Alphaxalchemy
af33f6c338
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.
57 lines
1.8 KiB
Python
57 lines
1.8 KiB
Python
#!/usr/bin/env python3
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"""Minimal supervisor that runs the SkillOpt-Sleep cycle on a fixed interval.
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Sanitized example (see docs/sleep/openai-compatible-endpoints.md). On Windows,
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register this under a Scheduled Task so it survives logout; on Linux/macOS a
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systemd timer or cron entry serves the same purpose and is usually preferable to
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a long-lived process.
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"""
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import os
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import sys
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import time
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import subprocess
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import datetime
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import traceback
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INTERVAL_SECONDS = int(os.environ.get("SKILLOPT_WATCHDOG_INTERVAL", str(4 * 3600)))
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RUNNER = os.environ.get("SKILLOPT_RUNNER", os.path.join(os.path.dirname(__file__), "runner.py"))
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LOG_FILE = os.environ.get("SKILLOPT_WATCHDOG_LOG", "brain/watchdog.log")
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def log(msg: str) -> None:
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os.makedirs(os.path.dirname(LOG_FILE) or ".", exist_ok=True)
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line = f"[{datetime.datetime.now().isoformat()}] {msg}"
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with open(LOG_FILE, "a", encoding="utf-8") as f:
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f.write(line + "\n")
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print(line)
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def run_once() -> None:
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log("Invoking skillopt-sleep run via runner.py...")
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try:
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result = subprocess.run([sys.executable, RUNNER, "run"],
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capture_output=True, text=True)
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if result.returncode == 0:
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log("Successfully completed run.")
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else:
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log(f"Run failed (exit {result.returncode}).")
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log(f"STDERR: {result.stderr}")
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except Exception as e:
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log(f"Exception while running skillopt: {e}")
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log(traceback.format_exc())
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def main() -> None:
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log(f"Watchdog started. Interval: {INTERVAL_SECONDS}s.")
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while True:
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try:
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run_once()
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except Exception as e:
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log(f"Unexpected error in watchdog loop: {e}")
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log(f"Sleeping for {INTERVAL_SECONDS}s...")
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time.sleep(INTERVAL_SECONDS)
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if __name__ == "__main__":
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main()
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