ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter4/perception-tools/test_analyze_video_release_on_error.py

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+"""Regression test: analyze_video_ai must release the VideoCapture even when a
+per-frame Vision API call raises mid-loop.
+
+The capture was previously released only on the success path, so a failing
+Vision call (network / rate-limit / auth) leaked the native decoder/file handle
+until GC. Release now happens in a finally.
+"""
+import asyncio
+import json
+import os
+import sys
+import types
+from pathlib import Path
+
+import cv2
+import numpy as np
+import pytest
+
+SRC = os.path.join(os.path.dirname(__file__), "src")
+
+
+class _TextContent:
+    def __init__(self, **kwargs):
+        self.__dict__.update(kwargs)
+
+
+@pytest.fixture
+def media_processing_tools(monkeypatch):
+    """Import the chapter module with its optional runtime deps stubbed only for
+    the duration of the test. monkeypatch restores sys.modules / sys.path
+    afterwards, so we never permanently overwrite a real `mcp` / `dotenv` (or
+    leave a partial stub in the global cache for other tests to pick up)."""
+    monkeypatch.syspath_prepend(SRC)
+    monkeypatch.setitem(
+        sys.modules, "dotenv", types.SimpleNamespace(load_dotenv=lambda: None)
+    )
+    mcp = types.ModuleType("mcp")
+    mcp_types = types.ModuleType("mcp.types")
+    mcp_types.TextContent = _TextContent
+    monkeypatch.setitem(sys.modules, "mcp", mcp)
+    monkeypatch.setitem(sys.modules, "mcp.types", mcp_types)
+    # Force a fresh import under the stubs even if another test already imported
+    # the module; monkeypatch restores the original entry on teardown.
+    monkeypatch.delitem(sys.modules, "media_processing_tools", raising=False)
+    import media_processing_tools
+
+    return media_processing_tools
+
+
+class _FakeCapture:
+    """Minimal VideoCapture stand-in that yields a few frames and records
+    whether release() was called."""
+
+    def __init__(self):
+        self.released = False
+        self._frames = 3
+        self._i = 0
+
+    def get(self, prop):
+        if prop == cv2.CAP_PROP_FPS:
+            return 10.0
+        if prop == cv2.CAP_PROP_FRAME_COUNT:
+            return float(self._frames)
+        return 0.0
+
+    def isOpened(self):
+        return True
+
+    def read(self):
+        if self._i < self._frames:
+            self._i += 1
+            return True, np.zeros((48, 64, 3), dtype=np.uint8)
+        return False, None
+
+    def release(self):
+        self.released = True
+
+
+def test_analyze_video_ai_releases_capture_when_vision_call_raises(
+    media_processing_tools, monkeypatch
+):
+    mpt = media_processing_tools
+    fake = _FakeCapture()
+    monkeypatch.setattr(mpt.cv2, "VideoCapture", lambda _path: fake)
+
+    def _boom(**kwargs):
+        raise RuntimeError("vision backend unavailable")
+
+    client = types.SimpleNamespace(
+        chat=types.SimpleNamespace(completions=types.SimpleNamespace(create=_boom))
+    )
+    monkeypatch.setattr(mpt, "_make_vision_client", lambda: (client, "fake-model"))
+    # validate_file_path would reject a non-existent path before we reach the
+    # capture; stub it to pass the path through unchanged.
+    monkeypatch.setattr(mpt, "validate_file_path", lambda p: Path(p))
+
+    result = asyncio.run(mpt.analyze_video_ai("some_clip.mp4", num_frames=2))
+    payload = json.loads(result.text)
+
+    assert payload["success"] is False
+    assert fake.released is True