chore: auto-sync update 2026-04-12 07:20:00

models.py

@@ -5,7 +5,6 @@
 # LICENSE file in the root directory of this source tree.
 
 from typing import List
-from pydantic import StrictFloat
 
 # FIX: Import the OpenEnv base classes instead of BaseModel
 from openenv.core.env_server import Action, Observation
@@ -17,5 +16,5 @@ class AuditorAction(Action):
 class AuditorObservation(Observation):
     # This is the (batch_size, 4) matrix Samarth will send
     # Features: [time_elapsed, price_delta, missing_freq, risk_score]
-    features: List[List[StrictFloat]] 
+    features: List[List[float]] 
     message: str = "Batch processed"

server/app.py

@@ -77,16 +77,52 @@ if HAS_ENV and NATIVE_VERIFIED:
         env_factory,
         AuditorAction,
         AuditorObservation,
+        max_concurrent_envs=4,  # 3 tasks + 1 buffer for probes
     )
 
 else:
     # Fallback for local development without the C++ binary
     app = FastAPI(title="PayGorn (MOCK MODE)")
+
+    @app.get("/health")
+    async def mock_health():
+        return {"status": "healthy"}
+
     @app.post("/reset")
-    async def mock_reset(): return {"reward": 0.01}
+    async def mock_reset(): return {"reward": None}
+
     @app.post("/step")
     async def mock_step(action: dict): return {"reward": 0.5, "done": False, "step_count": 0}
 
+    @app.websocket("/ws")
+    async def mock_ws(websocket: WebSocket):
+        """Bare-minimum WS so Phase 2 gets a valid response, not connection refused."""
+        await websocket.accept()
+        try:
+            while True:
+                raw = await websocket.receive_text()
+                msg = json.loads(raw)
+                msg_type = msg.get("type", "")
+                if msg_type == "reset":
+                    await websocket.send_text(json.dumps({
+                        "type": "observation",
+                        "data": {"observation": {"features": [], "message": "mock"}, "reward": None, "done": False}
+                    }))
+                elif msg_type == "step":
+                    await websocket.send_text(json.dumps({
+                        "type": "observation",
+                        "data": {"observation": {"features": [], "message": "mock"}, "reward": 0.5, "done": True}
+                    }))
+                elif msg_type == "close":
+                    break
+        except WebSocketDisconnect:
+            pass
+        finally:
+            try:
+                await websocket.close()
+            except RuntimeError:
+                pass
+
 # Initialize metrics for the dashboard latency middleware
 app_metrics = {"last_step_latency_us": 0.0}
 

server/fin_auditor_environment.py

@@ -137,7 +137,7 @@ class FinAuditorEnvironment(Environment):
         return FinAuditorObservation(
             features=anomalies,
             message=f"Fin Auditor engine ready. {len(anomalies)} trades loaded.",
-            reward=0.1,
+            reward=None,
             done=False
         )