nutze dies - VOR add_memory (Dubletten-Check) oder wenn du eine konkrete frühere Entscheidung suchst. - Treffer sind nach Relevanz sortiert.""" - items = _get("/api/memory", q=q) - if not items: - return f"Keine Treffer für '{q}'." - def _line(m): - sc = f" {m['score']:.2f}" if isinstance(m.get("score"), (int, float)) else "" - return f"[{m['category']}{sc}] {m['content']} (ID: {m['id'][:8]})" - return "\n".join(_line(m) for m in items) - - -@mcp.tool() -def add_memory(content: str, category: str = "knowledge", source: str = "agent") -> str: - """Speichert EINEN dauerhaften Fakt im geteilten Gedächtnis (alle Tools sehen ihn). - Nur aufrufen, WENN gerade etwas Dauerhaftes entstanden ist (Konvention, Architektur- - Entscheidung, Tech-Version, Nutzer-Präferenz) UND es noch nicht existiert (vorher - search_memories!). Knapp & atomar. Existiert ein passender Eintrag → update_memory. - category: identity (Nutzer/Vorlieben) | knowledge (Fakten/Stack) | rules (Regeln/Konventionen) | events (Ereignisse/Entscheidungen)""" - m = _post("/api/memory", {"content": content, "category": category, "source": source}) - return f"Gespeichert (ID: {m['id'][:8]}): {content}" - - -@mcp.tool() -def update_memory(memory_id: str, content: str = "", category: str = "") -> str: - """Aktualisiert einen bestehenden Eintrag (nur gesetzte Felder).""" - data = {k: v for k, v in (("content", content), ("category", category)) if v} - if not data: - return "Nichts zu aktualisieren." - m = _put(f"/api/memory/{memory_id}", data) - return f"Aktualisiert: {m['content']}" - - -@mcp.tool() -def delete_memory(memory_id: str) -> str: - """Löscht einen veralteten/falschen Eintrag anhand seiner ID.""" - _delete(f"/api/memory/{memory_id}") - return f"Eintrag {memory_id[:8]} gelöscht." - - -@mcp.tool() -def learn(text: str) -> str: - """Lässt das Gedächtnis AUTOMATISCH aus einem Gesprächsausschnitt lernen: reiche - rohe Nutzer-Aussagen/Turns durch — das Gedächtnis EXTRAHIERT die dauerhaften Fakten - selbst und mischt sie ein (ohne Dubletten). Nutze dies, wenn der Nutzer beiläufig etwas - Dauerhaftes über sich/seine Vorlieben/das Projekt erwähnt hat — du musst nicht selbst - den Fakt formulieren. Für einen bereits fertig formulierten Einzel-Fakt → add_memory.""" - res = _post("/api/memory/learn", {"text": text}) - items = res.get("results", []) if isinstance(res, dict) else [] - learned = [r for r in items if r.get("event") in (None, "ADD", "UPDATE")] - if not learned: - return "Nichts Neues gelernt (keine dauerhaften Fakten erkannt)." - return "Gelernt:\n" + "\n".join(f"· {r.get('content')}" for r in learned) - - -if __name__ == "__main__": - mcp.run() diff --git a/mem0_service/app.py b/mem0_service/app.py deleted file mode 100644 index 22beda9..0000000 --- a/mem0_service/app.py +++ /dev/null @@ -1,483 +0,0 @@ -#!/usr/bin/env python3 -""" -Mem0-Sidecar für Mission Control 2.0 — das auto-lernende, semantische Gedächtnis. - -WARUM ein eigener Dienst? Mem0 + chromadb laufen nur unter Python 3.12 (`~/.mem0/venv`), -das MC2-Backend aber unter Python 3.14 (kann mem0 nicht importieren). Darum kapselt dieser -schlanke FastAPI-Dienst die Mem0-Memory-Instanz und exponiert sie auf localhost. MC2 -(`backend/services/memory.py`) spricht ihn per HTTP an — die `/api/memory`-API-Form bleibt -nach außen unverändert (UI + MCP-Server kompatibel). - -Aufbau: -- Vektor-Store : Chroma embedded (kein Docker auf der Box) — Pfad MEM0_CHROMA_PATH. -- Embeddings : llama.cpp `embed`-Rolle über llama-swap (/v1/embeddings, 1024 Dim). -- LLM-Extraktion: lokales `fast`-Hirn (Qwen3.6) über llama-swap (/v1/chat/completions). - Thinking wird abgeschaltet (NoThinkLLM), sonst bricht die JSON-Extraktion ab. - -Läuft als systemd-User-Dienst (deploy/mem0-service.service) im `~/.mem0/venv`. -Bind: 127.0.0.1 (nur lokal; MC2 proxyt nach außen). -""" - -import logging -import os -import re -from contextlib import asynccontextmanager - -from fastapi import FastAPI, HTTPException -from mem0 import Memory -from mem0.configs.llms.openai import OpenAIConfig -from mem0.llms.openai import OpenAILLM -from pydantic import BaseModel - -log = logging.getLogger("mem0_service") - -# --- Konfiguration (alles über Env überschreibbar; Defaults = Box-Stand) ---------- -USER_ID = os.environ.get("MEM0_USER_ID", "mission-control") # ein geteiltes Gehirn -EMBED_URL = os.environ.get("MEM0_EMBED_URL", "http://127.0.0.1:8080/v1") -LLM_URL = os.environ.get("MEM0_LLM_URL", "http://127.0.0.1:8080/v1") -EMBED_MODEL = os.environ.get("MEM0_EMBED_MODEL", "embed") -LLM_MODEL = os.environ.get("MEM0_LLM_MODEL", "fast") -EMBED_DIMS = int(os.environ.get("MEM0_EMBED_DIMS", "1024")) -CHROMA_PATH = os.environ.get("MEM0_CHROMA_PATH", "/srv/models/mem0/chroma") -HISTORY_DB = os.environ.get("MEM0_HISTORY_DB", "/srv/models/mem0/history.db") -COLLECTION = os.environ.get("MEM0_COLLECTION", "mc2") -API_KEY = os.environ.get("MEM0_API_KEY", "sk-local") # llama.cpp ignoriert den Key -LLM_MAX_TOKENS = int(os.environ.get("MEM0_LLM_MAX_TOKENS", "2048")) -SEARCH_TOP_K = int(os.environ.get("MEM0_SEARCH_TOP_K", "50")) - -# --- Rerank-Zweitstufe (07.07.2026): Die Vektor-Suche findet ÄHNLICHES, der Reranker ordnet -# nach ECHTER Relevanz (Qwen3-Reranker via llama-swap /v1/rerank). Es ändert sich NUR die -# Reihenfolge: `score` bleibt der Vektor-Score (RECALL_MIN_SCORE im Hermes-Plugin bleibt -# kalibriert), Konsumenten, die vorne abschneiden (RECALL_LIMIT), bekommen automatisch die -# relevantesten Fakten. Jeder Fehler → lautlos Vektor-Reihenfolge (Gedächtnis bricht NIE). -RERANK_ENABLED = os.environ.get("MC_RERANK_ENABLED", "1") != "0" -RERANK_URL = os.environ.get("MC_RERANK_URL", "http://127.0.0.1:8080/v1/rerank") -RERANK_MODEL = os.environ.get("MC_RERANK_MODEL", "Qwen3-Reranker-0.6B") -RERANK_TIMEOUT = float(os.environ.get("MC_RERANK_TIMEOUT", "8")) -RERANK_CANDIDATES = int(os.environ.get("MC_RERANK_CANDIDATES", "20")) # nur die Top-N neu ordnen (Latenz) - -# Kategorien = fundierte Memory-Taxonomie (semantisch/prozedural/episodisch), bewusst knapp (4). -# Mem0-OSS kann nicht nativ klassifizieren (Cloud-Feature) → wir lassen das Hirn beim Lernen -# einordnen (classify_facts). Die Beschreibungen steuern die Treffsicherheit der Auto-Zuordnung. -CATEGORIES = ("identity", "knowledge", "rules", "events") -DEFAULT_CATEGORY = "knowledge" -CATEGORY_DESCRIPTIONS = { - "identity": "Identität & Vorlieben des Nutzers: wer er ist (Name, Rolle), wie er angesprochen werden " - "will, persönliche Vorlieben und seine Arbeitsweise.", - "knowledge": "Wissen & Fakten: stabile Fakten über Stack, Projekte, Tools, Infrastruktur und Umgebung.", - "rules": "Regeln & Konventionen: verbindliche Anweisungen und Workflows — wie etwas gemacht werden " - "soll, Do's und Don'ts.", - "events": "Ereignisse & Entscheidungen: was passiert ist, getroffene Entscheidungen, zeitgebundene Vorgänge.", -} - - -class NoThinkLLM(OpenAILLM): - """`fast` (Qwen3.6) ist ein Thinking-Modell. Unter response_format=json_object - verbrennt das Reasoning Tokens und schneidet die JSON-Fakten ab (leeres Ergebnis). - `enable_thinking=false` (chat_template_kwargs) → deterministische, schnelle Extraktion.""" - - def generate_response(self, messages, response_format=None, tools=None, - tool_choice="auto", **kwargs): - eb = dict(kwargs.pop("extra_body", {}) or {}) - eb.setdefault("chat_template_kwargs", {"enable_thinking": False}) - return super().generate_response( - messages, response_format=response_format, tools=tools, - tool_choice=tool_choice, extra_body=eb, **kwargs, - ) - - -def build_memory() -> Memory: - os.environ.setdefault("OPENAI_API_KEY", API_KEY) - os.environ.setdefault("TOKENIZERS_PARALLELISM", "false") - os.makedirs(CHROMA_PATH, exist_ok=True) - os.makedirs(os.path.dirname(HISTORY_DB), exist_ok=True) - cfg = { - "vector_store": {"provider": "chroma", "config": { - "collection_name": COLLECTION, "path": CHROMA_PATH}}, - "embedder": {"provider": "openai", "config": { - "model": EMBED_MODEL, "embedding_dims": EMBED_DIMS, - "openai_base_url": EMBED_URL, "api_key": API_KEY}}, - "llm": {"provider": "openai", "config": { - "model": LLM_MODEL, "openai_base_url": LLM_URL, "api_key": API_KEY, - "temperature": 0.1, "max_tokens": LLM_MAX_TOKENS}}, - "history_db_path": HISTORY_DB, - # Sprache zwingend Deutsch erzwingen — mem0s englischer Extraktions-Prompt zieht sonst - # Richtung Englisch. Eigennamen/Fachbegriffe bleiben unangetastet. - "custom_instructions": ( - "RELEVANZ (ZWINGEND, WICHTIGSTE REGEL): Extrahiere NUR dauerhaft nützliche Fakten ÜBER DEN " - "NUTZER (Identität, Vorlieben, Arbeitsweise), seine Projekte/Entscheidungen/Stände, stabile " - "Fakten über Stack/Tools/Infrastruktur sowie verbindliche Regeln und Workflows. " - "NIEMALS FAKTEN ÜBER DEN ASSISTENTEN SELBST (ZWINGEND): Extrahiere KEINE Aussagen über den " - "Assistenten/die KI (Hermes, Lucy), seine Fähigkeiten, seinen Zustand, seine Tools/MCP-Server, " - "seine Cronjobs, Commit-/Versionsstände oder welche Modelle er nutzt. Das Subjekt eines Fakts " - "ist IMMER der Nutzer oder sein Projekt — niemals 'der Assistent', 'Hermes' oder 'Lucy'. " - "KEINE ZEITGEBUNDENEN ZUSTÄNDE: Ignoriere transiente Momentaufnahmen (Fehler-/Job-Läufe, " - "Commit-Rückstand, Versions-Updates, 'gerade dabei'-/'hochgefahren'-/'aufgewärmt'-Status, " - "Test- und Onboarding-Fragen). IGNORIERE VOLLSTÄNDIG und gib KEINE Fakten zurück bei: " - "Tagesnachrichten und Welt-/Politik-/Börsen-/Promi-Ereignissen, Wetter, allgemeinem Weltwissen " - "ohne Bezug zum Nutzer, vom Assistenten erzeugten Zusammenfassungen oder Recherche-Ergebnissen, " - "Smalltalk, sowie Meta-Aussagen über den Gesprächsverlauf (z.B. 'der Nutzer fragt nach X', " - "'der Nutzer möchte Y prüfen', 'der Assistent tat Z'). Speichere nur, was in Wochen noch " - "nützlich ist; im Zweifel NICHT speichern. " - "SPRACHE (ZWINGEND): Formuliere ALLE Fakten auf DEUTSCH — unabhängig von der " - "Eingabesprache, niemals auf Englisch übersetzen. Eigennamen, Befehle, Pfade, Modell- und " - "Produktnamen sowie etablierte Fachbegriffe (z.B. PowerShell-Push, Deploy, Qwen3.6, Neovim, " - "Vulkan) bleiben unverändert. Schreibe jeden Fakt knapp und atomar — genau eine Aussage." - ), - } - m = Memory.from_config(cfg) - # LLM gegen die Thinking-freie Variante tauschen (gleiche Verbindung). - m.llm = NoThinkLLM(OpenAIConfig( - model=LLM_MODEL, openai_base_url=LLM_URL, api_key=API_KEY, - temperature=0.1, max_tokens=LLM_MAX_TOKENS, - )) - return m - - -_mem: Memory | None = None - - -def mem() -> Memory: - global _mem - if _mem is None: - _mem = build_memory() - return _mem - - -@asynccontextmanager -async def lifespan(_app: FastAPI): - logging.basicConfig(level=logging.INFO) - try: - mem() # Memory beim Start aufbauen (Chroma öffnen, Modelle anpingen) - log.info("Mem0 bereit (chroma=%s, embed=%s, llm=%s)", CHROMA_PATH, EMBED_MODEL, LLM_MODEL) - except Exception: - log.exception("Mem0-Init fehlgeschlagen (Dienst läuft, /health meldet down)") - yield - - -app = FastAPI(title="MC2 Mem0 Sidecar", lifespan=lifespan) - - -# --- Mapping Mem0 <-> MC2-API-Form ----------------------------------------------- -def _to_item(r: dict, score=None) -> dict: - meta = r.get("metadata") or {} - out = { - "id": r.get("id"), - "content": r.get("memory", ""), - "category": meta.get("category") or "stable", - "bereich": meta.get("bereich") or "", - "source": meta.get("source") or "auto", - "created_at": r.get("created_at") or "", - "updated_at": r.get("updated_at") or r.get("created_at") or "", - } - if score is not None: - try: - out["score"] = round(float(score), 4) - except (TypeError, ValueError): - pass - return out - - -class MemIn(BaseModel): - content: str - category: str = DEFAULT_CATEGORY - source: str = "manual" - - -class MemUp(BaseModel): - content: str | None = None - category: str | None = None - - -class LearnIn(BaseModel): - text: str | None = None - messages: list[dict] | None = None - source: str = "auto" - category: str = DEFAULT_CATEGORY - classify: bool = True # Hirn ordnet die gelernten Fakten automatisch ein - - -@app.get("/health") -def health() -> dict: - try: - mem().get_all(filters={"user_id": USER_ID}, top_k=1) - return {"ok": True} - except Exception as exc: - raise HTTPException(503, f"mem0 nicht bereit: {exc}") - - -def _rerank(query: str, items: list[dict]) -> list[dict]: - """Suchtreffer nach echter Relevanz umordnen; bei jedem Fehler unverändert zurück.""" - if not (RERANK_ENABLED and len(items) > 1): - return items - try: - import httpx - r = httpx.post(RERANK_URL, json={ - "model": RERANK_MODEL, - "query": query, - "documents": [i.get("content", "") for i in items], - "top_n": len(items), - }, timeout=RERANK_TIMEOUT) - r.raise_for_status() - results = r.json().get("results") or [] - ranked = [] - for s in sorted(results, key=lambda x: x.get("relevance_score", 0.0), reverse=True): - idx = s.get("index") - if isinstance(idx, int) and 0 <= idx < len(items): - item = dict(items[idx]) - item["rerank_score"] = round(float(s.get("relevance_score", 0.0)), 4) - ranked.append(item) - # Nur übernehmen, wenn der Reranker ALLE Kandidaten bewertet hat (sonst Verlustgefahr). - return ranked if len(ranked) == len(items) else items - except Exception as exc: - log.debug("rerank übersprungen: %s", exc) - return items - - -@app.get("/memory") -def list_memory(q: str = "", category: str = "", bereich: str = "") -> list[dict]: - """q gesetzt → semantische Suche (mit Relevanz-Score). Sonst → alle Fakten. - bereich='alltag'|'projekt' filtert (Fakten OHNE Bereichs-Feld laufen immer mit, - damit Alt-Bestand nie verschwindet).""" - if q: - res = mem().search(q, filters={"user_id": USER_ID}, top_k=SEARCH_TOP_K) - items = [_to_item(r, r.get("score")) for r in res.get("results", [])] - # Zweitstufe: die vorderen Kandidaten nach echter Relevanz ordnen (Rest bleibt hinten dran). - items = _rerank(q, items[:RERANK_CANDIDATES]) + items[RERANK_CANDIDATES:] - else: - res = mem().get_all(filters={"user_id": USER_ID}, top_k=1000) - items = [_to_item(r) for r in res.get("results", [])] - items.sort(key=lambda i: i.get("created_at", ""), reverse=True) - if category: - items = [i for i in items if i["category"] == category] - if bereich in ("alltag", "projekt"): - items = [i for i in items if i.get("bereich") in (bereich, "")] - return items - - -@app.post("/memory", status_code=201) -def add_memory(body: MemIn) -> dict: - """Manueller/agentischer Einzel-Fakt → VERBATIM speichern (infer=False, keine - LLM-Umformung). Auto-Lernen aus Gesprächen läuft über /learn (infer=True).""" - content = body.content.strip() - if not content: - raise HTTPException(400, "content leer") - res = mem().add( - [{"role": "user", "content": content}], - user_id=USER_ID, infer=False, - metadata={"category": body.category, "source": body.source}, - ) - results = res.get("results", []) - if not results: - raise HTTPException(500, "Mem0 hat nichts gespeichert") - new_id = results[0]["id"] - full = mem().get(new_id) or {} - return _to_item(full) if full else _to_item({"id": new_id, "memory": content, - "metadata": {"category": body.category, "source": body.source}}) - - -@app.put("/memory/{mid}") -def update_memory(mid: str, body: MemUp) -> dict: - existing = mem().get(mid) - if not existing: - raise HTTPException(404, "Eintrag nicht gefunden") - cur = _to_item(existing) - new_content = body.content.strip() if body.content is not None else cur["content"] - new_cat = body.category if body.category is not None else cur["category"] - mem().update(mid, data=new_content, - metadata={"category": new_cat, "source": cur["source"]}) - full = mem().get(mid) or {} - return _to_item(full) - - -@app.delete("/memory/{mid}") -def delete_memory(mid: str) -> dict: - if not mem().get(mid): - raise HTTPException(404, "Eintrag nicht gefunden") - mem().delete(mid) - return {"ok": True} - - -@app.get("/graph") -def graph(min_score: float = 0.45, top_k: int = 3) -> dict: - """Fakten als Graph: Knoten = Fakten, Kanten = semantische Ähnlichkeit (Kosinus - der gespeicherten Embeddings, je Knoten die top_k Nachbarn ≥ min_score). Für die - Obsidian-artige Gedächtnis-Visualisierung im UI.""" - items = mem().get_all(filters={"user_id": USER_ID}, top_k=2000).get("results", []) - nodes = [_to_item(r) for r in items] - node_ids = [n["id"] for n in nodes] - idx = {nid: i for i, nid in enumerate(node_ids)} - - # Embeddings direkt aus der Chroma-Collection ziehen (kein Re-Embedding). - col = mem().vector_store.collection - raw = col.get(include=["embeddings"]) - raw_ids = raw.get("ids") or [] - raw_embs = raw.get("embeddings") - edges: list[dict] = [] - vecs = [None] * len(node_ids) - have = 0 - if raw_embs is not None: - for rid, emb in zip(raw_ids, raw_embs): - if rid in idx and emb is not None: - vecs[idx[rid]] = emb - have += 1 - - if have >= 2: - import numpy as np - present = [i for i, v in enumerate(vecs) if v is not None] - M = np.array([vecs[i] for i in present], dtype=float) - norms = np.linalg.norm(M, axis=1, keepdims=True) - norms[norms == 0] = 1.0 - Mn = M / norms - sim = Mn @ Mn.T - seen: set[tuple[int, int]] = set() - for a in range(len(present)): - order = np.argsort(-sim[a]) - cnt = 0 - for b in order: - if b == a: - continue - s = float(sim[a][b]) - if s < min_score: - break - i, j = present[a], present[b] - key = (min(i, j), max(i, j)) - if key not in seen: - seen.add(key) - edges.append({"source": node_ids[i], "target": node_ids[j], - "weight": round(s, 3)}) - cnt += 1 - if cnt >= top_k: - break - return {"nodes": nodes, "edges": edges} - - -def classify_facts(facts: list[tuple[str, str]]) -> dict: - """Ordnet jeden Fakt per LLM einer Kategorie UND einem Bereich zu → - {id: {"category": , "bereich": "alltag"|"projekt"}}. - - Bereich (19.07.2026, Trennung der Welten): "alltag" = der Nutzer als Person - (Vorlieben, Leben, Arbeitsweise, Entscheidungen), "projekt" = Technik-/Code-/ - Infrastruktur-Stände. Grundlage für einen späteren Recall-Filter, damit - Projekt-Schutt nicht in Alltags-Gespräche streut — OHNE zweites Gedächtnis. - Nutzt dasselbe (Thinking-freie) Hirn wie die Extraktion. Fehler = leeres Mapping.""" - if not facts: - return {} - import json as _json - import re as _re - cat_lines = "\n".join(f"- {k}: {v}" for k, v in CATEGORY_DESCRIPTIONS.items()) - system = ( - "Du bist ein präziser Klassifikator für ein Langzeitgedächtnis. Ordne jeden Fakt GENAU EINER " - "Kategorie zu. Verfügbare Kategorien (nur diese Slugs verwenden):\n" + cat_lines + - "\nOrdne zusätzlich jeden Fakt GENAU EINEM Bereich zu: 'alltag' (der Nutzer als Person: " - "Vorlieben, Leben, Anrede, Arbeitsweise, grundsätzliche Entscheidungen) oder 'projekt' " - "(Technik: Code, Modelle, Server, Infrastruktur, Projekt- und Fehlerstände). " - "Antworte NUR als JSON-Objekt der Form " - "{\"\": {\"kategorie\": \"\", \"bereich\": \"alltag|projekt\"}, …}." - ) - body = "\n".join(f"{fid}: {txt}" for fid, txt in facts) - try: - resp = mem().llm.generate_response( - messages=[{"role": "system", "content": system}, - {"role": "user", "content": "Fakten:\n" + body}], - response_format={"type": "json_object"}, - ) - m = _re.search(r"\{.*\}", resp or "", _re.DOTALL) - data = _json.loads(m.group(0)) if m else {} - out: dict = {} - for k, v in data.items(): - if isinstance(v, str): # Alt-Form {"id": "slug"} weiter akzeptieren - if v in CATEGORIES: - out[str(k)] = {"category": v, "bereich": ""} - elif isinstance(v, dict): - cat = v.get("kategorie") or v.get("category") or "" - ber = v.get("bereich") or "" - if cat in CATEGORIES or ber in ("alltag", "projekt"): - out[str(k)] = {"category": cat if cat in CATEGORIES else DEFAULT_CATEGORY, - "bereich": ber if ber in ("alltag", "projekt") else ""} - return out - except Exception: - log.exception("Auto-Klassifikation fehlgeschlagen") - return {} - - -# Deterministischer Guard: mem0-OSS extrahiert trotz custom_instructions hartnäckig Fakten ÜBER -# den Assistenten selbst (Hermes/Lucy) und transiente Zustände (Commit-Rückstand, Cronjob-Läufe, -# Onboarding-/Test-Fragen). Diese Muster werden nach der Extraktion verworfen (der Fakt wird wieder -# gelöscht) — reine Sicherungsschicht, unabhängig vom Extraktions-LLM. -_JUNK_FACT_PATTERNS = [ - r"^\s*(?:der|die|das)\s+assistent", # "Der Assistent ..." (Selbstbeschreibung) - r"\bassistent(?:in)?\s+(?:hermes|lucy)\b", # "... Assistent Hermes/Lucy ..." - r"\bhermes[- ]agent\b", - r"commits?\s+hinter", # Versions-Rückstand (transient) - r"\bcronjob\b", - r"beim\s+letzten\s+(?:lauf|mal)", - r"onboarding[-\s]?frage|\btest-?frage\b", - r"hat\s+den\s+assistenten\s+gebeten", - r"auf\s+betriebstemperatur|hochgefahren", - r"aktualisiert\s+sein\s+ged(?:ä|ae)chtnis", # Selbst-Meta über das Gedächtnis -] -_JUNK_FACT_RE = re.compile("|".join(_JUNK_FACT_PATTERNS), re.IGNORECASE) - - -def _is_junk_fact(text: str) -> bool: - """True, wenn der extrahierte Fakt Assistenten-Meta oder ein transienter Zustand ist.""" - return bool(_JUNK_FACT_RE.search(text or "")) - - -@app.post("/learn") -def learn(body: LearnIn) -> dict: - """Auto-Lernen: Gesprächs-Turns/Text durchreichen → Mem0 EXTRAHIERT Fakten selbst - (infer=True). Anschließend ordnet das Hirn jeden neuen Fakt automatisch einer Kategorie zu.""" - msgs = body.messages - if not msgs and body.text: - msgs = [{"role": "user", "content": body.text}] - if not msgs: - raise HTTPException(400, "text oder messages erforderlich") - res = mem().add( - msgs, user_id=USER_ID, infer=True, - metadata={"category": body.category, "source": body.source}, - ) - results = res.get("results", []) - - # Guard: frisch extrahierte Assistenten-Meta/transiente Fakten sofort wieder verwerfen. - kept = [] - for r in results: - if r.get("event") in ("ADD", "UPDATE") and _is_junk_fact(r.get("memory", "")): - try: - mem().delete(r["id"]) - except Exception: - log.debug("Junk-Fakt-Löschung fehlgeschlagen für %s", r.get("id")) - log.info("mem0 guard: Junk-Fakt verworfen: %s", (r.get("memory") or "")[:80]) - continue - kept.append(r) - results = kept - - cats: dict = {} - if body.classify: - to_classify = [(r["id"], r.get("memory", "")) for r in results - if r.get("id") and r.get("memory") and r.get("event") in ("ADD", "UPDATE")] - cats = classify_facts(to_classify) - for r in results: - info = cats.get(r.get("id")) - if info: - meta = {"category": info["category"], "source": body.source} - if info.get("bereich"): - meta["bereich"] = info["bereich"] - try: - mem().update(r["id"], data=r.get("memory", ""), metadata=meta) - except Exception: - log.debug("Kategorie-Update fehlgeschlagen für %s", r.get("id")) - - return {"results": [ - {"id": r.get("id"), "content": r.get("memory"), "event": r.get("event"), - "category": (cats.get(r.get("id")) or {}).get("category", body.category), - "bereich": (cats.get(r.get("id")) or {}).get("bereich", "")} - for r in results - ]} - - -if __name__ == "__main__": - import uvicorn - - uvicorn.run(app, host="127.0.0.1", port=int(os.environ.get("MEM0_PORT", "8765"))) diff --git a/mem0_service/migrate.py b/mem0_service/migrate.py deleted file mode 100644 index 65b9c57..0000000 --- a/mem0_service/migrate.py +++ /dev/null @@ -1,62 +0,0 @@ -#!/usr/bin/env python3 -""" -Einmalige Migration: alte SQLite-Fakten (`memories`-Tabelle aus dem v1/v2-Memory) -→ Mem0. Läuft im ~/.mem0/venv. Idempotent über eine Marker-Datei. - -Jeder Alt-Eintrag wird VERBATIM übernommen (infer=False), Kategorie/Source als -Metadaten. Beim aktuellen Box-Stand ist die DB leer → No-Op, aber für -Reproduzierbarkeit/künftige Migrationen vorhanden. - -Aufruf: ~/.mem0/venv/bin/python migrate.py [pfad/zur/mc2-memory.db] -""" - -import os -import sqlite3 -import sys - -from app import USER_ID, mem # nutzt dieselbe Mem0-Instanz/Config - -DEFAULT_DB = os.environ.get("MC_MEMORY_DB", "/srv/models/mc2-memory.db") -MARKER = os.environ.get("MEM0_MIGRATION_MARKER", "/srv/models/mem0/.migrated_sqlite") - - -def main() -> int: - db_path = sys.argv[1] if len(sys.argv) > 1 else DEFAULT_DB - if os.path.exists(MARKER): - print(f"Migration bereits erledigt (Marker {MARKER}).") - return 0 - if not os.path.exists(db_path): - print(f"Keine Alt-DB unter {db_path} — nichts zu migrieren.") - os.makedirs(os.path.dirname(MARKER), exist_ok=True) - open(MARKER, "w").close() - return 0 - - conn = sqlite3.connect(db_path) - conn.row_factory = sqlite3.Row - try: - rows = conn.execute( - "SELECT content, category, source FROM memories ORDER BY created_at" - ).fetchall() - except sqlite3.OperationalError: - rows = [] - conn.close() - - m = mem() - n = 0 - for r in rows: - content = (r["content"] or "").strip() - if not content: - continue - m.add([{"role": "user", "content": content}], user_id=USER_ID, infer=False, - metadata={"category": r["category"] or "stable", - "source": r["source"] or "migrated"}) - n += 1 - - os.makedirs(os.path.dirname(MARKER), exist_ok=True) - open(MARKER, "w").close() - print(f"Migriert: {n} Einträge aus {db_path} → Mem0.") - return 0 - - -if __name__ == "__main__": - raise SystemExit(main()) diff --git a/mem0_service/requirements.txt b/mem0_service/requirements.txt deleted file mode 100644 index d4cc504..0000000 --- a/mem0_service/requirements.txt +++ /dev/null @@ -1,9 +0,0 @@ -# Mem0-Sidecar-Deps im ~/.mem0/venv (Python 3.12). BEWUSST GEPINNT — Upgrades nur -# absichtlich, weil der Sidecar mem0-INTERNA nutzt (NoThink-LLM-Swap, Roh-Zugriff auf die -# Chroma-Collection für den Graphen, Annahmen übers Result-Format). Ein unkontrolliertes -# mem0/chromadb-Upgrade kann das still brechen. -# Upgrade-Prozedur (Backup → Pin anheben → smoke_test.py): siehe docs/UPGRADE.md. -mem0ai==2.0.8 -chromadb==1.5.9 -fastapi==0.138.1 -uvicorn[standard]==0.49.0 diff --git a/mem0_service/smoke_test.py b/mem0_service/smoke_test.py deleted file mode 100644 index c198dd0..0000000 --- a/mem0_service/smoke_test.py +++ /dev/null @@ -1,71 +0,0 @@ -#!/usr/bin/env python3 -""" -Smoke-Test für den Mem0-Sidecar — VOR und NACH jedem mem0/chromadb-Upgrade laufen lassen. -Prüft genau die Pfade, die mem0-INTERNA nutzen (LLM-Extraktion/NoThink, Auto-Einordnung, -Embeddings/Suche, Roh-Chroma-Graph). Nutzt eine WEGWERF-Collection unter /tmp — das echte -Gedächtnis (/srv/models/mem0) wird NICHT angefasst. - -Aufruf: ~/.mem0/venv/bin/python ~/mission-control-v2/mem0_service/smoke_test.py -Exit 0 = alles grün, sonst 1. -""" - -import os -import shutil -import sys -import tempfile -import time - -# WICHTIG: Env vor dem Import von app setzen (app liest die Pfade beim Modul-Load). -_TMP = tempfile.mkdtemp(prefix="mem0_smoke_") -os.environ["MEM0_CHROMA_PATH"] = os.path.join(_TMP, "chroma") -os.environ["MEM0_HISTORY_DB"] = os.path.join(_TMP, "history.db") -os.environ["MEM0_COLLECTION"] = f"smoke_{int(time.time())}" - -sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) -import app - -_fails: list[str] = [] - - -def check(name: str, cond: bool, detail: str = "") -> None: - print(("PASS" if cond else "FAIL"), "—", name, ("" if cond else f":: {detail}")) - if not cond: - _fails.append(name) - - -def main() -> int: - app.mem() # Memory bauen (öffnet Chroma, pingt Modelle) - - # 1) Verbatim add + Rücklesen - r = app.add_memory(app.MemIn(content="Smoke: der Himmel ist blau.", category="knowledge", source="smoke")) - check("verbatim add + get", bool(r.get("id")) and "blau" in r.get("content", ""), str(r)[:160]) - - # 2) Embeddings / semantische Suche (Bedeutung, nicht Wort) - res = app.list_memory(q="Welche Farbe hat der Himmel?") - check("semantische Suche", any("blau" in i.get("content", "") for i in res), str(res)[:160]) - - # 3) Auto-Lernen: LLM-Extraktion (NoThink) + Deutsch erzwungen - lr = app.learn(app.LearnIn(text="Ich heiße Max und programmiere am liebsten in Go.", source="smoke")) - items = lr.get("results", []) - check("Auto-Lernen extrahiert Fakten", len(items) > 0, str(lr)[:160]) - joined = " ".join((i.get("content") or "") for i in items).lower() - check("Extraktion auf Deutsch", any(w in joined for w in ("heißt", "programmiert", "mag", "bevorzugt", "name", "nutzt")), joined[:160]) - - # 4) Auto-Einordnung in die 4 gültigen Kategorien - cats = {i.get("category") for i in items if i.get("category")} - check("Auto-Einordnung gültige Kategorie", bool(cats) and cats <= set(app.CATEGORIES), str(cats)) - - # 5) Graph aus den Roh-Embeddings (Chroma-Interna) - g = app.graph() - check("Graph liefert Knoten", len(g.get("nodes", [])) >= 1, str({k: len(v) for k, v in g.items()})) - - print("\n" + ("ALLE TESTS GRÜN ✓" if not _fails else f"FEHLGESCHLAGEN: {_fails}")) - return 0 if not _fails else 1 - - -if __name__ == "__main__": - try: - code = main() - finally: - shutil.rmtree(_TMP, ignore_errors=True) - sys.exit(code)