Update preprocessing_router.py

preprocessing_router.py

@@ -369,153 +369,6 @@ async def finalize_casting(
     face_identities = sorted([p.name for p in faces_out.iterdir() if p.is_dir()]) if faces_out.exists() else []
     voice_identities = sorted([p.name for p in voices_out.iterdir() if p.is_dir()]) if voices_out.exists() else []
 
-    print("faces_out exists:", faces_out.exists())
-    print("voice_out exists:", voices_out.exists())
-    print("Face identities found:", face_identities)
-    print("Voice identities found:", voice_identities)
-
-    if face_identities:
-        print("Face identities:", face_identities)
-    
-        for identity in face_identities:
-            print("Procesando identidad:", identity)
-            id_dir = faces_out / identity
-            if not id_dir.is_dir():
-                print(f"No existe directorio para {identity}")
-                continue
-    
-            img_path = None
-            for ext in (".jpg", ".jpeg", ".png", ".bmp", ".webp"):
-                candidates = list(id_dir.glob(f"*{ext}"))
-                if candidates:
-                    img_path = candidates[0]
-                    print(f"Imagen encontrada para {identity}: {img_path}")
-                    break
-    
-            if not img_path:
-                print(f"No se encontró imagen para {identity}")
-
-
-    casting_json = {"face_col": [], "voice_col": []}
-
-    try:
-        cfg = load_yaml("config.yaml")
-        router_llm = LLMRouter(cfg)
-    except Exception:
-        router_llm = None  # type: ignore
-
-    try:
-        if face_identities and router_llm is not None:
-            print("Face identities:", face_identities)
-            factory = router_llm.client_factories.get("salamandra-vision")  # type: ignore[attr-defined]
-            print("Factory:", factory)
-    
-            if factory is not None:
-                try:
-                    vclient = factory()
-                    print("VClient creado:", vclient)
-                    gclient = getattr(vclient, "_client", None)
-                    print("GClient obtenido:", gclient)
-                except Exception as e:
-                    print("Error al crear vclient desde la factory:", e)
-            else:
-                gclient = None
-                print("No se encontró la factory")
-    
-            if gclient is not None:
-                for identity in face_identities:
-                    print("Procesando identidad:", identity)
-                    id_dir = faces_out / identity
-                    if not id_dir.is_dir():
-                        print(f"No existe directorio para {identity}")
-                        continue
-    
-                    img_path = None
-                    for ext in (".jpg", ".jpeg", ".png", ".bmp", ".webp"):
-                        candidates = list(id_dir.glob(f"*{ext}"))
-                        if candidates:
-                            img_path = candidates[0]
-                            print("Imagen encontrada:", img_path)
-                            break
-    
-                    if not img_path:
-                        print(f"No se encontró imagen para {identity}")
-                        continue
-    
-                    try:
-                        out = gclient.predict(str(img_path), api_name="/face_image_embedding")
-                        print("Salida de predict:", out)
-    
-                        emb = None
-                        if isinstance(out, list):
-                            if out and isinstance(out[0], (list, tuple, float, int)):
-                                if out and isinstance(out[0], (list, tuple)):
-                                    emb = list(out[0])
-                                else:
-                                    emb = list(out)
-                        elif isinstance(out, dict) and "embedding" in out:
-                            emb = out.get("embedding")
-    
-                        if not emb:
-                            print(f"No se pudo extraer embedding de {identity}")
-                            continue
-    
-                        print(f"Embedding obtenido para {identity}: {emb[:5]}...")  # solo los primeros 5 valores
-                        casting_json["face_col"].append({
-                            "nombre": identity,
-                            "embedding": emb,
-                        })
-    
-                    except Exception as e:
-                        print(f"Error al predecir {identity}: {e}")
-                    
-    except Exception:
-        casting_json["face_col"] = []
-
-    try:
-        if voice_identities and router_llm is not None:
-            factory = router_llm.client_factories.get("whisper-catalan")  # type: ignore[attr-defined]
-            if factory is not None:
-                aclient = factory()
-                gclient = getattr(aclient, "_client", None)
-            else:
-                gclient = None
-
-            if gclient is not None:
-                for identity in voice_identities:
-                    id_dir = voices_out / identity
-                    if not id_dir.is_dir():
-                        continue
-                    wav_files = sorted([
-                        p for p in id_dir.iterdir()
-                        if p.is_file() and p.suffix.lower() in [".wav", ".flac", ".mp3"]
-                    ])
-                    if not wav_files:
-                        continue
-
-                    wf = wav_files[0]
-                    try:
-                        out = gclient.predict(str(wf), api_name="/voice_embedding")
-                        emb = None
-                        if isinstance(out, list):
-                            emb = list(out)
-                        elif isinstance(out, dict) and "embedding" in out:
-                            emb = out.get("embedding")
-
-                        if not emb:
-                            continue
-
-                        casting_json["voice_col"].append({
-                            "nombre": identity,
-                            "embedding": emb,
-                        })
-                    except Exception:
-                        continue
-    except Exception:
-        casting_json["voice_col"] = []
-
-    print(casting_json)
-
     return {
         "ok": True,
         "video_name": video_name,