#!/usr/bin/env python3 """Compile reviewed storyboard into production inputs; never generate or submit media.""" from pathlib import Path import csv import hashlib import json import re ROOT = Path(__file__).resolve().parents[1] SOURCE = ROOT / 'cinematic-storyboard-v2.md' OUT = ROOT / 'assembly' OUT.mkdir(exist_ok=True) text = SOURCE.read_text() source_hash = hashlib.sha256(SOURCE.read_bytes()).hexdigest() rows = {'user': [], 'channel': []} section = None for line in text.splitlines(): if line.startswith('## 3. 用户片'): section = 'user' elif line.startswith('## 4. 渠道片'): section = 'channel' elif line.startswith('## 5.'): section = None if section and re.match(r'^\| \d{2}:\d{2}–\d{2}:\d{2} \|', line): cells = [x.strip() for x in line.split('|')[1:-1]] assert len(cells) == 5, cells start, end = cells[0].split('–') sec = lambda v: sum(int(n) * m for n, m in zip(v.split(':'), [60, 1])) idx = len(rows[section]) + 1 rows[section].append({ 'id': ('U' if section == 'user' else 'C') + f'{idx:02}', 'slot_start': sec(start), 'slot_end': sec(end), 'slot_seconds': int(cells[1]), 'visual_direction': cells[2], 'voiceover': cells[3], 'evidence_boundary': cells[4], 'voice_status': 'not_recorded', 'picture_status': 'not_ready', 'source_sha256': source_hash, }) dependencies = { 'U01':['G01','P01'], 'U02':['P01','P02','P03'], 'U03':['P04'], 'U04':['P05'], 'U05':['G02','G03','G04','P06'], 'U06':['G05','P07'], 'U07':['G02','P08'], 'U08':['P09','P10'], 'U09':['G04','B01'], 'C01':['G06'], 'C02':['P01','P02','B02'], 'C03':['P04','B03'], 'C04':['P02','P05','P06','P08'], 'C05':['G06'], 'C06':['M01'], 'C07':['M02'], 'C08':['P11','M03'], 'C09':['G06','M04'], 'C10':['B01','P01'], } asset_specs = { 'G01':('清晨生活镜头','generative_broll','cloud_access_or_quota','生活演绎；不能替代设备/报告证据'), 'G02':('普通一餐','generative_broll','cloud_access_or_quota','无营养数值、品牌或疗效前后对比'), 'G03':('外食场景','generative_broll','cloud_access_or_quota','无可识别菜单/手机UI/个人信息'), 'G04':('普通步行','generative_broll','cloud_access_or_quota','非训练指导或消耗测量'), 'G05':('加班后调整安排','generative_broll','cloud_access_or_quota','匿名虚构成年人，无屏幕工作内容'), 'G06':('服务交流情境','generative_broll','cloud_access_or_quota','明确演绎，不是客户证言或签约证据'), 'P01':('设备外观和操作','real_capture','capture_and_rights_review','产品外观不能生成变形，人物获许可'), 'P02':('同会话领取和查看','screen_capture','current_build_verification','同一演示用户/设备/会话，不能拼成假联通'), 'P03':('无设备手机开始','screen_or_concept','capability_verification','未开放时标体验示意且同步限定旁白'), 'P04':('来源/时间/报告解释','screen_or_concept','capability_verification','不展示真实健康数值，示例标识明确'), 'P05':('目标确认与一致性','screen_or_concept','capability_verification','当前目标与后续吃动建议相符'), 'P06':('今日行动与选择','screen_or_concept','capability_verification','可执行资源真实，未实现则标体验示意'), 'P07':('反馈困难后调整','screen_or_concept','capability_verification','用户确认后才改变计划；不得假称已上线'), 'P08':('实际执行确认','screen_or_concept','capability_verification','订单/取餐/实吃分开，未知不补零'), 'P09':('周复盘','screen_or_concept','capability_verification','行为进展不是健康疗效'), 'P10':('复测与可比记录','real_capture','capture_and_professional_review','同条件可比，不编造改善'), 'P11':('安装培训与验收','real_capture','capture_and_delivery_scope','不用生成视频当真实交付证明'), 'B01':('品牌与最终CTA','approved_brand','brand_and_entry_review','无假二维码；只用批准Logo/入口'), 'B02':('可选原装SKU','approved_product','sku_and_policy_review','未审核的包装和价格不入片'), 'B03':('专业知识与规则依据','approved_evidence','professional_and_brand_review','不将知识库称专有基础模型训练'), 'M01':('收益与成本关系图','motion_graphic','channel_policy_review','无未核金额/保证收益'), 'M02':('渠道门店个人分工','motion_graphic','channel_policy_review','同笔订单不重复计益'), 'M03':('交付责任分工','motion_graphic','delivery_scope_review','不承诺免费/无限服务'), 'M04':('一店验证步骤','motion_graphic','reviewed_design','无虚假试点数据'), } manifest=[] for film, expected, length in [('user', 9, 150), ('channel', 10, 180)]: shots = rows[film] assert len(shots) == expected cursor=0 film_dir=OUT/film film_dir.mkdir(exist_ok=True) narration=[] for shot in shots: assert shot['slot_start'] == cursor assert shot['slot_end'] - shot['slot_start'] == shot['slot_seconds'] cursor=shot['slot_end'] shot['requires'] = dependencies[shot['id']] shot['voice_file'] = f"voice/{shot['id']}.wav" shot['voice_file_exists'] = False shot['timing_basis']='reviewed_scene_slot_not_recorded_audio' (film_dir/f"{shot['id']}-voice.txt").write_text(shot['voiceover']+'\n') narration.append(shot['voiceover']) manifest.append({'film':film, 'shot_id':shot['id'], 'start_seconds':shot['slot_start'], 'end_seconds':shot['slot_end'], 'duration_seconds':shot['slot_seconds'], 'required_assets':';'.join(shot['requires']), 'picture_status':'not_ready', 'voice_status':'not_recorded','public_release':'blocked_pending_evidence'}) assert cursor==length (film_dir/'narration.txt').write_text('\n\n'.join(narration)+'\n') (film_dir/'timeline.json').write_text(json.dumps({'film':film,'duration_seconds':length, 'width':1080 if film=='user' else 1920,'height':1920 if film=='user' else 1080, 'fps':30,'state':'assembly_inputs_only_not_a_film','source':'../../cinematic-storyboard-v2.md', 'source_sha256':source_hash,'shots':shots},ensure_ascii=False,indent=2)+'\n') with (OUT/'shot-readiness.csv').open('w',newline='') as f: w=csv.DictWriter(f,fieldnames=manifest[0]);w.writeheader();w.writerows(manifest) with (OUT/'asset-requirements.csv').open('w',newline='') as f: w=csv.writer(f);w.writerow(['asset_id','name','type','blocking_condition','claim_boundary','used_by']) for key,(name,typ,block,boundary) in asset_specs.items(): used=';'.join(s for s,ids in dependencies.items() if key in ids) assert used,key w.writerow([key,name,typ,block,boundary,used]) for deps in dependencies.values(): assert all(x in asset_specs for x in deps) report={'films':2,'shots':len(manifest),'asset_requirements':len(asset_specs), 'durations':{'user':150,'channel':180},'recorded_voice_tracks':0, 'generated_broll_assets':0,'new_generation_submissions':0,'ready_final_films':0, 'timeline_continuity':'passed','asset_references':'passed','source_sha256':source_hash} (OUT/'validation.json').write_text(json.dumps(report,ensure_ascii=False,indent=2)+'\n') print(json.dumps(report,ensure_ascii=False))