refactor(kb-workflow): 改用Prompt-based模式

- SKILL.md: 重写为详细workflow指导,主代理直接读取执行
- kb_workflow.py: 简化为辅助工具函数库
- skill_main.py: 简化为触发检测入口
- SkillBug.md: 记录架构变更

主代理读取SKILL.md后,按照指导调用sessions_spawn,无需配置allowlist
This commit is contained in:
OpenClaw Agent
2026-02-10 20:46:06 +08:00
parent 679cca3b2c
commit e370b6b39f
4 changed files with 445 additions and 937 deletions
+139 -585
View File
@@ -3,21 +3,10 @@
"""
KB Workflow - Knowledge Base Workflow Orchestrator
知识库工作流编排技能。
知识库工作流辅助工具函数。
核心职责:
1. 接收用户消息,识别触发词和链接
2. 查重(根据URL/文件名)
3. 调用子agent处理各阶段
4. 文件流转(mv)
5. Git版本管理
6. 归档和清理
设计原则:
- workflow不读文件内容
- 从文件名提取平台(第一个下划线之前)
- 子技能自己定义输入输出格式
- workflow只传递提示词 + 需要的路径信息
此模块提供查重、文件操作、Git 管理等工具函数,
供主代理在执行 SKILL.md 中定义的 workflow 时调用。
"""
import os
@@ -31,20 +20,21 @@ from datetime import datetime
from pathlib import Path
from typing import Dict, List, Optional, Any
# ==================== 子技能映射 ====================
LINK_PARSER_AGENT = "kb-link-parser"
METADATA_AGENTS = {
"bilibili": "kb-bilibili-metadata",
"zhihu": "kb-zhihu-metadata",
}
CONTENT_AGENTS = {
"bilibili": "kb-bilibili-content",
}
OCR_AGENT = "kb-ocr-processor"
ANALYZER_AGENT = "kb-deep-analyzer"
# ==================== 工具函数 ====================
def extract_platform(filename: str) -> str:
"""从文件名提取平台(第一个下划线之前)"""
match = re.match(r'^([a-zA-Z0-9]+)_(.+)$', filename)
@@ -58,9 +48,21 @@ def extract_base_name(filename: str) -> str:
return Path(filename).stem
def ensure_directories(base_path: Path) -> Dict[str, Path]:
def get_knowledge_base_path() -> Path:
"""获取知识库根目录"""
base_path_str = os.environ.get('KB_BASE_PATH', '')
if base_path_str:
return Path(base_path_str).expanduser()
return Path.home() / "work" / "knowledge-base"
def ensure_directories(base_path: Path = None) -> Dict[str, Path]:
"""确保目录存在"""
if base_path is None:
base_path = get_knowledge_base_path()
dirs = {
"base": base_path,
"pending": base_path / "pending",
"metadata": base_path / "metadata",
"content": base_path / "content",
@@ -72,19 +74,24 @@ def ensure_directories(base_path: Path) -> Dict[str, Path]:
}
for name, dir_path in dirs.items():
dir_path.mkdir(parents=True, exist_ok=True)
if isinstance(dir_path, Path):
dir_path.mkdir(parents=True, exist_ok=True)
return dirs
def check_duplicate(base_path: Path, url: str) -> Dict[str, Any]:
def check_duplicate(base_path: Path = None, url: str = None, platform: str = None, content_id: str = None) -> Dict[str, Any]:
"""查重检查"""
if base_path is None:
base_path = get_knowledge_base_path()
metadata_dir = base_path / "metadata"
archive_dir = base_path / "archive"
# 从URL提取ID
bv_match = re.search(r'BV[a-zA-Z0-9]+', url)
content_id = bv_match.group() if bv_match else None
if url and not content_id:
bv_match = re.search(r'BV[a-zA-Z0-9]+', url)
content_id = bv_match.group() if bv_match else None
result = {"duplicate": False, "status": None, "files": []}
@@ -107,364 +114,26 @@ def check_duplicate(base_path: Path, url: str) -> Dict[str, Any]:
return result
def call_subagent(agent_id: str, task: str, timeout: int = 120) -> Dict[str, Any]:
"""调用子agent(通过 OpenClaw sessions_spawn 或命令行)"""
print(f"\n{'='*50}")
print(f"调用子技能: {agent_id}")
print(f"{'='*50}")
# 尝试使用 sessions_spawn(OpenClaw 环境)
try:
from openclaw_tool import sessions_spawn
result = sessions_spawn(
agentId=agent_id,
task=task,
timeoutSeconds=timeout
)
print(f"\n子技能返回结果:")
print(json.dumps(result, ensure_ascii=False, indent=2))
return result
except ImportError:
# 回退到命令行调用
pass
# 命令行回退:调用子技能的脚本
print(f"使用命令行方式调用: {agent_id}")
# 技能目录路径
skills_path = Path(__file__).resolve().parent.parent
# 从任务中提取关键信息
import re
# 提取URL
url_match = re.search(r'URL: (\S+)', task)
url = url_match.group(1) if url_match else ""
# 提取输出目录
output_match = re.search(r'输出目录: (\S+)', task)
output_dir = output_match.group(1) if output_match else ""
# 提取输出文件名格式
filename_match = re.search(r'输出文件名格式: (\S+)', task)
filename_format = filename_match.group(1) if filename_match else "{platform}_{id}.json"
# 提取链接文件路径
link_file_match = re.search(r'链接文件: (\S+)', task)
link_file = link_file_match.group(1) if link_file_match else ""
# 提取元数据文件路径
meta_file_match = re.search(r'元数据文件: (\S+)', task)
meta_file = meta_file_match.group(1) if meta_file_match else ""
# kb-link-parser
if agent_id == "kb-link-parser":
cmd = ['python3', str(skills_path / "kb-link-parser" / "link-parser.py"), '--url', url]
try:
proc = subprocess.run(cmd, capture_output=True, text=True, timeout=timeout)
if proc.returncode == 0:
try:
data = json.loads(proc.stdout)
if data.get('success'):
platform = data.get('platform', 'unknown')
content_id = data.get('id', 'unknown')
ext = '.link.json'
filename = f"{platform}_{content_id}{ext}"
output_file = Path(output_dir) / filename
output_file.parent.mkdir(parents=True, exist_ok=True)
with open(output_file, 'w', encoding='utf-8') as f:
json.dump(data, f, ensure_ascii=False, indent=2)
print(f"保存文件: {output_file}")
return {"success": True, "output_file": str(output_file)}
else:
return {"success": False, "error": data.get('error', 'unknown')}
except json.JSONDecodeError:
return {"success": False, "error": f"解析失败: {proc.stdout[:200]}"}
else:
return {"success": False, "error": proc.stderr}
except Exception as e:
return {"success": False, "error": str(e)}
# kb-bilibili-metadata
elif agent_id == "kb-bilibili-metadata":
# 从链接文件或URL中提取BV号
bv = None
if link_file and Path(link_file).exists():
with open(link_file, 'r', encoding='utf-8') as f:
link_data = json.load(f)
bv = link_data.get('id')
if not bv:
bv_match = re.search(r'(BV[a-zA-Z0-9]+)', url or link_file)
bv = bv_match.group(1) if bv_match else None
if not bv:
return {"success": False, "error": "无法提取BV号"}
# 生成输出文件名
filename = f"bilibili_{bv}.meta.json"
output_file = Path(output_dir) / filename
output_file.parent.mkdir(parents=True, exist_ok=True)
cmd = [
'python3', str(skills_path / "kb-bilibili-metadata" / "bilibili_metadata.py"),
'--id', bv,
'--type', 'video',
'--output', str(output_file)
]
try:
proc = subprocess.run(cmd, capture_output=True, text=True, timeout=timeout)
if proc.returncode == 0:
print(f"保存文件: {output_file}")
return {"success": True, "output_file": str(output_file)}
else:
return {"success": False, "error": proc.stderr}
except Exception as e:
return {"success": False, "error": str(e)}
# kb-bilibili-content
elif agent_id == "kb-bilibili-content":
bv_match = re.search(r'(BV[a-zA-Z0-9]+)', url or meta_file)
bv = bv_match.group(1) if bv_match else None
if not bv:
return {"success": False, "error": "无法提取BV号"}
downloads_dir = Path(output_dir) / "downloads"
subtitles_dir = Path(output_dir) / "subtitles"
downloads_dir.mkdir(parents=True, exist_ok=True)
subtitles_dir.mkdir(parents=True, exist_ok=True)
video_file = None
subtitle_file = None
# 下载视频
cmd_video = [
'python3', str(skills_path / "kb-bilibili-content" / "bilibili_content.py"),
'--id', bv,
'--type', 'video',
'--output', output_dir
]
try:
proc = subprocess.run(cmd_video, capture_output=True, text=True, timeout=timeout)
if proc.returncode == 0:
# 查找生成的视频文件(可能包含BV号)
for f in Path(output_dir).iterdir():
if f.is_file() and bv in f.name and f.suffix in ['.flv', '.mp4']:
# 重命名为标准格式
new_name = f"bilibili_{bv}{f.suffix}"
new_path = downloads_dir / new_name
f.rename(new_path)
video_file = str(new_path)
break
except Exception as e:
print(f"视频下载警告: {e}")
# 下载字幕
cmd_subtitle = [
'python3', str(skills_path / "kb-bilibili-content" / "bilibili_content.py"),
'--id', bv,
'--type', 'subtitle',
'--output', output_dir
]
try:
proc = subprocess.run(cmd_subtitle, capture_output=True, text=True, timeout=timeout)
if proc.returncode == 0:
# 查找生成的字幕文件
for f in Path(output_dir).iterdir():
if f.is_file() and bv in f.name and f.suffix in ['.srt', '.lrc', '.ass']:
# 重命名为标准格式
new_name = f"bilibili_{bv}{f.suffix}"
new_path = subtitles_dir / new_name
f.rename(new_path)
subtitle_file = str(new_path)
break
except Exception as e:
print(f"字幕下载警告: {e}")
if video_file or subtitle_file:
return {"success": True, "output_file": video_file, "subtitles": subtitle_file}
else:
return {"success": False, "error": "下载未生成任何文件"}
# kb-ocr-processor
elif agent_id == "kb-ocr-processor":
# 查找字幕文件
subtitles_dir = Path(output_dir) / "subtitles"
subtitle_file = None
if subtitles_dir.exists():
for f in subtitles_dir.iterdir():
if f.suffix in ['.srt', '.lrc']:
subtitle_file = str(f)
break
if not subtitle_file:
return {"success": False, "error": "未找到字幕文件"}
# 生成输出文件名
text_file = Path(output_dir) / f"{Path(subtitle_file).stem}.txt"
cmd = [
'python3', str(skills_path / "kb-ocr-processor" / "ocr_processor.py"),
'--input', subtitle_file,
'--output', str(text_file)
]
try:
proc = subprocess.run(cmd, capture_output=True, text=True, timeout=timeout)
if proc.returncode == 0:
print(f"保存文件: {text_file}")
return {"success": True, "output_file": str(text_file)}
else:
return {"success": False, "error": proc.stderr}
except Exception as e:
return {"success": False, "error": str(e)}
# kb-deep-analyzer
elif agent_id == "kb-deep-analyzer":
# 生成输出文件名
meta_name = Path(meta_file).stem if meta_file else "unknown"
filename = f"{meta_name}.md"
output_file = Path(output_dir) / filename
output_file.parent.mkdir(parents=True, exist_ok=True)
# 从任务中提取文字内容文件路径
text_file_match = re.search(r'文字内容文件: (\S+)', task)
text_content_file = text_file_match.group(1) if text_file_match else ""
# 如果没有文字内容文件,使用 metadata 作为 content
content_file = meta_file
if text_content_file and Path(text_content_file).exists():
# 从文字文件创建 content JSON
content_json = {
"type": "transcript",
"source": text_content_file,
"text": Path(text_content_file).read_text(encoding='utf-8')[:10000] if Path(text_content_file).exists() else ""
}
content_file = Path(output_dir) / f"{meta_name}.content.json"
with open(content_file, 'w', encoding='utf-8') as f:
json.dump(content_json, f, ensure_ascii=False, indent=2)
cmd = [
'python3', str(skills_path / "kb-deep-analyzer" / "deep_analyzer.py"),
'--metadata', meta_file or output_dir,
'--content', str(content_file),
'--output', str(output_file)
]
try:
proc = subprocess.run(cmd, capture_output=True, text=True, timeout=timeout)
if proc.returncode == 0:
print(f"保存文件: {output_file}")
return {"success": True, "output_file": str(output_file)}
else:
return {"success": False, "error": proc.stderr}
except Exception as e:
return {"success": False, "error": str(e)}
return {"success": False, "error": f"暂未实现命令行回退: {agent_id}"}
def call_link_parser(url: str, pending_dir: Path) -> Dict[str, Any]:
"""调用 kb-link-parser"""
task = f"""解析以下URL,将结果保存到指定目录:
URL: {url}
输出目录: {pending_dir}
输出文件名格式: {{platform}}_{{id}}.link.json
请解析URL中的平台和内容ID,将解析结果保存为JSON文件。
返回结果时告诉我输出文件的完整路径。
只需要解析URL并保存结果,不需要下载内容。"""
return call_subagent(LINK_PARSER_AGENT, task, timeout=60)
def call_metadata_agent(platform: str, link_file: Path, metadata_dir: Path) -> Dict[str, Any]:
"""调用对应的元数据获取技能"""
agent_id = METADATA_AGENTS.get(platform)
if not agent_id:
return {"success": False, "error": f"不支持的平台: {platform}"}
task = f"""获取链接的元数据:
链接文件: {link_file}
输出目录: {metadata_dir}
请读取链接文件,提取URL,然后获取该链接的元数据(标题、作者、播放量等)。
将元数据保存为JSON文件,文件名格式: {{platform}}_{{id}}.meta.json
返回结果时告诉我输出文件的完整路径。"""
return call_subagent(agent_id, task, timeout=120)
def call_content_agent(platform: str, meta_file: Path, content_dir: Path) -> Dict[str, Any]:
"""调用对应的内容获取技能"""
agent_id = CONTENT_AGENTS.get(platform)
if not agent_id:
return {"success": False, "error": f"不支持的平台: {platform}"}
task = f"""下载视频内容:
元数据文件: {meta_file}
下载目录: {content_dir}
请读取元数据文件,获取视频信息,然后下载视频和字幕。
视频保存到: content/downloads/
字幕保存到: content/subtitles/
文件名格式: {{platform}}_{{id}}.mp4 和 {{platform}}_{{id}}.srt
返回结果时告诉我下载的视频文件和字幕文件的完整路径。"""
return call_subagent(agent_id, task, timeout=600)
def call_ocr_processor(source_file: Path, content_dir: Path, timeout: int = 1800) -> Dict[str, Any]:
"""调用 OCR 处理"""
task = f"""处理文件,提取文字内容:
源文件: {source_file}
输出目录: {content_dir}
请读取文件,提取文字内容。
输出文件名格式: {{platform}}_{{id}}.txt
返回结果时告诉我输出文件的完整路径。"""
return call_subagent(OCR_AGENT, task, timeout=timeout)
def call_deep_analyzer(meta_file: Path, text_file: Path, analyzed_dir: Path) -> Dict[str, Any]:
"""调用深度分析"""
task = f"""深度分析内容:
元数据文件: {meta_file}
文字内容文件: {text_file}
输出目录: {analyzed_dir}
请读取元数据和文字内容,进行深度分析。
生成分析报告,保存为Markdown文件。
文件名格式: {{platform}}_{{id}}.md
分析报告应包含:
- 一句话总结
- 核心要点
- 时间轴(如适用)
- 推荐标签
返回结果时告诉我输出文件的完整路径。"""
return call_subagent(ANALYZER_AGENT, task, timeout=180)
def archive_and_git(base_path: Path, analyzed_file: Path, git_root: Path, git_user: str, git_email: str, git_remote: str) -> Dict[str, Any]:
def archive_and_git(
analyzed_file: str,
base_path: Path = None,
git_root: Path = None,
git_user: str = None,
git_email: str = None,
git_remote: str = None
) -> Dict[str, Any]:
"""归档并提交Git"""
if base_path is None:
base_path = get_knowledge_base_path()
if git_root is None:
git_root = base_path / "archive"
if git_user is None:
git_user = os.environ.get('KB_GIT_USER', '')
if git_email is None:
git_email = os.environ.get('KB_GIT_EMAIL', '')
if git_remote is None:
git_remote = os.environ.get('KB_GIT_REMOTE', '')
result = {
"success": False,
"archive_path": "",
@@ -473,239 +142,124 @@ def archive_and_git(base_path: Path, analyzed_file: Path, git_root: Path, git_us
"error": None
}
# 1. 创建归档目录
date_str = datetime.now().strftime('%Y-%m-%d')
date_dir = base_path / "archive" / date_str
date_dir.mkdir(parents=True, exist_ok=True)
# 2. 复制文件到归档目录
archive_file = date_dir / analyzed_file.name
shutil.copy(analyzed_file, archive_file)
result["archive_path"] = str(archive_file)
# 3. 复制元数据
meta_file = base_path / "metadata" / f"{extract_base_name(analyzed_file.name)}.meta.json"
if meta_file.exists():
shutil.copy(meta_file, date_dir / meta_file.name)
# 4. Git操作
git_dir = git_root / ".git"
if not git_dir.exists():
subprocess.run(['git', 'init'], cwd=str(git_root), capture_output=True)
if git_user:
subprocess.run(['git', 'config', 'user.name', git_user], cwd=str(git_root))
if git_email:
subprocess.run(['git', 'config', 'user.email', git_email], cwd=str(git_root))
if (git_root / ".git").exists():
subprocess.run(['git', 'add', '.'], cwd=str(git_root), capture_output=True)
commit_msg = f"Archive: {analyzed_file.name} - {datetime.now().isoformat()}"
commit_result = subprocess.run(
['git', 'commit', '-m', commit_msg],
cwd=str(git_root), capture_output=True, text=True
)
result["git_commit"] = commit_result.returncode == 0
if git_remote and commit_result.returncode == 0:
push_result = subprocess.run(
['git', 'push', 'origin', 'master'],
cwd=str(git_root), capture_output=True, text=True, timeout=60
)
result["git_push"] = {"success": push_result.returncode == 0}
result["success"] = True
return result
def process_url(url: str, base_path: Path = None) -> Dict[str, Any]:
"""处理单个URL的完整流程"""
if not base_path:
base_path = Path.home() / "work" / "knowledge-base"
git_root = os.environ.get('KB_GIT_ROOT', str(base_path / 'archive'))
git_user = os.environ.get('KB_GIT_USER', '')
git_email = os.environ.get('KB_GIT_EMAIL', '')
git_remote = os.environ.get('KB_GIT_REMOTE', '')
dirs = ensure_directories(base_path)
result = {
"url": url,
"success": False,
"stages": [],
"final_file": None,
"archive": None,
"error": None
}
try:
# 查重
print(f"\n{'='*50}")
print(f"步骤1: 查重")
print(f"{'='*50}")
# 1. 创建归档目录
date_str = datetime.now().strftime('%Y-%m-%d')
date_dir = base_path / "archive" / date_str
date_dir.mkdir(parents=True, exist_ok=True)
dup_result = check_duplicate(base_path, url)
if dup_result["duplicate"]:
result["error"] = f"已存在: {dup_result['status']}"
result["duplicate"] = True
result["existing_files"] = dup_result["files"]
return result
# 2. 复制分析报告
src_file = Path(analyzed_file)
archive_file = date_dir / src_file.name
shutil.copy(src_file, archive_file)
result["archive_path"] = str(archive_file)
# kb-link-parser
print(f"\n{'='*50}")
print(f"步骤2: 链接解析 (kb-link-parser)")
print(f"{'='*50}")
# 3. 复制元数据
meta_file = base_path / "metadata" / f"{src_file.stem}.meta.json"
if meta_file.exists():
shutil.copy(meta_file, date_dir / meta_file.name)
link_result = call_link_parser(url, dirs["pending"])
if not link_result.get("success"):
result["error"] = f"链接解析失败: {link_result.get('error')}"
return result
# 4. Git 操作
git_dir = git_root / ".git"
if not git_dir.exists():
subprocess.run(['git', 'init'], cwd=str(git_root), capture_output=True)
if git_user:
subprocess.run(['git', 'config', 'user.name', git_user], cwd=str(git_root))
if git_email:
subprocess.run(['git', 'config', 'user.email', git_email], cwd=str(git_root))
link_file = link_result.get("output_file")
if not link_file:
result["error"] = "链接解析未返回输出文件"
return result
link_file = Path(link_file)
result["stages"].append({"stage": "link_parsing", "file": str(link_file)})
# 提取平台
filename = link_file.name
platform = extract_platform(filename)
content_id = extract_base_name(filename)
print(f"\n平台: {platform}")
print(f"内容ID: {content_id}")
# 元数据
print(f"\n{'='*50}")
print(f"步骤3: 元数据提取 ({METADATA_AGENTS.get(platform, 'unknown')})")
print(f"{'='*50}")
meta_result = call_metadata_agent(platform, link_file, dirs["metadata"])
if not meta_result.get("success"):
result["error"] = f"元数据获取失败: {meta_result.get('error')}"
return result
meta_file = meta_result.get("output_file")
if not meta_file:
result["error"] = "元数据获取未返回输出文件"
return result
meta_file = Path(meta_file)
result["stages"].append({"stage": "metadata", "file": str(meta_file)})
# 内容下载
print(f"\n{'='*50}")
print(f"步骤4: 内容下载 ({CONTENT_AGENTS.get(platform, 'unknown')})")
print(f"{'='*50}")
content_result = call_content_agent(platform, meta_file, dirs["content"])
if not content_result.get("success"):
result["error"] = f"内容下载失败: {content_result.get('error')}"
return result
video_file = content_result.get("output_file")
subtitle_file = content_result.get("subtitle") or content_result.get("subtitles")
result["stages"].append({"stage": "content", "video": video_file, "subtitles": subtitle_file})
# OCR
text_file = None
print(f"\n{'='*50}")
print(f"步骤5: OCR处理 (kb-ocr-processor)")
print(f"{'='*50}")
# 无论有没有字幕,都尝试OCR处理
ocr_source = subtitle_file
if not ocr_source and video_file:
ocr_source = video_file
if ocr_source:
# OCR超时设置为30分钟
ocr_result = call_ocr_processor(Path(ocr_source), dirs["content"], timeout=1800)
text_file = ocr_result.get("output_file") if ocr_result.get("success") else None
if (git_root / ".git").exists():
subprocess.run(['git', 'add', '.'], cwd=str(git_root), capture_output=True)
commit_msg = f"Archive: {src_file.name} - {datetime.now().isoformat()}"
commit_result = subprocess.run(
['git', 'commit', '-m', commit_msg],
cwd=str(git_root), capture_output=True, text=True
)
result["git_commit"] = commit_result.returncode == 0
if text_file:
result["stages"].append({"stage": "ocr", "file": text_file})
else:
print(f"OCR处理未生成文件")
else:
print(f"无字幕文件,跳过OCR处理")
if git_remote and commit_result.returncode == 0:
push_result = subprocess.run(
['git', 'push', 'origin', 'master'],
cwd=str(git_root), capture_output=True, text=True, timeout=60
)
result["git_push"] = {"success": push_result.returncode == 0}
# 深度分析
print(f"\n{'='*50}")
print(f"步骤6: 深度分析 (kb-deep-analyzer)")
print(f"{'='*50}")
analyze_result = call_deep_analyzer(
meta_file,
Path(text_file) if text_file else meta_file,
dirs["analyzed"]
)
if not analyze_result.get("success"):
result["error"] = f"深度分析失败: {analyze_result.get('error')}"
return result
analyzed_file = analyze_result.get("output_file")
if not analyzed_file:
result["error"] = "深度分析未返回输出文件"
return result
analyzed_file = Path(analyzed_file)
result["stages"].append({"stage": "analyzer", "file": str(analyzed_file)})
result["final_file"] = str(analyzed_file)
# 归档和Git
print(f"\n{'='*50}")
print(f"步骤7: 归档和Git")
print(f"{'='*50}")
archive_result = archive_and_git(
base_path, analyzed_file,
Path(git_root), git_user, git_email, git_remote
)
result["archive"] = archive_result
result["success"] = True
print(f"\n{'='*50}")
print(f"处理完成!")
print(f"{'='*50}")
except Exception as e:
result["error"] = str(e)
import traceback
traceback.print_exc()
return result
def generate_summary(url: str, stages: List[Dict], final_file: str, archive_result: Dict = None) -> str:
"""生成处理完成汇报"""
# 提取视频标题(如果有)
title_match = re.search(r'com/video/([^?]+)', url)
title = title_match.group(1) if title_match else "未知"
summary = f"""
✅ **处理完成!**
**视频:** {title}
**处理阶段:**
"""
for stage in stages:
stage_name = stage.get('stage', 'unknown')
emoji = "✓" if stage.get('success') else "○"
summary += f"{emoji} {stage_name}\n"
if final_file:
summary += f"\n**最终文件:** `{final_file}`"
if archive_result:
if archive_result.get('git_commit'):
summary += f"\n**Git:** 已提交"
if archive_result.get('git_push', {}).get('success'):
summary += " ✓"
elif archive_result.get('git_push'):
summary += " ✗"
return summary
# ==================== CLI ====================
def main():
"""CLI入口"""
"""CLI入口 - 用于命令行测试"""
parser = argparse.ArgumentParser(
description='KB Workflow - Knowledge Base Workflow Orchestrator',
formatter_class=argparse.RawDescriptionHelpFormatter
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog="""
使用示例:
# 查重
python kb_workflow.py --check --url "https://www.bilibili.com/video/BVxxx"
# 归档
python kb_workflow.py --archive "/path/to/analyzed.md"
"""
)
parser.add_argument('--url', type=str, help='要处理的URL')
parser.add_argument('--check', action='store_true', help='查重')
parser.add_argument('--url', type=str, help='要检查的URL')
parser.add_argument('--archive', type=str, help='要归档的文件路径')
parser.add_argument('--base-path', type=str, help='知识库根目录')
args = parser.parse_args()
if not args.url:
print("请提供URL: --url https://...")
sys.exit(1)
base_path = Path(args.base_path) if args.base_path else None
result = process_url(args.url, base_path)
print(f"\n{'='*50}")
print("KB Workflow Result")
print(f"{'='*50}")
print(json.dumps(result, ensure_ascii=False, indent=2, default=str))
if args.check and args.url:
result = check_duplicate(base_path, args.url)
print(json.dumps(result, ensure_ascii=False, indent=2))
sys.exit(0 if result.get('success') else 1)
elif args.archive:
result = archive_and_git(args.archive, base_path)
print(json.dumps(result, ensure_ascii=False, indent=2))
else:
parser.print_help()
if __name__ == '__main__':