neuer semantik retriever im Chat

app/models/dto.py

@@ -1,10 +1,9 @@
 """
 FILE: app/models/dto.py
 DESCRIPTION: Pydantic-Modelle (DTOs) für Request/Response Bodies. Definiert das API-Schema.
-VERSION: 0.6.2
+VERSION: 2.6.0 (WP-22 Semantic Graph Routing & Lifecycle)
 STATUS: Active
 DEPENDENCIES: pydantic, typing, uuid
-LAST_ANALYSIS: 2025-12-15
 """
 
 from __future__ import annotations
@@ -12,7 +11,7 @@ from pydantic import BaseModel, Field
 from typing import List, Literal, Optional, Dict, Any
 import uuid
 
-EdgeKind = Literal["references", "references_at", "backlink", "next", "prev", "belongs_to", "depends_on", "related_to", "similar_to"]
+EdgeKind = Literal["references", "references_at", "backlink", "next", "prev", "belongs_to", "depends_on", "related_to", "similar_to", "caused_by", "derived_from", "based_on", "solves", "blocks", "uses", "guides"]
 
 
 # --- Basis-DTOs ---
@@ -57,6 +56,11 @@ class QueryRequest(BaseModel):
     ret: Dict = {"with_paths": True, "with_notes": True, "with_chunks": True}
     explain: bool = False
     
+    # WP-22: Semantic Graph Routing
+    # Erlaubt dem Router, Kantengewichte dynamisch zu überschreiben.
+    # Format: {"caused_by": 3.0, "related_to": 0.5}
+    boost_edges: Optional[Dict[str, float]] = None 
+
 
 class FeedbackRequest(BaseModel):
     """
@@ -97,7 +101,8 @@ class ScoreBreakdown(BaseModel):
 
 class Reason(BaseModel):
     """Ein semantischer Grund für das Ranking."""
-    kind: Literal["semantic", "edge", "type", "centrality"]
+    # WP-22: 'lifecycle' hinzugefügt für Status-Begründungen (Draft vs Stable)
+    kind: Literal["semantic", "edge", "type", "centrality", "lifecycle"]
     message: str
     score_impact: Optional[float] = None
     details: Optional[Dict[str, Any]] = None
@@ -152,5 +157,3 @@ class ChatResponse(BaseModel):
     latency_ms: int
     intent: Optional[str] = Field("FACT", description="WP-06: Erkannter Intent (FACT/DECISION)")
     intent_source: Optional[str] = Field("Unknown", description="WP-06: Quelle der Intent-Erkennung (Keyword vs. LLM)")
-
-    

app/routers/chat.py

@@ -1,11 +1,10 @@
 """
 FILE: app/routers/chat.py
 DESCRIPTION: Haupt-Chat-Interface (RAG & Interview). Enthält Intent-Router (Keywords/LLM) und Prompt-Construction.
-VERSION: 2.5.0
+VERSION: 2.6.0 (WP-22 Semantic Graph Routing)
 STATUS: Active
 DEPENDENCIES: app.config, app.models.dto, app.services.llm_service, app.core.retriever, app.services.feedback_service
 EXTERNAL_CONFIG: config/decision_engine.yaml, config/types.yaml
-LAST_ANALYSIS: 2025-12-15
 """
 
 from fastapi import APIRouter, HTTPException, Depends
@@ -282,11 +281,19 @@ async def chat_endpoint(
             inject_types = strategy.get("inject_types", [])
             prepend_instr = strategy.get("prepend_instruction", "")
             
+            # --- WP-22: Semantic Graph Routing ---
+            # Wir laden die konfigurierten Edge-Boosts für diesen Intent
+            edge_boosts = strategy.get("edge_boosts", {})
+            if edge_boosts:
+                logger.info(f"[{query_id}] Applying Edge Boosts: {edge_boosts}")
+
             query_req = QueryRequest(
                 query=request.message,
                 mode="hybrid",     
                 top_k=request.top_k,
-                explain=request.explain
+                explain=request.explain,
+                # WP-22: Boosts weitergeben
+                boost_edges=edge_boosts
             )
             retrieve_result = await retriever.search(query_req)
             hits = retrieve_result.results
@@ -297,7 +304,9 @@ async def chat_endpoint(
                     mode="hybrid",
                     top_k=3,
                     filters={"type": inject_types},
-                    explain=False
+                    explain=False,
+                    # WP-22: Boosts auch hier anwenden (Konsistenz)
+                    boost_edges=edge_boosts
                 )
                 strategy_result = await retriever.search(strategy_req)
                 existing_ids = {h.node_id for h in hits}

config/decision_engine.yaml

@@ -1,8 +1,8 @@
 # config/decision_engine.yaml
 # Steuerung der Decision Engine (Intent Recognition)
-# Version: 2.4.0 (Clean Architecture: Generic Intents only)
+# Version: 2.5.0 (WP-22: Semantic Graph Routing)
 
-version: 1.4
+version: 2.5
 
 settings:
   llm_fallback_enabled: true
@@ -37,6 +37,12 @@ strategies:
     description: "Reine Wissensabfrage."
     trigger_keywords: [] 
     inject_types: []
+    # WP-22: Definitionen & Hierarchien bevorzugen
+    edge_boosts:
+      part_of: 2.0
+      composed_of: 2.0
+      similar_to: 1.5
+      caused_by: 0.5     # Kausalität ist hier oft Rauschen
     prompt_template: "rag_template"
     prepend_instruction: null
 
@@ -53,6 +59,12 @@ strategies:
       - "abwägung"
       - "vergleich"
     inject_types: ["value", "principle", "goal", "risk"]
+    # WP-22: Risiken und Konsequenzen hervorheben
+    edge_boosts:
+      blocks: 2.5        # Blocker/Risiken sind kritisch
+      solves: 2.0        # Lösungen sind relevant
+      depends_on: 1.5
+      risk_of: 2.5
     prompt_template: "decision_template"
     prepend_instruction: |
       !!! ENTSCHEIDUNGS-MODUS !!!
@@ -71,6 +83,12 @@ strategies:
       - "überfordert"
       - "müde"
     inject_types: ["experience", "belief", "profile"]
+    # WP-22: Weiche Assoziationen & Erfahrungen stärken
+    edge_boosts:
+      based_on: 2.0      # Werte-Bezug
+      related_to: 2.0    # Assoziatives Denken
+      experienced_in: 2.5
+      blocks: 0.1        # Stressoren ausblenden
     prompt_template: "empathy_template"
     prepend_instruction: null
 
@@ -88,6 +106,11 @@ strategies:
       - "yaml"
       - "bash"
     inject_types: ["snippet", "reference", "source"]
+    # WP-22: Technische Abhängigkeiten
+    edge_boosts:
+      uses: 2.5          # Tool-Nutzung
+      depends_on: 2.0
+      implemented_in: 3.0
     prompt_template: "technical_template"
     prepend_instruction: null
 
@@ -108,6 +131,7 @@ strategies:
       - "idee speichern"
       - "draft"
     inject_types: [] 
+    edge_boosts: {}      # Kein Retrieval im Interview Modus
     prompt_template: "interview_template"
     prepend_instruction: null