Initial commit: AI-Trainer Unsloth MoE & GRPO Control Center with Web Dashboard and Pipeline Scripts

scripts/harness_env.py

@@ -0,0 +1,36 @@
+#!/usr/bin/env python3
+"""
+harness_env.py - Command Execution Gym & Safety Sandbox
+"""
+import re
+import subprocess
+from typing import Tuple
+
+FORBIDDEN_PATTERNS = [r"rm\s+-rf\s+/", r"mkfs", r"dd\s+if=", r"shutdown", r"reboot"]
+
+class ExecutionHarnessEnv:
+    def __init__(self, dry_run: bool = True, timeout_sec: float = 3.0):
+        self.dry_run = dry_run
+        self.timeout_sec = timeout_sec
+
+    def is_safe(self, command: str) -> bool:
+        for p in FORBIDDEN_PATTERNS:
+            if re.search(p, command, re.IGNORECASE):
+                return False
+        return True
+
+    def execute(self, command: str) -> Tuple[int, str, str]:
+        if not self.is_safe(command):
+            return -999, "", "Forbidden destructive command"
+        if self.dry_run:
+            return 0, "DRY_RUN: Command syntax validated.", ""
+        try:
+            res = subprocess.run(command, shell=True, capture_output=True, text=True, timeout=self.timeout_sec)
+            return res.returncode, res.stdout, res.stderr
+        except Exception as e:
+            return -1, "", str(e)
+
+if __name__ == "__main__":
+    env = ExecutionHarnessEnv()
+    code, out, err = env.execute("adb connect 10.30.20.101:5555")
+    print(f"Harness test -> return code: {code}")