feat(sleep): support OpenAI-compatible endpoints in azure_openai backend

Let AzureOpenAIBackend drive any OpenAI-compatible chat-completions server
(DeepSeek, self-hosted vLLM/Ollama, ...) alongside native Azure deployments.

- __init__ resolves the endpoint as: explicit arg > AZURE_OPENAI_ENDPOINT env
  > the built-in _AZURE_ENDPOINTS table (previously a non-Azure endpoint could
  not be supplied at all).
- _get_client() builds a plain openai.OpenAI(base_url=...) client when
  AZURE_OPENAI_AUTH_MODE=openai_compatible, matching the auth mode already
  supported by the sibling skillopt/model/azure_openai.py. This avoids the
  AzureOpenAI SDK rewriting request URLs with Azure-only ?api-version= query
  params and deployment path segments, which non-Azure servers reject with 404.
- _call() sends max_tokens + extra_body thinking flag for deepseek* models and
  records the last exception in self.last_call_error so a failed night is
  diagnosable instead of collapsing to a silent empty->0 score.

Adds docs/sleep/openai-compatible-endpoints.md and sanitized example
runner/watchdog scripts documenting an Antigravity + DeepSeek integration.
The default managed-identity Azure path is unchanged.

docs/sleep/examples/watchdog.py

@@ -0,0 +1,56 @@
+#!/usr/bin/env python3
+"""Minimal supervisor that runs the SkillOpt-Sleep cycle on a fixed interval.
+
+Sanitized example (see docs/sleep/openai-compatible-endpoints.md). On Windows,
+register this under a Scheduled Task so it survives logout; on Linux/macOS a
+systemd timer or cron entry serves the same purpose and is usually preferable to
+a long-lived process.
+"""
+import os
+import sys
+import time
+import subprocess
+import datetime
+import traceback
+
+INTERVAL_SECONDS = int(os.environ.get("SKILLOPT_WATCHDOG_INTERVAL", str(4 * 3600)))
+RUNNER = os.environ.get("SKILLOPT_RUNNER", os.path.join(os.path.dirname(__file__), "runner.py"))
+LOG_FILE = os.environ.get("SKILLOPT_WATCHDOG_LOG", "brain/watchdog.log")
+
+
+def log(msg: str) -> None:
+    os.makedirs(os.path.dirname(LOG_FILE) or ".", exist_ok=True)
+    line = f"[{datetime.datetime.now().isoformat()}] {msg}"
+    with open(LOG_FILE, "a", encoding="utf-8") as f:
+        f.write(line + "\n")
+    print(line)
+
+
+def run_once() -> None:
+    log("Invoking skillopt-sleep run via runner.py...")
+    try:
+        result = subprocess.run([sys.executable, RUNNER, "run"],
+                                capture_output=True, text=True)
+        if result.returncode == 0:
+            log("Successfully completed run.")
+        else:
+            log(f"Run failed (exit {result.returncode}).")
+            log(f"STDERR: {result.stderr}")
+    except Exception as e:
+        log(f"Exception while running skillopt: {e}")
+        log(traceback.format_exc())
+
+
+def main() -> None:
+    log(f"Watchdog started. Interval: {INTERVAL_SECONDS}s.")
+    while True:
+        try:
+            run_once()
+        except Exception as e:
+            log(f"Unexpected error in watchdog loop: {e}")
+        log(f"Sleeping for {INTERVAL_SECONDS}s...")
+        time.sleep(INTERVAL_SECONDS)
+
+
+if __name__ == "__main__":
+    main()