Release v1.0.11: shared runtime diagnostics and media_assets probe helpers
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This commit is contained in:
2026-06-07 09:06:41 +08:00
parent 2a542c0be6
commit c9398451d0
7 changed files with 772 additions and 17 deletions

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@@ -97,6 +97,29 @@ bundle 内含背景音乐、字体与水印;**不包含** ffmpeg 二进制。f
- `MEDIA_ASSETS_ROOT=/path/to/custom/media-assets` — 本地资源目录
- `MEDIA_ASSETS_BUNDLE_URL=https://example.com/media-assets.zip` — bundle 下载地址
### Runtime diagnostics统一 health 诊断)
`jiangchang_skill_core.runtime_diagnostics` 提供各 Skill 共用的 Runtime / media-assets / ffmpeg 探测避免每个技能各自复制检查逻辑。Skill 的 `health` 命令可调用:
```python
from jiangchang_skill_core import (
collect_runtime_diagnostics,
format_runtime_health_lines,
runtime_diagnostics_dict,
)
diag = collect_runtime_diagnostics(
skill_slug="my-skill",
platform_kit_min_version="1.0.10", # 可选;省略则只报告当前版本
skill_root="/path/to/my-skill", # 可选;用于检测 vendored jiangchang_skill_core
)
for line in format_runtime_health_lines(diag):
print(line)
print(runtime_diagnostics_dict(diag)) # 可 JSON 序列化
```
诊断只读探测本地状态,不会触发 media-assets 下载。
### 录屏合成(`screencast`
`run_screencast()` / `compose_video()` 通过 `jiangchang_skill_core.media_assets` 解析 ffmpeg 与背景音乐,**不使用系统 PATH 中的 `ffmpeg`**。

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@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
[project]
name = "jiangchang-platform-kit"
version = "1.0.10"
version = "1.0.11"
description = "匠厂平台共享组件:Skill 实体 SDK + 桌面应用自动化 SDK"
readme = "README.md"
requires-python = ">=3.10"

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@@ -25,7 +25,10 @@ from .media_assets import (
MediaAssetsStatus,
background_music_issue,
ensure_media_assets,
is_git_lfs_pointer,
is_usable_audio_file,
pick_background_music,
probe_background_music,
probe_ffmpeg,
probe_media_assets,
resolve_ffmpeg,
@@ -33,6 +36,15 @@ from .media_assets import (
resolve_media_assets_root,
resolve_music_dir,
)
from .runtime_diagnostics import (
RuntimeDiagnostics,
RuntimeIssue,
collect_runtime_diagnostics,
format_runtime_health_lines,
is_jiangchang_skill_core_from_skill_tree,
runtime_diagnostics_dict,
version_ge,
)
try:
from . import rpa
@@ -46,8 +58,16 @@ __all__ = [
"EntitlementResult",
"EntitlementServiceError",
"MediaAssetsStatus",
"RuntimeDiagnostics",
"RuntimeIssue",
"background_music_issue",
"collect_runtime_diagnostics",
"ensure_media_assets",
"format_runtime_health_lines",
"is_git_lfs_pointer",
"is_jiangchang_skill_core_from_skill_tree",
"is_usable_audio_file",
"probe_background_music",
"probe_ffmpeg",
"probe_media_assets",
"pick_background_music",
@@ -55,6 +75,8 @@ __all__ = [
"resolve_ffprobe",
"resolve_media_assets_root",
"resolve_music_dir",
"runtime_diagnostics_dict",
"version_ge",
"apply_cli_local_defaults",
"attach_unified_file_handler",
"ensure_env_file",

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@@ -16,7 +16,7 @@ import zipfile
from dataclasses import dataclass, field
from datetime import datetime
from pathlib import Path
from typing import Optional
from typing import Any, Mapping, Optional
MEDIA_ASSETS_BUNDLE_URL = (
"https://git.jc2009.com/client-commons/media-assets/releases/download/vlatest/media-assets.zip"
@@ -29,17 +29,20 @@ _NON_WIN_DEFAULT_DATA_ROOT = Path.home() / ".jiangchang"
_AUDIO_EXTENSIONS = {".mp3", ".wav", ".m4a", ".aac"}
_GIT_LFS_POINTER_PREFIX = b"version https://git-lfs.github.com/spec/v1"
_MIN_AUDIO_BYTES = 128
_MIN_AUDIO_BYTES = 1024
def _is_git_lfs_pointer(path: Path) -> bool:
def is_git_lfs_pointer(path: str | Path) -> bool:
try:
head = path.read_bytes()[:256]
head = Path(path).read_bytes()[:256]
except OSError:
return False
return head.startswith(_GIT_LFS_POINTER_PREFIX)
_is_git_lfs_pointer = is_git_lfs_pointer
def _enumerate_audio_like(music_dir: Path) -> list[Path]:
return [
path
@@ -76,21 +79,25 @@ def _needs_music_content_repair(status: MediaAssetsStatus) -> bool:
)
def _is_usable_audio_file(path: Path) -> bool:
if not path.is_file():
def is_usable_audio_file(path: str | Path, *, min_bytes: int = _MIN_AUDIO_BYTES) -> bool:
p = Path(path)
if not p.is_file():
return False
if path.suffix.lower() not in _AUDIO_EXTENSIONS:
if p.suffix.lower() not in _AUDIO_EXTENSIONS:
return False
if _is_git_lfs_pointer(path):
if is_git_lfs_pointer(p):
return False
try:
if path.stat().st_size < _MIN_AUDIO_BYTES:
if p.stat().st_size < min_bytes:
return False
except OSError:
return False
return True
_is_usable_audio_file = is_usable_audio_file
@dataclass
class MediaAssetsStatus:
root: Path
@@ -724,6 +731,46 @@ def resolve_music_dir(
return status.music_dir
def probe_background_music(
root: str | Path | None = None,
*,
env: Mapping[str, str] | None = None,
) -> dict[str, Any]:
"""只读探测背景音乐目录,不触发 media-assets 下载。"""
env_map = _env_dict(dict(env) if env is not None else None)
if root is not None:
music_dir = Path(root) / "music"
if not music_dir.is_dir():
music_dir = Path(root) if Path(root).is_dir() else None
else:
data_root = (env_map.get("JIANGCHANG_DATA_ROOT") or env_map.get("CLAW_DATA_ROOT") or "").strip()
assets_root = resolve_media_assets_root(data_root or None, env_map)
status = _inspect_media_assets(assets_root, source="local")
music_dir = status.music_dir
music_root = str(music_dir) if music_dir is not None else None
if music_dir is None or not music_dir.is_dir():
return {
"music_root": music_root,
"mp3_count": 0,
"usable_count": 0,
"sample_path": None,
"issue": "music_dir_missing",
}
mp3_files = [path for path in music_dir.rglob("*.mp3") if path.is_file()]
usable = [path for path in music_dir.rglob("*") if is_usable_audio_file(path)]
issue = _music_content_issue(music_dir)
sample = str(sorted(usable, key=lambda p: str(p).lower())[0]) if usable else None
return {
"music_root": music_root,
"mp3_count": len(mp3_files),
"usable_count": len(usable),
"sample_path": sample,
"issue": issue,
}
def background_music_issue(
data_root: str | Path | None = None,
env: dict[str, str] | None = None,

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@@ -0,0 +1,321 @@
"""共享 Runtime 诊断health 输出与 media-assets / ffmpeg 探测。"""
from __future__ import annotations
import importlib.metadata
import logging
import os
import sys
from dataclasses import dataclass
from pathlib import Path
from typing import Any, Mapping
import jiangchang_skill_core
from .media_assets import probe_background_music, probe_media_assets, resolve_media_assets_root
from .runtime_env import platform_default_data_root
_SHARED_CORE_HINT = (
"jiangchang_skill_core is loaded from the skill tree; expected the shared "
"jiangchang-platform-kit installed in the host Python runtime."
)
@dataclass(frozen=True)
class RuntimeIssue:
code: str
message: str
severity: str = "warning"
@dataclass(frozen=True)
class RuntimeDiagnostics:
skill_slug: str
python_executable: str
platform_kit_version: str | None
platform_kit_min_version: str | None
platform_kit_version_ok: bool | None
jiangchang_skill_core_file: str | None
claw_data_root: str | None
jiangchang_data_root: str | None
resolved_data_root: str | None
media_assets_root: str | None
ffmpeg_available: bool
ffmpeg_path: str | None
background_music_mp3_count: int
background_music_usable_count: int
background_music_issue: str | None
background_music_sample_path: str | None
record_video_enabled: bool
issues: tuple[RuntimeIssue, ...]
@property
def has_fatal_issues(self) -> bool:
return any(issue.severity == "error" for issue in self.issues)
def issue_codes(self) -> list[str]:
return [issue.code for issue in self.issues]
def _env_dict(env: Mapping[str, str] | None) -> dict[str, str]:
return dict(env) if env is not None else dict(os.environ)
def _resolve_data_root(env: Mapping[str, str]) -> str:
root = (env.get("CLAW_DATA_ROOT") or env.get("JIANGCHANG_DATA_ROOT") or "").strip()
if root:
return root
return platform_default_data_root()
def _parse_version(version: str) -> tuple[int, ...]:
parts: list[int] = []
for piece in version.strip().split("."):
digits = ""
for ch in piece:
if ch.isdigit():
digits += ch
else:
break
if digits:
parts.append(int(digits))
return tuple(parts)
def version_ge(installed: str, required: str) -> bool:
"""Compare PEP 440-like versions without external deps (post release suffix ignored)."""
return _parse_version(installed) >= _parse_version(required)
def _path_under(parent: str | Path, child: str | Path) -> bool:
try:
parent_path = Path(parent).resolve()
child_path = Path(child).resolve()
if sys.platform == "win32":
parent_norm = os.path.normcase(str(parent_path))
child_norm = os.path.normcase(str(child_path))
common = os.path.commonpath([parent_norm, child_norm])
return common == parent_norm
return os.path.commonpath([str(parent_path), str(child_path)]) == str(parent_path)
except (OSError, ValueError):
return False
def is_jiangchang_skill_core_from_skill_tree(
*,
skill_root: str | Path,
core_file: str | Path | None = None,
) -> bool:
"""Return True when jiangchang_skill_core is loaded from inside skill_root."""
try:
root = Path(skill_root)
if not str(root).strip():
return False
core = Path(core_file) if core_file is not None else Path(jiangchang_skill_core.__file__)
return _path_under(root, core)
except (OSError, TypeError, ValueError):
return False
def _platform_kit_version() -> str | None:
try:
return importlib.metadata.version("jiangchang-platform-kit")
except importlib.metadata.PackageNotFoundError:
return None
def _bool_from_env(env: Mapping[str, str], key: str, default: bool = False) -> bool:
val = env.get(key)
if val is None or val == "":
return default
return str(val).strip().lower() in ("1", "true", "yes", "on")
def collect_runtime_diagnostics(
*,
skill_slug: str,
platform_kit_min_version: str | None = None,
skill_root: str | Path | None = None,
record_video: bool | None = None,
env: Mapping[str, str] | None = None,
) -> RuntimeDiagnostics:
env_map = _env_dict(env)
issues: list[RuntimeIssue] = []
claw_data_root = env_map.get("CLAW_DATA_ROOT")
jiangchang_data_root = env_map.get("JIANGCHANG_DATA_ROOT")
resolved_data_root = _resolve_data_root(env_map)
media_root_path = resolve_media_assets_root(resolved_data_root, env_map)
media_status = probe_media_assets(resolved_data_root, env_map)
ffmpeg_path_obj = media_status.ffmpeg_path
ffmpeg_ok = ffmpeg_path_obj is not None and ffmpeg_path_obj.is_file()
music_probe = probe_background_music(media_root_path, env=env_map)
mp3_count = int(music_probe["mp3_count"])
usable_count = int(music_probe["usable_count"])
music_issue = music_probe.get("issue")
music_sample = music_probe.get("sample_path")
if music_issue is None and not media_status.music_ready and media_status.warnings:
for warning in media_status.warnings:
if warning.startswith("background_music") or warning == "music_dir_missing":
music_issue = warning
break
platform_version = _platform_kit_version()
platform_ok: bool | None
if platform_kit_min_version is None:
platform_ok = None
elif platform_version is None:
platform_ok = False
else:
platform_ok = version_ge(platform_version, platform_kit_min_version)
if platform_version is None:
issues.append(
RuntimeIssue(
code="platform_kit_not_installed",
message="jiangchang-platform-kit package metadata not found",
severity="error",
)
)
elif platform_kit_min_version is not None and not platform_ok:
issues.append(
RuntimeIssue(
code="platform_kit_version_low",
message=(
f"jiangchang-platform-kit version {platform_version} "
f"is below required {platform_kit_min_version}"
),
severity="error",
)
)
core_file: str | None
try:
core_file = os.path.abspath(jiangchang_skill_core.__file__)
except (OSError, TypeError, ValueError):
core_file = None
if skill_root is not None and core_file is not None:
if is_jiangchang_skill_core_from_skill_tree(skill_root=skill_root, core_file=core_file):
issues.append(
RuntimeIssue(
code="jiangchang_skill_core_loaded_from_skill_tree",
message=_SHARED_CORE_HINT,
severity="warning",
)
)
if record_video is None:
record_video_enabled = _bool_from_env(env_map, "OPENCLAW_RECORD_VIDEO", False)
else:
record_video_enabled = record_video
if not ffmpeg_ok:
severity = "warning"
message = "ffmpeg not available"
if record_video_enabled:
message = "OPENCLAW_RECORD_VIDEO enabled but ffmpeg is not available"
issues.append(
RuntimeIssue(
code="ffmpeg_unavailable",
message=message,
severity=severity,
)
)
if record_video_enabled and music_issue:
issues.append(
RuntimeIssue(
code="background_music_unavailable",
message=f"background music unavailable: {music_issue}",
severity="warning",
)
)
return RuntimeDiagnostics(
skill_slug=skill_slug,
python_executable=sys.executable,
platform_kit_version=platform_version,
platform_kit_min_version=platform_kit_min_version,
platform_kit_version_ok=platform_ok,
jiangchang_skill_core_file=core_file,
claw_data_root=claw_data_root,
jiangchang_data_root=jiangchang_data_root,
resolved_data_root=resolved_data_root,
media_assets_root=str(media_root_path),
ffmpeg_available=ffmpeg_ok,
ffmpeg_path=str(ffmpeg_path_obj) if ffmpeg_path_obj else None,
background_music_mp3_count=mp3_count,
background_music_usable_count=usable_count,
background_music_issue=str(music_issue) if music_issue else None,
background_music_sample_path=str(music_sample) if music_sample else None,
record_video_enabled=record_video_enabled,
issues=tuple(issues),
)
def format_runtime_health_lines(diagnostics: RuntimeDiagnostics) -> list[str]:
lines = [
f"skill_slug: {diagnostics.skill_slug}",
f"python_executable: {diagnostics.python_executable}",
f"platform_kit_version: {diagnostics.platform_kit_version or ''}",
f"platform_kit_min_version: {diagnostics.platform_kit_min_version or ''}",
f"platform_kit_version_ok: {diagnostics.platform_kit_version_ok}",
f"jiangchang_skill_core_file: {diagnostics.jiangchang_skill_core_file or ''}",
f"CLAW_DATA_ROOT: {diagnostics.claw_data_root or ''}",
f"JIANGCHANG_DATA_ROOT: {diagnostics.jiangchang_data_root or ''}",
f"resolved_data_root: {diagnostics.resolved_data_root or ''}",
f"media_assets_root: {diagnostics.media_assets_root or ''}",
f"ffmpeg_available: {diagnostics.ffmpeg_available}",
f"ffmpeg_path: {diagnostics.ffmpeg_path or ''}",
f"background_music_mp3_count: {diagnostics.background_music_mp3_count}",
f"background_music_usable_count: {diagnostics.background_music_usable_count}",
f"background_music_issue: {diagnostics.background_music_issue or ''}",
f"background_music_sample_path: {diagnostics.background_music_sample_path or ''}",
f"record_video_enabled: {diagnostics.record_video_enabled}",
]
for issue in diagnostics.issues:
lines.append(f"runtime_issue[{issue.severity}]: {issue.code}{issue.message}")
return lines
def runtime_diagnostics_dict(diagnostics: RuntimeDiagnostics) -> dict[str, Any]:
return {
"skill_slug": diagnostics.skill_slug,
"python_executable": diagnostics.python_executable,
"platform_kit_version": diagnostics.platform_kit_version,
"platform_kit_min_version": diagnostics.platform_kit_min_version,
"platform_kit_version_ok": diagnostics.platform_kit_version_ok,
"jiangchang_skill_core_file": diagnostics.jiangchang_skill_core_file,
"CLAW_DATA_ROOT": diagnostics.claw_data_root,
"JIANGCHANG_DATA_ROOT": diagnostics.jiangchang_data_root,
"resolved_data_root": diagnostics.resolved_data_root,
"media_assets_root": diagnostics.media_assets_root,
"ffmpeg_available": diagnostics.ffmpeg_available,
"ffmpeg_path": diagnostics.ffmpeg_path,
"background_music_mp3_count": diagnostics.background_music_mp3_count,
"background_music_usable_count": diagnostics.background_music_usable_count,
"background_music_issue": diagnostics.background_music_issue,
"background_music_sample_path": diagnostics.background_music_sample_path,
"record_video_enabled": diagnostics.record_video_enabled,
"runtime_issues": [
{"code": issue.code, "message": issue.message, "severity": issue.severity}
for issue in diagnostics.issues
],
}
def log_runtime_diagnostics(
diagnostics: RuntimeDiagnostics,
logger: logging.Logger | None = None,
level: int = logging.INFO,
) -> None:
log = logger or logging.getLogger("jiangchang_skill_core.runtime_diagnostics")
for line in format_runtime_health_lines(diagnostics):
log.log(level, line)

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@@ -15,7 +15,7 @@ from jiangchang_skill_core import media_assets as ma
def _make_complete_assets(root: Path, *, with_ffmpeg: bool = True, with_ffprobe: bool = True) -> None:
(root / "music" / "calm").mkdir(parents=True)
(root / "music" / "calm" / "track.mp3").write_bytes(b"x" * 256)
(root / "music" / "calm" / "track.mp3").write_bytes(b"x" * 1024)
(root / "fonts").mkdir(parents=True)
(root / "watermark").mkdir(parents=True)
bin_key = ma._platform_bin_key()
@@ -63,7 +63,7 @@ def _build_archive_zip(dest: Path, inner_name: str) -> None:
with zipfile.ZipFile(dest, "w") as zf:
zf.writestr(f"{inner_name}/README.md", "# media-assets\n")
zf.writestr(f"{inner_name}/manifest.json", json.dumps(manifest, ensure_ascii=False))
zf.writestr(f"{inner_name}/music/calm/track.mp3", b"x" * 256)
zf.writestr(f"{inner_name}/music/calm/track.mp3", b"x" * 1024)
zf.writestr(f"{inner_name}/fonts/.keep", "")
zf.writestr(f"{inner_name}/watermark/.keep", "")
@@ -168,9 +168,9 @@ def test_pick_background_music_stable_first(tmp_path: Path, monkeypatch: pytest.
root = tmp_path / "data" / "shared" / "media-assets"
_make_complete_assets(root)
music = root / "music"
(music / "b-upbeat.mp3").write_bytes(b"x" * 256)
(music / "calm" / "a-calm.mp3").write_bytes(b"x" * 256)
(music / "z-last.wav").write_bytes(b"x" * 256)
(music / "b-upbeat.mp3").write_bytes(b"x" * 1024)
(music / "calm" / "a-calm.mp3").write_bytes(b"x" * 1024)
(music / "z-last.wav").write_bytes(b"x" * 1024)
monkeypatch.setattr(
ma,
@@ -297,7 +297,7 @@ def test_pick_background_music_skips_lfs_pointer(tmp_path: Path, monkeypatch: py
_make_complete_assets(root, with_ffmpeg=True, with_ffprobe=True)
music = root / "music"
(music / "calm" / "track.mp3").unlink()
(music / "real.mp3").write_bytes(b"x" * 256)
(music / "real.mp3").write_bytes(b"x" * 1024)
lfs = music / "lfs-only.mp3"
lfs.write_text("version https://git-lfs.github.com/spec/v1\noid sha256:abc\nsize 123\n")
@@ -390,7 +390,7 @@ def test_video_finalize_without_music_fallback(tmp_path: Path, monkeypatch: pyte
def test_manifest_ffmpeg_download(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
root = tmp_path / "data" / "shared" / "media-assets"
(root / "music" / "calm").mkdir(parents=True)
(root / "music" / "calm" / "track.mp3").write_bytes(b"x" * 256)
(root / "music" / "calm" / "track.mp3").write_bytes(b"x" * 1024)
(root / "fonts").mkdir(parents=True)
(root / "watermark").mkdir(parents=True)
(root / "manifest.json").write_text(
@@ -406,3 +406,32 @@ def test_manifest_ffmpeg_download(tmp_path: Path, monkeypatch: pytest.MonkeyPatc
assert status.ready is True
assert status.ffmpeg_path is not None
assert status.ffprobe_path is not None
def test_is_usable_audio_file_rejects_small_and_lfs(tmp_path: Path) -> None:
small = tmp_path / "small.mp3"
small.write_bytes(b"x" * 512)
assert ma.is_usable_audio_file(small) is False
ok = tmp_path / "ok.mp3"
ok.write_bytes(b"x" * 1024)
assert ma.is_usable_audio_file(ok) is True
lfs = tmp_path / "lfs.mp3"
lfs.write_text("version https://git-lfs.github.com/spec/v1\noid sha256:abc\nsize 123\n")
assert ma.is_usable_audio_file(lfs) is False
assert ma.is_git_lfs_pointer(lfs) is True
def test_probe_background_music_structure(tmp_path: Path) -> None:
root = tmp_path / "media-assets"
music = root / "music" / "calm"
music.mkdir(parents=True)
(music / "track.mp3").write_bytes(b"x" * 1024)
probe = ma.probe_background_music(root)
assert probe["music_root"] == str(root / "music")
assert probe["mp3_count"] == 1
assert probe["usable_count"] == 1
assert probe["issue"] is None
assert probe["sample_path"] == str(music / "track.mp3")

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@@ -0,0 +1,313 @@
# -*- coding: utf-8 -*-
"""runtime_diagnostics 公共 Runtime / media-assets 诊断测试。"""
from __future__ import annotations
import json
from pathlib import Path
from unittest.mock import patch
import pytest
import jiangchang_skill_core
from jiangchang_skill_core import media_assets as ma
from jiangchang_skill_core.runtime_diagnostics import (
RuntimeDiagnostics,
RuntimeIssue,
collect_runtime_diagnostics,
format_runtime_health_lines,
is_jiangchang_skill_core_from_skill_tree,
runtime_diagnostics_dict,
version_ge,
)
def test_version_ge_post_release() -> None:
assert version_ge("1.0.10.post23", "1.0.10") is True
assert version_ge("1.0.10", "1.0.10") is True
assert version_ge("1.0.9.post19", "1.0.10") is False
def test_is_jiangchang_skill_core_from_skill_tree(tmp_path: Path) -> None:
skill_root = tmp_path / "my-skill"
inside = skill_root / "scripts" / "jiangchang_skill_core" / "__init__.py"
inside.parent.mkdir(parents=True)
inside.write_text("# vendored\n", encoding="utf-8")
outside = tmp_path / "site-packages" / "jiangchang_skill_core" / "__init__.py"
outside.parent.mkdir(parents=True)
outside.write_text("# shared\n", encoding="utf-8")
assert is_jiangchang_skill_core_from_skill_tree(
skill_root=skill_root,
core_file=inside,
) is True
assert is_jiangchang_skill_core_from_skill_tree(
skill_root=skill_root,
core_file=outside,
) is False
def test_collect_runtime_diagnostics_json_serializable(
tmp_path: Path,
monkeypatch: pytest.MonkeyPatch,
) -> None:
data_root = tmp_path / "data"
env = {
"CLAW_DATA_ROOT": str(data_root),
"OPENCLAW_RECORD_VIDEO": "0",
}
media_root = data_root / "shared" / "media-assets"
(media_root / "music").mkdir(parents=True)
def _fake_probe_media_assets(data_root_arg=None, env_arg=None):
return ma.MediaAssetsStatus(
root=media_root,
exists=True,
ready=False,
source="local",
warnings=["ffmpeg_missing"],
ffmpeg_path=None,
music_dir=media_root / "music",
music_ready=False,
)
monkeypatch.setattr(
"jiangchang_skill_core.runtime_diagnostics.probe_media_assets",
_fake_probe_media_assets,
)
monkeypatch.setattr(
"jiangchang_skill_core.runtime_diagnostics.probe_background_music",
lambda *a, **k: {
"music_root": str(media_root / "music"),
"mp3_count": 0,
"usable_count": 0,
"sample_path": None,
"issue": "background_music_dir_empty",
},
)
monkeypatch.setattr(
"jiangchang_skill_core.runtime_diagnostics._platform_kit_version",
lambda: "1.0.10",
)
diag = collect_runtime_diagnostics(
skill_slug="my-skill",
platform_kit_min_version="1.0.9",
env=env,
)
payload = runtime_diagnostics_dict(diag)
json.dumps(payload)
assert payload["skill_slug"] == "my-skill"
assert payload["resolved_data_root"] == str(data_root)
assert payload["platform_kit_version_ok"] is True
def test_platform_kit_min_version_none_skips_version_issue(
tmp_path: Path,
monkeypatch: pytest.MonkeyPatch,
) -> None:
env = {"CLAW_DATA_ROOT": str(tmp_path / "data")}
monkeypatch.setattr(
"jiangchang_skill_core.runtime_diagnostics.probe_media_assets",
lambda *a, **k: ma.MediaAssetsStatus(
root=tmp_path,
exists=False,
ready=False,
source="local",
),
)
monkeypatch.setattr(
"jiangchang_skill_core.runtime_diagnostics.probe_background_music",
lambda *a, **k: {
"music_root": None,
"mp3_count": 0,
"usable_count": 0,
"sample_path": None,
"issue": "music_dir_missing",
},
)
monkeypatch.setattr(
"jiangchang_skill_core.runtime_diagnostics._platform_kit_version",
lambda: "1.0.8",
)
diag = collect_runtime_diagnostics(skill_slug="my-skill", env=env)
assert diag.platform_kit_version_ok is None
assert "platform_kit_version_low" not in diag.issue_codes()
def test_platform_kit_missing_records_issue(
tmp_path: Path,
monkeypatch: pytest.MonkeyPatch,
) -> None:
env = {"CLAW_DATA_ROOT": str(tmp_path / "data")}
monkeypatch.setattr(
"jiangchang_skill_core.runtime_diagnostics.probe_media_assets",
lambda *a, **k: ma.MediaAssetsStatus(
root=tmp_path,
exists=False,
ready=False,
source="local",
),
)
monkeypatch.setattr(
"jiangchang_skill_core.runtime_diagnostics.probe_background_music",
lambda *a, **k: {
"music_root": None,
"mp3_count": 0,
"usable_count": 0,
"sample_path": None,
"issue": None,
},
)
monkeypatch.setattr(
"jiangchang_skill_core.runtime_diagnostics._platform_kit_version",
lambda: None,
)
diag = collect_runtime_diagnostics(
skill_slug="my-skill",
platform_kit_min_version="1.0.10",
env=env,
)
assert "platform_kit_not_installed" in diag.issue_codes()
def test_record_video_ffmpeg_and_music_warnings_not_fatal(
tmp_path: Path,
monkeypatch: pytest.MonkeyPatch,
) -> None:
media_root = tmp_path / "shared" / "media-assets"
env = {"CLAW_DATA_ROOT": str(tmp_path), "OPENCLAW_RECORD_VIDEO": "1"}
monkeypatch.setattr(
"jiangchang_skill_core.runtime_diagnostics.probe_media_assets",
lambda *a, **k: ma.MediaAssetsStatus(
root=media_root,
exists=True,
ready=False,
source="local",
warnings=["ffmpeg_missing", "music_dir_missing"],
ffmpeg_path=None,
music_dir=None,
),
)
monkeypatch.setattr(
"jiangchang_skill_core.runtime_diagnostics.probe_background_music",
lambda *a, **k: {
"music_root": None,
"mp3_count": 0,
"usable_count": 0,
"sample_path": None,
"issue": "music_dir_missing",
},
)
monkeypatch.setattr(
"jiangchang_skill_core.runtime_diagnostics._platform_kit_version",
lambda: "1.0.10",
)
diag = collect_runtime_diagnostics(skill_slug="my-skill", env=env)
codes = diag.issue_codes()
assert "ffmpeg_unavailable" in codes
assert "background_music_unavailable" in codes
assert diag.has_fatal_issues is False
ffmpeg_issue = next(i for i in diag.issues if i.code == "ffmpeg_unavailable")
assert ffmpeg_issue.severity == "warning"
def test_skill_tree_core_issue_when_skill_root_given(tmp_path: Path) -> None:
skill_root = tmp_path / "my-skill"
fake_core = skill_root / "scripts" / "jiangchang_skill_core" / "__init__.py"
fake_core.parent.mkdir(parents=True)
fake_core.write_text("# vendored\n", encoding="utf-8")
env = {"CLAW_DATA_ROOT": str(tmp_path / "data")}
with patch.object(jiangchang_skill_core, "__file__", str(fake_core)):
diag = collect_runtime_diagnostics(
skill_slug="my-skill",
skill_root=skill_root,
record_video=False,
env=env,
)
assert "jiangchang_skill_core_loaded_from_skill_tree" in diag.issue_codes()
def test_format_runtime_health_lines_core_fields(
tmp_path: Path,
monkeypatch: pytest.MonkeyPatch,
) -> None:
env = {"CLAW_DATA_ROOT": str(tmp_path / "data")}
monkeypatch.setattr(
"jiangchang_skill_core.runtime_diagnostics.probe_media_assets",
lambda *a, **k: ma.MediaAssetsStatus(
root=tmp_path,
exists=False,
ready=False,
source="local",
),
)
monkeypatch.setattr(
"jiangchang_skill_core.runtime_diagnostics.probe_background_music",
lambda *a, **k: {
"music_root": None,
"mp3_count": 0,
"usable_count": 0,
"sample_path": None,
"issue": None,
},
)
monkeypatch.setattr(
"jiangchang_skill_core.runtime_diagnostics._platform_kit_version",
lambda: "1.0.10",
)
diag = collect_runtime_diagnostics(skill_slug="my-skill", env=env)
text = "\n".join(format_runtime_health_lines(diag))
for marker in (
"python_executable:",
"platform_kit_version:",
"resolved_data_root:",
"media_assets_root:",
"ffmpeg_available:",
"background_music_mp3_count:",
):
assert marker in text
def test_background_music_lfs_and_size_rules(tmp_path: Path) -> None:
music = tmp_path / "music"
music.mkdir()
(music / "tiny.mp3").write_bytes(b"x" * 512)
(music / "lfs.mp3").write_text(
"version https://git-lfs.github.com/spec/v1\noid sha256:abc\nsize 123\n"
)
(music / "ok.mp3").write_bytes(b"x" * 1024)
probe = ma.probe_background_music(tmp_path)
assert probe["mp3_count"] == 3
assert probe["usable_count"] == 1
assert probe["sample_path"] == str(music / "ok.mp3")
def test_runtime_diagnostics_frozen_dataclass() -> None:
diag = RuntimeDiagnostics(
skill_slug="x",
python_executable="python",
platform_kit_version="1.0.10",
platform_kit_min_version=None,
platform_kit_version_ok=None,
jiangchang_skill_core_file=None,
claw_data_root=None,
jiangchang_data_root=None,
resolved_data_root="/tmp",
media_assets_root="/tmp/media",
ffmpeg_available=False,
ffmpeg_path=None,
background_music_mp3_count=0,
background_music_usable_count=0,
background_music_issue=None,
background_music_sample_path=None,
record_video_enabled=False,
issues=(RuntimeIssue(code="ffmpeg_unavailable", message="no ffmpeg"),),
)
assert diag.has_fatal_issues is False
assert diag.issue_codes() == ["ffmpeg_unavailable"]