123 lines
4.7 KiB
Python
123 lines
4.7 KiB
Python
"""
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FILE: app/core/retrieval/retriever_scoring.py
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DESCRIPTION: Mathematische Kern-Logik für das WP-22/WP-15c Scoring.
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Berechnet Relevanz-Scores basierend auf Semantik, Graph-Intelligence und Content Lifecycle.
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FIX v1.0.3: Optimierte Interaktion zwischen Typ-Boost und Status-Dämpfung.
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VERSION: 1.0.3
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STATUS: Active
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"""
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import os
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import logging
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from functools import lru_cache
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from typing import Any, Dict, Tuple, Optional
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try:
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import yaml
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except ImportError:
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yaml = None
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logger = logging.getLogger(__name__)
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@lru_cache
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def get_weights() -> Tuple[float, float, float]:
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"""
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Liefert die Basis-Gewichtung (semantic, edge, centrality) aus der Konfiguration.
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"""
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from app.config import get_settings
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settings = get_settings()
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# Defaults aus Settings laden
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sem = float(getattr(settings, "RETRIEVER_W_SEM", 1.0))
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edge = float(getattr(settings, "RETRIEVER_W_EDGE", 0.0))
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cent = float(getattr(settings, "RETRIEVER_W_CENT", 0.0))
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# Optionaler Override via YAML
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config_path = os.getenv("MINDNET_RETRIEVER_CONFIG", "config/retriever.yaml")
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if yaml and os.path.exists(config_path):
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try:
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with open(config_path, "r", encoding="utf-8") as f:
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data = yaml.safe_load(f) or {}
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scoring = data.get("scoring", {})
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sem = float(scoring.get("semantic_weight", sem))
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edge = float(scoring.get("edge_weight", edge))
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cent = float(scoring.get("centrality_weight", cent))
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except Exception as e:
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logger.warning(f"Retriever Configuration could not be fully loaded from {config_path}: {e}")
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return sem, edge, cent
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def get_status_multiplier(payload: Dict[str, Any]) -> float:
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"""
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WP-22 A: Content Lifecycle Multiplier.
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Steuert das Ranking basierend auf dem Reifegrad der Information.
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- stable: 1.2 (Belohnung für verifiziertes Wissen)
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- active: 1.0 (Standard-Gewichtung)
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- draft: 0.5 (Dämpfung für unfertige Fragmente)
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"""
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status = str(payload.get("status", "active")).lower().strip()
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if status == "stable":
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return 1.2
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if status == "draft":
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return 0.5
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return 1.0
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def compute_wp22_score(
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semantic_score: float,
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payload: Dict[str, Any],
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edge_bonus_raw: float = 0.0,
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cent_bonus_raw: float = 0.0,
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dynamic_edge_boosts: Optional[Dict[str, float]] = None
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) -> Dict[str, Any]:
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"""
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Die zentrale mathematische Scoring-Formel (WP-15c optimiert).
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Implementiert das Hybrid-Scoring (Semantic * Lifecycle * Graph).
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LOGIK:
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1. Base = Similarity * StatusMult (Lifecycle-Filter).
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2. Boosts = (TypeBoost - 1) + (GraphBoni * IntentFactor).
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3. Final = Base * (1 + Boosts).
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Der edge_bonus_raw enthält bereits die Super-Edge-Aggregation (WP-15c).
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"""
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sem_w, edge_w_cfg, cent_w_cfg = get_weights()
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status_mult = get_status_multiplier(payload)
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# Retriever Weight (Typ-Boost aus types.yaml, z.B. 1.1 für Decisions)
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node_weight = float(payload.get("retriever_weight", 1.0))
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# 1. Berechnung des Base Scores (Semantik gewichtet durch Lifecycle-Status)
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# WICHTIG: Der Status wirkt hier als Multiplikator auf die Basis-Relevanz.
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base_val = float(semantic_score) * status_mult
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# 2. Graph Boost Factor (Intent-spezifische Verstärkung aus decision_engine.yaml)
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# Erhöht das Gewicht des gesamten Graphen um 50%, wenn ein spezifischer Intent vorliegt.
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graph_boost_factor = 1.5 if dynamic_edge_boosts and (edge_bonus_raw > 0 or cent_bonus_raw > 0) else 1.0
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# 3. Einzelne Graph-Komponenten berechnen
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# WP-15c Hinweis: edge_bonus_raw ist durch den retriever.py bereits gedämpft/aggregiert.
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edge_impact_final = (edge_w_cfg * edge_bonus_raw) * graph_boost_factor
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cent_impact_final = (cent_w_cfg * cent_bonus_raw) * graph_boost_factor
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# 4. Finales Zusammenführen (Merging)
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# (node_weight - 1.0) wandelt das Gewicht in einen relativen Bonus um (z.B. 1.2 -> +0.2).
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# Alle Boni werden addiert und wirken dann auf den base_val.
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type_impact = node_weight - 1.0
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total_boost = 1.0 + type_impact + edge_impact_final + cent_impact_final
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total = base_val * total_boost
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# Sicherstellen, dass der Score niemals 0 oder negativ ist (Floor)
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final_score = max(0.0001, float(total))
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return {
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"total": final_score,
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"edge_bonus": float(edge_bonus_raw),
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"cent_bonus": float(cent_bonus_raw),
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"status_multiplier": status_mult,
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"graph_boost_factor": graph_boost_factor,
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"type_impact": type_impact,
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"base_val": base_val,
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"edge_impact_final": edge_impact_final,
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"cent_impact_final": cent_impact_final
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} |