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134 lines
4.8 KiB
YAML
134 lines
4.8 KiB
YAML
# config/decision_engine.yaml
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# VERSION: 3.2.2 (WP-25a: Decoupled MoE Logic)
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# STATUS: Active
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# DESCRIPTION: Zentrale Orchestrierung der Multi-Stream-Engine.
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# FIX:
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# - Auslagerung der LLM-Profile in llm_profiles.yaml zur zentralen Wartbarkeit.
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# - Integration von compression_thresholds zur Inhaltsverdichtung (WP-25a).
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# - 100% Erhalt aller WP-25 Edge-Boosts und Filter-Typen (v3.1.6).
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version: 3.2
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settings:
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llm_fallback_enabled: true
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# "auto" nutzt den globalen Default-Provider aus der .env
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router_provider: "auto"
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# Verweis auf den Intent-Klassifizierer in der prompts.yaml
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router_prompt_key: "intent_router_v1"
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# Pfad zur neuen Experten-Konfiguration (WP-25a Architektur-Cleanliness)
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profiles_config_path: "config/llm_profiles.yaml"
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router_profile: "compression_fast"
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# --- EBENE 1: STREAM-LIBRARY (Bausteine basierend auf types.yaml v2.7.0) ---
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streams_library:
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values_stream:
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name: "Identität & Ethik"
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# Referenz auf Experten-Profil (z.B. lokal via Ollama für Privacy)
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llm_profile: "identity_safe"
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compression_profile: "identity_safe"
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compression_threshold: 2500
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query_template: "Welche meiner Werte und Prinzipien betreffen: {query}"
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filter_types: ["value", "principle", "belief", "trait", "boundary", "need", "motivation"]
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top_k: 5
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edge_boosts:
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guides: 3.0
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depends_on: 2.5
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based_on: 2.0
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facts_stream:
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name: "Operative Realität"
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llm_profile: "synthesis_pro"
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compression_profile: "compression_fast"
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compression_threshold: 3500
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query_template: "Status, Ressourcen und Fakten zu: {query}"
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filter_types: ["project", "decision", "task", "goal", "event", "state"]
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top_k: 5
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edge_boosts:
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part_of: 2.0
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depends_on: 1.5
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implemented_in: 1.5
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biography_stream:
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name: "Persönliche Erfahrung"
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llm_profile: "synthesis_pro"
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compression_profile: "compression_fast"
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compression_threshold: 3000
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query_template: "Welche Erlebnisse habe ich im Kontext von {query} gemacht?"
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filter_types: ["experience", "journal", "profile", "person"]
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top_k: 3
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edge_boosts:
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related_to: 1.5
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experienced_in: 2.0
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expert_for: 2.5
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risk_stream:
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name: "Risiko-Radar"
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llm_profile: "synthesis_pro"
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compression_profile: "compression_fast"
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compression_threshold: 2500
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query_template: "Gefahren, Hindernisse oder Risiken bei: {query}"
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filter_types: ["risk", "obstacle", "bias"]
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top_k: 3
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edge_boosts:
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blocks: 2.5
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impacts: 2.0
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risk_of: 2.5
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tech_stream:
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name: "Wissen & Technik"
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llm_profile: "tech_expert"
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compression_profile: "compression_fast"
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compression_threshold: 4500
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query_template: "Inhaltliche Details und Definitionen zu: {query}"
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filter_types: ["concept", "source", "glossary", "idea", "insight", "skill", "habit"]
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top_k: 5
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edge_boosts:
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uses: 2.5
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implemented_in: 3.0
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# --- EBENE 2: STRATEGIEN (Finale Komposition via MoE-Profile) ---
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strategies:
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FACT_WHEN:
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description: "Abfrage von exakten Zeitpunkten und Terminen."
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llm_profile: "synthesis_pro"
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trigger_keywords: ["wann", "datum", "uhrzeit", "zeitpunkt"]
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use_streams: ["facts_stream", "biography_stream", "tech_stream"]
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prompt_template: "fact_synthesis_v1"
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FACT_WHAT:
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description: "Abfrage von Definitionen, Listen und Inhalten."
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llm_profile: "synthesis_pro"
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trigger_keywords: ["was ist", "welche sind", "liste", "übersicht", "zusammenfassung"]
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use_streams: ["facts_stream", "tech_stream", "biography_stream"]
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prompt_template: "fact_synthesis_v1"
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DECISION:
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description: "Der User sucht Rat, Strategie oder Abwägung."
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llm_profile: "synthesis_pro"
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trigger_keywords: ["soll ich", "sollte ich", "entscheidung", "abwägen", "priorität", "empfehlung"]
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use_streams: ["values_stream", "facts_stream", "risk_stream"]
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prompt_template: "decision_synthesis_v1"
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prepend_instruction: |
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!!! ENTSCHEIDUNGS-MODUS (AGENTIC MULTI-STREAM) !!!
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Analysiere die Fakten vor dem Hintergrund meiner Werte und evaluiere die Risiken.
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Wäge ab, ob das Vorhaben mit meiner langfristigen Identität kompatibel ist.
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EMPATHY:
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description: "Reaktion auf emotionale Zustände."
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llm_profile: "synthesis_pro"
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trigger_keywords: ["fühle", "traurig", "glücklich", "stress", "angst"]
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use_streams: ["biography_stream", "values_stream"]
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prompt_template: "empathy_template"
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CODING:
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description: "Technische Anfragen und Programmierung."
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llm_profile: "tech_expert"
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trigger_keywords: ["code", "python", "script", "bug", "syntax"]
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use_streams: ["tech_stream", "facts_stream"]
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prompt_template: "technical_template"
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INTERVIEW:
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description: "Der User möchte Wissen erfassen (Eingabemodus)."
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llm_profile: "compression_fast"
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use_streams: []
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prompt_template: "interview_template" |