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test: replace plugin model client spec mocks with a recording fake (#43152)
This commit is contained in:
Asuka Minato authored and 
GitHub committed
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commit
fb0e55f5e7
1 file changed
+217
-154
@@ -1,10 +1,12 @@
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"""Unit tests for the plugin-backed model runtime adapter."""
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import datetime
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import inspect
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import uuid
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from collections import defaultdict
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from collections.abc import Callable
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from types import SimpleNamespace
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from unittest.mock import MagicMock, Mock, patch, sentinel
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from unittest.mock import MagicMock, Mock, call, patch, sentinel
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import pytest
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@@ -28,6 +30,50 @@ from graphon.model_runtime.entities.model_entities import AIModelEntity, FetchFr
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from graphon.model_runtime.entities.provider_entities import ConfigurateMethod, ProviderEntity
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class _RecordingModelClient(PluginModelClient):
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"""Record adapter calls and return explicit results without daemon access.
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An unconfigured operation fails immediately. Calls preserve omitted keyword
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arguments so tests can distinguish an absent app_id from an explicit None.
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"""
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def __init__(self) -> None:
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self.results: dict[str, object] = {}
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self.calls: dict[str, list[tuple[tuple[object, ...], dict[str, object]]]] = defaultdict(list)
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def _record(self, method: Callable[..., object], *args: object, **kwargs: object) -> object:
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inspect.signature(method).bind(self, *args, **kwargs)
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operation = method.__name__
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self.calls[operation].append((args, kwargs))
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if operation not in self.results:
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raise AssertionError(f"No result configured for {operation}")
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return self.results[operation]
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def fetch_model_providers(self, tenant_id: str):
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return self._record(PluginModelClient.fetch_model_providers, tenant_id)
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def validate_provider_credentials(self, **kwargs):
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return self._record(PluginModelClient.validate_provider_credentials, **kwargs)
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def invoke_llm(self, **kwargs):
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return self._record(PluginModelClient.invoke_llm, **kwargs)
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def start_llm_polling(self, **kwargs):
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return self._record(PluginModelClient.start_llm_polling, **kwargs)
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def check_llm_polling(self, **kwargs):
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return self._record(PluginModelClient.check_llm_polling, **kwargs)
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def invoke_tts(self, **kwargs):
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return self._record(PluginModelClient.invoke_tts, **kwargs)
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def get_model_schema(self, **kwargs):
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return self._record(PluginModelClient.get_model_schema, **kwargs)
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def get_llm_num_tokens(self, **kwargs):
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return self._record(PluginModelClient.get_llm_num_tokens, **kwargs)
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class _FakeRedis:
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def __init__(self) -> None:
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self._values: dict[str, str] = {}
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@@ -109,8 +155,8 @@ class TestPluginModelRuntime:
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"""Validate the adapter keeps plugin-specific routing out of the runtime port."""
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def test_fetch_model_providers_returns_runtime_entities(self) -> None:
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client = Mock(spec=PluginModelClient)
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client.fetch_model_providers.return_value = [
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client = _RecordingModelClient()
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client.results["fetch_model_providers"] = [
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PluginModelProviderEntity(
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id=uuid.uuid4().hex,
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created_at=datetime.datetime.now(),
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@@ -136,11 +182,11 @@ class TestPluginModelRuntime:
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assert providers[0].provider == "langgenius/openai/openai"
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assert providers[0].provider_name == "openai"
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assert providers[0].label.en_us == "OpenAI"
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client.fetch_model_providers.assert_called_once_with("tenant")
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assert client.calls["fetch_model_providers"] == [call("tenant")]
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def test_fetch_model_providers_only_exposes_short_name_for_canonical_provider(self) -> None:
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client = Mock(spec=PluginModelClient)
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client.fetch_model_providers.return_value = [
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client = _RecordingModelClient()
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client.results["fetch_model_providers"] = [
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PluginModelProviderEntity(
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id=uuid.uuid4().hex,
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created_at=datetime.datetime.now(),
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@@ -183,8 +229,8 @@ class TestPluginModelRuntime:
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assert provider_aliases["langgenius/openai/openai"] == "openai"
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def test_fetch_model_providers_keeps_google_alias_on_canonical_gemini_provider(self) -> None:
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client = Mock(spec=PluginModelClient)
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client.fetch_model_providers.return_value = [
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client = _RecordingModelClient()
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client.results["fetch_model_providers"] = [
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PluginModelProviderEntity(
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id=uuid.uuid4().hex,
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created_at=datetime.datetime.now(),
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@@ -210,7 +256,8 @@ class TestPluginModelRuntime:
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assert providers[0].provider_name == "google"
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def test_validate_provider_credentials_resolves_plugin_fields(self) -> None:
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client = Mock(spec=PluginModelClient)
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client = _RecordingModelClient()
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client.results["validate_provider_credentials"] = True
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runtime = PluginModelRuntime(tenant_id="tenant", user_id="user", client=client, plugin_service=PluginService)
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runtime.validate_provider_credentials(
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@@ -218,18 +265,20 @@ class TestPluginModelRuntime:
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credentials={"api_key": "secret"},
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)
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client.validate_provider_credentials.assert_called_once_with(
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tenant_id="tenant",
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user_id="user",
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plugin_id="langgenius/openai",
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provider="openai",
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credentials={"api_key": "secret"},
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)
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assert client.calls["validate_provider_credentials"] == [
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call(
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tenant_id="tenant",
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user_id="user",
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plugin_id="langgenius/openai",
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provider="openai",
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credentials={"api_key": "secret"},
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)
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]
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def test_invoke_llm_resolves_plugin_fields(self) -> None:
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client = Mock(spec=PluginModelClient)
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client = _RecordingModelClient()
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usage = LLMUsage.empty_usage()
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client.invoke_llm.return_value = iter(
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client.results["invoke_llm"] = iter(
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[
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LLMResultChunk(
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model="gpt-4o-mini",
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@@ -271,23 +320,25 @@ class TestPluginModelRuntime:
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assert result.message.content == "plugin response"
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assert result.usage == usage
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assert result.system_fingerprint == "fp-plugin"
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client.invoke_llm.assert_called_once_with(
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tenant_id="tenant",
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user_id="user",
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plugin_id="langgenius/openai",
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provider="openai",
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model="gpt-4o-mini",
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credentials={"api_key": "secret"},
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model_parameters={"temperature": 0.3},
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prompt_messages=[],
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tools=None,
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stop=None,
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stream=False,
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)
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assert client.calls["invoke_llm"] == [
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call(
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tenant_id="tenant",
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user_id="user",
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plugin_id="langgenius/openai",
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provider="openai",
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model="gpt-4o-mini",
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credentials={"api_key": "secret"},
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model_parameters={"temperature": 0.3},
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prompt_messages=[],
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tools=None,
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stop=None,
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stream=False,
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)
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]
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def test_invoke_llm_forwards_string_app_id_from_request_metadata(self) -> None:
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client = Mock(spec=PluginModelClient)
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client.invoke_llm.return_value = iter([])
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client = _RecordingModelClient()
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client.results["invoke_llm"] = iter([])
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runtime = PluginModelRuntime(tenant_id="tenant", user_id="user", client=client, plugin_service=PluginService)
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result = runtime.invoke_llm(
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@@ -303,24 +354,26 @@ class TestPluginModelRuntime:
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)
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assert list(result) == []
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client.invoke_llm.assert_called_once_with(
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tenant_id="tenant",
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user_id="user",
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plugin_id="langgenius/openai",
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provider="openai",
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model="gpt-4o-mini",
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credentials={"api_key": "secret"},
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model_parameters={"temperature": 0.3},
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prompt_messages=[],
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tools=None,
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stop=None,
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stream=True,
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app_id="app-1",
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)
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assert client.calls["invoke_llm"] == [
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call(
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tenant_id="tenant",
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user_id="user",
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plugin_id="langgenius/openai",
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provider="openai",
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model="gpt-4o-mini",
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credentials={"api_key": "secret"},
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model_parameters={"temperature": 0.3},
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prompt_messages=[],
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tools=None,
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stop=None,
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stream=True,
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app_id="app-1",
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)
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]
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def test_invoke_llm_ignores_non_string_app_id_request_metadata(self) -> None:
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client = Mock(spec=PluginModelClient)
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client.invoke_llm.return_value = iter([])
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client = _RecordingModelClient()
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client.results["invoke_llm"] = iter([])
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runtime = PluginModelRuntime(tenant_id="tenant", user_id="user", client=client, plugin_service=PluginService)
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result = runtime.invoke_llm(
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@@ -335,13 +388,13 @@ class TestPluginModelRuntime:
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request_metadata={"app_id": 123},
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)
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assert result is client.invoke_llm.return_value
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assert "app_id" not in client.invoke_llm.call_args.kwargs
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assert result is client.results["invoke_llm"]
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assert "app_id" not in client.calls["invoke_llm"][-1][1]
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def test_invoke_llm_returns_plugin_stream_directly(self) -> None:
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client = Mock(spec=PluginModelClient)
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client = _RecordingModelClient()
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stream_result = iter([])
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client.invoke_llm.return_value = stream_result
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client.results["invoke_llm"] = stream_result
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runtime = PluginModelRuntime(tenant_id="tenant", user_id="user", client=client, plugin_service=PluginService)
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result = runtime.invoke_llm(
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@@ -356,28 +409,30 @@ class TestPluginModelRuntime:
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)
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assert result is stream_result
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client.invoke_llm.assert_called_once_with(
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tenant_id="tenant",
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user_id="user",
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plugin_id="langgenius/openai",
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provider="openai",
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model="gpt-4o-mini",
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credentials={"api_key": "secret"},
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model_parameters={"temperature": 0.3},
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prompt_messages=[],
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tools=None,
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stop=["END"],
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stream=True,
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)
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assert client.calls["invoke_llm"] == [
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call(
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tenant_id="tenant",
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user_id="user",
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plugin_id="langgenius/openai",
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provider="openai",
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model="gpt-4o-mini",
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credentials={"api_key": "secret"},
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model_parameters={"temperature": 0.3},
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prompt_messages=[],
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tools=None,
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stop=["END"],
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stream=True,
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)
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]
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def test_start_llm_polling_resolves_plugin_fields(self) -> None:
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client = Mock(spec=PluginModelClient)
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client = _RecordingModelClient()
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polling_result = LLMPollingResult(
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status=LLMPollingStatus.RUNNING,
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plugin_state={"task_id": "poll-1"},
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next_check_after_seconds=2,
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)
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client.start_llm_polling.return_value = polling_result
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client.results["start_llm_polling"] = polling_result
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runtime = PluginModelRuntime(tenant_id="tenant", user_id="user", client=client, plugin_service=PluginService)
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result = runtime.start_llm_polling(
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@@ -392,22 +447,24 @@ class TestPluginModelRuntime:
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)
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assert result == polling_result
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client.start_llm_polling.assert_called_once_with(
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tenant_id="tenant",
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user_id="user",
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plugin_id="langgenius/openai",
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provider="openai",
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model="gpt-4o-mini",
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credentials={"api_key": "secret"},
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prompt_messages=[],
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model_parameters={"temperature": 0.2},
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tools=None,
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stop=["END"],
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json_schema={"type": "object"},
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)
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assert client.calls["start_llm_polling"] == [
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call(
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tenant_id="tenant",
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user_id="user",
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plugin_id="langgenius/openai",
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provider="openai",
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model="gpt-4o-mini",
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credentials={"api_key": "secret"},
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prompt_messages=[],
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model_parameters={"temperature": 0.2},
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tools=None,
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stop=["END"],
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json_schema={"type": "object"},
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)
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]
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def test_check_llm_polling_resolves_plugin_fields(self) -> None:
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client = Mock(spec=PluginModelClient)
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client = _RecordingModelClient()
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polling_result = LLMPollingResult(
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status=LLMPollingStatus.SUCCEEDED,
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result=model_runtime_module.LLMResult(
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@@ -417,7 +474,7 @@ class TestPluginModelRuntime:
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usage=LLMUsage.empty_usage(),
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),
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)
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client.check_llm_polling.return_value = polling_result
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client.results["check_llm_polling"] = polling_result
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runtime = PluginModelRuntime(tenant_id="tenant", user_id="user", client=client, plugin_service=PluginService)
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result = runtime.check_llm_polling(
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@@ -428,19 +485,21 @@ class TestPluginModelRuntime:
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)
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assert result == polling_result
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client.check_llm_polling.assert_called_once_with(
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tenant_id="tenant",
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user_id="user",
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plugin_id="langgenius/openai",
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provider="openai",
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model="gpt-4o-mini",
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credentials={"api_key": "secret"},
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plugin_state={"task_id": "poll-1"},
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)
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assert client.calls["check_llm_polling"] == [
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call(
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tenant_id="tenant",
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user_id="user",
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plugin_id="langgenius/openai",
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provider="openai",
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model="gpt-4o-mini",
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credentials={"api_key": "secret"},
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plugin_state={"task_id": "poll-1"},
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)
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]
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def test_invoke_llm_rejects_per_call_user_override(self) -> None:
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client = Mock(spec=PluginModelClient)
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client.invoke_llm.return_value = sentinel.result
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client = _RecordingModelClient()
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client.results["invoke_llm"] = sentinel.result
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runtime = PluginModelRuntime(
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tenant_id="tenant", user_id="bound-user", client=client, plugin_service=PluginService
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)
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@@ -458,11 +517,11 @@ class TestPluginModelRuntime:
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user_id="request-user",
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)
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client.invoke_llm.assert_not_called()
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assert not client.calls["invoke_llm"]
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def test_invoke_tts_uses_bound_runtime_user_when_runtime_is_unbound(self) -> None:
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client = Mock(spec=PluginModelClient)
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client.invoke_tts.return_value = iter([b"chunk"])
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client = _RecordingModelClient()
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client.results["invoke_tts"] = iter([b"chunk"])
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runtime = PluginModelRuntime(tenant_id="tenant", user_id=None, client=client, plugin_service=PluginService)
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result = runtime.invoke_tts(
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@@ -474,22 +533,24 @@ class TestPluginModelRuntime:
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)
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assert list(result) == [b"chunk"]
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client.invoke_tts.assert_called_once_with(
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tenant_id="tenant",
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user_id=None,
|
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plugin_id="langgenius/openai",
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provider="openai",
|
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model="tts-1",
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credentials={"api_key": "secret"},
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content_text="hello",
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voice="alloy",
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)
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assert client.calls["invoke_tts"] == [
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call(
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tenant_id="tenant",
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user_id=None,
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plugin_id="langgenius/openai",
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provider="openai",
|
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model="tts-1",
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credentials={"api_key": "secret"},
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content_text="hello",
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voice="alloy",
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)
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]
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def test_fetch_model_providers_does_not_keep_bound_runtime_cache(
|
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self, monkeypatch: pytest.MonkeyPatch, config_overrides: Callable[..., None]
|
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) -> None:
|
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client = Mock(spec=PluginModelClient)
|
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client.fetch_model_providers.return_value = []
|
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client = _RecordingModelClient()
|
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client.results["fetch_model_providers"] = []
|
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from core.plugin import plugin_service as plugin_service_module
|
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|
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monkeypatch.setattr(
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@@ -509,7 +570,7 @@ class TestPluginModelRuntime:
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runtime.fetch_model_providers()
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runtime.fetch_model_providers()
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|
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assert client.fetch_model_providers.call_count == 2
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assert len(client.calls["fetch_model_providers"]) == 2
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|
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def test_fetch_model_providers_uses_tenant_ttl_cache_across_runtime_instances(
|
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self, monkeypatch: pytest.MonkeyPatch, config_overrides: Callable[..., None]
|
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@@ -519,9 +580,9 @@ class TestPluginModelRuntime:
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from core.plugin import plugin_service as plugin_service_module
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|
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monkeypatch.setattr(plugin_service_module, "redis_client", redis)
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first_client = Mock(spec=PluginModelClient)
|
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first_client.fetch_model_providers.return_value = [_build_plugin_model_provider(tenant_id="tenant")]
|
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second_client = Mock(spec=PluginModelClient)
|
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first_client = _RecordingModelClient()
|
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first_client.results["fetch_model_providers"] = [_build_plugin_model_provider(tenant_id="tenant")]
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second_client = _RecordingModelClient()
|
||||
first_runtime = PluginModelRuntime(
|
||||
tenant_id="tenant", user_id="user-a", client=first_client, plugin_service=PluginService
|
||||
)
|
||||
@@ -534,8 +595,8 @@ class TestPluginModelRuntime:
|
||||
|
||||
assert [provider.provider for provider in first_providers] == ["langgenius/openai/openai"]
|
||||
assert [provider.provider for provider in second_providers] == ["langgenius/openai/openai"]
|
||||
first_client.fetch_model_providers.assert_called_once_with("tenant")
|
||||
second_client.fetch_model_providers.assert_not_called()
|
||||
assert first_client.calls["fetch_model_providers"] == [call("tenant")]
|
||||
assert not second_client.calls["fetch_model_providers"]
|
||||
assert redis.setex_calls[0][1] == 300
|
||||
|
||||
def test_fetch_model_providers_cache_is_tenant_isolated(
|
||||
@@ -546,10 +607,10 @@ class TestPluginModelRuntime:
|
||||
from core.plugin import plugin_service as plugin_service_module
|
||||
|
||||
monkeypatch.setattr(plugin_service_module, "redis_client", redis)
|
||||
first_client = Mock(spec=PluginModelClient)
|
||||
first_client.fetch_model_providers.return_value = [_build_plugin_model_provider(tenant_id="tenant-a")]
|
||||
second_client = Mock(spec=PluginModelClient)
|
||||
second_client.fetch_model_providers.return_value = [_build_plugin_model_provider(tenant_id="tenant-b")]
|
||||
first_client = _RecordingModelClient()
|
||||
first_client.results["fetch_model_providers"] = [_build_plugin_model_provider(tenant_id="tenant-a")]
|
||||
second_client = _RecordingModelClient()
|
||||
second_client.results["fetch_model_providers"] = [_build_plugin_model_provider(tenant_id="tenant-b")]
|
||||
first_runtime = PluginModelRuntime(
|
||||
tenant_id="tenant-a", user_id="user", client=first_client, plugin_service=PluginService
|
||||
)
|
||||
@@ -562,12 +623,12 @@ class TestPluginModelRuntime:
|
||||
|
||||
assert [provider.provider for provider in first_providers] == ["langgenius/openai/openai"]
|
||||
assert [provider.provider for provider in second_providers] == ["langgenius/openai/openai"]
|
||||
first_client.fetch_model_providers.assert_called_once_with("tenant-a")
|
||||
second_client.fetch_model_providers.assert_called_once_with("tenant-b")
|
||||
assert first_client.calls["fetch_model_providers"] == [call("tenant-a")]
|
||||
assert second_client.calls["fetch_model_providers"] == [call("tenant-b")]
|
||||
assert len(redis.setex_calls) == 2
|
||||
|
||||
def test_fetch_model_providers_delegates_cache_to_injected_plugin_service(self) -> None:
|
||||
client = Mock(spec=PluginModelClient)
|
||||
client = _RecordingModelClient()
|
||||
service_result = [
|
||||
ProviderEntity(
|
||||
provider="langgenius/openai/openai",
|
||||
@@ -591,7 +652,7 @@ class TestPluginModelRuntime:
|
||||
|
||||
assert result is service_result
|
||||
fetch_plugin_model_providers.assert_called_once_with(tenant_id="tenant", client=client)
|
||||
client.fetch_model_providers.assert_not_called()
|
||||
assert not client.calls["fetch_model_providers"]
|
||||
|
||||
|
||||
def test_create_plugin_model_runtime_without_user_context() -> None:
|
||||
@@ -610,13 +671,13 @@ def test_plugin_model_runtime_requires_plugin_service() -> None:
|
||||
PluginModelRuntime(
|
||||
tenant_id="tenant",
|
||||
user_id="user",
|
||||
client=Mock(spec=PluginModelClient),
|
||||
client=_RecordingModelClient(),
|
||||
plugin_service=None, # type: ignore[arg-type]
|
||||
)
|
||||
|
||||
|
||||
def test_get_model_schema_uses_cached_schema_without_hitting_client(monkeypatch: pytest.MonkeyPatch) -> None:
|
||||
client = Mock(spec=PluginModelClient)
|
||||
client = _RecordingModelClient()
|
||||
schema = _build_model_schema()
|
||||
monkeypatch.setattr(
|
||||
model_runtime_module,
|
||||
@@ -637,7 +698,7 @@ def test_get_model_schema_uses_cached_schema_without_hitting_client(monkeypatch:
|
||||
)
|
||||
|
||||
assert result == schema
|
||||
client.get_model_schema.assert_not_called()
|
||||
assert not client.calls["get_model_schema"]
|
||||
|
||||
|
||||
def test_structured_output_adapter_invokes_bound_runtime_streaming() -> None:
|
||||
@@ -705,7 +766,7 @@ def test_structured_output_adapter_invokes_bound_runtime_non_streaming() -> None
|
||||
|
||||
|
||||
def test_invoke_llm_with_structured_output_delegates_with_bound_adapter() -> None:
|
||||
client = Mock(spec=PluginModelClient)
|
||||
client = _RecordingModelClient()
|
||||
runtime = PluginModelRuntime(tenant_id="tenant", user_id="user", client=client, plugin_service=PluginService)
|
||||
schema = _build_model_schema()
|
||||
runtime.get_model_schema = Mock(return_value=schema) # type: ignore[method-assign]
|
||||
@@ -746,7 +807,7 @@ def test_invoke_llm_with_structured_output_delegates_with_bound_adapter() -> Non
|
||||
|
||||
|
||||
def test_invoke_llm_with_structured_output_raises_when_model_schema_is_missing() -> None:
|
||||
client = Mock(spec=PluginModelClient)
|
||||
client = _RecordingModelClient()
|
||||
runtime = PluginModelRuntime(tenant_id="tenant", user_id="user", client=client, plugin_service=PluginService)
|
||||
runtime.get_model_schema = Mock(return_value=None) # type: ignore[method-assign]
|
||||
|
||||
@@ -767,7 +828,7 @@ def test_get_model_schema_deletes_invalid_cache_and_refetches(
|
||||
monkeypatch: pytest.MonkeyPatch, config_overrides: Callable[..., None]
|
||||
) -> None:
|
||||
config_overrides(PLUGIN_MODEL_SCHEMA_CACHE_TTL=300)
|
||||
client = Mock(spec=PluginModelClient)
|
||||
client = _RecordingModelClient()
|
||||
schema = _build_model_schema()
|
||||
delete = Mock()
|
||||
setex = Mock()
|
||||
@@ -780,7 +841,7 @@ def test_get_model_schema_deletes_invalid_cache_and_refetches(
|
||||
setex=setex,
|
||||
),
|
||||
)
|
||||
client.get_model_schema.return_value = schema
|
||||
client.results["get_model_schema"] = schema
|
||||
runtime = PluginModelRuntime(tenant_id="tenant", user_id="user", client=client, plugin_service=PluginService)
|
||||
|
||||
result = runtime.get_model_schema(
|
||||
@@ -792,22 +853,24 @@ def test_get_model_schema_deletes_invalid_cache_and_refetches(
|
||||
|
||||
assert result == schema
|
||||
delete.assert_called_once()
|
||||
client.get_model_schema.assert_called_once_with(
|
||||
tenant_id="tenant",
|
||||
user_id="user",
|
||||
plugin_id="langgenius/openai",
|
||||
provider="openai",
|
||||
model_type=ModelType.LLM.value,
|
||||
model="gpt-4o-mini",
|
||||
credentials={"api_key": "secret"},
|
||||
)
|
||||
assert client.calls["get_model_schema"] == [
|
||||
call(
|
||||
tenant_id="tenant",
|
||||
user_id="user",
|
||||
plugin_id="langgenius/openai",
|
||||
provider="openai",
|
||||
model_type=ModelType.LLM.value,
|
||||
model="gpt-4o-mini",
|
||||
credentials={"api_key": "secret"},
|
||||
)
|
||||
]
|
||||
setex.assert_called_once()
|
||||
|
||||
|
||||
def test_get_llm_num_tokens_returns_zero_when_plugin_counting_is_disabled(
|
||||
config_overrides: Callable[..., None],
|
||||
) -> None:
|
||||
client = Mock(spec=PluginModelClient)
|
||||
client = _RecordingModelClient()
|
||||
config_overrides(PLUGIN_BASED_TOKEN_COUNTING_ENABLED=False)
|
||||
runtime = PluginModelRuntime(tenant_id="tenant", user_id="user", client=client, plugin_service=PluginService)
|
||||
|
||||
@@ -822,12 +885,12 @@ def test_get_llm_num_tokens_returns_zero_when_plugin_counting_is_disabled(
|
||||
)
|
||||
== 0
|
||||
)
|
||||
client.get_llm_num_tokens.assert_not_called()
|
||||
assert not client.calls["get_llm_num_tokens"]
|
||||
|
||||
|
||||
def test_get_provider_icon_reads_requested_variant_and_detects_svg_mime(monkeypatch: pytest.MonkeyPatch) -> None:
|
||||
client = Mock(spec=PluginModelClient)
|
||||
client.fetch_model_providers.return_value = [
|
||||
client = _RecordingModelClient()
|
||||
client.results["fetch_model_providers"] = [
|
||||
PluginModelProviderEntity(
|
||||
id=uuid.uuid4().hex,
|
||||
created_at=datetime.datetime.now(),
|
||||
@@ -863,8 +926,8 @@ def test_get_provider_icon_reads_requested_variant_and_detects_svg_mime(monkeypa
|
||||
|
||||
|
||||
def test_get_provider_icon_rejects_unsupported_types_and_missing_variants() -> None:
|
||||
client = Mock(spec=PluginModelClient)
|
||||
client.fetch_model_providers.return_value = [
|
||||
client = _RecordingModelClient()
|
||||
client.results["fetch_model_providers"] = [
|
||||
PluginModelProviderEntity(
|
||||
id=uuid.uuid4().hex,
|
||||
created_at=datetime.datetime.now(),
|
||||
@@ -901,7 +964,7 @@ def test_get_provider_icon_rejects_unsupported_types_and_missing_variants() -> N
|
||||
|
||||
def test_get_schema_cache_key_is_stable_across_credential_order() -> None:
|
||||
runtime = PluginModelRuntime(
|
||||
tenant_id="tenant", user_id="user", client=Mock(spec=PluginModelClient), plugin_service=PluginService
|
||||
tenant_id="tenant", user_id="user", client=_RecordingModelClient(), plugin_service=PluginService
|
||||
)
|
||||
|
||||
first = runtime._get_schema_cache_key(
|
||||
@@ -922,10 +985,10 @@ def test_get_schema_cache_key_is_stable_across_credential_order() -> None:
|
||||
|
||||
def test_get_schema_cache_key_separates_distinct_user_scopes() -> None:
|
||||
first_runtime = PluginModelRuntime(
|
||||
tenant_id="tenant", user_id="user-a", client=Mock(spec=PluginModelClient), plugin_service=PluginService
|
||||
tenant_id="tenant", user_id="user-a", client=_RecordingModelClient(), plugin_service=PluginService
|
||||
)
|
||||
second_runtime = PluginModelRuntime(
|
||||
tenant_id="tenant", user_id="user-b", client=Mock(spec=PluginModelClient), plugin_service=PluginService
|
||||
tenant_id="tenant", user_id="user-b", client=_RecordingModelClient(), plugin_service=PluginService
|
||||
)
|
||||
|
||||
first = first_runtime._get_schema_cache_key(
|
||||
@@ -946,10 +1009,10 @@ def test_get_schema_cache_key_separates_distinct_user_scopes() -> None:
|
||||
|
||||
def test_get_schema_cache_key_separates_tenant_scope_from_user_scope() -> None:
|
||||
tenant_runtime = PluginModelRuntime(
|
||||
tenant_id="tenant", user_id=None, client=Mock(spec=PluginModelClient), plugin_service=PluginService
|
||||
tenant_id="tenant", user_id=None, client=_RecordingModelClient(), plugin_service=PluginService
|
||||
)
|
||||
user_runtime = PluginModelRuntime(
|
||||
tenant_id="tenant", user_id="user-a", client=Mock(spec=PluginModelClient), plugin_service=PluginService
|
||||
tenant_id="tenant", user_id="user-a", client=_RecordingModelClient(), plugin_service=PluginService
|
||||
)
|
||||
|
||||
tenant_key = tenant_runtime._get_schema_cache_key(
|
||||
@@ -971,10 +1034,10 @@ def test_get_schema_cache_key_separates_tenant_scope_from_user_scope() -> None:
|
||||
|
||||
def test_get_schema_cache_key_separates_tenant_scope_from_empty_string_user_scope() -> None:
|
||||
tenant_runtime = PluginModelRuntime(
|
||||
tenant_id="tenant", user_id=None, client=Mock(spec=PluginModelClient), plugin_service=PluginService
|
||||
tenant_id="tenant", user_id=None, client=_RecordingModelClient(), plugin_service=PluginService
|
||||
)
|
||||
empty_user_runtime = PluginModelRuntime(
|
||||
tenant_id="tenant", user_id="", client=Mock(spec=PluginModelClient), plugin_service=PluginService
|
||||
tenant_id="tenant", user_id="", client=_RecordingModelClient(), plugin_service=PluginService
|
||||
)
|
||||
|
||||
tenant_key = tenant_runtime._get_schema_cache_key(
|
||||
@@ -996,8 +1059,8 @@ def test_get_schema_cache_key_separates_tenant_scope_from_empty_string_user_scop
|
||||
|
||||
|
||||
def test_get_provider_schema_supports_short_alias_and_rejects_invalid_provider() -> None:
|
||||
client = Mock(spec=PluginModelClient)
|
||||
client.fetch_model_providers.return_value = [
|
||||
client = _RecordingModelClient()
|
||||
client.results["fetch_model_providers"] = [
|
||||
PluginModelProviderEntity(
|
||||
id=uuid.uuid4().hex,
|
||||
created_at=datetime.datetime.now(),
|
||||
|
||||
Reference in new issue
Block a user