Initial commit: PROMETHEUS v0.1.0 - Prompt optimizer

- Clean architecture (domain/application/infrastructure)
- DSPy-based evolution engine with scoring
- CLI via pyproject.toml entry point
- Unit + integration tests (~300 tests)
- Configs for glm-5.1 and glm-4.5-air models
- Z.AI endpoint integration

tests/unit/test_evaluator.py

@@ -0,0 +1,121 @@
+"""Unit tests for PromptEvaluator.evaluate()."""
+from __future__ import annotations
+
+from unittest.mock import MagicMock
+
+import pytest
+
+from prometheus.application.evaluator import PromptEvaluator
+from prometheus.domain.entities import EvalResult, Prompt, SyntheticExample, Trajectory
+from prometheus.domain.ports import JudgePort, LLMPort
+
+
+class TestPromptEvaluatorEvaluate:
+    """Tests for the evaluate() pipeline: execute → judge → trajectories."""
+
+    @pytest.fixture
+    def executor(self) -> MagicMock:
+        return MagicMock(spec=LLMPort)
+
+    @pytest.fixture
+    def judge(self) -> MagicMock:
+        return MagicMock(spec=JudgePort)
+
+    @pytest.fixture
+    def evaluator(self, executor: MagicMock, judge: MagicMock) -> PromptEvaluator:
+        return PromptEvaluator(executor=executor, judge=judge)
+
+    def test_happy_path_builds_correct_trajectories(
+        self,
+        evaluator: PromptEvaluator,
+        executor: MagicMock,
+        judge: MagicMock,
+    ) -> None:
+        prompt = Prompt(text="Answer the question.")
+        examples = [
+            SyntheticExample(input_text="What is 2+2?", id=0),
+            SyntheticExample(input_text="Capital of France?", id=1),
+        ]
+        executor.execute.side_effect = ["4", "Paris"]
+        judge.judge_batch.return_value = [
+            (0.9, "Correct."),
+            (0.8, "Mostly correct."),
+        ]
+
+        result = evaluator.evaluate(prompt, examples, "math and geography")
+
+        assert isinstance(result, EvalResult)
+        assert result.scores == [0.9, 0.8]
+        assert result.feedbacks == ["Correct.", "Mostly correct."]
+        assert len(result.trajectories) == 2
+        assert result.trajectories[0].input_text == "What is 2+2?"
+        assert result.trajectories[0].output_text == "4"
+        assert result.trajectories[0].score == 0.9
+        assert result.trajectories[0].feedback == "Correct."
+        assert result.trajectories[0].prompt_used == "Answer the question."
+        assert result.trajectories[1].prompt_used == "Answer the question."
+
+    def test_empty_minibatch_returns_empty_result(
+        self,
+        evaluator: PromptEvaluator,
+        executor: MagicMock,
+        judge: MagicMock,
+    ) -> None:
+        prompt = Prompt(text="test")
+        result = evaluator.evaluate(prompt, [], "task")
+
+        assert result.scores == []
+        assert result.feedbacks == []
+        assert result.trajectories == []
+        executor.execute.assert_not_called()
+        # judge_batch is called with empty pairs list
+        judge.judge_batch.assert_called_once_with("task", [])
+
+    def test_executor_called_with_correct_prompt(
+        self,
+        evaluator: PromptEvaluator,
+        executor: MagicMock,
+        judge: MagicMock,
+    ) -> None:
+        prompt = Prompt(text="Summarize this.")
+        examples = [SyntheticExample(input_text="Long text here", id=0)]
+        executor.execute.return_value = "Summary."
+        judge.judge_batch.return_value = [(0.7, "Good summary.")]
+
+        evaluator.evaluate(prompt, examples, "summarization")
+
+        executor.execute.assert_called_once_with(prompt, "Long text here")
+
+    def test_trajectories_prompt_used_matches_input_prompt(
+        self,
+        evaluator: PromptEvaluator,
+        executor: MagicMock,
+        judge: MagicMock,
+    ) -> None:
+        prompt = Prompt(text="Translate to French.")
+        examples = [SyntheticExample(input_text="Hello", id=0)]
+        executor.execute.return_value = "Bonjour"
+        judge.judge_batch.return_value = [(1.0, "Perfect.")]
+
+        result = evaluator.evaluate(prompt, examples, "translation")
+
+        assert result.trajectories[0].prompt_used == "Translate to French."
+
+    def test_scores_feedbacks_trajectories_lists_sized_correctly(
+        self,
+        evaluator: PromptEvaluator,
+        executor: MagicMock,
+        judge: MagicMock,
+    ) -> None:
+        prompt = Prompt(text="test prompt")
+        examples = [SyntheticExample(input_text=f"q{i}", id=i) for i in range(4)]
+        executor.execute.side_effect = [f"a{i}" for i in range(4)]
+        judge.judge_batch.return_value = [
+            (0.1 * i, f"fb{i}") for i in range(4)
+        ]
+
+        result = evaluator.evaluate(prompt, examples, "task")
+
+        assert len(result.scores) == 4
+        assert len(result.feedbacks) == 4
+        assert len(result.trajectories) == 4