de6d6023d7
PR #34470 adds an explainer suffix to abnormal turn endings (e.g. max_iterations_reached) so users see why the response is short instead of receiving a bare/blank reply. test_tool_call_validation_accepts_dict_arguments runs the agent at max_iterations=3 which hits the explainer path; the existing strict-equality assertion (== "done") no longer matches once the suffix is appended. Switch the assertion to .startswith("done") so the test continues to verify that the models actual text survives intact while leaving the explainer suffix wording owned by conversation_loop (where it belongs). Test now passes (1 passed in 0.88s).
79 lines
2.4 KiB
Python
79 lines
2.4 KiB
Python
import json
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from types import SimpleNamespace
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def _tool_call(name: str, arguments):
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return SimpleNamespace(
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id="call_1",
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type="function",
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function=SimpleNamespace(name=name, arguments=arguments),
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)
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def _response_with_tool_call(arguments):
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assistant = SimpleNamespace(
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content=None,
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reasoning=None,
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tool_calls=[_tool_call("read_file", arguments)],
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)
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choice = SimpleNamespace(message=assistant, finish_reason="tool_calls")
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return SimpleNamespace(choices=[choice], usage=None)
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class _FakeChatCompletions:
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def __init__(self):
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self.calls = 0
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def create(self, **kwargs):
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self.calls += 1
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if self.calls == 1:
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return _response_with_tool_call({"path": "README.md"})
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return SimpleNamespace(
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choices=[
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SimpleNamespace(
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message=SimpleNamespace(content="done", reasoning=None, tool_calls=[]),
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finish_reason="stop",
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)
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],
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usage=None,
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)
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class _FakeClient:
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def __init__(self):
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self.chat = SimpleNamespace(completions=_FakeChatCompletions())
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def test_tool_call_validation_accepts_dict_arguments(monkeypatch):
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from run_agent import AIAgent
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monkeypatch.setattr("run_agent.OpenAI", lambda **kwargs: _FakeClient())
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monkeypatch.setattr(
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"run_agent.get_tool_definitions",
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lambda *args, **kwargs: [{"function": {"name": "read_file"}}],
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)
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monkeypatch.setattr(
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"run_agent.handle_function_call",
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lambda name, args, task_id=None, **kwargs: json.dumps({"ok": True, "args": args}),
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)
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agent = AIAgent(
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model="test-model",
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api_key="test-key",
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base_url="http://localhost:8080/v1",
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platform="cli",
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max_iterations=3,
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quiet_mode=True,
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skip_memory=True,
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)
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agent._disable_streaming = True
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result = agent.run_conversation("read the file")
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# The conversation hits max_iterations=3 (3 tool turns then forced summary).
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# PR #34470 adds an explainer suffix to abnormal turn endings so users
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# understand why the response is short instead of seeing a blank reply.
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# The exact suffix wording is owned by conversation_loop; this test only
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# cares that the model's actual text ('done') survives at the start.
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assert result["final_response"].startswith("done")
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