fix(intern-decision-serve): load and score on one dedicated inference thread

torch keeps CUDA state per host thread (cuBLAS handles and workspaces), partly outside the
per-process VRAM cap. Scoring on anyio's threadpool let 40 threads each create it: measured on
fv-ml1 GPU 3, +252 MiB outside the cap and +326 MiB inside, which pushed the process past the
10,300 MiB GPU 1 budget. Load, warm-up and every call now run on the same single thread.

services/intern-decision-serve/src/intern_decision_serve/main.py

@@ -5,7 +5,7 @@ import os
 
 from fastapi import FastAPI
 
-from .app import create_app
+from .app import create_app, inference_thread
 from .config import Settings
 
 
@@ -17,4 +17,7 @@ def app_from_env() -> FastAPI:
     os.environ["TRANSFORMERS_OFFLINE"] = "1"
     from .engine import TorchEngine   # torch loads only inside load(), never in the unit tests
 
-    return create_app(settings, TorchEngine.load(settings))
+    # INV-2: load, warm-up and every later call run on this one thread (per-thread CUDA state).
+    executor = inference_thread()
+    engine = executor.submit(TorchEngine.load, settings).result()
+    return create_app(settings, engine, executor)