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ai-agent-book 精选快照(<2MB 代码与文档,来自 github.com/bojieli/ai-agent-book)
2026-08-20 13:12:50 +00:00

82 lines
3.0 KiB
Python

"""回归测试:模型传错/漏工具参数时,编排器不应崩溃,而应把错误作为工具结果
回给模型(让它自行纠正),流程继续推进到最终回复。
此前 orchestrator.py 的 `impl(**args)` 未加保护:{"q": ...} 这类错键名、
缺必填参数、或无法 float() 转换的取值都会以 TypeError/ValueError 炸掉整个
多角色移交流程。
"""
import json
import sys
from types import SimpleNamespace
from orchestrator import MultiRoleOrchestrator
FINAL_TEXT = "已查完,最终汇报。"
def _tool_call_msg(name, arguments):
tc = SimpleNamespace(
id="call_1", type="function",
function=SimpleNamespace(name=name, arguments=arguments))
return SimpleNamespace(choices=[SimpleNamespace(
message=SimpleNamespace(content=None, tool_calls=[tc]))])
def _final_msg():
return SimpleNamespace(choices=[SimpleNamespace(
message=SimpleNamespace(content=FINAL_TEXT, tool_calls=None))])
def _fake_client(responses):
queue = list(responses)
return SimpleNamespace(chat=SimpleNamespace(
completions=SimpleNamespace(create=lambda **kw: queue.pop(0))))
def _run_with_bad_tool_args(tool_name, arguments):
orch = MultiRoleOrchestrator(
client=_fake_client([_tool_call_msg(tool_name, arguments), _final_msg()]),
verbose=False, start_role="research")
final = orch.run("查一下新能源汽车销量")
tool_results = [m["content"] for m in orch.history if m["role"] == "tool"]
return final, tool_results
def test_wrong_arg_name_returns_error_string_not_crash():
final, tool_results = _run_with_bad_tool_args(
"web_search", json.dumps({"q": "新能源汽车销量"}))
assert final == FINAL_TEXT
assert any("调用失败" in r for r in tool_results)
def test_missing_required_arg_returns_error_string_not_crash():
final, tool_results = _run_with_bad_tool_args("web_search", "{}")
assert final == FINAL_TEXT
assert any("调用失败" in r for r in tool_results)
def test_non_numeric_stats_input_returns_error_string_not_crash():
final, tool_results = _run_with_bad_tool_args(
"descriptive_stats", json.dumps({"numbers": ["a", "b"]}))
assert final == FINAL_TEXT
assert any("调用失败" in r for r in tool_results)
def test_valid_tool_call_still_works(monkeypatch):
# Unit tests do not spend a real Tavily request; the live acceptance run
# separately proves that web_search returns attributable external results.
monkeypatch.setitem(
sys.modules["orchestrator"].TOOL_IMPLEMENTATIONS,
"web_search",
lambda query: json.dumps({
"provider": "tavily",
"query": query,
"results": [{"url": "https://example.test", "content": "检索结果"}],
}, ensure_ascii=False),
)
final, tool_results = _run_with_bad_tool_args(
"web_search", json.dumps({"query": "新能源汽车 销量"}))
assert final == FINAL_TEXT
assert any("检索结果" in r for r in tool_results)