feat(backends): map LLM auth/rate-limit errors to backend-neutral errors
Closes the error-code gap between LangGraph and FastGPT backends: the endpoint's 401/429 branches previously could never trigger under the LangGraph backend because all provider failures collapsed into LLMAPIError (500). - agent/llm: LLMAuthError / LLMRateLimitError as LLMAPIError subclasses; OpenAILLMService raises them from openai AuthenticationError (401, no retry) and RateLimitError (429, after bounded retries exhausted) - backends/langgraph: _complete_turn translates LLMAuthError -> ChatBackendAuthenticationError and LLMRateLimitError -> ChatBackendRateLimitError; stream reuses complete() so the mapping applies to both paths; other errors (timeout etc.) propagate unchanged - endpoint untouched: existing 401/429 response branches now fire for both backends Verified: 212 unit tests (7 new error-mapping tests)
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@@ -27,6 +27,16 @@ class LLMAPIError(LLMError):
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"""provider 返回错误或无效响应。"""
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class LLMAuthError(LLMAPIError):
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"""provider 拒绝凭证(401)。不可重试,需区分上报(对照
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FastGPT 后端的 ChatBackendAuthenticationError 语义)。"""
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class LLMRateLimitError(LLMAPIError):
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"""provider 限流(429)。重试耗尽后抛出,需区分上报(对照
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FastGPT 后端的 ChatBackendRateLimitError 语义)。"""
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class LLMService(Protocol):
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"""节点依赖的最小 LLM 接口。"""
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@@ -128,7 +138,12 @@ class OpenAILLMService:
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) -> str:
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import asyncio
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from openai import APIConnectionError, APITimeoutError, RateLimitError
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from openai import (
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APIConnectionError,
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APITimeoutError,
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AuthenticationError,
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RateLimitError,
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)
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client = self._get_client()
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messages = [
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@@ -163,7 +178,15 @@ class OpenAILLMService:
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retries += 1
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await asyncio.sleep(min(2 ** retries, 10))
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continue
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if isinstance(exc, RateLimitError):
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# 限流耗尽:区分上报,API 层映射为 429(两后端错误码等价)
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raise LLMRateLimitError(
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f"LLM provider 限流(重试 {self._max_retries} 次后仍失败)"
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) from exc
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raise LLMAPIError(f"LLM provider 不可用:{type(exc).__name__}") from exc
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except AuthenticationError as exc:
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# 401 鉴权失败:不可重试,区分上报,API 层映射为 401
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raise LLMAuthError("LLM provider 认证失败") from exc
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except Exception as exc:
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# 其他错误(如 4xx 参数错)不可重试
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raise LLMAPIError(f"LLM 调用失败:{type(exc).__name__}") from exc
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