feat(core): 故事板/视频提示词改用户钦定 @图N 模板拼装
故事板:撤『分镜表』回『一镜=一张导演故事板』;refs 版出【设定】@图N是角色/商品/场景 + 导演故事板指令 + 【分镜脚本】(本段约X秒) + 该镜脚本;_storyboard_reference_images 按 角色→商品→场景 排序,@图N 与 image_edit 传图顺序锁死。视频:_video_reference_images 收齐 角色/场景/商品 基础资产 + 本镜故事板帧(四类带类型,角色→场景→商品→分镜图);build_video_segment_prompt 出【设定】@图N…【分镜】根据@图N分镜图…【脚本】该镜脚本;submit_video_segment 传图顺序与 @图N 对齐。新增 _segment_script_text 复用。 Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
seaislee1209
co-authored by
Claude Opus 4.8
Claude Opus 4.8
parent
016c859004
commit
edaa314261
@@ -676,48 +676,59 @@ def _scene_context(project) -> str:
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return " · ".join(parts)
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def build_storyboard_frame_prompt(project, version, segment) -> str:
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"""单场故事板提示词:把这一「场」拆成多个分镜,排成一张竖屏【分镜表】。
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用户要的结构是「一场 = 一个故事板,内含多个分镜图(不同景别/运镜)」,而非一场一张大图。"""
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visual = (segment.visual_prompt or segment.narration or "").strip()
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dur = segment.duration_seconds or 15
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sub = max(2, min(4, round(dur / 5))) # 按本场时长估分镜数:15s≈3 格
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lines = [
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_scene_context(project),
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f"生成一张竖屏【分镜故事板表】:把第 {segment.sort_order + 1} 场(约 {dur} 秒)拆成 {sub} 个分镜,"
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f"从上到下纵向排成 {sub} 个等宽分格,格与格之间用细线或留白分隔,每格角落标注分镜序号、景别与时长。",
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]
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def _segment_script_text(segment) -> str:
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"""本镜脚本文本(画面 + 口播/旁白 + 商品露出),拼进故事板/视频提示词的【分镜脚本】。"""
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parts = []
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visual = (segment.visual_prompt or "").strip()
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if visual:
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lines.append(f"本场画面:{visual}")
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if segment.narration:
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lines.append(f"台词/口播:{segment.narration.strip()}")
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if segment.product_exposure:
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lines.append(f"商品露出方式:{segment.product_exposure.strip()}")
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lines.append(
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"各分镜要体现不同景别与运镜(如 中景固定 → 特写微距 → 全景跟拍),镜头连贯,"
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"同一人物保持同一张脸、同一商品保持外观与配色一致。"
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)
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parts.append(f"画面:{visual}")
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narration = (segment.narration or "").strip()
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if narration:
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parts.append(f"口播/旁白:{narration}")
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if getattr(segment, "product_exposure", ""):
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parts.append(f"商品露出:{segment.product_exposure.strip()}")
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return "\n".join(parts)
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def build_storyboard_frame_prompt(project, version, segment) -> str:
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"""单镜导演故事板提示词(一镜 = 一张导演故事板,用户钦定结构)。无参考图时的文本版。"""
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dur = segment.duration_seconds or 15
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lines = [
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"根据以下脚本生成一个导演故事板,用于指导 seedance 的视频生成。",
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_scene_context(project),
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f"【分镜脚本】(本段时长约 {dur} 秒)",
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_segment_script_text(segment) or f"第 {segment.sort_order + 1} 镜",
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]
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if version.prompt:
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lines.append(version.prompt.strip())
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lines.append("真实清新、生活化的电商带货分镜表,竖屏 9:16,排版工整,画面清晰,可直接指导视频生成。")
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lines.append("电商竖屏 9:16 导演故事板,真实清新、生活化,画面清晰,可直接指导视频生成。")
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return "\n".join(line for line in lines if line)
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def build_video_segment_prompt(project, video_segment, scene, user_prompt: str) -> str:
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"""单段视频提示词:把本镜旁白 + 画面 + 风格锚点织进去,让每个视频片段跟住对应脚本/故事板。"""
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lines = [_scene_context(project)]
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if scene is not None:
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if scene.narration:
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lines.append(f"旁白:{scene.narration.strip()}")
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visual = (scene.visual_prompt or scene.narration or "").strip()
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if visual:
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lines.append(f"画面:{visual}")
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if user_prompt:
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lines.append(user_prompt.strip())
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lines.append(
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f"第 {video_segment.sort_order + 1} 段 · {video_segment.target_duration_seconds}s · "
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"9:16 竖屏电商带货短视频,镜头稳定,商品露出清晰,节奏有转化感"
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)
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def build_video_segment_prompt(project, video_segment, scene, refs, user_prompt: str = "") -> str:
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"""单段视频提示词(用户钦定 @图N 格式):
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【设定】@图N 点名 角色/场景/商品;【分镜】根据 @图(分镜图) 生成;【脚本】本镜脚本。
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refs 顺序与传给 seedance 的 reference_images 一致(@图N 对齐不错位)。"""
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product_name = (getattr(project.product, "title", "") or "商品").strip()
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setup_parts = []
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storyboard_idx = None
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for i, r in enumerate(refs or []):
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n = i + 1
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if r.get("type") == "storyboard":
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storyboard_idx = n
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else:
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setup_parts.append(f"@图{n}是{r.get('label') or ''}({_ENTITY_TYPE_CN.get(r.get('type'), '参考')})")
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lines = []
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if setup_parts:
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lines.append("【设定】" + "，".join(setup_parts) + "。")
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if storyboard_idx is not None:
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lines.append(f"【分镜】根据@图{storyboard_idx}分镜图生成「{product_name}」短视频。")
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script_text = _segment_script_text(scene) if scene is not None else ""
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extra = (user_prompt or "").strip()
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if extra:
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script_text = (script_text + "\n" + extra).strip() if script_text else extra
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lines.append("【脚本】" + (script_text or f"第 {video_segment.sort_order + 1} 段"))
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lines.append(f"{video_segment.target_duration_seconds}s · 9:16 竖屏电商带货短视频,镜头稳定,商品露出清晰,节奏有转化感。")
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return "\n".join(line for line in lines if line)
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@@ -780,22 +791,32 @@ def _storyboard_reference_images(project, segment) -> list[dict]:
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url = _asset_preview_url(pg.adopted_asset)
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if url:
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out.append({"url": url, "label": "商品", "type": "product"})
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# 规范 @图N 顺序:角色 → 商品 → 场景(与下游 image_edit 传图顺序一致,标注不错位)
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_ord = {"character": 0, "product": 1, "scene": 2}
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out.sort(key=lambda r: _ord.get(r.get("type"), 9))
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return out
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def build_storyboard_frame_prompt_refs(project, version, segment, refs: list[dict]) -> str:
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"""参考图合成版故事板提示词:在基础提示词上点名每张参考图,要求锁脸/锁商品外观。"""
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base = build_storyboard_frame_prompt(project, version, segment)
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"""参考图合成版(用户钦定格式):顶部 @图N 点名每张参考图(角色/商品/场景),再给导演故事板指令 + 分镜脚本。
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@图N 顺序与传给 gpt-image-2 的参考图顺序严格一致(refs 即 image_edit 的 images 顺序)。"""
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if not refs:
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return base
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ref_lines = "；".join(
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f"参考图{i + 1}={r['label']}({_ENTITY_TYPE_CN.get(r.get('type'), '参考')})" for i, r in enumerate(refs)
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)
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return (
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f"{base}\n参考图对应:{ref_lines}。"
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"请严格保持各参考图中角色的同一张脸、同一商品的外观与配色,按本场各分镜画面重新构图,"
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"合成为一张包含多个分镜格的竖屏分镜表(每格一个分镜画面)。"
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return build_storyboard_frame_prompt(project, version, segment)
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setup = "，".join(
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f"@图{i + 1}是{r['label']}({_ENTITY_TYPE_CN.get(r.get('type'), '参考')})" for i, r in enumerate(refs)
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)
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dur = segment.duration_seconds or 15
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lines = [
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f"【设定】{setup}。",
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"根据以下脚本生成一个导演故事板,用于指导 seedance 的视频生成。",
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_scene_context(project),
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f"【分镜脚本】(本段时长约 {dur} 秒)",
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_segment_script_text(segment) or f"第 {segment.sort_order + 1} 镜",
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"请严格保持各参考图中角色的同一张脸、同一商品的外观与配色;电商竖屏 9:16 导演故事板,一镜一图,画面清晰,可直接指导视频生成。",
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]
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if version.prompt:
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lines.append(version.prompt.strip())
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return "\n".join(line for line in lines if line)
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def _storyboard_frame_worker(task_id, version_id, segment_id, user_id) -> None:
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@@ -981,8 +1002,21 @@ def _asset_preview_url(asset) -> str:
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return ""
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def _video_reference_images(project, video_segment) -> list[str]:
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"""为本视频段挑一张视觉参考图:优先本镜故事板帧,兜底已采用商品基础资产。"""
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def _video_reference_images(project, video_segment) -> list[dict]:
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"""视频参考图(带类型,供 @图N):角色/场景/商品 基础资产 + 本镜故事板帧。
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顺序:角色 → 场景 → 商品 → 分镜图(与用户钦定 @图1角色@图2场景@图3商品@图4分镜图 一致)。
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返回 [{url,label,type}];都取不到时兜底商品图。"""
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out: list[dict] = []
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scene = None
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adopted_script = project.script_versions.filter(is_adopted=True).prefetch_related("segments").first()
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if adopted_script is not None:
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scene = adopted_script.segments.filter(sort_order=video_segment.sort_order).first()
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if scene is not None:
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refs = list(_storyboard_reference_images(project, scene)) # 角色/商品/场景 实体图
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_vord = {"character": 0, "scene": 1, "product": 2}
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refs.sort(key=lambda r: _vord.get(r.get("type"), 9))
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out = refs
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# 末位追加本镜故事板帧(@图N 末位 = 分镜图)
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version = (
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project.storyboard_versions.filter(is_adopted=True).order_by("-created_at").first()
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or project.storyboard_versions.order_by("-created_at").first()
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@@ -995,17 +1029,17 @@ def _video_reference_images(project, video_segment) -> list[str]:
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if frame is not None:
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url = _asset_preview_url(frame.asset)
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if url:
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return [url]
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product_group = (
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project.base_asset_groups.filter(kind=BaseAssetGroup.Kind.PRODUCT, adopted_asset__isnull=False)
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.order_by("-created_at")
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.first()
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)
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if product_group is not None:
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url = _asset_preview_url(product_group.adopted_asset)
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if url:
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return [url]
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return []
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out.append({"url": url, "label": "分镜图", "type": "storyboard"})
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if not out:
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product_group = (
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project.base_asset_groups.filter(kind=BaseAssetGroup.Kind.PRODUCT, adopted_asset__isnull=False)
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.order_by("-created_at").first()
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)
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if product_group is not None:
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url = _asset_preview_url(product_group.adopted_asset)
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if url:
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out.append({"url": url, "label": "商品", "type": "product"})
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return out
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def submit_video_segment(*, video_segment: VideoSegment, user, prompt: str) -> VideoSegmentVersion | None:
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@@ -1022,10 +1056,10 @@ def submit_video_segment(*, video_segment: VideoSegment, user, prompt: str) -> V
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if scene is not None and video_segment.script_segment_id != scene.id:
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video_segment.script_segment = scene
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video_segment.save(update_fields=["script_segment", "updated_at"])
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final_prompt = build_video_segment_prompt(project, video_segment, scene, prompt)
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# 参考图:优先用本镜故事板帧,其次商品/人物基础资产,给视频做视觉锚点(衔接故事板→视频)。
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reference_images = _video_reference_images(project, video_segment)
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# 参考图(带类型):角色/场景/商品 基础资产 + 本镜故事板帧;@图N 提示词与传图顺序严格对齐。
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refs = _video_reference_images(project, video_segment)
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reference_images = [r["url"] for r in refs]
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final_prompt = build_video_segment_prompt(project, video_segment, scene, refs, prompt)
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task = create_ai_task(
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project=project,
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