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kb-skills/kb_workflow/pipeline/processors/archive.py
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starmen1265 4d2645876b
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fix(srt): add disable_reasoning parameter for ASR correction and include title in archive filename
- SimpleAIClient: Add disable_reasoning parameter to control AI thinking mode
- ASRCorrector: Use disable_reasoning=True to get direct correction results
- ArchiveProcessor: Extract title from frontmatter and include in filename

File naming format: {YYYYMMDD}_{content_id}_{title}_analysis.md

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-21 22:19:14 +08:00

250 lines
8.8 KiB
Python

"""ArchiveProcessor - Copy analysis reports to archive directory
Final step in pipeline that copies the generated analysis.md
to the archive directory organized by platform.
"""
from __future__ import annotations
import logging
import re
import shutil
from datetime import datetime
from pathlib import Path
from typing import Optional
from kb_workflow.pipeline.config import get_settings
from kb_workflow.pipeline.schemas import ArchiveInput, ArchiveOutput
from kb_workflow.pipeline.state import WorkflowStateManager
from kb_workflow.pipeline.processors.base import BaseProcessor
logger = logging.getLogger(__name__)
class ArchiveProcessor(BaseProcessor):
"""Archive 处理器 - 归档分析报告
处理流程:
1. 检查步骤是否已完成(幂等执行)
2. 检查归档目录是否存在相同 content_id 的文件
3. 如果存在重复,询问用户是否覆盖
4. 复制 md 文件到归档目录
5. 记录处理状态到 workflow_state.json
归档目录结构:
{KB_ARCHIVE_PATH}/{platform}/{YYYYMMDD}_{content_id}_analysis.md
"""
STEP_NAME = "archive"
async def process(self, input_data: ArchiveInput) -> ArchiveOutput:
"""执行归档处理
Args:
input_data: Archive 输入数据
Returns:
Archive 处理结果
"""
try:
import sys
# Step 1: 检查是否已完成(幂等执行)
if self.state_manager:
state = self.state_manager.load()
if state and state.is_step_completed(self.STEP_NAME):
logger.info(f"Step {self.STEP_NAME} already completed, skipping")
return ArchiveOutput(
success=True,
skipped=True,
platform=input_data.platform,
archive_file=""
)
# Step 2: 准备归档路径
archive_base = Path(self.settings.archive_path)
platform_dir = archive_base / input_data.platform
platform_dir.mkdir(parents=True, exist_ok=True)
# 从源文件中提取标题(用于文件命名)
title = self._extract_title_from_file(Path(input_data.analysis_file))
# 清理标题:移除特殊字符,限制长度
safe_title = self._sanitize_title(title) if title else input_data.content_id
# 文件命名: {YYYYMMDD}_{content_id}_{title}_analysis.md
timestamp = datetime.now().strftime("%Y%m%d")
archive_filename = f"{timestamp}_{input_data.content_id}_{safe_title}_analysis.md"
archive_path = platform_dir / archive_filename
# Step 3: 检查重复
existing_file = self._find_existing_archive(
platform_dir, input_data.content_id
)
if existing_file:
# 检测是否为非交互式环境
is_non_interactive = not sys.stdin.isatty()
should_overwrite = self._ask_overwrite(existing_file, is_non_interactive)
if not should_overwrite:
logger.info(f"User chose not to overwrite, skipping archive")
return ArchiveOutput(
success=True,
skipped=True,
platform=input_data.platform,
archive_file=str(existing_file)
)
# 删除旧文件
existing_file.unlink()
logger.info(f"Removed existing archive: {existing_file}")
# Step 4: 复制文件
source_path = Path(input_data.analysis_file)
if not source_path.exists():
raise FileNotFoundError(f"Analysis file not found: {source_path}")
shutil.copy2(source_path, archive_path)
logger.info(f"Archived: {source_path} -> {archive_path}")
# Step 5: 记录成功状态
if self.state_manager:
state = self.state_manager.load()
if state:
state.mark_step_completed(
self.STEP_NAME,
f"archived to {archive_path}"
)
self.state_manager.save(state)
return ArchiveOutput(
success=True,
skipped=False,
platform=input_data.platform,
archive_file=str(archive_path)
)
except Exception as e:
logger.error(f"Archive failed: {e}")
if self.state_manager:
state = self.state_manager.load()
if state:
state.mark_step_failed(self.STEP_NAME, str(e))
self.state_manager.save(state)
return ArchiveOutput(
success=False,
error_message=str(e),
platform=input_data.platform,
archive_file=""
)
def _find_existing_archive(self, platform_dir: Path, content_id: str) -> Optional[Path]:
"""查找已存在的归档文件
使用 glob 模式 `*_{content_id}_analysis.md` 搜索
Args:
platform_dir: 平台目录路径
content_id: 内容 ID
Returns:
已存在的文件路径,如果不存在返回 None
"""
pattern = f"*_{content_id}_analysis.md"
matches = list(platform_dir.glob(pattern))
return matches[0] if matches else None
def _extract_title_from_file(self, file_path: Path) -> Optional[str]:
"""从 Markdown 文件的 frontmatter 中提取标题
Args:
file_path: Markdown 文件路径
Returns:
标题字符串,如果未找到返回 None
"""
try:
content = file_path.read_text(encoding='utf-8')
# 查找 frontmatter 中的 title 字段
# 格式:title: "标题内容" 或 title: 标题内容
title_match = re.search(r'^title:\s*(?:"([^"]*)"|(.+))$', content, re.MULTILINE)
if title_match:
# 优先使用引号内的内容,否则使用第二个捕获组
title = title_match.group(1) or title_match.group(2)
return title.strip() if title else None
return None
except Exception as e:
logger.warning(f"Failed to extract title from {file_path}: {e}")
return None
def _sanitize_title(self, title: str) -> str:
"""清理标题用于文件命名
移除特殊字符,限制长度,转换为安全的文件名。
Args:
title: 原始标题
Returns:
清理后的标题
"""
# 移除或替换不适合文件名的字符
# 保留中文、字母、数字、下划线、连字符
# 替换所有特殊字符(包括标点符号和常见符号)
safe = re.sub(r'[\\/:*?"<>|,。!?、;:""\'\'\s@#$%&*+\-=\[\]{}()<>]+', '_', title)
# 移除连续的下划线
safe = re.sub(r'_+', '_', safe)
# 去除首尾下划线和空格
safe = safe.strip('_')
# 限制长度(避免文件名过长)
if len(safe) > 50:
safe = safe[:50]
# 如果清理后为空,返回默认值
if not safe:
safe = "untitled"
return safe
def _ask_overwrite(self, existing_file: Path, is_non_interactive: bool = False) -> bool:
"""询问用户是否覆盖已存在的文件
使用 rich.prompt.Confirm 模式(与 Pipeline._ask_rerun_step 相同)
Args:
existing_file: 已存在的文件路径
is_non_interactive: 是否为非交互式环境(stdin不是tty)
Returns:
True 如果用户选择覆盖
"""
# 非交互式模式:使用配置决定
if is_non_interactive:
if self.settings.overwrite_archives:
logger.info(f"Non-interactive mode: Overwriting existing archive (KB_OVERWRITE_ARCHIVES=true): {existing_file.name}")
return True
else:
logger.info(f"Non-interactive mode: Skipping existing archive (KB_OVERWRITE_ARCHIVES=false): {existing_file.name}")
return False
# 交互式模式:询问用户
try:
from rich.console import Console
from rich.prompt import Confirm
console = Console()
return Confirm.ask(
f"Archive already exists: {existing_file.name}\nOverwrite?",
default=False
)
except ImportError:
response = input(
f"Archive already exists: {existing_file.name}\nOverwrite? [y/N] "
)
return response.lower() in ('y', 'yes')