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auto-save 2026-05-13 20:23 (~2)

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kang
2026-05-13 20:23:53 +08:00
parent 40a665a578
commit 989cc912ec
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13
.memory/worklog.json
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@@ -2295,6 +2295,19 @@
"message": "auto-save 2026-05-13 20:12 (~5)",
"hash": "0b6a463",
"files_changed": 5
},
{
"ts": "2026-05-13T20:18:24+08:00",
"type": "commit",
"message": "auto-save 2026-05-13 20:18 (~4)",
"hash": "40a665a",
"files_changed": 4
},
{
"ts": "2026-05-13T12:19:30Z",
"type": "session-heartbeat",
"message": "Codex 会话活跃 · 最近命令：codex · 2 项未提交变更 · 最近提交：auto-save 2026-05-13 20:18 (~4)",
"files_changed": 2
}
]
}

218
api/main.py
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@@ -5,6 +5,7 @@ import json
import os
import shutil
import subprocess
import time
import uuid
from contextlib import asynccontextmanager
from pathlib import Path
@@ -29,6 +30,13 @@ TRANSLATE_MODEL = os.getenv("TRANSLATE_MODEL", "gemini-2.5-flash")
REWRITE_MODEL = os.getenv("REWRITE_MODEL", "gemini-2.5-pro")
VISION_MODEL = os.getenv("VISION_MODEL", "gemini-2.5-flash")
IMAGE_MODEL = os.getenv("IMAGE_MODEL", "gemini-3-pro-image-preview")
VIDEO_MODEL = os.getenv("VIDEO_MODEL", "seedance").strip() or "seedance"
VIDEO_MODEL_ALIASES = {
"seedance": os.getenv("VIDEO_MODEL_SEEDANCE", "seedance").strip() or "seedance",
"kling": os.getenv("VIDEO_MODEL_KLING", "kling").strip() or "kling",
"veo3": os.getenv("VIDEO_MODEL_VEO3", "veo3").strip() or "veo3",
}
VIDEO_DURATION_FIELD = os.getenv("VIDEO_DURATION_FIELD", "seconds").strip() or "seconds"
# OpenAI 客户端（OpenAI 兼容网关，含 SKG ezlink）
from openai import OpenAI
@@ -63,6 +71,21 @@ class GeneratedImage(BaseModel):
created_at: float = 0.0
class GeneratedVideo(BaseModel):
id: str
provider_id: str = ""
frame_idx: int
prompt: str
model: str = ""
status: Literal["queued", "in_progress", "completed", "failed"] = "queued"
url: str = ""
poster_url: str = ""
duration: float = 4.0
progress: int = 0
error: str = ""
created_at: float = 0.0
class StoryboardScene(BaseModel):
"""分镜头编排：每个 selected 分镜对应一个 scene 描述
v2: 4 图槽 + 时长（复制粘贴模式）— 主体 / 场景 / 产品 / 动作 各一张图
@@ -141,6 +164,7 @@ class Job(BaseModel):
frames: list[KeyFrame] = Field(default_factory=list)
transcript: list[TranscriptSegment] = Field(default_factory=list)
storyboard_images: list[StoryboardImage] = Field(default_factory=list)
generated_videos: list[GeneratedVideo] = Field(default_factory=list)
error: str = ""
@@ -163,6 +187,79 @@ def update(job: Job, **kw) -> None:
save_state(job)
def public_api_base() -> str:
return (LLM_BASE_URL or "https://api.openai.com/v1").rstrip("/")
def storyboard_ref_path(job_id: str, ref: dict | None) -> Path | None:
if not ref:
return None
try:
kind = ref.get("kind")
frame_idx = int(ref.get("frame_idx"))
except Exception:
return None
if kind == "keyframe":
p = job_dir(job_id) / "frames" / f"{frame_idx:03d}.jpg"
return p if p.exists() else None
if kind == "cutout":
element_id = (ref.get("element_id") or "").strip()
cutout_id = (ref.get("cutout_id") or "").strip()
if not element_id:
return None
candidates = []
if cutout_id and cutout_id != element_id:
candidates.append(job_dir(job_id) / "elements" / f"{frame_idx:03d}_{element_id}_{cutout_id}.jpg")
candidates.append(job_dir(job_id) / "elements" / f"{frame_idx:03d}_{element_id}.jpg")
candidates.append(job_dir(job_id) / "elements" / f"{frame_idx:03d}_{element_id}.png")
for p in candidates:
if p.exists():
return p
return None
def storyboard_ref_url(job_id: str, ref: dict | None) -> str:
if not ref:
return ""
kind = ref.get("kind")
frame_idx = ref.get("frame_idx")
if kind == "keyframe" and frame_idx is not None:
return f"/jobs/{job_id}/frames/{int(frame_idx)}.jpg"
if kind == "cutout" and frame_idx is not None and ref.get("element_id"):
element_id = ref.get("element_id")
cutout_id = ref.get("cutout_id")
if cutout_id and cutout_id != element_id:
return f"/jobs/{job_id}/frames/{int(frame_idx)}/elements/{element_id}/cutouts/{cutout_id}.jpg"
return f"/jobs/{job_id}/frames/{int(frame_idx)}/elements/{element_id}/cutout.jpg"
return ""
def prepare_video_reference(src: Path, dst: Path, size: tuple[int, int] = (720, 1280)) -> None:
dst.parent.mkdir(parents=True, exist_ok=True)
img = Image.open(src).convert("RGB")
img.thumbnail(size, Image.Resampling.LANCZOS)
canvas = Image.new("RGB", size, (8, 8, 10))
x = (size[0] - img.width) // 2
y = (size[1] - img.height) // 2
canvas.paste(img, (x, y))
canvas.save(dst, "JPEG", quality=94)
def update_generated_video(job_id: str, video_id: str, **kw) -> None:
job = JOBS.get(job_id)
if not job:
return
updated = []
for v in job.generated_videos:
if v.id == video_id:
data = v.model_dump()
data.update(kw)
updated.append(GeneratedVideo(**data))
else:
updated.append(v)
update(job, generated_videos=updated)
@asynccontextmanager
async def lifespan(_: FastAPI):
# 启动时从磁盘恢复 jobs（简化版：只列目录）
@@ -1468,6 +1565,127 @@ class UpdateStoryboardReq(BaseModel):
reference_ids: list[str] = []
class GenerateStoryboardVideoReq(BaseModel):
prompt: str
duration: float = 4
subject_image: dict | None = None
scene_image: dict | None = None
product_image: dict | None = None
action_image: dict | None = None
model: str = ""
size: str = "720x1280"
def video_seconds(duration: float) -> str:
if duration <= 6:
return "4"
if duration <= 10:
return "8"
return "12"
def render_storyboard_video(job_id: str, local_id: str, provider_id: str, ref_path: Path, prompt: str, model: str, seconds: str, size: str) -> None:
import httpx
out_dir = job_dir(job_id) / "storyboard_videos" / local_id
ref_img = out_dir / "reference.jpg"
out_mp4 = out_dir / "video.mp4"
base = public_api_base()
headers = {"Authorization": f"Bearer {LLM_API_KEY}"}
try:
prepare_video_reference(ref_path, ref_img)
update_generated_video(job_id, local_id, status="in_progress", progress=5)
with httpx.Client(timeout=120) as client:
with ref_img.open("rb") as fh:
create = client.post(
f"{base}/videos",
headers=headers,
data={
"model": model,
"prompt": prompt,
"seconds": seconds,
"size": size,
},
files={"input_reference": ("reference.jpg", fh, "image/jpeg")},
)
create.raise_for_status()
data = create.json()
video_api_id = data.get("id") or provider_id
update_generated_video(job_id, local_id, provider_id=video_api_id, status=data.get("status", "queued"), progress=int(data.get("progress") or 5))
status = data.get("status", "queued")
progress = int(data.get("progress") or 5)
deadline = time.time() + 420
while status in {"queued", "in_progress"} and time.time() < deadline:
time.sleep(8)
poll = client.get(f"{base}/videos/{video_api_id}", headers=headers)
poll.raise_for_status()
pdata = poll.json()
status = pdata.get("status", status)
progress = int(pdata.get("progress") or progress)
update_generated_video(job_id, local_id, status=status, progress=progress)
if status != "completed":
update_generated_video(job_id, local_id, status="failed", error=f"video status: {status}", progress=progress)
return
content = client.get(f"{base}/videos/{video_api_id}/content", headers=headers)
content.raise_for_status()
out_mp4.write_bytes(content.content)
update_generated_video(
job_id,
local_id,
status="completed",
progress=100,
url=f"/jobs/{job_id}/storyboard-videos/{local_id}.mp4",
error="",
)
except Exception as e:
update_generated_video(job_id, local_id, status="failed", error=str(e)[:500])
@app.post("/jobs/{job_id}/frames/{idx}/storyboard/video", response_model=Job)
def generate_storyboard_video(job_id: str, idx: int, req: GenerateStoryboardVideoReq, bg: BackgroundTasks) -> Job:
job = JOBS.get(job_id)
if not job:
raise HTTPException(404, "job not found")
frame = next((f for f in job.frames if f.index == idx), None)
if not frame:
raise HTTPException(404, "frame not found")
if not LLM_API_KEY:
raise HTTPException(500, "LLM_API_KEY 未配置，无法调用视频生成 API")
prompt = req.prompt.strip()
if not prompt:
raise HTTPException(400, "prompt required")
ref = req.product_image or req.subject_image or req.scene_image or req.action_image
ref_path = storyboard_ref_path(job_id, ref) or (job_dir(job_id) / "frames" / f"{idx:03d}.jpg")
if not ref_path.exists():
raise HTTPException(404, "reference image missing")
poster = storyboard_ref_url(job_id, ref) or f"/jobs/{job_id}/frames/{idx}.jpg"
local_id = uuid.uuid4().hex[:12]
model = req.model.strip() or VIDEO_MODEL
seconds = video_seconds(float(req.duration or 4))
item = GeneratedVideo(
id=local_id,
provider_id="",
frame_idx=idx,
prompt=prompt,
model=model,
status="queued",
url="",
poster_url=poster,
duration=float(seconds),
progress=0,
created_at=time.time(),
)
update(job, generated_videos=[item] + job.generated_videos, message=f"视频生成已提交 · 分镜 {idx + 1}")
bg.add_task(render_storyboard_video, job_id, local_id, "", ref_path, prompt, model, seconds, req.size)
return job
@app.put("/jobs/{job_id}/frames/{idx}/storyboard", response_model=Job)
def update_storyboard(job_id: str, idx: int, req: UpdateStoryboardReq) -> Job:
"""更新分镜的编排字段（subject / product / scene / action / duration / reference_ids）"""