93a0c0cddd
Normalize tool call arguments when OpenAI-compatible backends return parsed dict/list payloads instead of JSON strings. This prevents the .strip() crash during tool-call validation for llama.cpp and similar servers, while preserving existing empty-string and invalid-JSON handling. Adds a focused regression test for dict arguments in the agent loop.
65 lines
1.8 KiB
Python
65 lines
1.8 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=[SimpleNamespace(message=SimpleNamespace(content="done", reasoning=None, tool_calls=[]), finish_reason="stop")],
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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("run_agent.get_tool_definitions", lambda *args, **kwargs: [{"function": {"name": "read_file"}}])
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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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result = agent.run_conversation("read the file")
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assert result["final_response"] == "done"
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