diff --git a/configs/system.yaml b/configs/system.yaml index 6964e02..501b5aa 100644 --- a/configs/system.yaml +++ b/configs/system.yaml @@ -43,10 +43,10 @@ dedup: # ── LLM 翻译+事件抽取 ──────────────────────────────── llm: provider: "deepseek" - deepseek_model: "deepseek-chat" + deepseek_model: "deepseek-v4-flash" qwen_model: "qwen-plus" timeout_sec: 60 - max_retries: 3 + max_attempts: 3 # 单篇总尝试次数（含首次），失败后指数退避重试；日报 AI 摘要同用此值 max_tokens: 8192 temperature: 0.1 concurrency: 3 @@ -57,6 +57,7 @@ embedding: dashscope_model: "text-embedding-v3" dimension: 1024 batch_size: 10 + max_attempts: 3 # 单批总尝试次数（含首次），失败后指数退避重试 timeout_sec: 30 # ── Qdrant ────────────────────────────────────────── diff --git a/embedding/client.py b/embedding/client.py index 1b70225..17dabb7 100644 --- a/embedding/client.py +++ b/embedding/client.py @@ -92,6 +92,7 @@ def load_embedding_config( dimension = int(sys_cfg.get("dimension", DASHSCOPE_DEFAULT_DIM)) batch_size = min(int(sys_cfg.get("batch_size", DASHSCOPE_BATCH_LIMIT)), DASHSCOPE_BATCH_LIMIT) timeout = float(sys_cfg.get("timeout_sec", 30.0)) + max_attempts = int(sys_cfg.get("max_attempts", DEFAULT_MAX_ATTEMPTS)) if not api_key: raise EmbeddingError("DASHSCOPE_API_KEY 未配置，请检查 .env") @@ -104,6 +105,7 @@ def load_embedding_config( dimension=dimension, batch_size=batch_size, timeout_sec=timeout, + max_attempts=max_attempts, ) diff --git a/llm/client.py b/llm/client.py index 728aa5e..d0d5dea 100644 --- a/llm/client.py +++ b/llm/client.py @@ -25,6 +25,9 @@ _QWEN_DEFAULT_BASE = "https://dashscope.aliyuncs.com/compatible-mode/v1" _DEEPSEEK_DEFAULT_MODEL = "deepseek-chat" _QWEN_DEFAULT_MODEL = "qwen-plus" +# 默认单次调用总尝试次数（含首次；system.yaml llm.max_attempts 未配置时兜底） +_DEFAULT_MAX_ATTEMPTS = 3 + def _load_system_config() -> dict: """加载 configs/system.yaml 中 llm 段配置。""" @@ -50,6 +53,7 @@ class LLMConfig: timeout_sec: float = 60.0 temperature: float = 0.1 max_tokens: int = 8192 + max_attempts: int = _DEFAULT_MAX_ATTEMPTS # 单次调用总尝试次数（含首次） def __post_init__(self) -> None: if not self.api_key: @@ -93,6 +97,7 @@ def load_llm_config( timeout = float(config.get("timeout_sec", 60.0)) temperature = float(config.get("temperature", 0.1)) max_tokens = int(config.get("max_tokens", 8192)) + max_attempts = int(config.get("max_attempts", _DEFAULT_MAX_ATTEMPTS)) return LLMConfig( provider=p, @@ -102,6 +107,7 @@ def load_llm_config( timeout_sec=timeout, temperature=temperature, max_tokens=max_tokens, + max_attempts=max_attempts, ) diff --git a/llm/extractor.py b/llm/extractor.py index 1397584..f785195 100644 --- a/llm/extractor.py +++ b/llm/extractor.py @@ -226,7 +226,7 @@ def translate_and_extract( article: ProcessedArticle, *, template: PromptTemplate | None = None, - max_attempts: int = DEFAULT_MAX_ATTEMPTS, + max_attempts: int | None = None, ) -> EnTranslatedArticle: """同步翻译 + 事件抽取（单篇文章，带重试）。 @@ -235,7 +235,8 @@ def translate_and_extract( config: LLM 配置 article: 待处理的英文新闻 template: Prompt 模板，默认加载 prompts/translation_and_extraction.md - max_attempts: 最大重试次数 + max_attempts: 最大尝试次数（含首次）；None 时取 config.max_attempts + （来自 system.yaml llm.max_attempts） Returns: EnTranslatedArticle 含双语内容 + 事件 @@ -243,6 +244,8 @@ def translate_and_extract( Raises: LLMCallError: 所有重试均失败 """ + if max_attempts is None: + max_attempts = config.max_attempts tpl = template or PromptTemplate() system_prompt, user_prompt = tpl.render(article) @@ -305,10 +308,12 @@ async def translate_and_extract_async( article: ProcessedArticle, *, template: PromptTemplate | None = None, - max_attempts: int = DEFAULT_MAX_ATTEMPTS, + max_attempts: int | None = None, semaphore: asyncio.Semaphore | None = None, ) -> EnTranslatedArticle: """异步翻译 + 事件抽取（批处理用），与同步版逻辑等价。""" + if max_attempts is None: + max_attempts = config.max_attempts tpl = template or PromptTemplate() system_prompt, user_prompt = tpl.render(article) diff --git a/scheduler/reporter.py b/scheduler/reporter.py index 77c1250..057a02f 100644 --- a/scheduler/reporter.py +++ b/scheduler/reporter.py @@ -283,7 +283,7 @@ def _call_llm_simple( system_prompt: str, user_prompt: str, max_tokens: int = 600, - max_retries: int = 2, + max_retries: int | None = None, ) -> str: """封装 LLM 调用，带重试和客户端复用。 @@ -291,7 +291,8 @@ def _call_llm_simple( system_prompt: system role 内容 user_prompt: user role 内容 max_tokens: 最大输出 token - max_retries: 最大重试次数（不含首次调用） + max_retries: 重试次数（不含首次）；None 时取 + config.max_attempts - 1（system.yaml llm.max_attempts） Returns: LLM 输出文本；所有重试均失败返回空字符串 @@ -308,6 +309,9 @@ def _call_llm_simple( config = _llm_client_cache["config"] client = _llm_client_cache[cache_key] + if max_retries is None: + max_retries = max(config.max_attempts - 1, 0) + last_err: str = "" for attempt in range(1, max_retries + 2): # 首次 + max_retries 次重试 try: diff --git a/tests/test_embedding.py b/tests/test_embedding.py index 89da9af..91cf684 100644 --- a/tests/test_embedding.py +++ b/tests/test_embedding.py @@ -87,6 +87,12 @@ class TestLoadEmbeddingConfig: assert cfg.provider == "dashscope" assert cfg.api_key == "sk-dashscope-test" + def test_max_attempts_from_system_yaml(self, monkeypatch): + """重试次数取自 system.yaml embedding.max_attempts（当前 3）。""" + monkeypatch.setenv("DASHSCOPE_API_KEY", "sk-dashscope-test") + cfg = load_embedding_config() + assert cfg.max_attempts == 3 + def test_fallback_to_qwen_key(self, monkeypatch): monkeypatch.delenv("DASHSCOPE_API_KEY", raising=False) monkeypatch.setenv("QWEN_API_KEY", "sk-qwen-key") diff --git a/tests/test_llm.py b/tests/test_llm.py index 408cad0..0f3e6a8 100644 --- a/tests/test_llm.py +++ b/tests/test_llm.py @@ -457,6 +457,12 @@ class TestLoadLLMConfig: with pytest.raises(ValueError, match="API key 未配置"): load_llm_config(provider="deepseek") + def test_max_attempts_from_system_yaml(self, monkeypatch): + """重试次数取自 system.yaml llm.max_attempts（当前 3）。""" + monkeypatch.setenv("DEEPSEEK_API_KEY", "sk-deepseek-test-key") + config = load_llm_config(provider="deepseek") + assert config.max_attempts == 3 + # --------------------------------------------------------------------------- # # translate_and_extract（mock LLM）