woogiandCursor
a6b0c8fdfa
Capture pipeline stdout into job.log + API/UI so failed runs can be reviewed, and let users pick OpenRouter vision vs text models independently. Co-authored-by: Cursor <cursoragent@cursor.com>
102 lines
3.4 KiB
Python
102 lines
3.4 KiB
Python
"""
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models_catalog.py - OpenRouter model list for the UI dropdowns.
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Fetches https://openrouter.ai/api/v1/models (cached ~1h) and splits into:
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- vision: accepts image input and returns text
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- text: chat models that return text (may also be multimodal)
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"""
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import time
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from typing import Any, Dict, List
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from backend import config
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_TTL_SEC = 3600
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_cache: Dict[str, Any] = {"at": 0.0, "payload": None}
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def _entry(m: Dict[str, Any]) -> Dict[str, str]:
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return {
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"id": m.get("id") or "",
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"name": m.get("name") or m.get("id") or "",
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}
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def _ensure_default(items: List[Dict[str, str]], model_id: str) -> List[Dict[str, str]]:
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"""Prepend the configured default if OpenRouter didn't return it."""
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if not model_id:
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return items
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if any(x["id"] == model_id for x in items):
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return items
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return [{"id": model_id, "name": model_id}] + items
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def _fetch_raw() -> List[Dict[str, Any]]:
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import httpx # local import so the app can start without httpx in odd envs
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headers = {"Accept": "application/json"}
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if config.AI_API_KEY:
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headers["Authorization"] = f"Bearer {config.AI_API_KEY}"
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url = f"{config.AI_BASE_URL.rstrip('/')}/models"
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# Ask for text-output chat models (includes multimodal). "all" is huge.
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with httpx.Client(timeout=30.0) as client:
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r = client.get(url, headers=headers, params={"output_modalities": "text"})
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r.raise_for_status()
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data = r.json()
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return data.get("data") or []
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def list_models() -> Dict[str, Any]:
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"""Return {vision, text, defaults} for the frontend selects."""
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now = time.time()
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if _cache["payload"] and (now - _cache["at"]) < _TTL_SEC:
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return _cache["payload"]
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try:
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raw = _fetch_raw()
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except Exception as e:
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# Degrade to configured defaults so the UI still works offline.
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print(f"[Models] OpenRouter catalog fetch failed: {e}")
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vision = _ensure_default([], config.MODEL)
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text = _ensure_default([], config.TEXT_MODEL)
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payload = {
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"vision": vision,
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"text": text,
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"defaults": {"vision": config.MODEL, "text": config.TEXT_MODEL},
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"error": str(e),
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}
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return payload
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vision: List[Dict[str, str]] = []
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text: List[Dict[str, str]] = []
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for m in raw:
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mid = m.get("id") or ""
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if not mid:
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continue
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arch = m.get("architecture") or {}
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inputs = arch.get("input_modalities") or []
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outputs = arch.get("output_modalities") or []
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# Legacy string form: "text+image->text"
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modality = (arch.get("modality") or "").lower()
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has_image_in = ("image" in inputs) or ("image" in modality.split("->")[0])
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has_text_out = ("text" in outputs) or ("->text" in modality) or (not outputs and not modality)
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has_text_in = ("text" in inputs) or ("text" in modality) or not inputs
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if has_image_in and has_text_out:
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vision.append(_entry(m))
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if has_text_in and has_text_out:
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text.append(_entry(m))
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vision.sort(key=lambda x: x["name"].lower())
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text.sort(key=lambda x: x["name"].lower())
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vision = _ensure_default(vision, config.MODEL)
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text = _ensure_default(text, config.TEXT_MODEL)
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payload = {
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"vision": vision,
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"text": text,
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"defaults": {"vision": config.MODEL, "text": config.TEXT_MODEL},
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}
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_cache["at"] = now
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_cache["payload"] = payload
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return payload
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