vee
103 lines
3.9 KiB
Python
103 lines
3.9 KiB
Python
from __future__ import annotations
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import sys
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from pathlib import Path
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from unittest.mock import patch
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from cognitive_agent.application.assistant_capabilities import AssistantCapabilityCatalog
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from cognitive_agent.application.codex_assistant import CodexAssistantService
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from cognitive_agent.application.mode_profile import ModeProfileRegistry
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from cognitive_agent.application.seat_service import REPOSITORY_ROOT, SeatDemoService
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from cognitive_agent.infrastructure.codex.app_server import CodexAppServerClient
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FAKE_SERVER = REPOSITORY_ROOT / "tests" / "fixtures" / "fake_codex_app_server.py"
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MCP_SERVER = (
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REPOSITORY_ROOT / "src/cognitive_agent/infrastructure/codex/vehicle_mcp_server.py"
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)
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CALLBACK_URL = "http://127.0.0.1:8765/api/internal/codex/vehicle-control"
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def test_structured_scene_turn_reaches_the_complete_local_dry_run_pipeline(
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tmp_path: Path,
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) -> None:
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service = SeatDemoService(REPOSITORY_ROOT)
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service.artifact_root = tmp_path / "runs"
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service.mode_profiles = ModeProfileRegistry(
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REPOSITORY_ROOT / "config" / "modes",
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user_root=tmp_path / "user-modes",
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)
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client = CodexAppServerClient(
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cwd=tmp_path / "codex-workspace",
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codex_command=[sys.executable, "-u", str(FAKE_SERVER)],
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model="gpt-test-fast",
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reasoning_effort="low",
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request_timeout=2,
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startup_timeout=2,
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environment={"OPENAI_BASE_URL": "https://api.openai.com/v1"},
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mcp_server_path=MCP_SERVER,
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)
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assistant = CodexAssistantService(client)
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catalog = AssistantCapabilityCatalog(service)
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snapshot = catalog.snapshot()
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events: list[dict[str, object]] = []
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def execute_control(
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instruction: str,
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progress: object,
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assistant_plan: object,
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) -> dict[str, object]:
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assert isinstance(assistant_plan, dict)
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return service.preview_native_can(
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instruction,
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provider="local",
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conversation_id="conv-scene-e2e-pipeline",
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execution_mode="hardware",
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vehicle_id="denza_n7",
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on_commands_validated=progress if callable(progress) else None,
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assistant_plan=assistant_plan,
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)
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try:
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assistant.start(CALLBACK_URL)
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with patch.object(
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service.hardware_execution,
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"reserve",
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side_effect=AssertionError("scene preview must never reserve hardware"),
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):
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response = assistant.stream(
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"构建一个星夜模式",
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conversation_id="conv-scene-e2e-pipeline",
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principal="scene-e2e-user",
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history=[],
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emit=lambda event: events.append(event) or True,
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execute_control=execute_control,
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capability_snapshot=snapshot,
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capability_context=catalog.compact_context(snapshot),
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scene_capability_context=catalog.scene_composition_context(snapshot),
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control_terms=catalog.control_terms(snapshot),
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)
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finally:
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assistant.close()
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result = response["result"]
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draft = result["mode_profile_draft"]
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assert response["route"] == "scene_composer"
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assert response["success"] is True
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assert result["status"] == "succeeded"
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assert result["execution_mode"] == "dry_run"
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assert result["hardware_execution_allowed"] is False
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assert result["orchestration_route"] == "mode_profile_create_preview"
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assert draft["name"] == "星夜模式"
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assert draft["generation_source"] == "codex_scene_composition"
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assert draft["operation_count"] == 2
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capabilities = {
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action["capability"] for action in result["actions"]
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}
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assert capabilities == {
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"climate.set_temperature",
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"roof.set_shade_position",
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}
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assert not list((tmp_path / "user-modes").rglob("*.yaml"))
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assert any(event.get("type") == "action.completed" for event in events)
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assert all("request_token" not in str(event) for event in events)
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