573 lines
22 KiB
Python
573 lines
22 KiB
Python
"""上传视频提炼 —— 参考视频 → 可人工逐镜编辑的中文分镜稿。
|
|
|
|
优先把**完整视频(含音轨)**内联给 Gemini 3.1 Pro,跟官网「直接上传视频」同一条能力:
|
|
模型能看全片、听口播,不会只拿到稀疏静帧。文件太大塞不进请求时,才退回 ffmpeg 抽帧。
|
|
|
|
拆视频必须会看视频/图。默认语言模型现在可能是纯文本豆包,不能用 get_default_model(TEXT)。
|
|
固定钉 Gemini 3.1 Pro 官转(``gemini-3.1-pro-preview``,展示名带「官转」优先)。
|
|
"""
|
|
|
|
from __future__ import annotations
|
|
|
|
import base64
|
|
import json
|
|
import logging
|
|
import math
|
|
import re
|
|
import shutil
|
|
import subprocess
|
|
import tempfile
|
|
import uuid
|
|
from dataclasses import dataclass
|
|
from functools import lru_cache
|
|
from pathlib import Path
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
from django.conf import settings
|
|
|
|
# 上传限制:超了直接 400,不进 ffmpeg,也不花模型钱
|
|
ALLOWED_SUFFIXES = (".mp4", ".mov", ".m4v", ".webm")
|
|
MAX_UPLOAD_BYTES = 200 * 1024 * 1024 # 200 MB
|
|
MAX_DURATION_SECONDS = 180 # 3 分钟。带货参考片远短于此;更长的帧采样密度不够,拆出来也是错的
|
|
|
|
# 官网直接传视频的上限大约是请求 20MB;base64 会胀到 4/3,所以原文件卡在 15MB。
|
|
INLINE_VIDEO_MAX_BYTES = 15 * 1024 * 1024
|
|
_SUFFIX_MIME = {
|
|
".mp4": "video/mp4",
|
|
".m4v": "video/mp4",
|
|
".mov": "video/quicktime",
|
|
".webm": "video/webm",
|
|
}
|
|
|
|
# 抽帧只在整段视频塞不进请求时启用。
|
|
SECONDS_PER_FRAME = 2
|
|
MIN_FRAMES = 8
|
|
MAX_FRAMES = 36
|
|
FRAME_WIDTH = 768
|
|
FRAME_QUALITY = 3
|
|
DIGEST_MAX_TOKENS = 8192
|
|
_SHOT_MARK = re.compile(r"【第\s*\d+\s*镜】")
|
|
|
|
_FFMPEG_TIMEOUT = 60
|
|
|
|
|
|
class VideoDigestError(ValueError):
|
|
"""用户可见的失败(文件不合格 / ffmpeg 读不动),一律 400。"""
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class VideoFrame:
|
|
at_seconds: int
|
|
jpeg: bytes
|
|
|
|
def as_data_url(self) -> str:
|
|
return "data:image/jpeg;base64," + base64.b64encode(self.jpeg).decode("ascii")
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class DigestVideo:
|
|
mime: str
|
|
data: bytes
|
|
|
|
def as_data_url(self) -> str:
|
|
return f"data:{self.mime};base64," + base64.b64encode(self.data).decode("ascii")
|
|
|
|
|
|
# --------------------------------------------------------------------------- #
|
|
# skill 加载
|
|
# --------------------------------------------------------------------------- #
|
|
def _skill_dir() -> Path:
|
|
"""与 script_agent._skill_dir 同源:优先 BASE_DIR/skills(镜像内),回落仓库根(本地旧布局)。"""
|
|
base = Path(settings.BASE_DIR)
|
|
for cand in (base / "skills", base.parent.parent / "skills"):
|
|
if (cand / "video-shot-digest").is_dir():
|
|
return cand / "video-shot-digest"
|
|
return base / "skills" / "video-shot-digest"
|
|
|
|
|
|
@lru_cache(maxsize=1)
|
|
def load_digest_skill() -> str:
|
|
main = _skill_dir() / "SKILL.md"
|
|
if main.exists():
|
|
return main.read_text(encoding="utf-8")
|
|
# 兜底:skill 丢了也别整条链路挂掉,退化成一句话提示词(产出会明显变差,交接文档已注明须带 skills 目录)
|
|
return (
|
|
"你是分镜拆解 agent。输入是一条电商短视频的完整文件,含画面和口播。"
|
|
"必须覆盖全片,从 0 秒写到片尾,有几镜写几镜,不要概括成几大段。"
|
|
"每镜写画面和解说词,解说词按听到的口播逐字写。输出中文纯文本。"
|
|
)
|
|
|
|
|
|
# --------------------------------------------------------------------------- #
|
|
# ffmpeg:探时长 + 抽帧
|
|
# --------------------------------------------------------------------------- #
|
|
def _binary(name: str) -> str:
|
|
found = shutil.which(name)
|
|
if not found:
|
|
raise VideoDigestError("服务器暂时无法解析视频,请稍后再试")
|
|
return found
|
|
|
|
|
|
def probe_duration(path: str | Path) -> float:
|
|
"""ffprobe 读时长(秒)。读不到 = 不是能解的视频。"""
|
|
try:
|
|
out = subprocess.run(
|
|
[
|
|
_binary("ffprobe"), "-v", "error",
|
|
"-print_format", "json", "-show_format",
|
|
str(path),
|
|
],
|
|
capture_output=True, timeout=_FFMPEG_TIMEOUT, check=True,
|
|
).stdout
|
|
duration = float(json.loads(out)["format"]["duration"])
|
|
except VideoDigestError:
|
|
raise
|
|
except Exception as exc: # noqa: BLE001 — ffprobe 各种失败对用户是同一件事
|
|
raise VideoDigestError("这个视频读不出来,请换一个 mp4 / mov 文件") from exc
|
|
if duration <= 0:
|
|
raise VideoDigestError("这个视频读不出来,请换一个 mp4 / mov 文件")
|
|
return duration
|
|
|
|
|
|
def plan_frame_times(duration: float) -> list[int]:
|
|
"""均匀采样时间点。取每段的**中点**,避开首尾黑场与片尾卡片。"""
|
|
count = max(MIN_FRAMES, min(MAX_FRAMES, math.ceil(duration / SECONDS_PER_FRAME)))
|
|
step = duration / count
|
|
return [int(step * (i + 0.5)) for i in range(count)]
|
|
|
|
|
|
def extract_frames(path: str | Path, times: list[int]) -> list[VideoFrame]:
|
|
"""逐时间点抽一帧。``-ss`` 放在 ``-i`` 前走关键帧快速定位,每帧约几十毫秒。"""
|
|
ffmpeg = _binary("ffmpeg")
|
|
frames: list[VideoFrame] = []
|
|
for at in times:
|
|
try:
|
|
done = subprocess.run(
|
|
[
|
|
ffmpeg, "-v", "error", "-ss", str(at), "-i", str(path),
|
|
"-frames:v", "1", "-vf", f"scale={FRAME_WIDTH}:-2",
|
|
"-q:v", str(FRAME_QUALITY), "-f", "image2", "-",
|
|
],
|
|
capture_output=True, timeout=_FFMPEG_TIMEOUT, check=True,
|
|
)
|
|
except Exception: # noqa: BLE001 — 单帧抽失败(定位越界等)跳过,别拖垮整次提炼
|
|
continue
|
|
if done.stdout:
|
|
frames.append(VideoFrame(at_seconds=at, jpeg=done.stdout))
|
|
if not frames:
|
|
raise VideoDigestError("没能从这个视频里取到画面,请换一个文件")
|
|
return frames
|
|
|
|
|
|
def _write_upload(upload) -> tuple[str, str, int]:
|
|
"""校验后缀和体积,把上传落到临时文件。返回 (path, suffix, size)。调用方负责删除。"""
|
|
name = (getattr(upload, "name", "") or "").lower()
|
|
if not name.endswith(ALLOWED_SUFFIXES):
|
|
raise VideoDigestError("只支持 mp4 / mov / m4v / webm 四种视频格式")
|
|
size = getattr(upload, "size", 0) or 0
|
|
if size > MAX_UPLOAD_BYTES:
|
|
raise VideoDigestError(f"视频不能超过 {MAX_UPLOAD_BYTES // 1024 // 1024} MB,请压缩后再传")
|
|
suffix = Path(name).suffix or ".mp4"
|
|
tmp = tempfile.NamedTemporaryFile(suffix=suffix, delete=False)
|
|
try:
|
|
for chunk in upload.chunks():
|
|
tmp.write(chunk)
|
|
tmp.flush()
|
|
finally:
|
|
tmp.close()
|
|
return tmp.name, suffix, Path(tmp.name).stat().st_size
|
|
|
|
|
|
def _materialize_upload(upload) -> tuple[str, str, int, float]:
|
|
"""校验 → 落盘 → 探时长。返回 (path, suffix, size, duration),调用方负责删文件。"""
|
|
path, suffix, size = _write_upload(upload)
|
|
try:
|
|
duration = probe_duration(path)
|
|
except Exception:
|
|
Path(path).unlink(missing_ok=True)
|
|
raise
|
|
if duration > MAX_DURATION_SECONDS:
|
|
Path(path).unlink(missing_ok=True)
|
|
raise VideoDigestError(
|
|
f"视频不能超过 {MAX_DURATION_SECONDS // 60} 分钟,请剪出要参考的那一段再传"
|
|
)
|
|
return path, suffix, size, duration
|
|
|
|
|
|
def _compress_video(path: str) -> bytes | None:
|
|
"""压到能内联的体积。失败返回 None,由调用方改抽帧。"""
|
|
ffmpeg = _binary("ffmpeg")
|
|
out = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False)
|
|
out.close()
|
|
try:
|
|
done = subprocess.run(
|
|
[
|
|
ffmpeg, "-v", "error", "-y", "-i", path,
|
|
"-c:v", "libx264", "-preset", "veryfast", "-crf", "28",
|
|
"-vf", "scale='min(1280,iw)':-2",
|
|
"-c:a", "aac", "-b:a", "64k",
|
|
"-movflags", "+faststart", out.name,
|
|
],
|
|
capture_output=True, timeout=_FFMPEG_TIMEOUT * 3,
|
|
)
|
|
if done.returncode != 0:
|
|
return None
|
|
data = Path(out.name).read_bytes()
|
|
if not data or len(data) > INLINE_VIDEO_MAX_BYTES:
|
|
return None
|
|
return data
|
|
except Exception: # noqa: BLE001 — 压缩失败就抽帧,别挡住提炼
|
|
return None
|
|
finally:
|
|
Path(out.name).unlink(missing_ok=True)
|
|
|
|
|
|
def _native_video(path: str, size: int, suffix: str) -> DigestVideo | None:
|
|
mime = _SUFFIX_MIME.get(suffix.lower(), "video/mp4")
|
|
if size <= INLINE_VIDEO_MAX_BYTES:
|
|
return DigestVideo(mime=mime, data=Path(path).read_bytes())
|
|
compressed = _compress_video(path)
|
|
if compressed:
|
|
return DigestVideo(mime="video/mp4", data=compressed)
|
|
return None
|
|
|
|
|
|
def digest_input_from_upload(upload) -> tuple[DigestVideo | None, list[VideoFrame], float]:
|
|
"""优先整段视频(含音轨);塞不进请求才抽帧。"""
|
|
path = ""
|
|
try:
|
|
path, suffix, size, duration = _materialize_upload(upload)
|
|
video = _native_video(path, size, suffix)
|
|
if video is not None:
|
|
return video, [], duration
|
|
return None, extract_frames(path, plan_frame_times(duration)), duration
|
|
finally:
|
|
if path:
|
|
Path(path).unlink(missing_ok=True)
|
|
|
|
|
|
def frames_from_upload(upload) -> tuple[list[VideoFrame], float]:
|
|
"""校验上传文件 → 落临时盘 → 探时长 → 抽帧。单测与抽帧兜底用。"""
|
|
path = ""
|
|
try:
|
|
path, _suffix, _size, duration = _materialize_upload(upload)
|
|
return extract_frames(path, plan_frame_times(duration)), duration
|
|
finally:
|
|
if path:
|
|
Path(path).unlink(missing_ok=True)
|
|
|
|
|
|
# --------------------------------------------------------------------------- #
|
|
# 组装多模态消息
|
|
# --------------------------------------------------------------------------- #
|
|
def build_digest_messages(
|
|
frames: list[VideoFrame] | None = None,
|
|
duration: float = 0,
|
|
*,
|
|
product_hint: str = "",
|
|
video: DigestVideo | None = None,
|
|
) -> list[dict]:
|
|
"""system = 拆解 skill;user = 完整视频(优先)或抽帧。"""
|
|
frames = frames or []
|
|
if video is not None:
|
|
head = [
|
|
f"这是一条时长约 {round(duration)} 秒的电商带货短视频的**完整文件**(含画面和口播音轨)。",
|
|
"请按技能还原全片分镜:从 0 秒写到片尾,有几镜写几镜。",
|
|
"解说词按听到的口播逐字写;画面上的花字一并写进画面。",
|
|
]
|
|
else:
|
|
head = [
|
|
f"这是一条时长约 {round(duration)} 秒的电商带货短视频,",
|
|
f"按时间顺序均匀抽了 {len(frames)} 帧。每帧图前面标了它在原片中的时间点。",
|
|
"请按技能还原**全片**分镜:从 0 秒写到片尾,有几镜写几镜。",
|
|
]
|
|
if product_hint:
|
|
head.append(f"用户接下来想用这条片子的结构去拍自己的商品:{product_hint}。")
|
|
|
|
content: list[dict] = [{"type": "text", "text": "".join(head)}]
|
|
if video is not None:
|
|
data_url = video.as_data_url()
|
|
# 官转(New-API)把 OpenAI image_url 的 data URI 转成 Gemini inline_data,
|
|
# mime 从 data:video/mp4 头读取,模型按整段视频+音轨理解,等同官网直接上传。
|
|
content.append({"type": "image_url", "image_url": {"url": data_url}})
|
|
else:
|
|
for frame in frames:
|
|
content.append({"type": "text", "text": f"[第 {frame.at_seconds} 秒]"})
|
|
content.append({"type": "image_url", "image_url": {"url": frame.as_data_url()}})
|
|
return [
|
|
{"role": "system", "content": load_digest_skill()},
|
|
{"role": "user", "content": content},
|
|
]
|
|
|
|
|
|
def min_digest_shots(duration: float, frame_count: int) -> int:
|
|
"""短片至少 3 镜;20 秒以上约每 6 秒一镜,且不超过抽到的帧数。"""
|
|
if duration < 20 and frame_count < 8:
|
|
return 3
|
|
by_time = max(4, int(duration // 6))
|
|
if frame_count:
|
|
return min(frame_count, by_time)
|
|
return by_time
|
|
|
|
|
|
def validate_digest_text(text: str, *, duration: float = 0, frame_count: int = 0) -> str:
|
|
"""模型偶尔吐空、只写片头、或概括成几大段。废稿不塞给用户。"""
|
|
cleaned = (text or "").strip()
|
|
if len(cleaned) < 80 or "【" not in cleaned:
|
|
raise ValueError("视频拆解结果不完整")
|
|
shots = _SHOT_MARK.findall(cleaned)
|
|
if not shots:
|
|
raise ValueError("视频拆解结果不完整")
|
|
if duration >= 20 or frame_count >= 8:
|
|
needed = min_digest_shots(duration, frame_count)
|
|
if len(shots) < needed:
|
|
raise ValueError("视频拆解镜头过少,请重试")
|
|
return cleaned
|
|
|
|
|
|
# 拆视频必须会看图。火山豆包直连读不了这组帧图,会在 ARK 上挂满 120s。
|
|
# 只认中转站的 Gemini 3.1 Pro;展示名带「官转」的优先。
|
|
DIGEST_VISION_MODEL_NAME = "gemini-3.1-pro-preview"
|
|
|
|
|
|
def _is_digest_vision_model(model) -> bool:
|
|
from apps.ai.services import OFFICIAL_DIRECT_PROVIDERS
|
|
|
|
provider_name = getattr(getattr(model, "provider", None), "name", "") or ""
|
|
if provider_name in OFFICIAL_DIRECT_PROVIDERS:
|
|
return False
|
|
blob = f"{model.name} {model.display_name}".lower()
|
|
return (
|
|
model.name == DIGEST_VISION_MODEL_NAME
|
|
or "gemini-3.1" in blob
|
|
or "gemini 3.1" in blob
|
|
)
|
|
|
|
|
|
def resolve_digest_model_config(preferred_id=None):
|
|
"""视频提炼用的多模态文本模型:Gemini 3.1 Pro 官转。找不到不回落默认语言模型。
|
|
|
|
前端可传 model_config_id(跟生成脚本同一套下拉)。只有会看图的 Gemini 3.1 才认,
|
|
选了豆包等纯文本模型仍钉回官转,避免拆帧直接失败。
|
|
"""
|
|
from apps.ai.models import ModelConfig
|
|
|
|
qs = (
|
|
ModelConfig.objects.select_related("provider")
|
|
.filter(
|
|
capability=ModelConfig.Capability.TEXT,
|
|
status=ModelConfig.Status.ACTIVE,
|
|
provider__status="active",
|
|
)
|
|
)
|
|
if preferred_id:
|
|
chosen = qs.filter(pk=preferred_id).first()
|
|
if chosen is not None and _is_digest_vision_model(chosen):
|
|
return chosen
|
|
|
|
def _blob(model) -> str:
|
|
return " ".join(
|
|
filter(
|
|
None,
|
|
[
|
|
model.name,
|
|
model.display_name,
|
|
getattr(model.provider, "name", ""),
|
|
getattr(model.provider, "display_name", ""),
|
|
],
|
|
)
|
|
)
|
|
|
|
ranked = []
|
|
for model in qs:
|
|
if not _is_digest_vision_model(model):
|
|
continue
|
|
blob = _blob(model)
|
|
# 官转 > 精确模型名 > 其它 Gemini 3.1
|
|
score = 0
|
|
if "官转" in blob:
|
|
score += 100
|
|
if model.name == DIGEST_VISION_MODEL_NAME:
|
|
score += 20
|
|
if getattr(model.provider, "name", "") == "yunqi_gemini":
|
|
score += 5
|
|
ranked.append((score, model.created_at, model))
|
|
if not ranked:
|
|
return None
|
|
ranked.sort(key=lambda item: (-item[0], item[1]))
|
|
return ranked[0][2]
|
|
|
|
|
|
# --------------------------------------------------------------------------- #
|
|
# 入口:一次真实的计费调用
|
|
# --------------------------------------------------------------------------- #
|
|
def digest_project_video(*, project, user, upload, model_config_id=None) -> dict:
|
|
"""上传视频 → 分镜稿。抽帧在建任务之前做,文件不合格不占积分。"""
|
|
product = getattr(project, "product", None)
|
|
return _digest_video(
|
|
team=project.team,
|
|
user=user,
|
|
upload=upload,
|
|
project=project,
|
|
product_hint=" · ".join(
|
|
filter(None, [getattr(product, "title", ""), getattr(product, "category", "")])
|
|
),
|
|
model_config_id=model_config_id,
|
|
)
|
|
|
|
|
|
def digest_team_video(*, team, user, upload, model_config_id=None) -> dict:
|
|
"""视频提炼页:不绑项目,计费挂当前团队。"""
|
|
return _digest_video(
|
|
team=team,
|
|
user=user,
|
|
upload=upload,
|
|
project=None,
|
|
product_hint="",
|
|
model_config_id=model_config_id,
|
|
)
|
|
|
|
|
|
def _digest_video(*, team, user, upload, project=None, product_hint="", model_config_id=None) -> dict:
|
|
"""上传视频 → 分镜稿。抽帧在建任务之前做,文件不合格不占积分。"""
|
|
from django.db import transaction
|
|
from django.utils import timezone
|
|
|
|
from apps.ai.models import AITask
|
|
from apps.ai.services import create_ai_task, execute_routed_text_request
|
|
from apps.billing.pricing import quote_video_digest
|
|
from apps.billing.services.ledger import charge_reserved_credit, reserve_credit
|
|
|
|
video, frames, duration = digest_input_from_upload(upload)
|
|
|
|
model_config = resolve_digest_model_config(preferred_id=model_config_id)
|
|
if model_config is None:
|
|
raise VideoDigestError("视频提炼需要 Gemini 3.1 Pro(会看图),当前没有启用,请联系管理员")
|
|
logger.info(
|
|
"video digest using %s:%s (%s) input=%s duration=%.1fs bytes=%s frames=%s",
|
|
model_config.provider.name,
|
|
model_config.name,
|
|
model_config.display_name,
|
|
"native_video" if video is not None else "frames",
|
|
duration,
|
|
len(video.data) if video is not None else 0,
|
|
len(frames),
|
|
)
|
|
|
|
messages = build_digest_messages(
|
|
frames, duration, product_hint=product_hint, video=video
|
|
)
|
|
request_payload = {
|
|
"model": model_config.name,
|
|
"endpoint": model_config.endpoint,
|
|
"feature": "video_remix" if project is None else "video_digest",
|
|
"duration_seconds": round(duration, 2),
|
|
"input": "native_video" if video is not None else "frames",
|
|
"frame_count": len(frames),
|
|
"video_bytes": len(video.data) if video is not None else 0,
|
|
"frame_times": [f.at_seconds for f in frames],
|
|
}
|
|
|
|
quote = quote_video_digest(team=team, model_config=model_config)
|
|
if quote.meta.get("rate"):
|
|
request_payload = {**request_payload, "points_per_yuan_snapshot": quote.meta["rate"]}
|
|
|
|
if project is not None:
|
|
task = create_ai_task(
|
|
project=project,
|
|
user=user,
|
|
task_type=AITask.Type.VIDEO_DIGEST,
|
|
model_config=model_config,
|
|
# 帧是几百 KB base64,绝不进 request_payload(会把 AITask 表撑爆),只记形状
|
|
request_payload=request_payload,
|
|
quote=quote,
|
|
)
|
|
else:
|
|
try:
|
|
with transaction.atomic():
|
|
task = AITask.objects.create(
|
|
team=team,
|
|
created_by=user,
|
|
project=None,
|
|
task_type=AITask.Type.VIDEO_DIGEST,
|
|
status=AITask.Status.CREATED,
|
|
model_config=model_config,
|
|
idempotency_key=f"video_digest:{team.id}:{uuid.uuid4()}",
|
|
request_payload=request_payload,
|
|
estimated_cost=quote.points,
|
|
base_cost=quote.base_cost_yuan,
|
|
)
|
|
reserve_credit(team=team, user=user, task=task, amount=quote.points)
|
|
task.status = AITask.Status.RESERVED
|
|
task.save(update_fields=["status", "updated_at"])
|
|
except ValueError as exc:
|
|
if "insufficient credit" in str(exc).lower():
|
|
raise VideoDigestError("团队余额不足，请充值后重试") from exc
|
|
raise VideoDigestError(str(exc)) from exc
|
|
reservation = task.credit_reservation
|
|
try:
|
|
task.status = AITask.Status.SUBMITTED
|
|
task.submitted_at = timezone.now()
|
|
task.save(update_fields=["status", "submitted_at", "updated_at"])
|
|
routed = execute_routed_text_request(
|
|
task=task,
|
|
primary_model=model_config,
|
|
messages=messages,
|
|
streaming=True,
|
|
structured_output=False,
|
|
business_operation="video_digest",
|
|
temperature=0.4,
|
|
validate_text=lambda text: validate_digest_text(
|
|
text, duration=duration, frame_count=len(frames) or (24 if video else 0)
|
|
),
|
|
extra_body={"max_tokens": DIGEST_MAX_TOKENS},
|
|
request_summary={
|
|
"duration_seconds": round(duration, 2),
|
|
"frame_count": len(frames),
|
|
"input": "native_video" if video is not None else "frames",
|
|
},
|
|
allow_retry=False,
|
|
allow_fallback=False,
|
|
)
|
|
_text, _response, digest = routed.value
|
|
except Exception as exc: # noqa: BLE001
|
|
_fail_digest_task(task, reservation, str(exc))
|
|
raise
|
|
|
|
with transaction.atomic():
|
|
task.status = AITask.Status.SUCCEEDED
|
|
task.response_payload = {"digest": digest[:32000]}
|
|
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)
|
|
|
|
return {
|
|
"text": digest,
|
|
"chars": len(digest),
|
|
"frames": len(frames),
|
|
"input": "native_video" if video is not None else "frames",
|
|
"duration": round(duration, 1),
|
|
"task_id": str(task.id),
|
|
"estimated_cost": str(task.estimated_cost),
|
|
}
|
|
|
|
|
|
def _fail_digest_task(task, reservation, message: str) -> None:
|
|
from django.utils import timezone
|
|
|
|
from apps.ai.models import AITask
|
|
from apps.billing.services.ledger import release_credit
|
|
|
|
try:
|
|
task.status = AITask.Status.FAILED
|
|
task.error_message = message[:2000]
|
|
task.completed_at = timezone.now()
|
|
task.save(update_fields=["status", "error_message", "completed_at", "updated_at"])
|
|
finally:
|
|
try:
|
|
release_credit(reservation=reservation, reason=message[:200])
|
|
except Exception: # noqa: BLE001
|
|
pass
|