John Wilganowski
afa1089311
- Job logs: each job's stdout/stderr is teed into outputs/<id>/job.log
(survives restarts) and served at GET /jobs/{id}/log as text/plain, so
full run logs can be shared for debugging and refinement.
- Model picker: GET /models proxies OpenRouter's public model list with
per-1M-token pricing (1h cache, 502 on failure); the UI shows a model
dropdown with costs when OpenRouter compute is selected, and the pick
overrides vision+text models for that job (Classic and Agent modes).
- Conflicts in the report view are grouped by discipline pair
(collapsible sections, severity-ordered within groups) instead of one
flat severity-only list.
66 lines
2.0 KiB
Python
66 lines
2.0 KiB
Python
"""
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models.py - Fetch the available OpenRouter model list with pricing (cached).
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The /models endpoint is public (no API key needed). Results are normalized to
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per-1M-token USD costs for display and cached in memory for an hour; callers
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degrade gracefully when OpenRouter is unreachable.
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"""
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import time
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from typing import List, Optional
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import httpx
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from backend import config
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_CACHE_TTL_SECONDS = 3600
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_cache = {"at": 0.0, "models": None}
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def _per_mtok(rate) -> float:
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"""OpenRouter pricing is USD per token (as a string); display is per 1M."""
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try:
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return round(float(rate) * 1_000_000, 4)
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except (TypeError, ValueError):
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return 0.0
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def _fetch_openrouter_models() -> Optional[List[dict]]:
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"""Raw GET of the OpenRouter model list; None on any failure."""
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try:
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response = httpx.get(f"{config.AI_BASE_URL.rstrip('/')}/models", timeout=10)
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response.raise_for_status()
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data = response.json().get("data")
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return data if isinstance(data, list) else None
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except Exception as e:
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print(f"[Models] OpenRouter /models fetch failed: {e}")
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return None
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def fetch_models(force: bool = False) -> Optional[List[dict]]:
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"""Normalized model list for the UI picker, or None when unavailable."""
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if (
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not force
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and _cache["models"] is not None
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and time.time() - _cache["at"] < _CACHE_TTL_SECONDS
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):
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return _cache["models"]
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data = _fetch_openrouter_models()
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if data is None:
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return None
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models = [
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{
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"id": item.get("id") or "",
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"name": item.get("name") or item.get("id") or "",
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"prompt_usd_per_mtok": _per_mtok((item.get("pricing") or {}).get("prompt")),
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"completion_usd_per_mtok": _per_mtok((item.get("pricing") or {}).get("completion")),
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"context_length": item.get("context_length"),
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}
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for item in data
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if item.get("id")
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]
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models.sort(key=lambda m: m["id"])
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_cache["models"] = models
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_cache["at"] = time.time()
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return models
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