Every classification returned "HTTP Error 404" because the configured model gemma4:26b-64k no longer exists on the Ollama host: the tag was retired upstream and the local weights were deleted, so all pending updates fell back to manual review. Switch to the current gemma4:26b tag (25.2B, 262k context) and make it explicit in .env so the classifier no longer depends on the code default matching reality. PieFed intermittently returned an empty body, which surfaced as a current version error in the digest. Retry version fetches with a short backoff so one bad response no longer triggers an alert. Leave-one-out validation for the new model: immich 6/7 (the miss is the conditional-breaking example where the model follows the written rule that thresholds below the running version do not apply), freshrss 6/6, uptime-kuma 4/4.
157 lines
6.3 KiB
Python
157 lines
6.3 KiB
Python
import json
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import os
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from pathlib import Path
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from typing import Dict, List, Optional
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from urllib.request import Request, urlopen
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def load_update_examples(examples_dir: Path) -> List[Dict[str, str]]:
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examples = []
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for path in sorted(examples_dir.glob("*.txt")):
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text = path.read_text(encoding="utf-8")
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if "---" not in text:
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continue
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header, _, body = text.partition("---\n")
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action = reason = None
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for line in header.strip().splitlines():
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if line.startswith("action:"):
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action = line.split(":", 1)[1].strip()
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elif line.startswith("reason:"):
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reason = line.split(":", 1)[1].strip()
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if action not in ("auto", "manual"):
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continue
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examples.append({"action": action, "reason": reason or "", "notes": body.strip()})
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return examples
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class Classifier:
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def __init__(
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self,
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base_url: str = "",
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model: str = "",
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) -> None:
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self.base_url = base_url or os.getenv("OLLAMA_BASE_URL", "http://192.168.1.20:11434")
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self.model = model or os.getenv("OLLAMA_MODEL", "gemma4:26b")
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def classify(
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self,
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service_dir: Path,
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release_notes: Optional[str],
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current: str,
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latest: str,
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timeout: float,
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) -> Dict[str, str]:
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if not release_notes:
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return {"action": "manual", "reason": "No release notes available; defaulting to manual review."}
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examples_dir = service_dir / "review-examples"
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examples = load_update_examples(examples_dir) if examples_dir.is_dir() else []
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if not examples:
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return {"action": "manual", "reason": "No review examples configured; defaulting to manual review."}
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release_notes = self._truncate(release_notes)
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context_file = service_dir / "context.txt"
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context = context_file.read_text(encoding="utf-8").strip() if context_file.is_file() else None
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messages = self._build_messages(service_dir.name, examples, release_notes, current, latest, context)
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try:
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payload = json.dumps({
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"model": self.model,
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"messages": messages,
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"stream": False,
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"options": {"temperature": 0},
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}).encode("utf-8")
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req = Request(
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f"{self.base_url}/v1/chat/completions",
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data=payload,
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headers={"Content-Type": "application/json"},
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method="POST",
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)
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with urlopen(req, timeout=timeout) as resp:
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data = json.loads(resp.read())
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text = data["choices"][0]["message"]["content"].strip()
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start, end = text.find("{"), text.rfind("}") + 1
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if start == -1 or end == 0:
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raise ValueError(f"No JSON in response: {text[:200]}")
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result = json.loads(text[start:end])
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action = result.get("action", "")
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if action not in ("auto", "manual"):
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raise ValueError(f"Unexpected action value: {action!r}")
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return {"action": action, "reason": result.get("reason", "")}
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except Exception as exc:
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return {"action": "manual", "reason": f"Classification error: {exc}"}
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def _build_messages(
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self,
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service_name: str,
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examples: List[Dict[str, str]],
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release_notes: str,
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current: str,
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latest: str,
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context: Optional[str] = None,
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) -> List[Dict[str, str]]:
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system_prompt = (
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f"You are an update safety classifier for self-hosted {service_name} instances.\n"
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"Given release notes for a software update, decide whether the update can be applied\n"
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"automatically (action: auto) or requires the admin to intervene manually before or\n"
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"during the update (action: manual).\n\n"
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)
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if context:
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system_prompt += f"Instance context: {context}\n\n"
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system_prompt += (
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"Rules:\n"
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"- Only flag as manual if the breaking changes actually affect this specific setup.\n"
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"- Classify only THIS release, not future or past releases mentioned in the notes.\n"
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"- Warnings or announcements about breaking changes in upcoming versions do NOT\n"
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" make the current release manual.\n"
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"- Conditional notes like 'follow X instructions if upgrading from <= Y' only apply\n"
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" if the current running version is <= Y. If we are already past Y, they do not apply.\n"
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'- Respond ONLY with a JSON object: {"action": "auto", "reason": "..."}\n'
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' or {"action": "manual", "reason": "..."}\n'
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"- Keep reason under 60 words."
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)
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messages: List[Dict[str, str]] = [{"role": "system", "content": system_prompt}]
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for ex in examples:
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messages.append({"role": "user", "content": f"Release notes:\n{ex['notes']}"})
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messages.append({
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"role": "assistant",
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"content": json.dumps({"action": ex["action"], "reason": ex["reason"]}),
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})
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messages.append({
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"role": "user",
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"content": f"Upgrading from {current} to {latest}.\n\nRelease notes:\n{release_notes}",
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})
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return messages
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@staticmethod
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def _truncate(text: str, max_chars: int = 16000) -> str:
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if len(text) <= max_chars:
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return text
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# Split into sections by markdown headers
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import re
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sections = re.split(r'(?=^#{1,4}\s)', text, flags=re.MULTILINE)
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important_keywords = re.compile(
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r'breaking|deprecat|migrat|important|caution|warning|manual|required|must|before.*upgrad',
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re.IGNORECASE,
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)
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# Always keep the intro (first section) and any important sections
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kept = []
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skipped = 0
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for i, section in enumerate(sections):
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if i == 0 or important_keywords.search(section[:500]):
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kept.append(section)
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else:
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skipped += 1
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result = "".join(kept)
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if skipped:
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result += f"\n\n[... {skipped} sections of features/bug fixes omitted ...]"
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# Final safety truncation if still too long
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if len(result) > max_chars:
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result = result[:max_chars] + "\n\n[... truncated ...]"
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return result
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