refactor: extract Pydantic modelleri üzerinden analyze.py into analyze_schemas.py ve the core api/analyze route ile rate limiting eklendi

app/routes/analyze_schemas.py

@@ -0,0 +1,141 @@
+"""
+Response models for the /api/analyze endpoint.
+
+Split out from analyze.py — that file was mixing 11 Pydantic response
+models with the route handlers and service-orchestration logic in one
+693-line file. This module holds only the response shape (kept in exact
+sync with platform/hooks/analysisTypes.ts); analyze.py imports from here.
+"""
+
+from __future__ import annotations
+
+from typing import Any, Dict, List, Literal, Optional
+
+from pydantic import BaseModel, Field
+
+
+class VocalAnalysis(BaseModel):
+    """Vocal analysis results for the response."""
+
+    hasVocals: bool = False
+    vocalConfidence: float = 0.0
+    vocalAiScore: float = 0.0
+    pitchStabilityScore: float = 0.0
+    vibratoRegularityScore: float = 0.0
+    formantConsistencyScore: float = 0.0
+    breathPatternScore: float = 0.0
+    vocalTextureScore: float = 0.0
+    pitchMeanHz: float = 0.0
+    pitchStdCents: float = 0.0
+    vibratoRateHz: float = 0.0
+    vibratoExtentCents: float = 0.0
+    indicators: List[str] = Field(default_factory=list)
+
+
+class AnalysisFeatures(BaseModel):
+    """Audio feature analysis results."""
+
+    spectralRegularity: float = 0.5
+    temporalPatterns: float = 0.5
+    harmonicStructure: float = 0.5
+    artificialIndicators: List[str] = Field(default_factory=list)
+
+
+class AudioInfo(BaseModel):
+    """Audio file information."""
+
+    duration: float = 0.0
+    sampleRate: int = 44100
+    bitrate: int = 128
+    format: str = "unknown"
+    channels: int = 2
+
+
+class ConfidenceBandModel(BaseModel):
+    tier: str
+    labelTr: str
+    labelEn: str
+    lowerBound: float
+    upperBound: float
+
+
+class ModelVoteModel(BaseModel):
+    name: str
+    probability: float
+    vote: str
+
+
+class FeatureContributionModel(BaseModel):
+    name: str
+    label: str
+    labelEn: str
+    category: str
+    value: float
+    zScore: float
+    shapValue: float
+    direction: str
+    description: str
+
+
+class XAIExplanation(BaseModel):
+    """Rich explainable analysis payload."""
+
+    probability: float
+    threshold: float
+    baseProbability: float
+    confidenceBand: ConfidenceBandModel
+    modelVotes: List[ModelVoteModel] = Field(default_factory=list)
+    bestModel: str = "XGBoost"
+    topContributions: List[FeatureContributionModel] = Field(default_factory=list)
+    allFeatures: Dict[str, FeatureContributionModel] = Field(default_factory=dict)
+    featureCount: int = 0
+
+
+class MetaFeatureImportance(BaseModel):
+    """One feature's contribution to the meta-classifier's prediction."""
+
+    feature: str
+    importance: float
+    value: float
+
+
+class MetaClassifierExplanation(BaseModel):
+    """
+    Trained stacking ensemble result — a second, independent opinion
+    (LightGBM over all tower outputs) shown alongside the primary XAI
+    verdict for transparency, not used to override it. Present only when
+    the trained model artifacts are available; absent (not error) otherwise.
+    """
+
+    isAIGenerated: bool
+    confidence: float
+    modelVersion: str
+    towerScores: Dict[str, float] = Field(default_factory=dict)
+    indicators: List[str] = Field(default_factory=list)
+    topFeatures: List[MetaFeatureImportance] = Field(default_factory=list)
+
+
+class AnalysisResult(BaseModel):
+    """Platform/hooks/analysisTypes.ts uyumlu."""
+
+    isAIGenerated: bool
+    confidence: float = Field(..., ge=0.03, le=0.97)
+    processingTime: float
+    modelVersion: str
+    decisionSource: str
+    analysisMode: Literal["production", "preview"]
+    source: Dict[str, Any]
+    features: AnalysisFeatures
+    audioInfo: AudioInfo
+    vocalAnalysis: Optional[VocalAnalysis] = None
+    xai: Optional[XAIExplanation] = None
+    towerScores: Dict[str, float] = Field(default_factory=dict)
+    metaClassifier: Optional[MetaClassifierExplanation] = None
+
+
+class AnalyzeResponse(BaseModel):
+    """Response model for analysis endpoint."""
+
+    result: Optional[AnalysisResult] = None
+    warnings: List[str] = Field(default_factory=list)
+    errors: List[str] = Field(default_factory=list)