chore(llm): one-shot OpenRouter free-tier reachability probe
Browse files
scripts/diagnose_openrouter.py
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"""Probe OpenRouter for which free-tier model IDs are reachable today.
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Reads OPENROUTER_API_KEY from .env (or process env). Issues a single
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8-token chat completion against a candidate list and prints one line per
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model: status (OK / HTTP-code / exception name) + a 30-char preview of
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the response when OK.
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Use:
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python scripts/diagnose_openrouter.py
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Or to probe a custom list:
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python scripts/diagnose_openrouter.py google/gemma-2-9b-it:free meta-llama/llama-3.2-3b-instruct:free
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"""
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from __future__ import annotations
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import os
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import sys
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from pathlib import Path
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# Manually parse .env without python-dotenv (some envs choke on its
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# frame-introspection in heredocs / non-stack-rooted callers).
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_env_path = Path(__file__).resolve().parent.parent / ".env"
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if _env_path.exists():
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for raw in _env_path.read_text().splitlines():
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s = raw.strip()
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if not s or s.startswith("#") or "=" not in s:
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continue
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k, v = s.split("=", 1)
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os.environ.setdefault(k.strip(), v.strip())
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if not os.environ.get("OPENROUTER_API_KEY"):
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sys.exit("OPENROUTER_API_KEY not set (looked in env and .env)")
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# Candidate list: well-known stable free-tier IDs as of 2026-Q2.
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# Update by replacing this list — script is a probe, not a config source.
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DEFAULT_CANDIDATES = [
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"google/gemma-2-9b-it:free",
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"google/gemini-2.0-flash-exp:free",
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"meta-llama/llama-3.2-3b-instruct:free",
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"meta-llama/llama-3.3-70b-instruct:free",
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"mistralai/mistral-7b-instruct:free",
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"qwen/qwen-2.5-72b-instruct:free",
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"deepseek/deepseek-r1:free",
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"deepseek/deepseek-chat:free",
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"nousresearch/hermes-3-llama-3.1-405b:free",
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"microsoft/phi-3-mini-128k-instruct:free",
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]
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candidates = sys.argv[1:] or DEFAULT_CANDIDATES
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from openai import ( # noqa: E402 (after env load)
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OpenAI, APIStatusError, APIConnectionError, RateLimitError, APITimeoutError,
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)
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client = OpenAI(
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base_url="https://openrouter.ai/api/v1",
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api_key=os.environ["OPENROUTER_API_KEY"],
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timeout=15.0,
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)
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for m in candidates:
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try:
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c = client.chat.completions.create(
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model=m,
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messages=[{"role": "user", "content": "Reply with the single word OK."}],
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max_tokens=8,
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temperature=0,
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)
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text = (c.choices[0].message.content or "").strip()
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print(f" OK {m} → {text[:30]!r}")
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except APIStatusError as e:
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code = getattr(e, "status_code", "?")
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print(f" {code:<5} {m}")
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except RateLimitError:
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print(f" 429 {m} (rate-limited)")
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except (APIConnectionError, APITimeoutError) as e:
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print(f" CONN {m} ({type(e).__name__})")
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except Exception as e:
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print(f" ERR {m} ({type(e).__name__}: {e})")
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