"""OpenAI-compatible Judge client with a durable append-only cache. Two request shapes, chosen by model name. Reasoning models are served on ``/responses`` instead of ``/chat/completions`` -- on the gateway this benchmark was scored with, a ``gpt-5.x`` model has no chat/completions cluster at all, so sending one there fails rather than falling back -- and they take an output-token budget and a reasoning effort in place of a temperature. Everything else uses ``/chat/completions``. """ from __future__ import annotations import hashlib import json import random import threading import time from pathlib import Path # Chat models: deterministic decoding. JUDGE_TEMPERATURE = 0.0 JUDGE_MAX_TOKENS = 2048 # Reasoning models: no temperature knob. Thinking is disabled so the Judge is # scoring rather than deliberating, and the token budget is higher because the # reasoning envelope counts against it even at effort "none". JUDGE_MAX_OUTPUT_TOKENS = 4096 JUDGE_REASONING_EFFORT = "none" def uses_responses_endpoint(model: str) -> bool: return model.startswith(("gpt-5", "gpt-6", "o1", "o3", "o4")) class JudgeRequestError(RuntimeError): pass class JudgeClient: def __init__( self, *, api_key: str, base_url: str, model: str, prompt_version: str, cache_path: Path, timeout: float = 360.0, max_attempts: int = 6, ) -> None: if not api_key: raise ValueError("JUDGE_API_KEY is required") from openai import OpenAI self.model = model self.prompt_version = prompt_version self.timeout = timeout self.max_attempts = max_attempts self._use_responses = uses_responses_endpoint(model) self.cache_path = cache_path self.cache_path.parent.mkdir(parents=True, exist_ok=True) self._client = OpenAI(api_key=api_key, base_url=base_url, timeout=timeout) self._lock = threading.Lock() self._cache: dict[str, str] = {} self._load_cache() def _key(self, prompt: str) -> str: # The decoding parameters belong in the key, and the two endpoints do not # share a set: keying a /responses verdict on a temperature it never used # would let a cached chat verdict answer a reasoning-model request. if self._use_responses: params: dict[str, object] = { "endpoint": "responses", "max_output_tokens": JUDGE_MAX_OUTPUT_TOKENS, "reasoning_effort": JUDGE_REASONING_EFFORT, } else: params = { "endpoint": "chat.completions", "temperature": JUDGE_TEMPERATURE, "max_tokens": JUDGE_MAX_TOKENS, } payload = json.dumps( { "model": self.model, "prompt_version": self.prompt_version, "prompt": prompt, **params, }, ensure_ascii=False, sort_keys=True, separators=(",", ":"), ) return hashlib.sha256(payload.encode("utf-8")).hexdigest() def _load_cache(self) -> None: if not self.cache_path.is_file(): return with self.cache_path.open(encoding="utf-8") as handle: for line_number, line in enumerate(handle, 1): if not line.strip(): continue try: record = json.loads(line) self._cache[record["key"]] = record["response"] except (json.JSONDecodeError, KeyError, TypeError): # An interrupted final append must not destroy earlier cache entries. if line_number > 1: continue def _cache_put(self, key: str, response: str) -> None: with self._lock: if key in self._cache: return self._cache[key] = response with self.cache_path.open("a", encoding="utf-8") as handle: handle.write(json.dumps({"key": key, "response": response}, ensure_ascii=False)) handle.write("\n") handle.flush() def _complete_via_chat(self, prompt: str) -> str: response = self._client.chat.completions.create( model=self.model, messages=[{"role": "user", "content": prompt}], temperature=JUDGE_TEMPERATURE, max_tokens=JUDGE_MAX_TOKENS, ) return response.choices[0].message.content or "" def _complete_via_responses(self, prompt: str) -> str: response = self._client.responses.create( model=self.model, input=prompt, max_output_tokens=JUDGE_MAX_OUTPUT_TOKENS, reasoning={"effort": JUDGE_REASONING_EFFORT}, ) # Walk the output blocks rather than reading output_text: with reasoning # enabled the array also carries reasoning items, and a provider that # ignores effort="none" would otherwise fold thinking into the verdict. parts = [] for block in response.output or []: if getattr(block, "type", None) != "message": continue for item in getattr(block, "content", None) or []: if getattr(item, "type", None) == "output_text": parts.append(getattr(item, "text", "") or "") return "".join(parts) def complete(self, prompt: str) -> tuple[str, bool]: """Return (response_text, served_from_cache).""" key = self._key(prompt) with self._lock: cached = self._cache.get(key) if cached is not None: return cached, True error: BaseException | None = None for attempt in range(self.max_attempts): try: content = ( self._complete_via_responses(prompt) if self._use_responses else self._complete_via_chat(prompt) ) self._cache_put(key, content) return content, False except BaseException as exc: error = exc status_code = getattr(exc, "status_code", None) retryable = status_code == 429 or ( isinstance(status_code, int) and 500 <= status_code < 600 ) # Connection/transport failures usually have no HTTP status. if status_code is None: retryable = True if retryable and attempt + 1 < self.max_attempts: time.sleep(min(2 ** (attempt + 1), 60) + random.uniform(0, 1)) continue break raise JudgeRequestError( f"Judge request failed after {self.max_attempts} attempts: {error}" ) from error @property def cache_entries(self) -> int: return len(self._cache)