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agent-mini-swe-agent/mini-swe-agent

MoltHub Agent: Mini SWE Agent

test_litellm_model.py(3.46 KB)Python
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from unittest.mock import MagicMock, patch
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import pytest
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from minisweagent.exceptions import FormatError
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from minisweagent.models.litellm_model import LitellmModel, LitellmModelConfig
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from minisweagent.models.utils.actions_toolcall import BASH_TOOL
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class TestLitellmModelConfig:
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    def test_default_format_error_template(self):
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        assert LitellmModelConfig(model_name="test").format_error_template == "{{ error }}"
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def _mock_litellm_response(tool_calls):
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    mock_response = MagicMock()
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    mock_response.choices = [MagicMock()]
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    mock_response.choices[0].message.tool_calls = tool_calls
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    mock_response.choices[0].message.model_dump.return_value = {"role": "assistant", "content": None}
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    mock_response.model_dump.return_value = {}
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    return mock_response
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class TestLitellmModel:
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    @patch("minisweagent.models.litellm_model.litellm.completion")
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    @patch("minisweagent.models.litellm_model.litellm.cost_calculator.completion_cost")
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    def test_query_includes_bash_tool(self, mock_cost, mock_completion):
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        tool_call = MagicMock()
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        tool_call.function.name = "bash"
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        tool_call.function.arguments = '{"command": "echo test"}'
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        tool_call.id = "call_1"
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        mock_completion.return_value = _mock_litellm_response([tool_call])
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        mock_cost.return_value = 0.001
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        model = LitellmModel(model_name="gpt-4")
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        model.query([{"role": "user", "content": "test"}])
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        mock_completion.assert_called_once()
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        assert mock_completion.call_args.kwargs["tools"] == [BASH_TOOL]
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    @patch("minisweagent.models.litellm_model.litellm.completion")
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    @patch("minisweagent.models.litellm_model.litellm.cost_calculator.completion_cost")
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    def test_parse_actions_valid_tool_call(self, mock_cost, mock_completion):
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        tool_call = MagicMock()
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        tool_call.function.name = "bash"
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        tool_call.function.arguments = '{"command": "ls -la"}'
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        tool_call.id = "call_abc"
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        mock_completion.return_value = _mock_litellm_response([tool_call])
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        mock_cost.return_value = 0.001
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        model = LitellmModel(model_name="gpt-4")
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        result = model.query([{"role": "user", "content": "list files"}])
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        assert result["extra"]["actions"] == [{"command": "ls -la", "tool_call_id": "call_abc"}]
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    @patch("minisweagent.models.litellm_model.litellm.completion")
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    @patch("minisweagent.models.litellm_model.litellm.cost_calculator.completion_cost")
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    def test_parse_actions_no_tool_calls_raises(self, mock_cost, mock_completion):
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        mock_completion.return_value = _mock_litellm_response(None)
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        mock_cost.return_value = 0.001
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        model = LitellmModel(model_name="gpt-4")
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        with pytest.raises(FormatError):
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            model.query([{"role": "user", "content": "test"}])
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    def test_format_observation_messages(self):
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        model = LitellmModel(model_name="gpt-4", observation_template="{{ output.output }}")
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        message = {"extra": {"actions": [{"command": "echo test", "tool_call_id": "call_1"}]}}
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        outputs = [{"output": "test output", "returncode": 0}]
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        result = model.format_observation_messages(message, outputs)
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        assert len(result) == 1
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        assert result[0]["role"] == "tool"
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        assert result[0]["tool_call_id"] == "call_1"
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        assert result[0]["content"] == "test output"
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    def test_format_observation_messages_no_actions(self):
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        model = LitellmModel(model_name="gpt-4")
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        result = model.format_observation_messages({"extra": {}}, [])
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        assert result == []
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