mindnet/config/types.yaml

version: 1.6 # Balance zwischen Speed, Kontext und Smartness

# ==============================================================================
# 1. CHUNKING PROFILES
# ==============================================================================

chunking_profiles:
  
  # A. SHORT & FAST (Für atomare Schnipsel)
  # Einsatz: Glossar, Tasks, Risiken
  # Vorteil: Präzise Treffer für kurze Infos.
  sliding_short:
    strategy: sliding_window
    enable_smart_edge_allocation: false # AUS (Speed)
    target: 200
    max: 350
    overlap: [30, 50]

  # B. STANDARD & FAST (Der neue "Mittelweg")
  # Einsatz: Quellen, Journal, Daily Logs
  # Vorteil: Viel Kontext für RAG, aber rasendschneller Import ohne LLM.
  sliding_standard:
    strategy: sliding_window
    enable_smart_edge_allocation: false # AUS (Speed)
    target: 450  # Größerer Kontext!
    max: 650
    overlap: [50, 100]

  # C. SMART FLOW (Premium Chunking)
  # Einsatz: Konzepte, Projekte, Erfahrungen
  # Vorteil: LLM prüft Inhalt und verlinkt präzise. Kostet Zeit.
  sliding_smart_edges:
    strategy: sliding_window
    enable_smart_edge_allocation: true # AN (Intelligenz)
    target: 400
    max: 600
    overlap: [50, 80]

  # D. SMART STRUCTURE
  # Einsatz: Profile, Werte, Prinzipien
  # Vorteil: Respektiert die Markdown-Struktur (H2).
  structured_smart_edges:
    strategy: by_heading
    enable_smart_edge_allocation: true # AN (Intelligenz)
    split_level: 2
    max: 600
    target: 400
    overlap: [50, 80]

# ==============================================================================
# 2. DEFAULTS
# ==============================================================================
defaults:
  retriever_weight: 1.0
  chunking_profile: sliding_standard # Fallback auf Standard (sicher & performant)
  edge_defaults: [] 

# ==============================================================================
# 3. TYPE DEFINITIONS
# ==============================================================================

types:

  # --- MASSENDATEN (Speed + Kontext) ---

  source:
    chunking_profile: sliding_standard # JETZT: Mehr Kontext (450 Token), trotzdem schnell
    retriever_weight: 0.50
    edge_defaults: [] 
    schema:
      - "Metadaten (Autor, URL, Datum)"
      - "Zusammenfassung"
      - "Originaltext / Ausschnitte"

  journal:
    chunking_profile: sliding_standard # JETZT: Mehr Kontext für Tagebucheinträge
    retriever_weight: 0.80
    edge_defaults: ["references", "related_to"]
    schema:
      - "Tages-Log"
      - "Erkenntnisse"
      - "Entscheidungen"

  # --- ATOMARE DATEN (Speed + Präzision) ---

  task:
    chunking_profile: sliding_short # Kurz halten
    retriever_weight: 0.80
    edge_defaults: ["depends_on", "part_of"]
    schema: ["Aufgabe", "Kontext", "DoD"]

  glossary:
    chunking_profile: sliding_short # Kurz halten
    retriever_weight: 0.40
    edge_defaults: ["related_to"]
    schema: ["Begriff", "Definition"]

  risk:
    chunking_profile: sliding_short
    retriever_weight: 0.85
    edge_defaults: ["related_to", "blocks"]
    schema: ["Beschreibung", "Mitigation"]

  belief:
    chunking_profile: sliding_short
    retriever_weight: 0.90
    edge_defaults: ["related_to"]
    schema: ["Glaubenssatz", "Reflexion"]

  # --- KERN-WISSEN (Smart Edges / LLM Active) ---

  concept:
    chunking_profile: sliding_smart_edges
    retriever_weight: 0.60
    edge_defaults: ["references", "related_to"]
    schema:
      - "Definition"
      - "Kontext"
      - "Verwandte Konzepte"

  project:
    chunking_profile: sliding_smart_edges
    retriever_weight: 0.97
    edge_defaults: ["references", "depends_on"] 
    schema:
      - "Mission"
      - "Status"
      - "Next Actions"

  experience:
    chunking_profile: sliding_smart_edges
    retriever_weight: 0.90
    edge_defaults: ["derived_from", "references"]
    schema: ["Situation", "Aktion", "Ergebnis", "Learning"]

  # --- STRUKTUR-DATEN (Smart Structure / LLM Active) ---

  profile:
    chunking_profile: structured_smart_edges
    retriever_weight: 0.70
    edge_defaults: ["references", "related_to"]
    schema: ["Rolle", "Fakten", "Historie"]

  value:
    chunking_profile: structured_smart_edges
    retriever_weight: 1.00
    edge_defaults: ["related_to"]
    schema: ["Definition", "Motivation", "Leitsätze"]

  principle:
    chunking_profile: structured_smart_edges
    retriever_weight: 0.95
    edge_defaults: ["derived_from", "references"]
    schema: ["Prinzip", "Anwendung"]

  decision:
    chunking_profile: structured_smart_edges 
    retriever_weight: 1.00
    edge_defaults: ["caused_by", "references"]
    schema: ["Problem", "Optionen", "Entscheidung", "Warum"]