types angepasst
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version: 1.4 # Merge WP-15 (Smart Edges) & WP-07 (Schemas)
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version: 1.6 # Balance zwischen Speed, Kontext und Smartness
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# ==============================================================================
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# 1. CHUNKING PROFILES (WP-15 Smart Edge Allocation)
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# 1. CHUNKING PROFILES
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# ==============================================================================
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# Diese Profile steuern, wie Texte zerlegt und ob sie semantisch angereichert werden.
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chunking_profiles:
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# A. Standard / Schnell (für einfache Quellen, Logs)
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# - Strategie: Sliding Window
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# - LLM-Filter: AUS (spart Kosten/Zeit)
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# A. SHORT & FAST (Für atomare Schnipsel)
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# Einsatz: Glossar, Tasks, Risiken
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# Vorteil: Präzise Treffer für kurze Infos.
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sliding_short:
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strategy: sliding_window
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enable_smart_edge_allocation: false
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enable_smart_edge_allocation: false # AUS (Speed)
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target: 200
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max: 350
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overlap: [30, 50]
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# B. Smart Flow (für Konzepte, Journal, Projekte)
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# - Strategie: Sliding Window (für flüssigen Text)
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# - LLM-Filter: AN (verteilt Kanten intelligent auf Absätze)
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# B. STANDARD & FAST (Der neue "Mittelweg")
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# Einsatz: Quellen, Journal, Daily Logs
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# Vorteil: Viel Kontext für RAG, aber rasendschneller Import ohne LLM.
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sliding_standard:
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strategy: sliding_window
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enable_smart_edge_allocation: false # AUS (Speed)
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target: 450 # Größerer Kontext!
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max: 650
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overlap: [50, 100]
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# C. SMART FLOW (Premium Chunking)
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# Einsatz: Konzepte, Projekte, Erfahrungen
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# Vorteil: LLM prüft Inhalt und verlinkt präzise. Kostet Zeit.
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sliding_smart_edges:
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strategy: sliding_window
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enable_smart_edge_allocation: true
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enable_smart_edge_allocation: true # AN (Intelligenz)
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target: 400
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max: 600
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overlap: [50, 80]
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# C. Smart Structure (für Profile, Werte, Entscheidungen)
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# - Strategie: By Heading (Harte Trennung an Überschriften)
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# - LLM-Filter: AN (verteilt Kanten auf Sektionen)
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# D. SMART STRUCTURE
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# Einsatz: Profile, Werte, Prinzipien
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# Vorteil: Respektiert die Markdown-Struktur (H2).
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structured_smart_edges:
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strategy: by_heading
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enable_smart_edge_allocation: true
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split_level: 2 # Trennt an H2 (##)
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enable_smart_edge_allocation: true # AN (Intelligenz)
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split_level: 2
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max: 600
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target: 400
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overlap: [50, 80] # Fallback
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overlap: [50, 80]
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# ==============================================================================
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# 2. DEFAULTS
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# ==============================================================================
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defaults:
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retriever_weight: 1.0
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chunking_profile: sliding_smart_edges # Fallback: Immer smart versuchen
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chunking_profile: sliding_standard # Fallback auf Standard (sicher & performant)
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edge_defaults: []
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# ==============================================================================
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# 3. TYPE DEFINITIONS
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# ==============================================================================
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# Hier werden Chunking, Retrieval-Gewichtung und GENERIERUNGS-SCHEMATA definiert.
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types:
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# --- WISSENSBAUSTEINE ---
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concept:
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chunking_profile: sliding_smart_edges
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retriever_weight: 0.60
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edge_defaults: ["references", "related_to"]
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schema: # WP-07: Anleitung für LLM zur Erstellung
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- "Definition & Kernidee"
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- "Kontext & Hintergrund"
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- "Anwendungsbeispiele"
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- "Verwandte Konzepte"
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# --- MASSENDATEN (Speed + Kontext) ---
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source:
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chunking_profile: sliding_short # Keine Smart Edges nötig (spart Ressourcen)
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chunking_profile: sliding_standard # JETZT: Mehr Kontext (450 Token), trotzdem schnell
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retriever_weight: 0.50
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edge_defaults: []
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schema:
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- "Metadaten (Autor, URL, Datum)"
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- "Zusammenfassung (Key Takeaways)"
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- "Wichtige Zitate"
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- "Zusammenfassung"
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- "Originaltext / Ausschnitte"
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glossary:
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chunking_profile: sliding_short
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retriever_weight: 0.40
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edge_defaults: ["related_to"]
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schema:
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- "Begriffserklärung"
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- "Synonyme & Abgrenzung"
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# --- IDENTITÄT & PERSÖNLICHKEIT ---
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profile:
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chunking_profile: structured_smart_edges # Struktur ist hier wichtig
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retriever_weight: 0.70
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journal:
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chunking_profile: sliding_standard # JETZT: Mehr Kontext für Tagebucheinträge
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retriever_weight: 0.80
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edge_defaults: ["references", "related_to"]
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schema:
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- "Rolle & Beziehung"
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- "Wichtige Fakten & Daten"
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- "Gemeinsame Historie / Erfahrungen"
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- "Präferenzen & Werte"
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- "Tages-Log"
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- "Erkenntnisse"
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- "Entscheidungen"
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value:
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chunking_profile: structured_smart_edges
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retriever_weight: 1.00 # Höchste Priorität für die Decision Engine
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# --- ATOMARE DATEN (Speed + Präzision) ---
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task:
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chunking_profile: sliding_short # Kurz halten
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retriever_weight: 0.80
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edge_defaults: ["depends_on", "part_of"]
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schema: ["Aufgabe", "Kontext", "DoD"]
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glossary:
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chunking_profile: sliding_short # Kurz halten
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retriever_weight: 0.40
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edge_defaults: ["related_to"]
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schema:
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- "Definition des Wertes"
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- "Warum ist das wichtig? (Motivation)"
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- "Leitsätze für Entscheidungen"
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- "Anti-Beispiele (Was wir vermeiden)"
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principle:
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chunking_profile: structured_smart_edges
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retriever_weight: 0.95
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edge_defaults: ["derived_from", "references"]
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schema:
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- "Das Prinzip (Kernsatz)"
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- "Herleitung / Begründung"
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- "Anwendung in der Praxis"
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belief:
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chunking_profile: sliding_short
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retriever_weight: 0.90
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edge_defaults: ["related_to"]
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schema:
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- "Glaubenssatz"
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- "Ursprung (Woher kommt das?)"
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- "Ist das noch hilfreich? (Reflexion)"
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experience:
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chunking_profile: sliding_smart_edges
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retriever_weight: 0.90
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edge_defaults: ["derived_from", "references"]
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schema:
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- "Situation (Was ist passiert?)"
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- "Aktion (Was habe ich getan?)"
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- "Ergebnis (Was war die Folge?)"
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- "Learning (Was nehme ich mit?)"
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# --- STRATEGIE & ENTSCHEIDUNG ---
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goal:
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chunking_profile: sliding_smart_edges
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retriever_weight: 0.95
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edge_defaults: ["depends_on", "related_to"]
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schema:
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- "Zielsetzung (SMART)"
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- "Motivation (Warum?)"
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- "Erfolgskriterien (KPIs)"
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- "Meilensteine"
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decision:
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chunking_profile: structured_smart_edges
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retriever_weight: 1.00
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edge_defaults: ["caused_by", "references"]
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schema:
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- "Kontext & Problemstellung"
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- "Betrachtete Optionen (Pros/Cons)"
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- "Die Entscheidung"
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- "Begründung (Warum diese Wahl?)"
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- "Erwartete Konsequenzen"
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schema: ["Begriff", "Definition"]
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risk:
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chunking_profile: sliding_short
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retriever_weight: 0.85
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edge_defaults: ["related_to", "blocks"]
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schema:
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- "Risiko-Beschreibung"
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- "Eintrittswahrscheinlichkeit & Impact"
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- "Mitigations-Strategie (Plan B)"
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schema: ["Beschreibung", "Mitigation"]
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# --- OPERATIV ---
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belief:
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chunking_profile: sliding_short
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retriever_weight: 0.90
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edge_defaults: ["related_to"]
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schema: ["Glaubenssatz", "Reflexion"]
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# --- KERN-WISSEN (Smart Edges / LLM Active) ---
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concept:
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chunking_profile: sliding_smart_edges
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retriever_weight: 0.60
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edge_defaults: ["references", "related_to"]
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schema:
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- "Definition"
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- "Kontext"
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- "Verwandte Konzepte"
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project:
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chunking_profile: sliding_smart_edges
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retriever_weight: 0.97
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edge_defaults: ["references", "depends_on"]
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schema:
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- "Mission / Zielsetzung"
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- "Aktueller Status"
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- "Nächste Schritte (Next Actions)"
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- "Offene Fragen / Blocker"
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- "Referenzen (Links)"
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- "Mission"
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- "Status"
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- "Next Actions"
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task:
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chunking_profile: sliding_short
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retriever_weight: 0.80
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edge_defaults: ["depends_on", "part_of"]
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schema:
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- "Aufgabe"
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- "Kontext / Wichtigkeit"
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- "Definition of Done"
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journal:
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experience:
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chunking_profile: sliding_smart_edges
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retriever_weight: 0.80
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retriever_weight: 0.90
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edge_defaults: ["derived_from", "references"]
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schema: ["Situation", "Aktion", "Ergebnis", "Learning"]
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# --- STRUKTUR-DATEN (Smart Structure / LLM Active) ---
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profile:
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chunking_profile: structured_smart_edges
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retriever_weight: 0.70
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edge_defaults: ["references", "related_to"]
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schema:
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- "Tages-Log / Ereignisse"
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- "Erkenntnisse & Gedanken"
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- "Entscheidungen des Tages"
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- "Fokus für Morgen"
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schema: ["Rolle", "Fakten", "Historie"]
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value:
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chunking_profile: structured_smart_edges
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retriever_weight: 1.00
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edge_defaults: ["related_to"]
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schema: ["Definition", "Motivation", "Leitsätze"]
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principle:
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chunking_profile: structured_smart_edges
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retriever_weight: 0.95
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edge_defaults: ["derived_from", "references"]
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schema: ["Prinzip", "Anwendung"]
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decision:
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chunking_profile: structured_smart_edges
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retriever_weight: 1.00
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edge_defaults: ["caused_by", "references"]
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schema: ["Problem", "Optionen", "Entscheidung", "Warum"]
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