Update server/env.py

server/env.py

@@ -0,0 +1,36 @@
+import numpy as np
+import gymnasium as gym
+from gymnasium import spaces
+
+class EmailTriageEnv(gym.Env):
+    def __init__(self, task="all"):
+        super().__init__()
+        self.full_dataset = [
+            {"difficulty": "easy", "description": "Spam promo", "correct_actions": (0, 0, 0)},
+            {"difficulty": "easy", "description": "Routine support", "correct_actions": (0, 1, 1)},
+            {"difficulty": "medium", "description": "Billing dispute", "correct_actions": (1, 2, 2)},
+            {"difficulty": "medium", "description": "Refund request", "correct_actions": (1, 2, 2)},
+            {"difficulty": "hard", "description": "IT password reset phish", "correct_actions": (2, 1, 2)},
+            {"difficulty": "hard", "description": "Ransomware threat", "correct_actions": (2, 2, 2)}
+        ]
+        self._queue = [e for e in self.full_dataset if e.get("difficulty") == task] if task != "all" else self.full_dataset
+        self._step_idx = 0
+
+    def reset(self, seed=None, options=None):
+        self._step_idx = 0
+        return np.zeros(10, dtype=np.float32), {}
+
+    def step(self, action):
+        if self._step_idx >= len(self._queue):
+            return np.zeros(10), 0.0, True, False, {}
+        email = self._queue[self._step_idx]
+        correct = email["correct_actions"]
+        reward = 1.0 if tuple(action) == tuple(correct) else 0.0
+        if correct[0] == 2 and action[0] != 2: reward = -2.0
+        self._step_idx += 1
+        done = self._step_idx >= len(self._queue)
+        return np.zeros(10), float(reward), done, False, {"raw_reward": reward}
+
+URGENCY_LABELS = ["General", "Billing", "Security Breach"]
+ROUTING_LABELS = ["AI Auto-Reply", "Tech Support", "Legal"]
+RESOLUTION_LABELS = ["Archive", "Draft Reply", "Escalate to Human"]