Files
Multi_Swarm_Coevolutive/src/multi_swarm/llm/client.py
T
Adriano 0e01de156f fix(llm): RateLimitError retryable + retry tenacity 3→5 + backoff fino a 30s
Run phase2-5-qwen25-prompt-mut-003 fallito a gen 5 (76 evals done, $0.061
spesi) per HTTP 429 RateLimit upstream da DeepInfra su qwen-2.5-72b.
RateLimitError NON era in _RETRYABLE_EXCEPTIONS quindi tenacity falliva
subito, propagando il 429 a propose() e all'orchestrator (run failed).

Tre fix:
1) Aggiunto openai.RateLimitError a _RETRYABLE_EXCEPTIONS.
2) Bumpato stop_after_attempt(3) → 5 e wait_exponential max 10s → 30s.
   Più tempo per il rate limit upstream di sbloccare prima di rinunciare.
3) hypothesis.py: try/except RateLimitError in propose() come per
   EmptyCompletionError — anche se tenacity esaurisce i 5 retry, il genome
   viene marcato fitness=0 e il loop esterno continua senza crash totale.

Test: aggiornato test_completion_retries_on_connection_error per
assert call_count == 5 (era 3). Tutti 182 verdi.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-12 00:44:32 +02:00

122 lines
3.9 KiB
Python

from __future__ import annotations
from dataclasses import dataclass
from typing import Any
import openai
from openai import OpenAI
from tenacity import (
retry,
retry_if_exception_type,
stop_after_attempt,
wait_exponential,
)
from ..genome.hypothesis import HypothesisAgentGenome, ModelTier
# Modelli configurati per Phase 1 — tutti via OpenRouter
MODEL_TIER_S = "google/gemini-3-flash-preview"
MODEL_TIER_A = "deepseek/deepseek-v4-flash"
MODEL_TIER_B = "deepseek/deepseek-v4-flash"
MODEL_TIER_C = "qwen/qwen-2.5-72b-instruct"
MODEL_TIER_D = "openai/gpt-oss-20b"
OPENROUTER_BASE_URL = "https://openrouter.ai/api/v1"
class EmptyCompletionError(RuntimeError):
pass
# Errori transient: retry. Auth/InvalidRequest: NO retry.
# RateLimitError (HTTP 429) ora retryable: provider OpenRouter come DeepInfra
# applicano rate limit upstream temporaneo, recuperabile con backoff.
_RETRYABLE_EXCEPTIONS: tuple[type[BaseException], ...] = (
openai.APIConnectionError,
openai.APITimeoutError,
openai.InternalServerError,
openai.RateLimitError,
EmptyCompletionError,
)
@dataclass(frozen=True)
class CompletionResult:
text: str
input_tokens: int
output_tokens: int
tier: ModelTier
model: str
class LLMClient:
# Provider OpenRouter da escludere di default. Novita rifiuta /completions
# endpoint per modelli Qwen 2.x — vedi bug 2026-05-12.
DEFAULT_PROVIDER_IGNORE: tuple[str, ...] = ("Novita",)
def __init__(
self,
openrouter_api_key: str,
model_tier_s: str = MODEL_TIER_S,
model_tier_a: str = MODEL_TIER_A,
model_tier_b: str = MODEL_TIER_B,
model_tier_c: str = MODEL_TIER_C,
model_tier_d: str = MODEL_TIER_D,
openrouter_base_url: str = OPENROUTER_BASE_URL,
provider_ignore: tuple[str, ...] | None = None,
) -> None:
self.model_tier_s = model_tier_s
self.model_tier_a = model_tier_a
self.model_tier_b = model_tier_b
self.model_tier_c = model_tier_c
self.model_tier_d = model_tier_d
self.openrouter_base_url = openrouter_base_url
self._provider_ignore = (
provider_ignore if provider_ignore is not None else self.DEFAULT_PROVIDER_IGNORE
)
self._tier_models: dict[ModelTier, str] = {
ModelTier.S: model_tier_s,
ModelTier.A: model_tier_a,
ModelTier.B: model_tier_b,
ModelTier.C: model_tier_c,
ModelTier.D: model_tier_d,
}
self._client = OpenAI(api_key=openrouter_api_key, base_url=openrouter_base_url)
@retry(
stop=stop_after_attempt(5),
wait=wait_exponential(multiplier=2.0, min=2.0, max=30.0),
retry=retry_if_exception_type(_RETRYABLE_EXCEPTIONS),
reraise=True,
)
def complete(
self,
genome: HypothesisAgentGenome,
system: str,
user: str,
max_tokens: int = 2000,
) -> CompletionResult:
model = self._tier_models[genome.model_tier]
extra_body: dict[str, Any] = {}
if self._provider_ignore:
extra_body["provider"] = {"ignore": list(self._provider_ignore)}
resp = self._client.chat.completions.create(
model=model,
messages=[
{"role": "system", "content": system},
{"role": "user", "content": user},
],
temperature=genome.temperature,
top_p=genome.top_p,
max_tokens=max_tokens,
extra_body=extra_body or None,
)
if not resp.choices or resp.choices[0].message.content is None:
raise EmptyCompletionError(f"empty response from {model}")
usage = resp.usage
return CompletionResult(
text=resp.choices[0].message.content,
input_tokens=usage.prompt_tokens if usage else 0,
output_tokens=usage.completion_tokens if usage else 0,
tier=genome.model_tier,
model=model,
)