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chore: import upstream snapshot with attribution
2026-07-13 13:00:43 +08:00

143 lines
4.3 KiB
Python

"""
Root conftest — shared fixtures for the entire test suite.
"""
from __future__ import annotations
from pathlib import Path
from unittest.mock import MagicMock
import pytest
from deeptutor.core.capability_protocol import BaseCapability, CapabilityManifest
from deeptutor.core.context import Attachment, UnifiedContext
from deeptutor.core.stream_bus import StreamBus
# ---------------------------------------------------------------------------
# Multi-user legacy migration guard
# ---------------------------------------------------------------------------
@pytest.fixture(autouse=True)
def _guard_legacy_multi_user_migration(monkeypatch):
"""Tests must never migrate the developer's real ``multi-user/`` tree.
``migrate_legacy_multi_user_tree`` runs on the auth/grants/workspace read
paths, so any test that exercises those without full path isolation would
otherwise move a real sibling ``multi-user/`` into ``data/``. Point the
legacy root at a path that cannot exist and reset the once-flag;
migration tests opt back in by patching the constants themselves.
"""
from deeptutor.multi_user import paths
monkeypatch.setattr(
paths, "LEGACY_MULTI_USER_ROOT", Path("/nonexistent/deeptutor-legacy-multi-user")
)
monkeypatch.setattr(paths, "_legacy_migration_done", False)
yield
# ---------------------------------------------------------------------------
# StreamBus
# ---------------------------------------------------------------------------
@pytest.fixture
def stream_bus() -> StreamBus:
"""Fresh StreamBus for one test."""
return StreamBus()
# ---------------------------------------------------------------------------
# UnifiedContext
# ---------------------------------------------------------------------------
@pytest.fixture
def minimal_context() -> UnifiedContext:
"""Context with just a user message."""
return UnifiedContext(
session_id="test-session",
user_message="Hello",
language="en",
)
@pytest.fixture
def rich_context() -> UnifiedContext:
"""Context with attachments, tools, KB, and metadata."""
return UnifiedContext(
session_id="test-session",
user_message="Explain RAG",
conversation_history=[
{"role": "user", "content": "What is AI?"},
{"role": "assistant", "content": "AI is..."},
],
enabled_tools=["rag", "web_search"],
active_capability="deep_solve",
knowledge_bases=["my-kb"],
attachments=[Attachment(type="image", url="https://img.png")],
config_overrides={"temperature": 0.7},
language="en",
metadata={"turn_id": "t-1"},
)
# ---------------------------------------------------------------------------
# SQLiteSessionStore (in-memory / tmp)
# ---------------------------------------------------------------------------
@pytest.fixture
def tmp_db_path(tmp_path: Path) -> Path:
"""Temporary database file path."""
return tmp_path / "test_chat.db"
@pytest.fixture
def sqlite_store(tmp_db_path: Path):
"""SQLiteSessionStore backed by a temp file."""
from deeptutor.services.session.sqlite_store import SQLiteSessionStore
return SQLiteSessionStore(db_path=tmp_db_path)
# ---------------------------------------------------------------------------
# Fake / stub capability
# ---------------------------------------------------------------------------
class _StubCapability(BaseCapability):
"""Capability that emits one content event and returns."""
manifest = CapabilityManifest(
name="stub",
description="Stub for testing.",
stages=["responding"],
)
async def run(self, context: UnifiedContext, stream: StreamBus) -> None:
await stream.content("stub response", source=self.name)
@pytest.fixture
def stub_capability() -> _StubCapability:
return _StubCapability()
# ---------------------------------------------------------------------------
# Fake LLM helpers
# ---------------------------------------------------------------------------
@pytest.fixture
def fake_llm_config() -> MagicMock:
"""MagicMock mimicking LLMConfig with common defaults."""
cfg = MagicMock()
cfg.model = "gpt-4o-mini"
cfg.max_tokens = 4096
cfg.temperature = 0.7
cfg.api_key = "sk-test"
cfg.api_base = "https://api.openai.com/v1"
return cfg