38 lines
1.6 KiB
Python
38 lines
1.6 KiB
Python
"""Ollama VM123 + fallback — Spec 029 T1."""
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from __future__ import annotations
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import os
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import httpx
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OLLAMA_BASE_URL = os.getenv("OLLAMA_BASE_URL", "http://10.10.10.123:11434").rstrip("/")
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AGENTIC_LLM_MODEL = os.getenv("AGENTIC_LLM_MODEL", "qwen2.5:7b-instruct")
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AGENTIC_LLM_ENABLED = os.getenv("AGENTIC_LLM_ENABLED", "false").lower() in ("1", "true", "yes")
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def ollama_available() -> bool:
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try:
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with httpx.Client(timeout=3.0) as c:
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return c.get(f"{OLLAMA_BASE_URL}/api/tags").status_code == 200
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except Exception:
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return False
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def advise_human_action(*, finding_title: str, finding_detail: str, kb_snippets: list[str] | None = None) -> tuple[str, str]:
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prompt = (
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"Advisor Agentic Ops Ligbox. Português BR, máx 6 frases. O que fazer AGORA?\n"
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f"Problema: {finding_title}\nDetalhe: {finding_detail}\nKB: {'---'.join(kb_snippets or [])[:2500] or 'N/A'}"
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)
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if not AGENTIC_LLM_ENABLED:
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return (f"Investigar manualmente: {finding_title}", "t0")
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if ollama_available():
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try:
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with httpx.Client(timeout=90.0) as c:
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r = c.post(f"{OLLAMA_BASE_URL}/api/chat", json={
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"model": AGENTIC_LLM_MODEL,
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"messages": [{"role": "user", "content": prompt}],
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"stream": False,
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})
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if r.status_code == 200:
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txt = (r.json().get("message") or {}).get("content", "").strip()
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if txt:
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return txt, AGENTIC_LLM_MODEL
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except Exception:
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pass
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return (f"Rever logs e specs para: {finding_title}", "t0-fallback")
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