From aa9c63df735725aef48f28dfabee4bb8ffc78e92 Mon Sep 17 00:00:00 2001 From: lhl Date: Sun, 9 Aug 2026 13:48:00 +0800 Subject: [PATCH] =?UTF-8?q?feat:=20engine=20=E9=80=8F=E4=BC=A0=20error=5Fc?= =?UTF-8?q?ode=EF=BC=88=E4=B8=8E=20error=20=E5=90=8C=E6=BA=90=E5=8F=96?= =?UTF-8?q?=E6=9C=80=E5=90=8E=E4=B8=80=E6=AC=A1=E5=BC=82=E5=B8=B8=EF=BC=89?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- _AI_USAGE_LOG.md | 1 + src/genesis/inference/engine.py | 10 ++++-- tests/test_inference_engine.py | 59 +++++++++++++++++++++++++++++++++ 3 files changed, 67 insertions(+), 3 deletions(-) diff --git a/_AI_USAGE_LOG.md b/_AI_USAGE_LOG.md index 7adc093..d4633d9 100644 --- a/_AI_USAGE_LOG.md +++ b/_AI_USAGE_LOG.md @@ -54,3 +54,4 @@ | 2026-08-09 11:20 | 反馈迭代 | Web UI 设计评审（v1.0→v1.1，7 项发现全修）：以大赛手册+api-design 为权威基准审查 web-ui-design.md——F1 上传区补「概要设计做成说明书」独立 write_instruction file_type（api-design §2.2 连带扩展）+ 命名统一；F2 §4.1 任务队列 Redis 写死→抽象 TaskQueue（InMemory 默认/Redis/Valkey 可选）；F3 新增设置页 §3.6；F4 预览路径改 ContentBlock→chapter_html+docx；F5 生成页新增规则冲突卡片（WS conflict_pending→conflicts/{id}/resolve）；F6 新增会话历史页 §3.7；F7 新增 §7 无障碍与设计规范。同步 design.md §8 镜像（上传区/设置/队列/会话/冲突卡片/历史简版//history 命令）；产出评审报告 docs/web-ui-design-review-v1.1.md；docs/design.md、docs/api-design.md 连带修订 | docs/web-ui-design.md, docs/web-ui-design-review-v1.1.md, docs/api-design.md, docs/design.md, _AI_USAGE_LOG.md | deepseek-v4-flash-free | | 2026-08-09 11:45 | Agent 实现 | LLM 错误码对齐 Task1：异常树 error_code 类属性（LLMError 基类 None + four 子类 four 码，对齐 api-design §7），沿用现有中文 docstring 未改动。TDD RED（AttributeError: type object 'LLMError' has no attribute 'error_code'）→ GREEN（聚焦 4 passed，exceptions.py 100%）；聚焦单文件运行触发全库 fail-under=99 coverage exit 1 为基线行为（总覆盖 9.95%），与本次改动无关；加入 _AI_USAGE_LOG.md 提交 | src/genesis/inference/exceptions.py, tests/test_inference_errors.py, _AI_USAGE_LOG.md | deepseek-v4-flash-free | | 2026-08-09 13:42 | Agent 实现 | LLM 错误码对齐 Task2：ChatResult/StructuredResult 增加 error_code 字段（默认 None 向后兼容）。TDD RED（AttributeError: 'ChatResult' object has no attribute 'error_code'）→ GREEN（聚焦 8 passed，types.py 100%）；pytest 全量 123 passed 覆盖 100.00%（799 stmts/188 br），fail_under=99 达标；提交见 git log | src/genesis/inference/types.py, tests/test_inference_types.py, _AI_USAGE_LOG.md | deepseek-v4-flash-free | +| 2026-08-09 14:02 | Agent 实现 | LLM 错误码对齐 Task3：engine 失败/parse_error 路径透传 error_code（与 error 同源取最后一次异常）。chat() 循环记 last_error_code=exc.error_code，失败返回 error_code=last_error_code；chat_structured() 三路径：JSONDecodeError 分支置 last_error_code="LLM_PARSE_ERROR"（解析耗尽→parse_error）、LLMError 分支 early return 带 error_code=exc.error_code、循环后 parse_error 用 last_error_code。TDD RED（5 failed，error_code=None）→ GREEN（聚焦 22 passed）；pytest 全量 128 passed 覆盖 100.00%（803 stmts/188 br），fail_under=99 达标；提交见 git log | src/genesis/inference/engine.py, tests/test_inference_engine.py, _AI_USAGE_LOG.md | deepseek-v4-flash-free | diff --git a/src/genesis/inference/engine.py b/src/genesis/inference/engine.py index f8bae78..0f114af 100644 --- a/src/genesis/inference/engine.py +++ b/src/genesis/inference/engine.py @@ -101,6 +101,7 @@ class InferenceEngine: start = time.monotonic() last_error: str | None = None + last_error_code: str | None = None for idx, name in enumerate(self._model_names(model)): try: text, usage = self._call( @@ -115,12 +116,13 @@ class InferenceEngine: ) except LLMError as exc: last_error = str(exc) + last_error_code = exc.error_code # 同源：取最后一次失败异常 return ChatResult( text="", model=name, prompt_version=getattr(prompt, "version", "inline"), usage=TokenUsage(), duration_ms=int((time.monotonic() - start) * 1000), - status="failed", error=last_error, + status="failed", error=last_error, error_code=last_error_code, ) def chat_structured( @@ -144,6 +146,7 @@ class InferenceEngine: attempts = 0 last_raw = "" last_error: str | None = None + last_error_code: str | None = None while attempts <= retry_count: attempts += 1 @@ -166,6 +169,7 @@ class InferenceEngine: ) except json.JSONDecodeError as exc: last_error = f"JSON 解析失败: {exc}" + last_error_code = "LLM_PARSE_ERROR" # 带错误信息重试 base_rendered = base_rendered + f"\n\n上次解析失败：{exc}。请重新输出合法 JSON。" except LLMError as exc: @@ -175,7 +179,7 @@ class InferenceEngine: prompt_version=getattr(prompt, "version", "inline"), usage=TokenUsage(), duration_ms=int((time.monotonic() - start) * 1000), - status="failed", error=str(exc), + status="failed", error=str(exc), error_code=exc.error_code, ) return StructuredResult( @@ -184,5 +188,5 @@ class InferenceEngine: prompt_version=getattr(prompt, "version", "inline"), usage=TokenUsage(), duration_ms=int((time.monotonic() - start) * 1000), - status="parse_error", error=last_error, + status="parse_error", error=last_error, error_code=last_error_code, ) \ No newline at end of file diff --git a/tests/test_inference_engine.py b/tests/test_inference_engine.py index 93eb8e5..adc1c08 100644 --- a/tests/test_inference_engine.py +++ b/tests/test_inference_engine.py @@ -81,6 +81,65 @@ def test_chat_all_failed_returns_failed(): assert r.status == "failed" and r.error +# ---------- error_code 透传（与 error 同源取最后一次异常） ---------- + +def test_chat_failed_error_code_timeout(): + # 主模型超时 + 备用也失败：error_code 与 error 同源（取最后一次异常） + client = FakeLLMClient([("raise_timeout", ""), ("raise_timeout", "")]) + eng = InferenceEngine(client=client, models=Models()) + r = eng.chat(session_id="s1", prompt=Prompt(name="p", version="v1", template="t"), variables={}) + assert r.status == "failed" + assert r.error_code == "LLM_TIMEOUT" + + +def test_chat_failed_error_code_network_last(): + # 主模型超时（第一次）、备用网络失败（最后一次）→ error_code 取最后一次 = LLM_NETWORK_ERROR + client = FakeLLMClient([("raise_timeout", ""), ("raise_network", "")]) + eng = InferenceEngine(client=client, models=Models()) + r = eng.chat(session_id="s1", prompt=Prompt(name="p", version="v1", template="t"), variables={}) + assert r.status == "failed" + assert r.error_code == "LLM_NETWORK_ERROR" + + +def test_chat_failed_error_code_not_configured(): + # 备用模型 Key 缺失（最后一次）→ LLM_NOT_CONFIGURED + client = FakeLLMClient([("raise_network", ""), ("raise_timeout", "")]) + # 用自定义异常客户端模拟 NotConfigured + class NotConfiguredClient: + def __init__(self): + self.calls = [] + def chat(self, *, model, messages, temperature, max_tokens): + self.calls.append(model) + from genesis.inference.exceptions import LLMNotConfiguredError + raise LLMNotConfiguredError("no key") + eng = InferenceEngine(client=NotConfiguredClient(), models=Models()) + r = eng.chat(session_id="s1", prompt=Prompt(name="p", version="v1", template="t"), variables={}) + assert r.status == "failed" + assert r.error_code == "LLM_NOT_CONFIGURED" + + +def test_chat_structured_parse_error_code(): + client = FakeLLMClient([("parse_fail", ""), ("parse_fail", "")]) + eng = InferenceEngine(client=client, models=Models()) + r = eng.chat_structured( + session_id="s1", prompt=Prompt(name="p", version="v1", template="提取"), + variables={}, schema={}, retry_count=1, + ) + assert r.status == "parse_error" + assert r.error_code == "LLM_PARSE_ERROR" + + +def test_chat_structured_failed_error_code_network(): + client = FakeLLMClient([("raise_network", "")]) + eng = InferenceEngine(client=client, models=Models()) + r = eng.chat_structured( + session_id="s1", prompt=Prompt(name="p", version="v1", template="提取"), + variables={}, schema={}, + ) + assert r.status == "failed" + assert r.error_code == "LLM_NETWORK_ERROR" + + def test_chat_plain_string_prompt(): eng = make_engine(FakeLLMClient([("ok", "hi")])) r = eng.chat(session_id="s1", prompt="直接文本", variables={})