feat(brain): Phase B — Vector-DB-Memory, Conversation-Loop, Skills, Tool-Use

OpenClaw (aria-core) ist raus, ARIA laeuft jetzt mit eigenem Agent-Framework
im aria-brain Container. Vector-DB-basiertes Gedaechtnis statt Sessions,
eigener Conversation-Loop mit Hot+Cold-Memory + Rolling Window, Tool-Use
fuer Skills, Memory-Destillat-Pipeline.

aria-brain/ (neuer Container)
  - main.py            FastAPI auf 8080, alle Endpoints
  - agent.py           Conversation-Loop mit Tool-Use (skill_create + run_<skill>)
  - conversation.py    Rolling Window, JSONL-Persistenz, Distill-Marker
  - proxy_client.py    httpx-Wrapper zum Claude-Proxy, OpenAI-Format
  - prompts.py         System-Prompt aus Hot+Cold+Skills
  - migration.py       Markdown-Parser fuer brain-import/ → atomare Memories
  - skills.py          Filesystem-Layer fuer /data/skills/<name>/ (Python-only,
                       venv pro Skill, tar.gz Export/Import, Run-Logs)
  - memory/            Embedder (sentence-transformers, multilingual MiniLM)
                       + VectorStore (Qdrant-Wrapper)

docker-compose.yml
  - aria-core (OpenClaw) raus, openclaw-config Volume raus
  - aria-brain Service (FastAPI + Memory)
  - aria-qdrant Service (Vector-DB) mit Bind-Mount aria-data/brain/qdrant/
  - Diagnostic teilt jetzt Netzwerk mit Bridge (vorher: aria-core)
  - Brain bekommt SSH-Mount fuer aria-wohnung + /import fuer brain-import/

bridge/aria_bridge.py
  - send_to_core → HTTP-Call an aria-brain:8080/chat (statt OpenClaw-WS)
  - aria-core-spezifische Handler raus: doctor_fix, aria_restart,
    aria_session_reset, Auto-Compact-Logik, OpenClaw-Handshake
  - Generischer container_restart-Handler (Whitelist Bridge/Brain/Qdrant)
  - Side-Channel-Events aus /chat-Response (z.B. skill_created) werden
    als RVS-Events forwarded
  - file_list_request / file_delete_request → an Diagnostic forwarded
  - Tote OpenClaw-Connection-Logik bleibt im Code als Referenz (nicht aktiv)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

aria-brain/conversation.py

@@ -0,0 +1,130 @@
+"""
+Conversation-State — ein einziger Rolling-Window-State fuer ARIAs
+laufendes Gespraech mit Stefan.
+
+Stefan-Entscheidung: KEINE Sessions, KEIN Multi-Thread. EIN Strang,
+intern rollend. Was rausfaellt, wird ggf. destilliert und landet
+als type=fact Memory in der Vector-DB.
+
+Persistenz: append-only JSONL unter /data/conversation.jsonl.
+Bei Restart wird die letzte N gelesen (komplett vermeidet Memory-
+Overhead bei sehr langen Verlaeufen).
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+import os
+from dataclasses import dataclass, field, asdict
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import List, Optional
+
+logger = logging.getLogger(__name__)
+
+CONVERSATION_FILE = Path(os.environ.get("CONVERSATION_FILE", "/data/conversation.jsonl"))
+
+
+@dataclass
+class Turn:
+    role: str         # "user" | "assistant"
+    content: str
+    ts: str = field(default_factory=lambda: datetime.now(timezone.utc).isoformat())
+    source: str = ""  # "app" / "diagnostic" / "stt" — optional
+
+
+class Conversation:
+    """In-Memory Rolling Window, mit JSONL-Persistenz."""
+
+    def __init__(self, max_window: int = 50, distill_threshold: int = 60,
+                 distill_count: int = 30):
+        self.max_window = max_window
+        self.distill_threshold = distill_threshold
+        self.distill_count = distill_count
+        self.turns: List[Turn] = []
+        self._load()
+
+    def _load(self):
+        if not CONVERSATION_FILE.exists():
+            return
+        try:
+            lines = CONVERSATION_FILE.read_text(encoding="utf-8").splitlines()
+        except Exception as exc:
+            logger.warning("Konversation laden fehlgeschlagen: %s", exc)
+            return
+        loaded: List[Turn] = []
+        for line in lines:
+            line = line.strip()
+            if not line:
+                continue
+            try:
+                obj = json.loads(line)
+            except Exception:
+                continue
+            if obj.get("op") == "distill":
+                # Marker: bis hierhin wurde alles destilliert
+                drop_until_ts = obj.get("ts", "")
+                if drop_until_ts:
+                    loaded = [t for t in loaded if t.ts > drop_until_ts]
+                continue
+            role = obj.get("role")
+            content = obj.get("content")
+            if role in ("user", "assistant") and isinstance(content, str):
+                loaded.append(Turn(role=role, content=content,
+                                   ts=obj.get("ts", ""),
+                                   source=obj.get("source", "")))
+        self.turns = loaded
+        logger.info("Konversation geladen: %d Turns aus %s", len(self.turns), CONVERSATION_FILE)
+
+    def _append_to_file(self, record: dict):
+        try:
+            CONVERSATION_FILE.parent.mkdir(parents=True, exist_ok=True)
+            with CONVERSATION_FILE.open("a", encoding="utf-8") as f:
+                f.write(json.dumps(record, ensure_ascii=False) + "\n")
+        except Exception as exc:
+            logger.warning("Konversation persist fehlgeschlagen: %s", exc)
+
+    def add(self, role: str, content: str, source: str = "") -> Turn:
+        t = Turn(role=role, content=content, source=source)
+        self.turns.append(t)
+        self._append_to_file({
+            "ts": t.ts, "role": t.role, "content": t.content, "source": t.source,
+        })
+        return t
+
+    def window(self) -> List[Turn]:
+        """Die letzten max_window Turns — gehen in den LLM-Prompt."""
+        return self.turns[-self.max_window:]
+
+    def needs_distill(self) -> bool:
+        return len(self.turns) > self.distill_threshold
+
+    def take_oldest_for_distill(self) -> List[Turn]:
+        """Gibt die N aeltesten Turns zurueck — fuer den Destillat-Call.
+        Entfernt sie NICHT — das macht commit_distill nach erfolgreichem Call."""
+        return self.turns[: self.distill_count]
+
+    def commit_distill(self, last_distilled_ts: str):
+        """Schreibt einen Distill-Marker, entfernt aus dem In-Memory-Window."""
+        self._append_to_file({"op": "distill", "ts": last_distilled_ts})
+        self.turns = [t for t in self.turns if t.ts > last_distilled_ts]
+        logger.info("Distill commit bei ts=%s — Window jetzt %d Turns", last_distilled_ts, len(self.turns))
+
+    def reset(self):
+        """Hardes Reset — verwende vorsichtig (Diagnostic-Button)."""
+        try:
+            if CONVERSATION_FILE.exists():
+                CONVERSATION_FILE.unlink()
+        except Exception:
+            pass
+        self.turns = []
+        logger.warning("Konversation komplett zurueckgesetzt")
+
+    def stats(self) -> dict:
+        return {
+            "turns": len(self.turns),
+            "max_window": self.max_window,
+            "distill_threshold": self.distill_threshold,
+            "needs_distill": self.needs_distill(),
+        }