Adriano
3fcad79f8d
Run phase2-6-flat-wfa-001 è andato in hang per 4h+ a gen 3/10 su una chiamata OpenRouter (process stuck in do_poll syscall, 0% CPU). Il SDK OpenAI ha default timeout 600s ma evidentemente il TLS/socket handshake può bloccarsi senza interrompere; senza timeout esplicito i retry tenacity non scattano mai e il run resta pending. Fix: OpenAI(timeout=60.0). Se una chiamata supera 60s, raise APITimeoutError (già in _RETRYABLE_EXCEPTIONS) e tenacity ritenta fino a 5 volte con backoff esponenziale fino a 30s. Worst case totale: ~5×60s = 5min per call (vs 4h+ hang precedente). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
128 lines
4.1 KiB
Python
128 lines
4.1 KiB
Python
from __future__ import annotations
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from dataclasses import dataclass
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from typing import Any
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import openai
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from openai import OpenAI
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from tenacity import (
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retry,
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retry_if_exception_type,
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stop_after_attempt,
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wait_exponential,
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)
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from ..genome.hypothesis import HypothesisAgentGenome, ModelTier
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# Modelli configurati per Phase 1 — tutti via OpenRouter
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MODEL_TIER_S = "google/gemini-3-flash-preview"
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MODEL_TIER_A = "deepseek/deepseek-v4-flash"
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MODEL_TIER_B = "deepseek/deepseek-v4-flash"
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MODEL_TIER_C = "qwen/qwen-2.5-72b-instruct"
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MODEL_TIER_D = "openai/gpt-oss-20b"
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OPENROUTER_BASE_URL = "https://openrouter.ai/api/v1"
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class EmptyCompletionError(RuntimeError):
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pass
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# Errori transient: retry. Auth/InvalidRequest: NO retry.
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# RateLimitError (HTTP 429) ora retryable: provider OpenRouter come DeepInfra
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# applicano rate limit upstream temporaneo, recuperabile con backoff.
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_RETRYABLE_EXCEPTIONS: tuple[type[BaseException], ...] = (
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openai.APIConnectionError,
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openai.APITimeoutError,
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openai.InternalServerError,
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openai.RateLimitError,
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EmptyCompletionError,
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)
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@dataclass(frozen=True)
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class CompletionResult:
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text: str
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input_tokens: int
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output_tokens: int
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tier: ModelTier
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model: str
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class LLMClient:
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# Provider OpenRouter da escludere di default. Novita rifiuta /completions
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# endpoint per modelli Qwen 2.x — vedi bug 2026-05-12.
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DEFAULT_PROVIDER_IGNORE: tuple[str, ...] = ("Novita",)
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def __init__(
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self,
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openrouter_api_key: str,
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model_tier_s: str = MODEL_TIER_S,
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model_tier_a: str = MODEL_TIER_A,
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model_tier_b: str = MODEL_TIER_B,
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model_tier_c: str = MODEL_TIER_C,
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model_tier_d: str = MODEL_TIER_D,
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openrouter_base_url: str = OPENROUTER_BASE_URL,
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provider_ignore: tuple[str, ...] | None = None,
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) -> None:
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self.model_tier_s = model_tier_s
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self.model_tier_a = model_tier_a
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self.model_tier_b = model_tier_b
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self.model_tier_c = model_tier_c
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self.model_tier_d = model_tier_d
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self.openrouter_base_url = openrouter_base_url
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self._provider_ignore = (
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provider_ignore if provider_ignore is not None else self.DEFAULT_PROVIDER_IGNORE
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)
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self._tier_models: dict[ModelTier, str] = {
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ModelTier.S: model_tier_s,
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ModelTier.A: model_tier_a,
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ModelTier.B: model_tier_b,
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ModelTier.C: model_tier_c,
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ModelTier.D: model_tier_d,
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}
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# Timeout esplicito (60s) per prevenire hang infinito su connessioni
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# stallate. Tenacity retry su APITimeoutError gestisce il recovery.
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self._client = OpenAI(
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api_key=openrouter_api_key,
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base_url=openrouter_base_url,
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timeout=60.0,
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)
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@retry(
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stop=stop_after_attempt(5),
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wait=wait_exponential(multiplier=2.0, min=2.0, max=30.0),
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retry=retry_if_exception_type(_RETRYABLE_EXCEPTIONS),
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reraise=True,
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)
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def complete(
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self,
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genome: HypothesisAgentGenome,
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system: str,
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user: str,
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max_tokens: int = 2000,
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) -> CompletionResult:
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model = self._tier_models[genome.model_tier]
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extra_body: dict[str, Any] = {}
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if self._provider_ignore:
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extra_body["provider"] = {"ignore": list(self._provider_ignore)}
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resp = self._client.chat.completions.create(
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model=model,
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messages=[
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{"role": "system", "content": system},
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{"role": "user", "content": user},
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],
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temperature=genome.temperature,
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top_p=genome.top_p,
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max_tokens=max_tokens,
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extra_body=extra_body or None,
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)
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if not resp.choices or resp.choices[0].message.content is None:
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raise EmptyCompletionError(f"empty response from {model}")
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usage = resp.usage
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return CompletionResult(
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text=resp.choices[0].message.content,
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input_tokens=usage.prompt_tokens if usage else 0,
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output_tokens=usage.completion_tokens if usage else 0,
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tier=genome.model_tier,
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model=model,
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)
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