feat: enhance analysis result with estimated bitrate and XAI verdict integration

app/routes/analyze.py

@@ -503,12 +503,31 @@ async def _analyze_file(
             indicators=vocals.indicators,
         )
 
+    # Estimate bitrate from file size + duration (kbps)
+    estimated_bitrate = 128
+    if features.duration_sec > 0:
+        estimated_bitrate = max(
+            32, min(
+                int((file_size * 8) / (features.duration_sec * 1000)),
+                2048,
+            )
+        )
+
+    # Prefer XAI verdict if available — it's the calibrated classifier
+    final_is_ai = fusion.is_ai_generated
+    final_confidence = fusion.confidence
+    final_decision = fusion.decision_source
+    if xai_payload is not None:
+        final_is_ai = xai_payload.probability >= xai_payload.threshold
+        final_confidence = round(xai_payload.probability, 4)
+        final_decision = f"auris_xai_{xai_payload.bestModel.lower()}"
+
     result = AnalysisResult(
-        isAIGenerated=fusion.is_ai_generated,
-        confidence=fusion.confidence,
+        isAIGenerated=final_is_ai,
+        confidence=final_confidence,
         processingTime=processing_time,
         modelVersion=fusion.model_version,
-        decisionSource=fusion.decision_source,
+        decisionSource=final_decision,
         analysisMode=fusion.analysis_mode,
         source={
             "kind": "file",
@@ -525,10 +544,13 @@ async def _analyze_file(
         audioInfo=AudioInfo(
             duration=round(features.duration_sec, 2),
             sampleRate=features.sample_rate,
-            bitrate=128,
+            bitrate=estimated_bitrate,
             format=content_type.replace("audio/", ""),
+            channels=1,
         ),
         vocalAnalysis=vocal_response,
+        xai=xai_payload,
+        towerScores=tower_scores,
     )
 
     return AnalyzeResponse(result=result, warnings=warnings, errors=[])