feat: integrate CLAP and FST detection into score fusion process

app/routes/analyze.py

@@ -331,8 +331,57 @@ async def _analyze_file(
         logger.warning(f"[{request_id}] Vocal analysis failed: {e}")
         warnings.append("vocal_analysis_unavailable")
 
-    # ── Step 3: Score fusion ───────────────
-    fusion: FusionResult = fuse_scores(features, vocals)
+    # ── Step 3: CLAP detection (Layer 2) ────
+    clap_result = None
+    try:
+        audio_bytes_clap = io.BytesIO(content)
+        clap_result = clap_service.predict(audio_bytes_clap)
+        if clap_result.available:
+            logger.info(
+                f"[{request_id}] CLAP: "
+                f"ai={clap_result.is_ai}, "
+                f"conf={clap_result.confidence:.3f}"
+            )
+        else:
+            logger.info(
+                f"[{request_id}] CLAP unavailable: "
+                f"{clap_result.error}"
+            )
+    except Exception as e:
+        logger.warning(
+            f"[{request_id}] CLAP failed: {e}"
+        )
+        warnings.append("clap_analysis_unavailable")
+
+    # ── Step 4: FST detection (Layer 3) ────
+    fst_result = None
+    try:
+        audio_bytes_fst = io.BytesIO(content)
+        fst_result = await fst_service.predict(audio_bytes_fst)
+        if fst_result.available:
+            logger.info(
+                f"[{request_id}] FST: "
+                f"ai={fst_result.is_ai}, "
+                f"conf={fst_result.confidence:.3f}, "
+                f"label={fst_result.label}"
+            )
+        else:
+            logger.info(
+                f"[{request_id}] FST unavailable: "
+                f"{fst_result.error}"
+            )
+    except Exception as e:
+        logger.warning(
+            f"[{request_id}] FST failed: {e}"
+        )
+        warnings.append("fst_analysis_unavailable")
+
+    # ── Step 5: Score fusion ───────────────
+    fusion: FusionResult = fuse_scores(
+        features, vocals,
+        clap_result=clap_result,
+        fst_result=fst_result,
+    )
 
     processing_time = round(time.monotonic() - start_time, 3)
     logger.info(