kb-skills/.planning/phases/03-processing-skills/03-01-VERIFICATION.md

phase, verified, status, score

phase	verified	status	score
03-processing-skills	2026-03-13T19:30:00Z	passed	6/6 must-haves verified

Phase 3: Processing Skills Verification Report

Phase Goal: 创建 ASRProcessor 处理器，统一封装 B站官方字幕下载和 Whisper.cpp 语音识别，遵循 Phase 1/2 建立的管道模式。 Verified: 2026-03-13T19:30:00Z Status: passed Re-verification: No - initial verification

Goal Achievement

Observable Truths

#	Truth	Status	Evidence
1	B站视频可以自动下载官方字幕	VERIFIED	_try_official_subtitle() method (lines 163-289) implements B站 API calls for pagelist, player/v2, and subtitle download with SRT/TXT/JSON output generation
2	无官方字幕时自动调用 Whisper.cpp 进行语音识别	VERIFIED	process() method (lines 114-161) first tries subtitle, then calls _run_whisper() if result is None; _run_whisper_basic() (lines 336-394) implements Whisper.cpp integration
3	HF_TOKEN 配置时自动启用说话者分离	VERIFIED	_run_whisper() (lines 319-334) checks self.settings.hf_token.get_secret_value() and routes to _run_whisper_with_diarization() if token present
4	输出包含 txt/srt/json 三种格式	VERIFIED	Both _try_official_subtitle() (lines 180-182, 257-271) and _parse_whisper_output() (lines 406-447) generate all three formats in output_files dict
5	ASR 完成后状态记录到 workflow_state.json	VERIFIED	process() method (lines 143-150, 156-160) calls state.mark_step_completed() on success and state.mark_step_failed() on failure, with proper state_manager.save()
6	临时音频文件处理后自动清理	VERIFIED	_run_whisper_basic() finally block (lines 388-394) removes temp audio file with os.remove(audio_path)

Score: 6/6 truths verified

Required Artifacts

Artifact	Expected	Status	Details
kb_pipeline/processors/__init__.py	Exports ASRProcessor	VERIFIED	9 lines, exports ASRProcessor in __all__
kb_pipeline/processors/asr.py	ASRProcessor class, min 150 lines	VERIFIED	575 lines, contains class ASRProcessor with full implementation
kb_pipeline/schemas.py	ASRInput, ASROutput classes	VERIFIED	Lines 194-235 define both schemas with correct inheritance and fields
tests/test_processors/__init__.py	Test module init	VERIFIED	Exists, contains docstring
tests/test_processors/conftest.py	Test fixtures	VERIFIED	97 lines with all required fixtures
tests/test_processors/test_asr.py	All test cases	VERIFIED	619 lines, 22 tests (25 collected including parametrized)

Key Link Verification

From	To	Via	Status	Details
kb_pipeline/processors/asr.py	kb_pipeline/schemas.py	from ..schemas import ASRInput, ASROutput	WIRED	Line 25 imports both schemas
kb_pipeline/processors/asr.py	kb_pipeline/state.py	WorkflowStateManager	WIRED	Line 26 imports, lines 144-150 and 156-160 use state_manager
kb_pipeline/processors/asr.py	kb_pipeline/config.py	get_settings	WIRED	Line 24 imports, line 111 uses for hf_token access

Requirements Coverage

No requirement IDs were declared in PLAN frontmatter (Phase 3 has no direct REQUIREMENTS.md entries - platform support was covered in Phase 2).

Orphaned Requirements: None

Anti-Patterns Found

File	Line	Pattern	Severity	Impact
None	-	-	-	No blocking anti-patterns detected

Notes:

• return None statements in _try_official_subtitle() are intentional - they signal "no subtitle available" to trigger Whisper fallback
• pass in WhisperNotFoundError class is standard exception class definition

Test Results

tests/test_processors/test_asr.py: 22 passed in 0.24s

Test Categories:
- Schema Tests: 8 passed (ASRInput, ASROutput validation)
- Processor Init Tests: 2 passed
- Official Subtitle Tests: 3 passed (found, not found, priority)
- Whisper Basic Tests: 3 passed (basic, cleanup, path error)
- Diarization Tests: 3 passed (no token, with token, result format)
- State Recording Tests: 3 passed (success, failure, no manager)

Human Verification Required

The following items require manual testing in a real environment:

1. End-to-end B站视频处理

   • Test: Run ASRProcessor on an actual B站 video with official subtitles
   • Expected: Subtitles downloaded and converted to txt/srt/json
   • Why human: Requires real B站 API access and network

2. Whisper.cpp 端到端测试

   • Test: Process a video without official subtitles using actual whisper.cpp
   • Expected: Whisper generates transcription with all output formats
   • Why human: Requires whisper.cpp installation and model download

3. 说话者分离功能测试

   • Test: Process video with HF_TOKEN configured
   • Expected: pyannote.audio performs diarization, segments include speaker labels
   • Why human: Requires HF_TOKEN and pyannote.audio installation

Summary

Phase 3 Processing Skills verification completed successfully.

All 6 must-haves are verified:

1. B站官方字幕自动下载 - VERIFIED (API integration complete)
2. Whisper.cpp 回退机制 - VERIFIED (conditional logic correct)
3. HF_TOKEN 说话者分离 - VERIFIED (auto-detection implemented)
4. 三格式输出 - VERIFIED (txt/srt/json generation in both paths)
5. 状态记录 - VERIFIED (workflow_state.json integration)
6. 临时文件清理 - VERIFIED (finally block cleanup)

The implementation follows the established pipeline pattern from Phase 1/2:

• Inherits from StepInput/StepOutput schemas
• Uses WorkflowStateManager for state recording
• Proper error handling with mark_step_failed
• Clean code structure with 575 lines, no blocking anti-patterns

All 22 automated tests pass. Manual testing recommended for end-to-end validation with real API calls and whisper.cpp execution.

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Verified: 2026-03-13T19:30:00Z Verifier: Claude (gsd-verifier)