258 lines
8.7 KiB
Python
258 lines
8.7 KiB
Python
"""Client fuer den Memory-Service (CT 117).
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Stellt Session-Management und Memory-Zugriff bereit.
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Kein Import von Bot- oder LLM-Logik — reiner HTTP-Client.
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"""
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import logging
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import time
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import uuid
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from typing import Optional
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import requests
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from core import config
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log = logging.getLogger("memory_client")
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_cfg = None
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_base_url = None
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_token = None
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SESSION_TIMEOUT = 1800 # 30 Minuten Inaktivitaet = neue Session
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_active_sessions: dict[str, dict] = {} # channel_key -> {id, last_activity}
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TOPIC_ALIASES = {
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"container": ["containers", "lxc", "lxc-container", "lxc container", "ct"],
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"server": ["servers", "proxmox", "pve", "host", "hosts"],
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"backup": ["backups", "pbs", "snapshot", "snapshots"],
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"projekt": ["projekte", "project", "projects"],
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"mail": ["mails", "email", "e-mail"],
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}
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def _normalize(text: str) -> str:
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"""Normalisiert Text fuer robustes Matching."""
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t = text.lower().strip()
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for old, new in [("ä", "ae"), ("ö", "oe"), ("ü", "ue"), ("ß", "ss")]:
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t = t.replace(old, new)
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t = t.replace("-", " ").replace("_", " ")
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return t
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def _topic_matches(text: str, topic: str) -> bool:
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"""Prueft ob ein Topic im normalisierten Text vorkommt (inkl. Aliase)."""
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norm_text = _normalize(text)
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norm_topic = _normalize(topic)
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if norm_topic in norm_text:
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return True
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aliases = TOPIC_ALIASES.get(norm_topic, [])
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for alias in aliases:
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if _normalize(alias) in norm_text:
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return True
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for base, alias_list in TOPIC_ALIASES.items():
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if norm_topic in [_normalize(a) for a in alias_list] or norm_topic == base:
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if base in norm_text:
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return True
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for a in alias_list:
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if _normalize(a) in norm_text:
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return True
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return False
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def _ensure_config():
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global _cfg, _base_url, _token
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if _base_url:
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return
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_cfg = config.parse_config()
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_base_url = _cfg.raw.get("MEMORY_API_URL", "").rstrip("/")
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_token = _cfg.raw.get("MEMORY_API_TOKEN", "")
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if not _base_url or not _token:
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log.warning("MEMORY_API_URL oder MEMORY_API_TOKEN nicht in homelab.conf")
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def _headers():
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return {"Authorization": f"Bearer {_token}", "Content-Type": "application/json"}
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def _post(path: str, data: dict) -> Optional[dict]:
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_ensure_config()
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if not _base_url:
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return None
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try:
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r = requests.post(f"{_base_url}{path}", json=data, headers=_headers(), timeout=5)
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if r.ok:
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return r.json()
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log.warning("Memory API %s: %s %s", path, r.status_code, r.text[:200])
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except Exception as e:
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log.warning("Memory API %s: %s", path, e)
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return None
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def _get(path: str, params: dict = None) -> Optional[dict]:
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_ensure_config()
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if not _base_url:
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return None
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try:
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r = requests.get(f"{_base_url}{path}", params=params, headers=_headers(), timeout=5)
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if r.ok:
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return r.json()
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log.warning("Memory API %s: %s %s", path, r.status_code, r.text[:200])
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except Exception as e:
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log.warning("Memory API %s: %s", path, e)
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return None
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def _patch(path: str, data: dict) -> Optional[dict]:
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_ensure_config()
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if not _base_url:
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return None
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try:
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r = requests.patch(f"{_base_url}{path}", json=data, headers=_headers(), timeout=5)
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if r.ok:
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return r.json()
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log.warning("Memory API PATCH %s: %s %s", path, r.status_code, r.text[:200])
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except Exception as e:
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log.warning("Memory API PATCH %s: %s", path, e)
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return None
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def get_or_create_session(channel_key: str, source: str = "telegram") -> Optional[str]:
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"""Gibt eine aktive Session-ID zurueck oder erstellt eine neue.
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Ueberlebt Bot-Restarts durch API-Lookup der letzten Session."""
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now = time.time()
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cached = _active_sessions.get(channel_key)
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if cached and (now - cached["last_activity"]) < SESSION_TIMEOUT:
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cached["last_activity"] = now
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return cached["id"]
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# Nach Restart: letzte Session vom API holen
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latest = _get("/sessions/latest", {"channel_key": channel_key})
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if latest and latest.get("id"):
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last_at = latest.get("last_activity_at", 0)
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if (now - last_at) < SESSION_TIMEOUT:
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_active_sessions[channel_key] = {"id": latest["id"], "last_activity": now}
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_patch(f"/sessions/{latest['id']}", {})
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log.info("Session wiederhergestellt nach Restart: %s", latest["id"][:12])
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return latest["id"]
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result = _post("/sessions", {"source": source, "channel_key": channel_key})
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if result and "id" in result:
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_active_sessions[channel_key] = {"id": result["id"], "last_activity": now}
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return result["id"]
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return None
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def log_message(session_id: str, role: str, content: str, source: str = None, meta: str = None):
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"""Speichert eine Nachricht in der Session."""
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if not session_id or not content:
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return
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data = {"role": role, "content": content}
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if source:
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data["source"] = source
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if meta:
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data["meta_json"] = meta
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_post(f"/sessions/{session_id}/messages", data)
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def get_active_memory() -> list[dict]:
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"""Holt alle aktiven Memory-Items fuer den System-Prompt."""
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result = _get("/memory", {"status": "active", "limit": 100})
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if result and "items" in result:
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return result["items"]
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return []
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def format_memory_for_prompt(items: list[dict]) -> str:
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"""Formatiert Memory-Items als Text-Block fuer den System-Prompt."""
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if not items:
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return ""
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lines = ["", "=== GEDAECHTNIS (persistente Fakten) ==="]
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for item in items:
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prefix = f"[{item['scope']}/{item['kind']}]"
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lines.append(f"{prefix} {item['content']}")
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lines.append("=== ENDE GEDAECHTNIS ===")
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return "\n".join(lines)
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def get_session_messages(session_id: str, limit: int = 10) -> list[dict]:
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"""Holt die letzten N Messages einer Session fuer den LLM-Kontext."""
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if not session_id:
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return []
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result = _get(f"/sessions/{session_id}/messages", {"limit": limit})
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if result and "messages" in result:
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return result["messages"]
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return []
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def get_session_summary(session_id: str, limit: int = 20, topic: str = None) -> str:
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"""Kompakte Zusammenfassung der aktuellen Session, optional nach Thema gefiltert."""
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if not session_id:
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return "Keine aktive Session."
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messages = get_session_messages(session_id, limit=limit)
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if not messages:
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return "Noch keine Nachrichten in dieser Session."
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exchanges = []
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current_q = None
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for msg in messages:
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role = msg.get("role", "")
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content = (msg.get("content") or "").strip()
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if not content:
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continue
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if role == "user":
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current_q = content[:200]
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elif role == "assistant" and current_q:
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exchanges.append((current_q, content[:200]))
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current_q = None
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if current_q:
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exchanges.append((current_q, None))
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if not exchanges:
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return "Keine Themen in dieser Session."
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if topic:
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matching_pairs = []
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matching_singles = []
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other_topics = []
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for q, a in exchanges:
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combined = q + " " + (a or "")
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if _topic_matches(combined, topic):
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matching_pairs.append((q, a))
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else:
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other_topics.append(q[:80])
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# Fallback: einzelne Messages pruefen (falls Pairing unvollstaendig)
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if not matching_pairs:
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for msg in messages:
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content = (msg.get("content") or "").strip()
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if content and _topic_matches(content, topic):
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role = msg.get("role", "?")
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matching_singles.append((role, content[:200]))
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lines = []
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if matching_pairs:
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lines.append("Zum Thema '" + topic + "' (" + str(len(matching_pairs)) + " Treffer):")
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for i, (q, a) in enumerate(matching_pairs, 1):
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line = str(i) + ". Frage: " + q
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if a:
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line += "\n Antwort: " + a
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lines.append(line)
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elif matching_singles:
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lines.append("Zum Thema '" + topic + "' (" + str(len(matching_singles)) + " relevante Messages):")
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for role, content in matching_singles:
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lines.append(" [" + role + "] " + content)
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else:
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lines.append("Zum Thema '" + topic + "' wurde in dieser Session nichts besprochen.")
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if other_topics:
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lines.append("\nSonstige Themen der Session: " + ", ".join(other_topics))
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return "\n".join(lines)
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lines = ["Session (" + str(len(exchanges)) + " Themen):"]
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for i, (q, a) in enumerate(exchanges, 1):
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line = str(i) + ". Frage: " + q
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if a:
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line += "\n Antwort: " + a
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lines.append(line)
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return "\n".join(lines)
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