feat: engine 透传 error_code（与 error 同源取最后一次异常）

2026-08-09 13:48:00 +08:00
parent 3b98412492
commit aa9c63df73
3 changed files with 67 additions and 3 deletions
@@ -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={})