mirror of
https://github.com/jxxghp/MoviePilot.git
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102 lines
3.8 KiB
Python
102 lines
3.8 KiB
Python
from unittest.mock import AsyncMock, patch
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from app.agent import MoviePilotAgent
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from app.agent.llm import AgentCapabilityManager, LLMHelper
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from app.chain.message import MessageChain
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from app.core.config import settings
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from app.schemas.types import MessageChannel
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def test_llm_supports_image_input_uses_model_catalog_text_only(monkeypatch):
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"""内置目录明确为纯文本模型时，应自动关闭图片输入。"""
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monkeypatch.setattr(settings, "LLM_SUPPORT_IMAGE_INPUT", True)
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assert not LLMHelper.supports_image_input(
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provider="minimax",
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model="MiniMax-M2.7",
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)
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def test_llm_supports_image_input_keeps_known_vision_model(monkeypatch):
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"""内置目录明确为视觉模型时，应允许图片输入。"""
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monkeypatch.setattr(settings, "LLM_SUPPORT_IMAGE_INPUT", True)
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assert LLMHelper.supports_image_input(
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provider="zhipuai",
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model="glm-5v-turbo",
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)
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def test_llm_supports_image_input_keeps_unknown_model_override(monkeypatch):
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"""未知自定义模型保持用户开关语义，避免误伤私有视觉模型。"""
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monkeypatch.setattr(settings, "LLM_SUPPORT_IMAGE_INPUT", True)
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assert LLMHelper.supports_image_input(
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provider="custom-provider",
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model="custom-vlm-model",
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)
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def test_agent_capability_manager_delegates_image_support():
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"""Agent 能力管理器应复用统一的模型图片能力判断。"""
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with patch.object(LLMHelper, "supports_image_input", return_value=False) as supports:
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assert not AgentCapabilityManager.supports_image_input()
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supports.assert_called_once_with()
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def test_handle_ai_message_routes_text_only_model_images_to_files(monkeypatch):
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"""纯文本模型收到图片消息时，应降级为文件附件而非 image_url 内容块。"""
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chain = MessageChain()
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monkeypatch.setattr(settings, "AI_AGENT_ENABLE", True)
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monkeypatch.setattr(settings, "LLM_SUPPORT_IMAGE_INPUT", True)
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monkeypatch.setattr(settings, "LLM_PROVIDER", "minimax")
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monkeypatch.setattr(settings, "LLM_MODEL", "MiniMax-M2.7")
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with patch.object(
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chain, "_get_or_create_session_id", return_value="session-1"
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), patch.object(
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chain, "_download_attachments_to_data_urls"
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) as download_images, patch.object(
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chain,
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"_prepare_agent_files",
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return_value=[
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{
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"name": "image_1.jpg",
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"mime_type": "image/jpeg",
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"local_path": "/tmp/image_1.jpg",
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"status": "ready",
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}
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],
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) as prepare_files, patch(
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"app.chain.message.agent_manager.process_message", new_callable=AsyncMock
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) as process_message, patch(
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"app.chain.message.asyncio.run_coroutine_threadsafe",
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side_effect=lambda coro, _loop: coro.close(),
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):
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chain._handle_ai_message(
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text="/ai 帮我看看这张图",
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channel=MessageChannel.Telegram,
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source="telegram-test",
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userid="10001",
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username="tester",
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images=["tg://file_id/image-1"],
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)
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download_images.assert_not_called()
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prepare_files.assert_called_once()
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assert prepare_files.call_args.kwargs["files"][0].ref == "tg://file_id/image-1"
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assert process_message.call_args.kwargs["images"] is None
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assert process_message.call_args.kwargs["files"][0]["local_path"] == "/tmp/image_1.jpg"
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def test_unsupported_image_error_recognizes_vlm_text_only_message():
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"""兼容端点返回 not a VLM 时，应识别为图片输入能力错误。"""
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error = Exception(
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"Error code: 400 - {'code': 20041, 'message': "
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"'The model is not a VLM (Vision Language Model). "
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"Please use text-only prompts.'}"
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)
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assert MoviePilotAgent._is_unsupported_image_input_error(error)
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