from pathlib import Path import tempfile import unittest from unittest.mock import MagicMock, patch from nightshift.agents import AgentExecutor, build_prompt_bundle, parse_review_output from nightshift.agents import AgentInvocation, format_agent_invocation from nightshift.artifacts import ArtifactStore from nightshift.config import AgentConfig, StageConfig from nightshift.tasks import parse_tasks TASK_MD = """# Tasks - [ ] TASK-001: Add fake agent coverage Description: Exercise fake command agents. Acceptance Criteria: - Prompt includes task details - Agent output is stored """ class AgentExecutorTests(unittest.TestCase): def test_build_prompt_bundle_includes_task_and_acceptance_criteria(self) -> None: task = parse_tasks(TASK_MD)[0] prompt = build_prompt_bundle( system_prompt="System rules", stage=StageConfig(id="plan", type="agent", agent="planner"), task=task, project_context="Project context", previous_outputs={"prior": "Earlier output"}, retry_notes=["Retry note"], ) self.assertIn("System rules", prompt) self.assertIn("TASK-001", prompt) self.assertIn("- Prompt includes task details", prompt) self.assertIn("Earlier output", prompt) self.assertIn("Retry note", prompt) def test_build_prompt_bundle_includes_task_context(self) -> None: task = parse_tasks(TASK_MD)[0] prompt = build_prompt_bundle( system_prompt="System rules", stage=StageConfig(id="plan", type="agent", agent="planner"), task=task, project_context="Project context", task_context="Task context body", previous_outputs={}, retry_notes=[], retry_context="- No retries", ) self.assertIn("## Task Context", prompt) self.assertIn("Task context body", prompt) self.assertIn("- No retries", prompt) def test_command_agent_writes_output_and_returns_pass(self) -> None: with tempfile.TemporaryDirectory() as directory: root = Path(directory) prompt_path = root / "planner.md" prompt_path.write_text("Plan carefully.", encoding="utf-8") artifacts = ArtifactStore(root, ".nightshift", run_id="test-run") executor = AgentExecutor( root, { "planner": AgentConfig( id="planner", backend="command", command='python -c "import sys; print(sys.stdin.read())"', system_prompt=Path("planner.md"), ) }, artifacts, ) task = parse_tasks(TASK_MD)[0] stage = StageConfig(id="plan", type="agent", agent="planner", output="plan.md") result = executor.run_stage(stage, task) self.assertEqual(result.status, "pass") output = (root / result.output_path).read_text(encoding="utf-8") self.assertIn("TASK-001", output) self.assertIn("Plan carefully.", output) def test_review_output_parser_accepts_structured_status(self) -> None: status, reason, next_stage, context_update = parse_review_output( "status: retry\nreason: Needs changes\nnext_stage: implement\ncontext_update: Fix tests\n" ) self.assertEqual(status, "retry") self.assertEqual(reason, "Needs changes") self.assertEqual(next_stage, "implement") self.assertEqual(context_update, "Fix tests") def test_ollama_agent_invocation_uses_model_without_real_ollama(self) -> None: with tempfile.TemporaryDirectory() as directory: root = Path(directory) prompt_path = root / "planner.md" prompt_path.write_text("Plan carefully.", encoding="utf-8") artifacts = ArtifactStore(root, ".nightshift", run_id="test-run") executor = AgentExecutor( root, { "planner": AgentConfig( id="planner", backend="ollama", command=None, model="tiny-model", system_prompt=Path("planner.md"), ) }, artifacts, ) task = parse_tasks(TASK_MD)[0] stage = StageConfig(id="plan", type="agent", agent="planner", output="plan.md") completed = type( "Completed", (), {"returncode": 0, "stdout": "ollama output", "stderr": ""}, )() with patch("nightshift.agents.subprocess.run", return_value=completed) as run: result = executor.run_stage(stage, task) self.assertEqual(result.status, "pass") run.assert_called_once() self.assertEqual(run.call_args.args[0], ["ollama", "run", "tiny-model"]) output = (root / result.output_path).read_text(encoding="utf-8") self.assertIn("ollama run tiny-model", output) def test_openai_compatible_agent_sends_temperature(self) -> None: with tempfile.TemporaryDirectory() as directory: root = Path(directory) prompt_path = root / "planner.md" prompt_path.write_text("Plan carefully.", encoding="utf-8") artifacts = ArtifactStore(root, ".nightshift", run_id="test-run") executor = AgentExecutor( root, { "planner": AgentConfig( id="planner", backend="openai_compatible", command=None, model="tiny-model", base_url="http://localhost:11434/v1", temperature=0.2, system_prompt=Path("planner.md"), ) }, artifacts, ) task = parse_tasks(TASK_MD)[0] stage = StageConfig(id="plan", type="agent", agent="planner", output="plan.md") response = MagicMock() response.__enter__.return_value.read.return_value = ( b'{"choices":[{"message":{"content":"api output"}}]}' ) with patch("nightshift.agents.request.urlopen", return_value=response) as urlopen: result = executor.run_stage(stage, task) self.assertEqual(result.status, "pass") request_obj = urlopen.call_args.args[0] body = request_obj.data.decode("utf-8") self.assertIn('"temperature": 0.2', body) self.assertIn("api output", (root / result.output_path).read_text(encoding="utf-8")) def test_agent_artifact_format_tolerates_missing_streams(self) -> None: invocation = AgentInvocation( agent_id="planner", command="ollama run model", prompt="prompt", exit_code=0, stdout=None, # type: ignore[arg-type] stderr=None, # type: ignore[arg-type] duration_seconds=0.1, ) output = format_agent_invocation("plan", invocation) self.assertIn("Agent: `planner`", output) self.assertIn("## stderr", output) if __name__ == "__main__": unittest.main()