mirror of
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311 lines
13 KiB
Python
311 lines
13 KiB
Python
"""
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LLM 提供商通用管理契约（provider_manage）守护测试
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验证通用模式的三条核心性质：
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1. 动作词汇表由 schemas 契约层统一定义，未支持动作返回统一错误结构
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2. 动作标识兼容枚举与原始字符串，统一返回 {"success", "message", "data"}
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3. 端点层零提供商特色：ManageRequest 原样透传，默认值填充/校验/脱敏封闭在 Manager 内
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"""
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import asyncio
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from types import SimpleNamespace
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from unittest.mock import AsyncMock, patch
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import pytest
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from app import schemas
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from app.agent.llm.helper import LLMHelper
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from app.agent.llm.provider import LLMProviderManager
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from app.runtime.config import settings
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from app.schemas.types import LlmProviderAction
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@pytest.fixture
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def manager():
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return LLMProviderManager()
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def test_provider_manage_rejects_unknown_action(manager):
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"""动作词汇表之外的请求返回统一错误结构。"""
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result = asyncio.run(manager.provider_manage("openai", "not_an_action"))
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assert result["success"] is False
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assert "不支持" in result["message"]
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assert "data" in result
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def test_provider_manage_accepts_enum_and_string_action(manager, monkeypatch):
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"""动作标识兼容枚举对象与原始字符串，两种形式等价。"""
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clear_mock = AsyncMock()
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monkeypatch.setattr(manager, "clear_auth", clear_mock)
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for action in (LlmProviderAction.DISCONNECT, "disconnect"):
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result = asyncio.run(manager.provider_manage("openai", action))
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assert result["success"] is True
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assert result["data"] is None
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assert clear_mock.await_count == 2
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def test_provider_manage_test_requires_ai_agent_enabled(manager):
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"""智能助手未启用时测试动作返回提示。"""
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with patch.object(settings, "AI_AGENT_ENABLE", False):
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result = asyncio.run(manager.provider_manage("deepseek", "test"))
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assert result["success"] is False
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assert result["message"] == "请先启用智能助手"
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def test_provider_manage_test_requires_model(manager):
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"""未配置模型时测试动作返回提示。"""
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with patch.object(settings, "AI_AGENT_ENABLE", True), patch.object(
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settings, "LLM_API_KEY", "sk-test"
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), patch.object(settings, "LLM_MODEL", ""):
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result = asyncio.run(manager.provider_manage("deepseek", "test"))
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assert result["success"] is False
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assert result["message"] == "请先配置 LLM 模型"
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def test_provider_manage_test_requires_api_key(manager, monkeypatch):
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"""无 OAuth 授权方式且无已保存凭据的提供商必须配置 API Key。"""
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monkeypatch.setattr(manager, "get_saved_auth", lambda provider_id: None)
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with patch.object(settings, "AI_AGENT_ENABLE", True), patch.object(
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settings, "LLM_API_KEY", None
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), patch.object(settings, "LLM_MODEL", "deepseek-chat"):
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result = asyncio.run(manager.provider_manage("deepseek", "test"))
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assert result["success"] is False
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assert result["message"] == "请先配置 LLM API Key"
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assert result["data"]["model"] == "deepseek-chat"
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def test_provider_manage_test_exempts_oauth_providers_from_api_key(manager, monkeypatch):
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"""支持 OAuth 授权的提供商无需 API Key，端点与 Manager 均不硬编码提供商名。"""
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monkeypatch.setattr(manager, "get_saved_auth", lambda provider_id: None)
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monkeypatch.setattr(
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manager, "get_provider", lambda provider_id: SimpleNamespace(oauth_methods=("browser_oauth",))
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)
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test_mock = AsyncMock(return_value={"provider": "chatgpt", "model": "gpt-4o", "reply_preview": "OK"})
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with patch.object(settings, "AI_AGENT_ENABLE", True), patch.object(
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settings, "LLM_API_KEY", None
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), patch.object(LLMHelper, "test_current_settings", test_mock):
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result = asyncio.run(
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manager.provider_manage("chatgpt", "test", model="gpt-4o")
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)
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assert result["success"] is True
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test_mock.assert_awaited_once()
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def test_provider_manage_test_returns_reply_preview(manager, monkeypatch):
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"""测试成功时返回模型响应预览，显式参数优先于已保存配置。"""
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monkeypatch.setattr(manager, "get_saved_auth", lambda provider_id: None)
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test_mock = AsyncMock(
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return_value={"provider": "openai", "model": "gpt-4.1-mini", "duration_ms": 123, "reply_preview": "OK"}
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)
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with patch.object(settings, "AI_AGENT_ENABLE", False), patch.object(
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LLMHelper, "test_current_settings", test_mock
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):
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result = asyncio.run(
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manager.provider_manage(
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"openai",
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"test",
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enabled=True,
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model="gpt-4.1-mini",
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thinking_level="high",
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api_key="sk-live",
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base_url="https://example.com/v1",
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use_proxy=False,
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)
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)
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test_mock.assert_awaited_once_with(
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provider="openai",
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model="gpt-4.1-mini",
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thinking_level="high",
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api_key="sk-live",
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base_url="https://example.com/v1",
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base_url_preset=None,
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user_agent=None,
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use_proxy=False,
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api_protocol=None,
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web_search_mode=None,
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)
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assert result["success"] is True
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assert result["data"]["reply_preview"] == "OK"
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def test_provider_manage_test_rejects_empty_reply(manager, monkeypatch):
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"""模型响应为空时返回失败但保留结果详情。"""
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monkeypatch.setattr(manager, "get_saved_auth", lambda provider_id: None)
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with patch.object(settings, "AI_AGENT_ENABLE", True), patch.object(
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LLMHelper,
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"test_current_settings",
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AsyncMock(return_value={"provider": "deepseek", "model": "deepseek-chat", "duration_ms": 12}),
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):
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result = asyncio.run(
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manager.provider_manage("deepseek", "test", model="deepseek-chat", api_key="sk-test")
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)
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assert result["success"] is False
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assert result["message"] == "模型响应为空"
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assert result["data"]["duration_ms"] == 12
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def test_provider_manage_test_maps_timeout_error(manager, monkeypatch):
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"""调用超时返回统一的超时提示。"""
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monkeypatch.setattr(manager, "get_saved_auth", lambda provider_id: None)
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with patch.object(settings, "AI_AGENT_ENABLE", True), patch.object(
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LLMHelper,
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"test_current_settings",
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AsyncMock(side_effect=TimeoutError("request timed out")),
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):
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result = asyncio.run(
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manager.provider_manage("deepseek", "test", model="deepseek-chat", api_key="sk-test")
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)
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assert result["success"] is False
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assert result["message"] == "LLM 调用超时"
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def test_provider_manage_test_sanitizes_error_message(manager, monkeypatch):
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"""错误信息中的密钥与授权头必须脱敏。"""
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monkeypatch.setattr(manager, "get_saved_auth", lambda provider_id: None)
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raw_error = (
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"request failed api_key=sk-secret "
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"Authorization: Bearer sk-secret "
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"base error sk-secret"
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)
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with patch.object(settings, "AI_AGENT_ENABLE", True), patch.object(
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LLMHelper, "test_current_settings", AsyncMock(side_effect=RuntimeError(raw_error))
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):
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result = asyncio.run(
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manager.provider_manage("deepseek", "test", model="deepseek-chat", api_key="sk-secret")
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)
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assert result["success"] is False
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assert "sk-secret" not in result["message"]
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assert "Authorization: Bearer" not in result["message"]
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assert "***" in result["message"]
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def test_provider_manage_test_maps_internal_error_to_base_url_hint(manager, monkeypatch):
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"""SDK 内部响应解析错误应改写为可定位的基础地址提示。"""
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monkeypatch.setattr(manager, "get_saved_auth", lambda provider_id: None)
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with patch.object(settings, "AI_AGENT_ENABLE", True), patch.object(
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LLMHelper,
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"test_current_settings",
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AsyncMock(side_effect=RuntimeError("'str' object has no attribute 'model_dump'")),
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):
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result = asyncio.run(
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manager.provider_manage("openai", "test", model="gpt-4o-mini", api_key="sk-test")
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)
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assert result["success"] is False
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assert "基础地址" in result["message"]
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assert "API Base URL" in result["message"]
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assert "model_dump" not in result["message"]
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def test_provider_manage_list_models_sanitizes_base_url_hint(manager):
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"""模型列表查询遇到 SDK 内部错误时同样给出基础地址提示。"""
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with patch.object(
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LLMHelper,
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"get_models",
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AsyncMock(side_effect=AttributeError("'str' object has no attribute '_set_private_attributes'")),
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):
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result = asyncio.run(
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manager.provider_manage("openai", "list_models", api_key="sk-test", base_url="https://example.com")
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)
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assert result["success"] is False
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assert "基础地址" in result["message"]
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assert "API Base URL" in result["message"]
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assert "_set_private_attributes" not in result["message"]
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def test_provider_manage_list_models_returns_catalog_with_auth_status(manager):
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"""模型目录查询成功时附带授权状态摘要。"""
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models = [{"id": "gpt-4o"}]
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with patch.object(LLMHelper, "get_models", AsyncMock(return_value=models)), patch.object(
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manager, "get_auth_status", lambda provider_id: {"connected": False}
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):
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result = asyncio.run(manager.provider_manage("openai", "list_models"))
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assert result["success"] is True
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assert result["data"]["provider"] == "openai"
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assert result["data"]["models"] == models
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assert result["data"]["auth_status"] == {"connected": False}
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def test_llm_manage_endpoint_passes_through_manage_request(monkeypatch):
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"""端点仅透传 ManageRequest，并按具名回调路由注入 OAuth 回跳地址。"""
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from app.api.endpoints import llm as llm_endpoint
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captured = {}
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async def fake_manage(self, provider, action, **params):
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captured["provider"] = provider
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captured["action"] = action
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captured["params"] = params
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return {"success": True, "message": "", "data": {"ok": True}}
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monkeypatch.setattr(LLMProviderManager, "provider_manage", fake_manage)
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request = SimpleNamespace(
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url_for=lambda name, **kwargs: f"https://host/api/v1/llm/provider-auth/callback/{kwargs['provider_id']}"
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)
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payload = schemas.ManageRequest(target="chatgpt", action="start_auth", params={"method": "browser_oauth"})
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resp = asyncio.run(llm_endpoint.manage_provider(request, payload, _="token"))
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assert resp.success is True
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assert resp.data == {"ok": True}
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assert captured["provider"] == "chatgpt"
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assert captured["action"] == "start_auth"
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assert captured["params"]["method"] == "browser_oauth"
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assert captured["params"]["callback_url"].endswith("/callback/chatgpt")
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def test_llm_manage_endpoint_accepts_empty_target(monkeypatch):
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"""目录类查询动作 target 可为空，不得因 url_for 空路径参数报 500。
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回归守护：前端加载提供商目录时 target 为空字符串，
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回调地址构造必须跳过空 target。
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"""
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from app.api.endpoints import llm as llm_endpoint
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captured = {}
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async def fake_manage(self, provider, action, **params):
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captured["provider"] = provider
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captured["params"] = params
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return {"success": True, "message": "", "data": []}
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def fail_url_for(name, **kwargs):
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raise AssertionError("空 target 不应构造回调地址")
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monkeypatch.setattr(LLMProviderManager, "provider_manage", fake_manage)
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request = SimpleNamespace(url_for=fail_url_for)
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payload = schemas.ManageRequest(target="", action="list_providers")
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resp = asyncio.run(llm_endpoint.manage_provider(request, payload, _="token"))
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assert resp.success is True
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assert captured["provider"] == ""
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assert "callback_url" not in captured["params"]
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def test_llm_manage_endpoint_response_model_accepts_list_data():
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"""目录查询动作 data 为列表，响应模型须同时覆盖列表与映射形态。
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回归守护：list_providers 返回 list[dict]，
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若响应模型声明为 Dict[str, Any] 会在序列化校验时直接 500；
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同时受响应模型守护测试约束，不得使用 Any/JsonData 弱类型。
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"""
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from typing import Any, Dict, List, Union
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from app.api.endpoints import llm as llm_endpoint
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route = next(
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r for r in llm_endpoint.router.routes if getattr(r, "path", "").endswith("/manage")
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)
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assert route.response_model is schemas.Response[
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Union[List[Dict[str, Any]], Dict[str, Any]]
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]
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list_resp = schemas.Response[Union[List[Dict[str, Any]], Dict[str, Any]]](
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success=True, message="", data=[{"id": "openai", "name": "OpenAI 兼容"}]
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)
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assert list_resp.data == [{"id": "openai", "name": "OpenAI 兼容"}]
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dict_resp = schemas.Response[Union[List[Dict[str, Any]], Dict[str, Any]]](
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success=True, message="", data={"models": ["gpt-4o"]}
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)
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assert dict_resp.data == {"models": ["gpt-4o"]}
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