优化脚本

This commit is contained in:
Azmat@qq.com
2026-08-28 14:45:38 +08:00
parent 849b14a0f6
commit c0a0b9603b
37 changed files with 541 additions and 1893 deletions
+33 -427
View File
@@ -41,10 +41,6 @@ from apps.projects.models import (
ProjectStage,
ScriptSegment,
ScriptVersion,
StoryboardFrame,
StoryboardShot,
StoryboardShotVersion,
StoryboardVersion,
Timeline,
VideoSegment,
VideoSegmentVersion,
@@ -67,26 +63,6 @@ def get_default_model(capability: str) -> ModelConfig:
return qs.filter(is_default=True).order_by("created_at").first() or qs.order_by("created_at").first()
def get_storyboard_image_model() -> ModelConfig | None:
"""故事板出图只走 GPT 图像模型(gpt-image / gpt-image-2)。
不回落默认图像模型,也不走火山 Seedream:用户明确要求故事板无论怎样都不改成其他生图模型。
"""
qs = (
ModelConfig.objects.select_related("provider")
.filter(
capability=ModelConfig.Capability.IMAGE,
status=ModelConfig.Status.ACTIVE,
provider__status="active",
name__icontains="gpt-image",
)
)
return (
qs.filter(name="gpt-image-2").order_by("created_at").first()
or qs.order_by("created_at").first()
)
def resolve_image_model(key: str | None) -> "ModelConfig | None":
"""前端「生图模型选择」→ ModelConfig。用户显式选的可以是 disabled 模型(故不按 status 过滤)。
· "volcano" → 火山官方 Seedream(取最新一版)
@@ -901,20 +877,6 @@ NO_EMBEDDED_CAPTIONS_REQUIREMENT = (
"只保留商品包装上参考图中原有的真实物理文字与标识。旁白和环境音可以保留,但不要把声音转成画面文字。"
)
# 故事板是创作者确认镜头节奏的导演稿,因此必须由 image-2 直接生成完整排版图;
# 视频提示词会明确要求只提取其中的角色、商品、场景、动作和节奏,忽略版式文字。
STORYBOARD_DIRECTOR_LAYOUT_REQUIREMENT = (
"【导演故事板成图硬性要求】输出必须是一张完整、正式、可交付的电商短视频导演故事板图片,而不是无说明的拼图或单张海报。"
"整体为竖版 9:16,采用清爽专业的影视分镜排版:顶部 1 行标题区,标出“导演故事板”、本段时长和画幅;"
"主体严格按照本段脚本的秒级分镜,优先整理为 3 个连续时间段(例如 0–5s、5–10s、10–15s;若脚本时长不同则按实际时间划分)。"
"每个时间段必须包含三部分:左侧约 22% 宽的浅色信息栏,清晰写时间、景别、机位/运镜和简短动作;右侧约 78% 的写实主画面;"
"画面底部横条使用扬声器图标与“口播/旁白:”呈现该时间段对应旁白。各段按时间自上而下排列,边框、间距、对齐统一。"
"右侧画面要真实展现该秒级分镜的不同关键动作,人物脸、服装、商品外观、配色和场景连续一致;商品用法必须正确,包装真实文字和 Logo 不得改造。"
"故事板中的中文标注必须工整、简洁、可读,只写脚本已有的时间、机位、动作与旁白,不虚构价格、功效、活动或品牌信息。"
"禁止只给一张静态人物图、禁止无文字的四格拼图、禁止把三段画面重复成同一姿势。"
)
def enforce_no_embedded_captions(prompt: str) -> str:
"""所有视频入口最终汇入这里,避免某个入口漏传“无字幕”导致模型自行加花字。"""
base = (prompt or "").strip()
@@ -1470,20 +1432,6 @@ def project_output_spec(project) -> dict:
}
def _storyboard_canvas_phrase(ratio: str) -> str:
r = (ratio or "9:16").strip() or "9:16"
if r in {"9:16", "3:4"}:
return f"电商竖屏 {r}"
if r == "1:1":
return f"电商方形 {r}"
return f"电商横屏 {r}"
def _apply_storyboard_output_ratio(text: str, project) -> str:
phrase = _storyboard_canvas_phrase(project_output_spec(project)["aspect_ratio"])
return (text or "").replace("电商竖屏 9:16", phrase)
def _sync_timeline_output_spec(project, *, aspect_ratio: str, resolution: str) -> None:
from apps.ai.video_pricing import get_resolution
@@ -2702,125 +2650,49 @@ def _segment_script_text(segment, entities=None, *, with_dialogue: bool = False,
return "\n".join(parts)
def build_storyboard_frame_prompt(project, segment, extra_prompt: str = "") -> str:
"""单镜导演故事板提示词(无参考图时的文本版)。与 refs 版共用 admin「提示词·分镜图」模板(设定为空)。
extra_prompt = 整张风格提示词(原 StoryboardVersion.prompt,现存项目级)。"""
dur = segment.duration_seconds or 15
default = (
"{设定}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。\n{场景上下文}\n"
"【分镜脚本】(本段时长约 {时长} 秒)\n{脚本}\n"
"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。"
"脚本里的 visual 是本段秒级分镜清单;请画商品用法正确、最能看清商品的那一拍作为关键帧。"
"禁止画出违背常识的用法(例如把茶包丢进冷白开、悬浮的手)。{补充}"
)
rendered = render_prompt(
"storyboard_frame", default,
设定="",
场景上下文=_scene_context(project),
时长=dur,
脚本=(_segment_script_text(segment) or f"{segment.sort_order + 1}"),
补充=(("\n" + extra_prompt.strip()) if extra_prompt else ""),
)
cleaned = "\n".join(line for line in rendered.split("\n") if line.strip())
return _apply_storyboard_output_ratio(
f"{cleaned}\n{STORYBOARD_DIRECTOR_LAYOUT_REQUIREMENT}", project
)
def build_video_segment_prompt(project, video_segment, scene, refs, user_prompt: str = "") -> str:
"""单段视频提示词(用户钦定 @图N 格式):
【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
【设定】@图N 点名 角色/场景/商品;【风格】全片统一的风格锚点;【脚本】本镜导演说明书(秒级分镜 + 台词)
★ 去掉故事板中间层后,导演信息不再经由一张分镜图传递,而是**全靠这份提示词直达出片模型**,
因此这里必须自足:参考图一致性约束 + 秒级执行纪律 + 物理常识 + 成片硬性规则,一条都不能少。
refs 顺序与传给 seedance 的 reference_images 一致(@图N 对齐不错位)。"""
product_name = (getattr(project.product, "title", "") or "商品").strip()
setup_parts = []
storyboard_idx = None
for i, r in enumerate(refs or []):
n = i + 1
if r.get("type") == "storyboard":
storyboard_idx = n
else:
setup_parts.append(f"@图{n}{r.get('label') or ''}({_ENTITY_TYPE_CN.get(r.get('type'), '参考')})")
setup_parts.append(f"@图{n}{r.get('label') or ''}({_ENTITY_TYPE_CN.get(r.get('type'), '参考')})")
# 视频脚本:用带说话人的台词(原样照脚本),不带「商品露出」那行(露出靠模板尾句统一要求)
entities = (project.metadata or {}).get("script_entities", [])
script_text = _segment_script_text(scene, entities, with_dialogue=True, with_exposure=False) if scene is not None else ""
extra = (user_prompt or "").strip()
if extra:
script_text = (script_text + "\n" + extra).strip() if script_text else extra
# 正文可在 admin「提示词·视频」页改。占位符:{设定}=@图N点名、{分镜}=分镜图引用、{脚本}=本段脚本、{时长}。
# 正文可在 admin「提示词·视频」页改。占位符:{设定}=@图N点名、{风格}=全片风格锚点、{脚本}=本段脚本、{时长}。
# 时长/比例靠 API 参数传(duration/ratio),不写进正文;尾句给风格 + 音效/字幕要求。
default = (
"{设定}{分镜}【脚本】{脚本}\n"
"严格按脚本里的秒级分镜切换景别和动作,商品用法必须真实,不要诡异姿势或错误容器。"
"如果参考图是带时间、机位、旁白标注的导演故事板,只提取其中的角色、商品、场景、动作和时间顺序;"
"不要把边框、标题、时间码、扬声器图标或任何故事板文字生成进视频。"
"电商带货短视频,商品露出清晰,节奏有转化感。不要字幕,不要背景音乐,但是要有音效,逼真的音效。"
"{设定}{风格}【脚本】{脚本}\n"
"【执行纪律】严格按脚本里的秒级分镜拍:每一个时间段都要拍到,景别、机位、运镜、动作按写的来;"
"不要把整段并成一个静止长镜头,也不要加脚本里没有的转场、人物或道具。"
"\n【一致性】参考图是本片唯一的视觉依据:角色保持同一张脸、同一发型、同一套服装;"
"商品保持参考图的外形、配色、材质、比例与包装上的真实文字标识,不得改造、换色、换包装或凭空加配件;"
"场景保持同一空间、同一陈设、同一光线方向与色温。多镜之间人物与商品必须看起来是同一次拍摄。"
"\n【物理常识】手从画面内自然入画,禁止悬浮肢体、反关节、商品凭空出现或消失;"
"商品用法必须是真人会做的(茶/咖啡用热水、有蒸汽与茶汤渐染;护肤品挤出并涂抹;食品打开并入口),"
"禁止诡异姿势、错误容器或违背常识的操作。"
"\n【画质】真人实拍质感,自然光影,肤色与材质真实,焦点始终落在脚本指定的主体上,画面稳定不糊。"
"\n电商带货短视频,商品露出清晰,节奏有转化感。不要字幕,不要背景音乐,但是要有音效,逼真的音效。"
)
rendered = render_prompt(
"video_segment", default,
设定=("【设定】" + "".join(setup_parts) + "\n" if setup_parts else ""),
分镜=(f"分镜】根据@图{storyboard_idx}分镜图生成「{product_name}」短视频\n" if storyboard_idx is not None else ""),
风格=(f"风格】{_scene_context(project)}\n" if _scene_context(project) else ""),
分镜="", # 兼容:旧模板行里可能还留着 {分镜}(故事板时代的占位符),渲染成空串而不是原样漏出
脚本=(script_text or f"{video_segment.sort_order + 1}"),
时长=video_segment.target_duration_seconds,
)
return enforce_no_embedded_captions("\n".join(line for line in rendered.split("\n") if line.strip()))
def ensure_storyboard_shots(project) -> list:
"""确保「采用版分镜数」= StoryboardShot 数:每镜一个 shot(对标视频段)。
缺则按 sort_order 建、补绑 script_segment;多出且从没出过图的尾 shot 裁掉(已出图的不动)。"""
adopted_script = project.script_versions.filter(is_adopted=True).prefetch_related("segments").first()
if adopted_script is None:
return []
segs = list(adopted_script.segments.order_by("sort_order"))
shots = {s.sort_order: s for s in project.storyboard_shots.all()}
for seg in segs:
shot = shots.get(seg.sort_order)
if shot is None:
shots[seg.sort_order] = StoryboardShot.objects.create(
project=project, script_segment=seg, sort_order=seg.sort_order, prompt=seg.visual_prompt or "")
elif shot.script_segment_id != seg.id:
shot.script_segment = seg
shot.save(update_fields=["script_segment", "updated_at"])
target = len(segs)
for order, shot in list(shots.items()):
if order >= target and not shot.versions.exists():
shot.delete()
del shots[order]
return [shots[k] for k in sorted(shots)]
def submit_storyboard(*, project, user, prompt: str = "", shot_ids: list | None = None) -> list:
"""故事板·提交(分镜制,对标视频「开始生成/单段重跑」):确保每镜一个 shot,把目标场标 QUEUED,
真正出图由 poll_storyboard 起后台线程。返回受影响的 shots。
- shot_ids 给定 → 只(重)生成这些场(单场重跑);
- 不给 → 还没出片的场;若全部已出片 → 视为整批重跑,全部重出。
prompt = 整张风格提示词,存项目级 metadata,供每场出图带上(原 StoryboardVersion.prompt 的去处)。"""
adopted_script = project.script_versions.filter(is_adopted=True).first()
if adopted_script is None:
raise ValueError("script must be adopted before generating storyboard")
if get_storyboard_image_model() is None:
raise ValueError("故事板只使用 GPT 图像模型,当前没有启用 gpt-image-2")
if prompt:
meta = dict(project.metadata or {})
if meta.get("storyboard_prompt") != prompt:
meta["storyboard_prompt"] = prompt
project.metadata = meta
project.save(update_fields=["metadata", "updated_at"])
shots = ensure_storyboard_shots(project)
if shot_ids is not None:
want = {str(x) for x in shot_ids}
targets = [s for s in shots if str(s.id) in want]
else:
pending = [s for s in shots if s.status != StoryboardShot.Status.SUCCEEDED or s.adopted_version_id is None]
targets = pending if pending else shots # 全部已出片 = 整批重跑
for s in targets:
s.status = StoryboardShot.Status.QUEUED
s.error_message = ""
s.save(update_fields=["status", "error_message", "updated_at"])
return targets
_ENTITY_TYPE_CN = {"character": "角色", "scene": "场景", "product": "商品"}
@@ -2846,9 +2718,9 @@ def _product_reference_image(project, groups: list | None = None) -> dict | None
return None
def _storyboard_reference_images(project, segment) -> list[dict]:
def _segment_reference_images(project, segment) -> list[dict]:
"""按本镜 entity_refs 取参考图(角色 / 场景 已采用基础资产)+ **无条件带上商品参考图**,
gpt-image-2 多图合成 @图N。返回 [{url,label,type}],最多 4 张(角色/场景 ≤3 + 商品 1)。
出片模型 @图N 锁脸 / 锁商品 / 锁场景。返回 [{url,label,type}],最多 4 张(角色/场景 ≤3 + 商品 1)。
商品不靠 entity_refs(预创建真实商品、不从脚本提),统一用商品三视图 / 主图带上,从根上保证
商品参考永不缺失。依赖提取步落进 metadata 的 script_entities。"""
entities = {
@@ -2911,65 +2783,6 @@ def _storyboard_reference_images(project, segment) -> list[dict]:
return out[:4]
def build_storyboard_frame_prompt_refs(project, segment, refs: list[dict], extra_prompt: str = "") -> str:
"""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。
@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)。"""
if not refs:
return build_storyboard_frame_prompt(project, segment, extra_prompt)
setup = "".join(
f"@图{i + 1}{r['label']}({_ENTITY_TYPE_CN.get(r.get('type'), '参考')})" for i, r in enumerate(refs)
)
dur = segment.duration_seconds or 15
# 正文可在 admin「提示词」页改。占位符:{设定}=@图N点名、{场景上下文}、{时长}、{脚本}=本镜脚本、{补充}=本版附加。
default = (
"{设定}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。\n{场景上下文}\n"
"【分镜脚本】(本段时长约 {时长} 秒)\n{脚本}\n"
"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。"
"脚本里的 visual 是本段秒级分镜清单;请画商品用法正确、最能看清商品的那一拍作为关键帧。"
"禁止画出违背常识的用法(例如把茶包丢进冷白开、悬浮的手)。{补充}"
)
rendered = render_prompt(
"storyboard_frame", default,
设定=(f"【设定】{setup}\n" if setup else ""),
场景上下文=_scene_context(project),
时长=dur,
脚本=(_segment_script_text(segment) or f"{segment.sort_order + 1}"),
补充=(("\n" + extra_prompt.strip()) if extra_prompt else ""),
)
cleaned = "\n".join(line for line in rendered.split("\n") if line.strip())
return _apply_storyboard_output_ratio(
f"{cleaned}\n{STORYBOARD_DIRECTOR_LAYOUT_REQUIREMENT}", project
)
def _is_transient_error(exc: Exception) -> bool:
"""网络抖动/超时类瞬时错误(可重试),区别于内容审核拦截、参数非法等确定性失败。
中转站(tokenssr 等)偶发 Read timeout / 连接重置会无谓掐掉单帧,这类才重试。
★ 不重试 400:实测故事板的 400 主因是 gpt-image-2 内容审核拦截(moderation_blocked,
safety_violations=[sexual],如脚本写到「蕾丝胸罩/抚摸/贴身」)—— 同一画面/文案重试还是被拦,
重试只会拖延报错、空耗调用。这类应「快速失败 + 友好提示」让用户改提示词,而非闷头重试。"""
msg = str(exc).lower()
return any(
k in msg
for k in ("timed out", "timeout", "connection", "reset by peer", "temporarily",
"bad gateway", "502", "503", "504", "remotedisconnected", "max retries")
)
# 审核类别英文 → 给用户的中文说明(摘自第三方 safety_violations 字段)。命不中则原样保留英文。
_MODERATION_CATEGORY_CN = {
"sexual": "性暗示 / 露骨",
"sexual/minors": "涉及未成年的性内容",
"violence": "暴力",
"violence/graphic": "血腥暴力",
"self-harm": "自残",
"hate": "仇恨",
"harassment": "骚扰",
"illicit": "违禁",
}
def _extract_moderation_categories(raw: str) -> list[str]:
"""从原始报错里抽出被审核命中的类别(如 safety_violations=[sexual] / "categories":["sexual"]),
译成中文标签。抽不到返回 []。供友好提示点名真实类别,而非泛化的「疑似敏感内容」。"""
@@ -3061,192 +2874,6 @@ def notify_generation_failure(
logger.exception("notify_generation_failure failed for task %s", getattr(task, "id", "?"))
def _call_image_with_retry(fn, *, attempts: int = 2, base_delay: float = 2.0):
"""对一次出图网络调用做有界重试:仅瞬时错误重试(指数退避),确定性失败立即抛出。
出图无副作用(失败=没拿到图),重试安全;成功一次即返回。
attempts 默认 2(一次重试):单次 HTTP 超时上限 300s,2 次≈10min,须 < poll 的「在途锁过期窗口」
(STORYBOARD_INFLIGHT_STALE_MINUTES)否则 worker 重试期间任务被判僵尸 → 重复起线程 + 重复扣费。"""
import time
last: Exception | None = None
for i in range(attempts):
try:
return fn()
except Exception as exc: # noqa: BLE001
last = exc
if i == attempts - 1 or not _is_transient_error(exc):
raise
time.sleep(base_delay * (i + 1))
raise last # 理论不可达(循环内已 return/raise)
def _storyboard_shot_worker(task_id, shot_id, user_id) -> None:
"""后台线程:为一个 StoryboardShot 出一张图 → 落成一条 StoryboardShotVersion 并采用。HTTP 永远秒回。"""
from django.db import connections
from apps.accounts.models import User
try:
task = AITask.objects.select_related("model_config__provider").get(id=task_id)
shot = StoryboardShot.objects.select_related("project__team", "script_segment").get(id=shot_id)
user = User.objects.get(id=user_id)
project = shot.project
segment = shot.script_segment
reservation = task.credit_reservation
extra_prompt = (project.metadata or {}).get("storyboard_prompt", "") or ""
spec = project_output_spec(project)
frame_ratio = spec["aspect_ratio"]
frame_size = _ratio_to_image_size(frame_ratio)
task.status = AITask.Status.SUBMITTED
task.save(update_fields=["status", "updated_at"])
try:
# 故事板无论任务上挂了什么模型、是否开了路由,都只走 GPT 图像;失败也不换 Seedream。
model_config = get_storyboard_image_model()
if model_config is None:
raise ValueError("故事板只使用 GPT 图像模型,当前没有启用 gpt-image-2")
provider = get_image_provider(model_config)
refs = _storyboard_reference_images(project, segment) if segment is not None else []
ref_urls = [r["url"] for r in refs]
if ref_urls and hasattr(provider, "image_edit"):
# gpt-image-2 多图参考:必须用 refs 版提示词(点名「参考图N=角色/场景/商品」+锁脸锁商品)
frame_prompt = build_storyboard_frame_prompt_refs(project, segment, refs, extra_prompt)
else:
frame_prompt = (
build_storyboard_frame_prompt(project, segment, extra_prompt) if segment is not None
else (task.request_payload.get("prompt") or "")
)
if ref_urls and hasattr(provider, "image_edit"):
response = _call_image_with_retry(
lambda: provider.image_edit(
model=model_config.name,
prompt=frame_prompt,
images=ref_urls,
size=frame_size,
)
)
else:
response = _call_image_with_retry(
lambda: provider.image_generation(
model=model_config.name,
endpoint=model_config.endpoint,
prompt=frame_prompt,
)
)
media = provider.extract_first_media_url(response)
asset = _store_generated_media(
team=project.team, user=user, project=project, task=task, media=media,
name=f"{project.name}-storyboard-{shot.sort_order + 1}",
category=Asset.Category.STORYBOARD, asset_type=Asset.Type.IMAGE,
)
with transaction.atomic():
task.status = AITask.Status.SUCCEEDED
task.response_payload = response
task.actual_cost = task.estimated_cost
task.completed_at = timezone.now()
task.save(update_fields=["status", "response_payload", "actual_cost", "completed_at", "updated_at"])
charge_reserved_credit(reservation=reservation, actual_amount=task.actual_cost)
# 落一条新版本并采用(反采用同 shot 其余版本)= 该场历史 +1,采用最新
version = StoryboardShotVersion.objects.create(
shot=shot, task=task, asset=asset,
prompt=(segment.visual_prompt if segment is not None else ""), is_adopted=True,
)
shot.versions.exclude(id=version.id).update(is_adopted=False)
StoryboardShot.objects.filter(id=shot.id).update(
adopted_version=version, status=StoryboardShot.Status.SUCCEEDED, error_message="", updated_at=timezone.now())
# 合规:分镜图含人脸,视频生成前必须过火山审核 → 事务提交后静默送审(best-effort)
from apps.assets.review import submit_asset_for_review
transaction.on_commit(lambda a=asset: submit_asset_for_review(a))
except Exception as exc: # noqa: BLE001 — 失败回滚额度,标记任务+shot 失败供 poll 上报
raw = str(exc)
public_error = classify_generation_error(
exc, operation="storyboard_generate", reference_id=str(task.id)
)
task.status = AITask.Status.FAILED
task.error_message = raw[:2000]
task.completed_at = timezone.now()
task.save(update_fields=["status", "error_message", "completed_at", "updated_at"])
release_credit(reservation=reservation, reason=raw[:200])
# 重跑失败时保留旧 adopted_version(画面不丢),只把状态标 FAILED + 友好提示供前端显示
StoryboardShot.objects.filter(id=shot.id).update(
status=StoryboardShot.Status.FAILED, error_message=public_error.fallback_message, updated_at=timezone.now())
# 落一条失败通知,正文带上第三方服务商 API 的原始报错(真因),供用户/排查直接查看
notify_generation_failure(
task=task, project=project, recipient=user,
stage_label=f"故事板·场 {shot.sort_order + 1}", raw=raw, hint=public_error.fallback_message,
)
finally:
connections.close_all() # 释放该线程的 DB 连接
def poll_storyboard(*, project, user) -> dict:
"""异步故事板·轮询(秒回):为 QUEUED/在制 shot 起线程出图;报告进度。永不阻塞在 ARK 调用上。
返回 {status: generating|succeeded|failed, done, total}。done = 已出片(有采用版且 SUCCEEDED)的场数。"""
import threading
from django.conf import settings as dj_settings
shots = list(project.storyboard_shots.select_related("script_segment").order_by("sort_order"))
if not shots:
return {"status": "succeeded", "done": 0, "total": 0}
total = len(shots)
done = sum(1 for s in shots if s.adopted_version_id is not None and s.status == StoryboardShot.Status.SUCCEEDED)
active = [s for s in shots if s.status in (StoryboardShot.Status.QUEUED, StoryboardShot.Status.RUNNING)]
if not active:
failed = [s for s in shots if s.status == StoryboardShot.Status.FAILED]
if failed:
return {"status": "failed", "done": done, "total": total, "error": failed[0].error_message or "storyboard shot failed"}
return {"status": "succeeded", "done": done, "total": total}
# 每镜独立「占位锁」:近 N 分钟内有 CREATED/RESERVED/SUBMITTED 任务的 shot = 在生成中(僵尸超时后释放)。
STORYBOARD_MAX_PARALLEL = int(getattr(dj_settings, "STORYBOARD_MAX_PARALLEL", 4))
stale_minutes = int(getattr(dj_settings, "STORYBOARD_INFLIGHT_STALE_MINUTES", 12))
stale_cutoff = timezone.now() - timedelta(minutes=stale_minutes)
inflight_shot_ids = {
str(v)
for v in AITask.objects.filter(
project=project, task_type=AITask.Type.STORYBOARD,
status__in=[AITask.Status.CREATED, AITask.Status.RESERVED, AITask.Status.SUBMITTED],
created_at__gte=stale_cutoff,
).values_list("request_payload__storyboard_shot", flat=True)
if v
}
model_config = get_storyboard_image_model()
if model_config is None:
return {"status": "failed", "done": done, "total": total, "error": "故事板只使用 GPT 图像模型,当前没有启用 gpt-image-2"}
extra_prompt = (project.metadata or {}).get("storyboard_prompt", "") or ""
spawnable = [s for s in active if str(s.id) not in inflight_shot_ids]
slots = max(0, STORYBOARD_MAX_PARALLEL - len(inflight_shot_ids))
for shot in spawnable[:slots]:
segment = shot.script_segment
task = create_ai_task(
project=project, user=user, task_type=AITask.Type.STORYBOARD, model_config=model_config,
request_payload={
"model": model_config.name, "endpoint": model_config.endpoint,
"prompt": build_storyboard_frame_prompt(project, segment, extra_prompt) if segment is not None else "",
"storyboard_shot": str(shot.id),
},
)
StoryboardShot.objects.filter(id=shot.id).update(status=StoryboardShot.Status.RUNNING, updated_at=timezone.now())
threading.Thread(
target=_storyboard_shot_worker, args=(str(task.id), str(shot.id), str(user.id)), daemon=True
).start()
return {"status": "generating", "done": done, "total": total}
def adopt_storyboard_shot_version(*, shot: StoryboardShot, version: StoryboardShotVersion) -> None:
"""采用某场的某个历史版本(对标 adopt-video-version):反采用同场其余版本,置该场为采用版+SUCCEEDED。"""
shot.versions.exclude(id=version.id).update(is_adopted=False)
if not version.is_adopted:
version.is_adopted = True
version.save(update_fields=["is_adopted", "updated_at"])
shot.adopted_version = version
shot.status = StoryboardShot.Status.SUCCEEDED
shot.error_message = ""
shot.save(update_fields=["adopted_version", "status", "error_message", "updated_at"])
def _asset_preview_url(asset) -> str:
"""资产主文件的可公开访问 URL(已写绝对 URL 优先,否则实时签 TOS GET)。"""
if asset is None:
@@ -3274,8 +2901,10 @@ def _seedance_ref_url(raw_url: str, review_status: str = "", review_remote_id: s
def _video_reference_images(project, video_segment) -> list[dict]:
"""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
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)。
"""视频参考图(带类型,供 @图N):角色 / 场景 / 商品 基础资产
顺序:角色 → 场景 → 商品(与提示词里 @图1角色@图2场景@图3商品 一致)。
★ 故事板已从流程中去掉,不再有「分镜图」这一张:导演信息全部走提示词
(build_video_segment_prompt),参考图只负责锁脸 / 锁商品 / 锁场景。
返回 [{url,label,type}];url 对过审人脸资产为 asset:// 素材库引用。都取不到时兜底商品图。"""
out: list[dict] = []
scene = None
@@ -3283,21 +2912,10 @@ def _video_reference_images(project, video_segment) -> list[dict]:
if adopted_script is not None:
scene = adopted_script.segments.filter(sort_order=video_segment.sort_order).first()
if scene is not None:
refs = list(_storyboard_reference_images(project, scene)) # 角色/商品/场景 实体图
refs = list(_segment_reference_images(project, scene)) # 角色/商品/场景 实体图
_vord = {"character": 0, "scene": 1, "product": 2}
refs.sort(key=lambda r: _vord.get(r.get("type"), 9))
out = refs
# 末位追加本镜故事板分镜图(@图N 末位 = 分镜图):取该 sort_order 的 shot 的采用版资产
shot = (
project.storyboard_shots.filter(sort_order=video_segment.sort_order, adopted_version__isnull=False).select_related("adopted_version__asset").first()
or project.storyboard_shots.filter(adopted_version__isnull=False).select_related("adopted_version__asset").order_by("sort_order").first()
)
if shot is not None and shot.adopted_version_id:
frame_asset = shot.adopted_version.asset
url = _asset_preview_url(frame_asset)
if url:
out.append({"url": url, "label": "分镜图", "type": "storyboard",
"review_status": frame_asset.review_status, "review_remote_id": frame_asset.review_remote_id})
if not out:
product_group = (
project.base_asset_groups.filter(kind=BaseAssetGroup.Kind.PRODUCT, adopted_asset__isnull=False)
@@ -3314,19 +2932,17 @@ def _video_reference_images(project, video_segment) -> list[dict]:
def collect_video_review_blockers(project, only_segment: "VideoSegment | None" = None) -> list[dict]:
"""点「生成视频」前的过审闸:列出本次将生成的段里,含真人脸的参考图(人物立绘 + 该镜故事板分镜)
**尚未过审(review_status != 'active')** 的项。火山视频对含真人脸的图,只接受素材库已过审的引用,
否则报 InputImageSensitiveContentDetected。这里在调火山前先拦,弹窗指明是哪一镜的哪个人物/分镜未过审。
"""点「生成视频」前的过审闸:列出本次将生成的段里,含真人脸的参考图(人物立绘)
**尚未过审(review_status != 'active')** 的项。火山视频对含真人脸的图,只接受素材库已过审的引用,
否则报 InputImageSensitiveContentDetected。这里在调火山前先拦,弹窗指明是哪一镜的哪个人物未过审。
★ 故事板去掉后不再有「分镜图」这一类待审资产,闸口只剩人物立绘。
only_segment 给定 → 只校验该段(单段重跑);为 None → 校验全部「未出片」段(整批生成)。
返回 [{video_segment_id, sort_order, scene_no, kind:'person'|'storyboard', name, asset_id, review_status}];
返回 [{video_segment_id, sort_order, scene_no, kind:'person', name, asset_id, review_status}];
空列表 = 全部已过审,可放行。"""
segs = [only_segment] if only_segment is not None else list(project.video_segments.order_by("sort_order"))
adopted_script = project.script_versions.filter(is_adopted=True).prefetch_related("segments").first()
shots_by_order = {
s.sort_order: s
for s in project.storyboard_shots.filter(adopted_version__isnull=False).select_related("adopted_version__asset")
}
blockers: list[dict] = []
for seg in segs:
# 整批生成只校验还没出片的段;单段重跑则无论状态都校验(用户主动要重出这一段)
@@ -3336,7 +2952,7 @@ def collect_video_review_blockers(project, only_segment: "VideoSegment | None" =
scene = adopted_script.segments.filter(sort_order=seg.sort_order).first() if adopted_script else None
# 人物立绘(与视频实际取图同一套逻辑,保证「拦的」就是「会传给火山的」)
if scene is not None:
for ref in _storyboard_reference_images(project, scene):
for ref in _segment_reference_images(project, scene):
if ref.get("type") != "character":
continue
if (ref.get("review_status") or "") != "active":
@@ -3345,16 +2961,6 @@ def collect_video_review_blockers(project, only_segment: "VideoSegment | None" =
"kind": "person", "name": ref.get("label") or "人物",
"asset_id": str(ref.get("asset_id") or ""), "review_status": ref.get("review_status") or "",
})
# 该镜故事板分镜图(分镜图里也有同一张脸,是另一个需过审的资产)= 对应 shot 的采用版资产
shot = shots_by_order.get(seg.sort_order)
if shot is not None and shot.adopted_version_id:
frame_asset = shot.adopted_version.asset
if (frame_asset.review_status or "") != "active":
blockers.append({
"video_segment_id": str(seg.id), "sort_order": seg.sort_order, "scene_no": scene_no,
"kind": "storyboard", "name": f"{scene_no} 分镜图",
"asset_id": str(frame_asset.id), "review_status": frame_asset.review_status or "",
})
return blockers