Update main.py

main.py

@@ -301,6 +301,67 @@ def compute_scores_srff_crff_ephi(prompt: str, answer: str):
     }
     return scores, feats
 
+    # ============================
+# Role profiles: perfiles de evaluación por rol
+# ============================
+
+# Cada perfil define pesos sobre los scores centrales (SRRF, CRRF, E_phi).
+# Puedes ajustar o añadir perfiles según tus necesidades.
+ROLE_PROFILES: Dict[str, Dict[str, float]] = {
+    # Perfil neutro: todos los scores cuentan igual.
+    "default": {
+        "SRRF": 1.0,
+        "CRRF": 1.0,
+        "E_phi": 1.0,
+    },
+    # Ejemplo: rol "creative" prioriza E_phi (entropía/creatividad resonante).
+    "creative": {
+        "SRRF": 0.5,
+        "CRRF": 0.5,
+        "E_phi": 1.5,
+    },
+    # Ejemplo: rol "precise" enfatiza CRRF (alineación conceptual fuerte).
+    "precise": {
+        "SRRF": 1.0,
+        "CRRF": 1.8,
+        "E_phi": 0.4,
+    },
+}
+
+
+def apply_role_profile(
+    scores: Dict[str, float],
+    role_name: Optional[str],
+) -> Dict[str, Any]:
+    """
+    Aplica un perfil de rol sobre los scores base y devuelve:
+      - nombre del rol efectivo
+      - pesos usados
+      - composite_score (score escalar para ese rol)
+    Si role_name es None o desconocido -> usa 'default'.
+    """
+    if not role_name:
+        role_name = "default"
+
+    profile = ROLE_PROFILES.get(role_name, ROLE_PROFILES["default"])
+
+    composite = 0.0
+    weight_sum = 0.0
+    for key, w in profile.items():
+        if key in scores:
+            composite += w * scores[key]
+            weight_sum += abs(w)
+
+    if weight_sum > 0.0:
+        composite /= weight_sum
+
+    return {
+        "role": role_name,
+        "weights": profile,
+        "composite_score": composite,
+    }
+
+
 # ============================
 # FastAPI app
 # ============================
@@ -315,6 +376,8 @@ class EvaluateResponse(BaseModel):
     scores: Dict[str, float]
     features: Dict[str, float]
     sim_summary: Dict[str, Any]
+    # NUEVO: resumen del perfil de rol aplicado (si hay model_label)
+    role_profile: Optional[Dict[str, Any]] = None
 
 
 # Para poder reutilizar EvaluateRequest en /quality_remote
@@ -329,6 +392,27 @@ app = FastAPI(
     version="1.0.0",
 )
 
+class RoleProfileInfo(BaseModel):
+    name: str
+    weights: Dict[str, float]
+
+
+class RoleProfilesResponse(BaseModel):
+    roles: List[RoleProfileInfo]
+
+
+@app.get("/roles", response_model=RoleProfilesResponse)
+def list_roles():
+    """
+    Devuelve todos los perfiles de rol configurados en ROLE_PROFILES.
+    Útil para que el cliente sepa qué valores puede pasar en model_label.
+    """
+    roles = [
+        RoleProfileInfo(name=name, weights=weights)
+        for name, weights in ROLE_PROFILES.items()
+    ]
+    return RoleProfilesResponse(roles=roles)
+
 
 class RerankRequest(BaseModel):
     """
@@ -440,12 +524,14 @@ def root():
 def health():
     return {"status": "ok"}
 
-
 @app.post("/evaluate", response_model=EvaluateResponse)
 def evaluate(req: EvaluateRequest):
     try:
         scores, feats = compute_scores_srff_crff_ephi(req.prompt, req.answer)
 
+        # NUEVO: aplicar perfil de rol usando model_label como selector
+        role_profile = apply_role_profile(scores, req.model_label)
+
         # resumen de una simulación adicional (fresca) solo para info
         H = build_dirac_hamiltonian(
             m=0.25, v=1.0, sigma=0.618,
@@ -453,7 +539,9 @@ def evaluate(req: EvaluateRequest):
             flux_vector=(0.0, 0.0, 0.0),
             gauge_scale=0.0,
         )
-        rng = np.random.default_rng(abs(hash(req.prompt + req.answer + "sim")) % (2 ** 32))
+        rng = np.random.default_rng(
+            abs(hash(req.prompt + req.answer + "sim")) % (2 ** 32)
+        )
         vec = rng.normal(0, 1, (2 * N,)) + 1j * rng.normal(0, 1, (2 * N,))
         vec /= np.sqrt(np.vdot(vec, vec))
         psi0 = vec
@@ -473,12 +561,12 @@ def evaluate(req: EvaluateRequest):
             scores=scores,
             features=feats,
             sim_summary=sim_summary,
+            role_profile=role_profile,  # NUEVO
         )
     except Exception as e:
         print(f"❌ [Runtime] Error en /evaluate: {e}", file=sys.stderr, flush=True)
         raise HTTPException(status_code=500, detail="Internal server error")
 
-
 # === SAVANT QUALITY_REMOTE PATCH (alias local de /evaluate) ===
 @app.post("/quality_remote", response_model=EvaluateResponse)
 def quality_remote(req: QualityRemoteRequest):