""" FILE: app/models/dto.py DESCRIPTION: Pydantic-Modelle (DTOs) für Request/Response Bodies. Definiert das API-Schema. VERSION: 0.6.3 (WP-22 Semantic Graph Routing & Lifecycle) STATUS: Active DEPENDENCIES: pydantic, typing, uuid LAST_ANALYSIS: 2025-12-15 """ from __future__ import annotations 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", "caused_by", "derived_from", "based_on", "solves", "blocks", "uses", "guides"] # --- Basis-DTOs --- class NodeDTO(BaseModel): """Darstellung eines Knotens (Note oder Chunk) im API-Graph.""" id: str type: Literal["note", "chunk"] title: Optional[str] = None note_id: Optional[str] = None tags: Optional[List[str]] = None in_degree: Optional[int] = None out_degree: Optional[int] = None score: Optional[float] = None section_title: Optional[str] = None section_path: Optional[str] = None path: Optional[str] = None class EdgeDTO(BaseModel): """Darstellung einer Kante im API-Graph.""" id: str kind: str source: str target: str weight: float direction: Literal["out", "in", "undirected"] = "out" # --- Request Models --- class QueryRequest(BaseModel): """ Request für /query. """ mode: Literal["semantic", "edge", "hybrid"] = "hybrid" query: Optional[str] = None query_vector: Optional[List[float]] = None top_k: int = 10 expand: Dict = {"depth": 1, "edge_types": ["references", "belongs_to", "prev", "next", "depends_on", "related_to"]} filters: Optional[Dict] = None 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): """ User-Feedback zu einem spezifischen Treffer oder der Gesamtantwort. """ query_id: str = Field(..., description="ID der ursprünglichen Suche") # node_id ist optional: Wenn leer oder "generated_answer", gilt es für die Antwort. # Wenn eine echte Chunk-ID, gilt es für die Quelle. node_id: str = Field(..., description="ID des bewerteten Treffers oder 'generated_answer'") # Update: Range auf 1-5 erweitert für differenziertes Tuning score: int = Field(..., ge=1, le=5, description="1 (Irrelevant/Falsch) bis 5 (Perfekt)") comment: Optional[str] = None class ChatRequest(BaseModel): """ WP-05: Request für /chat. """ message: str = Field(..., description="Die Nachricht des Users") conversation_id: Optional[str] = Field(None, description="Optional: ID für Chat-Verlauf (noch nicht implementiert)") # RAG Parameter (Override defaults) top_k: int = 5 explain: bool = False # --- WP-04b Explanation Models --- class ScoreBreakdown(BaseModel): """Aufschlüsselung der Score-Komponenten.""" semantic_contribution: float edge_contribution: float centrality_contribution: float raw_semantic: float raw_edge_bonus: float raw_centrality: float node_weight: float class Reason(BaseModel): """Ein semantischer Grund für das Ranking.""" # 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 class Explanation(BaseModel): """Container für alle Erklärungsdaten eines Treffers.""" breakdown: ScoreBreakdown reasons: List[Reason] related_edges: Optional[List[EdgeDTO]] = None # --- Response Models --- class QueryHit(BaseModel): """Einzelnes Trefferobjekt für /query.""" node_id: str note_id: Optional[str] semantic_score: float edge_bonus: float centrality_bonus: float total_score: float paths: Optional[List[List[Dict]]] = None source: Optional[Dict] = None payload: Optional[Dict] = None # Added for flexibility & WP-06 meta-data explanation: Optional[Explanation] = None class QueryResponse(BaseModel): """Antwortstruktur für /query.""" query_id: str = Field(default_factory=lambda: str(uuid.uuid4())) results: List[QueryHit] used_mode: str latency_ms: int class GraphResponse(BaseModel): """Antwortstruktur für /graph/{note_id}.""" center_note_id: str nodes: List[NodeDTO] edges: List[EdgeDTO] stats: Dict[str, int] class ChatResponse(BaseModel): """ WP-05/06: Antwortstruktur für /chat. """ query_id: str = Field(..., description="Traceability ID (dieselbe wie für Search)") answer: str = Field(..., description="Generierte Antwort vom LLM") sources: List[QueryHit] = Field(..., description="Die für die Antwort genutzten Quellen") 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)")