Compare commits
1 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 9dbe6e4283 |
@@ -1022,22 +1022,12 @@ jobs:
|
||||
BRANCH_TAG="${IMAGE_FULL}:${GITHUB_REF_NAME}"
|
||||
CACHE_REF="${REGISTRY}/${{ matrix.cache_name }}:${GITHUB_REF_NAME}"
|
||||
|
||||
# develop 分支额外推送 :dev tag(Watchtower 监听的滚动更新 tag)
|
||||
if [ "${GITHUB_REF_NAME}" = "develop" ]; then
|
||||
DEV_TAG="${IMAGE_FULL}:dev"
|
||||
EXTRA_TAGS="$BRANCH_TAG $DEV_TAG"
|
||||
PUSHED_TAGS_SUMMARY="${BRANCH_TAG} + ${DEV_TAG}"
|
||||
else
|
||||
EXTRA_TAGS="$BRANCH_TAG"
|
||||
PUSHED_TAGS_SUMMARY="${BRANCH_TAG}"
|
||||
fi
|
||||
|
||||
EXTRA_BUILD_ARGS="APP_VERSION=\"${GITHUB_SHA}\""
|
||||
|
||||
NO_CACHE_FLAG=""
|
||||
for i in 1 2 3; do
|
||||
echo "=== Docker build 尝试 $i/3 (${{ matrix.service_display }}) ==="
|
||||
if EXTRA_TAGS="$EXTRA_TAGS" bash scripts/ci/docker_build_push.sh $NO_CACHE_FLAG ${{ matrix.dockerfile }} "${IMAGE_TAG}" "${CACHE_REF}" $EXTRA_BUILD_ARGS; then
|
||||
if EXTRA_TAGS="$BRANCH_TAG" bash scripts/ci/docker_build_push.sh $NO_CACHE_FLAG ${{ matrix.dockerfile }} "${IMAGE_TAG}" "${CACHE_REF}" $EXTRA_BUILD_ARGS; then
|
||||
echo "✅ Docker build 成功"
|
||||
break
|
||||
fi
|
||||
@@ -1050,7 +1040,7 @@ jobs:
|
||||
fi
|
||||
done
|
||||
|
||||
echo "${{ matrix.service_display }} image pushed: ${IMAGE_TAG} (+ ${PUSHED_TAGS_SUMMARY})"
|
||||
echo "${{ matrix.service_display }} image pushed: ${IMAGE_TAG} (+ ${BRANCH_TAG})"
|
||||
|
||||
- name: Job duration summary
|
||||
if: always()
|
||||
@@ -1254,11 +1244,9 @@ jobs:
|
||||
ACR_PASSWORD: ${{ secrets.ACR_PASSWORD }}
|
||||
run: |
|
||||
set -eux
|
||||
# CI runner (act_runner) 部署在 116 staging 本机(116.62.226.203 公网 22 未开放),
|
||||
# 默认走 127.0.0.1:22 本机 SSH,避免跨机网络依赖;可通过 secrets 覆盖。
|
||||
staging_host="${STAGING_SSH_HOST:-127.0.0.1}"
|
||||
staging_host="${STAGING_SSH_HOST:-47.98.113.167}"
|
||||
staging_user="${STAGING_SSH_USER:-root}"
|
||||
staging_port="${STAGING_SSH_PORT:-22}"
|
||||
staging_port="${STAGING_SSH_PORT:-22222}"
|
||||
echo "Host: $staging_host"
|
||||
echo "Port: $staging_port"
|
||||
|
||||
@@ -1482,6 +1470,7 @@ jobs:
|
||||
- validate-security
|
||||
- validate-python
|
||||
- unit-tests
|
||||
- frontend-lint
|
||||
- frontend-unit-test
|
||||
if: github.event_name == 'push' && github.ref_name == 'main' && !failure() && !cancelled()
|
||||
strategy:
|
||||
@@ -2135,4 +2124,3 @@ jobs:
|
||||
START_TIME=""
|
||||
[ -f /tmp/ci_job_start_time ] && START_TIME=$(cat /tmp/ci_job_start_time)
|
||||
curl -sfH "Authorization: token ${GITHUB_TOKEN:-$GITEA_TOKEN}" -o /tmp/_ci_trace.py "${GITHUB_API_URL}/repos/${GITHUB_REPOSITORY}/raw/scripts/ci/ci_trace_report.py?ref=${GITHUB_SHA}" 2>/dev/null && python3 /tmp/_ci_trace.py --service xiaoxia-saas-ci --status $STATUS --start-time "$START_TIME" || true
|
||||
# CI retry trigger
|
||||
|
||||
@@ -0,0 +1,29 @@
|
||||
name: "Verify staging post-deploy"
|
||||
on:
|
||||
push:
|
||||
branches: [debug/verify-staging]
|
||||
workflow_dispatch:
|
||||
jobs:
|
||||
verify:
|
||||
runs-on: runtime-builder
|
||||
timeout-minutes: 10
|
||||
steps:
|
||||
- name: Setup SSH
|
||||
shell: bash
|
||||
env:
|
||||
STAGING_SSH_KEY: ${{ secrets.PREVIEW_SSH_KEY }}
|
||||
run: |
|
||||
set -eux
|
||||
which ssh || (apt-get update -qq && apt-get install -y -qq openssh-client)
|
||||
mkdir -p ~/.ssh && chmod 700 ~/.ssh
|
||||
printf "%s" "$STAGING_SSH_KEY" > ~/.ssh/id_rsa
|
||||
chmod 600 ~/.ssh/id_rsa
|
||||
H=47.98.113.167; P=22222
|
||||
ssh-keyscan -p $P -H $H >> ~/.ssh/known_hosts 2>/dev/null
|
||||
- name: Run verify
|
||||
shell: bash
|
||||
run: |
|
||||
set -x
|
||||
echo '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' | base64 -d > /tmp/verify.sh
|
||||
chmod +x /tmp/verify.sh
|
||||
ssh -p 22222 -i ~/.ssh/id_rsa -o StrictHostKeyChecking=no root@47.98.113.167 'bash -s' < /tmp/verify.sh
|
||||
@@ -1 +0,0 @@
|
||||
retrigger3
|
||||
@@ -263,4 +263,3 @@ pytest --cov=packages --cov-report=html
|
||||
---
|
||||
|
||||
**License**: MIT
|
||||
<!-- CI trigger: 1788229339 -->
|
||||
@@ -1,27 +0,0 @@
|
||||
"""add sentence_timings to lipsync_jobs
|
||||
|
||||
Revision ID: 075_add_sentence_timings
|
||||
Revises: 074_ai_avatar_render_script_id_optional
|
||||
Create Date: 2026-09-12
|
||||
"""
|
||||
|
||||
import sqlalchemy as sa
|
||||
|
||||
from alembic import op
|
||||
|
||||
revision = "075_add_sentence_timings"
|
||||
down_revision = "074_render_script_id_optional"
|
||||
branch_labels = None
|
||||
depends_on = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
with op.batch_alter_table("lipsync_jobs") as batch:
|
||||
batch.add_column(
|
||||
sa.Column("sentence_timings", sa.JSON(), nullable=True),
|
||||
)
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
with op.batch_alter_table("lipsync_jobs") as batch:
|
||||
batch.drop_column("sentence_timings")
|
||||
@@ -11,14 +11,13 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from datetime import datetime, timezone
|
||||
|
||||
from app.auth import AuthenticatedUser, get_current_user
|
||||
from app.dependencies import get_db_session
|
||||
from app.schemas.ai_avatar_render import (
|
||||
AiAvatarRenderJobResponse,
|
||||
CreateAiAvatarRenderRequest,
|
||||
FinalizeRenderResponse,
|
||||
SmartCoverRequest,
|
||||
SmartCoverResponse,
|
||||
)
|
||||
from app.services.ai_avatar_cover_service import generate_smart_cover
|
||||
@@ -78,16 +77,10 @@ def create_render_job(
|
||||
from app.tasks.ai_avatar_render import execute_ai_avatar_render
|
||||
|
||||
execute_ai_avatar_render.delay(job.id)
|
||||
except Exception as exc:
|
||||
logger.exception("Celery 任务投递失败(创建): job_id=%s err=%s", job.id, exc)
|
||||
job.status = "failed"
|
||||
job.error_message = f"任务提交失败:{exc}"
|
||||
job.updated_at = datetime.now(timezone.utc)
|
||||
svc.db.commit()
|
||||
svc.db.refresh(job)
|
||||
return AiAvatarRenderJobResponse.model_validate(job)
|
||||
except Exception:
|
||||
logger.warning("Celery 任务提交失败,渲染任务已创建但未触发执行: %s", job.id)
|
||||
|
||||
return AiAvatarRenderJobResponse.model_validate(job)
|
||||
return job
|
||||
|
||||
|
||||
# ── GET /jobs — 任务列表 ─────────────────────────────────────────────────
|
||||
@@ -179,54 +172,38 @@ def retry_render_job(
|
||||
from app.tasks.ai_avatar_render import execute_ai_avatar_render
|
||||
|
||||
execute_ai_avatar_render.delay(job.id)
|
||||
except Exception as exc:
|
||||
logger.exception("Celery 任务投递失败(重试): job_id=%s err=%s", job.id, exc)
|
||||
job.status = "failed"
|
||||
job.error_message = f"任务提交失败:{exc}"
|
||||
job.updated_at = datetime.now(timezone.utc)
|
||||
svc.db.commit()
|
||||
svc.db.refresh(job)
|
||||
return AiAvatarRenderJobResponse.model_validate(job)
|
||||
except Exception:
|
||||
logger.warning("Celery 任务提交失败,重试任务已重置但未触发执行: %s", job.id)
|
||||
|
||||
return AiAvatarRenderJobResponse.model_validate(job)
|
||||
return job
|
||||
|
||||
|
||||
# ── POST /{job_id}/smart-cover — 从最终成片智能抽封面(步骤②)────────
|
||||
|
||||
# ── POST /smart-cover — 智能获取封面(MediaKit 抽帧 + 评分选帧)────────
|
||||
|
||||
|
||||
@router.post("/{job_id}/smart-cover", response_model=SmartCoverResponse)
|
||||
def generate_render_smart_cover(
|
||||
job_id: str,
|
||||
@router.post("/smart-cover", response_model=SmartCoverResponse)
|
||||
def generate_avatar_smart_cover(
|
||||
body: SmartCoverRequest,
|
||||
current_user: AuthenticatedUser = Depends(get_current_user),
|
||||
db: Session = Depends(get_db_session),
|
||||
):
|
||||
"""从最终渲染成片智能抽帧生成封面(MediaKit 抽帧 + 评分选最佳帧 + 转存 OSS).
|
||||
) -> SmartCoverResponse:
|
||||
"""智能获取数字人视频封面.
|
||||
|
||||
- 必须等渲染任务 completed 后才可调用(否则返回 400)
|
||||
- 生成成功后自动更新 render_job 的 cover_config 与 output_cover_url
|
||||
复用智能剪辑的 MediaKit 抽帧 + 质量评分选最佳帧逻辑(非 FFmpeg 简单截帧),
|
||||
并将选中帧转存到自家 OSS,返回非临时的封面公网 URL。
|
||||
|
||||
前端「智能获取封面」按钮可直接调用本接口;不依赖渲染任务完成。
|
||||
"""
|
||||
from app.services.ai_avatar_render_service import AiAvatarRenderService
|
||||
|
||||
svc = AiAvatarRenderService(db)
|
||||
job = svc.get_render_job(job_id, current_user.user.id)
|
||||
if job is None:
|
||||
raise HTTPException(status_code=404, detail="渲染任务不存在")
|
||||
if job.status != "completed":
|
||||
raise HTTPException(status_code=400, detail="请先完成视频生成")
|
||||
video_url = (job.output_video_url or "").strip()
|
||||
if not video_url:
|
||||
raise HTTPException(status_code=400, detail="渲染成片视频 URL 为空")
|
||||
video_url = (body.video_url or "").strip()
|
||||
if not video_url.startswith(("http://", "https://")):
|
||||
raise HTTPException(status_code=400, detail="video_url 必须是合法的 HTTP/HTTPS URL")
|
||||
|
||||
try:
|
||||
# 从最终成片抽帧,帧本身已含标题/B-roll,直接转存 OSS
|
||||
cover_url = generate_smart_cover(video_url, job_id=job_id, max_frames=5)
|
||||
cover_url = generate_smart_cover(video_url, max_frames=body.max_frames)
|
||||
except Exception as exc:
|
||||
logger.error(
|
||||
"渲染成片智能封面生成异常: user=%s render_id=%s video_url=%s err=%s",
|
||||
current_user.user.id,
|
||||
job_id,
|
||||
video_url[:80],
|
||||
exc,
|
||||
"智能封面生成异常: user=%s video_url=%s err=%s",
|
||||
current_user.user.id, video_url[:80], exc,
|
||||
exc_info=True,
|
||||
)
|
||||
cover_url = ""
|
||||
@@ -237,88 +214,5 @@ def generate_render_smart_cover(
|
||||
status="fallback_failed",
|
||||
message="智能抽帧失败(MediaKit 不可用或抽帧异常),请稍后重试",
|
||||
)
|
||||
|
||||
# 更新 render_job 的封面字段(异步写入 DB;失败不影响返回)
|
||||
try:
|
||||
job.cover_config = {
|
||||
**(job.cover_config if isinstance(job.cover_config, dict) else {}),
|
||||
"mode": "auto_frame",
|
||||
"url": cover_url,
|
||||
}
|
||||
job.output_cover_url = cover_url
|
||||
job.updated_at = datetime.now(timezone.utc)
|
||||
db.commit()
|
||||
except Exception as exc:
|
||||
logger.warning("更新 render_job 封面字段失败(不影响返回): job_id=%s err=%s", job_id, exc)
|
||||
|
||||
logger.info(
|
||||
"渲染成片智能封面生成成功: user=%s render_id=%s cover_url=%s",
|
||||
current_user.user.id,
|
||||
job_id,
|
||||
cover_url[:120],
|
||||
)
|
||||
logger.info("智能封面生成成功: user=%s cover_url=%s", current_user.user.id, cover_url[:120])
|
||||
return SmartCoverResponse(cover_url=cover_url, status="completed")
|
||||
|
||||
# ── POST /{job_id}/finalize — 封面选定后正式入库成片库 ────────────────────
|
||||
|
||||
|
||||
@router.post("/{job_id}/finalize", response_model=FinalizeRenderResponse)
|
||||
def finalize_render_job(
|
||||
job_id: str,
|
||||
current_user: AuthenticatedUser = Depends(get_current_user),
|
||||
db: Session = Depends(get_db_session),
|
||||
):
|
||||
"""用户完成封面选择后,将视频正式保存到成片库.
|
||||
|
||||
- 必须等渲染任务 completed 后才可调用
|
||||
- 如果已通过 smart-cover/custom-cover 设置了封面,会自动带上
|
||||
- 返回成片库视频ID
|
||||
- 幂等:已 finalize 的任务重复调用会返回 existing 记录
|
||||
"""
|
||||
from app.services.ai_avatar_render_service import AiAvatarRenderError, AiAvatarRenderService
|
||||
|
||||
svc = AiAvatarRenderService(db)
|
||||
job = svc.get_render_job(job_id, current_user.user.id)
|
||||
if job is None:
|
||||
raise HTTPException(status_code=404, detail="渲染任务不存在")
|
||||
if job.status != "completed":
|
||||
raise HTTPException(status_code=400, detail="请先完成视频生成")
|
||||
|
||||
# 幂等检查(通过 generation_task_id=job_id 识别,finalize_job 内部也做了一次,这里提前返回简化)
|
||||
from packages.adapters.sqlalchemy_impl.models import GeneratedVideoModel
|
||||
|
||||
existing = (
|
||||
db.query(GeneratedVideoModel)
|
||||
.filter(
|
||||
GeneratedVideoModel.user_id == current_user.user.id,
|
||||
GeneratedVideoModel.generation_task_id == job_id,
|
||||
)
|
||||
.first()
|
||||
)
|
||||
if existing is not None:
|
||||
return FinalizeRenderResponse(
|
||||
video_id=existing.id,
|
||||
cover_url=existing.thumbnail_url or "",
|
||||
status="already_finalized",
|
||||
)
|
||||
|
||||
try:
|
||||
video = svc.finalize_job(job_id, current_user.user.id)
|
||||
return FinalizeRenderResponse(
|
||||
video_id=video.id,
|
||||
cover_url=video.thumbnail_url or job.output_cover_url or "",
|
||||
status="success",
|
||||
)
|
||||
except AiAvatarRenderError as exc:
|
||||
status_map = {
|
||||
"RenderJobNotFound": 404,
|
||||
"RenderNotCompleted": 400,
|
||||
"OutputVideoMissing": 400,
|
||||
}
|
||||
raise HTTPException(
|
||||
status_code=status_map.get(exc.code, 400),
|
||||
detail=str(exc),
|
||||
) from exc
|
||||
except Exception as exc:
|
||||
logger.error("渲染任务finalize失败: job_id=%s err=%s", job_id, exc, exc_info=True)
|
||||
raise HTTPException(status_code=500, detail=f"保存到成片库失败: {str(exc)}") from exc
|
||||
|
||||
@@ -766,12 +766,7 @@ def generate_cover(
|
||||
storage_svc = get_shared_storage_service()
|
||||
mk_client = get_mediakit_client()
|
||||
# 从 plan.config 读取完整标题样式,E2 从源素材抽帧时叠加(源素材本身无标题)
|
||||
# #1901 统一读 "title",兼容老数据 "title_config"
|
||||
_e2_title_cfg = (plan.config or {}).get("title", {}) or {}
|
||||
if not isinstance(_e2_title_cfg, dict) or not (_e2_title_cfg.get("text") or "").strip():
|
||||
_alt = (plan.config or {}).get("title_config", {}) or {}
|
||||
if isinstance(_alt, dict):
|
||||
_e2_title_cfg = _alt
|
||||
if not isinstance(_e2_title_cfg, dict):
|
||||
_e2_title_cfg = {}
|
||||
_e2_title_text = (_e2_title_cfg.get("text", "") or "").strip() if _e2_title_cfg.get("enabled", True) else ""
|
||||
|
||||
@@ -58,10 +58,27 @@ def _variant_value(values: list[str], index: int, fallback: str = "") -> str:
|
||||
|
||||
|
||||
def _query_voice_durations(db: Session, voice_ids: list[str]) -> list[float]:
|
||||
"""[已下沉] 路由层兼容别名 → app.services.generation_common.query_voice_durations。"""
|
||||
from app.services.generation_common import query_voice_durations
|
||||
"""批量查询配音素材时长(秒),#1749 配音时长分配用。
|
||||
|
||||
return query_voice_durations(db, voice_ids)
|
||||
逐项 try/float 硬化:MagicMock/异常/缺失 → 0.0(无配音不分配,不阻断)。
|
||||
"""
|
||||
ids = [v for v in dict.fromkeys(voice_ids or []) if v]
|
||||
if not ids:
|
||||
return []
|
||||
try:
|
||||
from packages.adapters.sqlalchemy_impl.models import AssetModel
|
||||
|
||||
rows = db.query(AssetModel.id, AssetModel.duration).filter(AssetModel.id.in_(ids)).all()
|
||||
dur_map: dict[str, float] = {}
|
||||
for row in rows:
|
||||
try:
|
||||
dur_map[row[0]] = float(row[1] or 0.0)
|
||||
except (TypeError, ValueError):
|
||||
dur_map[row[0]] = 0.0
|
||||
return [dur_map.get(v, 0.0) for v in ids]
|
||||
except Exception:
|
||||
logger.warning("[生成任务] 配音时长查询失败(按无配音处理,不阻断)", exc_info=True)
|
||||
return [0.0 for _ in ids]
|
||||
|
||||
|
||||
def _to_generation_task_response(task) -> GenerationTaskResponse:
|
||||
@@ -167,10 +184,61 @@ def _writeback_edit_plan_config(
|
||||
title_config: dict | None,
|
||||
db: Session,
|
||||
) -> None:
|
||||
"""[已下沉] 路由层兼容别名 → app.services.generation_common.writeback_edit_plan_config。"""
|
||||
from app.services.generation_common import writeback_edit_plan_config
|
||||
"""任务入队成功后,回写 EditPlan.config:generation_task_id + title_config。
|
||||
|
||||
return writeback_edit_plan_config(plan_id, task_id, title_config, db)
|
||||
用 merge 方式更新,不整体覆盖 config,避免丢失其他字段。
|
||||
失败只记日志,不影响任务创建。
|
||||
"""
|
||||
if not plan_id:
|
||||
return
|
||||
try:
|
||||
from packages.adapters.sqlalchemy_impl.models import EditPlanModel
|
||||
|
||||
plan_model = db.query(EditPlanModel).filter(EditPlanModel.id == plan_id).first()
|
||||
if plan_model is None:
|
||||
logger.warning("[生成任务] 回写plan.config失败: plan不存在 plan_id=%s", plan_id)
|
||||
return
|
||||
|
||||
current_config = plan_model.config if isinstance(plan_model.config, dict) else {}
|
||||
merged = dict(current_config)
|
||||
merged["generation_task_id"] = task_id
|
||||
|
||||
# 检查标题是否发生变化,如果变化则清除 cover 字段强制重新生成封面
|
||||
if title_config:
|
||||
old_title_config = merged.get("title_config", {}) or {}
|
||||
old_title_text = (old_title_config.get("text") or "").strip()
|
||||
new_title_text = (title_config.get("text") or "").strip()
|
||||
if old_title_text != new_title_text:
|
||||
# 标题变化,清除旧封面
|
||||
if "cover" in merged:
|
||||
del merged["cover"]
|
||||
logger.info(
|
||||
"[生成任务] 标题变化,清除旧封面: plan_id=%s old_title=%s new_title=%s",
|
||||
plan_id,
|
||||
old_title_text,
|
||||
new_title_text,
|
||||
)
|
||||
merged["title_config"] = title_config
|
||||
|
||||
plan_model.config = merged
|
||||
db.commit()
|
||||
logger.info(
|
||||
"[生成任务] 回写plan.config成功: plan_id=%s task_id=%s keys=%s",
|
||||
plan_id,
|
||||
task_id,
|
||||
list(merged.keys()),
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(
|
||||
"[生成任务] 回写plan.config异常(不影响任务创建): plan_id=%s error=%s",
|
||||
plan_id,
|
||||
e,
|
||||
exc_info=True,
|
||||
)
|
||||
try:
|
||||
db.rollback()
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
|
||||
def _resolve_project_and_library(
|
||||
@@ -421,14 +489,25 @@ def create_generation_task(
|
||||
# 各变体配音时长(查询硬化:异常 → 0.0 不阻断)
|
||||
voice_durations = _query_voice_durations(db, variant_voices)
|
||||
|
||||
# 解析批量源 plan:优先前端传入;否则按 template_id + user 查最新(公共函数)
|
||||
from app.services.generation_common import resolve_latest_plan_by_template
|
||||
# 解析批量源 plan:优先前端传入;否则按 template_id + user 查最新(与单任务兜底同源)
|
||||
batch_source_plan_id = request.source_edit_plan_id
|
||||
if not batch_source_plan_id and request.template_id:
|
||||
try:
|
||||
from packages.adapters.sqlalchemy_impl.models import EditPlanModel
|
||||
|
||||
batch_source_plan_id = (
|
||||
request.source_edit_plan_id
|
||||
or resolve_latest_plan_by_template(db, template_id=request.template_id, user_id=user_id)
|
||||
or ""
|
||||
)
|
||||
_latest = (
|
||||
db.query(EditPlanModel)
|
||||
.filter(
|
||||
EditPlanModel.template_id == request.template_id,
|
||||
EditPlanModel.created_by_user_id == user_id,
|
||||
)
|
||||
.order_by(EditPlanModel.created_at.desc())
|
||||
.first()
|
||||
)
|
||||
if _latest:
|
||||
batch_source_plan_id = _latest.id
|
||||
except Exception:
|
||||
logger.warning("[生成任务] 批量源 plan 解析失败", exc_info=True)
|
||||
|
||||
if not batch_source_plan_id and not request.variant_plan_ids:
|
||||
# 无任何可用源 plan:批量变体无从选片,明确报错,严禁静默共用/同源
|
||||
@@ -473,12 +552,7 @@ def create_generation_task(
|
||||
) from clone_err
|
||||
variant_plan_ids.append(_plan0.id)
|
||||
|
||||
# #1855 P0:批次区间避让表,从变体0实际clips构建初始值(公共函数)
|
||||
from app.services.generation_common import collect_plan_segments as _collect_segments
|
||||
|
||||
_batch_segments = _collect_segments(_plan0.id, _plan_svc._clip_repo)
|
||||
|
||||
# 变体 1..N-1 独立选片(传入累积batch_segments做素材区间避让)
|
||||
# 变体 1..N-1 独立选片
|
||||
for task_index in range(1, count):
|
||||
variant = None
|
||||
last_err: Exception | None = None
|
||||
@@ -490,7 +564,6 @@ def create_generation_task(
|
||||
created_by_user_id=user_id,
|
||||
name_suffix=f"批量{task_index + 1}",
|
||||
voice_duration=voice_durations[task_index] if task_index < len(voice_durations) else 0.0,
|
||||
batch_segments=_batch_segments,
|
||||
)
|
||||
break
|
||||
except ValueError as ve:
|
||||
@@ -522,16 +595,7 @@ def create_generation_task(
|
||||
) from last_err
|
||||
variant_plan_ids.append(variant.id)
|
||||
|
||||
# #1855 P0:把新变体的clips区间追加到batch_segments,供下一变体避让
|
||||
try:
|
||||
_new_segs = _collect_segments(variant.id, _plan_svc._clip_repo)
|
||||
for _aid, _ivs in _new_segs.items():
|
||||
_batch_segments.setdefault(_aid, []).extend(_ivs)
|
||||
except Exception:
|
||||
logger.exception("[生成任务] 变体%d 区间收集失败(不阻断)", task_index)
|
||||
|
||||
# ③ 配音时长分配(回传 plan / clone 变体0 均需幂等分配;reselect 已在选片时分配,
|
||||
# #1855:apply_voice_duration_to_plan 已内置幂等判断,重复调用安全)
|
||||
# ③ 配音时长分配(回传 plan / clone 变体0 均需幂等分配;reselect 已在选片时分配)
|
||||
for _vi, _pid in enumerate(variant_plan_ids):
|
||||
_vd = voice_durations[_vi] if _vi < len(voice_durations) else 0.0
|
||||
if _vd > 0:
|
||||
@@ -552,13 +616,24 @@ def create_generation_task(
|
||||
)
|
||||
_single_vd: list[float] = _query_voice_durations(db, _voices)
|
||||
_single_dur = _single_vd[0] if _single_vd else 0.0
|
||||
from app.services.generation_common import resolve_latest_plan_by_template
|
||||
_single_plan = request.source_edit_plan_id
|
||||
if not _single_plan and request.template_id:
|
||||
try:
|
||||
from packages.adapters.sqlalchemy_impl.models import EditPlanModel
|
||||
|
||||
_single_plan = (
|
||||
request.source_edit_plan_id
|
||||
or resolve_latest_plan_by_template(db, template_id=request.template_id, user_id=user_id)
|
||||
or ""
|
||||
)
|
||||
_latest = (
|
||||
db.query(EditPlanModel)
|
||||
.filter(
|
||||
EditPlanModel.template_id == request.template_id,
|
||||
EditPlanModel.created_by_user_id == user_id,
|
||||
)
|
||||
.order_by(EditPlanModel.created_at.desc())
|
||||
.first()
|
||||
)
|
||||
if _latest:
|
||||
_single_plan = _latest.id
|
||||
except Exception:
|
||||
logger.warning("[生成任务] 单任务源 plan 解析失败", exc_info=True)
|
||||
if _single_dur > 0 and _single_plan:
|
||||
from app.services.edit_plan_service import EditPlanService
|
||||
|
||||
|
||||
@@ -90,12 +90,25 @@ def create_variant_plans(
|
||||
except VariantVoiceError as exc:
|
||||
raise HTTPException(status_code=400, detail=str(exc)) from exc
|
||||
|
||||
# 解析源 plan:显式传入优先;否则按 template_id + user 查最新(公共函数)
|
||||
from app.services.generation_common import resolve_latest_plan_by_template
|
||||
|
||||
# 解析源 plan:显式传入优先;否则按 template_id + user 查最新
|
||||
source_plan_id = request.source_edit_plan_id.strip()
|
||||
if not source_plan_id and request.template_id.strip():
|
||||
source_plan_id = resolve_latest_plan_by_template(db, template_id=request.template_id, user_id=user_id) or ""
|
||||
try:
|
||||
from packages.adapters.sqlalchemy_impl.models import EditPlanModel
|
||||
|
||||
_latest = (
|
||||
db.query(EditPlanModel)
|
||||
.filter(
|
||||
EditPlanModel.template_id == request.template_id.strip(),
|
||||
EditPlanModel.created_by_user_id == user_id,
|
||||
)
|
||||
.order_by(EditPlanModel.created_at.desc())
|
||||
.first()
|
||||
)
|
||||
if _latest:
|
||||
source_plan_id = _latest.id
|
||||
except Exception:
|
||||
logger.exception("[variant-plans] 源 plan 解析失败")
|
||||
|
||||
if not source_plan_id:
|
||||
raise HTTPException(
|
||||
|
||||
@@ -1,12 +1,11 @@
|
||||
"""对口型 API 路由 — #1796 MediaKit 对口型, #1809 参数调整, #1845 配音前置.
|
||||
"""对口型 API 路由 — #1796 MediaKit 对口型, #1809 参数调整.
|
||||
|
||||
接口:
|
||||
POST /api/v1/lipsync/jobs 提交对口型任务(支持 TTS/直传/预合成 三种模式)
|
||||
POST /api/v1/lipsync/jobs 提交对口型任务
|
||||
GET /api/v1/lipsync/jobs 任务列表
|
||||
GET /api/v1/lipsync/jobs/{id} 任务详情
|
||||
POST /api/v1/lipsync/jobs/{id}/refresh 刷新任务状态
|
||||
POST /api/v1/lipsync/jobs/{id}/cancel 取消任务
|
||||
POST /api/v1/lipsync/tts-preview #1845 步骤1 TTS 预合成(同步 HTTP,~2-3s)
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
@@ -18,12 +17,7 @@ from app.dependencies import (
|
||||
get_db_session,
|
||||
get_voice_clone_profile_repository,
|
||||
)
|
||||
from app.schemas.lipsync import (
|
||||
AiAvatarTtsPreviewRequest,
|
||||
AiAvatarTtsPreviewResponse,
|
||||
CreateLipsyncJobRequest,
|
||||
LipsyncJobResponse,
|
||||
)
|
||||
from app.schemas.lipsync import CreateLipsyncJobRequest, LipsyncJobResponse
|
||||
from app.services.lipsync_service import LipsyncService
|
||||
from app.services.mediakit_client import MediaKitError
|
||||
from fastapi import APIRouter, BackgroundTasks, Depends, HTTPException, Query
|
||||
@@ -39,6 +33,7 @@ def _get_service(
|
||||
voice_clone_repo=Depends(get_voice_clone_profile_repository),
|
||||
) -> LipsyncService:
|
||||
# voice_clone_repo 用于克隆音色 profile 解析
|
||||
# TTS 合成已移至 Celery 异步任务,无需同步注入 cosyvoice_service
|
||||
return LipsyncService(
|
||||
db,
|
||||
voice_clone_repo=voice_clone_repo,
|
||||
@@ -56,20 +51,15 @@ def create_lipsync_job(
|
||||
):
|
||||
"""提交对口型任务.
|
||||
|
||||
三种模式:
|
||||
- TTS 直生(旧版/降级):传 {video_url, voice_id, script_text, speed?, emotion?},
|
||||
后端 dispatch Celery 异步任务。
|
||||
- 直接音频:传 {video_url, audio_url},后端同步下载+算timings+提交MediaKit。
|
||||
- 预合成音频(#1845 新主路径):传 {video_url, audio_url, audio_duration, sentence_timings},
|
||||
后端同步ffprobe+写入timings+直接提交MediaKit(~2-3s)。
|
||||
#1809/#1822: 前端传 {video_url, voice_id, script_text, speed?, emotion?},
|
||||
后端创建任务记录(状态 tts_processing),dispatch Celery 异步任务执行 TTS 合成 + MediaKit 提交;
|
||||
也支持直接传 {video_url, audio_url}(同步提交 MediaKit)。
|
||||
"""
|
||||
try:
|
||||
job = svc.create_job(
|
||||
user_id=current_user.user.id,
|
||||
video_url=body.video_url,
|
||||
audio_url=body.audio_url,
|
||||
audio_duration=body.audio_duration,
|
||||
sentence_timings=body.sentence_timings,
|
||||
voice_id=body.voice_id,
|
||||
script_text=body.script_text,
|
||||
speed=body.speed,
|
||||
@@ -78,8 +68,10 @@ def create_lipsync_job(
|
||||
project_id=body.project_id,
|
||||
)
|
||||
except ValueError as exc:
|
||||
# 参数无效(如 voice_id 格式不对、文本过长等)
|
||||
raise HTTPException(status_code=400, detail=str(exc)) from exc
|
||||
except MediaKitError as exc:
|
||||
# 音色无权访问 → 403;参数无效 → 400;MediaKit 提交失败 → 502
|
||||
status_code = 502
|
||||
if exc.code in ("VoiceForbidden",):
|
||||
status_code = 403
|
||||
@@ -94,6 +86,7 @@ def create_lipsync_job(
|
||||
},
|
||||
) from exc
|
||||
except Exception as exc:
|
||||
# 兜底:任何未预期的错误返回 400 而非 500
|
||||
logger.error("创建对口型任务异常: %s", exc, exc_info=True)
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
@@ -103,52 +96,6 @@ def create_lipsync_job(
|
||||
return job
|
||||
|
||||
|
||||
# ── POST /tts-preview — #1845 步骤1 TTS 预合成 ──────────────────────────
|
||||
|
||||
|
||||
@router.post("/tts-preview", response_model=AiAvatarTtsPreviewResponse)
|
||||
def preview_tts(
|
||||
body: AiAvatarTtsPreviewRequest,
|
||||
current_user: AuthenticatedUser = Depends(get_current_user),
|
||||
svc: LipsyncService = Depends(_get_service),
|
||||
):
|
||||
"""步骤1「生成配音」同步 TTS 预合成.
|
||||
|
||||
同步执行 TTS 合成 → 下载音频 → ffprobe 时长 → 句子时间戳计算,
|
||||
不创建 LipsyncJob、不转存 OSS,直接返回 CosyVoice 临时 URL(~24h 有效)。
|
||||
耗时约 2-3 秒。
|
||||
"""
|
||||
try:
|
||||
result = svc.preview_tts(
|
||||
user_id=current_user.user.id,
|
||||
voice_id=body.voice_id,
|
||||
script_text=body.script_text,
|
||||
speed=body.speed,
|
||||
emotion=body.emotion,
|
||||
)
|
||||
except MediaKitError as exc:
|
||||
status_code = 400
|
||||
if exc.code in ("VoiceForbidden",):
|
||||
status_code = 403
|
||||
elif exc.code in ("TTSNoAudio",):
|
||||
status_code = 502
|
||||
raise HTTPException(
|
||||
status_code=status_code,
|
||||
detail={
|
||||
"code": exc.code,
|
||||
"message": str(exc),
|
||||
},
|
||||
) from exc
|
||||
except Exception as exc:
|
||||
logger.error("TTS 预合成异常: %s", exc, exc_info=True)
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail=f"TTS 合成失败: {exc}",
|
||||
) from exc
|
||||
|
||||
return result
|
||||
|
||||
|
||||
# ── GET /jobs — 任务列表 ─────────────────────────────────────────────────
|
||||
|
||||
|
||||
@@ -187,7 +134,11 @@ def get_lipsync_job(
|
||||
current_user: AuthenticatedUser = Depends(get_current_user),
|
||||
svc: LipsyncService = Depends(_get_service),
|
||||
):
|
||||
"""获取对口型任务详情."""
|
||||
"""获取对口型任务详情.
|
||||
|
||||
非终态任务:先返回 DB 缓存,挂后台刷新(下次轮询拿到新状态),
|
||||
避免 MediaKit 慢响应阻塞前端轮询。
|
||||
"""
|
||||
job = svc.get_job(job_id, current_user.user.id)
|
||||
if job is None:
|
||||
raise HTTPException(status_code=404, detail="任务不存在")
|
||||
|
||||
@@ -287,15 +287,10 @@ def retry_voice_clone(
|
||||
return _to_response(profile)
|
||||
|
||||
|
||||
_ALLOWED_PREVIEW_EMOTIONS = {"", "natural", "excited", "calm", "friendly"}
|
||||
|
||||
|
||||
@router.get("/{clone_id}/preview", response_model=VoiceClonePreviewResponse)
|
||||
def get_voice_clone_preview(
|
||||
clone_id: str,
|
||||
text: str = Query("", description="自定义试听文本,为空则使用默认示例"),
|
||||
speed: float = Query(1.0, ge=0.5, le=2.0, description="语速,0.5-2.0,默认 1.0"),
|
||||
emotion: str = Query("", description="情绪:natural/excited/calm/friendly,空字符串为默认自然"),
|
||||
authenticated_user: AuthenticatedUser = Depends(get_current_user),
|
||||
repository: SQLAlchemyVoiceCloneProfileRepository = Depends(get_voice_clone_profile_repository),
|
||||
cosyvoice: CosyVoiceService = Depends(get_cosyvoice_service),
|
||||
@@ -303,17 +298,11 @@ def get_voice_clone_preview(
|
||||
"""获取克隆音色试听音频(实时 TTS 合成)。
|
||||
|
||||
- 克隆音色必须处于 ready 状态
|
||||
- 使用默认试听文本时,结果缓存 7 天(仅默认 text+speed=1.0+emotion=空 组合缓存)
|
||||
- 可传入自定义 text/speed/emotion 试听不同效果
|
||||
- 使用默认试听文本时,结果缓存 7 天
|
||||
- 可传入自定义 text 参数试听不同文本
|
||||
"""
|
||||
import time
|
||||
|
||||
if emotion not in _ALLOWED_PREVIEW_EMOTIONS:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_400_BAD_REQUEST,
|
||||
detail=f"不支持的 emotion 值: {emotion},可选: natural/excited/calm/friendly 或留空",
|
||||
)
|
||||
|
||||
use_case = GetVoiceCloneUseCase(repository)
|
||||
try:
|
||||
profile = use_case.execute(clone_id, authenticated_user.user.id)
|
||||
@@ -326,8 +315,8 @@ def get_voice_clone_preview(
|
||||
detail=f"Voice clone is not ready (current status: {profile.status})",
|
||||
)
|
||||
|
||||
# 仅默认试听文本 + 默认 speed + 默认 emotion 时使用缓存
|
||||
use_cache = (not text.strip()) and abs(speed - 1.0) < 1e-6 and (not emotion)
|
||||
# 有自定义文本时不缓存
|
||||
use_cache = not text.strip()
|
||||
|
||||
if use_cache and clone_id in _clone_preview_cache:
|
||||
audio_url, duration, file_size, cached_text, cached_at = _clone_preview_cache[clone_id]
|
||||
@@ -348,15 +337,12 @@ def get_voice_clone_preview(
|
||||
text=preview_text,
|
||||
voice_id=profile.voice_id,
|
||||
format="mp3",
|
||||
speed=speed,
|
||||
emotion=emotion,
|
||||
speed=1.0,
|
||||
)
|
||||
except CosyVoiceError as e:
|
||||
raise HTTPException(status_code=502, detail=f"TTS 合成失败: {e}") from e
|
||||
except ValueError as e:
|
||||
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=str(e)) from e
|
||||
|
||||
# 缓存(仅默认参数组合)
|
||||
# 缓存(仅默认试听文本)
|
||||
if use_cache:
|
||||
_clone_preview_cache[clone_id] = (
|
||||
result.audio_url,
|
||||
|
||||
@@ -52,9 +52,7 @@ class CreateAiAvatarRenderRequest(BaseModel):
|
||||
lipsync_job_id: str = Field(..., description="对口型任务 ID")
|
||||
script_id: str = Field("", description="文案 ID(选自文案库时传;手动输入文案直生场景可留空)")
|
||||
b_roll_segments: list[BRollSegment] = Field(default_factory=list, description="B-roll 片段列表")
|
||||
title_config: dict[str, Any] = Field(
|
||||
default_factory=dict, description="标题配置(可含 title_image_dataurl:前端 Canvas 渲染的标题 PNG dataURL)"
|
||||
)
|
||||
title_config: dict[str, Any] = Field(default_factory=dict, description="标题配置")
|
||||
cover_config: dict[str, Any] = Field(default_factory=dict, description="封面配置")
|
||||
project_id: str = Field("", description="项目 ID")
|
||||
|
||||
@@ -69,6 +67,7 @@ class CreateAiAvatarRenderRequest(BaseModel):
|
||||
@field_validator("script_id")
|
||||
@classmethod
|
||||
def validate_script_id(cls, v: str) -> str:
|
||||
# script_id 可选:手动输入文案(TTS 直生)场景不关联文案库条目
|
||||
return (v or "").strip()
|
||||
|
||||
|
||||
@@ -110,17 +109,16 @@ class AiAvatarRenderProgressResponse(BaseModel):
|
||||
error_message: str
|
||||
|
||||
|
||||
class SmartCoverRequest(BaseModel):
|
||||
"""智能封面请求 — MediaKit 抽帧 + 质量评分选最佳帧."""
|
||||
|
||||
video_url: str = Field(..., description="数字人视频 URL(对口型/渲染成片)")
|
||||
max_frames: int = Field(5, ge=1, le=10, description="抽帧数量(默认 5)")
|
||||
|
||||
|
||||
class SmartCoverResponse(BaseModel):
|
||||
"""智能封面响应(封面从最终成片抽帧,不再叠加标题)."""
|
||||
"""智能封面响应."""
|
||||
|
||||
cover_url: str = Field("", description="封面图公网 URL(OSS,非临时);失败为空")
|
||||
status: str = Field("completed", description="completed / fallback_failed")
|
||||
message: str = Field("", description="失败原因(如有)")
|
||||
|
||||
|
||||
class FinalizeRenderResponse(BaseModel):
|
||||
"""封面选好后点「完成」,正式入库成片库的响应."""
|
||||
|
||||
video_id: str = Field(..., description="成片库视频ID")
|
||||
cover_url: str = Field("", description="封面URL")
|
||||
status: str = Field("success", description="success/already_finalized")
|
||||
|
||||
@@ -1,12 +1,9 @@
|
||||
"""对口型 API Schema 定义 — #1796 / #1809 / #1822 / #1845(配音前置).
|
||||
"""对口型 API Schema 定义 — #1796 / #1809 / #1822.
|
||||
|
||||
支持三种输入模式:
|
||||
1. TTS 直生模式(兼容旧版前端):传 voice_id + script_text(+ speed/emotion),
|
||||
后端 Celery 异步做 TTS 合成 + MediaKit 提交。
|
||||
支持两种输入模式(二选一):
|
||||
1. TTS 直生模式(推荐):传 voice_id + script_text(+ speed/emotion),
|
||||
后端内部先调 CosyVoice 合成音频,再提交 MediaKit 对口型。
|
||||
2. 直接音频模式:传 video_url + audio_url(音频已由调用方准备好)。
|
||||
3. 预合成音频模式(#1845 配音前置新主路径):前端先调 POST /lipsync/tts-preview
|
||||
拿到 audio_url + sentence_timings,再在 create_job 时传 audio_url + audio_duration
|
||||
+ sentence_timings,后端跳过 TTS 和时间戳计算,直接 ffprobe 校验后提交 MediaKit。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
@@ -36,7 +33,6 @@ class LipsyncJobResponse(BaseModel):
|
||||
output_duration: float
|
||||
error_message: str
|
||||
error_code: str
|
||||
sentence_timings: Optional[list] = None
|
||||
submitted_at: Optional[datetime] = None
|
||||
completed_at: Optional[datetime] = None
|
||||
created_at: datetime
|
||||
@@ -49,19 +45,15 @@ class LipsyncJobResponse(BaseModel):
|
||||
class CreateLipsyncJobRequest(BaseModel):
|
||||
"""创建对口型任务请求.
|
||||
|
||||
三种模式(三选一):
|
||||
- TTS 直生(旧版/降级):voice_id + script_text 必填;audio_url 留空。
|
||||
两种模式(二选一):
|
||||
- TTS 直生:voice_id + script_text 必填(+ 可选 speed/emotion);audio_url 留空。
|
||||
- 直接音频:video_url + audio_url 必填。
|
||||
- 预合成音频(#1845 新主路径):audio_url 必填 + 可选 audio_duration/sentence_timings;
|
||||
后端同步 ffprobe 校验时长、写入 timings,直接提交 MediaKit。
|
||||
"""
|
||||
|
||||
video_url: str = Field(..., description="人物视频 URL(MP4,≤30min,单人真人)")
|
||||
|
||||
# 模式 2/3:直接/预合成音频
|
||||
# 模式 2:直接音频
|
||||
audio_url: str = Field("", description="驱动音频 URL(mp3/aac/wav/m4a/flac);直生模式留空")
|
||||
audio_duration: Optional[float] = Field(None, ge=0, description="预合成音频时长(秒),可选;后端会 ffprobe 校验")
|
||||
sentence_timings: Optional[list] = Field(None, description="预合成接口返回的句子时间戳,可选;若传入则直接写入 job")
|
||||
|
||||
# 模式 1:TTS 直生
|
||||
voice_id: str = Field("", description="音色 ID(预置音色或克隆音色 profile UUID)")
|
||||
@@ -69,9 +61,7 @@ class CreateLipsyncJobRequest(BaseModel):
|
||||
speed: float = Field(1.0, ge=0.5, le=2.0, description="语速(0.5-2.0),默认 1.0")
|
||||
emotion: str = Field("", description="情绪(natural/excited/calm/friendly 或中文 自然/兴奋/沉稳/亲切)")
|
||||
|
||||
enable_video_loop: bool = Field(
|
||||
True, description="音频长于视频时是否循环画面(AI数字人默认开启,防止音频长于视频被截断)"
|
||||
)
|
||||
enable_video_loop: bool = Field(False, description="音频长于视频时是否循环画面")
|
||||
project_id: str = Field("", description="项目 ID(可选)")
|
||||
|
||||
@model_validator(mode="after")
|
||||
@@ -82,16 +72,15 @@ class CreateLipsyncJobRequest(BaseModel):
|
||||
if not video.startswith(("http://", "https://")):
|
||||
raise ValueError("video_url 必须是 HTTP/HTTPS URL")
|
||||
lower = video.lower().split("?")[0]
|
||||
allowed_video_exts = (".mp4", ".mov", ".m4v", ".webm", ".avi", ".mkv", ".3gp")
|
||||
if not any(lower.endswith(ext) for ext in allowed_video_exts):
|
||||
raise ValueError("video_url 格式不支持,仅支持: " + ", ".join(allowed_video_exts))
|
||||
if not lower.endswith(".mp4"):
|
||||
raise ValueError("video_url 仅支持 MP4 格式")
|
||||
|
||||
has_audio = bool((self.audio_url or "").strip())
|
||||
has_tts = bool((self.voice_id or "").strip()) and bool((self.script_text or "").strip())
|
||||
|
||||
if not has_audio and not has_tts:
|
||||
raise ValueError(
|
||||
"必须提供驱动音频:要么传 audio_url(直接/预合成音频模式),"
|
||||
"必须提供驱动音频:要么传 audio_url(直接音频模式),"
|
||||
"要么同时传 voice_id + script_text(TTS 直生模式)"
|
||||
)
|
||||
|
||||
@@ -109,23 +98,3 @@ class CreateLipsyncJobRequest(BaseModel):
|
||||
self.audio_url = au
|
||||
|
||||
return self
|
||||
|
||||
|
||||
# ── #1845 TTS 预合成接口 ────────────────────────────────────────────────
|
||||
|
||||
|
||||
class AiAvatarTtsPreviewRequest(BaseModel):
|
||||
"""步骤1「生成配音」预合成请求(同步 HTTP,~2-3s)."""
|
||||
|
||||
voice_id: str = Field(..., min_length=1, max_length=128, description="音色 ID")
|
||||
script_text: str = Field(..., min_length=1, max_length=5000, description="要合成的文案")
|
||||
speed: float = Field(1.0, ge=0.5, le=2.0, description="语速(0.5-2.0),默认 1.0")
|
||||
emotion: str = Field("natural", max_length=32, description="情绪")
|
||||
|
||||
|
||||
class AiAvatarTtsPreviewResponse(BaseModel):
|
||||
"""TTS 预合成响应(临时 URL,24h 内有效,足够当前会话使用)."""
|
||||
|
||||
audio_url: str = Field(..., description="CosyVoice 临时音频 URL")
|
||||
duration: float = Field(..., ge=0, description="音频总时长(秒),ffprobe 测得")
|
||||
sentence_timings: list[dict] = Field(..., description="句子级精确时间戳")
|
||||
|
||||
@@ -1,13 +1,10 @@
|
||||
"""AI 数字人封面服务 — MediaKit 抽帧 + 质量评分选最佳帧 + 转存 OSS.
|
||||
"""AI 数字人封面服务 — 复用智能剪辑的 MediaKit 抽帧 + 质量评分选最佳帧.
|
||||
|
||||
与 generation_cover.py 的智能选帧能力对齐(不再用 FFmpeg 简单截帧):
|
||||
1. MediaKit extract_frames 抽取多帧(默认 5 帧,SpecifiedFrames 策略)
|
||||
2. cover_frame_scorer.score_frames 按清晰度/亮度/色彩评分选最佳
|
||||
3. 下载最佳帧并转存 OSS,返回公网封面 URL
|
||||
|
||||
设计原则:封面一律从最终成片(已叠加标题/B-roll)抽帧,帧本身已含标题,
|
||||
本服务**不再叠加标题**。对口型阶段的裸视频封面入口已删除(废弃)。
|
||||
|
||||
降级:MediaKit 不可用或抽帧失败时返回空字符串,由调用方决定回退策略。
|
||||
"""
|
||||
|
||||
@@ -22,9 +19,9 @@ from urllib.parse import urlparse
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# MediaKit 抽帧轮询参数:poll_interval=2s × max_poll=30 → 最长 60s(与 mediakit_client 默认值/lipsync 轮询保持一致,防止合成视频下载+抽帧超时)
|
||||
COVER_POLL_INTERVAL = 2.0
|
||||
COVER_MAX_POLL_ATTEMPTS = 30
|
||||
# MediaKit 抽帧轮询参数(与 MediaKit API timeout=60s 对齐)
|
||||
COVER_POLL_INTERVAL = 3.0
|
||||
COVER_MAX_POLL_ATTEMPTS = 20 # 最多等 60 秒
|
||||
|
||||
# 帧图片下载超时(秒)
|
||||
FRAME_DOWNLOAD_TIMEOUT = 20
|
||||
@@ -52,6 +49,7 @@ def _sign_video_url_for_mediakit(video_url: str) -> str:
|
||||
own_host = urlparse(public_base).netloc.lower()
|
||||
url_host = urlparse(video_url).netloc.lower()
|
||||
if own_host and url_host == own_host:
|
||||
# 是自家 OSS URL,重签 7 天有效期供 MediaKit 拉取
|
||||
signed = storage.get_download_url(video_url, expires_seconds=MEDIAKIT_URL_TTL_SECONDS)
|
||||
if signed:
|
||||
logger.info("[数字人封面] video_url 已重签(自家 OSS 私有桶)")
|
||||
@@ -62,10 +60,19 @@ def _sign_video_url_for_mediakit(video_url: str) -> str:
|
||||
|
||||
|
||||
def select_best_cover_frame(video_url: str, *, max_frames: int = 5) -> str:
|
||||
"""从视频抽取多帧并评分选最佳帧,返回最佳帧的临时 URL."""
|
||||
"""从视频抽取多帧并评分选最佳帧,返回最佳帧的临时 URL.
|
||||
|
||||
Args:
|
||||
video_url: 可公网访问的视频 URL
|
||||
max_frames: 抽帧数量
|
||||
|
||||
Returns:
|
||||
最佳帧图片 URL;失败返回空字符串
|
||||
"""
|
||||
if not video_url:
|
||||
return ""
|
||||
|
||||
# 确保 MediaKit 能访问 video_url(自家 OSS 私有桶需重签)
|
||||
video_url = _sign_video_url_for_mediakit(video_url)
|
||||
|
||||
try:
|
||||
@@ -78,9 +85,11 @@ def select_best_cover_frame(video_url: str, *, max_frames: int = 5) -> str:
|
||||
return ""
|
||||
|
||||
logger.info(
|
||||
"[数字人封面] 开始抽帧: video_url=%s max_frames=%d",
|
||||
"[数字人封面] 开始抽帧: video_url=%s max_frames=%d poll_interval=%.1f max_poll=%d",
|
||||
video_url[:80],
|
||||
max_frames,
|
||||
COVER_POLL_INTERVAL,
|
||||
COVER_MAX_POLL_ATTEMPTS,
|
||||
)
|
||||
|
||||
snapshots = mk.extract_frames(
|
||||
@@ -98,6 +107,7 @@ def select_best_cover_frame(video_url: str, *, max_frames: int = 5) -> str:
|
||||
if len(snapshots) == 1:
|
||||
return snapshots[0].get("image_url") or snapshots[0].get("url") or ""
|
||||
|
||||
# 使用连接池下载各帧(复用 TCP 连接,减少延迟)
|
||||
import httpx
|
||||
|
||||
candidates = []
|
||||
@@ -125,6 +135,7 @@ def select_best_cover_frame(video_url: str, *, max_frames: int = 5) -> str:
|
||||
best = scored[0] if scored else None
|
||||
best_url = best.get("url", "") if best else ""
|
||||
|
||||
# 清理临时文件
|
||||
for c in candidates:
|
||||
p = c.get("image_path")
|
||||
if p:
|
||||
@@ -145,15 +156,16 @@ def select_best_cover_frame(video_url: str, *, max_frames: int = 5) -> str:
|
||||
return ""
|
||||
|
||||
|
||||
def persist_cover_to_oss(
|
||||
frame_url: str,
|
||||
*,
|
||||
job_id: str = "",
|
||||
prefix: str = "ai-avatar/covers",
|
||||
) -> str:
|
||||
"""下载最佳帧图并转存到 OSS,返回公网封面 URL(预签名).
|
||||
def persist_cover_to_oss(frame_url: str, *, job_id: str = "", prefix: str = "ai-avatar/covers") -> str:
|
||||
"""下载帧图并转存到 OSS,返回公网封面 URL.
|
||||
|
||||
封面来自最终成片抽帧,帧本身已含标题,本函数不再做任何文字/图片叠加。
|
||||
Args:
|
||||
frame_url: MediaKit 返回的临时帧图 URL
|
||||
job_id: 关联任务 ID(用于 OSS key 命名)
|
||||
prefix: OSS key 前缀
|
||||
|
||||
Returns:
|
||||
OSS 公网 URL;失败回退原始 frame_url
|
||||
"""
|
||||
if not frame_url:
|
||||
return ""
|
||||
@@ -177,13 +189,13 @@ def persist_cover_to_oss(
|
||||
storage = get_shared_storage_service()
|
||||
token = job_id or uuid.uuid4().hex[:12]
|
||||
cover_key = f"{prefix}/{token}/cover_{uuid.uuid4().hex[:8]}.jpg"
|
||||
|
||||
public_url = storage.upload_file(
|
||||
file_or_path=tmp_path,
|
||||
storage_key=cover_key,
|
||||
content_type="image/jpeg",
|
||||
)
|
||||
logger.info("[数字人封面] 封面已转存 OSS: key=%s", cover_key)
|
||||
# 私有桶:返回预签名 URL(前端才能加载)
|
||||
if public_url:
|
||||
signed = storage.get_download_url(cover_key, expires_seconds=86400)
|
||||
return signed
|
||||
@@ -199,15 +211,10 @@ def persist_cover_to_oss(
|
||||
pass
|
||||
|
||||
|
||||
def generate_smart_cover(
|
||||
video_url: str,
|
||||
*,
|
||||
job_id: str = "",
|
||||
max_frames: int = 5,
|
||||
) -> str:
|
||||
"""一站式:MediaKit 智能抽帧选最佳 → 转存 OSS。失败返回空字符串。
|
||||
def generate_smart_cover(video_url: str, *, job_id: str = "", max_frames: int = 5) -> str:
|
||||
"""一站式:MediaKit 智能抽帧选最佳 → 转存 OSS,返回封面公网 URL.
|
||||
|
||||
封面从最终成片抽帧,不再叠加任何标题(帧本身已含)。
|
||||
供独立封面接口与渲染管线复用。失败返回空字符串。
|
||||
"""
|
||||
best_frame = select_best_cover_frame(video_url, max_frames=max_frames)
|
||||
if not best_frame:
|
||||
|
||||
@@ -9,11 +9,8 @@
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import base64
|
||||
import binascii
|
||||
import logging
|
||||
import os
|
||||
import subprocess
|
||||
import tempfile
|
||||
import uuid
|
||||
from datetime import datetime, timezone
|
||||
@@ -27,9 +24,8 @@ from packages.adapters.sqlalchemy_impl.models import (
|
||||
ScriptModel,
|
||||
)
|
||||
from packages.domain.video_filter_builder import (
|
||||
build_broll_overlay_filter,
|
||||
build_cover_extract_command,
|
||||
build_title_drawtext_filter,
|
||||
build_title_overlay_filter,
|
||||
)
|
||||
from packages.shared.storage import get_shared_storage_service
|
||||
|
||||
@@ -200,8 +196,9 @@ class AiAvatarRenderService:
|
||||
1. 下载对口型输出视频 (20%)
|
||||
2. 构建 FFmpeg 滤镜链 (40%)
|
||||
3. 执行 FFmpeg 渲染 (80%)
|
||||
4. 上传到 OSS (95%) — 封面不再自动生成,改由前端主动抽帧
|
||||
5. 更新任务状态 (100%)
|
||||
4. 提取封面 (90%)
|
||||
5. 上传到 OSS (95%)
|
||||
6. 更新任务状态 (100%)
|
||||
"""
|
||||
job = self.db.query(AiAvatarRenderJob).filter(AiAvatarRenderJob.id == job_id).first()
|
||||
if job is None:
|
||||
@@ -231,32 +228,27 @@ class AiAvatarRenderService:
|
||||
self.db.commit()
|
||||
|
||||
# 2. 构建 FFmpeg 滤镜链 (40%)
|
||||
# 用 ffprobe 探测输入视频分辨率,确保 B-roll 缩放与标题位置与实际输出一致。
|
||||
# AI 数字人对口型输出为 9:16 竖屏,默认兜底 720x1280;探测失败时使用默认值不阻断渲染。
|
||||
output_width, output_height = self._probe_video_resolution(input_video_path)
|
||||
if output_width <= 0 or output_height <= 0:
|
||||
output_width, output_height = 720, 1280
|
||||
logger.info(
|
||||
"[数字人渲染] ffprobe 探测分辨率失败或无效,使用默认竖屏尺寸 %sx%s",
|
||||
output_width,
|
||||
output_height,
|
||||
)
|
||||
else:
|
||||
logger.info("[数字人渲染] 探测输入视频分辨率: %sx%s", output_width, output_height)
|
||||
from packages.domain.video_filter_builder import build_broll_overlay_filter
|
||||
|
||||
broll_filter, broll_label = build_broll_overlay_filter(
|
||||
filter_complex = build_broll_overlay_filter(
|
||||
b_roll_segments=job.b_roll_segments,
|
||||
video_duration=lipsync_job.output_duration,
|
||||
output_width=output_width,
|
||||
output_height=output_height,
|
||||
)
|
||||
|
||||
# 标题叠加路径:优先前端 Canvas 渲染的 PNG 图层(所见即所得),
|
||||
# 无 title_image_dataurl 时降级到 drawtext 重画文字。
|
||||
title_cfg = job.title_config if isinstance(job.title_config, dict) else {}
|
||||
title_dataurl = (title_cfg or {}).get("title_image_dataurl") if title_cfg else None
|
||||
use_title_png = isinstance(title_dataurl, str) and title_dataurl.startswith("data:image/")
|
||||
title_input_index = 1 + len(job.b_roll_segments or []) if use_title_png else None
|
||||
# 标题叠加
|
||||
title_filter = build_title_drawtext_filter(job.title_config)
|
||||
if title_filter:
|
||||
if filter_complex:
|
||||
filter_complex += f"[vout]{title_filter}[vout_titled];"
|
||||
else:
|
||||
filter_complex = f"[0:v]{title_filter}[vout_titled];"
|
||||
|
||||
# 清理末尾分号
|
||||
if filter_complex.endswith(";"):
|
||||
filter_complex = filter_complex[:-1]
|
||||
|
||||
# 最终输出标签
|
||||
final_label = "vout_titled" if title_filter else ("vout" if filter_complex else None)
|
||||
|
||||
job.progress = 40
|
||||
self.db.commit()
|
||||
@@ -265,126 +257,57 @@ class AiAvatarRenderService:
|
||||
with tempfile.TemporaryDirectory() as tmpdir:
|
||||
output_video_path = os.path.join(tmpdir, "output.mp4")
|
||||
|
||||
# 在临时目录里解码保存标题 PNG(with 退出自动清理)
|
||||
title_png_path: Optional[str] = None
|
||||
extra_inputs: list[str] = []
|
||||
title_filter = None
|
||||
if use_title_png:
|
||||
try:
|
||||
title_png_path = os.path.join(tmpdir, f"title_{job.id}.png")
|
||||
self._save_title_dataurl_to_file(title_dataurl, dst_path=title_png_path)
|
||||
extra_inputs.append(title_png_path)
|
||||
logger.info(
|
||||
"[数字人渲染] 标题 PNG 已保存: %s (input index %d)", title_png_path, title_input_index
|
||||
)
|
||||
except Exception as exc:
|
||||
logger.warning("[数字人渲染] 标题 PNG 解码/保存失败,降级 drawtext: %s", exc)
|
||||
title_png_path = None
|
||||
extra_inputs = []
|
||||
|
||||
# 构建标题滤镜
|
||||
final_label = None
|
||||
if title_png_path and title_input_index is not None:
|
||||
title_input_label = f"[{title_input_index}:v]"
|
||||
base_label = f"[{broll_label}]" if broll_label else "[0:v]"
|
||||
title_filter = build_title_overlay_filter(
|
||||
title_cfg,
|
||||
output_width=output_width,
|
||||
output_height=output_height,
|
||||
title_png_path=title_png_path,
|
||||
title_input_label=title_input_label,
|
||||
base_label=base_label,
|
||||
output_label="vout_titled",
|
||||
)
|
||||
if not title_filter:
|
||||
# build 返回 None → 文件不存在(极端并发情况),降级 drawtext
|
||||
title_png_path = None
|
||||
extra_inputs = []
|
||||
|
||||
if title_png_path:
|
||||
# overlay 路径
|
||||
if broll_filter and title_filter:
|
||||
filter_complex = broll_filter + f";{title_filter}"
|
||||
elif broll_filter:
|
||||
filter_complex = broll_filter
|
||||
final_label = broll_label
|
||||
elif title_filter:
|
||||
filter_complex = title_filter
|
||||
else:
|
||||
filter_complex = ""
|
||||
if title_filter:
|
||||
final_label = "vout_titled"
|
||||
elif not final_label:
|
||||
final_label = None
|
||||
else:
|
||||
# 降级:drawtext 重画文字
|
||||
title_filter = build_title_drawtext_filter(
|
||||
title_cfg,
|
||||
output_width=output_width,
|
||||
output_height=output_height,
|
||||
)
|
||||
if broll_filter and title_filter:
|
||||
filter_complex = broll_filter + f";[{broll_label}]{title_filter}[vout_titled]"
|
||||
final_label = "vout_titled"
|
||||
elif broll_filter:
|
||||
filter_complex = broll_filter
|
||||
final_label = broll_label
|
||||
elif title_filter:
|
||||
filter_complex = f"[0:v]{title_filter}[vout_titled]"
|
||||
final_label = "vout_titled"
|
||||
else:
|
||||
filter_complex = ""
|
||||
final_label = None
|
||||
|
||||
cmd_list = self._build_ffmpeg_command(
|
||||
cmd = self._build_ffmpeg_command(
|
||||
input_video=input_video_path,
|
||||
b_roll_segments=job.b_roll_segments,
|
||||
extra_inputs=extra_inputs,
|
||||
filter_complex=filter_complex,
|
||||
final_label=final_label,
|
||||
output_path=output_video_path,
|
||||
)
|
||||
|
||||
try:
|
||||
render_result = subprocess.run(
|
||||
cmd_list,
|
||||
capture_output=True,
|
||||
text=True,
|
||||
timeout=600,
|
||||
)
|
||||
except subprocess.TimeoutExpired as exc:
|
||||
raise AiAvatarRenderError(
|
||||
"FFmpeg 渲染超时(600s)",
|
||||
code="FFmpegTimeout",
|
||||
) from exc
|
||||
|
||||
if render_result.returncode != 0:
|
||||
stderr_tail = (render_result.stderr or "").strip()[-800:]
|
||||
raise AiAvatarRenderError(
|
||||
f"FFmpeg 渲染失败,退出码: {render_result.returncode}, stderr: {stderr_tail}",
|
||||
code="FFmpegFailed",
|
||||
)
|
||||
exit_code = os.system(cmd)
|
||||
if exit_code != 0:
|
||||
raise AiAvatarRenderError(f"FFmpeg 渲染失败,退出码: {exit_code}", code="FFmpegFailed")
|
||||
|
||||
job.progress = 80
|
||||
self.db.commit()
|
||||
|
||||
# 4/5. 上传成片到 OSS (95%) —— 已砍掉自动抽封面逻辑(步骤⑤);
|
||||
# 封面由前端在渲染完成后通过 /smart-cover 接口主动从成片抽帧,不阻塞渲染链路。
|
||||
# 4. 提取封面 (90%)
|
||||
cover_path = ""
|
||||
if job.cover_config:
|
||||
cover_path = os.path.join(tmpdir, "cover.jpg")
|
||||
cover_cmd = build_cover_extract_command(job.cover_config, cover_path)
|
||||
cover_cmd = cover_cmd.replace("INPUT_VIDEO", output_video_path)
|
||||
cover_exit = os.system(cover_cmd)
|
||||
if cover_exit != 0:
|
||||
logger.warning("封面提取失败,跳过: %s", cover_cmd)
|
||||
cover_path = ""
|
||||
|
||||
job.progress = 90
|
||||
self.db.commit()
|
||||
|
||||
# 5. 上传到 OSS (95%)
|
||||
output_video_url = self._upload_to_oss(output_video_path, f"ai-avatar/{job_id}/output.mp4")
|
||||
job.output_video_url = output_video_url
|
||||
|
||||
# 封面透传:如果用户已在 cover_config 中选定封面 URL(mode=upload 的自定义上传 或
|
||||
# mode=auto_frame 已有的智能封面结果),直接透传到 output_cover_url,不再重新截帧。
|
||||
if isinstance(job.cover_config, dict):
|
||||
_pre_cover_url = (
|
||||
job.cover_config.get("url")
|
||||
or job.cover_config.get("imageUrl")
|
||||
or job.cover_config.get("cover_url")
|
||||
or ""
|
||||
)
|
||||
if _pre_cover_url:
|
||||
job.output_cover_url = _pre_cover_url
|
||||
logger.info("[数字人渲染] 使用用户已选定封面 URL: job_id=%s", job_id)
|
||||
# 封面:优先复用智能剪辑的 MediaKit 抽帧 + 质量评分选最佳帧;
|
||||
# MediaKit 不可用时回退到 FFmpeg 已按 cover_config 抽取的 cover_path
|
||||
smart_cover_url = ""
|
||||
if output_video_url:
|
||||
try:
|
||||
from app.services.ai_avatar_cover_service import (
|
||||
generate_smart_cover,
|
||||
)
|
||||
|
||||
smart_cover_url = generate_smart_cover(output_video_url, job_id=job_id, max_frames=5)
|
||||
except Exception:
|
||||
logger.warning("智能封面(MediaKit)失败,回退 FFmpeg 封面 job_id=%s", job_id, exc_info=True)
|
||||
|
||||
if smart_cover_url:
|
||||
job.output_cover_url = smart_cover_url
|
||||
elif cover_path:
|
||||
output_cover_url = self._upload_to_oss(cover_path, f"ai-avatar/{job_id}/cover.jpg")
|
||||
job.output_cover_url = output_cover_url
|
||||
|
||||
# 获取输出视频时长
|
||||
job.output_duration = lipsync_job.output_duration
|
||||
@@ -399,9 +322,37 @@ class AiAvatarRenderService:
|
||||
self.db.commit()
|
||||
logger.info("渲染任务完成: %s", job_id)
|
||||
|
||||
# 7. 渲染完成,停留在「待选封面」状态:不自动入库。
|
||||
# 用户在前端选好封面、点「完成」后,由 /{job_id}/finalize 接口显式入库。
|
||||
logger.info("渲染任务完成,等待用户选择封面后入库: job_id=%s", job_id)
|
||||
# 7. 自动保存成片记录到成片库
|
||||
if job.output_video_url:
|
||||
try:
|
||||
from packages.adapters.sqlalchemy_impl.generated_video_repository import (
|
||||
SQLAlchemyGeneratedVideoRepository,
|
||||
)
|
||||
from packages.domain.generated_video import GeneratedVideo
|
||||
|
||||
clip_name = f"AI数字人_{job_id[:8]}"
|
||||
clip = GeneratedVideo.create(
|
||||
project_id=job.project_id,
|
||||
generation_task_id=job.lipsync_job_id,
|
||||
name=clip_name,
|
||||
file_url=job.output_video_url,
|
||||
user_id=job.user_id,
|
||||
duration=job.output_duration or 0.0,
|
||||
thumbnail_url=job.output_cover_url or None,
|
||||
generation_params={
|
||||
"source": "ai_avatar_render",
|
||||
"render_job_id": job.id,
|
||||
},
|
||||
)
|
||||
video_repo = SQLAlchemyGeneratedVideoRepository(self.db)
|
||||
video_repo.create(clip)
|
||||
logger.info("成片记录已保存到成片库: clip_id=%s, render_job=%s", clip.id, job_id)
|
||||
except Exception as clip_err:
|
||||
logger.warning(
|
||||
"自动保存成片记录失败(不影响渲染任务状态): render_job=%s, error=%s",
|
||||
job_id,
|
||||
clip_err,
|
||||
)
|
||||
|
||||
except AiAvatarRenderError as exc:
|
||||
job.status = "failed"
|
||||
@@ -409,95 +360,12 @@ class AiAvatarRenderService:
|
||||
job.updated_at = datetime.now(timezone.utc)
|
||||
self.db.commit()
|
||||
logger.error("渲染任务失败 [%s]: %s", job_id, exc)
|
||||
raise
|
||||
except Exception as exc:
|
||||
job.status = "failed"
|
||||
job.error_message = f"渲染异常: {str(exc)}"
|
||||
job.updated_at = datetime.now(timezone.utc)
|
||||
self.db.commit()
|
||||
logger.exception("渲染任务异常 [%s]", job_id)
|
||||
raise
|
||||
|
||||
def _persist_to_library(self, job: AiAvatarRenderJob, cover_url: Optional[str] = None):
|
||||
"""将渲染结果写入成片库,返回 GeneratedVideo 领域对象.
|
||||
|
||||
Args:
|
||||
job: 渲染任务(必须 status=completed 且 output_video_url 非空)
|
||||
cover_url: 可选的封面 URL 覆盖(finalize 时传入即优先使用,否则取 job.output_cover_url)
|
||||
"""
|
||||
from packages.adapters.sqlalchemy_impl.generated_video_repository import (
|
||||
SQLAlchemyGeneratedVideoRepository,
|
||||
)
|
||||
from packages.domain.generated_video import GeneratedVideo
|
||||
|
||||
clip_name = f"AI数字人_{job.id[:8]}"
|
||||
# AI数字人入口是独立页面,前端可能不传 project_id(无项目概念),
|
||||
# 兜底为 "ai_avatar" 避免 DB 非空约束/查询问题;generation_task_id 用 render_job_id 便于反查。
|
||||
clip_project_id = (job.project_id or "").strip() or "ai_avatar"
|
||||
clip_generation_task_id = job.id
|
||||
effective_cover = (cover_url or "").strip() if cover_url else (job.output_cover_url or "").strip()
|
||||
clip = GeneratedVideo.create(
|
||||
project_id=clip_project_id,
|
||||
generation_task_id=clip_generation_task_id,
|
||||
name=clip_name,
|
||||
file_url=job.output_video_url,
|
||||
user_id=job.user_id,
|
||||
duration=job.output_duration or 0.0,
|
||||
thumbnail_url=effective_cover or None,
|
||||
generation_params={
|
||||
"source": "ai_avatar_render",
|
||||
"render_job_id": job.id,
|
||||
},
|
||||
)
|
||||
video_repo = SQLAlchemyGeneratedVideoRepository(self.db)
|
||||
video_repo.create(clip)
|
||||
logger.info("[数字人渲染] 成片已入库: clip_id=%s render_job=%s", clip.id, job.id)
|
||||
return clip
|
||||
|
||||
def finalize_job(self, job_id: str, user_id: str, cover_url: Optional[str] = None):
|
||||
"""用户在前端点「完成」后调用:将已 completed 的渲染任务正式入库到成片库.
|
||||
|
||||
- 必须 status=completed 才可调用
|
||||
- cover_url 若传入则优先使用并回写 job.output_cover_url;否则使用 job.output_cover_url(smart-cover/custom-cover 已写入)
|
||||
- 幂等:已入库则返回已存在的 GeneratedVideo
|
||||
"""
|
||||
from packages.adapters.sqlalchemy_impl.generated_video_repository import (
|
||||
SQLAlchemyGeneratedVideoRepository,
|
||||
)
|
||||
from packages.adapters.sqlalchemy_impl.models import GeneratedVideoModel
|
||||
|
||||
job = self.get_render_job(job_id, user_id)
|
||||
if job is None:
|
||||
raise AiAvatarRenderError("渲染任务不存在", code="RenderJobNotFound")
|
||||
if job.status != "completed":
|
||||
raise AiAvatarRenderError(f"渲染任务未完成(当前状态: {job.status}),无法入库", code="RenderNotCompleted")
|
||||
if not (job.output_video_url or "").strip():
|
||||
raise AiAvatarRenderError("渲染成片视频 URL 为空,无法入库", code="OutputVideoMissing")
|
||||
|
||||
# 幂等检查:已入库直接返回现有记录(通过 generation_task_id=job_id 识别,
|
||||
# 因为入库时 generation_task_id 被设置为 render_job_id 自身)
|
||||
existing = (
|
||||
self.db.query(GeneratedVideoModel)
|
||||
.filter(
|
||||
GeneratedVideoModel.user_id == user_id,
|
||||
GeneratedVideoModel.generation_task_id == job_id,
|
||||
)
|
||||
.first()
|
||||
)
|
||||
if existing is not None:
|
||||
logger.info("[数字人渲染] finalize 幂等命中,返回已存在记录: clip_id=%s job_id=%s", existing.id, job_id)
|
||||
return SQLAlchemyGeneratedVideoRepository(self.db).get(existing.id)
|
||||
|
||||
# 传入 cover_url 时回写到 job
|
||||
if cover_url and cover_url.strip():
|
||||
job.output_cover_url = cover_url.strip()
|
||||
# 同步更新 cover_config,保持 smart-cover 路径一致
|
||||
if isinstance(job.cover_config, dict):
|
||||
job.cover_config = {**job.cover_config, "mode": "auto_frame", "url": cover_url.strip()}
|
||||
job.updated_at = datetime.now(timezone.utc)
|
||||
self.db.commit()
|
||||
|
||||
return self._persist_to_library(job, cover_url=cover_url)
|
||||
|
||||
def _download_video(self, url: str) -> str:
|
||||
"""下载视频到临时文件."""
|
||||
@@ -515,132 +383,32 @@ class AiAvatarRenderService:
|
||||
os.unlink(tmp.name)
|
||||
raise
|
||||
|
||||
@staticmethod
|
||||
def _save_title_dataurl_to_file(dataurl: str, *, dst_path: str | None = None, job_id: str = "") -> str:
|
||||
"""解码前端传来的 data:image/png;base64,... 并保存为本地 PNG 文件。
|
||||
|
||||
Args:
|
||||
dataurl: 完整 dataURL 字符串
|
||||
dst_path: 指定输出路径;为 None 时创建临时文件并返回路径
|
||||
job_id: 仅在 dst_path 为空时用于临时文件命名
|
||||
|
||||
Returns:
|
||||
保存后的本地文件路径
|
||||
"""
|
||||
if not isinstance(dataurl, str) or not dataurl.startswith("data:image/"):
|
||||
raise ValueError("title_image_dataurl 不是合法的 data:image URL")
|
||||
# 拆分 data:image/png;base64,<payload>
|
||||
try:
|
||||
header, b64 = dataurl.split(",", 1)
|
||||
except ValueError as exc:
|
||||
raise ValueError("title_image_dataurl 缺少 base64 payload") from exc
|
||||
if "base64" not in header:
|
||||
raise ValueError("title_image_dataurl 不是 base64 编码")
|
||||
try:
|
||||
png_bytes = base64.b64decode(b64, validate=True)
|
||||
except (binascii.Error, ValueError) as exc:
|
||||
raise ValueError(f"title_image_dataurl base64 解码失败: {exc}") from exc
|
||||
if not png_bytes:
|
||||
raise ValueError("title_image_dataurl 解码后为空")
|
||||
|
||||
if dst_path:
|
||||
out_path = dst_path
|
||||
with open(out_path, "wb") as f:
|
||||
f.write(png_bytes)
|
||||
return out_path
|
||||
suffix = f"_title_{job_id}.png" if job_id else "_title.png"
|
||||
with tempfile.NamedTemporaryFile(suffix=suffix, delete=False) as tmp:
|
||||
tmp.write(png_bytes)
|
||||
return tmp.name
|
||||
|
||||
@staticmethod
|
||||
def _probe_video_resolution(video_path: str) -> tuple[int, int]:
|
||||
"""用 ffprobe 探测视频分辨率,返回 (width, height);失败返回 (0, 0)。"""
|
||||
try:
|
||||
result = subprocess.run(
|
||||
[
|
||||
"ffprobe",
|
||||
"-v",
|
||||
"error",
|
||||
"-select_streams",
|
||||
"v:0",
|
||||
"-show_entries",
|
||||
"stream=width,height",
|
||||
"-of",
|
||||
"csv=p=0:s=x",
|
||||
video_path,
|
||||
],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
timeout=15,
|
||||
)
|
||||
if result.returncode == 0 and result.stdout.strip():
|
||||
parts = result.stdout.strip().split("x")
|
||||
if len(parts) == 2:
|
||||
w, h = int(parts[0]), int(parts[1])
|
||||
if w > 0 and h > 0:
|
||||
return w, h
|
||||
except Exception as exc:
|
||||
logger.warning("[数字人渲染] ffprobe 探测分辨率失败: %s", exc)
|
||||
return 0, 0
|
||||
|
||||
def _build_ffmpeg_command(
|
||||
self,
|
||||
*,
|
||||
input_video: str,
|
||||
b_roll_segments: list[dict[str, Any]],
|
||||
extra_inputs: list[str] | None = None,
|
||||
filter_complex: str,
|
||||
final_label: Optional[str],
|
||||
output_path: str,
|
||||
) -> list[str]:
|
||||
"""构建 FFmpeg 命令(list 形式,shell=False).
|
||||
|
||||
根因修复 #1798 P0:OSS 预签名 URL 含 `&Expires=...&Signature=...` 特殊字符,
|
||||
os.system(shell=True) 会把 `&` 解释为后台命令分隔符,导致 -filter_complex 被
|
||||
当成独立命令报 sh: -filter_complex: not found(exit 127 → Python 32512)。
|
||||
list + shell=False 彻底规避 shell 转义问题。
|
||||
"""
|
||||
cmd: list[str] = ["ffmpeg", "-i", input_video]
|
||||
) -> str:
|
||||
"""构建 FFmpeg 命令."""
|
||||
# 输入文件
|
||||
inputs = f"-i {input_video}"
|
||||
for seg in b_roll_segments:
|
||||
asset_url = seg.get("asset_url", "")
|
||||
if asset_url:
|
||||
cmd.extend(["-i", asset_url])
|
||||
# 额外输入(例如前端 Canvas 渲染的标题 PNG)
|
||||
for extra in extra_inputs or []:
|
||||
cmd.extend(["-i", extra])
|
||||
inputs += f" -i {asset_url}"
|
||||
|
||||
# 滤镜
|
||||
if filter_complex and final_label:
|
||||
cmd.extend(
|
||||
[
|
||||
"-filter_complex",
|
||||
filter_complex,
|
||||
"-map",
|
||||
f"[{final_label}]",
|
||||
"-map",
|
||||
"0:a?",
|
||||
]
|
||||
)
|
||||
filter_arg = f'-filter_complex "{filter_complex}" -map "[{final_label}]"'
|
||||
elif filter_complex:
|
||||
cmd.extend(["-filter_complex", filter_complex])
|
||||
filter_arg = f'-filter_complex "{filter_complex}"'
|
||||
else:
|
||||
filter_arg = ""
|
||||
|
||||
cmd.extend(
|
||||
[
|
||||
"-c:v",
|
||||
"libx264",
|
||||
"-preset",
|
||||
"veryfast",
|
||||
"-crf",
|
||||
"23",
|
||||
"-c:a",
|
||||
"aac",
|
||||
"-b:a",
|
||||
"128k",
|
||||
"-y",
|
||||
output_path,
|
||||
]
|
||||
)
|
||||
return cmd
|
||||
return f"ffmpeg {inputs} {filter_arg} -c:v libx264 -preset veryfast -crf 23 -y {output_path}"
|
||||
|
||||
def _upload_to_oss(self, local_path: str, oss_key: str) -> str:
|
||||
"""上传文件到 OSS,返回 URL.
|
||||
|
||||
@@ -473,7 +473,6 @@ class EditPlanService:
|
||||
name_suffix: str = "变体",
|
||||
voice_duration: float = 0.0,
|
||||
rng=None,
|
||||
batch_segments: dict[str, list[tuple[float, float]]] | None = None,
|
||||
) -> EditPlan:
|
||||
"""为批量变体生成独立 plan:完整重跑单视频选片流程(#1743)。
|
||||
|
||||
@@ -490,8 +489,6 @@ class EditPlanService:
|
||||
created_by_user_id: 新 plan 归属用户。
|
||||
name_suffix: plan 名后缀。
|
||||
rng: 可选随机数(测试注入种子)。
|
||||
batch_segments: 可选,外部传入的批次内已使用素材区间(前序变体避让用)。
|
||||
传入时作为初始避让对象;未传则保持原逻辑从源 plan clips 自建(向后兼容)。
|
||||
|
||||
Raises:
|
||||
ValueError: 源 plan 不存在/无片段、素材池为空或时长全未知。
|
||||
@@ -540,26 +537,16 @@ class EditPlanService:
|
||||
voice = float(voice_duration or 0.0)
|
||||
except (TypeError, ValueError):
|
||||
voice = 0.0
|
||||
rhythm_template_for_reselect = None
|
||||
if source.config:
|
||||
rhythm_template_for_reselect = source.config.get("rhythm_template")
|
||||
|
||||
if voice > 0 and source_clips_data:
|
||||
from packages.domain.voice_duration_planner import plan_clip_durations
|
||||
|
||||
_effects: list[str | None] = [c.get("transition_effect") for c in source_clips_data]
|
||||
_tdurs: list[float] = [float(c.get("transition_duration") or 0.0) for c in source_clips_data]
|
||||
# #1855 P0:先占位durations为空dict,真正查durations在后面pool_ids确定后执行;
|
||||
# plan_clip_durations 的 asset_durations 参数在该函数中仅作最大段长钳制,
|
||||
# 这里先不依赖它(durations 还没查),传 None 让planner用默认策略;
|
||||
# 真正的asset_durations会在后面 clips_data 生成时传入 reselect_clips_for_variant
|
||||
target_durations = plan_clip_durations(
|
||||
len(source_clips_data),
|
||||
voice,
|
||||
transition_effects=_effects,
|
||||
transition_durations=_tdurs,
|
||||
rhythm_template=rhythm_template_for_reselect,
|
||||
asset_durations=None,
|
||||
)
|
||||
if target_durations:
|
||||
for _c, _d in zip(source_clips_data, target_durations, strict=False):
|
||||
@@ -595,18 +582,12 @@ class EditPlanService:
|
||||
created_by_user_id=created_by_user_id or (source.created_by_user_id or ""),
|
||||
)
|
||||
|
||||
# 批次内区间:外部传入时使用外部传入(含前序变体已用区间);
|
||||
# 否则保持原逻辑从源 plan clips 自建(向后兼容)
|
||||
if batch_segments is not None:
|
||||
batch_segments_resolved: dict[str, list[tuple[float, float]]] = {
|
||||
k: list(v) for k, v in batch_segments.items()
|
||||
}
|
||||
else:
|
||||
batch_segments_resolved = {}
|
||||
for c in clips:
|
||||
if c.asset_id and float(c.duration or 0) > 0:
|
||||
st = float(c.start_time or 0.0)
|
||||
batch_segments_resolved.setdefault(c.asset_id, []).append((st, st + float(c.duration)))
|
||||
# 批次内区间:以源 plan(变体 0)片段为初始避让对象
|
||||
batch_segments: dict[str, list[tuple[float, float]]] = {}
|
||||
for c in clips:
|
||||
if c.asset_id and float(c.duration or 0) > 0:
|
||||
st = float(c.start_time or 0.0)
|
||||
batch_segments.setdefault(c.asset_id, []).append((st, st + float(c.duration)))
|
||||
|
||||
clips_data = reselect_clips_for_variant(
|
||||
source_clips_data,
|
||||
@@ -614,7 +595,7 @@ class EditPlanService:
|
||||
asset_durations=durations,
|
||||
asset_scene_points=scene_points,
|
||||
historical_used_segments=historical,
|
||||
batch_segments=batch_segments_resolved,
|
||||
batch_segments=batch_segments,
|
||||
target_durations=target_durations,
|
||||
rng=rng,
|
||||
)
|
||||
@@ -786,17 +767,6 @@ class EditPlanService:
|
||||
if plan is None:
|
||||
return None
|
||||
|
||||
# #1855 P0:幂等判断——如果已成功分配过且当前 total_duration 已接近 voice_duration,直接返回
|
||||
try:
|
||||
existing_mark = None
|
||||
if plan.config:
|
||||
existing_mark = plan.config.get("voice_duration_applied")
|
||||
cur_total = float(plan.total_duration or 0.0)
|
||||
if existing_mark is not None and abs(existing_mark - voice) < 1e-6 and abs(cur_total - voice) < 0.5:
|
||||
return plan
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
clips: List[EditPlanClip] = []
|
||||
skip, page = 0, 500
|
||||
while True:
|
||||
@@ -868,10 +838,6 @@ class EditPlanService:
|
||||
)
|
||||
try:
|
||||
plan.total_duration = net
|
||||
# #1855 P0:写入幂等标记,避免二次调用时只重分配 duration 不重算 start_time
|
||||
new_cfg = dict(plan.config or {})
|
||||
new_cfg["voice_duration_applied"] = voice
|
||||
plan.config = new_cfg
|
||||
db = self._clip_repo.session
|
||||
db.commit()
|
||||
except Exception:
|
||||
@@ -912,69 +878,6 @@ class EditPlanService:
|
||||
rng = rng or _random.Random()
|
||||
plan_ids: list[str] = []
|
||||
|
||||
# #1855 P0:先确定片段数 clip_count(用于节奏模板生成长度匹配)
|
||||
from packages.domain.bgm_pool import allocate_bgm_pool_for_variants
|
||||
from packages.domain.variant_plan_selector import (
|
||||
generate_pixel_perturbation,
|
||||
generate_visual_perturbation,
|
||||
)
|
||||
from packages.domain.voice_duration_planner import RHYTHM_TEMPLATES, adapt_template_length
|
||||
|
||||
clip_count = 0
|
||||
# 从源 plan 获取片段数(分页读,避免关系加载问题)
|
||||
_sclips: list = []
|
||||
_sk, _pg = 0, 500
|
||||
while True:
|
||||
_b = self._clip_repo.list_by_plan(source_plan_id, skip=_sk, limit=_pg)
|
||||
if not _b:
|
||||
break
|
||||
_sclips.extend(_b)
|
||||
if len(_b) < _pg:
|
||||
break
|
||||
_sk += _pg
|
||||
clip_count = len(_sclips)
|
||||
|
||||
# 预先生成所有 N 个变体的节奏模板/BGM/扰动参数(时机提前到选片前写入config)
|
||||
rhythm_templates_for_variants: list = []
|
||||
for _idx in range(count):
|
||||
if clip_count > 0:
|
||||
variant_seed = rng.randint(0, 999999)
|
||||
_tpl = adapt_template_length(RHYTHM_TEMPLATES[variant_seed % len(RHYTHM_TEMPLATES)], clip_count)
|
||||
rhythm_templates_for_variants.append(_tpl)
|
||||
else:
|
||||
rhythm_templates_for_variants.append(None)
|
||||
|
||||
source_bgm_config: dict = {}
|
||||
source_plan = self.get_plan(source_plan_id)
|
||||
if source_plan and source_plan.config:
|
||||
source_bgm_config = source_plan.config.get("bgm", {}) or {}
|
||||
variant_seeds_for_bgm = [rng.randint(0, 999999) for _ in range(count)]
|
||||
bgm_pool_assignments = allocate_bgm_pool_for_variants(source_bgm_config, variant_seeds_for_bgm)
|
||||
|
||||
def _build_variant_config_update(idx: int) -> dict:
|
||||
"""构建单个变体的 config 更新(节奏模板/BGM/视觉/像素扰动)。"""
|
||||
upd: dict = {}
|
||||
try:
|
||||
perturbation = generate_visual_perturbation(rng)
|
||||
if idx == 0:
|
||||
perturbation["hflip"] = False
|
||||
upd["visual_perturbation"] = perturbation
|
||||
except Exception:
|
||||
logger.exception("变体 %d 视觉扰动生成失败(不阻断)", idx)
|
||||
try:
|
||||
pixel_pert = generate_pixel_perturbation(rng)
|
||||
upd["pixel_perturbation"] = pixel_pert
|
||||
except Exception:
|
||||
logger.exception("变体 %d 像素扰动生成失败(不阻断)", idx)
|
||||
rt = rhythm_templates_for_variants[idx] if idx < len(rhythm_templates_for_variants) else None
|
||||
if rt is not None:
|
||||
upd["rhythm_template"] = rt
|
||||
if idx < len(bgm_pool_assignments):
|
||||
existing_bgm = dict((source_plan.config or {}).get("bgm", {}) or {})
|
||||
existing_bgm.update(bgm_pool_assignments[idx])
|
||||
upd["bgm"] = existing_bgm
|
||||
return upd
|
||||
|
||||
# 变体 0:clone(片段结构同源 plan,起点重算),不污染源 plan
|
||||
plan0 = self.clone_plan_for_variant(
|
||||
source_plan_id,
|
||||
@@ -987,15 +890,6 @@ class EditPlanService:
|
||||
v0_voice = float(voice_durations[0] or 0.0)
|
||||
except (TypeError, ValueError):
|
||||
v0_voice = 0.0
|
||||
|
||||
# #1855 P0:在配音分配前先写入变体0的节奏模板/扰动/BGM,确保 apply_voice_duration_to_plan 能读到 rhythm_template
|
||||
try:
|
||||
_cfg0 = _build_variant_config_update(0)
|
||||
if _cfg0:
|
||||
self.update_plan_config(plan0.id, _cfg0)
|
||||
except Exception:
|
||||
logger.exception("变体0 配置写入失败(不阻断): plan=%s", plan0.id)
|
||||
|
||||
if v0_voice > 0:
|
||||
try:
|
||||
self.apply_voice_duration_to_plan(plan0.id, v0_voice)
|
||||
@@ -1003,12 +897,7 @@ class EditPlanService:
|
||||
logger.exception("变体0 配音分配失败(不阻断): plan=%s", plan0.id)
|
||||
plan_ids.append(plan0.id)
|
||||
|
||||
# #1855 P0:批次内素材区间避让表——从变体0实际落库的clips构建初始值(公共函数)
|
||||
from app.services.generation_common import collect_plan_segments as _collect_plan_segments
|
||||
|
||||
batch_segments_acc: dict[str, list[tuple[float, float]]] = _collect_plan_segments(plan0.id, self._clip_repo)
|
||||
|
||||
# 变体 1..N-1:独立选片(传入累积的 batch_segments 做区间避让)
|
||||
# 变体 1..N-1:独立选片
|
||||
for i in range(1, count):
|
||||
voice = 0.0
|
||||
if voice_durations and i < len(voice_durations):
|
||||
@@ -1016,14 +905,6 @@ class EditPlanService:
|
||||
voice = float(voice_durations[i] or 0.0)
|
||||
except (TypeError, ValueError):
|
||||
voice = 0.0
|
||||
|
||||
# #1855 P0:在reselect前先为"变体i"准备配置更新——但reselect内部复制的是source.config,
|
||||
# 所以每个变体独立的节奏模板需要在reselect后单独写入config;
|
||||
# 但 plan_clip_durations 用的是 source.config.rhythm_template(即源plan的节奏模板),
|
||||
# 为了让每个变体在选片阶段就使用自己的节奏模板分配段长,这里采用:
|
||||
# - reselect 仍使用源 plan 的 rhythm_template(保持片段骨架一致)
|
||||
# - 选片完成后立即写入该变体自己的 rhythm_template/扰动/BGM 到config,
|
||||
# 后续不再二次 apply_voice_duration_to_plan(由幂等标记跳过)
|
||||
variant = self.reselect_plan_for_variant(
|
||||
source_plan_id,
|
||||
candidate_asset_ids,
|
||||
@@ -1031,26 +912,73 @@ class EditPlanService:
|
||||
name_suffix=f"变体{i + 1}",
|
||||
voice_duration=voice,
|
||||
rng=rng,
|
||||
batch_segments=batch_segments_acc,
|
||||
)
|
||||
|
||||
# 选片完成后写入该变体的独立配置(节奏模板/扰动/BGM)
|
||||
try:
|
||||
_cfgi = _build_variant_config_update(i)
|
||||
if _cfgi:
|
||||
self.update_plan_config(variant.id, _cfgi)
|
||||
except Exception:
|
||||
logger.exception("变体 %d 配置写入失败(不阻断): plan=%s", i, variant.id)
|
||||
|
||||
plan_ids.append(variant.id)
|
||||
|
||||
# #1855 P0:把当前新变体的 clips 区间追加到 batch_segments,供下一变体避让
|
||||
# #1764:为每个变体生成独立节奏模板(让批量视频片段时长分布不同)
|
||||
from packages.domain.voice_duration_planner import RHYTHM_TEMPLATES, adapt_template_length
|
||||
|
||||
clip_count = 0
|
||||
if voice_durations and len(voice_durations) > 0:
|
||||
# 从源 plan 获取片段数
|
||||
source_plan = self.get_plan(source_plan_id)
|
||||
if source_plan and hasattr(source_plan, "clips"):
|
||||
clip_count = len(list(source_plan.clips)) if source_plan.clips else 0
|
||||
|
||||
rhythm_templates_for_variants = []
|
||||
if clip_count > 0:
|
||||
for idx in range(len(plan_ids)):
|
||||
# 每个变体用不同的 seed 选择节奏模板
|
||||
variant_seed = rng.randint(0, 999999)
|
||||
template = adapt_template_length(RHYTHM_TEMPLATES[variant_seed % len(RHYTHM_TEMPLATES)], clip_count)
|
||||
rhythm_templates_for_variants.append(template)
|
||||
logger.info("变体 %d 节奏模板: plan=%s template=%s", idx, plan_ids[idx], template)
|
||||
|
||||
# #1767:BGM 池差异化分配(让批量变体使用不同 BGM / 段落 / 音量)
|
||||
from packages.domain.bgm_pool import allocate_bgm_pool_for_variants
|
||||
|
||||
source_bgm_config = {}
|
||||
source_plan = self.get_plan(source_plan_id)
|
||||
if source_plan and source_plan.config:
|
||||
source_bgm_config = source_plan.config.get("bgm", {}) or {}
|
||||
|
||||
variant_seeds_for_bgm = [rng.randint(0, 999999) for _ in plan_ids]
|
||||
bgm_pool_assignments = allocate_bgm_pool_for_variants(source_bgm_config, variant_seeds_for_bgm)
|
||||
|
||||
# 为每个变体生成独立视觉扰动参数(让批量视频画面本身更不同)
|
||||
from packages.domain.variant_plan_selector import generate_visual_perturbation
|
||||
|
||||
for idx, pid in enumerate(plan_ids):
|
||||
try:
|
||||
_new_segs = _collect_plan_segments(variant.id, self._clip_repo)
|
||||
for _aid, _ivs in _new_segs.items():
|
||||
batch_segments_acc.setdefault(_aid, []).extend(_ivs)
|
||||
perturbation = generate_visual_perturbation(rng)
|
||||
# 变体 0 不做 hflip(保持预览 plan 原始画面方向)
|
||||
if idx == 0:
|
||||
perturbation["hflip"] = False
|
||||
config_update = {"visual_perturbation": perturbation}
|
||||
# #1764:写入节奏模板
|
||||
if idx < len(rhythm_templates_for_variants):
|
||||
config_update["rhythm_template"] = rhythm_templates_for_variants[idx]
|
||||
# #1765:写入像素级扰动滤镜
|
||||
from packages.domain.variant_plan_selector import generate_pixel_perturbation
|
||||
|
||||
pixel_pert = generate_pixel_perturbation(rng)
|
||||
config_update["pixel_perturbation"] = pixel_pert
|
||||
# #1767:写入 BGM 池分配(覆盖 bgm 配置中的 preset_id / audio_offset / volume_adjust_db)
|
||||
if idx < len(bgm_pool_assignments):
|
||||
existing_bgm = dict((source_plan.config or {}).get("bgm", {}) or {})
|
||||
existing_bgm.update(bgm_pool_assignments[idx])
|
||||
config_update["bgm"] = existing_bgm
|
||||
self.update_plan_config(pid, config_update)
|
||||
logger.info(
|
||||
"变体 %d 视觉扰动+像素扰动+BGM池: plan=%s vis=%s pix=%s bgm=%s",
|
||||
idx,
|
||||
pid,
|
||||
perturbation,
|
||||
pixel_pert,
|
||||
bgm_pool_assignments[idx] if idx < len(bgm_pool_assignments) else None,
|
||||
)
|
||||
except Exception:
|
||||
logger.exception("变体 %d 区间收集失败(不阻断): plan=%s", i, variant.id)
|
||||
logger.exception("变体 %d 视觉扰动生成失败(不阻断): plan=%s", idx, pid)
|
||||
|
||||
# 标记所有变体 plan 的 clips 为 ready(已分配素材+起点,语义上就是 ready)
|
||||
for pid in plan_ids:
|
||||
|
||||
@@ -1,189 +0,0 @@
|
||||
"""智能剪辑公共服务辅助函数(从 route 层下沉)。
|
||||
|
||||
集中管理:
|
||||
- query_voice_durations:批量查询配音素材时长
|
||||
- writeback_edit_plan_config:任务入队后回写 EditPlan.config
|
||||
- collect_plan_segments:分页读取 plan clips 构建素材区间表(变体避让用)
|
||||
- resolve_latest_plan_by_template:按 template_id + user_id 查最新 EditPlan
|
||||
|
||||
设计原则:
|
||||
- 无副作用的纯查询 / 幂等写回;失败一律不阻断主流程(记日志 + 返回安全默认值)
|
||||
- 不依赖 FastAPI / HTTPException,便于 service 层和 worker 复用
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from typing import Any, Optional
|
||||
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def query_voice_durations(db: Session, voice_ids: list[str]) -> list[float]:
|
||||
"""批量查询配音素材时长(秒),#1749 配音时长分配用。
|
||||
|
||||
逐项 try/float 硬化:MagicMock/异常/缺失 → 0.0(无配音不分配,不阻断)。
|
||||
|
||||
#1855 P0修复:不再对 voice_ids 去重,保持与调用方传入顺序/长度一致,
|
||||
允许同配音id多次出现时返回相同时长(支持"同配音N变体"的时长对齐)。
|
||||
"""
|
||||
raw_ids = list(voice_ids or [])
|
||||
if not raw_ids:
|
||||
return []
|
||||
unique_ids: list[str] = []
|
||||
_seen: set[str] = set()
|
||||
for v in raw_ids:
|
||||
if v and v not in _seen:
|
||||
_seen.add(v)
|
||||
unique_ids.append(v)
|
||||
if not unique_ids:
|
||||
return [0.0 for _ in raw_ids]
|
||||
try:
|
||||
from packages.adapters.sqlalchemy_impl.models import AssetModel
|
||||
|
||||
rows = db.query(AssetModel.id, AssetModel.duration).filter(AssetModel.id.in_(unique_ids)).all()
|
||||
dur_map: dict[str, float] = {}
|
||||
for row in rows:
|
||||
try:
|
||||
dur_map[row[0]] = float(row[1] or 0.0)
|
||||
except (TypeError, ValueError):
|
||||
dur_map[row[0]] = 0.0
|
||||
return [dur_map.get(v, 0.0) if v else 0.0 for v in raw_ids]
|
||||
except Exception:
|
||||
logger.warning("[generation_common] 配音时长查询失败(按无配音处理,不阻断)", exc_info=True)
|
||||
return [0.0 for _ in raw_ids]
|
||||
|
||||
|
||||
def writeback_edit_plan_config(
|
||||
plan_id: str,
|
||||
task_id: str,
|
||||
title_config: dict | None,
|
||||
db: Session,
|
||||
) -> None:
|
||||
"""任务入队成功后,回写 EditPlan.config:generation_task_id + title_config。
|
||||
|
||||
用 merge 方式更新,不整体覆盖 config,避免丢失其他字段。
|
||||
失败只记日志,不影响任务创建。
|
||||
"""
|
||||
if not plan_id:
|
||||
return
|
||||
try:
|
||||
from packages.adapters.sqlalchemy_impl.models import EditPlanModel
|
||||
|
||||
plan_model = db.query(EditPlanModel).filter(EditPlanModel.id == plan_id).first()
|
||||
if plan_model is None:
|
||||
logger.warning("[generation_common] 回写plan.config失败: plan不存在 plan_id=%s", plan_id)
|
||||
return
|
||||
|
||||
current_config = plan_model.config if isinstance(plan_model.config, dict) else {}
|
||||
merged = dict(current_config)
|
||||
merged["generation_task_id"] = task_id
|
||||
|
||||
if title_config:
|
||||
# #1901 统一字段名为 "title"(worker sync_configs_to_plan 写的是 "title")
|
||||
# 先读取新旧两个 key,判断标题文字是否变化
|
||||
old_title_cfg = merged.get("title", {}) or {}
|
||||
if not isinstance(old_title_cfg, dict) or not (old_title_cfg.get("text") or "").strip():
|
||||
old_title_cfg = merged.get("title_config", {}) or {}
|
||||
old_title_text = (old_title_cfg.get("text") or "").strip() if isinstance(old_title_cfg, dict) else ""
|
||||
new_title_text = (title_config.get("text") or "").strip()
|
||||
if old_title_text != new_title_text:
|
||||
if "cover" in merged:
|
||||
del merged["cover"]
|
||||
logger.info(
|
||||
"[generation_common] 标题变化,清除旧封面: plan_id=%s old_title=%s new_title=%s",
|
||||
plan_id,
|
||||
old_title_text,
|
||||
new_title_text,
|
||||
)
|
||||
# 字段名归一化(font_size→size, font_preset→font, font_color→color),与 worker sync_configs_to_plan 保持一致
|
||||
normalized = dict(title_config)
|
||||
if "font_size" in normalized and "size" not in normalized:
|
||||
normalized["size"] = normalized["font_size"]
|
||||
if "font_preset" in normalized and "font" not in normalized:
|
||||
normalized["font"] = normalized["font_preset"]
|
||||
if "font_color" in normalized and "color" not in normalized:
|
||||
normalized["color"] = normalized["font_color"]
|
||||
merged["title"] = normalized
|
||||
# 清掉旧 key,避免双字段并存
|
||||
merged.pop("title_config", None)
|
||||
|
||||
plan_model.config = merged
|
||||
db.commit()
|
||||
logger.info(
|
||||
"[generation_common] 回写plan.config成功: plan_id=%s task_id=%s keys=%s",
|
||||
plan_id,
|
||||
task_id,
|
||||
list(merged.keys()),
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning(
|
||||
"[generation_common] 回写plan.config异常(不影响任务创建): plan_id=%s error=%s",
|
||||
plan_id,
|
||||
e,
|
||||
exc_info=True,
|
||||
)
|
||||
try:
|
||||
db.rollback()
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
|
||||
def collect_plan_segments(
|
||||
plan_id: str,
|
||||
clip_repo: Any,
|
||||
*,
|
||||
page_size: int = 500,
|
||||
) -> dict[str, list[tuple[float, float]]]:
|
||||
"""分页读取 plan 所有 clips,构建 {asset_id: [(start, end), ...]} 素材区间表。
|
||||
|
||||
用于 #1855 P0 批次内素材区间避让(变体间素材片段重叠控制)。
|
||||
"""
|
||||
segs: dict[str, list[tuple[float, float]]] = {}
|
||||
sk, pg = 0, page_size
|
||||
while True:
|
||||
batch = clip_repo.list_by_plan(plan_id, skip=sk, limit=pg)
|
||||
if not batch:
|
||||
break
|
||||
for c in batch:
|
||||
if c.asset_id and float(c.duration or 0) > 0:
|
||||
st = float(c.start_time or 0.0)
|
||||
segs.setdefault(c.asset_id, []).append((st, st + float(c.duration)))
|
||||
if len(batch) < pg:
|
||||
break
|
||||
sk += pg
|
||||
return segs
|
||||
|
||||
|
||||
def resolve_latest_plan_by_template(
|
||||
db: Session,
|
||||
*,
|
||||
template_id: str,
|
||||
user_id: str,
|
||||
) -> Optional[str]:
|
||||
"""按 template_id + user_id 查找最新的 EditPlan.id(模板兜底用)。找不到返回 None。"""
|
||||
if not (template_id or "").strip():
|
||||
return None
|
||||
try:
|
||||
from packages.adapters.sqlalchemy_impl.models import EditPlanModel
|
||||
|
||||
latest = (
|
||||
db.query(EditPlanModel)
|
||||
.filter(
|
||||
EditPlanModel.template_id == template_id.strip(),
|
||||
EditPlanModel.created_by_user_id == user_id,
|
||||
)
|
||||
.order_by(EditPlanModel.created_at.desc())
|
||||
.first()
|
||||
)
|
||||
return latest.id if latest else None
|
||||
except Exception:
|
||||
logger.warning(
|
||||
"[generation_common] 按template查找最新plan失败: template=%s user=%s",
|
||||
template_id,
|
||||
user_id,
|
||||
exc_info=True,
|
||||
)
|
||||
return None
|
||||
@@ -1,12 +1,8 @@
|
||||
"""对口型 Service — #1796 MediaKit 对口型业务逻辑, #1809 参数调整, #1845 配音前置.
|
||||
"""对口型 Service — #1796 MediaKit 对口型业务逻辑, #1809 参数调整.
|
||||
|
||||
职责:
|
||||
- 创建/查询对口型任务
|
||||
- 三输入模式:
|
||||
1. TTS 直生(voice_id + script_text)→ 走 Celery 异步(降级路径)
|
||||
2. 直接音频(audio_url,前端未传 timings)→ 同步下载 + 算 timings + 提交 MediaKit
|
||||
3. 预合成音频(audio_url + sentence_timings,#1845 新主路径)→ 同步 ffprobe 校验时长 +
|
||||
写入前端传来的 timings → 直接提交 MediaKit(~2-3s)
|
||||
- 双输入模式:TTS 直生(voice_id + script_text,内部先合成音频转存 OSS)或直接音频(audio_url)
|
||||
- 调用 MediaKit 客户端提交异步任务
|
||||
- 轮询更新任务状态(中间状态同步 DB,成片转存自家 OSS)
|
||||
- 用户隔离(每个用户只能操作自己的任务)
|
||||
@@ -30,22 +26,19 @@ from app.services.mediakit_client import (
|
||||
get_mediakit_client,
|
||||
)
|
||||
|
||||
# Celery 异步任务:TTS 合成 + MediaKit 提交(降级路径)
|
||||
# Celery 异步任务:TTS 合成 + MediaKit 提交(#lipsync-speed-optimization)
|
||||
from app.tasks.lipsync_tts import tts_synthesize_and_submit
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from packages.adapters.sqlalchemy_impl.models import LipsyncJobModel
|
||||
from packages.application.cosyvoice_service import CosyVoiceError, normalize_emotion
|
||||
from packages.domain.sentence_timings import (
|
||||
compute_sentence_timings,
|
||||
probe_audio_duration,
|
||||
)
|
||||
from packages.shared.storage import get_shared_storage_service
|
||||
from packages.shared.url_security import ALLOWED_AUDIO_MIME_TYPES, safe_download_bytes
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 传给 MediaKit GPU worker / 回给前端播放的 OSS 预签名有效期:7 天。
|
||||
# MediaKit 排队 + 拉取可能延迟,私有桶裸 URL 或 1 小时短预签名都会 403,故统一重签长有效期。
|
||||
MEDIAKIT_URL_TTL_SECONDS = 7 * 24 * 3600
|
||||
|
||||
|
||||
@@ -149,100 +142,6 @@ class LipsyncService:
|
||||
logger.warning("TTS 音频转存 OSS 失败,回退临时 URL: job_id=%s err=%s", job_id, exc)
|
||||
return temp_url
|
||||
|
||||
def _submit_audio_direct(
|
||||
self,
|
||||
*,
|
||||
job: LipsyncJobModel,
|
||||
supplied_timings: Optional[list] = None,
|
||||
supplied_duration: Optional[float] = None,
|
||||
) -> None:
|
||||
"""音频直传模式(包含 #1845 预合成路径):同步下载 → ffprobe → timings → 提交 MediaKit.
|
||||
|
||||
直接在 HTTP 请求内完成,不走 Celery。job.status 成功后置为 submitted。
|
||||
失败时把 job 标成 failed 并 commit,然后抛 MediaKitError。
|
||||
|
||||
Args:
|
||||
job: 已 commit 的 LipsyncJobModel(audio_url / video_url 已写入)
|
||||
supplied_timings: 前端传来的预合成 timings(可选,可信时直接用)
|
||||
supplied_duration: 前端传来的预合成时长(可选,用于优先避免重复探测)
|
||||
"""
|
||||
# 1. 下载音频
|
||||
audio_data: bytes | None = None
|
||||
try:
|
||||
audio_data = safe_download_bytes(
|
||||
job.audio_url,
|
||||
purpose="lipsync_direct_audio",
|
||||
allowed_mime_types=ALLOWED_AUDIO_MIME_TYPES,
|
||||
timeout=60.0,
|
||||
)
|
||||
logger.info(
|
||||
"[lipsync] 直传音频下载完成: job_id=%s size=%d",
|
||||
job.id,
|
||||
len(audio_data) if audio_data else 0,
|
||||
)
|
||||
except Exception as exc:
|
||||
logger.warning("[lipsync] 直传音频下载失败,跳过 timings 计算: job_id=%s err=%s", job.id, exc)
|
||||
|
||||
# 2. ffprobe 探测时长(优先用前端传入的预合成时长,但以 ffprobe 为准做兜底校验)
|
||||
audio_duration = 0.0
|
||||
if audio_data:
|
||||
audio_duration = probe_audio_duration(audio_data)
|
||||
if audio_duration <= 0 and supplied_duration and supplied_duration > 0:
|
||||
audio_duration = supplied_duration
|
||||
logger.info(
|
||||
"[lipsync] ffprobe 失败,使用前端传入的预合成时长: job_id=%s duration=%.2f", job.id, audio_duration
|
||||
)
|
||||
|
||||
# 3. 句子时间戳:优先用前端预合成传入的 timings(后端预合成接口已经算过,可信);
|
||||
# 否则若音频下载成功则重算;否则不设置(不阻塞主流程)
|
||||
timings: Optional[list] = None
|
||||
if supplied_timings:
|
||||
timings = supplied_timings
|
||||
logger.info("[lipsync] 使用前端预合成句子时间戳: job_id=%s sentences=%d", job.id, len(timings))
|
||||
elif audio_data and audio_duration > 0 and job.script_text:
|
||||
try:
|
||||
timings = compute_sentence_timings(audio_data, job.script_text, audio_duration)
|
||||
logger.info(
|
||||
"[lipsync] 后端重算句子时间戳: job_id=%s sentences=%d duration=%.2f",
|
||||
job.id,
|
||||
len(timings) if timings else 0,
|
||||
audio_duration,
|
||||
)
|
||||
except Exception as exc:
|
||||
logger.warning("[lipsync] 句子时间戳计算失败(不阻塞): job_id=%s err=%s", job.id, exc)
|
||||
|
||||
if timings:
|
||||
job.sentence_timings = timings
|
||||
|
||||
# 4. 签名 URL 并提交 MediaKit
|
||||
video_url = self._sign_media_url(job.video_url)
|
||||
signed_audio_url = self._sign_media_url(job.audio_url)
|
||||
job.audio_url = signed_audio_url
|
||||
|
||||
try:
|
||||
result = self.client.submit_lipsync(
|
||||
video_url=video_url,
|
||||
audio_url=signed_audio_url,
|
||||
enable_video_loop=job.enable_video_loop,
|
||||
client_token=job.id,
|
||||
)
|
||||
job.mediakit_task_id = result["task_id"]
|
||||
job.status = "submitted"
|
||||
job.submitted_at = datetime.now(timezone.utc)
|
||||
self.db.commit()
|
||||
logger.info(
|
||||
"[lipsync] 直传音频已提交 MediaKit: job_id=%s task_id=%s",
|
||||
job.id,
|
||||
result["task_id"],
|
||||
)
|
||||
except MediaKitError as exc:
|
||||
job.status = "failed"
|
||||
job.error_message = str(exc)
|
||||
job.error_code = exc.code
|
||||
logger.error("[lipsync] 直传音频提交 MediaKit 失败: job_id=%s err=%s", job.id, exc)
|
||||
self.db.commit()
|
||||
raise
|
||||
|
||||
# ── 创建任务 ──────────────────────────────────────────────────────────
|
||||
|
||||
def create_job(
|
||||
@@ -251,35 +150,27 @@ class LipsyncService:
|
||||
user_id: str,
|
||||
video_url: str,
|
||||
audio_url: str = "",
|
||||
audio_duration: Optional[float] = None,
|
||||
sentence_timings: Optional[list] = None,
|
||||
voice_id: str = "",
|
||||
script_text: str = "",
|
||||
speed: float = 1.0,
|
||||
emotion: str = "",
|
||||
enable_video_loop: bool = True,
|
||||
enable_video_loop: bool = False,
|
||||
project_id: str = "",
|
||||
) -> LipsyncJobModel:
|
||||
"""创建对口型任务.
|
||||
|
||||
三种输入模式:
|
||||
两种输入模式:
|
||||
- TTS 直生:voice_id + script_text(audio_url 留空)
|
||||
→ 创建 DB 记录(状态 tts_processing),dispatch Celery 异步任务(降级路径)。
|
||||
API 响应 <1s。
|
||||
- 直接音频:audio_url 非空 + 无 sentence_timings
|
||||
→ 同步下载音频 + 重算 timings + 提交 MediaKit(几秒完成)。
|
||||
- 预合成音频(#1845 新主路径):audio_url 非空 + 传 sentence_timings
|
||||
→ 同步 ffprobe 校验时长 + 写入 timings + 提交 MediaKit(~2-3s)。
|
||||
→ 先创建 DB 记录(状态 tts_processing),再 dispatch Celery 异步任务
|
||||
执行 TTS 合成 + MediaKit 提交。API 响应 <1s。
|
||||
- 直接音频:提供 audio_url
|
||||
→ 同步提交 MediaKit,状态直接设为 submitted。
|
||||
|
||||
Raises:
|
||||
MediaKitError: 参数校验失败或 MediaKit 提交失败
|
||||
MediaKitError: 参数校验失败或 MediaKit 提交失败(仅直接音频模式)
|
||||
"""
|
||||
# 0. 输入校验
|
||||
is_pre_synth = bool(audio_url) and bool(sentence_timings)
|
||||
bool(audio_url) and not is_pre_synth
|
||||
is_tts_mode = not bool(audio_url)
|
||||
|
||||
if is_tts_mode:
|
||||
if not audio_url:
|
||||
if not (voice_id and script_text):
|
||||
raise MediaKitError(
|
||||
"必须提供 audio_url 或 voice_id+script_text",
|
||||
@@ -287,13 +178,10 @@ class LipsyncService:
|
||||
)
|
||||
# TTS 模式:在 HTTP 请求中同步校验音色归属,快速失败
|
||||
self._resolve_voice_id(voice_id, user_id)
|
||||
elif is_pre_synth:
|
||||
# 预合成模式:script_text 可空(因为 timings 已自带句子文本),但仍建议传
|
||||
if not isinstance(sentence_timings, list) or len(sentence_timings) == 0:
|
||||
raise MediaKitError("预合成模式 sentence_timings 不能为空", code="InvalidInput")
|
||||
|
||||
# 1. 创建数据库记录
|
||||
job_id = str(uuid.uuid4())
|
||||
is_tts_mode = not bool(audio_url)
|
||||
job = LipsyncJobModel(
|
||||
id=job_id,
|
||||
user_id=user_id,
|
||||
@@ -304,19 +192,14 @@ class LipsyncService:
|
||||
voice_id=voice_id or "",
|
||||
script_text=script_text or "",
|
||||
speed=speed,
|
||||
emotion=normalize_emotion(emotion) if is_tts_mode else (emotion or ""),
|
||||
# 音频直传(含预合成)直接进入 pending(后续同步改为 submitted);TTS 模式进入 tts_processing
|
||||
emotion=normalize_emotion(emotion),
|
||||
status="tts_processing" if is_tts_mode else "pending",
|
||||
)
|
||||
self.db.add(job)
|
||||
self.db.flush()
|
||||
|
||||
# ⚠️ 必须先 commit 再发 Celery 任务 / 后续同步操作,避免事务竞态
|
||||
self.db.commit()
|
||||
self.db.refresh(job)
|
||||
|
||||
if is_tts_mode:
|
||||
# 2a. TTS 模式:dispatch Celery 异步任务处理 TTS 合成 + MediaKit 提交(降级路径)
|
||||
# 2a. TTS 模式:dispatch Celery 异步任务处理 TTS 合成 + MediaKit 提交
|
||||
try:
|
||||
tts_synthesize_and_submit.apply_async(
|
||||
args=(
|
||||
@@ -329,6 +212,8 @@ class LipsyncService:
|
||||
)
|
||||
)
|
||||
except Exception as exc:
|
||||
# 投递失败时立即把 job 标成 failed 并写入 error_message,
|
||||
# 前端轮询时能直接看到失败原因,不会无限卡在 tts_processing。
|
||||
logger.exception(
|
||||
"Celery 任务提交失败,TTS 任务已创建但未触发执行: job_id=%s err=%s",
|
||||
job_id,
|
||||
@@ -338,102 +223,34 @@ class LipsyncService:
|
||||
job.error_message = f"Celery 任务投递失败: {exc}"
|
||||
job.error_code = "AsyncDispatchFailed"
|
||||
job.updated_at = datetime.now(timezone.utc)
|
||||
self.db.commit()
|
||||
else:
|
||||
# 2b/2c. 直接音频 / 预合成音频:同步路径
|
||||
self._submit_audio_direct(
|
||||
job=job,
|
||||
supplied_timings=sentence_timings,
|
||||
supplied_duration=audio_duration,
|
||||
)
|
||||
self.db.refresh(job)
|
||||
# 2b. 直接音频模式:同步签名并提交 MediaKit
|
||||
video_url = self._sign_media_url(video_url)
|
||||
if audio_url:
|
||||
audio_url = self._sign_media_url(audio_url)
|
||||
job.audio_url = audio_url
|
||||
|
||||
try:
|
||||
result = self.client.submit_lipsync(
|
||||
video_url=video_url,
|
||||
audio_url=audio_url,
|
||||
enable_video_loop=enable_video_loop,
|
||||
client_token=job_id,
|
||||
)
|
||||
job.mediakit_task_id = result["task_id"]
|
||||
job.status = "submitted"
|
||||
job.submitted_at = datetime.now(timezone.utc)
|
||||
except MediaKitError as exc:
|
||||
job.status = "failed"
|
||||
job.error_message = str(exc)
|
||||
job.error_code = exc.code
|
||||
logger.error("提交对口型任务失败: %s", exc)
|
||||
raise
|
||||
|
||||
self.db.commit()
|
||||
self.db.refresh(job)
|
||||
return job
|
||||
|
||||
# ── TTS 预合成(#1845 步骤1「生成配音」同步接口使用) ──────────────────
|
||||
|
||||
def preview_tts(
|
||||
self,
|
||||
*,
|
||||
user_id: str,
|
||||
voice_id: str,
|
||||
script_text: str,
|
||||
speed: float = 1.0,
|
||||
emotion: str = "natural",
|
||||
) -> dict:
|
||||
"""同步做 TTS 合成 + 下载 + ffprobe + 句子时间戳计算.
|
||||
|
||||
不创建 LipsyncJob、不转存 OSS,直接返回 CosyVoice 临时 URL(~24h 有效期)。
|
||||
耗时约 2-3 秒,由前端在步骤1点「生成配音」时同步等待。
|
||||
|
||||
Returns:
|
||||
{"audio_url": str, "duration": float, "sentence_timings": list[dict]}
|
||||
|
||||
Raises:
|
||||
MediaKitError: TTS 合成失败 / 下载失败 / ffprobe 失败
|
||||
"""
|
||||
# 1. 音色解析(校验克隆音色归属)
|
||||
actual_voice_id = self._resolve_voice_id(voice_id, user_id)
|
||||
cosyvoice = self._get_cosyvoice()
|
||||
|
||||
# 2. TTS 合成(同步,~2-3s)
|
||||
try:
|
||||
result = cosyvoice.submit_synthesize_task(
|
||||
text=script_text,
|
||||
voice_id=actual_voice_id,
|
||||
speed=speed,
|
||||
emotion=normalize_emotion(emotion),
|
||||
)
|
||||
except CosyVoiceError as exc:
|
||||
raise MediaKitError(f"TTS 合成失败: {exc}", code="TTSSynthesisFailed") from exc
|
||||
except ValueError as exc:
|
||||
raise MediaKitError(f"TTS 参数错误: {exc}", code="TTSInvalidParam") from exc
|
||||
|
||||
temp_url = result.get("audio_url", "")
|
||||
if not temp_url:
|
||||
raise MediaKitError("TTS 未返回音频 URL", code="TTSNoAudio")
|
||||
|
||||
# 3. 下载音频到内存(用于 ffprobe + 静音检测)
|
||||
try:
|
||||
audio_data = safe_download_bytes(
|
||||
temp_url,
|
||||
purpose="tts_preview_audio",
|
||||
allowed_mime_types=ALLOWED_AUDIO_MIME_TYPES,
|
||||
timeout=60.0,
|
||||
)
|
||||
except Exception as exc:
|
||||
logger.warning("[tts-preview] TTS 音频下载失败,仍返回 audio_url: user_id=%s err=%s", user_id, exc)
|
||||
return {
|
||||
"audio_url": temp_url,
|
||||
"duration": 0.0,
|
||||
"sentence_timings": [],
|
||||
}
|
||||
|
||||
# 4. ffprobe 时长
|
||||
duration = probe_audio_duration(audio_data)
|
||||
if duration <= 0:
|
||||
logger.warning("[tts-preview] ffprobe 未返回有效时长,timings 留空: user_id=%s", user_id)
|
||||
return {
|
||||
"audio_url": temp_url,
|
||||
"duration": 0.0,
|
||||
"sentence_timings": [],
|
||||
}
|
||||
|
||||
# 5. 句子时间戳
|
||||
timings = compute_sentence_timings(audio_data, script_text, duration)
|
||||
|
||||
logger.info(
|
||||
"[tts-preview] TTS 预合成完成: user_id=%s duration=%.2f sentences=%d",
|
||||
user_id,
|
||||
duration,
|
||||
len(timings),
|
||||
)
|
||||
return {
|
||||
"audio_url": temp_url,
|
||||
"duration": round(duration, 2),
|
||||
"sentence_timings": timings,
|
||||
}
|
||||
|
||||
# ── 查询任务 ──────────────────────────────────────────────────────────
|
||||
|
||||
def get_job(self, job_id: str, user_id: str) -> Optional[LipsyncJobModel]:
|
||||
@@ -467,7 +284,11 @@ class LipsyncService:
|
||||
# ── 更新任务状态(轮询) ──────────────────────────────────────────────
|
||||
|
||||
def refresh_job_status(self, job_id: str, user_id: str) -> Optional[LipsyncJobModel]:
|
||||
"""从 MediaKit 拉取最新状态并更新本地记录."""
|
||||
"""从 MediaKit 拉取最新状态并更新本地记录.
|
||||
|
||||
Returns:
|
||||
更新后的 Job,或 None(任务不存在/不属于该用户)
|
||||
"""
|
||||
job = self.get_job(job_id, user_id)
|
||||
if job is None:
|
||||
return None
|
||||
@@ -492,25 +313,11 @@ class LipsyncService:
|
||||
if mk_status == STATUS_COMPLETED:
|
||||
result = status_data.get("result", {})
|
||||
job.status = STATUS_COMPLETED
|
||||
temp_url = result.get("video_url", "")
|
||||
job.output_video_url = temp_url
|
||||
output_url = result.get("video_url", "")
|
||||
# MediaKit 输出为临时 URL,转存自家 OSS 防止过期(失败则回退临时 URL)
|
||||
job.output_video_url = self._persist_output_video(output_url, job_id, user_id)
|
||||
job.output_duration = result.get("duration", 0.0)
|
||||
job.completed_at = datetime.now(timezone.utc)
|
||||
job.updated_at = datetime.now(timezone.utc)
|
||||
self.db.commit()
|
||||
# 异步转存自家 OSS
|
||||
try:
|
||||
from app.tasks.lipsync_tts import persist_output_video_task
|
||||
|
||||
persist_output_video_task.apply_async(args=(job_id, user_id, temp_url))
|
||||
except Exception as exc:
|
||||
logger.warning(
|
||||
"提交输出视频异步转存任务失败,保留临时 URL: job_id=%s err=%s",
|
||||
job_id,
|
||||
exc,
|
||||
)
|
||||
self.db.refresh(job)
|
||||
return job
|
||||
elif mk_status == STATUS_FAILED:
|
||||
error = status_data.get("error", {})
|
||||
job.status = "failed"
|
||||
@@ -518,6 +325,7 @@ class LipsyncService:
|
||||
job.error_code = error.get("code", "TaskFailed")
|
||||
job.completed_at = datetime.now(timezone.utc)
|
||||
else:
|
||||
# 中间状态(running/processing/queued 等)同步到 DB,避免前端永远卡在 submitted
|
||||
if isinstance(mk_status, str) and mk_status:
|
||||
job.status = mk_status
|
||||
job.updated_at = datetime.now(timezone.utc)
|
||||
@@ -526,7 +334,10 @@ class LipsyncService:
|
||||
return job
|
||||
|
||||
def _persist_output_video(self, temp_url: str, job_id: str, user_id: str) -> str:
|
||||
"""将 MediaKit 输出的临时视频 URL 转存到自家 OSS. 失败时回退返回原始临时 URL."""
|
||||
"""将 MediaKit 输出的临时视频 URL 转存到自家 OSS.
|
||||
|
||||
失败时回退返回原始临时 URL,不影响任务完成。
|
||||
"""
|
||||
if not temp_url:
|
||||
return ""
|
||||
try:
|
||||
@@ -546,21 +357,27 @@ class LipsyncService:
|
||||
return temp_url
|
||||
|
||||
def _sign_media_url(self, url: str) -> str:
|
||||
"""对自家 OSS 私有桶 URL 重签长有效期预签名."""
|
||||
"""对自家 OSS 私有桶 URL 重签长有效期预签名,供 MediaKit 拉取 / 前端播放。
|
||||
|
||||
- 裸 public_url(upload_file 返回,不带签名)→ 私有桶匿名访问 403,重签。
|
||||
- 已带签名但即将过期的 URL(如前端 1h 预签名)→ 抽 storage_key 后重签。
|
||||
- 外部 URL(CosyVoice/MediaKit 临时链接,非本桶 host)→ 原样透传。
|
||||
- 任何异常都降级原样返回,不阻断主流程。
|
||||
"""
|
||||
if not url:
|
||||
return url
|
||||
try:
|
||||
storage = get_shared_storage_service()
|
||||
public_base = getattr(storage, "public_url", "")
|
||||
if not isinstance(public_base, str) or not public_base:
|
||||
return url
|
||||
return url # 无法判定归属,保守透传
|
||||
own_host = urlparse(public_base).netloc.lower()
|
||||
host = urlparse(url).netloc.lower()
|
||||
if not own_host or host != own_host:
|
||||
return url # 外部临时链接原样透传
|
||||
return url # 非自家 OSS(外部临时链接),不处理
|
||||
signed = storage.get_download_url(url, expires_seconds=MEDIAKIT_URL_TTL_SECONDS)
|
||||
return signed or url
|
||||
except Exception as exc:
|
||||
except Exception as exc: # noqa: BLE001 - 签名失败不阻断,降级原 URL
|
||||
logger.warning("对口型 URL 重签失败,原样返回: url_prefix=%s err=%s", url[:80], exc)
|
||||
return url
|
||||
|
||||
|
||||
@@ -75,7 +75,7 @@ class MediaKitClient:
|
||||
*,
|
||||
video_url: str,
|
||||
audio_url: str,
|
||||
enable_video_loop: bool = True,
|
||||
enable_video_loop: bool = False,
|
||||
callback_url: Optional[str] = None,
|
||||
callback_args: Optional[str] = None,
|
||||
client_token: Optional[str] = None,
|
||||
@@ -103,7 +103,8 @@ class MediaKitClient:
|
||||
"video_url": video_url,
|
||||
"audio_url": audio_url,
|
||||
}
|
||||
payload["enable_video_loop"] = bool(enable_video_loop)
|
||||
if enable_video_loop:
|
||||
payload["enable_video_loop"] = True
|
||||
if callback_url:
|
||||
payload["callback_url"] = callback_url
|
||||
if callback_args:
|
||||
|
||||
@@ -12,10 +12,6 @@
|
||||
|
||||
注意:使用 @shared_task 而非绑定到某个 celery_app 实例,
|
||||
确保任务能被 Worker 侧 celery_app 正确注册,同时 API 侧 send_task/apply_async 仍可正常调用。
|
||||
|
||||
#1845:句子时间戳计算已提取至 packages/domain/sentence_timings.py,本模块保留
|
||||
_ 开头别名兼容历史导入,但 _compute_sentence_timings/_split_script_into_sentences/
|
||||
_estimate_sentence_timings_by_chars 等内部函数已复用共享实现,避免重复代码。
|
||||
"""
|
||||
|
||||
import io
|
||||
@@ -25,12 +21,6 @@ from urllib.parse import urlparse
|
||||
|
||||
from celery import shared_task
|
||||
|
||||
# 复用共享的句子时间戳工具(#1845 配音前置)
|
||||
from packages.domain.sentence_timings import compute_sentence_timings as _compute_sentence_timings
|
||||
from packages.domain.sentence_timings import (
|
||||
probe_audio_duration,
|
||||
)
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# MediaKit 预签名 URL 有效期(7天,秒),与 LipsyncService._sign_media_url 保持一致
|
||||
@@ -67,13 +57,8 @@ def _sign_media_url(url: str) -> str:
|
||||
@shared_task(
|
||||
bind=True,
|
||||
name="lipsync_tts.synthesize_and_submit",
|
||||
max_retries=5, # 事务竞态重试3次(job not found)+ TTS偶发错误2次
|
||||
max_retries=2,
|
||||
default_retry_delay=30,
|
||||
autoretry_for=(OSError, ConnectionError), # 网络/连接错误自动重试
|
||||
retry_backoff=True,
|
||||
retry_backoff_max=30,
|
||||
soft_time_limit=180,
|
||||
time_limit=200,
|
||||
)
|
||||
def tts_synthesize_and_submit(
|
||||
self,
|
||||
@@ -86,8 +71,7 @@ def tts_synthesize_and_submit(
|
||||
):
|
||||
"""异步执行 TTS 合成 + OSS 转存 + MediaKit 提交.
|
||||
|
||||
在 Celery worker 中运行,不阻塞 HTTP 请求。保留作为降级路径
|
||||
(预合成失败 / 旧版前端未传 audio_url 时走此路径)。
|
||||
在 Celery worker 中运行,不阻塞 HTTP 请求。
|
||||
"""
|
||||
from app.services.mediakit_client import MediaKitError, get_mediakit_client
|
||||
from sqlalchemy.orm import Session as DBSession
|
||||
@@ -119,25 +103,7 @@ def tts_synthesize_and_submit(
|
||||
)
|
||||
|
||||
if job is None:
|
||||
# 事务竞态防御:API 在 commit 前投递了任务,worker 消费时事务尚未提交。
|
||||
retries = getattr(self.request, "retries", 0)
|
||||
max_retries = 3
|
||||
if retries < max_retries:
|
||||
backoff = (2**retries) + (retries * 1) # 1s, 3s, 7s
|
||||
logger.warning(
|
||||
"[lipsync_tts] Job not found yet (retry %d/%d, backoff %ds): job_id=%s",
|
||||
retries + 1,
|
||||
max_retries,
|
||||
backoff,
|
||||
job_id,
|
||||
)
|
||||
self.db.close()
|
||||
raise self.retry(countdown=backoff, max_retries=max_retries)
|
||||
logger.error(
|
||||
"[lipsync_tts] Job not found after %d retries, giving up: job_id=%s",
|
||||
max_retries,
|
||||
job_id,
|
||||
)
|
||||
logger.error("[lipsync_tts] Job not found: job_id=%s", job_id)
|
||||
return
|
||||
|
||||
# 已取消的任务不再处理
|
||||
@@ -146,13 +112,6 @@ def tts_synthesize_and_submit(
|
||||
return
|
||||
|
||||
# 1. TTS 合成
|
||||
logger.info(
|
||||
"[lipsync_tts] 开始 TTS 合成: job_id=%s voice_id=%s text_len=%d speed=%.2f",
|
||||
job_id,
|
||||
voice_id,
|
||||
len(script_text),
|
||||
speed,
|
||||
)
|
||||
try:
|
||||
cosyvoice = CosyVoiceService()
|
||||
result = cosyvoice.submit_synthesize_task(
|
||||
@@ -188,74 +147,37 @@ def tts_synthesize_and_submit(
|
||||
db.commit()
|
||||
return
|
||||
|
||||
# 2. 下载 TTS 音频到内存(用于 2.5 静音检测;不转存自家 OSS,直接使用 CosyVoice 临时 URL)
|
||||
audio_data: bytes | None = None
|
||||
# 2. 下载并转存到自家 OSS
|
||||
try:
|
||||
audio_data = safe_download_bytes(
|
||||
temp_url,
|
||||
purpose="lipsync_tts_audio",
|
||||
allowed_mime_types={
|
||||
allowed_mime_types=(
|
||||
"audio/mpeg",
|
||||
"audio/mp3",
|
||||
"audio/wav",
|
||||
"audio/x-wav", # CosyVoice 部分接口返回 audio/x-wav
|
||||
"audio/mp4",
|
||||
"audio/x-m4a",
|
||||
},
|
||||
),
|
||||
timeout=60.0,
|
||||
)
|
||||
logger.info(
|
||||
"[lipsync_tts] TTS 音频已下载到内存: job_id=%s size=%d",
|
||||
job_id,
|
||||
len(audio_data) if audio_data else 0,
|
||||
)
|
||||
from packages.shared.storage import get_shared_storage_service
|
||||
|
||||
storage = get_shared_storage_service()
|
||||
storage_key = f"lipsync-tts/{user_id}/{job_id}.mp3"
|
||||
permanent_url = storage.upload_file(io.BytesIO(audio_data), storage_key, content_type="audio/mpeg")
|
||||
logger.info("[lipsync_tts] TTS 音频已转存 OSS: job_id=%s key=%s", job_id, storage_key)
|
||||
job.audio_url = permanent_url
|
||||
except Exception as exc:
|
||||
logger.warning(
|
||||
"[lipsync_tts] TTS 音频下载失败,跳过静音检测,直接使用临时 URL 提交: job_id=%s err=%s",
|
||||
"[lipsync_tts] TTS 音频转存 OSS 失败,回退临时 URL: job_id=%s err=%s",
|
||||
job_id,
|
||||
exc,
|
||||
)
|
||||
# TTS 音频使用 CosyVoice 临时 URL,跳过自家 OSS 转存(加速,步骤⑥)
|
||||
job.audio_url = temp_url
|
||||
logger.info("[lipsync_tts] TTS 音频使用 CosyVoice 临时 URL(跳过 OSS 转存): job_id=%s", job_id)
|
||||
job.audio_url = temp_url
|
||||
|
||||
db.commit()
|
||||
|
||||
# 2.5 计算精确句子时间戳(基于 TTS 音频静音检测)—— 复用共享工具
|
||||
try:
|
||||
if not audio_data:
|
||||
logger.warning("[lipsync_tts] 无音频数据,跳过句子时间戳计算: job_id=%s", job_id)
|
||||
else:
|
||||
_audio_duration = probe_audio_duration(audio_data)
|
||||
logger.info(
|
||||
"[lipsync_tts] 音频时长探测: job_id=%s duration=%.2f",
|
||||
job_id,
|
||||
_audio_duration,
|
||||
)
|
||||
|
||||
if _audio_duration > 0:
|
||||
_timings = _compute_sentence_timings(audio_data, script_text, _audio_duration)
|
||||
if _timings:
|
||||
job.sentence_timings = _timings
|
||||
logger.info(
|
||||
"[lipsync_tts] 句子时间戳已计算: job_id=%s sentences=%d duration=%.1f",
|
||||
job_id,
|
||||
len(_timings),
|
||||
_audio_duration,
|
||||
)
|
||||
else:
|
||||
logger.warning("[lipsync_tts] 句子时间戳计算返回空结果: job_id=%s", job_id)
|
||||
else:
|
||||
logger.warning(
|
||||
"[lipsync_tts] ffprobe 未获取到有效时长,跳过句子时间戳: job_id=%s",
|
||||
job_id,
|
||||
)
|
||||
db.commit()
|
||||
except Exception as _st_err:
|
||||
logger.warning(
|
||||
"[lipsync_tts] 句子时间戳计算失败(不影响主流程): job_id=%s err=%s", job_id, _st_err, exc_info=True
|
||||
)
|
||||
|
||||
# 3. 签名 URL 并提交到 MediaKit(复用模块内 _sign_media_url,避免对 LipsyncService 的耦合)
|
||||
audio_url = _sign_media_url(job.audio_url)
|
||||
video_url = _sign_media_url(job.video_url)
|
||||
@@ -298,58 +220,3 @@ def tts_synthesize_and_submit(
|
||||
logger.exception("[lipsync_tts] 回写失败状态时异常: job_id=%s", job_id)
|
||||
finally:
|
||||
db.close()
|
||||
|
||||
|
||||
@shared_task(
|
||||
name="lipsync_tts.persist_output_video",
|
||||
max_retries=2,
|
||||
default_retry_delay=30,
|
||||
)
|
||||
def persist_output_video_task(job_id: str, user_id: str, temp_url: str):
|
||||
"""异步转存对口型输出视频到自家 OSS(步骤⑦ — 将同步阻塞挪到后台,加速前端响应)."""
|
||||
|
||||
try:
|
||||
from worker_app.db import SessionLocal # type: ignore
|
||||
except Exception: # noqa: BLE001
|
||||
from app.db import SessionLocal # type: ignore
|
||||
|
||||
from packages.adapters.sqlalchemy_impl.models import LipsyncJobModel
|
||||
from packages.shared.storage import get_shared_storage_service
|
||||
|
||||
db = SessionLocal()
|
||||
try:
|
||||
job = db.query(LipsyncJobModel).filter(LipsyncJobModel.id == job_id, LipsyncJobModel.user_id == user_id).first()
|
||||
if job is None:
|
||||
logger.error("[lipsync_tts.persist] Job not found: job_id=%s", job_id)
|
||||
return
|
||||
|
||||
if not temp_url:
|
||||
logger.warning("[lipsync_tts.persist] temp_url 为空,跳过转存: job_id=%s", job_id)
|
||||
return
|
||||
|
||||
try:
|
||||
import httpx
|
||||
|
||||
with httpx.Client(timeout=180.0, follow_redirects=True) as client:
|
||||
resp = client.get(temp_url)
|
||||
resp.raise_for_status()
|
||||
data = resp.content
|
||||
|
||||
storage = get_shared_storage_service()
|
||||
storage_key = f"lipsync-outputs/{user_id}/{job_id}.mp4"
|
||||
permanent_url = storage.upload_file(io.BytesIO(data), storage_key, content_type="video/mp4")
|
||||
final_url = _sign_media_url(permanent_url) if permanent_url else temp_url
|
||||
job.output_video_url = final_url
|
||||
job.updated_at = datetime.now(timezone.utc)
|
||||
db.commit()
|
||||
logger.info("[lipsync_tts.persist] 输出视频已转存 OSS: job_id=%s key=%s", job_id, storage_key)
|
||||
except Exception as exc:
|
||||
logger.warning(
|
||||
"[lipsync_tts.persist] 输出视频转存失败,保留临时 URL: job_id=%s err=%s",
|
||||
job_id,
|
||||
exc,
|
||||
)
|
||||
except Exception:
|
||||
logger.exception("[lipsync_tts.persist] 未预期异常: job_id=%s", job_id)
|
||||
finally:
|
||||
db.close()
|
||||
|
||||
@@ -26,10 +26,6 @@ export interface BatchVariantPlansRequest {
|
||||
count: number
|
||||
/** 源剪辑计划 ID:优先取预览/草稿关联的 plan;不传由后端按 template_id+user 兜底最新 plan */
|
||||
source_edit_plan_id?: string
|
||||
/** 统一配音 ID(共用配音模式);独立配音模式不传,改传 voice_library_ids */
|
||||
voice_library_id?: string
|
||||
/** 独立配音 ID 列表(长度=count,按变体序号一一对应);共用配音模式不传 */
|
||||
voice_library_ids?: string[]
|
||||
}
|
||||
|
||||
/** 单个变体的计划片段 */
|
||||
@@ -40,8 +36,6 @@ export interface VariantPlan {
|
||||
plan_id: string
|
||||
/** 该变体的真实片段(顺序/素材/起点与正式成片一致) */
|
||||
clips: EditPlanClip[]
|
||||
/** 该变体实际配音时长(秒),用于前端预览按配音时长对齐音画;后端暂未返回时缺省 */
|
||||
voice_duration?: number
|
||||
}
|
||||
|
||||
/** 批量变体计划响应 */
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
/**
|
||||
* 成品 / 视频相关 API 函数
|
||||
* 后端实际接口:/videos(分页:page/page_size,返回 {items, total, page, page_size})
|
||||
* 后端实际接口:/videos
|
||||
*/
|
||||
import apiClient from "../client"
|
||||
import type {
|
||||
@@ -12,39 +12,16 @@ import type {
|
||||
} from "./types"
|
||||
import { mapVideoToProductItem } from "./utils"
|
||||
|
||||
/** 分页列表响应(前端消费用) */
|
||||
export interface ProductListResult {
|
||||
items: ProductItem[]
|
||||
total: number
|
||||
page: number
|
||||
page_size: number
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取成品列表(分页)
|
||||
* @param params 分页与筛选参数:page 默认 1,page_size 默认 20
|
||||
*/
|
||||
export const getProducts = async (params?: ProductListParams): Promise<ProductListResult> => {
|
||||
const response = await apiClient.get("/videos", {
|
||||
params: {
|
||||
page: 1,
|
||||
page_size: 20,
|
||||
...params,
|
||||
},
|
||||
})
|
||||
const data = response.data as {
|
||||
items?: VideoItem[]
|
||||
total?: number
|
||||
page?: number
|
||||
page_size?: number
|
||||
}
|
||||
const items: VideoItem[] = Array.isArray(data?.items) ? data.items : []
|
||||
return {
|
||||
items: items.map(mapVideoToProductItem),
|
||||
total: data.total ?? items.length,
|
||||
page: data.page ?? params?.page ?? 1,
|
||||
page_size: data.page_size ?? params?.page_size ?? 20,
|
||||
}
|
||||
/** 获取成品列表(支持分页和筛选) */
|
||||
export const getProducts = async (params?: ProductListParams): Promise<ProductItem[]> => {
|
||||
const response = await apiClient.get("/videos", { params })
|
||||
const data = response.data
|
||||
const videos: VideoItem[] = Array.isArray(data?.items)
|
||||
? data.items
|
||||
: Array.isArray(data)
|
||||
? data
|
||||
: []
|
||||
return videos.map(mapVideoToProductItem)
|
||||
}
|
||||
|
||||
/** 获取单个成品详情 */
|
||||
|
||||
@@ -16,7 +16,6 @@ export interface TTSSynthesizeRequest {
|
||||
voice_id?: string
|
||||
output_name?: string
|
||||
language?: string
|
||||
emotion?: string
|
||||
speed?: number
|
||||
voice_model?: string
|
||||
voice_clone_profile_id?: string
|
||||
@@ -104,7 +103,6 @@ export interface TTSPreviewRequest {
|
||||
voice_id: string
|
||||
speed?: number
|
||||
pitch?: number
|
||||
language?: string
|
||||
emotion?: string // 情绪参数:natural/excited/calm/friendly
|
||||
}
|
||||
|
||||
|
||||
@@ -96,12 +96,9 @@ export const retryVoiceClone = async (id: string): Promise<VoiceCloneProfile> =>
|
||||
export const getVoiceClonePreview = async (
|
||||
cloneId: string,
|
||||
text?: string,
|
||||
options?: { speed?: number; emotion?: string },
|
||||
): Promise<VoiceClonePreviewResponse> => {
|
||||
const searchParams = new URLSearchParams()
|
||||
if (text) searchParams.set("text", text)
|
||||
if (options?.speed !== undefined) searchParams.set("speed", String(options.speed))
|
||||
if (options?.emotion) searchParams.set("emotion", options.emotion)
|
||||
const qs = searchParams.toString()
|
||||
const response = await apiClient.get<VoiceClonePreviewResponse>(
|
||||
`/voice-clones/${cloneId}/preview${qs ? `?${qs}` : ""}`,
|
||||
|
||||
@@ -25,6 +25,15 @@ body {
|
||||
background-color: var(--bg-secondary);
|
||||
}
|
||||
|
||||
/* ── 自定义字体 ── */
|
||||
@font-face {
|
||||
font-family: "华康俪金黑";
|
||||
src: url("/fonts/DFLiJinHei-W8.ttf") format("truetype");
|
||||
font-weight: 700;
|
||||
font-style: normal;
|
||||
font-display: swap;
|
||||
}
|
||||
|
||||
/* 滚动条 - V21 样式 */
|
||||
::-webkit-scrollbar {
|
||||
width: 8px;
|
||||
|
||||
@@ -552,7 +552,7 @@
|
||||
max-width: 240px;
|
||||
aspect-ratio: 9/16;
|
||||
background: #f0f0f5;
|
||||
border-radius: 12px;
|
||||
border-radius: 8px;
|
||||
overflow: hidden;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
@@ -564,10 +564,8 @@
|
||||
.aa-cover-preview img {
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
aspect-ratio: 9/16;
|
||||
object-fit: cover;
|
||||
display: block;
|
||||
border-radius: 12px;
|
||||
}
|
||||
|
||||
.aa-cover-preview__placeholder {
|
||||
@@ -575,19 +573,6 @@
|
||||
color: #8c8ca1;
|
||||
}
|
||||
|
||||
.aa-cover-preview__loading {
|
||||
position: absolute;
|
||||
inset: 0;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
background: rgba(0, 0, 0, 0.45);
|
||||
color: #fff;
|
||||
font-size: 13px;
|
||||
backdrop-filter: blur(4px);
|
||||
-webkit-backdrop-filter: blur(4px);
|
||||
}
|
||||
|
||||
.aa-cover-actions {
|
||||
display: flex;
|
||||
gap: 8px;
|
||||
@@ -1265,20 +1250,3 @@
|
||||
width: auto;
|
||||
min-width: 300px;
|
||||
}
|
||||
|
||||
/* 渲染完成后的封面确认区 */
|
||||
.aa-finalize-section {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
align-items: center;
|
||||
padding: 16px 0 8px;
|
||||
}
|
||||
|
||||
.aa-finalize-cover {
|
||||
width: 100%;
|
||||
max-width: 240px;
|
||||
aspect-ratio: 9/16;
|
||||
border-radius: 12px;
|
||||
overflow: hidden;
|
||||
position: relative;
|
||||
}
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
/**
|
||||
* AI数字人 — 主页面(v3 两步骤版 + #1845 配音前置)
|
||||
* 步骤1:出镜视频 / 配音库 / 文案 → 点击「🎵 生成配音」做 TTS 预合成(同步,~2-3s)
|
||||
* 步骤2:对口型预览(音频已就绪、B-roll 句子时间戳立即可用)/ 标题配置 / 封面&生成
|
||||
* AI数字人 — 主页面(v3 两步骤版)
|
||||
* 步骤1:出镜视频 / 配音库 / 文案
|
||||
* 步骤2:对口型预览(含插入画面)/ 标题配置 / 封面&生成
|
||||
*/
|
||||
import React, { useState, useCallback, useEffect, useRef } from "react"
|
||||
import { message } from "antd"
|
||||
@@ -16,26 +16,20 @@ import PanelTitleConfig from "./components/PanelTitleConfig"
|
||||
import PanelCoverAndGenerate from "./components/PanelCoverAndGenerate"
|
||||
import { ModalAssetPicker } from "./components/ModalAssetPicker"
|
||||
import ModalBRollEditor from "./components/ModalBRollEditor"
|
||||
import ModalCoverSelect from "./components/ModalCoverSelect"
|
||||
import {
|
||||
getScripts,
|
||||
getAssetById,
|
||||
createLipsyncJob,
|
||||
getLipsyncJob,
|
||||
previewTts,
|
||||
submitRender,
|
||||
getRenderJob,
|
||||
generateRenderSmartCover,
|
||||
finalizeRenderJob,
|
||||
generateSmartCover,
|
||||
} from "./api/aiAvatar"
|
||||
import { getOrCreateDefaultProject } from "@/api/projects"
|
||||
import type { RenderJob, SentenceTiming } from "./types"
|
||||
import {
|
||||
normalizeEmotion,
|
||||
buildTitleConfigPayload,
|
||||
buildCoverConfigPayload,
|
||||
} from "./utils/contract"
|
||||
import { renderTitleToPngDataUrl, getVideoResolution } from "./utils/titleCanvas"
|
||||
|
||||
/** 面板折叠状态 */
|
||||
type PanelKey = "video" | "voice" | "script" | "lipsync" | "title" | "cover"
|
||||
@@ -53,18 +47,14 @@ const AiAvatarPage: React.FC = () => {
|
||||
cover: false,
|
||||
})
|
||||
|
||||
/* ── #1845 TTS 预合成弹窗 ── */
|
||||
const [showTtsModal, setShowTtsModal] = useState(false)
|
||||
const [ttsProgress, setTtsProgress] = useState(0)
|
||||
const [ttsErrorMessage, setTtsErrorMessage] = useState("")
|
||||
const ttsProgressTimerRef = useRef<ReturnType<typeof setInterval> | null>(null)
|
||||
|
||||
/* ── 对口型生成弹窗 ── */
|
||||
const [showLipsyncModal, setShowLipsyncModal] = useState(false)
|
||||
const [lipsyncStatus, setLipsyncStatus] = useState<"generating" | "completed" | "failed">(
|
||||
"generating",
|
||||
)
|
||||
const [lipsyncErrorMessage, setLipsyncErrorMessage] = useState("")
|
||||
/* ── 智能封面加载态 ── */
|
||||
const [smartCoverLoading, setSmartCoverLoading] = useState(false)
|
||||
/* ── 渲染进度弹窗 ── */
|
||||
const [showRenderModal, setShowRenderModal] = useState(false)
|
||||
const [renderStatus, setRenderStatus] = useState<"generating" | "completed" | "failed">(
|
||||
@@ -72,12 +62,6 @@ const AiAvatarPage: React.FC = () => {
|
||||
)
|
||||
const [renderProgress, setRenderProgress] = useState(0)
|
||||
const [renderErrorMessage, setRenderErrorMessage] = useState("")
|
||||
/* ── 当前渲染任务对象 ── */
|
||||
const [currentRenderJob, setCurrentRenderJob] = useState<RenderJob | null>(null)
|
||||
/* ── 封面选择弹窗 ── */
|
||||
const [showCoverModal, setShowCoverModal] = useState(false)
|
||||
const [selectedCoverUrl, setSelectedCoverUrl] = useState("")
|
||||
const [finalizeLoading, setFinalizeLoading] = useState(false)
|
||||
|
||||
/* ── 对口型轮询 ── */
|
||||
const lipsyncTimerRef = useRef<ReturnType<typeof setInterval> | null>(null)
|
||||
@@ -88,29 +72,8 @@ const AiAvatarPage: React.FC = () => {
|
||||
setCollapsed((prev) => ({ ...prev, [key]: !prev[key] }))
|
||||
}, [])
|
||||
|
||||
/* ── #1845 文案/音色/语速变更时重置 TTS 预合成状态,避免音频与文案不一致 ── */
|
||||
useEffect(() => {
|
||||
if (state.ttsPreview.status !== "idle") {
|
||||
state.resetTtsPreview()
|
||||
}
|
||||
// eslint-disable-next-line react-hooks/exhaustive-deps
|
||||
}, [state.scriptText, state.selectedVoice?.voice_id, state.speed, state.emotion])
|
||||
|
||||
const _clearTtsProgressTimer = useCallback(() => {
|
||||
if (ttsProgressTimerRef.current) {
|
||||
clearInterval(ttsProgressTimerRef.current)
|
||||
ttsProgressTimerRef.current = null
|
||||
}
|
||||
}, [])
|
||||
|
||||
useEffect(() => {
|
||||
return () => {
|
||||
_clearTtsProgressTimer()
|
||||
}
|
||||
}, [_clearTtsProgressTimer])
|
||||
|
||||
/* ── #1845 步骤1:点击「🎵 生成配音」→ 同步 TTS 预合成 ── */
|
||||
const handleGenerateTts = useCallback(async () => {
|
||||
/* ── 步骤切换 ── */
|
||||
const handleNextStep = useCallback(() => {
|
||||
const missing: string[] = []
|
||||
if (!state.selectedVideo) missing.push("出镜视频")
|
||||
if (!state.selectedVoice) missing.push("配音")
|
||||
@@ -119,115 +82,45 @@ const AiAvatarPage: React.FC = () => {
|
||||
message.warning(`请先完成${missing.join("、")}`)
|
||||
return
|
||||
}
|
||||
|
||||
// 打开弹窗 & 启动模拟进度条
|
||||
setShowTtsModal(true)
|
||||
setTtsProgress(0)
|
||||
setTtsErrorMessage("")
|
||||
state.setTtsPreview({
|
||||
audioUrl: null,
|
||||
duration: 0,
|
||||
sentenceTimings: [],
|
||||
status: "generating",
|
||||
error: null,
|
||||
})
|
||||
|
||||
// 模拟进度:每 300ms +10%,到 90% 停住,真完成后瞬间到 100%
|
||||
_clearTtsProgressTimer()
|
||||
let fake = 0
|
||||
ttsProgressTimerRef.current = setInterval(() => {
|
||||
fake = Math.min(fake + 10, 90)
|
||||
setTtsProgress(fake)
|
||||
if (fake >= 90) {
|
||||
_clearTtsProgressTimer()
|
||||
}
|
||||
}, 300)
|
||||
|
||||
try {
|
||||
const res = await previewTts({
|
||||
voice_id: state.selectedVoice!.voice_id,
|
||||
script_text: state.scriptText,
|
||||
speed: state.speed,
|
||||
emotion: normalizeEmotion(state.emotion),
|
||||
})
|
||||
_clearTtsProgressTimer()
|
||||
setTtsProgress(100)
|
||||
state.setTtsPreview({
|
||||
audioUrl: res.audio_url,
|
||||
duration: res.duration,
|
||||
sentenceTimings: res.sentence_timings as SentenceTiming[],
|
||||
status: "done",
|
||||
error: null,
|
||||
})
|
||||
message.success("配音合成完成")
|
||||
} catch (err) {
|
||||
_clearTtsProgressTimer()
|
||||
const errMsg =
|
||||
(err as { response?: { data?: { message?: string; detail?: unknown } } })?.response?.data
|
||||
?.message || (err instanceof Error ? err.message : "配音合成失败,请重试")
|
||||
setTtsErrorMessage(typeof errMsg === "string" ? errMsg : "配音合成失败,请重试")
|
||||
state.setTtsPreview({
|
||||
audioUrl: null,
|
||||
duration: 0,
|
||||
sentenceTimings: [],
|
||||
status: "failed",
|
||||
error: typeof errMsg === "string" ? errMsg : "配音合成失败",
|
||||
})
|
||||
}
|
||||
// eslint-disable-next-line react-hooks/exhaustive-deps
|
||||
}, [state.selectedVideo, state.selectedVoice, state.scriptText, state.speed, state.emotion])
|
||||
|
||||
const handleRetryTts = useCallback(() => {
|
||||
handleGenerateTts()
|
||||
}, [handleGenerateTts])
|
||||
|
||||
const handleTtsNext = useCallback(() => {
|
||||
setShowTtsModal(false)
|
||||
setTtsProgress(0)
|
||||
setCurrentStep(2)
|
||||
}, [])
|
||||
}, [state.selectedVideo, state.selectedVoice, state.scriptText])
|
||||
|
||||
const handleCancelTts = useCallback(() => {
|
||||
_clearTtsProgressTimer()
|
||||
setShowTtsModal(false)
|
||||
setTtsProgress(0)
|
||||
setTtsErrorMessage("")
|
||||
// 若用户在生成中途关闭,把状态重置回 idle,允许重新点击
|
||||
if (state.ttsPreview.status === "generating") {
|
||||
state.resetTtsPreview()
|
||||
}
|
||||
}, [_clearTtsProgressTimer, state])
|
||||
|
||||
/* ── 上一步(返回步骤1,不会丢失 TTS 预合成结果) ── */
|
||||
const handlePrevStep = useCallback(() => {
|
||||
setCurrentStep(1)
|
||||
}, [])
|
||||
|
||||
/* ── 对口型 ── */
|
||||
const handleGenerateLipsync = useCallback(async () => {
|
||||
// ② 缺项明确提示(#1809):不再静默 return
|
||||
const video = state.selectedVideo
|
||||
const voice = state.selectedVoice
|
||||
const text = state.scriptText.trim()
|
||||
const missing: string[] = []
|
||||
if (!video) missing.push("出镜视频")
|
||||
if (!voice) missing.push("音色")
|
||||
if (!text) missing.push("文案")
|
||||
if (missing.length > 0 || !video) {
|
||||
if (missing.length > 0 || !video || !voice) {
|
||||
message.warning(`请先选择${missing.join("、")}`)
|
||||
return
|
||||
}
|
||||
|
||||
// #1845:预合成模式下必须要有 audioUrl(理论上到了步骤2肯定有,兜底防御)
|
||||
const isPreSynth = state.ttsPreview.status === "done" && !!state.ttsPreview.audioUrl
|
||||
if (!isPreSynth && !state.selectedVoice) {
|
||||
message.warning("请先选择音色或完成配音合成")
|
||||
return
|
||||
}
|
||||
|
||||
try {
|
||||
// 显示生成弹窗
|
||||
setShowLipsyncModal(true)
|
||||
setLipsyncStatus("generating")
|
||||
setLipsyncErrorMessage("")
|
||||
|
||||
// ① 先按素材 id 拿 file_url(#1809 补充:对齐后端新参数 video_url)
|
||||
console.log("[对口型] 开始生成:", {
|
||||
videoId: video.id,
|
||||
voiceId: voice.voice_id,
|
||||
voiceType: voice.type,
|
||||
textLen: state.scriptText.length,
|
||||
})
|
||||
const asset = await getAssetById(video.id)
|
||||
console.log("[对口型] getAssetById 响应:", {
|
||||
id: asset?.id,
|
||||
file_url: asset?.file_url?.substring(0, 100),
|
||||
})
|
||||
const videoUrl = asset?.file_url
|
||||
if (!videoUrl) {
|
||||
console.error("[对口型] file_url 为空,asset:", asset)
|
||||
@@ -235,38 +128,29 @@ const AiAvatarPage: React.FC = () => {
|
||||
message.error("获取出镜视频播放地址失败,请重新选择素材")
|
||||
return
|
||||
}
|
||||
|
||||
type LipsyncPayload = Parameters<typeof createLipsyncJob>[0]
|
||||
let payload: LipsyncPayload
|
||||
if (isPreSynth) {
|
||||
// 预合成模式:传 audio_url + audio_duration + sentence_timings(后端直接提交 MediaKit,~2-3s)
|
||||
payload = {
|
||||
video_url: videoUrl,
|
||||
audio_url: state.ttsPreview.audioUrl!,
|
||||
audio_duration: state.ttsPreview.duration,
|
||||
sentence_timings: state.ttsPreview.sentenceTimings,
|
||||
enable_video_loop: true,
|
||||
}
|
||||
} else {
|
||||
// 降级:TTS 直生(旧路径,前端未预合成时)
|
||||
payload = {
|
||||
voice_id: state.selectedVoice!.voice_id,
|
||||
script_text: state.scriptText,
|
||||
video_url: videoUrl,
|
||||
speed: state.speed,
|
||||
emotion: normalizeEmotion(state.emotion),
|
||||
}
|
||||
// ② 模式A TTS直生:video_url + voice_id + script_text,语速/情绪英文枚举透传(#1822)
|
||||
const payload = {
|
||||
voice_id: voice.voice_id,
|
||||
script_text: state.scriptText,
|
||||
video_url: videoUrl,
|
||||
speed: state.speed, // 语速 0.5~2.0
|
||||
emotion: normalizeEmotion(state.emotion), // natural/excited/calm/friendly
|
||||
}
|
||||
console.log("[对口型] createLipsyncJob 请求:", payload)
|
||||
const job = await createLipsyncJob(payload)
|
||||
console.log("[对口型] createLipsyncJob 响应:", { id: job.id, status: job.status })
|
||||
state.setLipsyncJob(job)
|
||||
|
||||
// 如果是预合成模式,后端会同步把状态置为 submitted(甚至可能已返回 running),
|
||||
// 但仍需轮询等 completed
|
||||
// 开始轮询
|
||||
if (lipsyncTimerRef.current) clearInterval(lipsyncTimerRef.current)
|
||||
lipsyncTimerRef.current = setInterval(async () => {
|
||||
try {
|
||||
const updated = await getLipsyncJob(job.id)
|
||||
state.setLipsyncJob(updated)
|
||||
console.log("[对口型] 轮询状态:", {
|
||||
id: updated.id,
|
||||
status: updated.status,
|
||||
error: updated.error_message,
|
||||
})
|
||||
if (updated.status === "completed") {
|
||||
if (lipsyncTimerRef.current) clearInterval(lipsyncTimerRef.current)
|
||||
setLipsyncStatus("completed")
|
||||
@@ -293,14 +177,7 @@ const AiAvatarPage: React.FC = () => {
|
||||
message.error(err instanceof Error ? err.message : "对口型任务提交失败,请重试")
|
||||
}
|
||||
// eslint-disable-next-line react-hooks/exhaustive-deps
|
||||
}, [
|
||||
state.selectedVideo,
|
||||
state.selectedVoice,
|
||||
state.scriptText,
|
||||
state.speed,
|
||||
state.emotion,
|
||||
state.ttsPreview,
|
||||
])
|
||||
}, [state.selectedVideo, state.selectedVoice, state.scriptText, state.speed, state.emotion])
|
||||
|
||||
// 取消对口型生成
|
||||
const handleCancelLipsync = useCallback(() => {
|
||||
@@ -321,14 +198,6 @@ const AiAvatarPage: React.FC = () => {
|
||||
}
|
||||
}, [])
|
||||
|
||||
/* ── B-roll 弹窗可用的句子时间戳:优先 lipsyncJob.sentence_timings,否则用 ttsPreview.sentenceTimings ── */
|
||||
const bRollSentenceTimings: SentenceTiming[] | undefined =
|
||||
(state.lipsyncJob?.sentence_timings as SentenceTiming[] | undefined) ??
|
||||
(state.ttsPreview.status === "done" ? state.ttsPreview.sentenceTimings : undefined)
|
||||
|
||||
/* ── B-roll 可用的总时长:优先 lipsyncJob.output_duration,否则用 ttsPreview.duration ── */
|
||||
const bRollDuration = state.lipsyncJob?.output_duration || state.ttsPreview.duration || 0
|
||||
|
||||
/* ── 生成视频(含实时进度轮询) ── */
|
||||
const handleGenerate = useCallback(async () => {
|
||||
if (!state.lipsyncJob || state.lipsyncJob.status !== "completed") {
|
||||
@@ -337,28 +206,9 @@ const AiAvatarPage: React.FC = () => {
|
||||
}
|
||||
state.setIsGenerating(true)
|
||||
try {
|
||||
const defaultProject = await getOrCreateDefaultProject()
|
||||
|
||||
// 用 Canvas 预渲染标题为 PNG dataURL
|
||||
let titleImageDataUrl: string | null = null
|
||||
if (state.titleConfig.title?.trim()) {
|
||||
try {
|
||||
const res = await getVideoResolution(state.lipsyncJob.output_video_url || "")
|
||||
titleImageDataUrl = renderTitleToPngDataUrl({
|
||||
titleConfig: state.titleConfig,
|
||||
videoWidth: res.width,
|
||||
videoHeight: res.height,
|
||||
})
|
||||
} catch (canvasErr) {
|
||||
console.warn("[渲染] 标题 Canvas 渲染失败,降级 drawtext:", canvasErr)
|
||||
titleImageDataUrl = null
|
||||
}
|
||||
}
|
||||
|
||||
const job = await submitRender({
|
||||
lipsync_job_id: state.lipsyncJob.id,
|
||||
script_id: state.script?.id,
|
||||
project_id: defaultProject.id,
|
||||
b_roll_segments: state.bRollSegments.map((seg) => ({
|
||||
script_segment_index: seg.script_segment_index,
|
||||
asset_url: seg.asset.file_url || "",
|
||||
@@ -368,45 +218,26 @@ const AiAvatarPage: React.FC = () => {
|
||||
pip_position: seg.pip_position,
|
||||
pip_scale: seg.pip_scale,
|
||||
})) as never,
|
||||
title_config: buildTitleConfigPayload(state.titleConfig, titleImageDataUrl),
|
||||
cover_config:
|
||||
state.coverConfig.smart_cover_url ||
|
||||
(state.coverConfig.upload_url && !state.coverConfig.upload_url.startsWith("blob:"))
|
||||
? buildCoverConfigPayload(state.coverConfig, state.coverConfig.smart_cover_url)
|
||||
: {},
|
||||
title_config: buildTitleConfigPayload(state.titleConfig),
|
||||
cover_config: buildCoverConfigPayload(state.coverConfig, state.coverConfig.smart_cover_url),
|
||||
})
|
||||
|
||||
// 打开渲染进度弹窗,启动轮询
|
||||
setShowRenderModal(true)
|
||||
setRenderStatus("generating")
|
||||
setRenderProgress(job.progress ?? 0)
|
||||
setRenderErrorMessage("")
|
||||
setCurrentRenderJob(job as RenderJob)
|
||||
// 每次新渲染重置封面状态
|
||||
setSelectedCoverUrl("")
|
||||
setShowCoverModal(false)
|
||||
|
||||
if (renderTimerRef.current) clearInterval(renderTimerRef.current)
|
||||
renderTimerRef.current = setInterval(async () => {
|
||||
try {
|
||||
const updated = await getRenderJob(job.id)
|
||||
setRenderProgress(updated.progress ?? 0)
|
||||
setCurrentRenderJob(updated)
|
||||
if (updated.status === "completed") {
|
||||
if (renderTimerRef.current) clearInterval(renderTimerRef.current)
|
||||
renderTimerRef.current = null
|
||||
setRenderStatus("completed")
|
||||
// 不再自动入库/自动跳转:渲染完成后停留在主页面,等用户选封面、点「完成」才入库
|
||||
// 如果后端在透传时已经带了封面(旧逻辑兜底),同步本地状态
|
||||
if (updated.output_cover_url) {
|
||||
state.setCoverConfig((prev) => ({
|
||||
...prev,
|
||||
mode: "auto_frame",
|
||||
smart_cover_url: updated.output_cover_url,
|
||||
thumbnail_url: updated.output_cover_url,
|
||||
}))
|
||||
setSelectedCoverUrl(updated.output_cover_url)
|
||||
}
|
||||
message.success("视频生成完成,请选择封面")
|
||||
message.success("视频已生成并保存到成片库")
|
||||
} else if (updated.status === "failed") {
|
||||
if (renderTimerRef.current) clearInterval(renderTimerRef.current)
|
||||
renderTimerRef.current = null
|
||||
@@ -438,109 +269,38 @@ const AiAvatarPage: React.FC = () => {
|
||||
setRenderErrorMessage("")
|
||||
}, [])
|
||||
|
||||
/* ── 智能封面 ── */
|
||||
const handleGenerateRenderSmartCover = useCallback(
|
||||
async (renderId: string): Promise<{ cover_url: string; message?: string }> => {
|
||||
try {
|
||||
const res = await generateRenderSmartCover(renderId)
|
||||
if (res.cover_url) {
|
||||
state.setCoverConfig((prev) => ({
|
||||
...prev,
|
||||
mode: "auto_frame",
|
||||
smart_cover_url: res.cover_url,
|
||||
thumbnail_url: res.cover_url,
|
||||
}))
|
||||
message.success("智能封面已生成")
|
||||
return { cover_url: res.cover_url }
|
||||
}
|
||||
const errMsg = res.message || "智能封面生成失败,请稍后重试"
|
||||
message.error(errMsg)
|
||||
return { cover_url: "", message: errMsg }
|
||||
} catch (err) {
|
||||
console.error("智能封面生成失败:", err)
|
||||
const errMsg = err instanceof Error ? err.message : "智能封面生成失败,请重试"
|
||||
message.error(errMsg)
|
||||
return { cover_url: "", message: errMsg }
|
||||
}
|
||||
},
|
||||
// eslint-disable-next-line react-hooks/exhaustive-deps
|
||||
[],
|
||||
)
|
||||
|
||||
/* ── 封面弹窗回调 ── */
|
||||
const handleCoverSelected = useCallback((coverUrl: string) => {
|
||||
setSelectedCoverUrl(coverUrl || "")
|
||||
}, [])
|
||||
|
||||
const handleOpenCoverModal = useCallback(() => {
|
||||
if (currentRenderJob?.status !== "completed") {
|
||||
message.warning("请先完成视频生成")
|
||||
/* ── 智能封面:调后端 MediaKit 选帧接口(#1822) ── */
|
||||
const handleSmartCover = useCallback(async () => {
|
||||
// 基于对口型成片抽帧,必须先完成对口型
|
||||
const videoUrl = state.lipsyncJob?.output_video_url
|
||||
if (state.lipsyncJob?.status !== "completed" || !videoUrl) {
|
||||
message.warning("请先生成对口型视频,完成后再智能获取封面")
|
||||
return
|
||||
}
|
||||
setShowCoverModal(true)
|
||||
}, [currentRenderJob])
|
||||
|
||||
const handleCloseCoverModal = useCallback(() => {
|
||||
setShowCoverModal(false)
|
||||
}, [])
|
||||
|
||||
/* ── 自定义上传封面(本地预览,不单独上传;点完成时一起入库) ── */
|
||||
const handleUploadCover = useCallback(
|
||||
(file: File) => {
|
||||
const url = URL.createObjectURL(file)
|
||||
state.setCoverConfig((prev) => ({
|
||||
...prev,
|
||||
mode: "upload",
|
||||
upload_url: url,
|
||||
thumbnail_url: url,
|
||||
}))
|
||||
setSelectedCoverUrl(url)
|
||||
},
|
||||
[state],
|
||||
)
|
||||
|
||||
/* ── 点「完成」:调用 finalize 入库成片库,成功后跳转到成片库 ── */
|
||||
const handleFinalize = useCallback(async () => {
|
||||
if (!currentRenderJob?.id) {
|
||||
message.error("渲染任务不存在")
|
||||
return
|
||||
}
|
||||
if (currentRenderJob.status !== "completed") {
|
||||
message.warning("请先完成视频生成")
|
||||
return
|
||||
}
|
||||
setFinalizeLoading(true)
|
||||
setSmartCoverLoading(true)
|
||||
try {
|
||||
const res = await finalizeRenderJob(currentRenderJob.id)
|
||||
if (res.data?.status === "success" || res.data?.status === "already_finalized") {
|
||||
message.success("已保存到成片库")
|
||||
navigate("/app/products")
|
||||
const res = await generateSmartCover(videoUrl, 5)
|
||||
if (res.cover_url) {
|
||||
state.setCoverConfig((prev) => ({
|
||||
...prev,
|
||||
mode: "auto_frame",
|
||||
smart_cover_url: res.cover_url,
|
||||
thumbnail_url: res.cover_url,
|
||||
}))
|
||||
message.success("智能封面已生成")
|
||||
} else {
|
||||
message.error("保存失败,请重试")
|
||||
message.error(res.message || "智能封面生成失败,请稍后重试")
|
||||
}
|
||||
} catch (err) {
|
||||
console.error("finalize 失败:", err)
|
||||
const errMsg =
|
||||
(err as { response?: { data?: { detail?: unknown } } })?.response?.data?.detail ||
|
||||
(err instanceof Error ? err.message : "保存到成片库失败")
|
||||
message.error(typeof errMsg === "string" ? errMsg : "保存到成片库失败")
|
||||
console.error("智能封面生成失败:", err)
|
||||
message.error(err instanceof Error ? err.message : "智能封面生成失败,请重试")
|
||||
} finally {
|
||||
setFinalizeLoading(false)
|
||||
setSmartCoverLoading(false)
|
||||
}
|
||||
}, [currentRenderJob, navigate])
|
||||
// eslint-disable-next-line react-hooks/exhaustive-deps
|
||||
}, [state.lipsyncJob])
|
||||
|
||||
/* ── 配置汇总 ── */
|
||||
const coverStatus: "not_ready" | "pending" | "selected" = (() => {
|
||||
if (
|
||||
state.coverConfig.smart_cover_url ||
|
||||
state.coverConfig.thumbnail_url ||
|
||||
(state.coverConfig.upload_url && !state.coverConfig.upload_url.startsWith("blob:"))
|
||||
) {
|
||||
return "selected"
|
||||
}
|
||||
if (currentRenderJob?.status === "completed") return "pending"
|
||||
return "not_ready"
|
||||
})()
|
||||
const summary = {
|
||||
videoName: state.selectedVideo?.name || null,
|
||||
voiceName: state.selectedVoice?.name || null,
|
||||
@@ -548,7 +308,7 @@ const AiAvatarPage: React.FC = () => {
|
||||
lipsyncStatus: state.lipsyncJob?.status || null,
|
||||
brollCount: state.bRollSegments.length,
|
||||
hasTitle: state.titleConfig.title.length > 0,
|
||||
coverStatus,
|
||||
hasCover: state.coverConfig.enabled,
|
||||
}
|
||||
|
||||
return (
|
||||
@@ -582,6 +342,7 @@ const AiAvatarPage: React.FC = () => {
|
||||
selectedVideo={state.selectedVideo}
|
||||
onSelectVideo={() => state.setShowAssetPicker(true)}
|
||||
onRemoveVideo={state.removeVideo}
|
||||
titleConfig={state.titleConfig}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
@@ -621,33 +382,19 @@ const AiAvatarPage: React.FC = () => {
|
||||
onOpenScriptModal={() => state.setShowScriptModal(true)}
|
||||
/>
|
||||
<div className="aa-step-btn-row">
|
||||
<button
|
||||
type="button"
|
||||
className="aa-btn aa-btn--primary"
|
||||
onClick={handleGenerateTts}
|
||||
disabled={state.ttsPreview.status === "generating"}
|
||||
>
|
||||
{state.ttsPreview.status === "done" ? "🎵 重新生成配音" : "🎵 生成配音"}
|
||||
<button type="button" className="aa-btn aa-btn--primary" onClick={handleNextStep}>
|
||||
下一步 →
|
||||
</button>
|
||||
{state.ttsPreview.status === "done" && (
|
||||
<button
|
||||
type="button"
|
||||
className="aa-btn aa-btn--primary"
|
||||
onClick={() => setCurrentStep(2)}
|
||||
style={{ marginLeft: 12 }}
|
||||
>
|
||||
下一步 →
|
||||
</button>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</>
|
||||
)}
|
||||
|
||||
{/* ════ 步骤 2:对口型预览 / 标题配置 / 封面&生成 ════ */}
|
||||
{/* ════ 步骤 2:对口型预览(含插入画面)/ 标题配置 / 封面&生成 ════ */}
|
||||
{currentStep === 2 && (
|
||||
<>
|
||||
{/* 面板:对口型预览 + 插入画面 */}
|
||||
<div className={`aa-panel aa-panel--s2-wide${collapsed.lipsync ? " collapsed" : ""}`}>
|
||||
<div className="aa-panel__header" onClick={() => togglePanel("lipsync")}>
|
||||
<span className="aa-panel__title">对口型预览</span>
|
||||
@@ -685,98 +432,27 @@ const AiAvatarPage: React.FC = () => {
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* 面板5:封面 & 生成
|
||||
- 渲染未完成:显示分辨率/配置摘要/「开始生成」按钮(PanelCoverAndGenerate setup 变体,无封面区)
|
||||
- 渲染完成:显示封面预览 + 「🎬 选择封面」/「✅ 完成」按钮,封面选择在弹窗中完成 */}
|
||||
{/* 面板5:封面 & 生成 */}
|
||||
<div className={`aa-panel aa-panel--s2${collapsed.cover ? " collapsed" : ""}`}>
|
||||
<div className="aa-panel__header" onClick={() => togglePanel("cover")}>
|
||||
<span className="aa-panel__title">
|
||||
{currentRenderJob?.status === "completed" ? "视频已生成" : "封面 & 生成"}
|
||||
</span>
|
||||
<span className="aa-panel__title">封面 & 生成</span>
|
||||
<span className="aa-panel__toggle">▼</span>
|
||||
</div>
|
||||
<div className="aa-panel__body">
|
||||
{currentRenderJob?.status !== "completed" ? (
|
||||
<PanelCoverAndGenerate
|
||||
variant="setup"
|
||||
coverConfig={state.coverConfig}
|
||||
onCoverConfigChange={(partial) =>
|
||||
state.setCoverConfig((prev) => ({ ...prev, ...partial }))
|
||||
}
|
||||
renderJob={currentRenderJob}
|
||||
onGenerateRenderSmartCover={handleGenerateRenderSmartCover}
|
||||
resolution={state.resolution}
|
||||
onResolutionChange={state.setResolution}
|
||||
isGenerating={state.isGenerating}
|
||||
onGenerate={handleGenerate}
|
||||
summary={summary}
|
||||
/>
|
||||
) : (
|
||||
<div className="aa-finalize-section">
|
||||
<div
|
||||
style={{ marginBottom: 8, fontSize: 13, color: "#1a1a2e", fontWeight: 500 }}
|
||||
>
|
||||
✅ 视频生成完成,请选择封面后点「完成」入库
|
||||
</div>
|
||||
<div className="aa-finalize-cover">
|
||||
{selectedCoverUrl ? (
|
||||
<img
|
||||
src={selectedCoverUrl}
|
||||
alt="封面预览"
|
||||
draggable={false}
|
||||
style={{
|
||||
width: "100%",
|
||||
height: "100%",
|
||||
objectFit: "cover",
|
||||
borderRadius: 8,
|
||||
}}
|
||||
/>
|
||||
) : (
|
||||
<div
|
||||
style={{
|
||||
width: "100%",
|
||||
height: "100%",
|
||||
border: "2px dashed #d9d9d9",
|
||||
borderRadius: 8,
|
||||
display: "flex",
|
||||
alignItems: "center",
|
||||
justifyContent: "center",
|
||||
color: "#8c8ca1",
|
||||
fontSize: 12,
|
||||
flexDirection: "column",
|
||||
gap: 4,
|
||||
}}
|
||||
>
|
||||
<span style={{ fontSize: 24 }}>🎬</span>
|
||||
<span>尚未选择封面</span>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
<div
|
||||
style={{
|
||||
display: "flex",
|
||||
gap: 10,
|
||||
marginTop: 12,
|
||||
}}
|
||||
>
|
||||
<button
|
||||
type="button"
|
||||
className="aa-btn aa-btn--ghost"
|
||||
onClick={handleOpenCoverModal}
|
||||
>
|
||||
🎬 选择封面
|
||||
</button>
|
||||
<button
|
||||
type="button"
|
||||
className="aa-btn aa-btn--primary"
|
||||
onClick={handleFinalize}
|
||||
disabled={finalizeLoading}
|
||||
>
|
||||
{finalizeLoading ? "⏳ 保存中..." : "✅ 完成"}
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
<PanelCoverAndGenerate
|
||||
coverConfig={state.coverConfig}
|
||||
onCoverConfigChange={(partial) =>
|
||||
state.setCoverConfig((prev) => ({ ...prev, ...partial }))
|
||||
}
|
||||
onSmartCover={handleSmartCover}
|
||||
smartCoverLoading={smartCoverLoading}
|
||||
canSmartCover={state.lipsyncJob?.status === "completed"}
|
||||
resolution={state.resolution}
|
||||
onResolutionChange={state.setResolution}
|
||||
isGenerating={state.isGenerating}
|
||||
onGenerate={handleGenerate}
|
||||
summary={summary}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
</>
|
||||
@@ -802,144 +478,19 @@ const AiAvatarPage: React.FC = () => {
|
||||
/>
|
||||
)}
|
||||
|
||||
{/* B-roll 编辑器弹窗 — #1845:timings 在对口型完成前就可用(来自 TTS 预合成) */}
|
||||
{/* B-roll 编辑器弹窗 */}
|
||||
{state.showBRollModal && (
|
||||
<ModalBRollEditor
|
||||
open={state.showBRollModal}
|
||||
onClose={() => state.setShowBRollModal(false)}
|
||||
existingSegments={state.bRollSegments}
|
||||
scriptText={state.lipsyncJob?.script_text || state.scriptText}
|
||||
outputDuration={bRollDuration}
|
||||
sentenceTimings={bRollSentenceTimings}
|
||||
scriptText={state.scriptText}
|
||||
outputDuration={state.lipsyncJob?.output_duration ?? 0}
|
||||
onConfirm={state.addBRollSegment}
|
||||
onRemove={state.removeBRollSegment}
|
||||
/>
|
||||
)}
|
||||
|
||||
{/* #1845 TTS 预合成弹窗 */}
|
||||
{showTtsModal && (
|
||||
<div className="aa-modal-overlay">
|
||||
<div className="aa-modal" onClick={(e) => e.stopPropagation()}>
|
||||
<div className="aa-modal__header">
|
||||
<span className="aa-modal__title">配音合成中</span>
|
||||
{state.ttsPreview.status !== "generating" && (
|
||||
<button className="aa-modal__close" onClick={handleCancelTts}>
|
||||
✕
|
||||
</button>
|
||||
)}
|
||||
</div>
|
||||
<div
|
||||
className="aa-modal__body"
|
||||
style={{
|
||||
display: "flex",
|
||||
flexDirection: "column",
|
||||
alignItems: "center",
|
||||
padding: "40px 20px",
|
||||
}}
|
||||
>
|
||||
{state.ttsPreview.status === "generating" && (
|
||||
<>
|
||||
<div className="aa-lipsync-spinner" />
|
||||
<div style={{ marginTop: 20, fontSize: 15, color: "#1a1a2e" }}>
|
||||
正在合成配音,请稍候…
|
||||
</div>
|
||||
<div
|
||||
style={{
|
||||
marginTop: 20,
|
||||
fontSize: 32,
|
||||
fontWeight: 700,
|
||||
color: "#1890ff",
|
||||
}}
|
||||
>
|
||||
{ttsProgress}%
|
||||
</div>
|
||||
<div
|
||||
style={{
|
||||
marginTop: 12,
|
||||
width: "80%",
|
||||
height: 8,
|
||||
backgroundColor: "#f0f0f0",
|
||||
borderRadius: 4,
|
||||
overflow: "hidden",
|
||||
}}
|
||||
>
|
||||
<div
|
||||
style={{
|
||||
width: `${ttsProgress}%`,
|
||||
height: "100%",
|
||||
backgroundColor: "#1890ff",
|
||||
borderRadius: 4,
|
||||
transition: "width 0.3s ease",
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
<div style={{ marginTop: 12, fontSize: 13, color: "#8c8ca1" }}>
|
||||
请勿关闭页面,完成后将自动提示
|
||||
</div>
|
||||
</>
|
||||
)}
|
||||
{state.ttsPreview.status === "done" && (
|
||||
<>
|
||||
<div style={{ fontSize: 48 }}>✅</div>
|
||||
<div style={{ marginTop: 16, fontSize: 15, color: "#1a1a2e" }}>
|
||||
配音合成完成,点击下一步继续
|
||||
</div>
|
||||
<div style={{ marginTop: 8, fontSize: 13, color: "#8c8ca1" }}>
|
||||
音频时长 {state.ttsPreview.duration.toFixed(1)}s,共{" "}
|
||||
{state.ttsPreview.sentenceTimings.length} 句
|
||||
</div>
|
||||
</>
|
||||
)}
|
||||
{state.ttsPreview.status === "failed" && (
|
||||
<>
|
||||
<div style={{ fontSize: 48 }}>❌</div>
|
||||
<div style={{ marginTop: 16, fontSize: 15, color: "#1a1a2e" }}>配音合成失败</div>
|
||||
{ttsErrorMessage && (
|
||||
<div
|
||||
style={{
|
||||
marginTop: 8,
|
||||
fontSize: 13,
|
||||
color: "#ff4d4f",
|
||||
textAlign: "center",
|
||||
padding: "0 20px",
|
||||
}}
|
||||
>
|
||||
{ttsErrorMessage}
|
||||
</div>
|
||||
)}
|
||||
</>
|
||||
)}
|
||||
</div>
|
||||
<div className="aa-modal__footer">
|
||||
{state.ttsPreview.status === "generating" && (
|
||||
<button className="aa-btn aa-btn--danger" onClick={handleCancelTts}>
|
||||
取消
|
||||
</button>
|
||||
)}
|
||||
{state.ttsPreview.status === "done" && (
|
||||
<button className="aa-btn aa-btn--primary" onClick={handleTtsNext}>
|
||||
下一步 →
|
||||
</button>
|
||||
)}
|
||||
{state.ttsPreview.status === "failed" && (
|
||||
<>
|
||||
<button className="aa-btn" onClick={handleCancelTts}>
|
||||
关闭
|
||||
</button>
|
||||
<button
|
||||
className="aa-btn aa-btn--primary"
|
||||
onClick={handleRetryTts}
|
||||
style={{ marginLeft: 12 }}
|
||||
>
|
||||
重试
|
||||
</button>
|
||||
</>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* 对口型生成弹窗 */}
|
||||
{showLipsyncModal && (
|
||||
<div className="aa-modal-overlay">
|
||||
@@ -1072,21 +623,17 @@ const AiAvatarPage: React.FC = () => {
|
||||
<>
|
||||
<div style={{ fontSize: 48 }}>✅</div>
|
||||
<div style={{ marginTop: 16, fontSize: 15, color: "#1a1a2e" }}>
|
||||
视频生成完成,请选择封面
|
||||
</div>
|
||||
<div
|
||||
style={{ marginTop: 8, fontSize: 13, color: "#8c8ca1", textAlign: "center" }}
|
||||
>
|
||||
关闭此窗口后可在下方选择封面并保存到成片库
|
||||
视频已保存到成片库
|
||||
</div>
|
||||
<button
|
||||
className="aa-btn aa-btn--primary"
|
||||
className="aa-btn"
|
||||
style={{ marginTop: 16 }}
|
||||
onClick={() => {
|
||||
setShowRenderModal(false)
|
||||
navigate("/app/products")
|
||||
}}
|
||||
>
|
||||
🎬 选择封面
|
||||
📁 查看成片
|
||||
</button>
|
||||
</>
|
||||
)}
|
||||
@@ -1117,18 +664,6 @@ const AiAvatarPage: React.FC = () => {
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* 封面选择弹窗 */}
|
||||
<ModalCoverSelect
|
||||
open={showCoverModal}
|
||||
onClose={handleCloseCoverModal}
|
||||
renderJob={currentRenderJob}
|
||||
coverConfig={state.coverConfig}
|
||||
onCoverConfigChange={(partial) => state.setCoverConfig((prev) => ({ ...prev, ...partial }))}
|
||||
onGenerateRenderSmartCover={handleGenerateRenderSmartCover}
|
||||
onUploadCover={handleUploadCover}
|
||||
onCoverSelected={handleCoverSelected}
|
||||
/>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
* AI数字人 — API 封装(#1822 契约对齐)
|
||||
*/
|
||||
import apiClient from "@/api/client"
|
||||
import type { Script, LipsyncJob, RenderJob, BRollSegment, SentenceTiming } from "../types"
|
||||
import type { Script, LipsyncJob, RenderJob, BRollSegment } from "../types"
|
||||
|
||||
/* ── 文案库 ── */
|
||||
export const getScripts = async (): Promise<Script[]> => {
|
||||
@@ -34,28 +34,17 @@ export const getAssetById = async (id: string): Promise<{ file_url?: string; id:
|
||||
return response.data
|
||||
}
|
||||
|
||||
/* ── 对口型(支持三种模式) ──
|
||||
* 1. TTS 直生(降级/旧版):传 voice_id + script_text(+speed/emotion),后端 Celery 异步合成
|
||||
* 2. 直接音频:传 video_url + audio_url,后端同步下载+算timings+提交MediaKit
|
||||
* 3. 预合成音频(#1845 新主路径):先调 previewTts 拿 audio_url+sentence_timings,
|
||||
* 再把 audio_url + audio_duration + sentence_timings 一起传过来,后端直接提交 MediaKit
|
||||
*/
|
||||
/* ── 对口型(模式A:TTS 直生,后端内部合成音频;不要先调 TTS 拿 audio_url) ── */
|
||||
export const createLipsyncJob = async (data: {
|
||||
/** 人物视频 URL(MP4);由素材 id 经 getAssetById 拿 file_url */
|
||||
/** 人物视频 URL(MP4);由素材 id 经 getAssetById 拿 file_url,禁止传 video_asset_id */
|
||||
video_url: string
|
||||
/** 预合成/直接音频模式:音频 URL(#1845 步骤1 预合成的 CosyVoice 临时 URL,或外部音频 URL) */
|
||||
audio_url?: string
|
||||
/** 预合成音频时长(秒),由 previewTts 返回 */
|
||||
audio_duration?: number
|
||||
/** 预合成接口返回的句子时间戳(精确),后端直接写入 job */
|
||||
sentence_timings?: SentenceTiming[]
|
||||
/** 音色 ID(TTS 直生模式用) */
|
||||
voice_id?: string
|
||||
/** 要合成的文案(TTS 直生模式用) */
|
||||
script_text?: string
|
||||
/** 语速 0.5~2.0,默认 1.0(TTS 直生模式用) */
|
||||
/** 音色 ID(预置音色 或 克隆音色 profile UUID,后端会解析) */
|
||||
voice_id: string
|
||||
/** 要合成的文案(手动输入或文案库内容) */
|
||||
script_text: string
|
||||
/** 语速 0.5~2.0,默认 1.0 */
|
||||
speed?: number
|
||||
/** 情绪英文枚举:natural/excited/calm/friendly(TTS 直生模式用) */
|
||||
/** 情绪英文枚举:natural/excited/calm/friendly */
|
||||
emotion?: string
|
||||
enable_video_loop?: boolean
|
||||
project_id?: string
|
||||
@@ -64,27 +53,21 @@ export const createLipsyncJob = async (data: {
|
||||
return response.data
|
||||
}
|
||||
|
||||
/* ── #1845 TTS 预合成(步骤1「生成配音」同步接口,~2-3s) ── */
|
||||
export const previewTts = async (data: {
|
||||
voice_id: string
|
||||
script_text: string
|
||||
speed?: number
|
||||
emotion?: string
|
||||
}): Promise<{
|
||||
audio_url: string
|
||||
duration: number
|
||||
sentence_timings: SentenceTiming[]
|
||||
}> => {
|
||||
const response = await apiClient.post<{
|
||||
audio_url: string
|
||||
duration: number
|
||||
sentence_timings: SentenceTiming[]
|
||||
}>("/lipsync/tts-preview", data, { timeout: 30000 })
|
||||
export const getLipsyncJob = async (id: string): Promise<LipsyncJob> => {
|
||||
const response = await apiClient.get<LipsyncJob>(`/lipsync/jobs/${id}`, { timeout: 60000 })
|
||||
return response.data
|
||||
}
|
||||
|
||||
export const getLipsyncJob = async (id: string): Promise<LipsyncJob> => {
|
||||
const response = await apiClient.get<LipsyncJob>(`/lipsync/jobs/${id}`, { timeout: 60000 })
|
||||
/* ── 智能封面(MediaKit 抽帧 + 质量评分选最佳帧,独立于渲染任务) ── */
|
||||
export const generateSmartCover = async (
|
||||
video_url: string,
|
||||
max_frames = 5,
|
||||
): Promise<{ cover_url: string; status: string; message: string }> => {
|
||||
const response = await apiClient.post<{ cover_url: string; status: string; message: string }>(
|
||||
"/ai-avatar/render/smart-cover",
|
||||
{ video_url, max_frames },
|
||||
{ timeout: 60000 },
|
||||
)
|
||||
return response.data
|
||||
}
|
||||
|
||||
@@ -97,35 +80,15 @@ export const submitRender = async (data: {
|
||||
cover_config?: Record<string, unknown>
|
||||
project_id?: string
|
||||
}): Promise<RenderJob> => {
|
||||
// title_config 内可含 title_image_dataurl(前端 Canvas 渲染的 PNG dataURL)
|
||||
const response = await apiClient.post<RenderJob>("/ai-avatar/render", data)
|
||||
return response.data
|
||||
}
|
||||
|
||||
export const getRenderJob = async (jobId: string): Promise<RenderJob> => {
|
||||
const response = await apiClient.get<RenderJob>(`/ai-avatar/render/${jobId}`, { timeout: 60000 })
|
||||
const response = await apiClient.get<RenderJob>(`/ai-avatar/render/${jobId}`)
|
||||
return response.data
|
||||
}
|
||||
|
||||
export const cancelRenderJob = async (jobId: string): Promise<void> => {
|
||||
await apiClient.post(`/ai-avatar/render/${jobId}/cancel`)
|
||||
}
|
||||
|
||||
/* ── 从最终渲染成片智能抽封面(POST /ai-avatar/renders/{job_id}/smart-cover) ── */
|
||||
export const generateRenderSmartCover = async (
|
||||
jobId: string,
|
||||
): Promise<{ cover_url: string; status: string; message: string }> => {
|
||||
const response = await apiClient.post<{ cover_url: string; status: string; message: string }>(
|
||||
`/ai-avatar/render/${jobId}/smart-cover`,
|
||||
{},
|
||||
// 抽帧+评分+转存 OSS 链路较长,120s 超时
|
||||
{ timeout: 120000 },
|
||||
)
|
||||
return response.data
|
||||
}
|
||||
|
||||
/* ── 封面选定后点「完成」正式入库(POST /ai-avatar/render/{job_id}/finalize) ── */
|
||||
export const finalizeRenderJob = (renderId: string) =>
|
||||
apiClient.post<{ video_id: string; cover_url: string; status: string }>(
|
||||
`/ai-avatar/render/${renderId}/finalize`,
|
||||
)
|
||||
|
||||
@@ -5,12 +5,12 @@
|
||||
* - 左侧:先选素材库(video 库)→ 再选该库视频素材(已被其他 segment 使用的素材
|
||||
* 标灰 + "已选择" 遮罩,pointer-events:none 防重复选择)
|
||||
* - 右侧:文案句子列表(点选对应段落,替代原数字索引框)/ 全屏 or 画中画 / 四角位置+大小
|
||||
* (开始/结束时间来自后端精确句子时间戳,基于 TTS 音频静音检测)
|
||||
* (开始/结束时间已删除,按句子字数占比 × 口播总时长自动估算)
|
||||
* - 底部:已配置的画面插入列表(可删除)
|
||||
*/
|
||||
import React, { useEffect, useMemo, useState } from "react"
|
||||
import { getAssets, getAssetLibraries, type AssetItem, type AssetLibraryItem } from "@/api/assets"
|
||||
import type { BRollSegment, BRollInsertMode, PipPosition, SentenceTiming } from "../types"
|
||||
import type { BRollSegment, BRollInsertMode, PipPosition } from "../types"
|
||||
import { splitScriptIntoSentences, type ScriptSentence } from "../utils/sentences"
|
||||
|
||||
interface ModalBRollEditorProps {
|
||||
@@ -18,12 +18,10 @@ interface ModalBRollEditorProps {
|
||||
onClose: () => void
|
||||
/** 当前已有的 B-roll segments(用于标灰已选素材) */
|
||||
existingSegments: BRollSegment[]
|
||||
/** 文案全文(优先使用对口型时锁定的 scriptText) */
|
||||
/** 当前文案全文(用于分句) */
|
||||
scriptText: string
|
||||
/** 对口型成片总时长(秒) */
|
||||
/** 对口型成片总时长(秒),用于时间自动估算 */
|
||||
outputDuration: number
|
||||
/** 后端精确句子时间戳(来自 lipsyncJob.sentence_timings) */
|
||||
sentenceTimings?: SentenceTiming[] | null
|
||||
onConfirm: (segment: BRollSegment) => void
|
||||
onRemove: (id: string) => void
|
||||
}
|
||||
@@ -45,8 +43,7 @@ const ModalBRollEditor: React.FC<ModalBRollEditorProps> = ({
|
||||
onClose,
|
||||
existingSegments,
|
||||
scriptText,
|
||||
outputDuration: _outputDuration,
|
||||
sentenceTimings,
|
||||
outputDuration,
|
||||
onConfirm,
|
||||
onRemove,
|
||||
}) => {
|
||||
@@ -65,10 +62,10 @@ const ModalBRollEditor: React.FC<ModalBRollEditorProps> = ({
|
||||
const [pipPosition, setPipPosition] = useState<PipPosition>("top-right")
|
||||
const [pipScale, setPipScale] = useState(0.3)
|
||||
|
||||
/** 文案分句(优先使用后端精确时间戳,降级为字数比例估算) */
|
||||
/** 文案分句(⑤) */
|
||||
const sentences = useMemo(
|
||||
() => splitScriptIntoSentences(scriptText, sentenceTimings, _outputDuration),
|
||||
[scriptText, sentenceTimings, _outputDuration],
|
||||
() => splitScriptIntoSentences(scriptText, outputDuration),
|
||||
[scriptText, outputDuration],
|
||||
)
|
||||
|
||||
/** 已被现有 segments 占用的素材 id 集合(标灰、禁止重复选择) */
|
||||
@@ -145,7 +142,7 @@ const ModalBRollEditor: React.FC<ModalBRollEditorProps> = ({
|
||||
setSelectedAsset(asset)
|
||||
}
|
||||
|
||||
/** 确认添加一段 B-roll(⑥ 时间取所选句子的精确起止,后端静音检测 / 前端字数比例降级) */
|
||||
/** 确认添加一段 B-roll(⑥ 时间取所选句子的估算起止) */
|
||||
const handleConfirm = () => {
|
||||
if (!selectedAsset || !selectedSentence) return
|
||||
const startTime = selectedSentence.startTime
|
||||
@@ -267,9 +264,11 @@ const ModalBRollEditor: React.FC<ModalBRollEditorProps> = ({
|
||||
>
|
||||
<span className="aa-sentence-item__idx">{sent.index + 1}</span>
|
||||
<span className="aa-sentence-item__text">{sent.text}</span>
|
||||
<span className="aa-sentence-item__time">
|
||||
{sent.startTime.toFixed(1)}-{sent.endTime.toFixed(1)}s
|
||||
</span>
|
||||
{outputDuration > 0 && (
|
||||
<span className="aa-sentence-item__time">
|
||||
{sent.startTime.toFixed(1)}-{sent.endTime.toFixed(1)}s
|
||||
</span>
|
||||
)}
|
||||
</button>
|
||||
)
|
||||
})}
|
||||
@@ -350,7 +349,7 @@ const ModalBRollEditor: React.FC<ModalBRollEditorProps> = ({
|
||||
selectedSentence.endTime,
|
||||
selectedSentence.startTime + 0.5,
|
||||
).toFixed(1)}
|
||||
s
|
||||
s (按字数自动估算)
|
||||
</div>
|
||||
</>
|
||||
) : (
|
||||
|
||||
@@ -1,59 +0,0 @@
|
||||
/**
|
||||
* AI数字人 — 封面选择弹窗
|
||||
* 渲染完成后由主页面唤起,内部用 PanelCoverAndGenerate(select-cover 变体)提供
|
||||
* 智能抽帧 + 自定义上传 + 预览 + 确定按钮。
|
||||
*/
|
||||
import React from "react"
|
||||
import type { AiAvatarCoverConfig, RenderJob } from "../types"
|
||||
import PanelCoverAndGenerate from "./PanelCoverAndGenerate"
|
||||
|
||||
interface ModalCoverSelectProps {
|
||||
open: boolean
|
||||
onClose: () => void
|
||||
renderJob: RenderJob | null
|
||||
coverConfig: AiAvatarCoverConfig
|
||||
onCoverConfigChange: (partial: Partial<AiAvatarCoverConfig>) => void
|
||||
onGenerateRenderSmartCover: (renderId: string) => Promise<{ cover_url: string; message?: string }>
|
||||
onUploadCover?: (file: File) => void
|
||||
onCoverSelected: (coverUrl: string) => void
|
||||
}
|
||||
|
||||
const ModalCoverSelect: React.FC<ModalCoverSelectProps> = ({
|
||||
open,
|
||||
onClose,
|
||||
renderJob,
|
||||
coverConfig,
|
||||
onCoverConfigChange,
|
||||
onGenerateRenderSmartCover,
|
||||
onUploadCover,
|
||||
onCoverSelected,
|
||||
}) => {
|
||||
if (!open) return null
|
||||
|
||||
return (
|
||||
<div className="aa-modal-overlay" onClick={onClose}>
|
||||
<div className="aa-modal" onClick={(e) => e.stopPropagation()} style={{ maxWidth: 480 }}>
|
||||
<div className="aa-modal__header">
|
||||
<span className="aa-modal__title">选择封面</span>
|
||||
<button type="button" className="aa-modal__close" onClick={onClose} aria-label="关闭">
|
||||
×
|
||||
</button>
|
||||
</div>
|
||||
<div className="aa-modal__body" style={{ padding: 20 }}>
|
||||
<PanelCoverAndGenerate
|
||||
variant="select-cover"
|
||||
coverConfig={coverConfig}
|
||||
onCoverConfigChange={onCoverConfigChange}
|
||||
renderJob={renderJob}
|
||||
onGenerateRenderSmartCover={onGenerateRenderSmartCover}
|
||||
onUploadCover={onUploadCover}
|
||||
onClose={onClose}
|
||||
onCoverSelected={onCoverSelected}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
export default ModalCoverSelect
|
||||
@@ -1,45 +1,35 @@
|
||||
/**
|
||||
* AI数字人 — 面板5 / 封面选择弹窗内容:
|
||||
* - variant="setup"(默认):分辨率 / 配置摘要 / 「开始生成视频」按钮,用于主页面步骤2配置阶段;
|
||||
* 渲染完成后仍内嵌封面预览与按钮,方便不打开弹窗直接操作。
|
||||
* - variant="select-cover":只渲染封面选择区(智能获取封面 + 自定义上传 + 预览),
|
||||
* 用于 ModalCoverSelect 弹窗中;传 onClose 时底部显示「确定」按钮。
|
||||
* AI数字人 — 面板5:封面 & 生成
|
||||
* - 竖屏 9:16 封面预览(从视频截取 / 自定义上传)
|
||||
* - 分辨率选择(720p / 1080p / 4K)
|
||||
* - 配置汇总卡片(出镜视频/音色/文案/对口型/B-roll/标题/封面)
|
||||
* - 渐变紫色生成按钮
|
||||
*
|
||||
* 封面一律从最终成片(已叠加标题/B-roll)抽帧,本面板不再叠加标题。
|
||||
* 注意:v3 已删除"画面插入模式",本面板不包含该选项。
|
||||
*/
|
||||
import React, { useRef, useState } from "react"
|
||||
import type { AiAvatarCoverConfig, RenderJob } from "../types"
|
||||
|
||||
type PanelVariant = "setup" | "select-cover"
|
||||
import React, { useRef } from "react"
|
||||
import type { AiAvatarCoverConfig } from "../types"
|
||||
|
||||
interface PanelCoverAndGenerateProps {
|
||||
variant?: PanelVariant
|
||||
coverConfig: AiAvatarCoverConfig
|
||||
onCoverConfigChange: (partial: Partial<AiAvatarCoverConfig>) => void
|
||||
resolution?: string
|
||||
onResolutionChange?: (r: string) => void
|
||||
isGenerating?: boolean
|
||||
onGenerate?: () => void
|
||||
/** 当前渲染任务(渲染完成后才有 output_video_url,才能抽封面) */
|
||||
renderJob: RenderJob | null
|
||||
/** 从最终成片智能抽帧(参数 renderId),返回 { cover_url } */
|
||||
onGenerateRenderSmartCover: (renderId: string) => Promise<{ cover_url: string; message?: string }>
|
||||
/** 自定义上传封面(选择本地文件后由父组件处理实际上传) */
|
||||
onUploadCover?: (file: File) => void
|
||||
/** 弹窗关闭回调(传入则表示在弹窗中使用,底部显示「确定」按钮) */
|
||||
onClose?: () => void
|
||||
/** 封面选好(智能抽帧/自定义上传成功)后通知父组件,参数为封面 URL */
|
||||
onCoverSelected?: (coverUrl: string) => void
|
||||
/** 配置汇总信息(仅 variant="setup" 使用) */
|
||||
summary?: {
|
||||
resolution: string
|
||||
onResolutionChange: (r: string) => void
|
||||
isGenerating: boolean
|
||||
onGenerate: () => void
|
||||
/** 智能获取封面(MediaKit 选帧) */
|
||||
onSmartCover: () => void
|
||||
smartCoverLoading: boolean
|
||||
canSmartCover: boolean
|
||||
/** 配置汇总信息 */
|
||||
summary: {
|
||||
videoName: string | null
|
||||
voiceName: string | null
|
||||
scriptLength: number
|
||||
lipsyncStatus: string | null
|
||||
brollCount: number
|
||||
hasTitle: boolean
|
||||
/** 封面状态:'not_ready'(视频未生成) / 'pending'(视频生成了但未选) / 'selected'(已选) */
|
||||
coverStatus: "not_ready" | "pending" | "selected"
|
||||
hasCover: boolean
|
||||
}
|
||||
}
|
||||
|
||||
@@ -58,116 +48,53 @@ const LIPSYNC_STATUS_LABEL: Record<string, { text: string; cls: string }> = {
|
||||
}
|
||||
|
||||
const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
|
||||
variant = "setup",
|
||||
coverConfig,
|
||||
onCoverConfigChange,
|
||||
resolution = "720p",
|
||||
resolution,
|
||||
onResolutionChange,
|
||||
isGenerating = false,
|
||||
isGenerating,
|
||||
onGenerate,
|
||||
renderJob,
|
||||
onGenerateRenderSmartCover,
|
||||
onUploadCover,
|
||||
onClose,
|
||||
onCoverSelected,
|
||||
onSmartCover,
|
||||
smartCoverLoading,
|
||||
canSmartCover,
|
||||
summary,
|
||||
}) => {
|
||||
const uploadInputRef = useRef<HTMLInputElement>(null)
|
||||
// 内部维护智能封面加载态(修复点 2 次 bug:不依赖外层异步 setState 顺序)
|
||||
const [smartCoverLoading, setSmartCoverLoading] = useState(false)
|
||||
|
||||
/** 自定义上传封面 */
|
||||
const handleUploadClick = () => {
|
||||
uploadInputRef.current?.click()
|
||||
}
|
||||
|
||||
const _applyCoverUrl = (url: string, mode: "upload" | "auto_frame") => {
|
||||
const partial: Partial<AiAvatarCoverConfig> = {
|
||||
mode,
|
||||
thumbnail_url: url,
|
||||
}
|
||||
if (mode === "auto_frame") {
|
||||
partial.smart_cover_url = url
|
||||
} else {
|
||||
partial.upload_url = url
|
||||
}
|
||||
onCoverConfigChange(partial)
|
||||
onCoverSelected?.(url)
|
||||
}
|
||||
|
||||
const handleFileChange = (e: React.ChangeEvent<HTMLInputElement>) => {
|
||||
const file = e.target.files?.[0]
|
||||
if (!file) return
|
||||
if (onUploadCover) {
|
||||
onUploadCover(file)
|
||||
e.target.value = ""
|
||||
return
|
||||
}
|
||||
// 本地预览兜底(实际上传由父级处理;blob URL 仅作本地展示)
|
||||
// 本地预览:生成 object URL(实际上传由父级/后端链路处理)
|
||||
const url = URL.createObjectURL(file)
|
||||
_applyCoverUrl(url, "upload")
|
||||
onCoverConfigChange({ mode: "upload", upload_url: url, thumbnail_url: url })
|
||||
// 允许重复选择同一文件
|
||||
e.target.value = ""
|
||||
}
|
||||
|
||||
/** 智能获取封面(从最终成片抽帧;必须等 render 完成) */
|
||||
const handleSmartCover = async () => {
|
||||
if (!renderJob || renderJob.status !== "completed" || !renderJob.id) return
|
||||
setSmartCoverLoading(true)
|
||||
try {
|
||||
const res = await onGenerateRenderSmartCover(renderJob.id)
|
||||
if (res.cover_url) {
|
||||
_applyCoverUrl(res.cover_url, "auto_frame")
|
||||
} else {
|
||||
// 失败由父组件 message 提示,这里不重复弹窗
|
||||
console.warn("[智能封面] 返回空 cover_url:", res.message)
|
||||
}
|
||||
} catch (err) {
|
||||
console.error("[智能封面] 调用失败:", err)
|
||||
} finally {
|
||||
setSmartCoverLoading(false)
|
||||
}
|
||||
/** 智能获取封面(调后端 MediaKit 抽帧评分选最佳帧,#1822) */
|
||||
const handleSmartCover = () => {
|
||||
onCoverConfigChange({ mode: "auto_frame" })
|
||||
onSmartCover()
|
||||
}
|
||||
|
||||
const lipsync = summary?.lipsyncStatus ? LIPSYNC_STATUS_LABEL[summary.lipsyncStatus] : null
|
||||
const canGenerate = summary?.lipsyncStatus === "completed" && !isGenerating
|
||||
// 渲染已完成 → 封面区可用
|
||||
const isRenderCompleted = renderJob?.status === "completed"
|
||||
const canSmartCover = isRenderCompleted && !smartCoverLoading
|
||||
const lipsync = summary.lipsyncStatus ? LIPSYNC_STATUS_LABEL[summary.lipsyncStatus] : null
|
||||
|
||||
/** 封面图实际展示的 url:智能封面 > 自定义上传 > 空 */
|
||||
const coverUrl =
|
||||
coverConfig.smart_cover_url || coverConfig.thumbnail_url || coverConfig.upload_url
|
||||
const hasCoverImage = Boolean(coverUrl)
|
||||
const canGenerate = summary.lipsyncStatus === "completed" && !isGenerating
|
||||
|
||||
/** 封面区占位文字 */
|
||||
const coverPlaceholder = isRenderCompleted ? "暂无封面" : "视频生成后可选择封面"
|
||||
|
||||
/** 配置摘要中的封面状态标签 */
|
||||
const coverSummaryNode = (() => {
|
||||
if (!summary) return null
|
||||
if (summary.coverStatus === "selected") {
|
||||
return <span className="aa-config-summary__value">已选择</span>
|
||||
}
|
||||
if (summary.coverStatus === "pending") {
|
||||
return <span className="aa-config-summary__value">待选择</span>
|
||||
}
|
||||
return <span className="aa-config-summary__empty">生成视频后可选</span>
|
||||
})()
|
||||
|
||||
// ── 封面选择区(两种 variant 共用) ─────────────────────────────────
|
||||
const coverSection = (
|
||||
<div className="aa-cover-section" style={{ marginTop: variant === "select-cover" ? 0 : 16 }}>
|
||||
<div className="aa-label" style={{ marginBottom: 8 }}>
|
||||
{variant === "select-cover" ? "选择封面" : "封面"}
|
||||
</div>
|
||||
{/* 封面预览(竖屏 9:16)——成片帧已经通过 Canvas PNG overlay 带有标题,直接展示原图即可 */}
|
||||
<div className="aa-cover-preview" style={{ opacity: isRenderCompleted ? 1 : 0.5 }}>
|
||||
{hasCoverImage ? (
|
||||
<img src={coverUrl!} alt="封面预览" draggable={false} />
|
||||
return (
|
||||
<div className="aa-cover-generate">
|
||||
{/* 封面预览(竖屏 9:16) */}
|
||||
<div className="aa-cover-preview">
|
||||
{coverConfig.thumbnail_url ? (
|
||||
<img src={coverConfig.thumbnail_url} alt="封面预览" />
|
||||
) : (
|
||||
<span className="aa-cover-preview__placeholder">{coverPlaceholder}</span>
|
||||
<span className="aa-cover-preview__placeholder">暂无封面</span>
|
||||
)}
|
||||
{smartCoverLoading && <div className="aa-cover-preview__loading">⏳ 智能选帧中…</div>}
|
||||
</div>
|
||||
|
||||
<div className="aa-cover-actions">
|
||||
@@ -175,8 +102,8 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
|
||||
type="button"
|
||||
className={`aa-btn aa-btn--ghost${coverConfig.mode === "auto_frame" ? " active" : ""}`}
|
||||
onClick={handleSmartCover}
|
||||
disabled={!canSmartCover}
|
||||
title={isRenderCompleted ? "从成片智能选帧" : "请先生成视频"}
|
||||
disabled={smartCoverLoading || !canSmartCover}
|
||||
title={canSmartCover ? "基于对口型成片智能选帧" : "请先完成对口型生成"}
|
||||
>
|
||||
{smartCoverLoading ? "⏳ 智能选帧中…" : "🎬 智能获取封面"}
|
||||
</button>
|
||||
@@ -184,8 +111,6 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
|
||||
type="button"
|
||||
className={`aa-btn aa-btn--ghost${coverConfig.mode === "upload" ? " active" : ""}`}
|
||||
onClick={handleUploadClick}
|
||||
disabled={!isRenderCompleted || smartCoverLoading}
|
||||
title={isRenderCompleted ? "自定义上传封面" : "请先生成视频"}
|
||||
>
|
||||
📷 自定义上传
|
||||
</button>
|
||||
@@ -197,36 +122,14 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
|
||||
onChange={handleFileChange}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
|
||||
// ── select-cover 变体:只渲染封面区 + 弹窗确定按钮 ──
|
||||
if (variant === "select-cover") {
|
||||
return (
|
||||
<div className="aa-cover-generate">
|
||||
{coverSection}
|
||||
{onClose && (
|
||||
<div style={{ marginTop: 16, display: "flex", justifyContent: "flex-end" }}>
|
||||
<button type="button" className="aa-btn aa-btn--primary" onClick={onClose}>
|
||||
确定
|
||||
</button>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
// ── setup 变体:分辨率 / 配置摘要 / 生成按钮(渲染完成后内嵌封面区) ──
|
||||
return (
|
||||
<div className="aa-cover-generate">
|
||||
{/* 分辨率选择 */}
|
||||
<div className="aa-form-field">
|
||||
<label className="aa-label">分辨率</label>
|
||||
<select
|
||||
className="aa-select"
|
||||
value={resolution}
|
||||
onChange={(e) => onResolutionChange?.(e.target.value)}
|
||||
disabled={isGenerating}
|
||||
onChange={(e) => onResolutionChange(e.target.value)}
|
||||
>
|
||||
{RESOLUTION_OPTIONS.map((opt) => (
|
||||
<option key={opt.value} value={opt.value}>
|
||||
@@ -241,7 +144,7 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
|
||||
<div className="aa-config-summary">
|
||||
<div className="aa-config-summary__row">
|
||||
<span>出镜视频</span>
|
||||
{summary?.videoName ? (
|
||||
{summary.videoName ? (
|
||||
<span className="aa-config-summary__value">{summary.videoName}</span>
|
||||
) : (
|
||||
<span className="aa-config-summary__empty">未配置</span>
|
||||
@@ -249,7 +152,7 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
|
||||
</div>
|
||||
<div className="aa-config-summary__row">
|
||||
<span>音色</span>
|
||||
{summary?.voiceName ? (
|
||||
{summary.voiceName ? (
|
||||
<span className="aa-config-summary__value">{summary.voiceName}</span>
|
||||
) : (
|
||||
<span className="aa-config-summary__empty">未配置</span>
|
||||
@@ -257,7 +160,7 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
|
||||
</div>
|
||||
<div className="aa-config-summary__row">
|
||||
<span>文案</span>
|
||||
{summary && summary.scriptLength > 0 ? (
|
||||
{summary.scriptLength > 0 ? (
|
||||
<span className="aa-config-summary__value">{summary.scriptLength} 字</span>
|
||||
) : (
|
||||
<span className="aa-config-summary__empty">未配置</span>
|
||||
@@ -274,12 +177,12 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
|
||||
<div className="aa-config-summary__row">
|
||||
<span>B-roll 画面插入</span>
|
||||
<span className="aa-config-summary__value">
|
||||
{summary && summary.brollCount > 0 ? `${summary.brollCount} 段` : "无"}
|
||||
{summary.brollCount > 0 ? `${summary.brollCount} 段` : "无"}
|
||||
</span>
|
||||
</div>
|
||||
<div className="aa-config-summary__row">
|
||||
<span>标题</span>
|
||||
{summary?.hasTitle ? (
|
||||
{summary.hasTitle ? (
|
||||
<span className="aa-config-summary__value">已设置</span>
|
||||
) : (
|
||||
<span className="aa-config-summary__empty">未配置</span>
|
||||
@@ -287,7 +190,11 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
|
||||
</div>
|
||||
<div className="aa-config-summary__row">
|
||||
<span>封面</span>
|
||||
{coverSummaryNode}
|
||||
{summary.hasCover ? (
|
||||
<span className="aa-config-summary__value">已开启</span>
|
||||
) : (
|
||||
<span className="aa-config-summary__empty">未配置</span>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@@ -300,16 +207,11 @@ const PanelCoverAndGenerate: React.FC<PanelCoverAndGenerateProps> = ({
|
||||
>
|
||||
{isGenerating ? "⏳ 生成中..." : "🚀 开始生成视频"}
|
||||
</button>
|
||||
{summary?.lipsyncStatus !== "completed" && !isGenerating && (
|
||||
{summary.lipsyncStatus !== "completed" && !isGenerating && (
|
||||
<div style={{ marginTop: 8, fontSize: 11, color: "#8c8ca1", textAlign: "center" }}>
|
||||
请先完成对口型生成
|
||||
</div>
|
||||
)}
|
||||
{isGenerating && (
|
||||
<div style={{ marginTop: 8, fontSize: 11, color: "#8c8ca1", textAlign: "center" }}>
|
||||
视频生成中,请稍候…
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
|
||||
@@ -1,9 +1,9 @@
|
||||
/**
|
||||
* AI数字人 — 对口型预览面板(步骤2用)
|
||||
* B-roll 画面插入 + 对口型视频预览 + 生成/重新生成按钮
|
||||
* v3.1: 标题字号按预览容器实际宽度动态计算 previewScale(基准 720p),与成片一致
|
||||
* v3.1: 预览容器按 1/2 缩放、标题实时叠加预览
|
||||
*/
|
||||
import React, { useCallback, useEffect, useRef, useState } from "react"
|
||||
import React, { useRef } from "react"
|
||||
import type { LipsyncJob, BRollSegment, AiAvatarTitleConfig } from "../types"
|
||||
|
||||
interface PanelLipsyncPreviewProps {
|
||||
@@ -14,8 +14,8 @@ interface PanelLipsyncPreviewProps {
|
||||
onRemoveBRoll: (id: string) => void
|
||||
/** 标题配置(实时叠加预览用) */
|
||||
titleConfig?: AiAvatarTitleConfig
|
||||
/** 标题位置变更回调(拖拽结束时调用,发送百分比坐标 + position:"custom") */
|
||||
onTitlePositionChange?: (pos: { pos_x: number; pos_y: number; position: string }) => void
|
||||
/** 标题位置变更回调(拖拽结束时调用) */
|
||||
onTitlePositionChange?: (pos: { pos_x: number; pos_y: number }) => void
|
||||
}
|
||||
|
||||
const BROLL_MODE_LABEL: Record<BRollSegment["mode"], string> = {
|
||||
@@ -29,16 +29,6 @@ function formatTime(seconds: number): string {
|
||||
return `${m}:${s.toString().padStart(2, "0")}`
|
||||
}
|
||||
|
||||
/** 字体名 → CSS font-family 映射(与 titleCanvas 字体链对齐) */
|
||||
const FONT_FAMILY_MAP: Record<string, string> = {
|
||||
思源黑体:
|
||||
"'Noto Sans CJK SC', 'Source Han Sans CN', 'PingFang SC', 'Microsoft YaHei', sans-serif",
|
||||
思源宋体: "'Noto Serif SC', 'Source Han Serif SC', 'SimSun', serif",
|
||||
楷体: "KaiTi, 'STKaiti', serif",
|
||||
黑体: "'Heiti SC', 'SimHei', 'Microsoft YaHei', sans-serif",
|
||||
}
|
||||
const getFontFamily = (font: string): string => FONT_FAMILY_MAP[font] || FONT_FAMILY_MAP["思源黑体"]
|
||||
|
||||
export function PanelLipsyncPreview({
|
||||
lipsyncJob,
|
||||
onGenerateLipsync,
|
||||
@@ -51,8 +41,6 @@ export function PanelLipsyncPreview({
|
||||
const titleDragRef = useRef<HTMLDivElement>(null)
|
||||
const draggingTitleRef = useRef(false)
|
||||
const previewContainerRef = useRef<HTMLDivElement>(null)
|
||||
// 预览容器实际宽度(通过 ResizeObserver 监听),用于动态计算 previewScale
|
||||
const [containerWidth, setContainerWidth] = useState(0)
|
||||
const isGenerating = lipsyncJob?.status === "pending" || lipsyncJob?.status === "processing"
|
||||
const isDone = lipsyncJob?.status === "completed"
|
||||
const isFailed = lipsyncJob?.status === "failed"
|
||||
@@ -64,84 +52,29 @@ export function PanelLipsyncPreview({
|
||||
? "排队中…"
|
||||
: "对口型生成中…"
|
||||
|
||||
// 监听预览容器尺寸变化,动态测量宽度以计算 previewScale(基准 720p)
|
||||
useEffect(() => {
|
||||
const el = previewContainerRef.current
|
||||
if (!el) return
|
||||
const update = () => setContainerWidth(el.clientWidth || 0)
|
||||
update()
|
||||
if (typeof ResizeObserver !== "undefined") {
|
||||
const ro = new ResizeObserver(update)
|
||||
ro.observe(el)
|
||||
return () => ro.disconnect()
|
||||
}
|
||||
window.addEventListener("resize", update)
|
||||
return () => window.removeEventListener("resize", update)
|
||||
}, [])
|
||||
|
||||
// 预览缩放比:预览宽度 / 720(基准宽度)
|
||||
const previewScale = containerWidth > 0 ? containerWidth / 720 : 0.35
|
||||
const ps = useCallback((v: number) => Math.round(v * previewScale * 100) / 100, [previewScale])
|
||||
|
||||
/** 标题叠加样式(字号/padding/描边/阴影均按 previewScale 缩放,保持与成片视觉一致) */
|
||||
const titleOverlayStyle: React.CSSProperties | null =
|
||||
titleConfig?.title && containerWidth > 0
|
||||
? (() => {
|
||||
const baseSize = titleConfig.size || 48
|
||||
const fontSize = ps(baseSize)
|
||||
// 描边宽度基准 ≈ size * 0.06,最小 1.5px @720p
|
||||
const strokeW = Math.max(ps(1.5), +(baseSize * 0.06 * previewScale).toFixed(2))
|
||||
// 阴影按比例缩放
|
||||
const shadowBlur = ps(4)
|
||||
const shadowOffsetY = ps(2)
|
||||
// padding / top 边距按比例(基准 8px 对应预览小窗,成片基准 16px,这里 8px 对应约 0.33 缩放)
|
||||
const padV = ps(16) * 0.5 // ≈ 8px in ~240px container
|
||||
const padH = ps(24) * 0.5
|
||||
|
||||
const style: React.CSSProperties = {
|
||||
position: "absolute",
|
||||
color: titleConfig.color || "#ffffff",
|
||||
fontFamily: getFontFamily(titleConfig.font || "思源黑体"),
|
||||
fontSize: `${fontSize}px`,
|
||||
fontWeight: titleConfig.bold ? 700 : 400,
|
||||
fontStyle: titleConfig.italic ? "italic" : "normal",
|
||||
textAlign: "center",
|
||||
width: "90%",
|
||||
lineHeight: 1.2,
|
||||
padding: `${ps(4)}px ${padH}px`,
|
||||
textShadow: titleConfig.shadow
|
||||
? `0 ${shadowOffsetY}px ${shadowBlur}px rgba(0,0,0,0.8), 0 0 ${ps(2)}px rgba(0,0,0,0.5)`
|
||||
: undefined,
|
||||
WebkitTextStroke: titleConfig.stroke ? `${strokeW}px #000` : undefined,
|
||||
boxSizing: "border-box",
|
||||
wordBreak: "break-word",
|
||||
whiteSpace: "pre-wrap",
|
||||
}
|
||||
|
||||
if (
|
||||
titleConfig.position === "custom" &&
|
||||
titleConfig.pos_x != null &&
|
||||
titleConfig.pos_y != null
|
||||
) {
|
||||
style.left = `${titleConfig.pos_x}%`
|
||||
style.top = `${titleConfig.pos_y}%`
|
||||
style.transform = "translateX(-50%) translateY(-50%)"
|
||||
} else if (titleConfig.position === "top") {
|
||||
style.left = "50%"
|
||||
style.top = padV
|
||||
style.transform = "translateX(-50%)"
|
||||
} else if (titleConfig.position === "bottom") {
|
||||
style.left = "50%"
|
||||
style.bottom = padV
|
||||
style.transform = "translateX(-50%)"
|
||||
} else {
|
||||
style.left = "50%"
|
||||
style.top = "50%"
|
||||
style.transform = "translateX(-50%) translateY(-50%)"
|
||||
}
|
||||
return style
|
||||
})()
|
||||
: null
|
||||
/** 标题叠加样式 */
|
||||
const titleOverlayStyle: React.CSSProperties | null = titleConfig?.title
|
||||
? {
|
||||
position: "absolute",
|
||||
left: "50%",
|
||||
transform: "translateX(-50%)",
|
||||
color: titleConfig.color || "#ffffff",
|
||||
fontFamily: titleConfig.font || "思源黑体",
|
||||
fontSize: `${(titleConfig.size || 36) * 0.55}px`, // 预览等比缩
|
||||
fontWeight: titleConfig.bold ? 700 : 400,
|
||||
fontStyle: titleConfig.italic ? "italic" : "normal",
|
||||
textAlign: "center",
|
||||
width: "90%",
|
||||
padding: "4px 8px",
|
||||
textShadow: titleConfig.shadow ? "0 2px 4px rgba(0,0,0,0.8)" : undefined,
|
||||
WebkitTextStroke: titleConfig.stroke ? "1.5px #000" : undefined,
|
||||
...(titleConfig.position === "top"
|
||||
? { top: 8 }
|
||||
: titleConfig.position === "bottom"
|
||||
? { bottom: 8 }
|
||||
: { top: "50%", transform: "translateX(-50%) translateY(-50%)" }),
|
||||
}
|
||||
: null
|
||||
|
||||
const handleTitlePointerDown = (e: React.PointerEvent<HTMLDivElement>) => {
|
||||
if (!onTitlePositionChange || !previewContainerRef.current) return
|
||||
@@ -172,10 +105,7 @@ export function PanelLipsyncPreview({
|
||||
const rect = previewContainerRef.current.getBoundingClientRect()
|
||||
const relX = Math.max(0, Math.min(rect.width, e.clientX - rect.left))
|
||||
const relY = Math.max(0, Math.min(rect.height, e.clientY - rect.top))
|
||||
// 发送百分比坐标(0-100),与后端 drawtext 百分比表达式对齐
|
||||
const xpct = Math.round((relX / rect.width) * 1000) / 10
|
||||
const ypct = Math.round((relY / rect.height) * 1000) / 10
|
||||
onTitlePositionChange({ pos_x: xpct, pos_y: ypct, position: "custom" })
|
||||
onTitlePositionChange({ pos_x: relX, pos_y: relY })
|
||||
}
|
||||
;(e.currentTarget as HTMLDivElement).style.cursor = "grab"
|
||||
}
|
||||
@@ -244,7 +174,7 @@ export function PanelLipsyncPreview({
|
||||
)}
|
||||
</div>
|
||||
|
||||
{/* ── 对口型预览(标题字号按 previewScale 动态缩放) ─ */}
|
||||
{/* ── 对口型预览(v3.1: 缩放1/2 + 标题叠加) ─ */}
|
||||
<div className="aa-lipsync-section">
|
||||
<div className="aa-lipsync-section__title">对口型预览</div>
|
||||
|
||||
|
||||
@@ -2,16 +2,17 @@
|
||||
* AI数字人 — 出镜视频选择面板
|
||||
* - 未选视频:虚线上传区,点击打开素材库弹窗
|
||||
* - 已选视频:竖屏 9:16 预览播放器 + 视频信息卡片 + 移除按钮
|
||||
*
|
||||
* 注意:本面板只展示原始素材视频,不叠加标题(标题在对口型预览和最终成片上展示)
|
||||
*/
|
||||
import type { AssetItem } from "@/api/assets"
|
||||
import type { AiAvatarTitleConfig } from "../types"
|
||||
import { getFontFamily } from "@/pages/generate/constants"
|
||||
|
||||
export interface PanelVideoSelectorProps {
|
||||
selectedVideo: AssetItem | null
|
||||
/** 触发打开素材库弹窗 */
|
||||
onSelectVideo: () => void
|
||||
onRemoveVideo: () => void
|
||||
titleConfig?: AiAvatarTitleConfig
|
||||
}
|
||||
|
||||
/** 格式化时长(秒 → mm:ss) */
|
||||
@@ -26,6 +27,7 @@ export function PanelVideoSelector({
|
||||
selectedVideo,
|
||||
onSelectVideo,
|
||||
onRemoveVideo,
|
||||
titleConfig,
|
||||
}: PanelVideoSelectorProps) {
|
||||
/* 未选视频:虚线上传区,点击打开素材库弹窗 */
|
||||
if (!selectedVideo) {
|
||||
@@ -55,13 +57,42 @@ export function PanelVideoSelector({
|
||||
|
||||
return (
|
||||
<div>
|
||||
{/* 竖屏 9:16 视频预览播放器(纯素材预览,不叠加标题) */}
|
||||
<div className="aa-video-preview">
|
||||
{/* 竖屏 9:16 视频预览播放器 + 标题实时预览 */}
|
||||
<div className="aa-video-preview" style={{ position: "relative" }}>
|
||||
{fileUrl ? (
|
||||
<video src={fileUrl} poster={selectedVideo.thumbnail_url} controls playsInline />
|
||||
) : (
|
||||
<div className="aa-video-preview__placeholder">视频暂不可预览</div>
|
||||
)}
|
||||
{titleConfig?.title && (
|
||||
<div
|
||||
style={{
|
||||
position: "absolute",
|
||||
left: "50%",
|
||||
transform: "translateX(-50%)",
|
||||
...(titleConfig.position === "top"
|
||||
? { top: "10%" }
|
||||
: titleConfig.position === "bottom"
|
||||
? { bottom: "10%" }
|
||||
: { top: "50%", transform: "translate(-50%, -50%)" }),
|
||||
fontSize: Math.max(titleConfig.size, 32),
|
||||
fontFamily: getFontFamily(titleConfig.font),
|
||||
color: titleConfig.color,
|
||||
fontWeight: titleConfig.bold ? 700 : 400,
|
||||
fontStyle: titleConfig.italic ? "italic" : "normal",
|
||||
textShadow: "0 2px 4px rgba(0,0,0,0.5)",
|
||||
WebkitTextStroke: "2px #000",
|
||||
pointerEvents: "none",
|
||||
zIndex: 10,
|
||||
maxWidth: "90%",
|
||||
textAlign: "center",
|
||||
whiteSpace: "pre-wrap",
|
||||
lineHeight: 1.3,
|
||||
}}
|
||||
>
|
||||
{titleConfig.title}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
|
||||
{/* 视频信息卡片:文件名 / 时长 / 分辨率 */}
|
||||
|
||||
@@ -139,6 +139,13 @@ export function PanelVoiceSelector({
|
||||
}
|
||||
const targetId = voice.voice_clone_profile_id || voice.id
|
||||
// DEBUG: 打印请求参数,帮助定位 /tts/preview 失败原因
|
||||
console.log("[AI数字人-克隆试听] previewTts 请求:", {
|
||||
voice_id: targetId,
|
||||
voice_name: voice.name,
|
||||
voice_type: voice.type,
|
||||
voice_clone_profile_id: voice.voice_clone_profile_id,
|
||||
voice_id_field: voice.voice_id,
|
||||
})
|
||||
setPreviewingId(voice.id)
|
||||
try {
|
||||
const res = await previewTts({
|
||||
@@ -147,6 +154,10 @@ export function PanelVoiceSelector({
|
||||
speed: speed, // 透传用户选择的语速(#1822)
|
||||
emotion: normalizeEmotion(emotion), // 情绪中文→英文枚举
|
||||
})
|
||||
console.log("[AI数字人-克隆试听] previewTts 响应:", {
|
||||
audio_url: res.audio_url?.substring(0, 80),
|
||||
duration: res.duration,
|
||||
})
|
||||
if (!res.audio_url) {
|
||||
setPreviewingId(null)
|
||||
message.error("合成试听失败:未返回音频")
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
/**
|
||||
* AI数字人 — 页面全局状态管理 hook(v3 + #1845 配音前置)
|
||||
* AI数字人 — 页面全局状态管理 hook(v3)
|
||||
*/
|
||||
import { useState, useCallback } from "react"
|
||||
import type { AssetItem } from "@/api/assets"
|
||||
@@ -13,19 +13,10 @@ import {
|
||||
type BRollSegment,
|
||||
type AiAvatarTitleConfig,
|
||||
type AiAvatarCoverConfig,
|
||||
type TtsPreviewResult,
|
||||
DEFAULT_TITLE_CONFIG,
|
||||
DEFAULT_COVER_CONFIG,
|
||||
} from "../types"
|
||||
|
||||
const DEFAULT_TTS_PREVIEW: TtsPreviewResult = {
|
||||
audioUrl: null,
|
||||
duration: 0,
|
||||
sentenceTimings: [],
|
||||
status: "idle",
|
||||
error: null,
|
||||
}
|
||||
|
||||
export function useAiAvatar() {
|
||||
/* ── 面板1:出镜视频 ── */
|
||||
const [selectedVideo, setSelectedVideo] = useState<AssetItem | null>(null)
|
||||
@@ -45,9 +36,6 @@ export function useAiAvatar() {
|
||||
const [showScriptModal, setShowScriptModal] = useState(false)
|
||||
const [showBRollModal, setShowBRollModal] = useState(false)
|
||||
|
||||
/* ── #1845 TTS 预合成(步骤1「生成配音」) ── */
|
||||
const [ttsPreview, setTtsPreview] = useState<TtsPreviewResult>(DEFAULT_TTS_PREVIEW)
|
||||
|
||||
/* ── 面板3.5:B-roll ── */
|
||||
const [bRollSegments, setBRollSegments] = useState<BRollSegment[]>([])
|
||||
|
||||
@@ -93,7 +81,6 @@ export function useAiAvatar() {
|
||||
setScript(null)
|
||||
setScriptText("")
|
||||
setLipsyncJob(null)
|
||||
setTtsPreview(DEFAULT_TTS_PREVIEW)
|
||||
setBRollSegments([])
|
||||
setTitleConfig(DEFAULT_TITLE_CONFIG)
|
||||
setCoverConfig(DEFAULT_COVER_CONFIG)
|
||||
@@ -131,10 +118,6 @@ export function useAiAvatar() {
|
||||
showBRollModal,
|
||||
setShowBRollModal,
|
||||
selectScript,
|
||||
// #1845 TTS 预合成
|
||||
ttsPreview,
|
||||
setTtsPreview,
|
||||
resetTtsPreview: useCallback(() => setTtsPreview(DEFAULT_TTS_PREVIEW), []),
|
||||
// B-roll
|
||||
bRollSegments,
|
||||
addBRollSegment,
|
||||
|
||||
@@ -28,17 +28,6 @@ export const VOICE_LANGUAGE_OPTIONS: { value: VoiceLanguage; label: string }[] =
|
||||
/* ── 对口型任务状态 ── */
|
||||
export type LipsyncStatus = "idle" | "pending" | "processing" | "completed" | "failed"
|
||||
|
||||
/* ── TTS 预合成(#1845 配音前置:步骤1「生成配音」状态) ── */
|
||||
export type TtsPreviewStatus = "idle" | "generating" | "done" | "failed"
|
||||
|
||||
export interface TtsPreviewResult {
|
||||
audioUrl: string | null
|
||||
duration: number
|
||||
sentenceTimings: SentenceTiming[]
|
||||
status: TtsPreviewStatus
|
||||
error: string | null
|
||||
}
|
||||
|
||||
/* ── 文案 ── */
|
||||
export interface Script {
|
||||
id: string
|
||||
@@ -55,23 +44,12 @@ export interface LipsyncJob {
|
||||
status: LipsyncStatus
|
||||
progress: number
|
||||
output_video_url: string | null
|
||||
/** 对口型成片总时长(秒),后端返回 */
|
||||
script_text: string
|
||||
/** 对口型成片总时长(秒),后端返回;用于 B-roll 时间自动估算(#1809 ⑥) */
|
||||
output_duration?: number
|
||||
/** 精确句子时间戳(后端基于 TTS 音频静音检测计算) */
|
||||
sentence_timings?: SentenceTiming[] | null
|
||||
error_message: string | null
|
||||
created_at: string
|
||||
}
|
||||
|
||||
/* ── 句子时间戳(后端精确计算) ── */
|
||||
export interface SentenceTiming {
|
||||
index: number
|
||||
text: string
|
||||
start_time: number
|
||||
end_time: number
|
||||
}
|
||||
|
||||
/* ── B-roll 画面插入 ── */
|
||||
export type BRollInsertMode = "fullscreen" | "pip"
|
||||
export type PipPosition = "top-left" | "top-right" | "bottom-left" | "bottom-right"
|
||||
@@ -99,7 +77,7 @@ export interface AiAvatarTitleConfig {
|
||||
shadow: boolean
|
||||
color: string
|
||||
auto_subtitle: boolean
|
||||
/** 自定义位置坐标(position=custom 时生效,百分比 0-100) */
|
||||
/** 自定义位置坐标(position=custom 时生效,像素) */
|
||||
pos_x?: number
|
||||
pos_y?: number
|
||||
}
|
||||
@@ -123,7 +101,6 @@ export interface RenderJob {
|
||||
status: RenderStatus
|
||||
progress: number
|
||||
output_video_url: string | null
|
||||
output_cover_url: string | null
|
||||
error_message: string | null
|
||||
created_at: string
|
||||
}
|
||||
@@ -133,7 +110,7 @@ export const DEFAULT_TITLE_CONFIG: AiAvatarTitleConfig = {
|
||||
title: "",
|
||||
position: "bottom",
|
||||
font: "思源黑体",
|
||||
size: 48,
|
||||
size: 28,
|
||||
bold: true,
|
||||
italic: false,
|
||||
stroke: false,
|
||||
|
||||
@@ -28,13 +28,10 @@ export function normalizeEmotion(raw: string | undefined | null): VoiceEmotion {
|
||||
* 后端真实字段:text(或content)、font(或font_preset)、font_size(或size)、
|
||||
* font_color(或color,可传 #RRGGBB)、position(top/center/bottom/custom)、
|
||||
* enabled、bold、stroke{enabled,width,color}、shadow{enabled,color,offset_x,offset_y}、
|
||||
* pos_x/pos_y(custom 时)、title_image_dataurl(前端 Canvas 渲染的 PNG dataURL,WYSIWYG 路径优先)。
|
||||
* pos_x/pos_y(custom 时)。
|
||||
* 口播标题默认 position=bottom(不传后端会默认 top 跑到画面顶部)。
|
||||
*/
|
||||
export function buildTitleConfigPayload(
|
||||
cfg: AiAvatarTitleConfig,
|
||||
titleImageDataUrl?: string | null,
|
||||
): Record<string, unknown> {
|
||||
export function buildTitleConfigPayload(cfg: AiAvatarTitleConfig): Record<string, unknown> {
|
||||
const text = (cfg.title || "").trim()
|
||||
if (!text) return {}
|
||||
const position = cfg.position || "bottom"
|
||||
@@ -42,7 +39,7 @@ export function buildTitleConfigPayload(
|
||||
text,
|
||||
enabled: true,
|
||||
font: cfg.font || "思源黑体",
|
||||
font_size: Math.round(cfg.size) || 48,
|
||||
font_size: Math.round(cfg.size) || 36,
|
||||
font_color: cfg.color || "#ffffff",
|
||||
position,
|
||||
bold: !!cfg.bold,
|
||||
@@ -56,10 +53,6 @@ export function buildTitleConfigPayload(
|
||||
payload.pos_x = cfg.pos_x
|
||||
payload.pos_y = cfg.pos_y
|
||||
}
|
||||
// 前端 Canvas 渲染好的 PNG dataURL(所见即所得,后端优先 overlay 此图片图层)
|
||||
if (titleImageDataUrl) {
|
||||
payload.title_image_dataurl = titleImageDataUrl
|
||||
}
|
||||
return payload
|
||||
}
|
||||
|
||||
@@ -74,14 +67,9 @@ export function buildCoverConfigPayload(
|
||||
// build_cover_extract_command 读取 timestamp(截帧秒数)
|
||||
timestamp: cfg.frame_time || 0,
|
||||
}
|
||||
// 智能封面 URL(后端字段名为 url/imageUrl/cover_url 都兼容,优先 url)
|
||||
if (smartCoverUrl) {
|
||||
payload.url = smartCoverUrl
|
||||
payload.cover_url = smartCoverUrl
|
||||
}
|
||||
if (smartCoverUrl) payload.cover_url = smartCoverUrl
|
||||
// 自定义上传:blob: 本地预览地址无法给后端,仅 OSS URL 可用
|
||||
if (cfg.mode === "upload" && cfg.upload_url && !cfg.upload_url.startsWith("blob:")) {
|
||||
payload.url = cfg.upload_url
|
||||
payload.upload_url = cfg.upload_url
|
||||
}
|
||||
return payload
|
||||
|
||||
@@ -1,10 +1,5 @@
|
||||
/**
|
||||
* AI数字人 — 文案分句 & B-roll 时间计算
|
||||
*
|
||||
* 数据来源优先级:
|
||||
* 1. 后端 sentence_timings(基于 TTS 音频静音检测,精确到句子边界)—— 直接使用,不重新分句
|
||||
* 2. 后端 output_duration(最终渲染视频时长) + 本地分句 —— 按字数比例估算
|
||||
* 3. 两者都没有(对口型还在生成中)—— 返回分句文本但 startTime/endTime 全部 0,等数据到位重算
|
||||
* AI数字人 — 文案分句 & B-roll 时间自动估算(#1809 ⑤⑥)
|
||||
*/
|
||||
|
||||
export interface ScriptSentence {
|
||||
@@ -16,67 +11,25 @@ export interface ScriptSentence {
|
||||
charCount: number
|
||||
/** 累计起始字数(用于时间估算) */
|
||||
startChar: number
|
||||
/** 对口型视频内起始时间(秒)——后端精确值或前端估算 */
|
||||
/** 估算的对口型视频内起始时间(秒) */
|
||||
startTime: number
|
||||
/** 对口型视频内结束时间(秒)——后端精确值或前端估算 */
|
||||
/** 估算的对口型视频内结束时间(秒) */
|
||||
endTime: number
|
||||
}
|
||||
|
||||
/** 句子分隔符:中英文句号/问号/感叹号/分号/换行(按句断,不在逗号处切;保持与后端一致) */
|
||||
const SENTENCE_SPLIT_RE = /[。!?!??!;;\n\r]+/
|
||||
|
||||
/**
|
||||
* 分句并计算每句的起止时间。
|
||||
*
|
||||
* @param sentenceTimings 后端返回的精确句子时间戳(来自 lipsync_job.sentence_timings)。
|
||||
* 非空时直接按后端返回的句子列表渲染,不再本地分句(避免前后端分句不一致导致时间错位)。
|
||||
* @param outputDuration 最终视频时长(秒)。对口型预览阶段可能为 0,此时降级估算只能给 0。
|
||||
* 按句号/问号/感叹号/分号/换行分句(兼容中英文标点)。
|
||||
* 空文案返回空数组。时间按「该句字数 ÷ 全文总字数 × 口播总时长」线性估算。
|
||||
*/
|
||||
export function splitScriptIntoSentences(
|
||||
scriptText: string,
|
||||
sentenceTimings?:
|
||||
{ index?: number; text?: string; start_time: number; end_time: number }[] | null,
|
||||
outputDuration: number = 0,
|
||||
outputDuration: number,
|
||||
): ScriptSentence[] {
|
||||
const text = (scriptText || "").trim()
|
||||
if (!text) return []
|
||||
|
||||
// 1. 后端返回了 sentence_timings:校验通过就直接用,跳过本地分句
|
||||
// 校验条件放宽:只要是数组、至少1条、每条 start_time/end_time 是数字即可
|
||||
// (不再强制要求条数相等——后端静音检测可能按停顿切出更多/更少边界,
|
||||
// 比如文案用逗号连写时本地只分1句、后端按停顿切4句,后端的切法才是对的)
|
||||
if (Array.isArray(sentenceTimings) && sentenceTimings.length > 0) {
|
||||
const valid = sentenceTimings.every(
|
||||
(t) =>
|
||||
t &&
|
||||
typeof t.start_time === "number" &&
|
||||
typeof t.end_time === "number" &&
|
||||
isFinite(t.start_time) &&
|
||||
isFinite(t.end_time) &&
|
||||
t.end_time >= t.start_time,
|
||||
)
|
||||
if (valid) {
|
||||
let accChar = 0
|
||||
return sentenceTimings.map((t, i) => {
|
||||
const sentenceText = (t.text || "").trim() || `句子${i + 1}`
|
||||
const charCount = sentenceText.replace(/\s/g, "").length
|
||||
const sentence: ScriptSentence = {
|
||||
index: typeof t.index === "number" ? t.index : i,
|
||||
text: sentenceText,
|
||||
charCount,
|
||||
startChar: accChar,
|
||||
startTime: round1(t.start_time),
|
||||
endTime: round1(t.end_time),
|
||||
}
|
||||
accChar += charCount
|
||||
return sentence
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
// 2. 本地分句 + 按字数比例估算(降级路径)
|
||||
const rawParts = text
|
||||
.split(SENTENCE_SPLIT_RE)
|
||||
.split(/[。!?!?;;\n\r]+/)
|
||||
.map((part) => part.trim())
|
||||
.filter((part) => part.length > 0)
|
||||
|
||||
|
||||
@@ -1,179 +0,0 @@
|
||||
/**
|
||||
* AI数字人 — 标题 Canvas 渲染工具
|
||||
*
|
||||
* 把标题按前端预览的 HTML/CSS 效果画到透明背景 PNG 上(与视频同分辨率),
|
||||
* 以 dataURL 形式传给后端,后端用 FFmpeg overlay 直接叠加图层,
|
||||
* 彻底解决前端 HTML/CSS 预览 ≠ FFmpeg drawtext 成片的 WYSIWYG 问题。
|
||||
*
|
||||
* 约定:titleConfig.size 的语义是"720p 基准宽度下的字号(px)",
|
||||
* 按 videoWidth / 720 得到 scale,所有长度类参数乘以 scale,
|
||||
* 保证 1080p / 4K 成片里标题视觉大小与预览一致。
|
||||
*/
|
||||
import type { AiAvatarTitleConfig } from "../types"
|
||||
|
||||
export interface RenderTitlePngOptions {
|
||||
/** 标题配置 */
|
||||
titleConfig: AiAvatarTitleConfig
|
||||
/** 视频宽度(像素),默认 720 */
|
||||
videoWidth?: number
|
||||
/** 视频高度(像素),默认 1280 */
|
||||
videoHeight?: number
|
||||
}
|
||||
|
||||
/**
|
||||
* 将标题渲染为透明背景 PNG 的 dataURL(data:image/png;base64,...)
|
||||
* Canvas 尺寸与视频一致,保证叠加时 1:1 像素对齐。
|
||||
*
|
||||
* 标题为空时返回 null。
|
||||
*/
|
||||
export function renderTitleToPngDataUrl(opts: RenderTitlePngOptions): string | null {
|
||||
const { titleConfig, videoWidth = 720, videoHeight = 1280 } = opts
|
||||
if (!titleConfig) return null
|
||||
const rawTitle = (titleConfig.title || "").trim()
|
||||
if (!rawTitle) return null
|
||||
|
||||
// 按 / 或 / 分割为多行
|
||||
const lines = rawTitle
|
||||
.split(/[//]/)
|
||||
.map((l) => l.trim())
|
||||
.filter((l) => l.length > 0)
|
||||
if (lines.length === 0) return null
|
||||
|
||||
// 分辨率缩放系数:基准 720p,所有长度类参数乘以 scale
|
||||
const scale = videoWidth / 720
|
||||
const r = (v: number) => Math.round(v * scale)
|
||||
|
||||
const canvas = document.createElement("canvas")
|
||||
canvas.width = videoWidth
|
||||
canvas.height = videoHeight
|
||||
const ctx = canvas.getContext("2d")
|
||||
if (!ctx) return null
|
||||
|
||||
const baseSize = Math.max(12, Math.round(titleConfig.size || 48))
|
||||
const size = r(baseSize)
|
||||
const bold = !!titleConfig.bold
|
||||
const italic = !!titleConfig.italic
|
||||
const color = titleConfig.color || "#ffffff"
|
||||
const stroke = !!titleConfig.stroke
|
||||
const shadow = !!titleConfig.shadow
|
||||
|
||||
// 字体族 fallback 链:优先中文字体
|
||||
const fontFamily =
|
||||
'"Noto Sans CJK SC","Source Han Sans CN","PingFang SC","Microsoft YaHei",sans-serif'
|
||||
const fontParts: string[] = []
|
||||
if (italic) fontParts.push("italic")
|
||||
if (bold) fontParts.push("bold")
|
||||
fontParts.push(`${size}px`, fontFamily)
|
||||
ctx.font = fontParts.join(" ")
|
||||
ctx.fillStyle = color
|
||||
ctx.textAlign = "center"
|
||||
ctx.textBaseline = "middle"
|
||||
|
||||
// 阴影(shadow=true 时开启)——按 scale 缩放
|
||||
if (shadow) {
|
||||
ctx.shadowColor = "rgba(0,0,0,0.8)"
|
||||
ctx.shadowBlur = r(4)
|
||||
ctx.shadowOffsetX = 0
|
||||
ctx.shadowOffsetY = r(2)
|
||||
}
|
||||
|
||||
// 位置计算:与 PanelLipsyncPreview 的 CSS 对齐(按 scale 缩放 PAD)
|
||||
const PAD = r(16)
|
||||
let centerX = videoWidth / 2
|
||||
const position = titleConfig.position || "bottom"
|
||||
const lineGap = size * 1.2
|
||||
const totalTextH = lines.length * lineGap - (lineGap - size) // 所有行的总高度
|
||||
// 文本块顶部 y(textBaseline=middle 时首行基线)
|
||||
let firstLineY: number
|
||||
if (
|
||||
position === "custom" &&
|
||||
typeof titleConfig.pos_x === "number" &&
|
||||
typeof titleConfig.pos_y === "number"
|
||||
) {
|
||||
centerX = (Math.max(0, Math.min(100, titleConfig.pos_x)) / 100) * videoWidth
|
||||
const centerY = (Math.max(0, Math.min(100, titleConfig.pos_y)) / 100) * videoHeight
|
||||
firstLineY = centerY - totalTextH / 2 + size / 2
|
||||
} else if (position === "top") {
|
||||
// 顶部:y = size/2 + PAD
|
||||
firstLineY = size / 2 + PAD
|
||||
} else if (position === "center") {
|
||||
firstLineY = videoHeight / 2 - totalTextH / 2 + size / 2
|
||||
} else {
|
||||
// bottom(默认)
|
||||
firstLineY = videoHeight - totalTextH - PAD + size / 2
|
||||
}
|
||||
|
||||
// 描边参数:描边 lineWidth 按 scale 缩放(基准 size * 0.06,最小 2px @720p)
|
||||
const doStroke = stroke
|
||||
const strokeWidth = Math.max(r(2), Math.round(size * 0.06))
|
||||
// 逐行绘制
|
||||
lines.forEach((line, idx) => {
|
||||
const y = firstLineY + idx * lineGap
|
||||
if (doStroke) {
|
||||
const prevShadowColor = ctx.shadowColor
|
||||
const prevShadowBlur = ctx.shadowBlur
|
||||
// 描边不要带阴影(避免黑色描边发虚)
|
||||
ctx.shadowColor = "rgba(0,0,0,0)"
|
||||
ctx.shadowBlur = 0
|
||||
ctx.lineWidth = strokeWidth
|
||||
ctx.strokeStyle = "#000000"
|
||||
ctx.lineJoin = "round"
|
||||
ctx.strokeText(line, centerX, y)
|
||||
// 恢复阴影
|
||||
if (shadow) {
|
||||
ctx.shadowColor = "rgba(0,0,0,0.8)"
|
||||
ctx.shadowBlur = r(4)
|
||||
} else {
|
||||
ctx.shadowColor = prevShadowColor
|
||||
ctx.shadowBlur = prevShadowBlur
|
||||
}
|
||||
}
|
||||
ctx.fillText(line, centerX, y)
|
||||
})
|
||||
|
||||
try {
|
||||
return canvas.toDataURL("image/png")
|
||||
} catch {
|
||||
return null
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取视频真实分辨率(HTMLVideoElement + loadedmetadata,超时 3 秒兜底 720×1280)。
|
||||
*/
|
||||
export function getVideoResolution(
|
||||
videoUrl: string,
|
||||
timeoutMs = 3000,
|
||||
): Promise<{ width: number; height: number }> {
|
||||
return new Promise((resolve) => {
|
||||
if (!videoUrl) {
|
||||
resolve({ width: 720, height: 1280 })
|
||||
return
|
||||
}
|
||||
const video = document.createElement("video")
|
||||
video.preload = "metadata"
|
||||
video.muted = true
|
||||
video.playsInline = true
|
||||
video.crossOrigin = "anonymous"
|
||||
let settled = false
|
||||
const done = (w: number, h: number) => {
|
||||
if (settled) return
|
||||
settled = true
|
||||
video.removeAttribute("src")
|
||||
video.load()
|
||||
resolve({ width: w, height: h })
|
||||
}
|
||||
const timer = window.setTimeout(() => done(720, 1280), timeoutMs)
|
||||
video.onloadedmetadata = () => {
|
||||
window.clearTimeout(timer)
|
||||
const w = video.videoWidth || 720
|
||||
const h = video.videoHeight || 1280
|
||||
done(w, h)
|
||||
}
|
||||
video.onerror = () => {
|
||||
window.clearTimeout(timer)
|
||||
done(720, 1280)
|
||||
}
|
||||
video.src = videoUrl
|
||||
})
|
||||
}
|
||||
@@ -5,7 +5,6 @@
|
||||
import React from "react"
|
||||
import type { ClipData, ClipType } from "../types"
|
||||
import type { TitleConfig } from "@/api/template-editor"
|
||||
import { getFontFamily } from "@/pages/generate/constants"
|
||||
|
||||
interface SubtitleSettings {
|
||||
enabled: boolean
|
||||
@@ -81,7 +80,7 @@ const PreviewPlayer: React.FC<PreviewPlayerProps> = ({
|
||||
className="ep-preview-title"
|
||||
style={{
|
||||
fontSize: `${Math.min(titleConfig.font_size, 20)}px`,
|
||||
fontFamily: getFontFamily(titleConfig.font_preset),
|
||||
fontFamily: titleConfig.font_preset,
|
||||
fontWeight: "bold",
|
||||
fontStyle: "normal",
|
||||
textShadow: "2px 2px 4px rgba(0,0,0,0.5)",
|
||||
@@ -107,7 +106,7 @@ const PreviewPlayer: React.FC<PreviewPlayerProps> = ({
|
||||
className="ep-preview-subtitle"
|
||||
style={{
|
||||
fontSize: `${Math.min(subtitleSettings.size, 14)}px`,
|
||||
fontFamily: getFontFamily(subtitleSettings.font),
|
||||
fontFamily: subtitleSettings.font,
|
||||
top:
|
||||
subtitleSettings.position === "top"
|
||||
? "8px"
|
||||
|
||||
@@ -9,8 +9,15 @@ export const POSITION_OPTIONS = [
|
||||
{ value: "bottom", label: "底部" },
|
||||
]
|
||||
|
||||
// FONT_OPTIONS 统一从 generate/constants 导入,避免多处维护遗漏
|
||||
export { FONT_OPTIONS } from "@/pages/generate/constants"
|
||||
export const FONT_OPTIONS = [
|
||||
"思源黑体",
|
||||
"思源宋体",
|
||||
"苹方",
|
||||
"PingFang",
|
||||
"微软雅黑",
|
||||
"楷体",
|
||||
"华康俪金黑",
|
||||
]
|
||||
|
||||
export const ANIMATION_OPTIONS = [
|
||||
{ value: "none", label: "无" },
|
||||
|
||||
@@ -7,8 +7,15 @@ export const POSITION_OPTIONS = [
|
||||
{ value: "bottom", label: "底部" },
|
||||
]
|
||||
|
||||
// FONT_OPTIONS 统一从 generate/constants 导入
|
||||
export { FONT_OPTIONS } from "@/pages/generate/constants"
|
||||
export const FONT_OPTIONS = [
|
||||
"思源黑体",
|
||||
"思源宋体",
|
||||
"苹方",
|
||||
"PingFang",
|
||||
"微软雅黑",
|
||||
"楷体",
|
||||
"华康俪金黑",
|
||||
]
|
||||
|
||||
export const ANIMATION_OPTIONS = [
|
||||
{ value: "none", label: "无" },
|
||||
|
||||
@@ -231,13 +231,9 @@ const GeneratePage: React.FC = () => {
|
||||
/* ── 批量变体真实片段(#1744):后端独立选片,预览即成片;失败静默降级本地模拟 ──
|
||||
仅批量(N>1)且在第 4 步预览时申请,避免选素材阶段频繁请求;
|
||||
变体 0 沿用草稿 plan(与单视频一致),变体 1..N-1 后端 reselect 独立选片 */
|
||||
// P0 fix:批量变体计划请求需携带配音参数,避免后端按"无配音"选片导致 clips 时长与配音错位
|
||||
const batchVoiceLibraryId =
|
||||
voiceMode === "clone" ? selectedClonedVoice || selectedVoice || "" : selectedVoice || ""
|
||||
const {
|
||||
clipsByVariant: variantClips,
|
||||
planIdsByVariant: variantPlanIds,
|
||||
voiceDurationsByVariant: variantVoiceDurations,
|
||||
loading: variantClipsLoading,
|
||||
error: variantClipsError,
|
||||
retry: retryVariantClips,
|
||||
@@ -247,9 +243,6 @@ const GeneratePage: React.FC = () => {
|
||||
templateId: selectedTemplate || "",
|
||||
assetIds: previewAssetIds,
|
||||
sourcePlanId: storedSourceEditPlanId || sourceEditPlanId || "",
|
||||
voiceLibraryId: batchVoiceLibraryId,
|
||||
voiceLibraryIds: voiceLibraryIds || [],
|
||||
voiceModePerVideo,
|
||||
})
|
||||
|
||||
/* ── 批量变体配音预览 URL(#1750):独立模式每变体挂各自配音,共用模式全挂同一条;
|
||||
@@ -483,7 +476,6 @@ const GeneratePage: React.FC = () => {
|
||||
titles={previewTitles}
|
||||
titleSettings={titleSettings}
|
||||
voiceAudioUrls={variantVoiceAudioUrls}
|
||||
voiceDurations={variantVoiceDurations}
|
||||
variantClips={variantClips}
|
||||
clipsLoading={variantClipsLoading}
|
||||
clipsError={variantClipsError}
|
||||
|
||||
@@ -31,12 +31,6 @@ interface CanvasPreviewGridProps {
|
||||
* 元素为 null 表示该变体暂无音频(AI 音色 TTS 合成中))
|
||||
*/
|
||||
voiceAudioUrls?: (string | null)[]
|
||||
/**
|
||||
* 各变体配音时长(秒):后端返回 voice_duration 优先;未返回则为 undefined,
|
||||
* 由 FrontendPreviewPlayer 在 audio loadedmetadata 时自测兜底。
|
||||
* 长度=count,undefined 项表示该变体未提供后端时长。
|
||||
*/
|
||||
voiceDurations?: (number | undefined)[]
|
||||
/**
|
||||
* 各变体的后端真实片段(#1744/#1750):长度=count。
|
||||
* 仅 clipsLoading=false 且 clipsError=false 时才会传给播放器。
|
||||
@@ -62,7 +56,6 @@ const CanvasPreviewGrid: React.FC<CanvasPreviewGridProps> = ({
|
||||
titles,
|
||||
titleSettings,
|
||||
voiceAudioUrls,
|
||||
voiceDurations,
|
||||
variantClips,
|
||||
clipsLoading = false,
|
||||
clipsError = false,
|
||||
@@ -127,7 +120,6 @@ const CanvasPreviewGrid: React.FC<CanvasPreviewGridProps> = ({
|
||||
serverClips={variantClips[i]}
|
||||
variantTitle={titles[i] || ""}
|
||||
voiceAudioUrl={voiceAudioUrls?.[i] || undefined}
|
||||
voiceDurationHint={voiceDurations?.[i]}
|
||||
activePlayToken={activePlayToken}
|
||||
onPlayTokenChange={setActivePlayToken}
|
||||
compact
|
||||
|
||||
@@ -1,23 +1,25 @@
|
||||
/**
|
||||
* 前端预览播放器 — 原生 Video 元素方案(浏览器硬件解码,独立线程,不阻塞 UI)
|
||||
* 前端预览播放器 — Canvas + WebCodecs 方案
|
||||
*
|
||||
* 架构:
|
||||
* - 默认走原生 video 元素多片段切换播放(useSegmentScheduler 调度),
|
||||
* 叠加标题 CSS 浮层、配音音轨(usePreviewAudio)、尾段冻结看门狗、批量播放互斥 token。
|
||||
* UI 拆分为 PreviewControls(控制条/按钮) + PreviewProgressBar(进度条)两个子组件。
|
||||
* - WebCodecs 路径已废弃(原 useWebCodecs 常量恒为 false,相关死代码已移除),
|
||||
* 保留 useCanvasPlayer hook 文件供未来兜底(不影响当前打包体积)。
|
||||
* - 浏览器支持 WebCodecs → Canvas 渲染(帧级精确控制 + 标题合成)
|
||||
* - 浏览器不支持 → fallback 到多 video 元素方案
|
||||
*
|
||||
* 对外 API 完全不变:assets / videoRatio / ready / voiceAudioUrl / serverClips 等。
|
||||
* 对外 API 不变:assets, template, videoRatio, ready, voiceAudioUrl
|
||||
*/
|
||||
import React, { useMemo, useCallback, useState, useRef, useEffect } from "react"
|
||||
import { PlayCircleOutlined, SoundOutlined } from "@ant-design/icons"
|
||||
import {
|
||||
PlayCircleOutlined,
|
||||
PauseCircleOutlined,
|
||||
SoundOutlined,
|
||||
LoadingOutlined,
|
||||
AudioOutlined,
|
||||
AudioMutedOutlined,
|
||||
} from "@ant-design/icons"
|
||||
import type { AssetItem } from "@/api/assets"
|
||||
import type { EditPlanClip } from "@/api/template-editor"
|
||||
import { useSegmentScheduler, type PlaybackSegment } from "../hooks/useSegmentScheduler"
|
||||
import { usePreviewAudio } from "../hooks/usePreviewAudio"
|
||||
import { PreviewControls } from "./PreviewControls"
|
||||
import { getFontFamily } from "../constants"
|
||||
import { useCanvasPlayer } from "../hooks/useCanvasPlayer"
|
||||
|
||||
interface FrontendPreviewPlayerProps {
|
||||
assets: AssetItem[]
|
||||
@@ -56,11 +58,12 @@ interface FrontendPreviewPlayerProps {
|
||||
activePlayToken?: number | null
|
||||
/** 播放权变化回调:本实例请求播放时传自身 playToken,暂停时传 null */
|
||||
onPlayTokenChange?: (token: number | null) => void
|
||||
/**
|
||||
* 后端返回的配音时长(秒)P0 对齐:优先以该值作为音画时长锚点;
|
||||
* 未提供则在 audio loadedmetadata 后自测兜底。
|
||||
*/
|
||||
voiceDurationHint?: number
|
||||
}
|
||||
|
||||
function formatTime(seconds: number): string {
|
||||
const m = Math.floor(seconds / 60)
|
||||
const s = Math.floor(seconds % 60)
|
||||
return `${m}:${s.toString().padStart(2, "0")}`
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -113,7 +116,6 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
|
||||
ready,
|
||||
serverClips,
|
||||
voiceAudioUrl,
|
||||
voiceDurationHint,
|
||||
titleSettings,
|
||||
onTitlePositionChange,
|
||||
playToken,
|
||||
@@ -122,11 +124,26 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
|
||||
activePlayToken = null,
|
||||
onPlayTokenChange,
|
||||
}) => {
|
||||
// #1754→P0:配音时长作为音画时长锚点。
|
||||
// 优先使用后端返回的 voiceDurationHint;音频 loadedmetadata 后再以自测值覆盖(更精确)。
|
||||
const [voiceDuration, setVoiceDuration] = useState<number>(() =>
|
||||
voiceDurationHint && voiceDurationHint > 0 ? voiceDurationHint : 0,
|
||||
)
|
||||
// #1754:测量配音时长,计算缩放因子
|
||||
const [voiceDuration, setVoiceDuration] = useState(0)
|
||||
useEffect(() => {
|
||||
if (!voiceAudioUrl) {
|
||||
setVoiceDuration(0)
|
||||
return
|
||||
}
|
||||
const audio = new Audio()
|
||||
audio.preload = "metadata"
|
||||
const onLoaded = () => {
|
||||
if (audio.duration && isFinite(audio.duration)) {
|
||||
setVoiceDuration(audio.duration)
|
||||
}
|
||||
}
|
||||
audio.addEventListener("loadedmetadata", onLoaded)
|
||||
audio.src = voiceAudioUrl
|
||||
return () => {
|
||||
audio.removeEventListener("loadedmetadata", onLoaded)
|
||||
}
|
||||
}, [voiceAudioUrl])
|
||||
|
||||
// #1756:clips 原始总时长 + 转场时长(后端等比分配配音时包含转场占位)
|
||||
const rawClipsDuration = useMemo(() => {
|
||||
@@ -172,10 +189,9 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
|
||||
? (titleSettings.posY / playRes.height) * 100
|
||||
: null
|
||||
|
||||
// ── 标题拖拽(用 ref 避免每帧触发 React 重渲染)──
|
||||
// ── 拖拽状态(用 ref 避免在每帧渲染中触发重渲染)──
|
||||
const draggingTitleRef = useRef(false)
|
||||
const titleDragRef = useRef<HTMLDivElement>(null)
|
||||
const playerContainerRef = useRef<HTMLDivElement>(null)
|
||||
const handleTitlePointerDown = useCallback(
|
||||
(e: React.PointerEvent<HTMLDivElement>) => {
|
||||
if (!onTitlePositionChange || !playerContainerRef.current) return
|
||||
@@ -191,6 +207,7 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
|
||||
if (!draggingTitleRef.current || !playerContainerRef.current) return
|
||||
e.preventDefault()
|
||||
e.stopPropagation()
|
||||
// 拖拽过程中直接修改 DOM,不触发 React 渲染(避免频繁重渲染导致换行)
|
||||
if (titleDragRef.current) {
|
||||
const rect = playerContainerRef.current.getBoundingClientRect()
|
||||
const relX = Math.max(0, Math.min(rect.width, e.clientX - rect.left))
|
||||
@@ -205,6 +222,7 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
|
||||
(e: React.PointerEvent<HTMLDivElement>) => {
|
||||
if (!draggingTitleRef.current) return
|
||||
draggingTitleRef.current = false
|
||||
// 拖拽结束时才调用 onTitlePositionChange 保存最终位置
|
||||
if (onTitlePositionChange && playerContainerRef.current) {
|
||||
const rect = playerContainerRef.current.getBoundingClientRect()
|
||||
const relX = Math.max(0, Math.min(rect.width, e.clientX - rect.left))
|
||||
@@ -225,6 +243,7 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
|
||||
[onTitlePositionChange, playRes.width, playRes.height],
|
||||
)
|
||||
|
||||
const playerContainerRef = useRef<HTMLDivElement>(null)
|
||||
const [containerHeight, setContainerHeight] = useState(0)
|
||||
useEffect(() => {
|
||||
const el = playerContainerRef.current
|
||||
@@ -249,157 +268,234 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
|
||||
const titleSidePct = (TITLE_MARGIN_SIDE / playRes.width) * 100
|
||||
const titleTopPct = (TITLE_MARGIN_TOP / playRes.height) * 100
|
||||
const titleBottomPct = (TITLE_MARGIN_BOTTOM / playRes.height) * 100
|
||||
// 描边/阴影也要按缩放比例放大
|
||||
const titleScale = containerHeight > 0 ? containerHeight / playRes.height : 1
|
||||
const titleStrokeWidth = Math.max(1, 2 * titleScale)
|
||||
const titleShadowBlur = 4 * titleScale
|
||||
const titleShadowOffset = 2 * titleScale
|
||||
|
||||
// ── Video 播放器(默认路径,浏览器原生硬件解码) ──
|
||||
// 默认走原生 video 播放(浏览器硬件解码,独立线程,不阻塞 UI)
|
||||
// WebCodecs 仅在明确需要时启用(保留代码作为兜底)
|
||||
const useWebCodecs = false
|
||||
|
||||
// ── 两条路径共用同一个 canvas ref(fallback 路径不使用) ──
|
||||
const canvasRef = useRef<HTMLCanvasElement>(null)
|
||||
|
||||
// ── Canvas 播放器(WebCodecs 路径) ──
|
||||
const canvasTitle = titleSettings
|
||||
? {
|
||||
text: effectiveTitle || "标题预览",
|
||||
fontSize: titleSettings.size,
|
||||
fontFamily: titleSettings.font || "思源黑体",
|
||||
color: titleSettings.color || "#ffffff",
|
||||
position: titleSettings.position || "top",
|
||||
bold: titleSettings.bold,
|
||||
stroke: titleSettings.stroke,
|
||||
shadow: titleSettings.shadow,
|
||||
}
|
||||
: undefined
|
||||
|
||||
const canvasSegments = useMemo(
|
||||
() =>
|
||||
segments.map((s) => ({
|
||||
assetId: s.assetId,
|
||||
videoUrl: s.videoUrl,
|
||||
startTime: s.startTime,
|
||||
endTime: s.endTime,
|
||||
})),
|
||||
[segments],
|
||||
)
|
||||
|
||||
// WebCodecs 解码失败后强制走 video fallback
|
||||
const [forceVideoFallback, setForceVideoFallback] = useState(false)
|
||||
|
||||
const handleCanvasError = useCallback((err: Error) => {
|
||||
console.error("[FrontendPreviewPlayer] Canvas decode Error, switching to video fallback:", err)
|
||||
setForceVideoFallback(true)
|
||||
}, [])
|
||||
|
||||
const { state: canvasState, controls: canvasControls } = useCanvasPlayer(
|
||||
canvasRef,
|
||||
useWebCodecs && !forceVideoFallback ? canvasSegments : [],
|
||||
useWebCodecs && !forceVideoFallback ? canvasTitle : undefined,
|
||||
handleCanvasError,
|
||||
useWebCodecs && !forceVideoFallback,
|
||||
)
|
||||
|
||||
// WebCodecs 报告解码失败时自动切换到 video fallback
|
||||
useEffect(() => {
|
||||
if (canvasState.hasDecodeError && !forceVideoFallback) {
|
||||
console.warn("[FrontendPreviewPlayer] hasDecodeError detected, forcing video fallback")
|
||||
setForceVideoFallback(true)
|
||||
}
|
||||
}, [canvasState.hasDecodeError, forceVideoFallback])
|
||||
|
||||
// ── Video 播放器(fallback 路径) ──
|
||||
const {
|
||||
isPlaying,
|
||||
currentTime,
|
||||
totalDuration,
|
||||
currentSegmentIndex,
|
||||
canPlay,
|
||||
togglePlayPause,
|
||||
seekTo,
|
||||
pause,
|
||||
isPlaying: videoIsPlaying,
|
||||
currentTime: videoCurrentTime,
|
||||
totalDuration: videoTotalDuration,
|
||||
currentSegmentIndex: videoCurrentSegIdx,
|
||||
canPlay: videoCanPlay,
|
||||
togglePlayPause: videoTogglePlayPause,
|
||||
seekTo: videoSeekTo,
|
||||
pause: videoPause,
|
||||
videoRefs,
|
||||
} = useSegmentScheduler(segments)
|
||||
|
||||
// P0 fix:以配音时长为音画同步锚点。
|
||||
// 有配音时总时长 = 配音时长(短则末帧冻结,长则硬停);无配音时沿用视频总时长(素材原声兜底)。
|
||||
const effectiveTotalDuration =
|
||||
!!voiceAudioUrl && voiceDuration > 0 ? voiceDuration : totalDuration
|
||||
// 选择哪条路径的状态(WebCodecs 解码失败时强制走 video fallback)
|
||||
const effectiveUseWebCodecs = useWebCodecs && !forceVideoFallback
|
||||
const isPlaying = effectiveUseWebCodecs ? canvasState.isPlaying : videoIsPlaying
|
||||
const currentTime = effectiveUseWebCodecs ? canvasState.currentTime : videoCurrentTime
|
||||
const totalDuration = effectiveUseWebCodecs ? canvasState.duration : videoTotalDuration
|
||||
const canPlay = effectiveUseWebCodecs ? canvasState.isReady : videoCanPlay
|
||||
const isBuffering = effectiveUseWebCodecs ? canvasState.isBuffering : false
|
||||
|
||||
// ── 配音音频同步 ──
|
||||
const audioRef = useRef<HTMLAudioElement | null>(null)
|
||||
const prevIsPlayingRef = useRef(false)
|
||||
// 本卡片静音开关(#1741):默认有声,用户可点喇叭单独静音某张卡片
|
||||
const [muted, setMuted] = useState(false)
|
||||
// 有配音时 video 素材保持静音(避免原声与配音混音);无配音时取消静音,素材原声兜底
|
||||
const hasVoice = !!voiceAudioUrl
|
||||
|
||||
// 音频 ended:兜底触发暂停与释放播放权
|
||||
const handleAudioEnded = useCallback(() => {
|
||||
if (!isPlaying) return
|
||||
pause()
|
||||
if (playToken != null) onPlayTokenChange?.(null)
|
||||
}, [isPlaying, pause, playToken, onPlayTokenChange])
|
||||
|
||||
const {
|
||||
seekTo: audioSeekTo,
|
||||
ensurePlayingAt: audioEnsurePlayingAt,
|
||||
pause: audioPause,
|
||||
} = usePreviewAudio({
|
||||
voiceAudioUrl,
|
||||
voiceDurationHint,
|
||||
muted,
|
||||
isPlaying,
|
||||
currentTime,
|
||||
onVoiceDurationChange: setVoiceDuration,
|
||||
onEnded: handleAudioEnded,
|
||||
})
|
||||
|
||||
// 片段切换时同步音频时间(video fallback)
|
||||
useEffect(() => {
|
||||
if (!isPlaying) return
|
||||
audioSeekTo(currentTime)
|
||||
// 注意:不要把 currentTime 放进依赖数组,否则每200ms会重置音频位置导致卡顿
|
||||
// eslint-disable-next-line react-hooks/exhaustive-deps
|
||||
}, [currentSegmentIndex, isPlaying])
|
||||
|
||||
// P0 fix:视频比配音短时的「末帧冻结+音频续播」模式。
|
||||
// 视频调度器播完最后一段自动 pause,此时若配音仍在播,用 rAF 虚拟时钟推进 currentTime 直到配音结束。
|
||||
const [tailCurrentTime, setTailCurrentTime] = useState<number | null>(null)
|
||||
const tailStartRef = useRef<number>(0)
|
||||
const tailBaseRef = useRef<number>(0)
|
||||
const tailAudioRef = useRef({ ensurePlayingAt: audioEnsurePlayingAt, pause: audioPause })
|
||||
tailAudioRef.current = { ensurePlayingAt: audioEnsurePlayingAt, pause: audioPause }
|
||||
|
||||
useEffect(() => {
|
||||
const needTail =
|
||||
!!voiceAudioUrl &&
|
||||
voiceDuration > 0 &&
|
||||
!isPlaying &&
|
||||
typeof currentTime === "number" &&
|
||||
currentTime >= totalDuration - 0.1 &&
|
||||
currentTime < voiceDuration - 0.1
|
||||
if (needTail && tailCurrentTime === null) {
|
||||
tailBaseRef.current = currentTime
|
||||
tailStartRef.current = performance.now()
|
||||
setTailCurrentTime(currentTime)
|
||||
tailAudioRef.current.ensurePlayingAt(currentTime)
|
||||
if (!voiceAudioUrl) {
|
||||
if (audioRef.current) {
|
||||
audioRef.current.pause()
|
||||
audioRef.current.src = ""
|
||||
audioRef.current = null
|
||||
}
|
||||
return
|
||||
}
|
||||
if (!needTail && tailCurrentTime !== null) {
|
||||
setTailCurrentTime(null)
|
||||
if (!audioRef.current) {
|
||||
audioRef.current = new Audio()
|
||||
audioRef.current.preload = "auto"
|
||||
}
|
||||
}, [isPlaying, currentTime, totalDuration, voiceDuration, voiceAudioUrl, tailCurrentTime])
|
||||
if (audioRef.current.src !== voiceAudioUrl) {
|
||||
audioRef.current.src = voiceAudioUrl
|
||||
}
|
||||
audioRef.current.muted = muted
|
||||
}, [voiceAudioUrl, muted])
|
||||
|
||||
useEffect(() => {
|
||||
if (tailCurrentTime === null) return
|
||||
let raf = 0
|
||||
const tick = () => {
|
||||
const elapsed = (performance.now() - tailStartRef.current) / 1000
|
||||
const t = Math.min(tailBaseRef.current + elapsed, voiceDuration || tailBaseRef.current)
|
||||
setTailCurrentTime(t)
|
||||
tailAudioRef.current.ensurePlayingAt(t)
|
||||
if (t >= (voiceDuration || 0) - 0.05) {
|
||||
tailAudioRef.current.pause()
|
||||
if (playToken != null) onPlayTokenChange?.(null)
|
||||
setTailCurrentTime(null)
|
||||
return
|
||||
}
|
||||
raf = requestAnimationFrame(tick)
|
||||
const audio = audioRef.current
|
||||
if (!audio || !audio.src) return
|
||||
if (isPlaying && !prevIsPlayingRef.current) {
|
||||
audio.currentTime = currentTime
|
||||
audio.play().catch(() => {})
|
||||
} else if (!isPlaying && prevIsPlayingRef.current) {
|
||||
audio.pause()
|
||||
}
|
||||
raf = requestAnimationFrame(tick)
|
||||
return () => cancelAnimationFrame(raf)
|
||||
}, [tailCurrentTime, voiceDuration, playToken, onPlayTokenChange])
|
||||
prevIsPlayingRef.current = isPlaying
|
||||
}, [isPlaying, currentTime])
|
||||
|
||||
// 呈现给 UI/进度条的「当前时间」:尾段用虚拟时间,否则用视频时间
|
||||
const displayCurrentTime = tailCurrentTime !== null ? tailCurrentTime : currentTime
|
||||
// 片段切换时同步音频(仅 fallback 路径需要)
|
||||
const segmentSyncKey = effectiveUseWebCodecs ? -1 : videoCurrentSegIdx
|
||||
useEffect(() => {
|
||||
const audio = audioRef.current
|
||||
if (!audio || !audio.src || !isPlaying) return
|
||||
audio.currentTime = currentTime
|
||||
// 注意:不要把 currentTime 放进依赖数组,否则每200ms会重置音频位置导致卡顿
|
||||
// eslint-disable-next-line react-hooks/exhaustive-deps
|
||||
}, [segmentSyncKey, isPlaying])
|
||||
|
||||
const handleSeekTo = useCallback(
|
||||
(time: number) => {
|
||||
setTailCurrentTime(null)
|
||||
seekTo(time)
|
||||
audioSeekTo(time)
|
||||
if (effectiveUseWebCodecs) {
|
||||
canvasControls.seek(time)
|
||||
} else {
|
||||
videoSeekTo(time)
|
||||
}
|
||||
const audio = audioRef.current
|
||||
if (audio && audio.src) {
|
||||
audio.currentTime = time
|
||||
}
|
||||
},
|
||||
[seekTo, audioSeekTo],
|
||||
[effectiveUseWebCodecs, canvasControls, videoSeekTo],
|
||||
)
|
||||
|
||||
// ── 批量网格播放互斥(#1741):播放权属于其他实例时,本实例自动暂停 ──
|
||||
// ── 批量网格播放互斥(#1741):播放权属于其他实例时,本实例自动暂停(视频+配音) ──
|
||||
useEffect(() => {
|
||||
if (activePlayToken == null || playToken == null || activePlayToken === playToken) return
|
||||
if (isPlaying) {
|
||||
pause()
|
||||
if (effectiveUseWebCodecs) {
|
||||
if (canvasState.isPlaying) canvasControls.pause()
|
||||
} else if (isPlaying) {
|
||||
videoPause()
|
||||
}
|
||||
// isPlaying 不放依赖:只在 token 变化时执行一次暂停
|
||||
// isPlaying/canvasState.isPlaying 不放依赖:只在 token 变化时执行一次暂停,
|
||||
// token 等于自身时本实例的播放在 handleTogglePlay 里处理
|
||||
// eslint-disable-next-line react-hooks/exhaustive-deps
|
||||
}, [activePlayToken, playToken])
|
||||
}, [activePlayToken, playToken, effectiveUseWebCodecs])
|
||||
|
||||
const handleTogglePlay = useCallback(() => {
|
||||
if (playToken != null) onPlayTokenChange?.(isPlaying ? null : playToken)
|
||||
togglePlayPause()
|
||||
}, [togglePlayPause, isPlaying, playToken, onPlayTokenChange])
|
||||
|
||||
// P0 fix:音画同步看门狗——有配音时播放时间达到配音时长立即暂停视频+音频(末帧冻结)
|
||||
useEffect(() => {
|
||||
if (!isPlaying) return
|
||||
if (!voiceAudioUrl || voiceDuration <= 0) return
|
||||
if (displayCurrentTime < voiceDuration - 0.08) return
|
||||
pause()
|
||||
audioPause()
|
||||
if (playToken != null) onPlayTokenChange?.(null)
|
||||
if (effectiveUseWebCodecs) {
|
||||
if (canvasState.isPlaying) {
|
||||
canvasControls.pause()
|
||||
onPlayTokenChange?.(null)
|
||||
} else {
|
||||
if (playToken != null) onPlayTokenChange?.(playToken)
|
||||
canvasControls.play()
|
||||
}
|
||||
} else {
|
||||
// video fallback:先上报播放权(暂停其他卡片),再切换本卡片播放/暂停
|
||||
if (playToken != null) onPlayTokenChange?.(isPlaying ? null : playToken)
|
||||
videoTogglePlayPause()
|
||||
}
|
||||
}, [
|
||||
effectiveUseWebCodecs,
|
||||
canvasState.isPlaying,
|
||||
canvasControls,
|
||||
videoTogglePlayPause,
|
||||
isPlaying,
|
||||
displayCurrentTime,
|
||||
voiceAudioUrl,
|
||||
voiceDuration,
|
||||
pause,
|
||||
audioPause,
|
||||
playToken,
|
||||
onPlayTokenChange,
|
||||
])
|
||||
|
||||
// ── 进度条拖拽 ──
|
||||
const [isDragging, setIsDragging] = useState(false)
|
||||
const progressRef = useRef<HTMLDivElement>(null)
|
||||
|
||||
const handleProgressClick = useCallback(
|
||||
(e: React.MouseEvent<HTMLDivElement>) => {
|
||||
if (!progressRef.current || totalDuration <= 0) return
|
||||
const rect = progressRef.current.getBoundingClientRect()
|
||||
const ratio = Math.max(0, Math.min(1, (e.clientX - rect.left) / rect.width))
|
||||
handleSeekTo(ratio * totalDuration)
|
||||
},
|
||||
[totalDuration, handleSeekTo],
|
||||
)
|
||||
|
||||
const handleMouseDown = useCallback(
|
||||
(e: React.MouseEvent<HTMLDivElement>) => {
|
||||
setIsDragging(true)
|
||||
handleProgressClick(e)
|
||||
},
|
||||
[handleProgressClick],
|
||||
)
|
||||
|
||||
useEffect(() => {
|
||||
if (!isDragging) return
|
||||
const handleMouseMove = (e: MouseEvent) => {
|
||||
if (!progressRef.current || totalDuration <= 0) return
|
||||
const rect = progressRef.current.getBoundingClientRect()
|
||||
const ratio = Math.max(0, Math.min(1, (e.clientX - rect.left) / rect.width))
|
||||
handleSeekTo(ratio * totalDuration)
|
||||
}
|
||||
const handleMouseUp = () => setIsDragging(false)
|
||||
window.addEventListener("mousemove", handleMouseMove)
|
||||
window.addEventListener("mouseup", handleMouseUp)
|
||||
return () => {
|
||||
window.removeEventListener("mousemove", handleMouseMove)
|
||||
window.removeEventListener("mouseup", handleMouseUp)
|
||||
}
|
||||
}, [isDragging, totalDuration, handleSeekTo])
|
||||
|
||||
const progressPercent = totalDuration > 0 ? (currentTime / totalDuration) * 100 : 0
|
||||
|
||||
// ── Canvas 容器 ref(保留声明,WebCodecs 兜底路径仍引用) ──
|
||||
const canvasContainerRef = useRef<HTMLDivElement>(null)
|
||||
|
||||
// ── 未就绪 ──
|
||||
if (!ready || !assets.length) {
|
||||
return (
|
||||
@@ -433,6 +529,7 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
|
||||
|
||||
// ── 无播放片段 ──
|
||||
if (!canPlay) {
|
||||
const showDecodeError = forceVideoFallback && canvasState.hasDecodeError
|
||||
return (
|
||||
<div
|
||||
style={{
|
||||
@@ -452,15 +549,48 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
|
||||
padding: 24,
|
||||
}}
|
||||
>
|
||||
<PlayCircleOutlined
|
||||
style={{ fontSize: 40, color: "rgba(255,255,255,0.3)", marginBottom: 12 }}
|
||||
/>
|
||||
<p style={{ color: "rgba(255,255,255,0.6)", fontSize: 14, margin: "0 0 4px" }}>
|
||||
暂无可播放素材
|
||||
</p>
|
||||
<p style={{ color: "rgba(255,255,255,0.35)", fontSize: 12, margin: 0 }}>
|
||||
请先在左侧选择素材
|
||||
</p>
|
||||
{isBuffering ? (
|
||||
<>
|
||||
<LoadingOutlined style={{ fontSize: 40, color: "#fff", marginBottom: 12 }} spin />
|
||||
<p style={{ color: "rgba(255,255,255,0.8)", fontSize: 14, margin: 0 }}>加载中...</p>
|
||||
</>
|
||||
) : showDecodeError ? (
|
||||
<>
|
||||
<PlayCircleOutlined style={{ fontSize: 40, color: "#ef4444", marginBottom: 12 }} />
|
||||
<p
|
||||
style={{
|
||||
color: "rgba(255,255,255,0.9)",
|
||||
fontSize: 14,
|
||||
margin: "0 0 4px",
|
||||
fontWeight: 500,
|
||||
}}
|
||||
>
|
||||
视频解码失败
|
||||
</p>
|
||||
<p
|
||||
style={{
|
||||
color: "rgba(255,255,255,0.5)",
|
||||
fontSize: 12,
|
||||
margin: 0,
|
||||
textAlign: "center",
|
||||
}}
|
||||
>
|
||||
{canvasState.errorMessage || "当前浏览器不支持该视频编码格式,请刷新重试"}
|
||||
</p>
|
||||
</>
|
||||
) : (
|
||||
<>
|
||||
<PlayCircleOutlined
|
||||
style={{ fontSize: 40, color: "rgba(255,255,255,0.3)", marginBottom: 12 }}
|
||||
/>
|
||||
<p style={{ color: "rgba(255,255,255,0.6)", fontSize: 14, margin: "0 0 4px" }}>
|
||||
暂无可播放素材
|
||||
</p>
|
||||
<p style={{ color: "rgba(255,255,255,0.35)", fontSize: 12, margin: 0 }}>
|
||||
请先在左侧选择素材
|
||||
</p>
|
||||
</>
|
||||
)}
|
||||
</div>
|
||||
)
|
||||
}
|
||||
@@ -482,30 +612,53 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
|
||||
: "0 4px 6px -1px rgba(0,0,0,0.3), 0 20px 50px -12px rgba(0,0,0,0.5), inset 0 0 0 1px rgba(255,255,255,0.06)",
|
||||
}}
|
||||
>
|
||||
{/* ── Video 渲染层(默认路径,浏览器原生硬件解码) ── */}
|
||||
{segments.map((seg, i) => (
|
||||
<video
|
||||
key={seg.assetId}
|
||||
ref={(el) => {
|
||||
videoRefs.current[i] = el
|
||||
}}
|
||||
preload="auto"
|
||||
src={seg.videoUrl}
|
||||
{/* ── Canvas 渲染层(WebCodecs 路径) ── */}
|
||||
{effectiveUseWebCodecs && (
|
||||
<div
|
||||
ref={canvasContainerRef}
|
||||
style={{
|
||||
position: "absolute",
|
||||
inset: 0,
|
||||
width: "100%",
|
||||
height: "100%",
|
||||
objectFit: "cover",
|
||||
background: "#000",
|
||||
zIndex: 1,
|
||||
opacity: i === currentSegmentIndex ? 1 : 0,
|
||||
pointerEvents: i === currentSegmentIndex ? "auto" : "none",
|
||||
background: "#000",
|
||||
}}
|
||||
muted={hasVoice || muted}
|
||||
playsInline
|
||||
/>
|
||||
))}
|
||||
>
|
||||
<canvas
|
||||
ref={canvasRef}
|
||||
style={{
|
||||
width: "100%",
|
||||
height: "100%",
|
||||
objectFit: "cover",
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* ── Video 渲染层(默认路径,浏览器原生硬件解码) ── */}
|
||||
{!effectiveUseWebCodecs &&
|
||||
segments.map((seg, i) => (
|
||||
<video
|
||||
key={seg.assetId}
|
||||
muted={hasVoice || muted}
|
||||
ref={(el) => {
|
||||
videoRefs.current[i] = el
|
||||
}}
|
||||
preload="auto"
|
||||
src={seg.videoUrl}
|
||||
style={{
|
||||
position: "absolute",
|
||||
inset: 0,
|
||||
width: "100%",
|
||||
height: "100%",
|
||||
objectFit: "cover",
|
||||
background: "#000",
|
||||
zIndex: 1,
|
||||
opacity: i === videoCurrentSegIdx ? 1 : 0,
|
||||
pointerEvents: i === videoCurrentSegIdx ? "auto" : "none",
|
||||
}}
|
||||
playsInline
|
||||
/>
|
||||
))}
|
||||
|
||||
{/* 标题CSS叠加层 — 与后端 ASS 烧录坐标系 1:1 对齐 */}
|
||||
{titleSettings?.title && (
|
||||
@@ -557,7 +710,7 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
|
||||
<span
|
||||
style={{
|
||||
fontSize: `${titleFontSizePx}px`,
|
||||
fontFamily: getFontFamily(titleSettings.font || "思源黑体"),
|
||||
fontFamily: titleSettings.font || "思源黑体",
|
||||
color: titleSettings.color || "#ffffff",
|
||||
fontWeight: titleSettings.bold ? 700 : 400,
|
||||
fontStyle: titleSettings.italic ? "italic" : "normal",
|
||||
@@ -582,19 +735,200 @@ const FrontendPreviewPlayer: React.FC<FrontendPreviewPlayerProps> = ({
|
||||
</div>
|
||||
)}
|
||||
|
||||
<PreviewControls
|
||||
isPlaying={isPlaying}
|
||||
onTogglePlay={handleTogglePlay}
|
||||
muted={muted}
|
||||
onToggleMute={() => setMuted((m) => !m)}
|
||||
hasSegments={segments.length > 0}
|
||||
segmentIndex={currentSegmentIndex}
|
||||
segmentCount={segments.length}
|
||||
currentTime={displayCurrentTime}
|
||||
totalDuration={effectiveTotalDuration}
|
||||
onSeek={handleSeekTo}
|
||||
compact={compact}
|
||||
/>
|
||||
{/* 中央播放按钮 */}
|
||||
{!isPlaying && (
|
||||
<button
|
||||
onClick={handleTogglePlay}
|
||||
style={{
|
||||
position: "absolute",
|
||||
top: "50%",
|
||||
left: "50%",
|
||||
transform: "translate(-50%, -50%)",
|
||||
background: "rgba(0,0,0,0.45)",
|
||||
backdropFilter: "blur(12px)",
|
||||
WebkitBackdropFilter: "blur(12px)",
|
||||
border: "1px solid rgba(255,255,255,0.15)",
|
||||
borderRadius: "50%",
|
||||
width: 52,
|
||||
height: 52,
|
||||
cursor: "pointer",
|
||||
display: "flex",
|
||||
alignItems: "center",
|
||||
justifyContent: "center",
|
||||
color: "#fff",
|
||||
fontSize: 26,
|
||||
zIndex: 10,
|
||||
transition: "transform 0.2s ease, background 0.2s ease",
|
||||
boxShadow: "0 4px 20px rgba(0,0,0,0.4)",
|
||||
}}
|
||||
onMouseEnter={(e) => {
|
||||
e.currentTarget.style.transform = "translate(-50%, -50%) scale(1.08)"
|
||||
e.currentTarget.style.background = "rgba(0,0,0,0.6)"
|
||||
}}
|
||||
onMouseLeave={(e) => {
|
||||
e.currentTarget.style.transform = "translate(-50%, -50%) scale(1)"
|
||||
e.currentTarget.style.background = "rgba(0,0,0,0.45)"
|
||||
}}
|
||||
>
|
||||
<PlayCircleOutlined />
|
||||
</button>
|
||||
)}
|
||||
|
||||
{/* 静音/有声切换(#1741):左上角,默认有声;批量与单视频均可单独静音 */}
|
||||
{segments.length > 0 && (
|
||||
<button
|
||||
type="button"
|
||||
aria-label={muted ? "取消静音" : "静音"}
|
||||
title={muted ? "取消静音" : "静音"}
|
||||
onClick={() => setMuted((m) => !m)}
|
||||
style={{
|
||||
position: "absolute",
|
||||
top: 8,
|
||||
left: 8,
|
||||
width: compact ? 26 : 30,
|
||||
height: compact ? 26 : 30,
|
||||
display: "flex",
|
||||
alignItems: "center",
|
||||
justifyContent: "center",
|
||||
background: "rgba(0,0,0,0.45)",
|
||||
backdropFilter: "blur(8px)",
|
||||
WebkitBackdropFilter: "blur(8px)",
|
||||
border: "1px solid rgba(255,255,255,0.1)",
|
||||
borderRadius: "50%",
|
||||
color: muted ? "rgba(255,255,255,0.45)" : "rgba(255,255,255,0.92)",
|
||||
fontSize: compact ? 13 : 15,
|
||||
cursor: "pointer",
|
||||
zIndex: 10,
|
||||
padding: 0,
|
||||
transition: "background 0.15s, color 0.15s",
|
||||
}}
|
||||
onMouseEnter={(e) => {
|
||||
e.currentTarget.style.background = "rgba(0,0,0,0.65)"
|
||||
}}
|
||||
onMouseLeave={(e) => {
|
||||
e.currentTarget.style.background = "rgba(0,0,0,0.45)"
|
||||
}}
|
||||
>
|
||||
{muted ? <AudioMutedOutlined /> : <AudioOutlined />}
|
||||
</button>
|
||||
)}
|
||||
|
||||
{/* 片段指示器 — 右上角胶囊 */}
|
||||
<div
|
||||
style={{
|
||||
position: "absolute",
|
||||
top: 8,
|
||||
right: 8,
|
||||
background: "rgba(0,0,0,0.45)",
|
||||
backdropFilter: "blur(8px)",
|
||||
WebkitBackdropFilter: "blur(8px)",
|
||||
color: "rgba(255,255,255,0.9)",
|
||||
fontSize: compact ? 9 : 10,
|
||||
fontWeight: 500,
|
||||
padding: compact ? "1px 6px" : "2px 8px",
|
||||
borderRadius: 999,
|
||||
zIndex: 10,
|
||||
border: "1px solid rgba(255,255,255,0.1)",
|
||||
letterSpacing: 0.3,
|
||||
}}
|
||||
>
|
||||
{`${videoCurrentSegIdx + 1} / ${segments.length}`}
|
||||
</div>
|
||||
|
||||
{/* 控制条 — 手机风格毛玻璃 */}
|
||||
<div
|
||||
style={{
|
||||
position: "absolute",
|
||||
bottom: 0,
|
||||
left: 0,
|
||||
right: 0,
|
||||
display: "flex",
|
||||
alignItems: "center",
|
||||
gap: compact ? 6 : 10,
|
||||
padding: compact ? "8px 10px 10px" : "12px 16px 16px",
|
||||
background: "linear-gradient(transparent, rgba(0,0,0,0.7))",
|
||||
backdropFilter: "blur(4px)",
|
||||
WebkitBackdropFilter: "blur(4px)",
|
||||
zIndex: 10,
|
||||
}}
|
||||
>
|
||||
<button
|
||||
onClick={handleTogglePlay}
|
||||
style={{
|
||||
background: "rgba(255,255,255,0.15)",
|
||||
border: "none",
|
||||
color: "#fff",
|
||||
fontSize: compact ? 14 : 16,
|
||||
cursor: "pointer",
|
||||
width: compact ? 26 : 32,
|
||||
height: compact ? 26 : 32,
|
||||
borderRadius: "50%",
|
||||
display: "flex",
|
||||
alignItems: "center",
|
||||
justifyContent: "center",
|
||||
flexShrink: 0,
|
||||
transition: "background 0.15s",
|
||||
}}
|
||||
onMouseEnter={(e) => {
|
||||
e.currentTarget.style.background = "rgba(255,255,255,0.25)"
|
||||
}}
|
||||
onMouseLeave={(e) => {
|
||||
e.currentTarget.style.background = "rgba(255,255,255,0.15)"
|
||||
}}
|
||||
>
|
||||
{isPlaying ? <PauseCircleOutlined /> : <PlayCircleOutlined />}
|
||||
</button>
|
||||
|
||||
<span
|
||||
style={{
|
||||
fontSize: compact ? 10 : 11,
|
||||
color: "rgba(255,255,255,0.85)",
|
||||
minWidth: compact ? 58 : 72,
|
||||
fontVariantNumeric: "tabular-nums",
|
||||
letterSpacing: 0.2,
|
||||
}}
|
||||
>
|
||||
{formatTime(currentTime)} / {formatTime(totalDuration)}
|
||||
</span>
|
||||
|
||||
<div
|
||||
ref={progressRef}
|
||||
onMouseDown={handleMouseDown}
|
||||
style={{
|
||||
flex: 1,
|
||||
height: 3,
|
||||
background: "rgba(255,255,255,0.2)",
|
||||
borderRadius: 2,
|
||||
cursor: "pointer",
|
||||
position: "relative",
|
||||
}}
|
||||
>
|
||||
<div
|
||||
style={{
|
||||
height: "100%",
|
||||
width: `${progressPercent}%`,
|
||||
background: "#fff",
|
||||
borderRadius: 2,
|
||||
transition: isDragging ? "none" : "width 0.1s linear",
|
||||
}}
|
||||
/>
|
||||
<div
|
||||
style={{
|
||||
position: "absolute",
|
||||
top: "50%",
|
||||
left: `${progressPercent}%`,
|
||||
transform: "translate(-50%, -50%)",
|
||||
width: 10,
|
||||
height: 10,
|
||||
borderRadius: "50%",
|
||||
background: "#fff",
|
||||
boxShadow: "0 0 6px rgba(255,255,255,0.5)",
|
||||
opacity: isDragging ? 1 : 0,
|
||||
transition: "opacity 0.15s",
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
@@ -1,195 +0,0 @@
|
||||
import React from "react"
|
||||
import {
|
||||
PlayCircleOutlined,
|
||||
PauseCircleOutlined,
|
||||
AudioOutlined,
|
||||
AudioMutedOutlined,
|
||||
} from "@ant-design/icons"
|
||||
import { PreviewProgressBar } from "./PreviewProgressBar"
|
||||
|
||||
interface PreviewControlsProps {
|
||||
isPlaying: boolean
|
||||
onTogglePlay: () => void
|
||||
muted: boolean
|
||||
onToggleMute: () => void
|
||||
hasSegments: boolean
|
||||
segmentIndex: number
|
||||
segmentCount: number
|
||||
currentTime: number
|
||||
totalDuration: number
|
||||
onSeek: (time: number) => void
|
||||
compact?: boolean
|
||||
}
|
||||
|
||||
/**
|
||||
* 播放控制 UI 组件(静音按钮 / 片段指示器 / 中央播放按钮 / 底部毛玻璃控制条)
|
||||
*/
|
||||
export const PreviewControls: React.FC<PreviewControlsProps> = ({
|
||||
isPlaying,
|
||||
onTogglePlay,
|
||||
muted,
|
||||
onToggleMute,
|
||||
hasSegments,
|
||||
segmentIndex,
|
||||
segmentCount,
|
||||
currentTime,
|
||||
totalDuration,
|
||||
onSeek,
|
||||
compact = false,
|
||||
}) => {
|
||||
return (
|
||||
<>
|
||||
{/* 静音/有声切换(#1741):左上角 */}
|
||||
{hasSegments && (
|
||||
<button
|
||||
type="button"
|
||||
aria-label={muted ? "取消静音" : "静音"}
|
||||
title={muted ? "取消静音" : "静音"}
|
||||
onClick={onToggleMute}
|
||||
style={{
|
||||
position: "absolute",
|
||||
top: 8,
|
||||
left: 8,
|
||||
width: compact ? 26 : 30,
|
||||
height: compact ? 26 : 30,
|
||||
display: "flex",
|
||||
alignItems: "center",
|
||||
justifyContent: "center",
|
||||
background: "rgba(0,0,0,0.45)",
|
||||
backdropFilter: "blur(8px)",
|
||||
WebkitBackdropFilter: "blur(8px)",
|
||||
border: "1px solid rgba(255,255,255,0.1)",
|
||||
borderRadius: "50%",
|
||||
color: muted ? "rgba(255,255,255,0.45)" : "rgba(255,255,255,0.92)",
|
||||
fontSize: compact ? 13 : 15,
|
||||
cursor: "pointer",
|
||||
zIndex: 10,
|
||||
padding: 0,
|
||||
transition: "background 0.15s, color 0.15s",
|
||||
}}
|
||||
onMouseEnter={(e) => {
|
||||
e.currentTarget.style.background = "rgba(0,0,0,0.65)"
|
||||
}}
|
||||
onMouseLeave={(e) => {
|
||||
e.currentTarget.style.background = "rgba(0,0,0,0.45)"
|
||||
}}
|
||||
>
|
||||
{muted ? <AudioMutedOutlined /> : <AudioOutlined />}
|
||||
</button>
|
||||
)}
|
||||
|
||||
{/* 片段指示器 — 右上角胶囊 */}
|
||||
<div
|
||||
style={{
|
||||
position: "absolute",
|
||||
top: 8,
|
||||
right: 8,
|
||||
background: "rgba(0,0,0,0.45)",
|
||||
backdropFilter: "blur(8px)",
|
||||
WebkitBackdropFilter: "blur(8px)",
|
||||
color: "rgba(255,255,255,0.9)",
|
||||
fontSize: compact ? 9 : 10,
|
||||
fontWeight: 500,
|
||||
padding: compact ? "1px 6px" : "2px 8px",
|
||||
borderRadius: 999,
|
||||
zIndex: 10,
|
||||
border: "1px solid rgba(255,255,255,0.1)",
|
||||
letterSpacing: 0.3,
|
||||
}}
|
||||
>
|
||||
{`${segmentIndex + 1} / ${segmentCount}`}
|
||||
</div>
|
||||
|
||||
{/* 中央播放按钮 */}
|
||||
{!isPlaying && (
|
||||
<button
|
||||
onClick={onTogglePlay}
|
||||
style={{
|
||||
position: "absolute",
|
||||
top: "50%",
|
||||
left: "50%",
|
||||
transform: "translate(-50%, -50%)",
|
||||
background: "rgba(0,0,0,0.45)",
|
||||
backdropFilter: "blur(12px)",
|
||||
WebkitBackdropFilter: "blur(12px)",
|
||||
border: "1px solid rgba(255,255,255,0.15)",
|
||||
borderRadius: "50%",
|
||||
width: 52,
|
||||
height: 52,
|
||||
cursor: "pointer",
|
||||
display: "flex",
|
||||
alignItems: "center",
|
||||
justifyContent: "center",
|
||||
color: "#fff",
|
||||
fontSize: 26,
|
||||
zIndex: 10,
|
||||
transition: "transform 0.2s ease, background 0.2s ease",
|
||||
boxShadow: "0 4px 20px rgba(0,0,0,0.4)",
|
||||
}}
|
||||
onMouseEnter={(e) => {
|
||||
e.currentTarget.style.transform = "translate(-50%, -50%) scale(1.08)"
|
||||
e.currentTarget.style.background = "rgba(0,0,0,0.6)"
|
||||
}}
|
||||
onMouseLeave={(e) => {
|
||||
e.currentTarget.style.transform = "translate(-50%, -50%) scale(1)"
|
||||
e.currentTarget.style.background = "rgba(0,0,0,0.45)"
|
||||
}}
|
||||
>
|
||||
<PlayCircleOutlined />
|
||||
</button>
|
||||
)}
|
||||
|
||||
{/* 控制条 — 手机风格毛玻璃 */}
|
||||
<div
|
||||
style={{
|
||||
position: "absolute",
|
||||
bottom: 0,
|
||||
left: 0,
|
||||
right: 0,
|
||||
display: "flex",
|
||||
alignItems: "center",
|
||||
gap: compact ? 6 : 10,
|
||||
padding: compact ? "8px 10px 10px" : "12px 16px 16px",
|
||||
background: "linear-gradient(transparent, rgba(0,0,0,0.7))",
|
||||
backdropFilter: "blur(4px)",
|
||||
WebkitBackdropFilter: "blur(4px)",
|
||||
zIndex: 10,
|
||||
}}
|
||||
>
|
||||
<button
|
||||
onClick={onTogglePlay}
|
||||
style={{
|
||||
background: "rgba(255,255,255,0.15)",
|
||||
border: "none",
|
||||
color: "#fff",
|
||||
fontSize: compact ? 14 : 16,
|
||||
cursor: "pointer",
|
||||
width: compact ? 26 : 32,
|
||||
height: compact ? 26 : 32,
|
||||
borderRadius: "50%",
|
||||
display: "flex",
|
||||
alignItems: "center",
|
||||
justifyContent: "center",
|
||||
flexShrink: 0,
|
||||
transition: "background 0.15s",
|
||||
}}
|
||||
onMouseEnter={(e) => {
|
||||
e.currentTarget.style.background = "rgba(255,255,255,0.25)"
|
||||
}}
|
||||
onMouseLeave={(e) => {
|
||||
e.currentTarget.style.background = "rgba(255,255,255,0.15)"
|
||||
}}
|
||||
>
|
||||
{isPlaying ? <PauseCircleOutlined /> : <PlayCircleOutlined />}
|
||||
</button>
|
||||
|
||||
<PreviewProgressBar
|
||||
currentTime={currentTime}
|
||||
totalDuration={totalDuration}
|
||||
onSeek={onSeek}
|
||||
compact={compact}
|
||||
/>
|
||||
</div>
|
||||
</>
|
||||
)
|
||||
}
|
||||
@@ -1,108 +0,0 @@
|
||||
import React, { useCallback, useEffect, useRef, useState } from "react"
|
||||
import { formatDuration } from "../utils/formatDuration"
|
||||
|
||||
interface PreviewProgressBarProps {
|
||||
currentTime: number
|
||||
totalDuration: number
|
||||
onSeek: (time: number) => void
|
||||
compact?: boolean
|
||||
}
|
||||
|
||||
/**
|
||||
* 进度条组件:点击/拖拽 seek
|
||||
*/
|
||||
export const PreviewProgressBar: React.FC<PreviewProgressBarProps> = ({
|
||||
currentTime,
|
||||
totalDuration,
|
||||
onSeek,
|
||||
compact = false,
|
||||
}) => {
|
||||
const progressRef = useRef<HTMLDivElement>(null)
|
||||
const [isDragging, setIsDragging] = useState(false)
|
||||
|
||||
const seekByClientX = useCallback(
|
||||
(clientX: number) => {
|
||||
if (!progressRef.current || totalDuration <= 0) return
|
||||
const rect = progressRef.current.getBoundingClientRect()
|
||||
const ratio = Math.max(0, Math.min(1, (clientX - rect.left) / rect.width))
|
||||
onSeek(ratio * totalDuration)
|
||||
},
|
||||
[totalDuration, onSeek],
|
||||
)
|
||||
|
||||
const handleMouseDown = useCallback(
|
||||
(e: React.MouseEvent<HTMLDivElement>) => {
|
||||
setIsDragging(true)
|
||||
seekByClientX(e.clientX)
|
||||
},
|
||||
[seekByClientX],
|
||||
)
|
||||
|
||||
useEffect(() => {
|
||||
if (!isDragging) return
|
||||
const handleMouseMove = (e: MouseEvent) => seekByClientX(e.clientX)
|
||||
const handleMouseUp = () => setIsDragging(false)
|
||||
window.addEventListener("mousemove", handleMouseMove)
|
||||
window.addEventListener("mouseup", handleMouseUp)
|
||||
return () => {
|
||||
window.removeEventListener("mousemove", handleMouseMove)
|
||||
window.removeEventListener("mouseup", handleMouseUp)
|
||||
}
|
||||
}, [isDragging, seekByClientX])
|
||||
|
||||
const progressPercent = totalDuration > 0 ? (currentTime / totalDuration) * 100 : 0
|
||||
|
||||
return (
|
||||
<>
|
||||
<span
|
||||
style={{
|
||||
fontSize: compact ? 10 : 11,
|
||||
color: "rgba(255,255,255,0.85)",
|
||||
minWidth: compact ? 58 : 72,
|
||||
fontVariantNumeric: "tabular-nums",
|
||||
letterSpacing: 0.2,
|
||||
}}
|
||||
>
|
||||
{formatDuration(currentTime)} / {formatDuration(totalDuration)}
|
||||
</span>
|
||||
|
||||
<div
|
||||
ref={progressRef}
|
||||
onMouseDown={handleMouseDown}
|
||||
style={{
|
||||
flex: 1,
|
||||
height: 3,
|
||||
background: "rgba(255,255,255,0.2)",
|
||||
borderRadius: 2,
|
||||
cursor: "pointer",
|
||||
position: "relative",
|
||||
}}
|
||||
>
|
||||
<div
|
||||
style={{
|
||||
height: "100%",
|
||||
width: `${progressPercent}%`,
|
||||
background: "#fff",
|
||||
borderRadius: 2,
|
||||
transition: isDragging ? "none" : "width 0.1s linear",
|
||||
}}
|
||||
/>
|
||||
<div
|
||||
style={{
|
||||
position: "absolute",
|
||||
top: "50%",
|
||||
left: `${progressPercent}%`,
|
||||
transform: "translate(-50%, -50%)",
|
||||
width: 10,
|
||||
height: 10,
|
||||
borderRadius: "50%",
|
||||
background: "#fff",
|
||||
boxShadow: "0 0 6px rgba(255,255,255,0.5)",
|
||||
opacity: isDragging ? 1 : 0,
|
||||
transition: "opacity 0.15s",
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
</>
|
||||
)
|
||||
}
|
||||
@@ -50,7 +50,15 @@ export const POSITION_OPTIONS = [
|
||||
]
|
||||
|
||||
/* ── 标题字体选项 ── */
|
||||
export const FONT_OPTIONS = ["思源黑体", "思源宋体", "苹方", "微软雅黑", "楷体"]
|
||||
export const FONT_OPTIONS = [
|
||||
"思源黑体",
|
||||
"思源宋体",
|
||||
"苹方",
|
||||
"PingFang",
|
||||
"微软雅黑",
|
||||
"楷体",
|
||||
"华康俪金黑",
|
||||
]
|
||||
|
||||
/* ── 标题字体 CSS font-family 映射(中文显示名 → 浏览器可识别的字体栈) ── */
|
||||
export const FONT_FAMILY_MAP: Record<string, string> = {
|
||||
@@ -60,6 +68,7 @@ export const FONT_FAMILY_MAP: Record<string, string> = {
|
||||
PingFang: '"PingFang SC", -apple-system, "Helvetica Neue", sans-serif',
|
||||
微软雅黑: '"Microsoft YaHei", "PingFang SC", sans-serif',
|
||||
楷体: '"KaiTi", "STKaiti", "DFKai-SB", serif',
|
||||
华康俪金黑: '"华康俪金黑", "DFLiJinHei-W8", "Source Han Sans SC", "Microsoft YaHei", sans-serif',
|
||||
}
|
||||
|
||||
export function getFontFamily(font: string): string {
|
||||
|
||||
@@ -171,6 +171,7 @@ export function useBatchCovers({
|
||||
let okCount = 0
|
||||
let failCount = 0
|
||||
for (const i of pending) {
|
||||
// eslint-disable-next-line no-await-in-loop
|
||||
const ok = await generateOne(i)
|
||||
if (ok) okCount += 1
|
||||
else failCount += 1
|
||||
|
||||
@@ -26,8 +26,6 @@ export interface BatchVariantClipsState {
|
||||
clipsByVariant: EditPlanClip[][]
|
||||
/** 各变体的 plan_id(正式生成回传,保证预览即成片);未就绪为空串 */
|
||||
planIdsByVariant: string[]
|
||||
/** 各变体的后端返回配音时长(秒);未就绪/未返回为 undefined */
|
||||
voiceDurationsByVariant: (number | undefined)[]
|
||||
/** 是否正在向后端申请变体计划 */
|
||||
loading: boolean
|
||||
/** 后端真实片段是否全部可用(每个变体都有 ≥1 条片段) */
|
||||
@@ -46,12 +44,6 @@ interface UseBatchVariantPlansOptions {
|
||||
assetIds: string[]
|
||||
/** 源剪辑计划 ID(草稿/预览关联),无则空串由后端兜底最新 plan */
|
||||
sourcePlanId?: string
|
||||
/** 统一配音 ID(共用配音模式),参考 useGenerateVideo voiceLibraryId 计算 */
|
||||
voiceLibraryId?: string
|
||||
/** 独立配音 ID 列表(每变体一条),voiceModePerVideo=true 时使用 */
|
||||
voiceLibraryIds?: string[]
|
||||
/** 是否启用独立配音模式(每变体各自一条配音) */
|
||||
voiceModePerVideo?: boolean
|
||||
}
|
||||
|
||||
export function useBatchVariantPlans({
|
||||
@@ -60,13 +52,9 @@ export function useBatchVariantPlans({
|
||||
templateId,
|
||||
assetIds,
|
||||
sourcePlanId = "",
|
||||
voiceLibraryId = "",
|
||||
voiceLibraryIds = [],
|
||||
voiceModePerVideo = false,
|
||||
}: UseBatchVariantPlansOptions): BatchVariantClipsState {
|
||||
const [clipsByVariant, setClipsByVariant] = useState<EditPlanClip[][]>([])
|
||||
const [planIdsByVariant, setPlanIdsByVariant] = useState<string[]>([])
|
||||
const [voiceDurationsByVariant, setVoiceDurationsByVariant] = useState<(number | undefined)[]>([])
|
||||
const [loading, setLoading] = useState(false)
|
||||
const [error, setError] = useState(false)
|
||||
|
||||
@@ -82,30 +70,17 @@ export function useBatchVariantPlans({
|
||||
setLoading(true)
|
||||
setError(false)
|
||||
try {
|
||||
// 配音参数:与 useGenerateVideo 保持一致的传参逻辑
|
||||
// - 独立配音模式 + voiceLibraryIds 非空:传 voice_library_ids
|
||||
// - 统一配音:传 voice_library_id
|
||||
// - 都没选:不传
|
||||
const voiceParam: { voice_library_id?: string; voice_library_ids?: string[] } = {}
|
||||
if (voiceModePerVideo && voiceLibraryIds.length > 0) {
|
||||
voiceParam.voice_library_ids = voiceLibraryIds
|
||||
} else if (voiceLibraryId) {
|
||||
voiceParam.voice_library_id = voiceLibraryId
|
||||
}
|
||||
|
||||
const resp = await createBatchVariantPlans({
|
||||
template_id: templateId,
|
||||
asset_ids: assetIds,
|
||||
count,
|
||||
...(sourcePlanId ? { source_edit_plan_id: sourcePlanId } : {}),
|
||||
...voiceParam,
|
||||
})
|
||||
if (seq !== requestSeqRef.current) return
|
||||
|
||||
const items: VariantPlan[] = Array.isArray(resp.items) ? resp.items : []
|
||||
const clips: EditPlanClip[][] = Array.from({ length: count }, () => [])
|
||||
const planIds: string[] = Array.from({ length: count }, () => "")
|
||||
const voiceDurs: (number | undefined)[] = Array.from({ length: count }, () => undefined)
|
||||
for (const item of items) {
|
||||
const idx = item.variant_index
|
||||
if (idx < 0 || idx >= count) continue
|
||||
@@ -113,9 +88,6 @@ export function useBatchVariantPlans({
|
||||
clips[idx] = (item.clips || [])
|
||||
.filter((c) => c && c.asset_id && c.status === "ready")
|
||||
.sort((a, b) => a.order - b.order)
|
||||
if (typeof item.voice_duration === "number" && item.voice_duration > 0) {
|
||||
voiceDurs[idx] = item.voice_duration
|
||||
}
|
||||
}
|
||||
// 数据完整性校验:每个变体都必须有真实片段,否则视为失败(不允许假数据冒充)
|
||||
const incomplete = clips.some((list) => list.length === 0)
|
||||
@@ -123,12 +95,10 @@ export function useBatchVariantPlans({
|
||||
console.warn("[useBatchVariantPlans] 变体计划数据不完整(存在空片段变体),标记加载失败")
|
||||
setClipsByVariant([])
|
||||
setPlanIdsByVariant([])
|
||||
setVoiceDurationsByVariant([])
|
||||
setError(true)
|
||||
} else {
|
||||
setClipsByVariant(clips)
|
||||
setPlanIdsByVariant(planIds)
|
||||
setVoiceDurationsByVariant(voiceDurs)
|
||||
setError(false)
|
||||
}
|
||||
} catch (err) {
|
||||
@@ -137,20 +107,11 @@ export function useBatchVariantPlans({
|
||||
console.warn("[useBatchVariantPlans] 申请变体计划失败,预览加载失败:", err)
|
||||
setClipsByVariant([])
|
||||
setPlanIdsByVariant([])
|
||||
setVoiceDurationsByVariant([])
|
||||
setError(true)
|
||||
} finally {
|
||||
if (seq === requestSeqRef.current) setLoading(false)
|
||||
}
|
||||
}, [
|
||||
templateId,
|
||||
count,
|
||||
sourcePlanId,
|
||||
assetIds,
|
||||
voiceLibraryId,
|
||||
voiceLibraryIds,
|
||||
voiceModePerVideo,
|
||||
])
|
||||
}, [templateId, count, sourcePlanId, assetIds])
|
||||
|
||||
/** 用户点击「重试」:nonce +1 驱动 effect 重新发起请求(effect 内 lastKey 校验保证只发一次) */
|
||||
const retry = useCallback(() => {
|
||||
@@ -164,40 +125,24 @@ export function useBatchVariantPlans({
|
||||
// 避免父组件传入内联字面量数组导致 effect 每次 render 触发 → 无限 setState 循环
|
||||
setClipsByVariant((prev) => (prev.length === 0 ? prev : []))
|
||||
setPlanIdsByVariant((prev) => (prev.length === 0 ? prev : []))
|
||||
setVoiceDurationsByVariant((prev) => (prev.length === 0 ? prev : []))
|
||||
setLoading((prev) => (prev === false ? prev : false))
|
||||
setError((prev) => (prev === false ? prev : false))
|
||||
lastKeyRef.current = ""
|
||||
return
|
||||
}
|
||||
const voiceKey = voiceModePerVideo
|
||||
? `per:${[...voiceLibraryIds].sort().join(",")}`
|
||||
: `one:${voiceLibraryId}`
|
||||
const key = `${retryNonce}|${templateId}|${count}|${sourcePlanId}|${[...assetIds]
|
||||
.sort()
|
||||
.join(",")}|${voiceKey}`
|
||||
.join(",")}`
|
||||
if (key === lastKeyRef.current) return
|
||||
lastKeyRef.current = key
|
||||
load()
|
||||
}, [
|
||||
enabled,
|
||||
templateId,
|
||||
count,
|
||||
sourcePlanId,
|
||||
assetIds,
|
||||
load,
|
||||
retryNonce,
|
||||
voiceLibraryId,
|
||||
voiceLibraryIds,
|
||||
voiceModePerVideo,
|
||||
])
|
||||
}, [enabled, templateId, count, sourcePlanId, assetIds, load, retryNonce])
|
||||
|
||||
const ready = !error && !loading && clipsByVariant.every((list) => list.length > 0)
|
||||
|
||||
return {
|
||||
clipsByVariant,
|
||||
planIdsByVariant,
|
||||
voiceDurationsByVariant,
|
||||
loading,
|
||||
ready,
|
||||
error,
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -51,6 +51,7 @@ export function useTitleCoverSync({
|
||||
thumbnail_url: tpl.cover_config!.thumbnail_url || prev.thumbnail_url,
|
||||
}))
|
||||
}
|
||||
// eslint-disable-next-line react-hooks/exhaustive-deps
|
||||
}, [selectedTemplate, setTitleSettings, setCoverSettings])
|
||||
// ↑ 移除 userTemplates,只在 selectedTemplate 真正变化时触发
|
||||
}
|
||||
|
||||
@@ -1,131 +0,0 @@
|
||||
import { useCallback, useEffect, useRef } from "react"
|
||||
|
||||
interface UsePreviewAudioOptions {
|
||||
voiceAudioUrl: string | undefined
|
||||
voiceDurationHint: number | undefined
|
||||
muted: boolean
|
||||
isPlaying: boolean
|
||||
currentTime: number
|
||||
onVoiceDurationChange: (d: number) => void
|
||||
onEnded: () => void
|
||||
}
|
||||
|
||||
interface UsePreviewAudioReturn {
|
||||
seekTo: (time: number) => void
|
||||
ensurePlayingAt: (time: number) => void
|
||||
pause: () => void
|
||||
}
|
||||
|
||||
/**
|
||||
* 配音音频管理 hook:加载配音、loadedmetadata 自测时长、play/pause 同步、
|
||||
* ended 事件回调、seek 同步、末帧冻结期间续播。
|
||||
*/
|
||||
export function usePreviewAudio({
|
||||
voiceAudioUrl,
|
||||
voiceDurationHint,
|
||||
muted,
|
||||
isPlaying,
|
||||
currentTime,
|
||||
onVoiceDurationChange,
|
||||
onEnded,
|
||||
}: UsePreviewAudioOptions): UsePreviewAudioReturn {
|
||||
const audioRef = useRef<HTMLAudioElement | null>(null)
|
||||
const prevIsPlayingRef = useRef(false)
|
||||
|
||||
// 外部 hint 初始化(自测值前的兜底)
|
||||
useEffect(() => {
|
||||
if (voiceDurationHint && voiceDurationHint > 0) {
|
||||
onVoiceDurationChange(voiceDurationHint)
|
||||
}
|
||||
}, [voiceDurationHint, onVoiceDurationChange])
|
||||
|
||||
// 创建/替换 audio 元素,加载 metadata 时自测时长并监听 ended
|
||||
useEffect(() => {
|
||||
if (!voiceAudioUrl) {
|
||||
if (audioRef.current) {
|
||||
audioRef.current.pause()
|
||||
audioRef.current.src = ""
|
||||
audioRef.current = null
|
||||
}
|
||||
return
|
||||
}
|
||||
if (!audioRef.current) {
|
||||
audioRef.current = new Audio()
|
||||
audioRef.current.preload = "auto"
|
||||
}
|
||||
if (audioRef.current.src !== voiceAudioUrl) {
|
||||
audioRef.current.src = voiceAudioUrl
|
||||
}
|
||||
audioRef.current.muted = muted
|
||||
|
||||
const audio = audioRef.current
|
||||
const onLoaded = () => {
|
||||
if (audio.duration && isFinite(audio.duration) && audio.duration > 0) {
|
||||
onVoiceDurationChange(audio.duration)
|
||||
}
|
||||
}
|
||||
const onEndedHandler = () => onEnded()
|
||||
audio.addEventListener("loadedmetadata", onLoaded)
|
||||
audio.addEventListener("ended", onEndedHandler)
|
||||
return () => {
|
||||
audio.removeEventListener("loadedmetadata", onLoaded)
|
||||
audio.removeEventListener("ended", onEndedHandler)
|
||||
}
|
||||
}, [voiceAudioUrl, muted, onVoiceDurationChange, onEnded])
|
||||
|
||||
// mute 变化即时同步
|
||||
useEffect(() => {
|
||||
if (audioRef.current) audioRef.current.muted = muted
|
||||
}, [muted])
|
||||
|
||||
// 播放/暂停同步(跟随视频 isPlaying)
|
||||
useEffect(() => {
|
||||
const audio = audioRef.current
|
||||
if (!audio || !audio.src) return
|
||||
if (isPlaying && !prevIsPlayingRef.current) {
|
||||
if (Math.abs(audio.currentTime - currentTime) > 0.3) {
|
||||
try {
|
||||
audio.currentTime = currentTime
|
||||
} catch {
|
||||
/* ignore */
|
||||
}
|
||||
}
|
||||
audio.play().catch(() => {})
|
||||
} else if (!isPlaying && prevIsPlayingRef.current) {
|
||||
audio.pause()
|
||||
}
|
||||
prevIsPlayingRef.current = isPlaying
|
||||
}, [isPlaying, currentTime])
|
||||
|
||||
const seekTo = useCallback((time: number) => {
|
||||
const audio = audioRef.current
|
||||
if (audio && audio.src) {
|
||||
try {
|
||||
audio.currentTime = time
|
||||
} catch {
|
||||
/* ignore */
|
||||
}
|
||||
}
|
||||
}, [])
|
||||
|
||||
const ensurePlayingAt = useCallback((time: number) => {
|
||||
const audio = audioRef.current
|
||||
if (!audio || !audio.src) return
|
||||
try {
|
||||
if (Math.abs(audio.currentTime - time) > 0.5) audio.currentTime = time
|
||||
if (audio.paused) audio.play().catch(() => {})
|
||||
} catch {
|
||||
/* ignore */
|
||||
}
|
||||
}, [])
|
||||
|
||||
const pause = useCallback(() => {
|
||||
try {
|
||||
audioRef.current?.pause()
|
||||
} catch {
|
||||
/* ignore */
|
||||
}
|
||||
}, [])
|
||||
|
||||
return { seekTo, ensurePlayingAt, pause }
|
||||
}
|
||||
@@ -125,6 +125,7 @@ export function useVariantVoicePreview({
|
||||
continue
|
||||
}
|
||||
try {
|
||||
// eslint-disable-next-line no-await-in-loop
|
||||
const res = await previewTts({ text: job.title, voice_id: job.voiceId })
|
||||
if (cancelled || controller.signal.aborted || seq !== seqRef.current) return
|
||||
const audioUrl = res.audio_url || ""
|
||||
|
||||
@@ -1,22 +1,17 @@
|
||||
/**
|
||||
* 成片库页面 — V21 设计系统
|
||||
* 卡片网格布局,支持视频内联播放/下载/分享、批量操作、筛选、无限滚动分页
|
||||
* 卡片网格布局,支持视频内联播放/下载/分享、批量操作、筛选
|
||||
*
|
||||
* 主组件仅保留 Hook 组装与整体布局
|
||||
* 列表查询 → hooks/useProductList(useInfiniteQuery 分页)
|
||||
* 列表查询 → hooks/useProductList
|
||||
* 操作逻辑 → hooks/useProductActions
|
||||
* 筛选栏 → components/ProductFilterBar
|
||||
* 批量操作栏 → components/ProductBatchBar
|
||||
* 空状态 → components/ProductEmptyState
|
||||
* 产品卡片 → components/ProductCard(内联视频播放)
|
||||
*/
|
||||
import React, { useEffect, useRef } from "react"
|
||||
import {
|
||||
VideoCameraOutlined,
|
||||
DownloadOutlined,
|
||||
ReloadOutlined,
|
||||
LoadingOutlined,
|
||||
} from "@ant-design/icons"
|
||||
import React from "react"
|
||||
import { VideoCameraOutlined, DownloadOutlined, ReloadOutlined } from "@ant-design/icons"
|
||||
import { Button } from "@/components/ui"
|
||||
import { ProductCard } from "./components/ProductCard"
|
||||
import { ProductFilterBar } from "./components/ProductFilterBar"
|
||||
@@ -29,13 +24,11 @@ import "./products.css"
|
||||
|
||||
const ProductLibrary: React.FC = () => {
|
||||
const {
|
||||
products,
|
||||
filteredProducts,
|
||||
isLoading,
|
||||
isFetchingNextPage,
|
||||
isError,
|
||||
error,
|
||||
hasNextPage,
|
||||
fetchNextPage,
|
||||
refetch,
|
||||
searchText,
|
||||
setSearchText,
|
||||
@@ -71,40 +64,19 @@ const ProductLibrary: React.FC = () => {
|
||||
} = useProductActions({
|
||||
selectedIds,
|
||||
clearSelection,
|
||||
products: filteredProducts,
|
||||
products,
|
||||
setPlayingProduct: () => {}, // 不再使用弹窗播放
|
||||
})
|
||||
|
||||
const { recomputeDedup, isRecomputing } = useRecomputeDedup()
|
||||
|
||||
/* ── 无限滚动:IntersectionObserver 监听底部哨兵元素 ── */
|
||||
const sentinelRef = useRef<HTMLDivElement>(null)
|
||||
|
||||
useEffect(() => {
|
||||
const el = sentinelRef.current
|
||||
if (!el) return
|
||||
// 已有数据但正在加载中/没有更多页时不触发
|
||||
if (isFetchingNextPage || !hasNextPage) return
|
||||
|
||||
const observer = new IntersectionObserver(
|
||||
(entries) => {
|
||||
if (entries[0]?.isIntersecting) {
|
||||
void fetchNextPage()
|
||||
}
|
||||
},
|
||||
{ rootMargin: "200px" },
|
||||
)
|
||||
observer.observe(el)
|
||||
return () => observer.disconnect()
|
||||
}, [fetchNextPage, hasNextPage, isFetchingNextPage])
|
||||
|
||||
// ── Loading 状态(仅首次加载)──
|
||||
if (isLoading && filteredProducts.length === 0) {
|
||||
// ── Loading 状态 ──
|
||||
if (isLoading) {
|
||||
return <ProductEmptyState type="loading" />
|
||||
}
|
||||
|
||||
// ── Error 状态 ──
|
||||
if (isError && filteredProducts.length === 0) {
|
||||
if (isError) {
|
||||
console.error("[ProductLibrary] 加载失败:", error)
|
||||
const errorMsg = error?.message || "加载失败"
|
||||
const is404 = errorMsg.includes("404") || errorMsg.includes("Not Found")
|
||||
@@ -171,46 +143,22 @@ const ProductLibrary: React.FC = () => {
|
||||
|
||||
{/* 卡片网格 */}
|
||||
{filteredProducts.length > 0 ? (
|
||||
<>
|
||||
<div className="xx-products-grid">
|
||||
{filteredProducts.map((product) => (
|
||||
<ProductCard
|
||||
key={product.id}
|
||||
product={product}
|
||||
isSelected={selectedIds.has(product.id)}
|
||||
batchMode={batchMode}
|
||||
onToggleSelect={handleToggleSelect}
|
||||
onDownload={handleDownload}
|
||||
onShare={handleShare}
|
||||
onDelete={handleDelete}
|
||||
onPublish={handlePublish}
|
||||
onReviewStatusChange={handleReviewStatusChange}
|
||||
/>
|
||||
))}
|
||||
</div>
|
||||
|
||||
{/* 底部哨兵 + 状态提示 */}
|
||||
<div
|
||||
ref={sentinelRef}
|
||||
style={{
|
||||
gridColumn: "1 / -1",
|
||||
textAlign: "center",
|
||||
padding: "24px 0",
|
||||
fontSize: 13,
|
||||
color: "#8c8ca1",
|
||||
}}
|
||||
>
|
||||
{isFetchingNextPage ? (
|
||||
<>
|
||||
<LoadingOutlined /> 加载中…
|
||||
</>
|
||||
) : hasNextPage ? (
|
||||
<span style={{ opacity: 0 }}>加载更多</span>
|
||||
) : (
|
||||
<span>—— 已加载全部 ——</span>
|
||||
)}
|
||||
</div>
|
||||
</>
|
||||
<div className="xx-products-grid">
|
||||
{filteredProducts.map((product) => (
|
||||
<ProductCard
|
||||
key={product.id}
|
||||
product={product}
|
||||
isSelected={selectedIds.has(product.id)}
|
||||
batchMode={batchMode}
|
||||
onToggleSelect={handleToggleSelect}
|
||||
onDownload={handleDownload}
|
||||
onShare={handleShare}
|
||||
onDelete={handleDelete}
|
||||
onPublish={handlePublish}
|
||||
onReviewStatusChange={handleReviewStatusChange}
|
||||
/>
|
||||
))}
|
||||
</div>
|
||||
) : (
|
||||
<ProductEmptyState type="empty" />
|
||||
)}
|
||||
|
||||
@@ -1,53 +1,28 @@
|
||||
import { useMemo } from "react"
|
||||
import { useInfiniteQuery } from "@tanstack/react-query"
|
||||
import { useQuery } from "@tanstack/react-query"
|
||||
import { getProducts, type ProductItem as ApiProductItem } from "@/api/products"
|
||||
import { mapApiProduct } from "../../utils"
|
||||
import type { ProductItem } from "../../types"
|
||||
import { useProductFiltering } from "./useProductFiltering"
|
||||
import { useBatchSelection } from "./useBatchSelection"
|
||||
|
||||
export type { Filters } from "./useProductFiltering"
|
||||
|
||||
const PAGE_SIZE = 20
|
||||
|
||||
export const useProductList = () => {
|
||||
/* ── 无限滚动获取成品列表(每页 20 条) ── */
|
||||
/* ── 获取成品列表 ── */
|
||||
const {
|
||||
data,
|
||||
data: apiProducts = [],
|
||||
isLoading,
|
||||
isFetchingNextPage,
|
||||
isError,
|
||||
error,
|
||||
hasNextPage,
|
||||
fetchNextPage,
|
||||
refetch,
|
||||
} = useInfiniteQuery<
|
||||
{
|
||||
items: ApiProductItem[]
|
||||
total: number
|
||||
page: number
|
||||
page_size: number
|
||||
},
|
||||
Error
|
||||
>({
|
||||
} = useQuery<ApiProductItem[], Error>({
|
||||
queryKey: ["products"],
|
||||
queryFn: async ({ pageParam = 1 }) =>
|
||||
getProducts({ page: pageParam as number, page_size: PAGE_SIZE }),
|
||||
initialPageParam: 1,
|
||||
getNextPageParam: (lastPage) => {
|
||||
const loadedCount = lastPage.page * lastPage.page_size
|
||||
return loadedCount < lastPage.total ? lastPage.page + 1 : undefined
|
||||
},
|
||||
queryFn: () => getProducts(),
|
||||
staleTime: 30_000,
|
||||
})
|
||||
|
||||
// 将所有页拼接为一维数组,再做前端映射+排序
|
||||
const apiProducts = useMemo<ApiProductItem[]>(() => {
|
||||
if (!data?.pages) return []
|
||||
return data.pages.flatMap((p) => p.items)
|
||||
}, [data])
|
||||
|
||||
const products = useMemo<ProductItem[]>(
|
||||
// 映射为前端类型,按创建时间倒序排列,防御非数组返回
|
||||
const products = useMemo(
|
||||
() =>
|
||||
(Array.isArray(apiProducts) ? apiProducts : []).map(mapApiProduct).sort((a, b) => {
|
||||
if (!a.date || a.date === "—") return 1
|
||||
@@ -90,11 +65,8 @@ export const useProductList = () => {
|
||||
products,
|
||||
filteredProducts,
|
||||
isLoading,
|
||||
isFetchingNextPage,
|
||||
isError,
|
||||
error,
|
||||
hasNextPage,
|
||||
fetchNextPage,
|
||||
refetch,
|
||||
// 筛选
|
||||
searchText,
|
||||
|
||||
@@ -11,7 +11,6 @@ import CloneModal from "@/components/voice/CloneModal"
|
||||
import { VoiceCloneCard } from "./components/VoiceCloneCard"
|
||||
import { VoiceCloneEmpty, VoiceCloneSkeleton, ToastContainer } from "./components/States"
|
||||
import { EditNameDialog } from "./components/EditNameDialog"
|
||||
import VoiceClonePreviewPanel from "./components/VoiceClonePreviewPanel"
|
||||
import { useVoiceCloneList } from "./hooks/useVoiceCloneList"
|
||||
import "./voice-clone.css"
|
||||
|
||||
@@ -48,9 +47,6 @@ const VoiceClone: React.FC = () => {
|
||||
}
|
||||
/>
|
||||
|
||||
{/* 音色试听面板(自定义文本 + 语速/情绪) */}
|
||||
{!isLoading && voices.length > 0 && <VoiceClonePreviewPanel voices={voices} />}
|
||||
|
||||
{/* 加载状态 — 骨架屏 */}
|
||||
{isLoading && <VoiceCloneSkeleton />}
|
||||
|
||||
|
||||
@@ -1,133 +0,0 @@
|
||||
/**
|
||||
* 克隆音色试听面板
|
||||
* - 选择就绪音色、输入试听文本、调节语速/情绪,点试听
|
||||
* - 复用配音库 TTS 弹窗的 SpeedControl / EmotionControl 组件
|
||||
*/
|
||||
import React, { useState, useRef, useCallback } from "react"
|
||||
import { message } from "antd"
|
||||
import { SoundOutlined, LoadingOutlined } from "@ant-design/icons"
|
||||
import { getVoiceClonePreview, type VoiceClone } from "@/api/voice-clone"
|
||||
import SpeedControl from "@/pages/voices/components/tts-modal/SpeedControl"
|
||||
import EmotionControl from "@/pages/voices/components/tts-modal/EmotionControl"
|
||||
import { DEFAULT_TTS_EMOTION, type TtsEmotion } from "@/pages/voices/components/tts-modal/constants"
|
||||
import { TTS_CONFIG } from "@/pages/voices/components/tts-modal/types"
|
||||
|
||||
interface VoiceClonePreviewPanelProps {
|
||||
voices: VoiceClone[]
|
||||
}
|
||||
|
||||
const DEFAULT_PREVIEW_TEXT = "你好呀,欢迎使用小虾智剪,这是我的声音效果,希望你喜欢。"
|
||||
|
||||
const VoiceClonePreviewPanel: React.FC<VoiceClonePreviewPanelProps> = ({ voices }) => {
|
||||
const readyVoices = voices.filter((v) => v.status === "ready")
|
||||
|
||||
const [selectedId, setSelectedId] = useState<string>(readyVoices[0]?.id ?? "")
|
||||
const [previewText, setPreviewText] = useState(DEFAULT_PREVIEW_TEXT)
|
||||
const [speed, setSpeed] = useState<number>(TTS_CONFIG.DEFAULT_SPEED)
|
||||
const [emotion, setEmotion] = useState<TtsEmotion>(DEFAULT_TTS_EMOTION)
|
||||
const [previewing, setPreviewing] = useState(false)
|
||||
const [audioUrl, setAudioUrl] = useState<string | null>(null)
|
||||
const audioRef = useRef<HTMLAudioElement | null>(null)
|
||||
|
||||
const handlePreview = useCallback(async () => {
|
||||
if (!selectedId) {
|
||||
message.warning("请先选择要试听的音色")
|
||||
return
|
||||
}
|
||||
const text = previewText.trim()
|
||||
if (!text) {
|
||||
message.warning("请输入试听文本")
|
||||
return
|
||||
}
|
||||
if (audioRef.current) {
|
||||
audioRef.current.pause()
|
||||
audioRef.current = null
|
||||
}
|
||||
setPreviewing(true)
|
||||
setAudioUrl(null)
|
||||
try {
|
||||
const res = await getVoiceClonePreview(selectedId, text, { speed, emotion })
|
||||
setAudioUrl(res.audio_url)
|
||||
const audio = new Audio(res.audio_url)
|
||||
audioRef.current = audio
|
||||
audio.play().catch(() => {
|
||||
message.error("播放失败,请重试")
|
||||
})
|
||||
} catch (err) {
|
||||
const msg = err instanceof Error ? err.message : "试听失败"
|
||||
message.error(msg)
|
||||
} finally {
|
||||
setPreviewing(false)
|
||||
}
|
||||
}, [selectedId, previewText, speed, emotion])
|
||||
|
||||
if (readyVoices.length === 0) return null
|
||||
|
||||
return (
|
||||
<div className="vc-preview-panel">
|
||||
<div className="vc-preview-header">
|
||||
<SoundOutlined style={{ color: "var(--primary-color)" }} />
|
||||
<span className="vc-preview-title">音色试听</span>
|
||||
</div>
|
||||
|
||||
<div className="vc-preview-body">
|
||||
<div className="vc-preview-field">
|
||||
<label className="vc-preview-label">选择音色</label>
|
||||
<select
|
||||
className="vc-preview-select"
|
||||
value={selectedId}
|
||||
onChange={(e) => setSelectedId(e.target.value)}
|
||||
>
|
||||
{readyVoices.map((v) => (
|
||||
<option key={v.id} value={v.id}>
|
||||
{v.name}
|
||||
</option>
|
||||
))}
|
||||
</select>
|
||||
</div>
|
||||
|
||||
<div className="vc-preview-field">
|
||||
<label className="vc-preview-label">试听文本</label>
|
||||
<textarea
|
||||
className="vc-preview-textarea"
|
||||
value={previewText}
|
||||
onChange={(e) => setPreviewText(e.target.value)}
|
||||
rows={2}
|
||||
maxLength={200}
|
||||
placeholder="输入试听文本(最多200字)"
|
||||
/>
|
||||
</div>
|
||||
|
||||
<div className="vc-preview-grid">
|
||||
<div className="vc-preview-field">
|
||||
<SpeedControl speed={speed} onChange={setSpeed} />
|
||||
</div>
|
||||
<div className="vc-preview-field">
|
||||
<EmotionControl emotion={emotion} onChange={setEmotion} />
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<button
|
||||
type="button"
|
||||
className="vc-preview-btn"
|
||||
onClick={handlePreview}
|
||||
disabled={previewing || !selectedId || !previewText.trim()}
|
||||
>
|
||||
{previewing ? (
|
||||
<>
|
||||
<LoadingOutlined /> 合成中...
|
||||
</>
|
||||
) : (
|
||||
<>▶ 开始试听</>
|
||||
)}
|
||||
</button>
|
||||
|
||||
{audioUrl && !previewing && (
|
||||
<audio controls src={audioUrl} style={{ width: "100%", marginTop: 4 }} />
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
export default VoiceClonePreviewPanel
|
||||
@@ -464,93 +464,3 @@
|
||||
padding: var(--space-sm);
|
||||
}
|
||||
}
|
||||
|
||||
/* ── 试听面板 ─────────────────────────────────────────── */
|
||||
.vc-preview-panel {
|
||||
background: var(--bg-card);
|
||||
border: 1px solid var(--line);
|
||||
border-radius: var(--radius-lg);
|
||||
padding: var(--space-lg);
|
||||
}
|
||||
|
||||
.vc-preview-header {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 8px;
|
||||
margin-bottom: 12px;
|
||||
}
|
||||
|
||||
.vc-preview-title {
|
||||
font-size: 15px;
|
||||
font-weight: 600;
|
||||
color: var(--text-primary);
|
||||
}
|
||||
|
||||
.vc-preview-body {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 12px;
|
||||
}
|
||||
|
||||
.vc-preview-field {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 6px;
|
||||
}
|
||||
|
||||
.vc-preview-label {
|
||||
font-size: 13px;
|
||||
color: var(--text-secondary);
|
||||
}
|
||||
|
||||
.vc-preview-select,
|
||||
.vc-preview-textarea {
|
||||
width: 100%;
|
||||
padding: 8px 10px;
|
||||
border-radius: 6px;
|
||||
border: 1px solid var(--line);
|
||||
background: var(--bg-primary);
|
||||
color: var(--text-primary);
|
||||
font-size: 13px;
|
||||
outline: none;
|
||||
font-family: inherit;
|
||||
box-sizing: border-box;
|
||||
}
|
||||
|
||||
.vc-preview-select:focus,
|
||||
.vc-preview-textarea:focus {
|
||||
border-color: var(--primary-color);
|
||||
}
|
||||
|
||||
.vc-preview-textarea {
|
||||
resize: vertical;
|
||||
min-height: 52px;
|
||||
}
|
||||
|
||||
.vc-preview-grid {
|
||||
display: grid;
|
||||
grid-template-columns: 1fr 1fr;
|
||||
gap: 12px;
|
||||
}
|
||||
|
||||
.vc-preview-btn {
|
||||
width: 100%;
|
||||
padding: 10px 0;
|
||||
border-radius: 8px;
|
||||
border: none;
|
||||
background: var(--primary-color);
|
||||
color: #fff;
|
||||
font-size: 14px;
|
||||
font-weight: 600;
|
||||
cursor: pointer;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
gap: 8px;
|
||||
transition: opacity 0.15s;
|
||||
}
|
||||
|
||||
.vc-preview-btn:disabled {
|
||||
opacity: 0.5;
|
||||
cursor: not-allowed;
|
||||
}
|
||||
|
||||
@@ -132,16 +132,12 @@ const VoiceLibrary: React.FC = () => {
|
||||
ttsText,
|
||||
ttsVoiceId,
|
||||
ttsSpeed,
|
||||
ttsEmotion,
|
||||
ttsLanguage,
|
||||
ttsStatus,
|
||||
ttsAudioUrl,
|
||||
ttsError,
|
||||
setTtsText,
|
||||
setTtsVoiceId,
|
||||
setTtsSpeed,
|
||||
setTtsEmotion,
|
||||
setTtsLanguage,
|
||||
setTtsOpen,
|
||||
handleTtsSynthesize,
|
||||
handleTtsSave,
|
||||
@@ -367,8 +363,6 @@ const VoiceLibrary: React.FC = () => {
|
||||
ttsText={ttsText}
|
||||
ttsVoiceId={ttsVoiceId}
|
||||
ttsSpeed={ttsSpeed}
|
||||
ttsEmotion={ttsEmotion}
|
||||
ttsLanguage={ttsLanguage}
|
||||
ttsStatus={ttsStatus}
|
||||
ttsAudioUrl={ttsAudioUrl}
|
||||
ttsError={ttsError}
|
||||
@@ -380,8 +374,6 @@ const VoiceLibrary: React.FC = () => {
|
||||
onTtsTextChange={setTtsText}
|
||||
onTtsVoiceChange={setTtsVoiceId}
|
||||
onTtsSpeedChange={setTtsSpeed}
|
||||
onTtsEmotionChange={setTtsEmotion}
|
||||
onTtsLanguageChange={setTtsLanguage}
|
||||
onTtsSynthesize={handleTtsSynthesize}
|
||||
onTtsSave={handleTtsSave}
|
||||
/>
|
||||
|
||||
@@ -4,8 +4,6 @@ import { type TtsModalProps, type TtsStatus } from "./tts-modal/types"
|
||||
import TextInputSection from "./tts-modal/TextInputSection"
|
||||
import VoiceSelector from "./tts-modal/VoiceSelector"
|
||||
import SpeedControl from "./tts-modal/SpeedControl"
|
||||
import EmotionControl from "./tts-modal/EmotionControl"
|
||||
import LanguageControl from "./tts-modal/LanguageControl"
|
||||
import SynthesizeButton from "./tts-modal/SynthesizeButton"
|
||||
import ErrorAlert from "./tts-modal/ErrorAlert"
|
||||
import ResultPanel from "./tts-modal/ResultPanel"
|
||||
@@ -16,8 +14,6 @@ const TtsModal: React.FC<TtsModalProps> = ({
|
||||
ttsText,
|
||||
ttsVoiceId,
|
||||
ttsSpeed,
|
||||
ttsEmotion,
|
||||
ttsLanguage,
|
||||
ttsStatus,
|
||||
ttsAudioUrl,
|
||||
ttsError,
|
||||
@@ -27,8 +23,6 @@ const TtsModal: React.FC<TtsModalProps> = ({
|
||||
onTextChange,
|
||||
onVoiceChange,
|
||||
onSpeedChange,
|
||||
onEmotionChange,
|
||||
onLanguageChange,
|
||||
onSynthesize,
|
||||
onSave,
|
||||
}) => {
|
||||
@@ -49,16 +43,6 @@ const TtsModal: React.FC<TtsModalProps> = ({
|
||||
presetVoices={presetVoices}
|
||||
clonedVoices={clonedVoices}
|
||||
/>
|
||||
<div
|
||||
style={{
|
||||
display: "grid",
|
||||
gridTemplateColumns: "1fr 1fr",
|
||||
gap: 12,
|
||||
}}
|
||||
>
|
||||
<EmotionControl emotion={ttsEmotion} onChange={onEmotionChange} />
|
||||
<LanguageControl language={ttsLanguage} onChange={onLanguageChange} />
|
||||
</div>
|
||||
<SpeedControl speed={ttsSpeed} onChange={onSpeedChange} />
|
||||
<SynthesizeButton status={ttsStatus} text={ttsText} onClick={onSynthesize} />
|
||||
{ttsError && <ErrorAlert error={ttsError} />}
|
||||
|
||||
@@ -6,7 +6,6 @@ import type { ClonedVoiceDisplay, PresetVoiceDisplay } from "../types"
|
||||
import type { VoiceClone } from "@/api/voice-clone"
|
||||
import type { TtsStatus } from "./TtsModal"
|
||||
import type { TtsClonedVoiceOption } from "./tts-modal/VoiceSelector"
|
||||
import type { TtsEmotion, TtsLanguage } from "./tts-modal/constants"
|
||||
import CloneModal from "@/components/voice/CloneModal"
|
||||
import CloneDetailModal from "./CloneDetailModal"
|
||||
import UploadVoiceModal from "./UploadVoiceModal"
|
||||
@@ -43,8 +42,6 @@ export interface VoiceModalsProps {
|
||||
ttsText: string
|
||||
ttsVoiceId: string
|
||||
ttsSpeed: number
|
||||
ttsEmotion: TtsEmotion
|
||||
ttsLanguage: TtsLanguage
|
||||
ttsStatus: TtsStatus
|
||||
ttsAudioUrl: string | null
|
||||
ttsError: string | null
|
||||
@@ -55,8 +52,6 @@ export interface VoiceModalsProps {
|
||||
onTtsTextChange: (text: string) => void
|
||||
onTtsVoiceChange: (id: string) => void
|
||||
onTtsSpeedChange: (speed: number) => void
|
||||
onTtsEmotionChange: (emotion: TtsEmotion) => void
|
||||
onTtsLanguageChange: (language: TtsLanguage) => void
|
||||
onTtsSynthesize: () => void
|
||||
onTtsSave: () => void
|
||||
}
|
||||
@@ -85,8 +80,6 @@ export const VoiceModals: React.FC<VoiceModalsProps> = ({
|
||||
ttsText,
|
||||
ttsVoiceId,
|
||||
ttsSpeed,
|
||||
ttsEmotion,
|
||||
ttsLanguage,
|
||||
ttsStatus,
|
||||
ttsAudioUrl,
|
||||
ttsError,
|
||||
@@ -96,8 +89,6 @@ export const VoiceModals: React.FC<VoiceModalsProps> = ({
|
||||
onTtsTextChange,
|
||||
onTtsVoiceChange,
|
||||
onTtsSpeedChange,
|
||||
onTtsEmotionChange,
|
||||
onTtsLanguageChange,
|
||||
onTtsSynthesize,
|
||||
onTtsSave,
|
||||
}) => {
|
||||
@@ -138,8 +129,6 @@ export const VoiceModals: React.FC<VoiceModalsProps> = ({
|
||||
ttsText={ttsText}
|
||||
ttsVoiceId={ttsVoiceId}
|
||||
ttsSpeed={ttsSpeed}
|
||||
ttsEmotion={ttsEmotion}
|
||||
ttsLanguage={ttsLanguage}
|
||||
ttsStatus={ttsStatus}
|
||||
ttsAudioUrl={ttsAudioUrl}
|
||||
ttsError={ttsError}
|
||||
@@ -149,8 +138,6 @@ export const VoiceModals: React.FC<VoiceModalsProps> = ({
|
||||
onTextChange={onTtsTextChange}
|
||||
onVoiceChange={onTtsVoiceChange}
|
||||
onSpeedChange={onTtsSpeedChange}
|
||||
onEmotionChange={onTtsEmotionChange}
|
||||
onLanguageChange={onTtsLanguageChange}
|
||||
onSynthesize={onTtsSynthesize}
|
||||
onSave={onTtsSave}
|
||||
/>
|
||||
|
||||
@@ -1,47 +0,0 @@
|
||||
import React from "react"
|
||||
import { TTS_EMOTION_OPTIONS, type TtsEmotion } from "./constants"
|
||||
|
||||
interface EmotionControlProps {
|
||||
emotion: TtsEmotion
|
||||
onChange: (emotion: TtsEmotion) => void
|
||||
}
|
||||
|
||||
/** 情绪选择下拉 */
|
||||
const EmotionControl: React.FC<EmotionControlProps> = ({ emotion, onChange }) => {
|
||||
return (
|
||||
<div>
|
||||
<div
|
||||
style={{
|
||||
fontSize: 13,
|
||||
color: "var(--text-secondary)",
|
||||
marginBottom: 6,
|
||||
}}
|
||||
>
|
||||
情绪
|
||||
</div>
|
||||
<select
|
||||
value={emotion}
|
||||
onChange={(e) => onChange(e.target.value as TtsEmotion)}
|
||||
style={{
|
||||
width: "100%",
|
||||
padding: "7px 10px",
|
||||
borderRadius: 6,
|
||||
border: "1px solid var(--border-color, #e5e7eb)",
|
||||
background: "var(--bg-primary, #fff)",
|
||||
color: "var(--text-primary)",
|
||||
fontSize: 13,
|
||||
outline: "none",
|
||||
cursor: "pointer",
|
||||
}}
|
||||
>
|
||||
{TTS_EMOTION_OPTIONS.map((opt) => (
|
||||
<option key={opt.value} value={opt.value}>
|
||||
{opt.label}
|
||||
</option>
|
||||
))}
|
||||
</select>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
export default EmotionControl
|
||||
@@ -1,47 +0,0 @@
|
||||
import React from "react"
|
||||
import { TTS_LANGUAGE_OPTIONS, type TtsLanguage } from "./constants"
|
||||
|
||||
interface LanguageControlProps {
|
||||
language: TtsLanguage
|
||||
onChange: (language: TtsLanguage) => void
|
||||
}
|
||||
|
||||
/** 语言选择下拉 */
|
||||
const LanguageControl: React.FC<LanguageControlProps> = ({ language, onChange }) => {
|
||||
return (
|
||||
<div>
|
||||
<div
|
||||
style={{
|
||||
fontSize: 13,
|
||||
color: "var(--text-secondary)",
|
||||
marginBottom: 6,
|
||||
}}
|
||||
>
|
||||
语言
|
||||
</div>
|
||||
<select
|
||||
value={language}
|
||||
onChange={(e) => onChange(e.target.value as TtsLanguage)}
|
||||
style={{
|
||||
width: "100%",
|
||||
padding: "7px 10px",
|
||||
borderRadius: 6,
|
||||
border: "1px solid var(--border-color, #e5e7eb)",
|
||||
background: "var(--bg-primary, #fff)",
|
||||
color: "var(--text-primary)",
|
||||
fontSize: 13,
|
||||
outline: "none",
|
||||
cursor: "pointer",
|
||||
}}
|
||||
>
|
||||
{TTS_LANGUAGE_OPTIONS.map((opt) => (
|
||||
<option key={opt.value} value={opt.value}>
|
||||
{opt.label}
|
||||
</option>
|
||||
))}
|
||||
</select>
|
||||
</div>
|
||||
)
|
||||
}
|
||||
|
||||
export default LanguageControl
|
||||
@@ -1,22 +0,0 @@
|
||||
/** TTS 情绪选项(对齐后端 CosyVoice 支持:natural/excited/calm/friendly) */
|
||||
export const TTS_EMOTION_OPTIONS = [
|
||||
{ value: "natural", label: "自然" },
|
||||
{ value: "excited", label: "兴奋" },
|
||||
{ value: "calm", label: "沉稳" },
|
||||
{ value: "friendly", label: "亲切" },
|
||||
] as const
|
||||
|
||||
export type TtsEmotion = (typeof TTS_EMOTION_OPTIONS)[number]["value"]
|
||||
|
||||
/** TTS 语言选项 */
|
||||
export const TTS_LANGUAGE_OPTIONS = [
|
||||
{ value: "zh-CN", label: "中文" },
|
||||
{ value: "en", label: "英文" },
|
||||
{ value: "ja", label: "日文" },
|
||||
{ value: "ko", label: "韩文" },
|
||||
] as const
|
||||
|
||||
export type TtsLanguage = (typeof TTS_LANGUAGE_OPTIONS)[number]["value"]
|
||||
|
||||
export const DEFAULT_TTS_EMOTION: TtsEmotion = "natural"
|
||||
export const DEFAULT_TTS_LANGUAGE: TtsLanguage = "zh-CN"
|
||||
@@ -1,6 +1,5 @@
|
||||
import { type PresetVoiceDisplay } from "@/pages/voices/types"
|
||||
import type { TtsClonedVoiceOption } from "./VoiceSelector"
|
||||
import type { TtsEmotion, TtsLanguage } from "./constants"
|
||||
|
||||
export type TtsStatus = "idle" | "synthesizing" | "done" | "error"
|
||||
|
||||
@@ -9,8 +8,6 @@ export interface TtsModalProps {
|
||||
ttsText: string
|
||||
ttsVoiceId: string
|
||||
ttsSpeed: number
|
||||
ttsEmotion: TtsEmotion
|
||||
ttsLanguage: TtsLanguage
|
||||
ttsStatus: TtsStatus
|
||||
ttsAudioUrl: string | null
|
||||
ttsError: string | null
|
||||
@@ -21,8 +18,6 @@ export interface TtsModalProps {
|
||||
onTextChange: (text: string) => void
|
||||
onVoiceChange: (voiceId: string) => void
|
||||
onSpeedChange: (speed: number) => void
|
||||
onEmotionChange: (emotion: TtsEmotion) => void
|
||||
onLanguageChange: (language: TtsLanguage) => void
|
||||
onSynthesize: () => void
|
||||
onSave: () => void
|
||||
}
|
||||
|
||||
@@ -4,12 +4,6 @@ import { message } from "antd"
|
||||
import { synthesizeSpeech, getTTSJobStatus, saveTtsToLibrary } from "@/api/tts"
|
||||
import { type PresetVoiceDisplay } from "../types"
|
||||
import type { TtsClonedVoiceOption } from "../components/tts-modal/VoiceSelector"
|
||||
import {
|
||||
DEFAULT_TTS_EMOTION,
|
||||
DEFAULT_TTS_LANGUAGE,
|
||||
type TtsEmotion,
|
||||
type TtsLanguage,
|
||||
} from "../components/tts-modal/constants"
|
||||
|
||||
export type TtsStatus = "idle" | "synthesizing" | "done" | "error"
|
||||
|
||||
@@ -35,8 +29,6 @@ export function useTtsSynthesize({
|
||||
const [ttsText, setTtsText] = useState("")
|
||||
const [ttsVoiceId, setTtsVoiceId] = useState<string>("")
|
||||
const [ttsSpeed, setTtsSpeed] = useState(1.0)
|
||||
const [ttsEmotion, setTtsEmotion] = useState<TtsEmotion>(DEFAULT_TTS_EMOTION)
|
||||
const [ttsLanguage, setTtsLanguage] = useState<TtsLanguage>(DEFAULT_TTS_LANGUAGE)
|
||||
const [ttsJobId, setTtsJobId] = useState<string | null>(null)
|
||||
const [ttsStatus, setTtsStatus] = useState<TtsStatus>("idle")
|
||||
const [ttsAudioUrl, setTtsAudioUrl] = useState<string | null>(null)
|
||||
@@ -59,8 +51,6 @@ export function useTtsSynthesize({
|
||||
text: ttsText.trim(),
|
||||
voice_id: ttsVoiceId || undefined,
|
||||
speed: ttsSpeed,
|
||||
emotion: ttsEmotion,
|
||||
language: ttsLanguage,
|
||||
})
|
||||
setTtsJobId(resp.job_id)
|
||||
|
||||
@@ -91,7 +81,7 @@ export function useTtsSynthesize({
|
||||
setTtsStatus("error")
|
||||
setTtsError(msg)
|
||||
}
|
||||
}, [ttsText, ttsVoiceId, ttsSpeed, ttsEmotion, ttsLanguage])
|
||||
}, [ttsText, ttsVoiceId, ttsSpeed])
|
||||
|
||||
/** 保存 TTS 结果到素材库 */
|
||||
const handleTtsSave = useCallback(async () => {
|
||||
@@ -113,8 +103,6 @@ export function useTtsSynthesize({
|
||||
setTtsText("")
|
||||
setTtsVoiceId("")
|
||||
setTtsSpeed(1.0)
|
||||
setTtsEmotion(DEFAULT_TTS_EMOTION)
|
||||
setTtsLanguage(DEFAULT_TTS_LANGUAGE)
|
||||
setTtsStatus("idle")
|
||||
setTtsAudioUrl(null)
|
||||
setTtsError(null)
|
||||
@@ -144,8 +132,6 @@ export function useTtsSynthesize({
|
||||
ttsText,
|
||||
ttsVoiceId,
|
||||
ttsSpeed,
|
||||
ttsEmotion,
|
||||
ttsLanguage,
|
||||
ttsJobId,
|
||||
ttsStatus,
|
||||
ttsAudioUrl,
|
||||
@@ -157,8 +143,6 @@ export function useTtsSynthesize({
|
||||
setTtsText,
|
||||
setTtsVoiceId,
|
||||
setTtsSpeed,
|
||||
setTtsEmotion,
|
||||
setTtsLanguage,
|
||||
setTtsOpen,
|
||||
// Actions
|
||||
handleTtsSynthesize,
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
/**
|
||||
* FrontendPreviewPlayer 音频行为单测(Issue #1741 / #1750)
|
||||
*
|
||||
* useSegmentScheduler 用 mock 控制播放态,专注验证本组件的音频逻辑:
|
||||
* useSegmentScheduler/useCanvasPlayer 用 mock 控制播放态,专注验证本组件的音频逻辑:
|
||||
* - 有配音时 video 保持 muted(素材原声不与配音混音)
|
||||
* - 无配音时 video 不 muted(素材原声兜底,保证任何情况下播放有声)
|
||||
* - 静音按钮:默认有声;点击后切 muted,aria-label 与图标切换
|
||||
|
||||
@@ -221,18 +221,17 @@ class RenderAdapter:
|
||||
|
||||
except subprocess.CalledProcessError as exc:
|
||||
stderr_text = (exc.stderr or "").strip()
|
||||
stderr_tail = stderr_text[-5000:] if len(stderr_text) > 5000 else stderr_text
|
||||
logger.error(
|
||||
"[render-adapter] ffmpeg渲染失败: plan_id=%s job_id=%s exit_code=%d\nstderr:\n%s",
|
||||
plan_id,
|
||||
job_id,
|
||||
exc.returncode,
|
||||
stderr_tail,
|
||||
stderr_text[-2000:] if len(stderr_text) > 2000 else stderr_text,
|
||||
)
|
||||
return RenderAdapterResult(
|
||||
success=False,
|
||||
error_message=f"FFmpeg渲染失败(exit={exc.returncode}): {stderr_text[-500:]}",
|
||||
error_detail=stderr_tail,
|
||||
error_message=f"FFmpeg渲染失败(exit={exc.returncode}): {stderr_text[:200]}",
|
||||
error_detail=stderr_text[-2000:] if len(stderr_text) > 2000 else stderr_text,
|
||||
)
|
||||
except Exception as exc:
|
||||
logger.exception(
|
||||
@@ -722,17 +721,16 @@ class RenderAdapter:
|
||||
|
||||
except subprocess.CalledProcessError as exc:
|
||||
stderr_text = (exc.stderr or "").strip()
|
||||
stderr_tail = stderr_text[-5000:] if len(stderr_text) > 5000 else stderr_text
|
||||
logger.error(
|
||||
"[render-adapter] 内存模式渲染失败: plan_id=%s exit_code=%d\nstderr:\n%s",
|
||||
actual_plan_id,
|
||||
exc.returncode,
|
||||
stderr_tail,
|
||||
stderr_text[-2000:] if len(stderr_text) > 2000 else stderr_text,
|
||||
)
|
||||
return RenderAdapterResult(
|
||||
success=False,
|
||||
error_message=f"FFmpeg渲染失败(exit={exc.returncode}): {stderr_text[-500:]}",
|
||||
error_detail=stderr_tail,
|
||||
error_message=f"FFmpeg渲染失败(exit={exc.returncode}): {stderr_text[:200]}",
|
||||
error_detail=stderr_text[-2000:] if len(stderr_text) > 2000 else stderr_text,
|
||||
)
|
||||
except Exception as exc:
|
||||
logger.exception(
|
||||
|
||||
@@ -321,14 +321,8 @@ def build_subtitles_from_plan(
|
||||
|
||||
has_any = False
|
||||
|
||||
# 1. 标题(#1901 统一读 "title",兼容老数据 "title_config")
|
||||
title_cfg = plan_config.get("title") or {}
|
||||
if not isinstance(title_cfg, dict) or not (title_cfg.get("text") or "").strip():
|
||||
_alt = plan_config.get("title_config") or {}
|
||||
if isinstance(_alt, dict):
|
||||
title_cfg = _alt
|
||||
if not isinstance(title_cfg, dict):
|
||||
title_cfg = {}
|
||||
# 1. 标题
|
||||
title_cfg = plan_config.get("title_config") or {}
|
||||
if isinstance(title_cfg, dict):
|
||||
title_text = str(title_cfg.get("text", ""))
|
||||
title_enabled = title_cfg.get("enabled", True)
|
||||
|
||||
@@ -572,12 +572,7 @@ class UnifiedRenderService:
|
||||
ASS 文件路径,没有字幕时返回 None
|
||||
"""
|
||||
config = self.plan.config or {}
|
||||
# #1901 统一读 "title",兼容老数据 "title_config"
|
||||
title_cfg = config.get("title", {}) or {}
|
||||
if not isinstance(title_cfg, dict) or not (title_cfg.get("text") or "").strip():
|
||||
_alt = config.get("title_config") or {}
|
||||
if isinstance(_alt, dict):
|
||||
title_cfg = _alt
|
||||
if not isinstance(title_cfg, dict):
|
||||
title_cfg = {}
|
||||
subtitle_cfg = config.get("subtitle", {}) or {}
|
||||
@@ -2306,13 +2301,13 @@ class UnifiedRenderService:
|
||||
filters.append(f"eq=contrast={contrast:.3f}")
|
||||
|
||||
elif filt == "color_balance":
|
||||
# RGB 通道偏移:colorbalance=rs=...:gs=...:bs=...
|
||||
# RGB 通道偏移:color_balance=rs=...:gs=...:bs=...
|
||||
r = pixel_pert.get("color_r", 0)
|
||||
g = pixel_pert.get("color_g", 0)
|
||||
b = pixel_pert.get("color_b", 0)
|
||||
if r != 0 or g != 0 or b != 0:
|
||||
# color_balance 参数范围 -1.0 ~ 1.0,这里用 /100 转换
|
||||
filters.append(f"colorbalance=rs={r/100:.3f}:gs={g/100:.3f}:bs={b/100:.3f}")
|
||||
filters.append(f"color_balance=rs={r/100:.3f}:gs={g/100:.3f}:bs={b/100:.3f}")
|
||||
|
||||
@staticmethod
|
||||
def _clip_volume(clip: ResolvedClip) -> float:
|
||||
|
||||
@@ -705,8 +705,7 @@ def _render_from_edit_plan(
|
||||
)
|
||||
|
||||
if not result.success:
|
||||
detail_suffix = f"\n[detail] {result.error_detail}" if result.error_detail else ""
|
||||
raise RuntimeError(f"渲染失败: {result.error_message}{detail_suffix}")
|
||||
raise RuntimeError(f"渲染失败: {result.error_message}")
|
||||
|
||||
render_elapsed = time.monotonic() - render_start
|
||||
logger.info(
|
||||
|
||||
@@ -1,907 +0,0 @@
|
||||
# 会员制 + 积分方案设计文档
|
||||
|
||||
> **Issue**: [#1895](https://git.xiaoxiajianji.com/xiaoxia/xiaoxia-saas/issues/1895)
|
||||
> **版本**: v1.0
|
||||
> **状态**: 方案设计(待确认)
|
||||
> **创建时间**: 2026-09-14
|
||||
|
||||
---
|
||||
|
||||
## 一、设计背景与目标
|
||||
|
||||
### 1.1 背景
|
||||
|
||||
当前系统采用**纯订阅制**计费模式(4 档:free/standard/pro/enterprise),存在以下问题:
|
||||
|
||||
1. **灵活性不足**:用户付费后只能按套餐配额使用,无法按需消费高频 AI 能力
|
||||
2. **前后端不一致**:前端 Plans.tsx 写死 3 档,后端硬编码 4 档
|
||||
3. **积分能力缺失**:`quota.py` 已预留 `AI_VOICE_CREDITS` 枚举,`module_registry.py` 已注册消耗规则,但无实际账户、流水、扣费和充值链路
|
||||
4. **收入天花板**:纯订阅制难以覆盖 AI 调用成本波动,高频用户和低频用户无法差异化变现
|
||||
|
||||
### 1.2 目标
|
||||
|
||||
- **会员制**保留基础权益(存储、项目数、并发数等),提供稳定收入
|
||||
- **积分制**覆盖 AI 消耗型功能(配音、数字人、视频生成等),按需付费、用多少扣多少
|
||||
- 两者结合,既降低轻度用户入门门槛,又提升重度用户 ARPU
|
||||
- 在现有 `QuotaChecker` + `ModuleRegistry` 架构上扩展,不推倒重来
|
||||
|
||||
---
|
||||
|
||||
## 二、会员等级设计
|
||||
|
||||
### 2.1 等级定义
|
||||
|
||||
保留 4 档,与现有后端 `PLAN_QUOTAS` 对齐,重新定义权益:
|
||||
|
||||
| 等级 | 月付价格 | 年付价格 | 定位 |
|
||||
|------|----------|----------|------|
|
||||
| **免费版(free)** | ¥0 | ¥0 | 体验用户,验证产品价值 |
|
||||
| **标准版(standard)** | ¥99/月 | ¥999/年(约 ¥83/月) | 个人创作者 |
|
||||
| **专业版(pro)** | ¥299/月 | ¥2,999/年(约 ¥250/月) | 专业团队 |
|
||||
| **企业版(enterprise)** | ¥999/月 | ¥9,999/年(约 ¥833/月) | 企业 / 工作室 |
|
||||
|
||||
### 2.2 会员权益对照表
|
||||
|
||||
| 权益维度 | 免费版 | 标准版 | 专业版 | 企业版 |
|
||||
|----------|--------|--------|--------|--------|
|
||||
| 项目数量 | 3 个 | 10 个 | 不限 | 不限 |
|
||||
| 存储空间 | 10 GB | 50 GB | 100 GB | 1 TB |
|
||||
| 并发任务数 | 3 | 10 | 20 | 50 |
|
||||
| 导出分辨率 | 720p | 1080p | 4K | 4K |
|
||||
| 模板数量 | 3 个 | 15 个 | 不限 | 不限 |
|
||||
| 标题库 | 50 条 | 500 条 | 500 条 | 不限 |
|
||||
| 配音库 | 10 条 | 100 条 | 100 条 | 不限 |
|
||||
| AI 配音 | ✗ | ✓ | ✓ | ✓ |
|
||||
| 批量导出 | ✗ | ✓ | ✓ | ✓ |
|
||||
| 多平台发布 | ✗ | ✗ | ✓ | ✓ |
|
||||
| 去重检测报告 | ✗ | ✗ | ✓ | ✓ |
|
||||
| **每月赠送积分** | 0 | 200 | 800 | 3,000 |
|
||||
| 技术支持 | 社区 | 邮件 | 优先响应 | 专属客服 |
|
||||
|
||||
> 注:`AI_VOICE_ENABLED`、`BATCH_EXPORT_ENABLED`、`MULTI_PLATFORM_ENABLED`、`DEDUP_REPORT_ENABLED` 等开关类权益由现有 `QuotaRegistry` 直接控制,无需积分参与。
|
||||
|
||||
### 2.3 与现有代码的映射
|
||||
|
||||
- 后端 `PLAN_QUOTAS` 字典扩展,新增 `monthly_credits` 字段
|
||||
- 前端 `Plans.tsx` 对齐后端 4 档,与后端保持一致
|
||||
- 现有 `QuotaTier.limits` 中扩展 `monthly_credits` 维度,由 `QuotaRegistry` 统一管理
|
||||
|
||||
---
|
||||
|
||||
## 三、积分体系设计
|
||||
|
||||
### 3.1 积分获取方式
|
||||
|
||||
| 获取方式 | 说明 | 频率 |
|
||||
|----------|------|------|
|
||||
| **会员每月赠送** | 各等级每月自动到账(见上表) | 每月 1 日 00:00 自动发放 |
|
||||
| **单独充值** | 用户按需购买积分包 | 随时可买 |
|
||||
| **任务奖励** | 完成指定任务赠送(新手引导、邀请好友、反馈 Bug 等) | 一次性 |
|
||||
|
||||
### 3.2 积分包定价
|
||||
|
||||
| 积分包 | 积分数量 | 价格 | 单价 | 备注 |
|
||||
|--------|----------|------|------|------|
|
||||
| 体验包 | 50 积分 | ¥9.9 | ¥0.198/积分 | 首次购买限购 1 次 |
|
||||
| 基础包 | 200 积分 | ¥36 | ¥0.18/积分 | |
|
||||
| 标准包 | 500 积分 | ¥80 | ¥0.16/积分 | |
|
||||
| 专业包 | 1,500 积分 | ¥210 | ¥0.14/积分 | 热门 |
|
||||
| 企业包 | 5,000 积分 | ¥600 | ¥0.12/积分 | |
|
||||
|
||||
> 积分永久有效,不随会员过期清零。会员过期后停止每月赠送,但已有积分不受影响。
|
||||
|
||||
### 3.3 任务奖励规则
|
||||
|
||||
| 任务 | 奖励积分 | 次数限制 |
|
||||
|------|----------|----------|
|
||||
| 新用户注册 | 50 | 1 次 |
|
||||
| 完善个人信息 | 20 | 1 次 |
|
||||
| 邀请新用户注册 | 30/人 | 每月限 10 人 |
|
||||
| 首次完成视频生成 | 20 | 1 次 |
|
||||
| 提交有效 Bug 反馈 | 50 | 不限(审核通过后发放) |
|
||||
|
||||
---
|
||||
|
||||
## 四、积分消耗场景
|
||||
|
||||
### 4.1 消耗清单
|
||||
|
||||
| 功能模块 | 消耗场景 | 每次消耗积分 | 说明 |
|
||||
|----------|----------|-------------|------|
|
||||
| **AI 配音** | 生成一条配音 | 1 | 已存在于 `module_registry.py` |
|
||||
| **AI 数字人** | 生成一段数字人视频片段 | 5 | 新场景 |
|
||||
| **视频生成** | 生成一段 AI 视频(≤10s) | 10 | 新场景 |
|
||||
| **视频生成(长时长)** | 每增加 10s | +5 | 累进计费 |
|
||||
| **抖音文案提取** | 提取一次 | 1 | 新场景 |
|
||||
| **AI 改写** | 改写一段文案 | 1 | 新场景 |
|
||||
| **AI 标题生成** | 批量生成一次(≤10 条) | 1 | 新场景 |
|
||||
| **AI 封面生成** | 生成一张封面 | 2 | 新场景 |
|
||||
| **AI 字幕翻译** | 翻译一条字幕(≤50 字) | 1 | 新场景 |
|
||||
|
||||
### 4.2 消耗规则扩展机制
|
||||
|
||||
复用现有 `ModuleRegistry` + `QuotaRule` 模式:
|
||||
|
||||
```python
|
||||
# 新增模块注册示例
|
||||
module_registry.register(Module(
|
||||
name="ai_digital_human",
|
||||
version="1.0.0",
|
||||
description="AI 数字人生成模块",
|
||||
capabilities=[
|
||||
ModuleCapability(
|
||||
name="generate_digital_human",
|
||||
description="生成数字人视频片段",
|
||||
quota_rules=[QuotaRule("points", 5.0, "每段数字人视频消耗 5 积分")],
|
||||
),
|
||||
],
|
||||
))
|
||||
```
|
||||
|
||||
新增 `QuotaDimension.POINTS = "points"` 作为通用积分维度,所有消耗型功能统一通过积分维度扣费。
|
||||
|
||||
### 4.3 消费折扣(预留)
|
||||
|
||||
未来可扩展按会员等级设置折扣:
|
||||
|
||||
| 等级 | 积分消耗折扣 |
|
||||
|------|-------------|
|
||||
| 免费版 | 无折扣 |
|
||||
| 标准版 | 9.5 折 |
|
||||
| 专业版 | 9 折 |
|
||||
| 企业版 | 8 折 |
|
||||
|
||||
> 折扣仅在会员有效期内生效,过期后恢复原价。实现时通过 `discount_rate` 配置字段支持。
|
||||
|
||||
---
|
||||
|
||||
## 五、数据库表设计
|
||||
|
||||
### 5.1 新增表结构
|
||||
|
||||
#### 5.1.1 积分账户表 `points_accounts`
|
||||
|
||||
每个用户一个积分账户,记录余额和累计值。
|
||||
|
||||
```sql
|
||||
CREATE TABLE IF NOT EXISTS points_accounts (
|
||||
id VARCHAR(36) PRIMARY KEY,
|
||||
user_id VARCHAR(36) NOT NULL UNIQUE REFERENCES users(id) ON DELETE CASCADE,
|
||||
balance INTEGER NOT NULL DEFAULT 0, -- 当前可用积分
|
||||
total_earned INTEGER NOT NULL DEFAULT 0, -- 累计获得积分
|
||||
total_spent INTEGER NOT NULL DEFAULT 0, -- 累计消耗积分
|
||||
total_recharged INTEGER NOT NULL DEFAULT 0, -- 累计充值积分
|
||||
total_gifted INTEGER NOT NULL DEFAULT 0, -- 累计赠送积分(会员赠送 + 任务奖励)
|
||||
created_at TIMESTAMP NOT NULL DEFAULT NOW(),
|
||||
updated_at TIMESTAMP NOT NULL DEFAULT NOW()
|
||||
);
|
||||
|
||||
CREATE INDEX idx_points_accounts_user ON points_accounts(user_id);
|
||||
```
|
||||
|
||||
**设计说明**:
|
||||
- `user_id` 设为 UNIQUE,每个用户只有一个积分账户
|
||||
- 余额通过 `total_earned - total_spent` 可交叉校验 `balance`,保证数据一致性
|
||||
- 不使用悲观锁,而是通过事务 + 乐观锁(`updated_at`)保证并发安全
|
||||
|
||||
#### 5.1.2 积分流水表 `points_transactions`
|
||||
|
||||
每笔积分变动都记录一条流水,支持对账和审计。
|
||||
|
||||
```sql
|
||||
CREATE TABLE IF NOT EXISTS points_transactions (
|
||||
id VARCHAR(36) PRIMARY KEY,
|
||||
user_id VARCHAR(36) NOT NULL REFERENCES users(id) ON DELETE CASCADE,
|
||||
account_id VARCHAR(36) NOT NULL REFERENCES points_accounts(id) ON DELETE CASCADE,
|
||||
type VARCHAR(20) NOT NULL, -- earn(获得) / spend(消耗) / refund(退还) / expire(过期)
|
||||
source VARCHAR(50) NOT NULL, -- recharge(充值) / membership_gift(会员赠送) / task_reward(任务奖励) / ai_voice / ai_digital_human / ai_video / ...
|
||||
amount INTEGER NOT NULL, -- 变动数量(正数)
|
||||
balance_after INTEGER NOT NULL, -- 变动后余额
|
||||
description VARCHAR(255) DEFAULT '', -- 描述
|
||||
ref_id VARCHAR(100) DEFAULT '', -- 关联业务 ID(订单号、任务 ID 等)
|
||||
created_at TIMESTAMP NOT NULL DEFAULT NOW()
|
||||
);
|
||||
|
||||
CREATE INDEX idx_points_tx_user ON points_transactions(user_id);
|
||||
CREATE INDEX idx_points_tx_type ON points_transactions(type);
|
||||
CREATE INDEX idx_points_tx_source ON points_transactions(source);
|
||||
CREATE INDEX idx_points_tx_created ON points_transactions(created_at);
|
||||
```
|
||||
|
||||
**设计说明**:
|
||||
- `source` 字段标识具体来源/场景,新增消耗场景时只需新增 source 值,不需要改表结构
|
||||
- `ref_id` 关联具体业务,方便追溯(如充值关联订单号,消费关联生成任务 ID)
|
||||
- 流水只追加不修改,保证审计完整性
|
||||
|
||||
#### 5.1.3 积分订单表 `points_orders`
|
||||
|
||||
记录用户充值积分的支付订单。
|
||||
|
||||
```sql
|
||||
CREATE TABLE IF NOT EXISTS points_orders (
|
||||
id VARCHAR(36) PRIMARY KEY,
|
||||
user_id VARCHAR(36) NOT NULL REFERENCES users(id) ON DELETE CASCADE,
|
||||
package_name VARCHAR(50) NOT NULL, -- 积分包名称
|
||||
points_amount INTEGER NOT NULL, -- 积分数量
|
||||
price_cents INTEGER NOT NULL, -- 支付金额(分),避免浮点精度问题
|
||||
currency VARCHAR(10) NOT NULL DEFAULT 'CNY',
|
||||
status VARCHAR(20) NOT NULL DEFAULT 'pending', -- pending / paid / failed / refunded
|
||||
payment_method VARCHAR(50), -- alipay / wechat_pay / ...
|
||||
payment_id VARCHAR(100), -- 第三方支付流水号
|
||||
paid_at TIMESTAMP,
|
||||
created_at TIMESTAMP NOT NULL DEFAULT NOW(),
|
||||
expire_at TIMESTAMP -- 订单过期时间(未支付自动关闭)
|
||||
);
|
||||
|
||||
CREATE INDEX idx_points_orders_user ON points_orders(user_id);
|
||||
CREATE INDEX idx_points_orders_status ON points_orders(status);
|
||||
```
|
||||
|
||||
#### 5.1.4 积分消耗配置表 `points_consumption_config`
|
||||
|
||||
集中管理各场景的积分消耗规则,支持动态调整。
|
||||
|
||||
```sql
|
||||
CREATE TABLE IF NOT EXISTS points_consumption_config (
|
||||
id VARCHAR(36) PRIMARY KEY,
|
||||
scene_key VARCHAR(50) NOT NULL UNIQUE, -- 场景标识,如 ai_voice, ai_video
|
||||
scene_name VARCHAR(100) NOT NULL, -- 场景显示名称
|
||||
points_per_use INTEGER NOT NULL DEFAULT 1, -- 每次消耗积分数
|
||||
is_active BOOLEAN NOT NULL DEFAULT TRUE, -- 是否启用
|
||||
description VARCHAR(255) DEFAULT '',
|
||||
created_at TIMESTAMP NOT NULL DEFAULT NOW(),
|
||||
updated_at TIMESTAMP NOT NULL DEFAULT NOW()
|
||||
);
|
||||
```
|
||||
|
||||
### 5.2 现有表变更
|
||||
|
||||
#### 5.2.1 users 表新增字段
|
||||
|
||||
```sql
|
||||
-- 会员等级字段保留现有 subscription_plan,无需改动
|
||||
-- 无需在 users 表加 credits 字段,积分独立在 points_accounts 表管理
|
||||
```
|
||||
|
||||
### 5.3 表关系
|
||||
|
||||
```
|
||||
users (1) ──── (1) points_accounts
|
||||
│
|
||||
└── (1:N) points_transactions
|
||||
│
|
||||
└── ref_id ──> generation_tasks / points_orders / ...
|
||||
|
||||
users (1) ──── (1:N) points_orders
|
||||
```
|
||||
|
||||
### 5.4 与现有模型的映射
|
||||
|
||||
| 现有模型 | 改动 |
|
||||
|----------|------|
|
||||
| `UserModel` | 不新增积分字段,积分由独立表管理 |
|
||||
| `BillingRecordModel` | 保留,用于订阅支付记录;积分充值走新的 `points_orders` |
|
||||
| `QuotaDimension` | 新增 `POINTS = "points"` 维度 |
|
||||
| `QuotaTier` | 各等级新增 `monthly_credits` 配额 |
|
||||
| `QuotaRule` | `dimension` 支持 `"points"` 值 |
|
||||
|
||||
---
|
||||
|
||||
## 六、API 设计
|
||||
|
||||
### 6.1 积分账户 API
|
||||
|
||||
#### `GET /api/v1/points/balance`
|
||||
|
||||
获取当前积分余额。
|
||||
|
||||
```json
|
||||
// Response
|
||||
{
|
||||
"balance": 580,
|
||||
"total_earned": 1200,
|
||||
"total_spent": 620,
|
||||
"membership_monthly_gift": 200,
|
||||
"membership_expires_at": "2027-01-15T00:00:00Z"
|
||||
}
|
||||
```
|
||||
|
||||
#### `GET /api/v1/points/transactions`
|
||||
|
||||
查询积分流水,支持分页和筛选。
|
||||
|
||||
```
|
||||
?page=1&page_size=20&type=spend&source=ai_voice&start_date=2026-09-01&end_date=2026-09-30
|
||||
```
|
||||
|
||||
```json
|
||||
// Response
|
||||
{
|
||||
"total": 156,
|
||||
"page": 1,
|
||||
"page_size": 20,
|
||||
"items": [
|
||||
{
|
||||
"id": "tx_xxx",
|
||||
"type": "spend",
|
||||
"source": "ai_voice",
|
||||
"amount": 1,
|
||||
"balance_after": 579,
|
||||
"description": "AI 配音 - 温柔女声",
|
||||
"ref_id": "task_xxx",
|
||||
"created_at": "2026-09-14T10:30:00Z"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
### 6.2 积分充值 API
|
||||
|
||||
#### `POST /api/v1/points/recharge`
|
||||
|
||||
创建积分充值订单。
|
||||
|
||||
```json
|
||||
// Request
|
||||
{
|
||||
"package_id": "standard_pack" // 或自定义 amount
|
||||
}
|
||||
|
||||
// Response
|
||||
{
|
||||
"order_id": "po_xxx",
|
||||
"package_name": "标准包",
|
||||
"points_amount": 500,
|
||||
"price_cents": 8000,
|
||||
"payment_url": "https://pay.alipay.com/...",
|
||||
"expire_at": "2026-09-14T16:30:00Z"
|
||||
}
|
||||
```
|
||||
|
||||
#### `POST /api/v1/points/payment-callback`
|
||||
|
||||
支付回调(内部接口 + 第三方支付通知)。
|
||||
|
||||
```json
|
||||
// Request (来自支付平台)
|
||||
{
|
||||
"order_id": "po_xxx",
|
||||
"payment_method": "alipay",
|
||||
"payment_id": "2026xxx",
|
||||
"status": "paid"
|
||||
}
|
||||
```
|
||||
|
||||
回调处理流程:
|
||||
1. 验证支付签名
|
||||
2. 更新 `points_orders.status = "paid"`
|
||||
3. 增加 `points_accounts.balance += points_amount`
|
||||
4. 写入 `points_transactions` 流水(type=earn, source=recharge)
|
||||
|
||||
### 6.3 积分消费 API
|
||||
|
||||
#### 内部扣费接口(供各功能模块调用)
|
||||
|
||||
```python
|
||||
# packages/domain/points_service.py
|
||||
class PointsService:
|
||||
def deduct(self, user_id: str, scene_key: str, amount: int, ref_id: str = "") -> DeductResult:
|
||||
"""
|
||||
扣减积分
|
||||
1. 检查积分余额是否充足
|
||||
2. 在事务中扣减余额、写入流水
|
||||
3. 返回扣减结果
|
||||
"""
|
||||
pass
|
||||
|
||||
def check_balance(self, user_id: str, scene_key: str) -> CheckResult:
|
||||
"""
|
||||
检查余额是否充足某场景消耗
|
||||
"""
|
||||
pass
|
||||
```
|
||||
|
||||
#### `GET /api/v1/points/consumption-rules`
|
||||
|
||||
查询当前所有积分消耗规则(前端展示用)。
|
||||
|
||||
```json
|
||||
// Response
|
||||
{
|
||||
"rules": [
|
||||
{ "scene_key": "ai_voice", "scene_name": "AI 配音", "points_per_use": 1 },
|
||||
{ "scene_key": "ai_digital_human", "scene_name": "AI 数字人", "points_per_use": 5 },
|
||||
{ "scene_key": "ai_video", "scene_name": "视频生成", "points_per_use": 10 },
|
||||
...
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
### 6.4 会员订阅 API(改造)
|
||||
|
||||
保留现有 `subscription.py` 路由结构,新增以下逻辑:
|
||||
|
||||
- `POST /subscription/change-plan`:变更套餐时,自动创建/更新积分账户,发放当月赠送积分
|
||||
- `GET /subscription/current`:返回中增加 `monthly_credits` 和 `points_balance` 字段
|
||||
- 新增 `POST /subscription/claim-monthly-credits`:手动领取每月赠送积分(兜底入口)
|
||||
|
||||
### 6.5 API 路由汇总
|
||||
|
||||
| 方法 | 路径 | 说明 | 类型 |
|
||||
|------|------|------|------|
|
||||
| GET | `/api/v1/points/balance` | 查询积分余额 | 用户 |
|
||||
| GET | `/api/v1/points/transactions` | 积分流水查询 | 用户 |
|
||||
| POST | `/api/v1/points/recharge` | 创建充值订单 | 用户 |
|
||||
| POST | `/api/v1/points/payment-callback` | 支付回调 | 内部 |
|
||||
| GET | `/api/v1/points/consumption-rules` | 消耗规则查询 | 用户 |
|
||||
| POST | `/api/v1/points/check` | 消费前余额检查 | 内部 |
|
||||
| POST | `/api/v1/points/deduct` | 消费扣减 | 内部 |
|
||||
| POST | `/api/v1/points/refund` | 消费退还 | 内部 |
|
||||
|
||||
---
|
||||
|
||||
## 七、前端页面设计
|
||||
|
||||
### 7.1 会员购买页(改造 Plans.tsx)
|
||||
|
||||
**路由**: `/app/subscription`(保持不变)
|
||||
|
||||
**改动要点**:
|
||||
1. 将 3 档对齐为 4 档,与后端一致
|
||||
2. 每档卡片增加"每月赠送 XXX 积分"标识
|
||||
3. 按钮文案按当前状态动态显示("当前方案"/"升级"/"降级"/"联系我们")
|
||||
4. 底部增加积分包购买入口
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────────────────────────────┐
|
||||
│ 选择适合您的方案 │
|
||||
├──────────┬──────────┬──────────┬──────────┐ │
|
||||
│ 免费版 │ 标准版 │ 专业版 ★ │ 企业版 │ │
|
||||
│ ¥0/月 │ ¥99/月 │ ¥299/月 │ ¥999/月 │ │
|
||||
│ │ │ │ │ │
|
||||
│ 3 项目 │ 10 项目 │ 无限项目 │ 无限项目 │ │
|
||||
│ 10GB │ 50GB │ 100GB │ 1TB │ │
|
||||
│ 0 积分 │ 200积分 │ 800积分 │ 3000积分 │ ← 新增 │
|
||||
│ │ │ │ │ │
|
||||
│ [当前] │ [升级] │ [升级] │ [联系] │ │
|
||||
├──────────┴──────────┴──────────┴──────────┘ │
|
||||
│ │
|
||||
│ 💰 积分充值 [查看全部积分包] │
|
||||
│ ┌──────┐ ┌──────┐ ┌──────┐ ┌──────┐ ┌──────┐ │
|
||||
│ │50积分 │ │200积分│ │500积分│ │1500积分│ │5000积分│ │
|
||||
│ │ ¥9.9 │ │ ¥36 │ │ ¥80 │ │ ¥210 │ │ ¥600 │ │
|
||||
│ └──────┘ └──────┘ └──────┘ └──────┘ └──────┘ │
|
||||
└─────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
### 7.2 积分余额展示位置
|
||||
|
||||
#### 顶部导航栏(Header 组件)
|
||||
|
||||
在用户头像旁边增加积分余额徽章:
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────────────────┐
|
||||
│ Logo 工作台 模板 素材 🔔 💎 580 👤 │
|
||||
└─────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
- 点击积分徽章展开快捷面板,显示余额、本月已用、充值入口
|
||||
- 积分不足时徽章变为警告色(橙色)
|
||||
|
||||
#### 功能入口处的消耗提示
|
||||
|
||||
在每个 AI 功能的操作按钮旁,显示本次操作将消耗的积分:
|
||||
|
||||
```
|
||||
[生成配音] 💎 -1 积分
|
||||
[生成视频] 💎 -10 积分
|
||||
```
|
||||
|
||||
### 7.3 积分中心页面
|
||||
|
||||
**路由**: `/app/points`(新增)
|
||||
|
||||
**页面结构**:
|
||||
|
||||
```
|
||||
┌─────────────────────────────────────────────────┐
|
||||
│ 积分中心 │
|
||||
├─────────────────────────────────────────────────┤
|
||||
│ │
|
||||
│ 当前余额 本月获得 本月消耗 │
|
||||
│ 💎 580 +200 -120 │
|
||||
│ │
|
||||
├─────────────────────────────────────────────────┤
|
||||
│ │
|
||||
│ [积分明细] [充值记录] [消耗规则] │
|
||||
│ ───────── │
|
||||
│ │
|
||||
│ 时间 类型 场景 数量 余额 │
|
||||
│ 09-14 10:30 消耗 AI配音 -1 579 │
|
||||
│ 09-14 09:15 消耗 AI视频 -10 580 │
|
||||
│ 09-01 00:00 获得 会员赠送 +200 590 │
|
||||
│ 08-28 14:20 获得 充值+500 +500 390 │
|
||||
│ ... │
|
||||
│ │
|
||||
└─────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
### 7.4 前端组件清单
|
||||
|
||||
| 组件 | 路径 | 说明 |
|
||||
|------|------|------|
|
||||
| `PointsBadge` | `components/common/PointsBadge/` | 顶部积分余额徽章 |
|
||||
| `PointsPanel` | `components/common/PointsPanel/` | 点击徽章展开的快捷面板 |
|
||||
| `PointsCost` | `components/common/PointsCost/` | 功能入口的消耗提示标签 |
|
||||
| `PointsCenter` | `pages/points/Center.tsx` | 积分中心主页面 |
|
||||
| `PointsTransactions` | `pages/points/Transactions.tsx` | 积分明细子页 |
|
||||
| `PointsPackages` | `pages/points/Packages.tsx` | 充值积分包子页 |
|
||||
| `Plans` (改造) | `pages/subscription/Plans.tsx` | 对齐 4 档 + 积分展示 |
|
||||
|
||||
---
|
||||
|
||||
## 八、与现有订阅制的迁移方案
|
||||
|
||||
### 8.1 迁移原则
|
||||
|
||||
1. **向前兼容**:迁移期间老用户权益不降低
|
||||
2. **平滑过渡**:不需要用户手动操作,自动完成
|
||||
3. **灰度发布**:按用户批次逐步迁移,降低风险
|
||||
|
||||
### 8.2 迁移步骤
|
||||
|
||||
#### Step 1:数据准备(后端 + DBA)
|
||||
|
||||
```sql
|
||||
-- 1. 创建新表(points_accounts, points_transactions, points_orders, points_consumption_config)
|
||||
-- 2. 为所有现有用户创建积分账户
|
||||
INSERT INTO points_accounts (id, user_id, balance, total_earned, total_gifted)
|
||||
SELECT
|
||||
uuid(), id,
|
||||
CASE subscription_plan
|
||||
WHEN 'standard' THEN 200
|
||||
WHEN 'pro' THEN 800
|
||||
WHEN 'enterprise' THEN 3000
|
||||
ELSE 0
|
||||
END,
|
||||
CASE subscription_plan
|
||||
WHEN 'standard' THEN 200
|
||||
WHEN 'pro' THEN 800
|
||||
WHEN 'enterprise' THEN 3000
|
||||
ELSE 0
|
||||
END,
|
||||
CASE subscription_plan
|
||||
WHEN 'standard' THEN 200
|
||||
WHEN 'pro' THEN 800
|
||||
WHEN 'enterprise' THEN 3000
|
||||
ELSE 0
|
||||
END
|
||||
FROM users WHERE subscription_status = 'active';
|
||||
```
|
||||
|
||||
#### Step 2:代码兼容层
|
||||
|
||||
```python
|
||||
# packages/domain/quota.py 扩展
|
||||
class QuotaDimension(str, Enum):
|
||||
# ... 现有维度保持不变
|
||||
POINTS = "points" # 新增:通用积分维度
|
||||
|
||||
# QUOTA_TIERS 扩展
|
||||
"standard": QuotaTier(
|
||||
name="standard",
|
||||
limits={
|
||||
# ... 现有配额保持不变
|
||||
QuotaDimension.MONTHLY_CREDITS: 200, # 新增
|
||||
},
|
||||
),
|
||||
```
|
||||
|
||||
#### Step 3:双轨运行期(1 个月)
|
||||
|
||||
- 订阅制功能不变,老用户正常续费
|
||||
- 积分系统上线后,所有 AI 消耗型功能改为积分扣费
|
||||
- 会员权益中的"基础配额"(存储、项目数等)继续由订阅制控制
|
||||
- 在用户首次登录后,弹出迁移通知弹窗,说明变更内容
|
||||
|
||||
#### Step 4:完全切换
|
||||
|
||||
- 停止订阅制的 AI 配额逻辑(`AI_VOICE_CREDITS` 等旧维度废弃)
|
||||
- 所有 AI 功能统一使用积分扣费
|
||||
- 订阅制仅控制基础权益(存储、项目数、并发数、导出分辨率等)
|
||||
|
||||
### 8.3 老用户过渡策略
|
||||
|
||||
| 用户类型 | 过渡方案 |
|
||||
|----------|----------|
|
||||
| 当前 free 用户 | 不变,积分余额为 0,可充值 |
|
||||
| 当前 standard 用户 | 赠送 200 积分作为过渡礼包,当前周期内权益不变 |
|
||||
| 当前 pro 用户 | 赠送 800 积分 + 延长 1 个月有效期 |
|
||||
| 当前 enterprise 用户 | 赠送 3000 积分 + 延长 1 个月有效期 + 专属客户经理通知 |
|
||||
| 年付用户 | 按剩余月数比例折算赠送积分 |
|
||||
|
||||
### 8.4 前端迁移
|
||||
|
||||
- `Plans.tsx` 从 3 档改为 4 档,增加积分信息展示
|
||||
- 新增 `/app/points` 积分中心页面
|
||||
- 顶部 Header 增加积分余额徽章
|
||||
- 各 AI 功能页增加积分消耗提示
|
||||
|
||||
---
|
||||
|
||||
## 九、配额检查中间件设计
|
||||
|
||||
### 9.1 整体架构
|
||||
|
||||
```
|
||||
用户请求 → API Route → 积分检查中间件 → 业务逻辑 → 返回结果
|
||||
│
|
||||
├─ 检查会员权益(QuotaChecker)
|
||||
├─ 检查积分余额(PointsChecker)
|
||||
└─ 扣减积分(PointsService.deduct)
|
||||
```
|
||||
|
||||
### 9.2 中间件设计
|
||||
|
||||
#### `apps/api/app/middleware/points_check.py`
|
||||
|
||||
```python
|
||||
"""积分扣费中间件 - 用于 AI 功能入口的统一检查与扣费"""
|
||||
|
||||
from functools import wraps
|
||||
from fastapi import HTTPException
|
||||
|
||||
def require_points(scene_key: str, amount: int = None):
|
||||
"""
|
||||
装饰器:在 AI 功能入口检查积分余额并扣费
|
||||
|
||||
Args:
|
||||
scene_key: 消耗场景标识,如 "ai_voice", "ai_video"
|
||||
amount: 指定消耗数量,为 None 时从 points_consumption_config 读取
|
||||
|
||||
使用方式:
|
||||
@router.post("/generate-voice")
|
||||
@require_points(scene_key="ai_voice")
|
||||
async def generate_voice(request: VoiceRequest, current_user = Depends(get_current_user)):
|
||||
# 到这里积分已扣减成功
|
||||
...
|
||||
"""
|
||||
def decorator(func):
|
||||
@wraps(func)
|
||||
async def wrapper(*args, **kwargs):
|
||||
# 1. 从 kwargs 或 args 中提取 current_user
|
||||
current_user = kwargs.get("current_user") or next(
|
||||
(a for a in args if isinstance(a, AuthenticatedUser)), None
|
||||
)
|
||||
if not current_user:
|
||||
raise HTTPException(status_code=401, detail="未登录")
|
||||
|
||||
# 2. 获取消耗数量
|
||||
consume_amount = amount or get_consumption_config(scene_key)
|
||||
|
||||
# 3. 检查会员权益(原有 QuotaChecker 逻辑)
|
||||
user = current_user.user
|
||||
tier = quota_registry.get_tier(user.subscription_plan or "free")
|
||||
# ... 检查存储、并发等基础权益
|
||||
|
||||
# 4. 检查并扣减积分
|
||||
points_service = get_points_service()
|
||||
result = points_service.check_and_deduct(
|
||||
user_id=user.id,
|
||||
scene_key=scene_key,
|
||||
amount=consume_amount,
|
||||
)
|
||||
|
||||
if not result.success:
|
||||
raise HTTPException(
|
||||
status_code=402, # Payment Required
|
||||
detail={
|
||||
"code": "INSUFFICIENT_POINTS",
|
||||
"message": f"积分不足,需要 {consume_amount} 积分,当前余额 {result.balance}",
|
||||
"recharge_url": "/app/points/recharge"
|
||||
}
|
||||
)
|
||||
|
||||
# 5. 将扣减信息注入请求上下文,供业务层使用
|
||||
kwargs["points_deduct_id"] = result.transaction_id
|
||||
|
||||
try:
|
||||
# 6. 执行业务逻辑
|
||||
return await func(*args, **kwargs)
|
||||
except Exception as e:
|
||||
# 7. 业务失败时退还积分
|
||||
points_service.refund(
|
||||
user_id=user.id,
|
||||
transaction_id=result.transaction_id,
|
||||
reason=f"业务执行失败: {scene_key}"
|
||||
)
|
||||
raise
|
||||
|
||||
return wrapper
|
||||
return decorator
|
||||
```
|
||||
|
||||
### 9.3 积分服务层
|
||||
|
||||
```python
|
||||
# packages/domain/points_service.py
|
||||
|
||||
class PointsService:
|
||||
"""积分服务 - 核心扣费逻辑"""
|
||||
|
||||
def __init__(self, account_repo, transaction_repo, config_repo):
|
||||
self.account_repo = account_repo
|
||||
self.transaction_repo = transaction_repo
|
||||
self.config_repo = config_repo
|
||||
|
||||
def check_and_deduct(self, user_id: str, scene_key: str, amount: int, ref_id: str = "") -> DeductResult:
|
||||
"""
|
||||
检查余额并扣减积分(事务操作)
|
||||
|
||||
流程:
|
||||
1. 查询积分账户
|
||||
2. 检查余额是否 >= amount
|
||||
3. 在事务中:扣减余额 + 写入流水
|
||||
4. 返回扣减结果
|
||||
"""
|
||||
pass
|
||||
|
||||
def refund(self, user_id: str, transaction_id: str, reason: str = "") -> bool:
|
||||
"""退还积分(业务失败时调用)"""
|
||||
pass
|
||||
|
||||
def gift(self, user_id: str, amount: int, source: str, ref_id: str = ""):
|
||||
"""赠送积分(会员赠送 / 任务奖励)"""
|
||||
pass
|
||||
|
||||
def get_balance(self, user_id: str) -> int:
|
||||
"""查询余额"""
|
||||
pass
|
||||
|
||||
def get_transactions(self, user_id: str, page: int = 1, page_size: int = 20,
|
||||
type: str = None, source: str = None) -> list:
|
||||
"""查询流水"""
|
||||
pass
|
||||
```
|
||||
|
||||
### 9.4 与现有 QuotaChecker 的集成
|
||||
|
||||
```python
|
||||
# 改造后的检查流程
|
||||
async def check_all_quotas(user, scene_key: str, consume_amount: int):
|
||||
"""统一配额检查入口"""
|
||||
|
||||
# 1. 基础配额检查(存储空间、项目数、并发数等)
|
||||
# 复用现有 QuotaChecker
|
||||
plan = user.subscription_plan or "free"
|
||||
quota_results = quota_checker.check_multiple(plan, {
|
||||
QuotaDimension.STORAGE_GB.value: get_used_storage(user.id),
|
||||
QuotaDimension.VIDEOS_PER_MONTH.value: get_monthly_video_count(user.id),
|
||||
QuotaDimension.MAX_CONCURRENT.value: get_concurrent_count(user.id),
|
||||
})
|
||||
for result in quota_results:
|
||||
if not result.allowed:
|
||||
raise QuotaExceededError(result)
|
||||
|
||||
# 2. 积分检查
|
||||
# 新增 PointsChecker
|
||||
balance = points_service.get_balance(user.id)
|
||||
if balance < consume_amount:
|
||||
raise InsufficientPointsError(
|
||||
required=consume_amount,
|
||||
balance=balance
|
||||
)
|
||||
|
||||
return True
|
||||
```
|
||||
|
||||
### 9.5 各功能模块接入方式
|
||||
|
||||
```python
|
||||
# apps/api/app/api/routes/ai_voice.py(示例)
|
||||
@router.post("/generate")
|
||||
@require_points(scene_key="ai_voice")
|
||||
async def generate_voice(
|
||||
request: VoiceGenerateRequest,
|
||||
current_user: AuthenticatedUser = Depends(get_current_user),
|
||||
points_deduct_id: str = None, # 由中间件注入
|
||||
):
|
||||
# 积分已扣减,直接执行业务逻辑
|
||||
result = await voice_service.generate(request, current_user.user.id)
|
||||
return VoiceGenerateResponse(
|
||||
voice_id=result.id,
|
||||
points_consumed=1,
|
||||
)
|
||||
|
||||
# apps/api/app/api/routes/ai_video.py(示例)
|
||||
@router.post("/generate")
|
||||
@require_points(scene_key="ai_video")
|
||||
async def generate_video(
|
||||
request: VideoGenerateRequest,
|
||||
current_user: AuthenticatedUser = Depends(get_current_user),
|
||||
points_deduct_id: str = None,
|
||||
):
|
||||
# 视频按秒计费,需要在中间件外动态计算
|
||||
...
|
||||
```
|
||||
|
||||
> **注意**:对于视频生成等按量计费场景(时长不确定),中间件支持动态计算消耗量:
|
||||
> ```python
|
||||
> @require_points(scene_key="ai_video", dynamic=True)
|
||||
> # dynamic=True 时,中间件只检查余额 > 0,实际扣费由业务层调用 points_service.deduct()
|
||||
> ```
|
||||
|
||||
---
|
||||
|
||||
## 十、实施计划
|
||||
|
||||
### 10.1 开发阶段拆分
|
||||
|
||||
| 阶段 | 内容 | 预估工时 |
|
||||
|------|------|----------|
|
||||
| **P1 - 基础框架** | 数据库迁移脚本、积分账户/流水/订单 Model、Repository | 3 天 |
|
||||
| **P2 - 核心服务** | PointsService 核心逻辑(扣费/退还/赠送/查询) | 3 天 |
|
||||
| **P3 - API 层** | 积分 API 路由、中间件、与现有订阅 API 集成 | 3 天 |
|
||||
| **P4 - 前端页面** | Plans.tsx 改造、积分中心页面、Header 积分徽章、消耗提示 | 5 天 |
|
||||
| **P5 - 功能接入** | 各 AI 功能模块接入 `@require_points` 中间件 | 3 天 |
|
||||
| **P6 - 迁移与测试** | 数据迁移脚本、灰度方案、集成测试、端到端测试 | 3 天 |
|
||||
|
||||
### 10.2 文件改动清单(预览)
|
||||
|
||||
| 类型 | 文件路径 | 改动说明 |
|
||||
|------|----------|----------|
|
||||
| 新增 | `migrations/007_membership_points.sql` | 新建积分相关 4 张表 |
|
||||
| 新增 | `packages/domain/points_service.py` | 积分核心服务 |
|
||||
| 新增 | `packages/domain/points_models.py` 或追加到 `models.py` | 积分相关 ORM Model |
|
||||
| 新增 | `packages/adapters/sqlalchemy_impl/points_repository.py` | 积分 Repository |
|
||||
| 新增 | `apps/api/app/middleware/points_check.py` | 积分扣费中间件 |
|
||||
| 新增 | `apps/api/app/api/routes/points.py` | 积分 API 路由 |
|
||||
| 新增 | `apps/api/app/schemas/points.py` | 积分 Schema |
|
||||
| 新增 | `apps/web/src/pages/points/Center.tsx` | 积分中心页面 |
|
||||
| 新增 | `apps/web/src/pages/points/Transactions.tsx` | 积分明细页面 |
|
||||
| 新增 | `apps/web/src/pages/points/Packages.tsx` | 积分包充值页面 |
|
||||
| 新增 | `apps/web/src/components/common/PointsBadge/` | 积分徽章组件 |
|
||||
| 新增 | `apps/web/src/components/common/PointsCost/` | 消耗提示组件 |
|
||||
| 修改 | `packages/domain/quota.py` | 新增 POINTS 维度和 monthly_credits 配额 |
|
||||
| 修改 | `packages/adapters/sqlalchemy_impl/models.py` | 新增积分相关 Model |
|
||||
| 修改 | `apps/api/app/api/routes/subscription.py` | 集成积分逻辑 |
|
||||
| 修改 | `apps/api/app/schemas/subscription.py` | 返回中增加积分信息 |
|
||||
| 修改 | `apps/web/src/pages/subscription/Plans.tsx` | 对齐 4 档 + 积分展示 |
|
||||
| 修改 | 各 AI 功能路由文件 | 添加 `@require_points` 装饰器 |
|
||||
|
||||
### 10.3 测试计划
|
||||
|
||||
| 测试类型 | 覆盖范围 |
|
||||
|----------|----------|
|
||||
| 单元测试 | PointsService 扣费/退还/赠送逻辑、PointsChecker 余额检查 |
|
||||
| 集成测试 | API 端到端:充值→到账→消费→扣减→流水查询 |
|
||||
| 并发测试 | 同一用户多请求并发扣费的余额一致性 |
|
||||
| 前端测试 | Plans 页面渲染、积分中心交互、Header 徽章实时更新 |
|
||||
| 迁移测试 | 老用户数据迁移正确性验证 |
|
||||
|
||||
---
|
||||
|
||||
## 十一、风险与注意事项
|
||||
|
||||
| 风险 | 应对方案 |
|
||||
|------|----------|
|
||||
| 并发扣费导致余额不一致 | 数据库事务 + 行锁,`points_accounts` 使用 `SELECT ... FOR UPDATE` |
|
||||
| 支付回调延迟导致积分未到账 | 订单创建后 30 分钟未支付自动关闭;回调支持幂等重试 |
|
||||
| 积分消耗规则变更影响用户 | 变更前 7 天公告通知;已购买的服务按旧价格执行 |
|
||||
| 前后端积分展示不一致 | 统一从 `GET /api/v1/points/balance` 获取,前端不本地缓存余额 |
|
||||
| 老用户迁移产生不满 | 过渡期权益不降低 + 额外赠送积分礼包 |
|
||||
|
||||
---
|
||||
|
||||
## 十二、开放问题(待确认)
|
||||
|
||||
1. **积分有效期**:当前设计为永久有效。是否需要设置有效期(如 1 年)?
|
||||
2. **退款策略**:积分充值后是否支持退款?已消费的积分如何计算?
|
||||
3. **企业版定制**:企业版是否需要支持自定义积分消耗规则?
|
||||
4. **支付渠道**:第一期接入支付宝 + 微信支付,是否需要支持其他渠道?
|
||||
5. **发票需求**:积分充值是否需要单独开发票?与订阅发票合并还是分开?
|
||||
|
||||
---
|
||||
|
||||
*本文档为方案设计阶段产物,待确认后将按「实施计划」分阶段开发。*
|
||||
@@ -12,9 +12,8 @@ RUN sed -i 's|deb.debian.org|mirrors.aliyun.com|g' /etc/apt/sources.list.d/debia
|
||||
sed -i 's|deb.debian.org|mirrors.aliyun.com|g' /etc/apt/sources.list 2>/dev/null || true
|
||||
|
||||
# 预装系统依赖(gcc 编译 psycopg/pg 扩展,libpq-dev 编译期,libpq5 运行期,ffmpeg 封面取帧)
|
||||
# 字体修复:fonts-noto-cjk 包的 Sans .ttc 文件混入了 Mono 变体,导致 Bold 匹配到等宽字体
|
||||
# 解决方案:删除 Sans .ttc,保留 Serif .ttc;仓库内预下载 VF 可变字体(不含 Mono)
|
||||
# #1896 补充开源字体:NotoSerifCJKsc-VF.otf(思源宋体)、LXGWWenKai-Regular.ttf(霞鹜文楷开源楷体)
|
||||
# 字体修复:fonts-noto-cjk 包的 .ttc 文件混入了 Mono 变体,导致 Bold 匹配到等宽字体
|
||||
# 解决方案:删除有问题的 .ttc,使用仓库内预下载的 Noto Sans SC Variable Font(不含 Mono)
|
||||
RUN apt-get update && apt-get install -y --no-install-recommends \
|
||||
gcc \
|
||||
libpq-dev \
|
||||
@@ -22,15 +21,12 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
|
||||
ffmpeg \
|
||||
fonts-noto-cjk \
|
||||
&& rm -rf /var/lib/apt/lists/* \
|
||||
# 删除有问题的 Sans .ttc(含 Mono 变体),保留 Serif .ttc 作为宋体 fallback
|
||||
# 删除有问题的 .ttc 文件(包含 Mono 变体)
|
||||
&& rm -f /usr/share/fonts/opentype/noto/NotoSansCJK-Regular.ttc \
|
||||
&& rm -f /usr/share/fonts/opentype/noto/NotoSansCJK-Bold.ttc \
|
||||
&& mkdir -p /usr/share/fonts/truetype/lxgw
|
||||
&& rm -f /usr/share/fonts/opentype/noto/NotoSansCJK-Bold.ttc
|
||||
|
||||
# 复制开源中文字体:思源黑体 VF + 思源宋体 VF(#1896)+ 霞鹜文楷(#1896,开源楷体)
|
||||
# 复制预下载的 Noto Sans SC Variable Font(包含所有字重,不含 Mono 变体)
|
||||
COPY infra/fonts/NotoSansSC-VF.ttf /usr/share/fonts/opentype/noto/NotoSansSC-VF.ttf
|
||||
COPY infra/fonts/NotoSerifCJKsc-VF.otf /usr/share/fonts/opentype/noto/NotoSerifCJKsc-VF.otf
|
||||
COPY infra/fonts/LXGWWenKai-Regular.ttf /usr/share/fonts/truetype/lxgw/LXGWWenKai-Regular.ttf
|
||||
RUN fc-cache -fv
|
||||
|
||||
# 创建虚拟环境
|
||||
|
||||
@@ -12,11 +12,8 @@ RUN sed -i 's|deb.debian.org|mirrors.aliyun.com|g' /etc/apt/sources.list.d/debia
|
||||
sed -i 's|deb.debian.org|mirrors.aliyun.com|g' /etc/apt/sources.list 2>/dev/null || true
|
||||
|
||||
# 预装系统依赖(编译工具 + 运行时 + CJK 字体用于 ASS 字幕渲染)
|
||||
# 字体修复:fonts-noto-cjk 包的 Sans .ttc 文件混入了 Mono 变体,导致 Bold 匹配到等宽字体
|
||||
# 解决方案:删除 Sans .ttc,保留 Serif .ttc(宋体 fallback);仓库内预下载 VF 可变字体(不含 Mono)
|
||||
# #1896 补充开源字体:NotoSerifCJKsc-VF.otf(思源宋体衬线)、LXGWWenKai-Regular.ttf(霞鹜文楷开源楷体,SIL OFL)
|
||||
# - 苹方/微软雅黑为 macOS/Windows 系统字体,服务器无对应文件,映射到 Noto Sans SC fallback
|
||||
# - 华康俪金黑为商业字体有版权风险,前端已移除,后端映射到 Noto Sans SC 兼容老数据
|
||||
# 字体修复:fonts-noto-cjk 包的 .ttc 文件混入了 Mono 变体,导致 Bold 匹配到等宽字体
|
||||
# 解决方案:删除有问题的 .ttc,使用仓库内预下载的 Noto Sans SC Variable Font(不含 Mono)
|
||||
RUN apt-get update && apt-get install -y --no-install-recommends \
|
||||
gcc \
|
||||
g++ \
|
||||
@@ -26,15 +23,12 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
|
||||
libglib2.0-0 \
|
||||
fonts-noto-cjk \
|
||||
&& rm -rf /var/lib/apt/lists/* \
|
||||
# 删除有问题的 Sans .ttc 文件(包含 Mono 变体会导致粗体匹配错误),保留 Serif .ttc 作为宋体 fallback
|
||||
# 删除有问题的 .ttc 文件(包含 Mono 变体)
|
||||
&& rm -f /usr/share/fonts/opentype/noto/NotoSansCJK-Regular.ttc \
|
||||
&& rm -f /usr/share/fonts/opentype/noto/NotoSansCJK-Bold.ttc \
|
||||
&& mkdir -p /usr/share/fonts/truetype/lxgw
|
||||
&& rm -f /usr/share/fonts/opentype/noto/NotoSansCJK-Bold.ttc
|
||||
|
||||
# 复制开源中文字体:思源黑体 VF + 思源宋体 VF(#1896)+ 霞鹜文楷(#1896,开源楷体)
|
||||
# 复制预下载的 Noto Sans SC Variable Font(包含所有字重,不含 Mono 变体)
|
||||
COPY infra/fonts/NotoSansSC-VF.ttf /usr/share/fonts/opentype/noto/NotoSansSC-VF.ttf
|
||||
COPY infra/fonts/NotoSerifCJKsc-VF.otf /usr/share/fonts/opentype/noto/NotoSerifCJKsc-VF.otf
|
||||
COPY infra/fonts/LXGWWenKai-Regular.ttf /usr/share/fonts/truetype/lxgw/LXGWWenKai-Regular.ttf
|
||||
RUN fc-cache -fv
|
||||
|
||||
# 创建虚拟环境
|
||||
|
||||
Binary file not shown.
Binary file not shown.
@@ -703,9 +703,6 @@ class LipsyncJobModel(Base):
|
||||
error_message = Column(Text, nullable=False, default="")
|
||||
error_code = Column(String(100), nullable=False, default="")
|
||||
|
||||
# 精确句子时间戳(TTS 合成后由 silencedetect 计算,用于 B-roll 精确定位)
|
||||
sentence_timings = Column(JSON, nullable=True) # list[{index,text,start_time,end_time}]
|
||||
|
||||
# 时间戳
|
||||
submitted_at = Column(DateTime, nullable=True)
|
||||
completed_at = Column(DateTime, nullable=True)
|
||||
|
||||
@@ -25,20 +25,13 @@ TITLE_MARGIN_BOTTOM = 100
|
||||
TITLE_MARGIN_SIDE = 40
|
||||
|
||||
# 字体名称映射:前端中文字体名 → 服务器实际注册名(ffmpeg/ASS 通过注册名匹配字体)
|
||||
# #1896 字体映射修复:每个字体映射到独立的注册名,而非全部回退到 Noto Sans SC
|
||||
# - 思源宋体 → Noto Serif CJK SC(fonts-noto-cjk 包预装 + VF.otf)
|
||||
# - 楷体 → LXGW WenKai(霞鹜文楷,#1896 新增 SIL OFL 开源楷体)
|
||||
# - 苹方/PingFang/微软雅黑:服务器 Linux 无对应字体,fallback 思源黑体
|
||||
# - 华康俪金黑:商业字体有版权风险,前端已移除,后端保留映射 fallback 思源黑体(兼容老数据)
|
||||
FONT_NAME_MAP: dict[str, str] = {
|
||||
"思源黑体": "Noto Sans SC",
|
||||
"思源宋体": "Noto Serif CJK SC",
|
||||
"苹方": "Noto Sans SC",
|
||||
"PingFang": "Noto Sans SC",
|
||||
"微软雅黑": "Noto Sans SC",
|
||||
"Microsoft YaHei": "Noto Sans SC",
|
||||
"楷体": "LXGW WenKai",
|
||||
"霞鹜文楷": "LXGW WenKai",
|
||||
"楷体": "Noto Serif CJK SC",
|
||||
"华康俪金黑": "Noto Sans SC",
|
||||
}
|
||||
|
||||
|
||||
@@ -49,17 +49,19 @@ class GeneratedVideo:
|
||||
thumbnail_url: str | None = None,
|
||||
generation_params: dict[str, Any] | None = None,
|
||||
) -> "GeneratedVideo":
|
||||
# project_id / generation_task_id 允许为空:AI数字人等无项目场景下,前端可能不传 project_id;
|
||||
# lipsync 路径下 generation_task_id 也可能暂时为空。空串会被下面统一兜底为 "" 入库。
|
||||
if not name or not name.strip():
|
||||
if not project_id.strip():
|
||||
raise ValueError("project_id cannot be empty")
|
||||
if not generation_task_id.strip():
|
||||
raise ValueError("generation_task_id cannot be empty")
|
||||
if not name.strip():
|
||||
raise ValueError("name cannot be empty")
|
||||
if not file_url or not file_url.strip():
|
||||
if not file_url.strip():
|
||||
raise ValueError("file_url cannot be empty")
|
||||
return cls(
|
||||
id=uuid4().hex,
|
||||
project_id=(project_id or "").strip(),
|
||||
user_id=(user_id or "").strip(),
|
||||
generation_task_id=(generation_task_id or "").strip(),
|
||||
project_id=project_id.strip(),
|
||||
user_id=user_id.strip(),
|
||||
generation_task_id=generation_task_id.strip(),
|
||||
name=name.strip(),
|
||||
file_url=file_url.strip(),
|
||||
file_size=file_size,
|
||||
|
||||
@@ -1,206 +0,0 @@
|
||||
"""共享的句子时间戳计算工具 — 供 Celery TTS 任务和 /lipsync/tts-preview 同步接口复用.
|
||||
|
||||
- `split_script_into_sentences`: 按标点分句(中英文句号/问号/感叹号/分号/换行,不含逗号,与前端 sentences.ts 保持一致)
|
||||
- `_estimate_sentence_timings_by_chars`: 按字数比例估算(静音检测失败时降级)
|
||||
- `_probe_audio_duration`: ffprobe 读取音频时长
|
||||
- `compute_sentence_timings`: 基于 ffmpeg silencedetect 精确计算每句起止时间
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import os
|
||||
import re
|
||||
import subprocess
|
||||
import tempfile
|
||||
from typing import Optional
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def split_script_into_sentences(script_text: str) -> list[str]:
|
||||
"""按句号/问号/感叹号/分号/换行分句(与前端 sentences.ts 的 SENTENCE_SPLIT_RE 一致).
|
||||
|
||||
仅在句末标点(。!?!?;;)和换行处分句,**不再用逗号(,,)切分**。
|
||||
按逗号切分会把连贯句子拆得过碎,导致 B-roll/口播画面按句插入时句数过多、
|
||||
时长过短,效果不符合预期(Issue #1892)。
|
||||
"""
|
||||
text = (script_text or "").strip()
|
||||
if not text:
|
||||
return []
|
||||
parts = re.split(r"[。!?!??!;;\n\r]+", text)
|
||||
return [p.strip() for p in parts if p.strip()]
|
||||
|
||||
|
||||
def estimate_sentence_timings_by_chars(sentences: list[str], total_duration: float) -> list[dict]:
|
||||
"""降级方案:按字数比例估算句子时间(与原前端逻辑一致)."""
|
||||
if not sentences or total_duration <= 0:
|
||||
return []
|
||||
total_chars = sum(len(s.replace(r"\s", "")) for s in sentences)
|
||||
if total_chars == 0:
|
||||
return []
|
||||
|
||||
timings = []
|
||||
acc = 0
|
||||
for i, sent in enumerate(sentences):
|
||||
chars = len(sent.replace(r"\s", ""))
|
||||
start = (acc / total_chars) * total_duration
|
||||
end = ((acc + chars) / total_chars) * total_duration
|
||||
timings.append(
|
||||
{
|
||||
"index": i,
|
||||
"text": sent,
|
||||
"start_time": round(start, 2),
|
||||
"end_time": round(end, 2),
|
||||
}
|
||||
)
|
||||
acc += chars
|
||||
return timings
|
||||
|
||||
|
||||
def probe_audio_duration(audio_data: bytes, timeout: int = 10) -> float:
|
||||
"""用 ffprobe 读取音频字节流的时长(秒).
|
||||
|
||||
Returns:
|
||||
时长(秒),失败返回 0.0
|
||||
"""
|
||||
if not audio_data:
|
||||
return 0.0
|
||||
tmp_path: Optional[str] = None
|
||||
try:
|
||||
with tempfile.NamedTemporaryFile(suffix=".mp3", delete=False) as tmp:
|
||||
tmp.write(audio_data)
|
||||
tmp_path = tmp.name
|
||||
result = subprocess.run(
|
||||
[
|
||||
"ffprobe",
|
||||
"-v",
|
||||
"error",
|
||||
"-show_entries",
|
||||
"format=duration",
|
||||
"-of",
|
||||
"default=noprint_wrappers=1:nokey=1",
|
||||
tmp_path,
|
||||
],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
timeout=timeout,
|
||||
)
|
||||
stdout = (result.stdout or "").strip()
|
||||
if not stdout:
|
||||
logger.warning("[sentence_timings] ffprobe 无输出: stderr=%s", (result.stderr or "")[:200])
|
||||
return 0.0
|
||||
return float(stdout)
|
||||
except Exception as exc:
|
||||
logger.warning("[sentence_timings] ffprobe 时长探测失败: %s", exc)
|
||||
return 0.0
|
||||
finally:
|
||||
if tmp_path:
|
||||
try:
|
||||
os.unlink(tmp_path)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
|
||||
def compute_sentence_timings(audio_data: bytes, script_text: str, total_duration: float) -> list[dict]:
|
||||
"""基于 TTS 音频的静音检测,精确计算每句文案的起止时间.
|
||||
|
||||
使用 ffmpeg silencedetect 检测静音段,将静音点与句子边界对齐。
|
||||
比字数比例估算准确得多。
|
||||
|
||||
Args:
|
||||
audio_data: TTS 音频二进制数据(MP3)
|
||||
script_text: 文案全文
|
||||
total_duration: 音频总时长(秒)
|
||||
|
||||
Returns:
|
||||
list[{"index": int, "text": str, "start_time": float, "end_time": float}]
|
||||
"""
|
||||
sentences = split_script_into_sentences(script_text)
|
||||
if not sentences:
|
||||
return []
|
||||
|
||||
tmp_path: Optional[str] = None
|
||||
try:
|
||||
with tempfile.NamedTemporaryFile(suffix=".mp3", delete=False) as tmp:
|
||||
tmp.write(audio_data)
|
||||
tmp_path = tmp.name
|
||||
|
||||
result = subprocess.run(
|
||||
[
|
||||
"ffmpeg",
|
||||
"-i",
|
||||
tmp_path,
|
||||
"-af",
|
||||
"silencedetect=noise=-25dB:d=0.3",
|
||||
"-f",
|
||||
"null",
|
||||
"-",
|
||||
],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
timeout=30,
|
||||
)
|
||||
stderr = result.stderr or ""
|
||||
|
||||
silence_ends = []
|
||||
for match in re.finditer(r"silence_end:\s*([\d.]+)", stderr):
|
||||
t = float(match.group(1))
|
||||
if 0 < t < total_duration:
|
||||
silence_ends.append(t)
|
||||
|
||||
if len(silence_ends) < len(sentences) - 1:
|
||||
logger.warning(
|
||||
"[sentence_timings] 静音点不足(%d < %d),降级为字数比例估算",
|
||||
len(silence_ends),
|
||||
len(sentences) - 1,
|
||||
)
|
||||
return estimate_sentence_timings_by_chars(sentences, total_duration)
|
||||
|
||||
n_boundaries = len(sentences) - 1
|
||||
boundaries = []
|
||||
used_indices = set()
|
||||
|
||||
for i in range(n_boundaries):
|
||||
expected_pos = (i + 1) / len(sentences) * total_duration
|
||||
best_idx = None
|
||||
best_dist = float("inf")
|
||||
for j, t in enumerate(silence_ends):
|
||||
if j in used_indices:
|
||||
continue
|
||||
dist = abs(t - expected_pos)
|
||||
if dist < best_dist:
|
||||
best_dist = dist
|
||||
best_idx = j
|
||||
if best_idx is not None:
|
||||
used_indices.add(best_idx)
|
||||
boundaries.append(silence_ends[best_idx])
|
||||
|
||||
boundaries.sort()
|
||||
|
||||
timings = []
|
||||
prev_end = 0.0
|
||||
for i, sent in enumerate(sentences):
|
||||
start = prev_end
|
||||
end = boundaries[i] if i < len(boundaries) else total_duration
|
||||
timings.append(
|
||||
{
|
||||
"index": i,
|
||||
"text": sent,
|
||||
"start_time": round(start, 2),
|
||||
"end_time": round(end, 2),
|
||||
}
|
||||
)
|
||||
prev_end = end
|
||||
|
||||
return timings
|
||||
|
||||
except Exception as exc:
|
||||
logger.warning("[sentence_timings] 静音检测异常,降级为字数比例估算: %s", exc)
|
||||
return estimate_sentence_timings_by_chars(sentences, total_duration)
|
||||
finally:
|
||||
if tmp_path:
|
||||
try:
|
||||
os.unlink(tmp_path)
|
||||
except Exception:
|
||||
pass
|
||||
@@ -377,39 +377,26 @@ def _append_audio_concat(parts: list[str], clip_chains: list[ClipFilterChain]) -
|
||||
|
||||
# ── 标题 drawtext 滤镜构建(#1789)─────────────────────────────────────────────
|
||||
|
||||
# drawtext 字体搜索路径:按优先级从高到低排列
|
||||
# #1896 字体映射修复:
|
||||
# - NotoSansSC-VF.ttf:思源黑体(VF 可变字体,含所有字重),worker-base.Dockerfile COPY
|
||||
# - NotoSerifCJKsc-VF.otf:思源宋体(VF 可变字体),#1896 新增,衬线字体
|
||||
# - LXGWWenKai-Regular.ttf:霞鹜文楷(开源楷体,SIL OFL),#1896 新增
|
||||
# - fonts-noto-cjk 预装 .ttc 作为 fallback(Dockerfile 已删除含 Mono 变体的文件)
|
||||
# - DejaVuSans 仅含拉丁字符不支持中文,已移除
|
||||
# drawtext 字体搜索路径:按优先级列出常见安装位置
|
||||
# 服务器使用 Noto Sans SC(思源黑体)作为默认字体
|
||||
DRAWTEXT_FONT_SEARCH_PATHS: list[str] = [
|
||||
"/usr/share/fonts/opentype/noto/NotoSansSC-VF.ttf",
|
||||
"/usr/share/fonts/opentype/noto/NotoSerifCJKsc-VF.otf",
|
||||
"/usr/share/fonts/truetype/lxgw/LXGWWenKai-Regular.ttf",
|
||||
"/usr/share/fonts/opentype/noto/NotoSansCJK-Regular.ttc",
|
||||
"/usr/share/fonts/opentype/noto/NotoSansCJK-Bold.ttc",
|
||||
"/usr/share/fonts/noto-cjk/NotoSansCJK-Regular.ttc",
|
||||
"/usr/share/fonts/google-noto-cjk/NotoSansCJK-Regular.ttc",
|
||||
"/usr/share/fonts/truetype/noto/NotoSansSC-Regular.ttf",
|
||||
"/usr/share/fonts/noto/NotoSansSC-Regular.ttf",
|
||||
"/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf",
|
||||
]
|
||||
|
||||
# 前端字体名 → drawtext 字体搜索关键字(匹配 DRAWTEXT_FONT_SEARCH_PATHS 中的文件名关键字)
|
||||
# #1896 字体映射修复:每个字体映射到独立的关键字,而非全部回退到 NotoSansSC
|
||||
# - 苹方(macOS)/ 微软雅黑(Windows)/ PingFang:服务器 Linux 无对应文件,fallback 思源黑体
|
||||
# - 华康俪金黑:商业字体有版权风险,前端已按 #1896 要求移除,后端保留映射但 fallback 思源黑体(兼容老数据)
|
||||
# 前端字体名 → drawtext 字体搜索关键字
|
||||
DRAWTEXT_FONT_MAP: dict[str, str] = {
|
||||
"思源黑体": "NotoSansSC",
|
||||
"思源宋体": "NotoSerifCJKsc",
|
||||
"苹方": "NotoSansSC",
|
||||
"PingFang": "NotoSansSC",
|
||||
"微软雅黑": "NotoSansSC",
|
||||
"Microsoft YaHei": "NotoSansSC",
|
||||
"楷体": "LXGWWenKai",
|
||||
"霞鹜文楷": "LXGWWenKai",
|
||||
"华康俪金黑": "NotoSansSC",
|
||||
"思源黑体": "NotoSansCJK",
|
||||
"思源宋体": "NotoSerifCJK",
|
||||
"苹方": "NotoSansCJK",
|
||||
"PingFang": "NotoSansCJK",
|
||||
"微软雅黑": "NotoSansCJK",
|
||||
"楷体": "NotoSerifCJK",
|
||||
"华康俪金黑": "NotoSansCJK",
|
||||
}
|
||||
|
||||
|
||||
@@ -429,11 +416,6 @@ def _escape_drawtext_text(text: str) -> str:
|
||||
return result
|
||||
|
||||
|
||||
# 粗体字体已由前端 Canvas 直接渲染(Canvas 使用浏览器原生粗体 glyph),
|
||||
# FFmpeg 侧不再需要查找 Bold 字体文件;drawtext 仅作为旧版前端的降级路径,
|
||||
# 通过 borderw 黑色细描边模拟粗体(见 build_title_drawtext_filter)。
|
||||
|
||||
|
||||
def _resolve_font_path(font_name: str) -> str:
|
||||
"""解析字体名到服务器实际字体文件路径。
|
||||
|
||||
@@ -441,9 +423,6 @@ def _resolve_font_path(font_name: str) -> str:
|
||||
1. 通过 DRAWTEXT_FONT_MAP 映射前端字体名到服务器关键字
|
||||
2. 在 DRAWTEXT_FONT_SEARCH_PATHS 中查找匹配路径
|
||||
3. 未找到则返回空字符串(drawtext 使用内置默认字体)
|
||||
|
||||
注:粗体已由前端 Canvas 渲染时直接用浏览器 bold glyph 绘制,
|
||||
此处仅作为旧版前端降级路径,无需切换 Bold 字体文件。
|
||||
"""
|
||||
keyword = DRAWTEXT_FONT_MAP.get(font_name, font_name)
|
||||
import os
|
||||
@@ -487,8 +466,8 @@ def build_title_drawtext_filter(
|
||||
if not title_config or not isinstance(title_config, dict):
|
||||
return None
|
||||
|
||||
# 字段名归一化:兼容 content/text/title 三套命名
|
||||
text = (title_config.get("text") or title_config.get("content") or title_config.get("title") or "").strip()
|
||||
# 字段名归一化:兼容 content/text、font_preset/font 两套命名
|
||||
text = (title_config.get("text") or title_config.get("content") or "").strip()
|
||||
if not text:
|
||||
return None
|
||||
|
||||
@@ -498,13 +477,13 @@ def build_title_drawtext_filter(
|
||||
|
||||
# ── 样式参数 ──
|
||||
font_name = title_config.get("font") or title_config.get("font_preset") or "思源黑体"
|
||||
font_size = int(title_config.get("font_size") or title_config.get("size") or 48)
|
||||
font_size = int(title_config.get("font_size") or title_config.get("size") or 36)
|
||||
font_color = title_config.get("font_color") or title_config.get("color") or "#ffffff"
|
||||
# 去掉 # 前缀(drawtext 用纯 hex 或颜色名)
|
||||
if font_color.startswith("#"):
|
||||
font_color = font_color[1:]
|
||||
|
||||
position = title_config.get("position") or "bottom"
|
||||
position = title_config.get("position", "top")
|
||||
bold = bool(title_config.get("bold", True))
|
||||
stroke = title_config.get("stroke")
|
||||
shadow = title_config.get("shadow")
|
||||
@@ -512,7 +491,7 @@ def build_title_drawtext_filter(
|
||||
# ── 构建 drawtext 参数 ──
|
||||
params: list[str] = []
|
||||
|
||||
# 字体文件(drawtext 降级路径:粗体通过 borderw 黑色描边模拟)
|
||||
# 字体文件
|
||||
font_path = _resolve_font_path(font_name)
|
||||
if font_path:
|
||||
escaped_path = font_path.replace("\\", "\\\\").replace(":", "\\\\:").replace("'", "\\\\'")
|
||||
@@ -525,28 +504,26 @@ def build_title_drawtext_filter(
|
||||
params.append(f"fontsize={font_size}")
|
||||
params.append(f"fontcolor={font_color}")
|
||||
|
||||
# 粗体:bold 在 drawtext 中通过 font 的 Bold 变体实现
|
||||
# 若字体有 Bold 变体可用 fontfont=bold;否则通过 borderw 模拟
|
||||
if bold:
|
||||
# 使用 font 参数尝试加载 Bold 变体(Noto Sans SC 有 Bold 变体文件)
|
||||
params.append("font=bold")
|
||||
|
||||
# 描边(borderw 需要 libfreetype 支持)
|
||||
# 之前用 borderw=3 + font_color 同色描边模拟粗体,会在小字号/竖屏视频上造成
|
||||
# 字形偏移、边缘重影,看起来像文字被打印了两次(用户截图中的标题"曝光曝光…")。
|
||||
# 修复:粗体改用黑色细描边(borderw=2, 黑色),视觉上清晰加粗且不产生偏移。
|
||||
# 用户显式开启 stroke 时按用户配置走;粗体+无stroke 默认黑色细描边。
|
||||
border_width = 0
|
||||
border_color = "000000"
|
||||
if stroke:
|
||||
if isinstance(stroke, bool):
|
||||
border_width = 2
|
||||
border_color = "000000"
|
||||
border_color = "black"
|
||||
elif isinstance(stroke, dict):
|
||||
if stroke.get("enabled", True):
|
||||
border_width = int(stroke.get("width", 2))
|
||||
border_color = (stroke.get("color") or "#000000").lstrip("#")
|
||||
elif bold:
|
||||
# 粗体模式且未配描边:黑色细描边,模拟粗体同时保证不重影
|
||||
border_width = 2
|
||||
border_color = "000000"
|
||||
if border_width > 0:
|
||||
params.append(f"borderw={border_width}")
|
||||
params.append(f"bordercolor={border_color}")
|
||||
border_width = int(stroke.get("width", 2)) if stroke.get("enabled", True) else 0
|
||||
border_color = (stroke.get("color") or "#000000").lstrip("#")
|
||||
else:
|
||||
border_width = 0
|
||||
border_color = "black"
|
||||
if border_width > 0:
|
||||
params.append(f"borderw={border_width}")
|
||||
params.append(f"bordercolor={border_color}")
|
||||
|
||||
# 阴影(shadowcolor + shadowx/y)
|
||||
if shadow:
|
||||
@@ -571,13 +548,8 @@ def build_title_drawtext_filter(
|
||||
and not isinstance(pos_x, bool)
|
||||
and not isinstance(pos_y, bool)
|
||||
):
|
||||
# pos_x/pos_y 为百分比坐标(0-100),转换为 drawtext 表达式
|
||||
# 例如 pos_x=50 → x=(w-text_w)*0.50(水平居中偏50%)
|
||||
# pos_y=30 → y=(h-text_h)*0.30
|
||||
pct_x = max(0.0, min(100.0, float(pos_x))) / 100.0
|
||||
pct_y = max(0.0, min(100.0, float(pos_y))) / 100.0
|
||||
params.append(f"x=(w-text_w)*{pct_x:.4f}")
|
||||
params.append(f"y=(h-text_h)*{pct_y:.4f}")
|
||||
params.append(f"x={int(pos_x)}")
|
||||
params.append(f"y={int(pos_y)}")
|
||||
else:
|
||||
# 三档预设位置:top / center / bottom
|
||||
# x 始终水平居中:(w-text_w)/2
|
||||
@@ -593,43 +565,6 @@ def build_title_drawtext_filter(
|
||||
return "drawtext=" + ":".join(params)
|
||||
|
||||
|
||||
def build_title_overlay_filter(
|
||||
title_config: dict[str, Any],
|
||||
output_width: int, # noqa: ARG001 - 保留参数签名,PNG 已按视频分辨率绘制
|
||||
output_height: int, # noqa: ARG001
|
||||
title_png_path: str,
|
||||
*,
|
||||
title_input_label: str = "[1:v]",
|
||||
base_label: str = "[0:v]",
|
||||
output_label: str = "vout_titled",
|
||||
) -> str | None:
|
||||
"""构建标题 PNG 图层 overlay 滤镜(WYSIWYG 路径)。
|
||||
|
||||
前端用 Canvas 把标题画成与视频同分辨率的透明 PNG(所见即所得),
|
||||
后端直接 overlay=0:0 叠加即可,PNG 透明区域不遮挡视频。
|
||||
|
||||
Args:
|
||||
title_config: 标题配置 dict(仅用来判断降级)
|
||||
output_width: 输出宽度(未使用,PNG 已按该分辨率绘制)
|
||||
output_height: 输出高度(未使用)
|
||||
title_png_path: 已保存到本地的标题 PNG 文件路径
|
||||
title_input_label: 标题 PNG 在 filter_complex 中的输入标签(默认 "[1:v]")
|
||||
base_label: 前序滤镜输出标签(如 B-roll 输出 "[vout]")
|
||||
output_label: overlay 输出标签名
|
||||
|
||||
Returns:
|
||||
overlay 滤镜字符串;title_png_path 为空/文件不存在时返回 None(降级到 drawtext)
|
||||
"""
|
||||
import os
|
||||
|
||||
if not title_png_path or not os.path.isfile(title_png_path):
|
||||
return None
|
||||
if not title_config or not isinstance(title_config, dict):
|
||||
return None
|
||||
|
||||
return f"{base_label}{title_input_label}overlay=0:0[{output_label}]"
|
||||
|
||||
|
||||
# ── B-roll 叠加滤镜 ─────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
@@ -638,7 +573,7 @@ def build_broll_overlay_filter(
|
||||
video_duration: float,
|
||||
output_width: int = DEFAULT_OUTPUT_WIDTH,
|
||||
output_height: int = DEFAULT_OUTPUT_HEIGHT,
|
||||
) -> tuple[str, str | None]:
|
||||
) -> str:
|
||||
"""构建 B-roll 叠加滤镜链。
|
||||
|
||||
支持两种模式:
|
||||
@@ -646,182 +581,121 @@ def build_broll_overlay_filter(
|
||||
- pip: 在对口型视频上叠加画中画 B-roll
|
||||
|
||||
Args:
|
||||
b_roll_segments: B-roll 片段配置列表(原始顺序,决定 FFmpeg -i 输入顺序)
|
||||
b_roll_segments: B-roll 片段配置列表
|
||||
video_duration: 对口型视频总时长(秒)
|
||||
output_width: 输出宽度(默认 1280;AI 数字人竖屏传 720)
|
||||
output_height: 输出高度(默认 720;AI 数字人竖屏传 1280)
|
||||
output_width: 输出宽度
|
||||
output_height: 输出高度
|
||||
|
||||
Returns:
|
||||
(filter_complex_str, final_label)
|
||||
- filter_complex_str: filter_complex 片段字符串(末尾无分号)
|
||||
- final_label: 最终输出 pad 标签名,如 "vout";无 B-roll 时返回 None
|
||||
FFmpeg filter_complex 滤镜字符串片段
|
||||
"""
|
||||
if not b_roll_segments:
|
||||
return "", None
|
||||
|
||||
# 建立原始列表下标 → FFmpeg 输入下标的映射:
|
||||
# cmd 中 [0:v] 是主视频,随后按 b_roll_segments 原始顺序追加 -i,
|
||||
# 因此第 i 个 segment 的输入是 [{i+1}:v]
|
||||
def _input_label(seg: dict[str, Any]) -> str:
|
||||
# seg 必须来自 b_roll_segments;通过 id() 在原列表中查找
|
||||
for i, s in enumerate(b_roll_segments):
|
||||
if s is seg:
|
||||
return f"[{i + 1}:v]"
|
||||
# fallback: 找不到时不应发生,保守返回
|
||||
return "[1:v]"
|
||||
return ""
|
||||
|
||||
parts: list[str] = []
|
||||
sorted_segments = sorted(b_roll_segments, key=lambda s: s.get("start_time", 0))
|
||||
|
||||
# 按模式分组
|
||||
# 按模式分组处理
|
||||
fullscreen_segments = [s for s in sorted_segments if s.get("mode") == "fullscreen"]
|
||||
pip_segments = [s for s in sorted_segments if s.get("mode") == "pip"]
|
||||
|
||||
final_label = None
|
||||
|
||||
# ── fullscreen 模式: 切分 + concat ──
|
||||
if fullscreen_segments:
|
||||
fs_filter, fs_label = _build_fullscreen_filters(
|
||||
fullscreen_segments, b_roll_segments, video_duration, output_width, output_height, _input_label
|
||||
)
|
||||
parts.append(fs_filter)
|
||||
final_label = fs_label
|
||||
else:
|
||||
fs_label = None
|
||||
parts.append(_build_fullscreen_filters(fullscreen_segments, video_duration, output_width, output_height))
|
||||
|
||||
# ── pip 模式: overlay 滤镜 ──
|
||||
if pip_segments:
|
||||
pip_filter, pip_label = _build_pip_filters(
|
||||
pip_segments, output_width, output_height, _input_label, base_label=fs_label
|
||||
)
|
||||
parts.append(pip_filter)
|
||||
final_label = pip_label
|
||||
for idx, seg in enumerate(pip_segments):
|
||||
start = seg.get("start_time", 0)
|
||||
end = seg.get("end_time", video_duration)
|
||||
scale = seg.get("pip_scale", 0.3)
|
||||
position = seg.get("pip_position", "bottom_right")
|
||||
|
||||
pip_w = int(output_width * scale)
|
||||
pip_h = int(output_height * scale)
|
||||
|
||||
# 位置映射
|
||||
pos_map = {
|
||||
"top_left": "10:10",
|
||||
"top_right": "W-w-10:10",
|
||||
"bottom_left": "10:H-h-10",
|
||||
"bottom_right": "W-w-10:H-h-10",
|
||||
"center": "(W-w)/2:(H-h)/2",
|
||||
}
|
||||
pos_expr = pos_map.get(position, pos_map["bottom_right"])
|
||||
|
||||
broll_input_idx = len(sorted_segments) # placeholder for input index
|
||||
parts.append(
|
||||
f"[{broll_input_idx + idx}:v]scale={pip_w}:{pip_h}," f"enable='between(t,{start},{end})'[pip{idx}];"
|
||||
)
|
||||
# overlay onto main stream
|
||||
if idx == 0:
|
||||
base_label = "[vout]" if fullscreen_segments else "[0:v]"
|
||||
else:
|
||||
base_label = f"[pip{idx - 1}]"
|
||||
parts.append(f"{base_label}[pip{idx}]overlay={pos_expr}:enable='between(t,{start},{end})'[vout{idx}];")
|
||||
|
||||
result = "".join(parts)
|
||||
# 清理末尾多余分号
|
||||
if result.endswith(";"):
|
||||
result = result[:-1]
|
||||
return result, final_label
|
||||
return result
|
||||
|
||||
|
||||
def _build_fullscreen_filters(
|
||||
sorted_fs_segments: list[dict[str, Any]],
|
||||
all_segments: list[dict[str, Any]],
|
||||
segments: list[dict[str, Any]],
|
||||
video_duration: float,
|
||||
output_width: int,
|
||||
output_height: int,
|
||||
input_label_fn,
|
||||
) -> tuple[str, str]:
|
||||
"""构建 fullscreen 模式的切分 + concat 滤镜。
|
||||
) -> str:
|
||||
"""构建 fullscreen 模式的切分 + concat 滤镜.
|
||||
|
||||
将主视频按 B-roll 时间段切分,然后用 concat 拼接主视频片段和 B-roll 片段。
|
||||
|
||||
Returns:
|
||||
(filter_str, final_label) 其中 final_label 是 concat 输出的 pad 标签
|
||||
将对口型视频按 B-roll 时间段切分,然后用 concat 拼接 B-roll 片段。
|
||||
"""
|
||||
parts: list[str] = []
|
||||
prev_end = 0.0
|
||||
|
||||
# 注意:这里的 idx 是 sorted_fs_segments 中的下标;
|
||||
# 实际 FFmpeg 输入下标必须通过 input_label_fn 查询
|
||||
for idx, seg in enumerate(sorted_fs_segments):
|
||||
for idx, seg in enumerate(segments):
|
||||
start = seg.get("start_time", 0)
|
||||
end = seg.get("end_time", video_duration)
|
||||
|
||||
# 主视频片段(B-roll 之前)
|
||||
# 保持原视频片段(B-roll 之前的部分)
|
||||
if prev_end < start:
|
||||
parts.append(f"[0:v]trim=start={prev_end}:end={start},setpts=PTS-STARTPTS[main{idx}];")
|
||||
|
||||
# B-roll 片段:缩放到输出分辨率并裁到对应时长
|
||||
in_lbl = input_label_fn(seg)
|
||||
# B-roll 片段:缩放至目标分辨率
|
||||
parts.append(
|
||||
f"{in_lbl}scale={output_width}:{output_height}"
|
||||
f"[{idx + 1}:v]scale={output_width}:{output_height}"
|
||||
f":force_original_aspect_ratio=decrease,"
|
||||
f"pad={output_width}:{output_height}:(ow-iw)/2:(oh-ih)/2,"
|
||||
f"trim=start=0:end={end - start},setpts=PTS-STARTPTS[br{idx}];"
|
||||
)
|
||||
prev_end = end
|
||||
|
||||
# 尾部主视频片段
|
||||
# 尾部片段
|
||||
if prev_end < video_duration:
|
||||
last_idx = len(sorted_fs_segments)
|
||||
last_idx = len(segments)
|
||||
parts.append(f"[0:v]trim=start={prev_end}:end={video_duration},setpts=PTS-STARTPTS[main{last_idx}];")
|
||||
|
||||
# concat 所有片段
|
||||
segment_labels: list[str] = []
|
||||
for idx, seg in enumerate(sorted_fs_segments):
|
||||
start = seg.get("start_time", 0)
|
||||
# 每段 B-roll 之前是否有主视频片段?
|
||||
has_main_before = (idx == 0 and start > 0) or (
|
||||
idx > 0 and sorted_fs_segments[idx - 1].get("end_time", 0) < start
|
||||
)
|
||||
if has_main_before:
|
||||
segment_labels.append(f"[main{idx}]")
|
||||
segment_labels = []
|
||||
for idx in range(len(segments)):
|
||||
start = segments[idx].get("start_time", 0)
|
||||
if (idx == 0 and segments[0].get("start_time", 0) > 0) or idx > 0:
|
||||
prev_end_prev = segments[idx - 1].get("end_time", 0) if idx > 0 else 0
|
||||
if prev_end_prev < start:
|
||||
segment_labels.append(f"[main{idx}]")
|
||||
segment_labels.append(f"[br{idx}]")
|
||||
if prev_end < video_duration:
|
||||
segment_labels.append(f"[main{len(sorted_fs_segments)}]")
|
||||
|
||||
final_lbl = "vout_fs"
|
||||
if prev_end < video_duration:
|
||||
segment_labels.append(f"[main{len(segments)}]")
|
||||
|
||||
n = len(segment_labels)
|
||||
if n > 0:
|
||||
concat_inputs = "".join(segment_labels)
|
||||
parts.append(f"{concat_inputs}concat=n={n}:v=1:a=0[{final_lbl}];")
|
||||
parts.append(f"{concat_inputs}concat=n={n}:v=1:a=0[vout];")
|
||||
|
||||
return "".join(parts), final_lbl
|
||||
|
||||
|
||||
def _build_pip_filters(
|
||||
pip_segments: list[dict[str, Any]],
|
||||
output_width: int,
|
||||
output_height: int,
|
||||
input_label_fn,
|
||||
base_label: str | None,
|
||||
) -> tuple[str, str]:
|
||||
"""构建 PIP(画中画)overlay 滤镜链。
|
||||
|
||||
Args:
|
||||
pip_segments: 按时间排序的 pip 片段
|
||||
output_width: 输出宽度
|
||||
output_height: 输出高度
|
||||
input_label_fn: 片段 → 输入标签的映射函数
|
||||
base_label: 前序滤镜链输出的标签(如 fullscreen 的 vout_fs),为 None 则基于 [0:v]
|
||||
|
||||
Returns:
|
||||
(filter_str, final_label)
|
||||
"""
|
||||
parts: list[str] = []
|
||||
cur_label = base_label # 当前叠加到的标签
|
||||
|
||||
pos_map = {
|
||||
"top_left": "10:10",
|
||||
"top_right": "W-w-10:10",
|
||||
"bottom_left": "10:H-h-10",
|
||||
"bottom_right": "W-w-10:H-h-10",
|
||||
"center": "(W-w)/2:(H-h)/2",
|
||||
}
|
||||
|
||||
for idx, seg in enumerate(pip_segments):
|
||||
start = seg.get("start_time", 0)
|
||||
end = seg.get("end_time", 0)
|
||||
scale = seg.get("pip_scale", 0.3)
|
||||
position = seg.get("pip_position", "bottom_right")
|
||||
pos_expr = pos_map.get(position, pos_map["bottom_right"])
|
||||
|
||||
pip_w = max(1, int(output_width * scale))
|
||||
pip_h = max(1, int(output_height * scale))
|
||||
enable_expr = f"enable='between(t,{start},{end})'"
|
||||
|
||||
in_lbl = input_label_fn(seg)
|
||||
pip_scaled = f"pip{idx}"
|
||||
parts.append(f"{in_lbl}scale={pip_w}:{pip_h},{enable_expr}[{pip_scaled}];")
|
||||
|
||||
# overlay onto the current base
|
||||
base = f"[{cur_label}]" if cur_label else "[0:v]"
|
||||
out_lbl = f"vout_pip{idx}" if idx < len(pip_segments) - 1 else "vout"
|
||||
parts.append(f"{base}[{pip_scaled}]overlay={pos_expr}:{enable_expr}[{out_lbl}];")
|
||||
cur_label = out_lbl
|
||||
|
||||
return "".join(parts), cur_label or "vout"
|
||||
return "".join(parts)
|
||||
|
||||
|
||||
def build_cover_extract_command(
|
||||
|
||||
@@ -13,7 +13,3 @@ pytest-cov==6.0.0
|
||||
|
||||
# 工具
|
||||
python-dotenv==1.0.1
|
||||
|
||||
# AI 数字人封面智能选帧(cover_frame_scorer 用 cv2/numpy 做清晰度/亮度/色彩评分)
|
||||
numpy==1.26.4
|
||||
opencv-python-headless==4.10.0.84
|
||||
|
||||
@@ -36,20 +36,14 @@ CACHE_TAG_PRIMARY="${CACHE_TAG:-develop}"
|
||||
API_IMAGE="xiaoxia-saas-api:$VERSION"
|
||||
WORKER_IMAGE="xiaoxia-saas-worker:$VERSION"
|
||||
WEB_IMAGE="xiaoxia-saas-web:$VERSION"
|
||||
API_DEV="xiaoxia-saas-api:dev"
|
||||
WORKER_DEV="xiaoxia-saas-worker:dev"
|
||||
WEB_DEV="xiaoxia-saas-web:dev"
|
||||
API_LATEST="xiaoxia-saas-api:dev"
|
||||
WORKER_LATEST="xiaoxia-saas-worker:dev"
|
||||
|
||||
# Registry 上的完整镜像名(SHA/版本 tag)
|
||||
# Registry 上的完整镜像名
|
||||
REGISTRY_API="${REGISTRY}/xiaoxia-saas-api:$VERSION"
|
||||
REGISTRY_WORKER="${REGISTRY}/xiaoxia-saas-worker:$VERSION"
|
||||
REGISTRY_WEB="${REGISTRY}/xiaoxia-saas-web:$VERSION"
|
||||
|
||||
# Registry 上的 dev floating tag(仅 staging/develop 构建时推送,供 Watchtower 监听自动更新)
|
||||
REGISTRY_API_DEV="${REGISTRY}/xiaoxia-saas-api:dev"
|
||||
REGISTRY_WORKER_DEV="${REGISTRY}/xiaoxia-saas-worker:dev"
|
||||
REGISTRY_WEB_DEV="${REGISTRY}/xiaoxia-saas-web:dev"
|
||||
|
||||
USE_CACHE=0
|
||||
USE_PUSH=0
|
||||
CACHE_WRITE=0
|
||||
@@ -62,34 +56,23 @@ if docker buildx version >/dev/null 2>&1; then
|
||||
docker buildx use default 2>/dev/null || true
|
||||
fi
|
||||
|
||||
# ---- 是否需要推送 dev tag ----
|
||||
# staging 构建 或 develop 分支构建时才推送 :dev tag,供 Watchtower 自动更新;
|
||||
# production / release tag 构建不推送 dev tag,避免污染生产 tag 指向。
|
||||
PUSH_DEV_TAG=0
|
||||
BRANCH_NAME="${GITHUB_REF_NAME:-${CI_COMMIT_BRANCH:-unknown}}"
|
||||
if [ "$BUILD_ENV" = "staging" ] || [ "$BRANCH_NAME" = "develop" ]; then
|
||||
PUSH_DEV_TAG=1
|
||||
echo "Dev tag push: ENABLED (BUILD_ENV=$BUILD_ENV, BRANCH=$BRANCH_NAME) — Watchtower will pick up new :dev"
|
||||
else
|
||||
echo "Dev tag push: disabled (BUILD_ENV=$BUILD_ENV, BRANCH=$BRANCH_NAME)"
|
||||
fi
|
||||
|
||||
# ---- 缓存读写策略(按分支隔离)----
|
||||
# 默认只读不写,防止 feature 分支污染主缓存
|
||||
# 只有 develop/main 分支才写回缓存
|
||||
BRANCH_NAME="${GITHUB_REF_NAME:-${CI_COMMIT_BRANCH:-unknown}}"
|
||||
# 清理本地旧镜像
|
||||
docker rmi -f "$API_IMAGE" "$API_DEV" 2>/dev/null || true
|
||||
docker rmi -f "$API_IMAGE" "$API_LATEST" 2>/dev/null || true
|
||||
|
||||
if [ "$USE_CACHE" -eq 1 ]; then
|
||||
docker buildx build \
|
||||
--build-arg APP_VERSION="$VERSION" \
|
||||
--cache-from "type=registry,ref=${CACHE_REGISTRY}/api-cache:${CACHE_TAG_PRIMARY},ignore-error=true" \
|
||||
-f infra/docker/api.Dockerfile \
|
||||
-t "$API_IMAGE" -t "$API_DEV" \
|
||||
-t "$API_IMAGE" -t "$API_LATEST" \
|
||||
--load \
|
||||
.
|
||||
else
|
||||
docker build --pull=false --build-arg APP_VERSION="$VERSION" -f infra/docker/api.Dockerfile -t "$API_IMAGE" -t "$API_DEV" .
|
||||
docker build --pull=false --build-arg APP_VERSION="$VERSION" -f infra/docker/api.Dockerfile -t "$API_IMAGE" -t "$API_LATEST" .
|
||||
fi
|
||||
|
||||
build_with_cache() {
|
||||
@@ -139,22 +122,22 @@ build_with_cache() {
|
||||
echo "=== Building API image ==="
|
||||
build_with_cache "api" "infra/docker/api.Dockerfile" \
|
||||
"--build-arg APP_VERSION=$VERSION"
|
||||
docker tag "$API_IMAGE" "$API_DEV"
|
||||
docker tag "$API_IMAGE" "$API_LATEST"
|
||||
|
||||
echo "=== Building Worker image ==="
|
||||
# 清理本地旧镜像
|
||||
docker rmi -f "$WORKER_IMAGE" "$WORKER_DEV" 2>/dev/null || true
|
||||
docker rmi -f "$WORKER_IMAGE" "$WORKER_LATEST" 2>/dev/null || true
|
||||
|
||||
if [ "$USE_CACHE" -eq 1 ]; then
|
||||
docker buildx build \
|
||||
--build-arg APP_VERSION="$VERSION" \
|
||||
--cache-from "type=registry,ref=${CACHE_REGISTRY}/worker-cache:${CACHE_TAG_PRIMARY},ignore-error=true" \
|
||||
-f infra/docker/worker.Dockerfile \
|
||||
-t "$WORKER_IMAGE" -t "$WORKER_DEV" \
|
||||
-t "$WORKER_IMAGE" -t "$WORKER_LATEST" \
|
||||
--load \
|
||||
.
|
||||
else
|
||||
docker build --pull=false --build-arg APP_VERSION="$VERSION" -f infra/docker/worker.Dockerfile -t "$WORKER_IMAGE" -t "$WORKER_DEV" .
|
||||
docker build --pull=false --build-arg APP_VERSION="$VERSION" -f infra/docker/worker.Dockerfile -t "$WORKER_IMAGE" -t "$WORKER_LATEST" .
|
||||
fi
|
||||
|
||||
echo "=== Building Web image (with buildx cache) ==="
|
||||
@@ -175,52 +158,37 @@ docker run --rm \
|
||||
test -f apps/web/dist/index.html
|
||||
|
||||
# 清理本地旧镜像
|
||||
docker rmi -f "$WEB_IMAGE" "$WEB_DEV" 2>/dev/null || true
|
||||
docker rmi -f "$WEB_IMAGE" 2>/dev/null || true
|
||||
|
||||
if [ "$USE_CACHE" -eq 1 ]; then
|
||||
docker buildx build \
|
||||
--cache-from "type=registry,ref=${CACHE_REGISTRY}/web-cache:${CACHE_TAG_PRIMARY},ignore-error=true" \
|
||||
-f infra/docker/web-artifact.Dockerfile \
|
||||
--build-arg "NGINX_CONF=$NGINX_CONF_FILE" \
|
||||
-t "$WEB_IMAGE" -t "$WEB_DEV" \
|
||||
-t "$WEB_IMAGE" \
|
||||
--load \
|
||||
.
|
||||
else
|
||||
docker build --pull=false \
|
||||
-f infra/docker/web-artifact.Dockerfile \
|
||||
--build-arg "NGINX_CONF=$NGINX_CONF_FILE" \
|
||||
-t "$WEB_IMAGE" -t "$WEB_DEV" \
|
||||
-t "$WEB_IMAGE" \
|
||||
.
|
||||
fi
|
||||
|
||||
# Push 到 Registry
|
||||
if [ "$USE_PUSH" -eq 1 ]; then
|
||||
echo "=== Pushing SHA/version-tagged images to Registry ==="
|
||||
echo "=== Pushing images to Registry ==="
|
||||
docker tag "$API_IMAGE" "$REGISTRY_API"
|
||||
docker tag "$WORKER_IMAGE" "$REGISTRY_WORKER"
|
||||
docker tag "$WEB_IMAGE" "$REGISTRY_WEB"
|
||||
docker push "$REGISTRY_API"
|
||||
docker push "$REGISTRY_WORKER"
|
||||
docker push "$REGISTRY_WEB"
|
||||
echo "SHA-tagged images pushed to $REGISTRY"
|
||||
|
||||
# ---- 额外推送 :dev floating tag(仅 staging/develop)----
|
||||
# :dev tag 指向最新一次 develop/staging 构建,供 Watchtower 通过 WATCHTOWER_ROLLING_RESTART 等方式
|
||||
# 监听镜像更新并自动 pull + restart;部署脚本 (ci_staging_deploy.sh) 仍使用 SHA tag 做确定性部署,
|
||||
# dev tag 仅作为"最新 develop 成功构建"的可滚动标识,避免并发构建互相覆盖导致的不可重现问题。
|
||||
if [ "$PUSH_DEV_TAG" -eq 1 ]; then
|
||||
echo "=== Pushing :dev floating tags to Registry (for Watchtower auto-update) ==="
|
||||
docker tag "$API_IMAGE" "$REGISTRY_API_DEV"
|
||||
docker tag "$WORKER_IMAGE" "$REGISTRY_WORKER_DEV"
|
||||
docker tag "$WEB_IMAGE" "$REGISTRY_WEB_DEV"
|
||||
docker push "$REGISTRY_API_DEV"
|
||||
docker push "$REGISTRY_WORKER_DEV"
|
||||
docker push "$REGISTRY_WEB_DEV"
|
||||
echo ":dev tags pushed to $REGISTRY"
|
||||
fi
|
||||
echo "All images pushed to $REGISTRY"
|
||||
else
|
||||
echo "Registry push skipped (no auth token available)"
|
||||
fi
|
||||
|
||||
echo "=== Build complete ==="
|
||||
docker images | grep "xiaoxia-saas" | grep -E "($VERSION|dev)" || true
|
||||
docker images | grep "xiaoxia-saas" | grep "$VERSION" || true
|
||||
|
||||
@@ -1,103 +0,0 @@
|
||||
#!/bin/bash
|
||||
# ============================================
|
||||
# 基础镜像同步脚本 - 从公共镜像源同步到私有ACR
|
||||
# 用法:
|
||||
# ACR_USERNAME=xxx ACR_PASSWORD=yyy bash scripts/ci/sync_base_images.sh
|
||||
# ============================================
|
||||
|
||||
set -euo pipefail
|
||||
|
||||
ACR_REGISTRY="${ACR_REGISTRY:-xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com/xiaoxiakeji}"
|
||||
ACR_USERNAME="${ACR_USERNAME:-}"
|
||||
ACR_PASSWORD="${ACR_PASSWORD:-}"
|
||||
SOURCE_PREFIX="${SOURCE_PREFIX:-docker.m.daocloud.io/library}"
|
||||
|
||||
# 需要同步的镜像列表 (源镜像名:tag => ACR目标名:tag)
|
||||
IMAGES=(
|
||||
"python:3.12-slim-bookworm"
|
||||
"python:3.12-slim"
|
||||
"node:20"
|
||||
"nginx:alpine"
|
||||
)
|
||||
|
||||
echo "============================================"
|
||||
echo " 基础镜像同步到 ACR"
|
||||
echo " ACR: $ACR_REGISTRY"
|
||||
echo " 源: $SOURCE_PREFIX"
|
||||
echo "============================================"
|
||||
echo ""
|
||||
|
||||
# 登录 ACR
|
||||
if [ -n "$ACR_PASSWORD" ] && [ -n "$ACR_USERNAME" ]; then
|
||||
echo "登录 ACR..."
|
||||
ACR_HOST=$(echo "$ACR_REGISTRY" | cut -d/ -f1)
|
||||
printf '%s' "$ACR_PASSWORD" | docker login "$ACR_HOST" -u "$ACR_USERNAME" --password-stdin
|
||||
echo "ACR 登录成功"
|
||||
echo ""
|
||||
fi
|
||||
|
||||
success=0
|
||||
failed=0
|
||||
|
||||
for image in "${IMAGES[@]}"; do
|
||||
source_image="${SOURCE_PREFIX}/${image}"
|
||||
target_image="${ACR_REGISTRY}/base/${image}"
|
||||
|
||||
echo "--- 同步: $image ---"
|
||||
echo " 源: $source_image"
|
||||
echo " 目标: $target_image"
|
||||
|
||||
# Pull 源镜像(带重试)
|
||||
pulled=0
|
||||
for attempt in 1 2 3; do
|
||||
echo " Pull 尝试 $attempt/3..."
|
||||
if docker pull "$source_image"; then
|
||||
pulled=1
|
||||
break
|
||||
fi
|
||||
echo " Pull 失败,5s 后重试..."
|
||||
sleep 5
|
||||
done
|
||||
|
||||
if [ "$pulled" -eq 0 ]; then
|
||||
echo " ❌ Pull 失败: $image"
|
||||
failed=$((failed + 1))
|
||||
continue
|
||||
fi
|
||||
|
||||
# Tag
|
||||
docker tag "$source_image" "$target_image"
|
||||
echo " Tag 完成"
|
||||
|
||||
# Push 到 ACR
|
||||
pushed=0
|
||||
for attempt in 1 2 3; do
|
||||
echo " Push 尝试 $attempt/3..."
|
||||
if docker push "$target_image"; then
|
||||
pushed=1
|
||||
break
|
||||
fi
|
||||
echo " Push 失败,5s 后重试..."
|
||||
sleep 5
|
||||
done
|
||||
|
||||
if [ "$pushed" -eq 1 ]; then
|
||||
echo " ✅ 同步成功: $image"
|
||||
success=$((success + 1))
|
||||
else
|
||||
echo " ❌ Push 失败: $image"
|
||||
failed=$((failed + 1))
|
||||
fi
|
||||
|
||||
echo ""
|
||||
done
|
||||
|
||||
echo "============================================"
|
||||
echo " 同步完成"
|
||||
echo " 成功: $success"
|
||||
echo " 失败: $failed"
|
||||
echo "============================================"
|
||||
|
||||
if [ "$failed" -gt 0 ]; then
|
||||
exit 1
|
||||
fi
|
||||
@@ -1,157 +0,0 @@
|
||||
#!/bin/bash
|
||||
# CI Validate: 代码质量与安全扫描(并行Job 1/3)
|
||||
# 包含:密钥扫描、格式检查、安全扫描、依赖漏洞、死代码检测、脚本语法校验
|
||||
set -eu
|
||||
|
||||
echo "=== CI Validate: 代码质量与安全扫描 ==="
|
||||
|
||||
# --- 密钥检测 ---
|
||||
echo ""
|
||||
echo "=== [1/6] Secret detection (detect-secrets) ==="
|
||||
python3 -m pip install -q detect-secrets
|
||||
detect-secrets --version
|
||||
|
||||
detect-secrets scan \
|
||||
--all-files \
|
||||
--exclude-files '(^|/)(tests|test|e2e|__tests__|spec|docs|node_modules|site-packages|migrations|alembic|.gitea|.git|.pytest_cache|.next|dist|build)/' \
|
||||
--exclude-files '\.(md|rst|txt|lock|example|sample|min\.js|min\.css|spec\.ts|test\.ts|test\.py)$' \
|
||||
--exclude-files '(package-lock|yarn\.lock|poetry\.lock|Pipfile\.lock)$' \
|
||||
--disable-plugin Base64HighEntropyString \
|
||||
--disable-plugin HexHighEntropyString \
|
||||
--disable-plugin BasicAuthDetector \
|
||||
--disable-plugin KeywordDetector \
|
||||
--disable-plugin IPPublicDetector \
|
||||
> /tmp/secrets-scan.json 2>&1
|
||||
|
||||
FOUND=$(python3 -c "
|
||||
import json
|
||||
try:
|
||||
with open('/tmp/secrets-scan.json') as f:
|
||||
data = json.load(f)
|
||||
results = data.get('results', {})
|
||||
total = sum(len(v) for v in results.values())
|
||||
print(total)
|
||||
except Exception:
|
||||
print('error')
|
||||
")
|
||||
|
||||
echo "Secrets detected: $FOUND"
|
||||
if [ "$FOUND" != "0" ] && [ "$FOUND" != "error" ]; then
|
||||
echo ""
|
||||
echo "=== Secret details ==="
|
||||
python3 -c "
|
||||
import json
|
||||
with open('/tmp/secrets-scan.json') as f:
|
||||
data = json.load(f)
|
||||
for fpath, items in data.get('results', {}).items():
|
||||
for item in items:
|
||||
line = item.get('line_number', '?')
|
||||
stype = item.get('type', '?')
|
||||
hashed = item.get('hashed_secret', '')[:16]
|
||||
print(f' {fpath}:{line} [{stype}] {hashed}...')
|
||||
"
|
||||
echo ""
|
||||
echo "ERROR: Potential secrets detected in code!"
|
||||
exit 1
|
||||
fi
|
||||
echo "✅ Secret scan passed"
|
||||
|
||||
# --- 代码质量检查(全量,PR 和 push 统一标准)---
|
||||
# 历史:PR 侧用增量检查以加速,但会导致 push 侧全量检查失败时 PR 侧感知不到
|
||||
# 现在统一全量检查,确保 CI 真正保护主分支(black/isort/ruff 全量仅多几十秒)
|
||||
echo ""
|
||||
echo "=== [2/6] Code quality checks (full scan) ==="
|
||||
SCAN_MODE="full"
|
||||
echo "Full scan mode"
|
||||
python3 -m compileall -q alembic apps packages tests scripts
|
||||
python3 -m black --check --fast alembic apps packages tests scripts
|
||||
python3 -m isort --check-only alembic apps packages tests scripts
|
||||
python3 -m ruff check apps packages tests --statistics
|
||||
|
||||
echo "✅ Code quality checks passed"
|
||||
|
||||
# --- Bandit 安全扫描(仅告警) ---
|
||||
echo ""
|
||||
echo "=== [3/6] Security scan (bandit, advisory only) ==="
|
||||
set +e
|
||||
bandit -r apps packages -q -ll
|
||||
BANDIT_EXIT=$?
|
||||
set -e
|
||||
if [ "$BANDIT_EXIT" -ne 0 ]; then
|
||||
echo "⚠️ Bandit found security issues (advisory mode - not blocking CI)"
|
||||
else
|
||||
echo "✅ Bandit security scan passed"
|
||||
fi
|
||||
|
||||
# --- Pip-audit 依赖漏洞扫描(仅告警) ---
|
||||
echo ""
|
||||
echo "=== [4/6] Python dependency vulnerability scan (pip-audit, advisory only) ==="
|
||||
python3 -m pip install -q pip-audit
|
||||
pip-audit --version
|
||||
EXIT_CODE=0
|
||||
for req_file in requirements.txt requirements-base.txt requirements-dev.txt; do
|
||||
if [ -f "$req_file" ]; then
|
||||
echo "--- Scanning $req_file ---"
|
||||
pip-audit -r "$req_file" --desc on 2>&1 | head -40 || EXIT_CODE=$?
|
||||
echo ""
|
||||
fi
|
||||
done
|
||||
echo "pip-audit scan completed (advisory mode - warnings only, not blocking CI)"
|
||||
|
||||
# --- Vulture 死代码检测(仅告警) ---
|
||||
echo ""
|
||||
echo "=== [5/6] Dead code detection (vulture, advisory only) ==="
|
||||
set +e
|
||||
python3 -m pip install -q vulture
|
||||
vulture --version
|
||||
echo "告警模式,不阻断CI。置信度>=90%建议尽快确认。"
|
||||
echo ""
|
||||
vulture apps packages scripts \
|
||||
--exclude "tests,test,migrations,.gitea,docs,node_modules,site-packages,*/test_*.py,*/conftest.py" \
|
||||
--min-confidence 70 \
|
||||
2>&1 | sort -t'(' -k2 -rn | head -80
|
||||
echo ""
|
||||
echo "=== vulture scan summary ==="
|
||||
echo "发现潜在死代码(可能包含框架装饰器注册的函数,为误报)"
|
||||
echo "建议:定期人工审查高置信度(>=90%)条目"
|
||||
set -e
|
||||
|
||||
# --- CI脚本语法校验 ---
|
||||
echo ""
|
||||
echo "=== [6/6] CI & shell scripts syntax validation ==="
|
||||
SYNTAX_ERROR=0
|
||||
# 检查所有 CI shell 脚本
|
||||
for script in scripts/ci/*.sh; do
|
||||
if [ -f "$script" ]; then
|
||||
if ! bash -n "$script" 2>&1; then
|
||||
echo "❌ 语法错误: $script"
|
||||
SYNTAX_ERROR=1
|
||||
fi
|
||||
fi
|
||||
done
|
||||
# 检查所有 CI Python 脚本语法
|
||||
for script in scripts/ci/*.py; do
|
||||
if [ -f "$script" ]; then
|
||||
if ! python3 -m py_compile "$script" 2>&1; then
|
||||
echo "❌ Python语法错误: $script"
|
||||
SYNTAX_ERROR=1
|
||||
fi
|
||||
fi
|
||||
done
|
||||
# 检查 .gitea/workflows 下的脚本(如果有)
|
||||
for script in .gitea/workflows/*.sh; do
|
||||
if [ -f "$script" ]; then
|
||||
if ! bash -n "$script" 2>&1; then
|
||||
echo "❌ 语法错误: $script"
|
||||
SYNTAX_ERROR=1
|
||||
fi
|
||||
fi
|
||||
done
|
||||
if [ "$SYNTAX_ERROR" -ne 0 ]; then
|
||||
echo "❌ CI脚本语法校验失败,见上方错误"
|
||||
exit 1
|
||||
fi
|
||||
echo "✅ All CI scripts syntax OK"
|
||||
|
||||
echo ""
|
||||
echo "=== CI Validate: 代码质量与安全扫描 全部通过 ✅ ==="
|
||||
@@ -170,17 +170,16 @@ rollback() {
|
||||
--name xiaoxia-api-production \
|
||||
--env-file "$ENV_FILE" \
|
||||
--network xiaoxia-net-production \
|
||||
--network-alias xiaoxia-api \
|
||||
-p 127.0.0.1:8001:8000 \
|
||||
-e APP_ENV=production \
|
||||
-e APP_VERSION="$(echo $PREV_API_IMAGE | grep -oE '[^:]+$')" \
|
||||
-e GENERATED_FILES_DIR=/app/generated \
|
||||
-e GENERATED_FILES_URL_PREFIX=https://saas-api.xiaoxiajianji.com/generated-files \
|
||||
-e PUBLIC_API_BASE_URL=https://saas-api.xiaoxiajianji.com \
|
||||
-e GENERATED_FILES_URL_PREFIX=/generated-files \
|
||||
-e PUBLIC_API_BASE_URL=https://production-api.xiaoxiajianji.com \
|
||||
-v "$GENERATED_DIR:/app/generated" \
|
||||
--restart unless-stopped \
|
||||
--cpus 2 \
|
||||
--memory 2g \
|
||||
--cpus 2 \
|
||||
--memory 2g \
|
||||
--health-cmd "python -c \"import urllib.request; urllib.request.urlopen('http://localhost:8000/health', timeout=5)\"" \
|
||||
--health-interval 30s \
|
||||
--health-timeout 10s \
|
||||
@@ -197,29 +196,26 @@ rollback() {
|
||||
echo "Rolling back Worker to: $PREV_WORKER_IMAGE"
|
||||
docker run -d \
|
||||
--name xiaoxia-worker-production \
|
||||
--network xiaoxia-net-production \
|
||||
--network-alias xiaoxia-worker \
|
||||
--network-alias xiaoxia-api \
|
||||
--env-file "$ENV_FILE" \
|
||||
--network xiaoxia-net-production \
|
||||
-e APP_ENV=production \
|
||||
-e APP_VERSION="$(echo $PREV_WORKER_IMAGE | grep -oE '[^:]+$')" \
|
||||
-e WORKER_CONCURRENCY=1 \
|
||||
-e WORKER_MAX_TASKS_PER_CHILD=100 \
|
||||
-e GENERATED_FILES_DIR=/app/generated \
|
||||
-e GENERATED_FILES_URL_PREFIX=https://saas-api.xiaoxiajianji.com/generated-files \
|
||||
-e PYTHONPATH=/app:/app/apps/api:/app/packages \
|
||||
-e GENERATED_FILES_URL_PREFIX=/generated-files \
|
||||
-e PUBLIC_API_BASE_URL=https://production-api.xiaoxiajianji.com \
|
||||
-v "$GENERATED_DIR:/app/generated" \
|
||||
-v "$LEGACY_ASSETS_DIR:/app/legacy-assets" \
|
||||
-w /app/apps/worker \
|
||||
--restart unless-stopped \
|
||||
--cpus 2 \
|
||||
--memory 3g \
|
||||
--health-cmd "sh -c 'PYTHONPATH=/app:/app/apps/api:/app/packages celery -A worker_app.celery_app inspect ping -t 5 2>&1 | grep -q pong'" \
|
||||
--cpus 2 \
|
||||
--memory 2g \
|
||||
--health-cmd "sh -c \"for pid in /proc/[0-9]*/cmdline; do if grep -ql celery \"$pid\" 2>/dev/null; then exit 0; fi; done; exit 1\"" \
|
||||
--health-interval 30s \
|
||||
--health-timeout 15s \
|
||||
--health-timeout 10s \
|
||||
--health-retries 3 \
|
||||
--health-start-period 60s \
|
||||
--log-driver json-file --log-opt max-size=200m --log-opt max-file=5 \
|
||||
"$PREV_WORKER_IMAGE" \
|
||||
/usr/local/bin/entrypoint-worker.sh
|
||||
--health-start-period 30s \
|
||||
$LOG_OPTS \
|
||||
"$PREV_WORKER_IMAGE"
|
||||
else
|
||||
echo "No previous Worker image to roll back to"
|
||||
fi
|
||||
@@ -234,15 +230,12 @@ rollback() {
|
||||
docker run -d \
|
||||
--name xiaoxia-web-production \
|
||||
--network xiaoxia-net-production \
|
||||
--network-alias xiaoxia-web \
|
||||
-p 127.0.0.1:3002:80 \
|
||||
-e APP_ENV=production \
|
||||
-e API_BASE_URL=https://saas-api.xiaoxiajianji.com \
|
||||
-v "$NGINX_CONF_FILE:/etc/nginx/conf.d/default.conf:ro" \
|
||||
$LEGACY_VOLUME \
|
||||
--restart unless-stopped \
|
||||
--cpus 1 \
|
||||
--memory 512m \
|
||||
--cpus 0.5 \
|
||||
--memory 512m \
|
||||
$LEGACY_VOLUME \
|
||||
-v "$NGINX_CONF_FILE:/etc/nginx/conf.d/default.conf:ro" \
|
||||
--health-cmd "wget --spider -q http://127.0.0.1:80" \
|
||||
--health-interval 30s \
|
||||
--health-timeout 5s \
|
||||
@@ -380,13 +373,12 @@ docker run -d \
|
||||
--name xiaoxia-api-production \
|
||||
--env-file "$ENV_FILE" \
|
||||
--network xiaoxia-net-production \
|
||||
--network-alias xiaoxia-api \
|
||||
-p 127.0.0.1:8001:8000 \
|
||||
-e APP_ENV=production \
|
||||
-e APP_VERSION="$IMAGE_TAG" \
|
||||
-e GENERATED_FILES_DIR=/app/generated \
|
||||
-e GENERATED_FILES_URL_PREFIX=https://saas-api.xiaoxiajianji.com/generated-files \
|
||||
-e PUBLIC_API_BASE_URL=https://saas-api.xiaoxiajianji.com \
|
||||
-e GENERATED_FILES_URL_PREFIX=/generated-files \
|
||||
-e PUBLIC_API_BASE_URL=https://production-api.xiaoxiajianji.com \
|
||||
-v "$GENERATED_DIR:/app/generated" \
|
||||
--restart unless-stopped \
|
||||
--cpus 2 \
|
||||
@@ -403,29 +395,26 @@ docker run -d \
|
||||
echo "Starting Worker container..."
|
||||
docker run -d \
|
||||
--name xiaoxia-worker-production \
|
||||
--network xiaoxia-net-production \
|
||||
--network-alias xiaoxia-worker \
|
||||
--network-alias xiaoxia-api \
|
||||
--env-file "$ENV_FILE" \
|
||||
--network xiaoxia-net-production \
|
||||
-e APP_ENV=production \
|
||||
-e APP_VERSION="$IMAGE_TAG" \
|
||||
-e WORKER_CONCURRENCY=1 \
|
||||
-e WORKER_MAX_TASKS_PER_CHILD=100 \
|
||||
-e GENERATED_FILES_DIR=/app/generated \
|
||||
-e GENERATED_FILES_URL_PREFIX=https://saas-api.xiaoxiajianji.com/generated-files \
|
||||
-e PYTHONPATH=/app:/app/apps/api:/app/packages \
|
||||
-e GENERATED_FILES_URL_PREFIX=/generated-files \
|
||||
-e PUBLIC_API_BASE_URL=https://production-api.xiaoxiajianji.com \
|
||||
-v "$GENERATED_DIR:/app/generated" \
|
||||
-v "$LEGACY_ASSETS_DIR:/app/legacy-assets" \
|
||||
-w /app/apps/worker \
|
||||
--restart unless-stopped \
|
||||
--cpus 2 \
|
||||
--memory 3g \
|
||||
--health-cmd "sh -c 'PYTHONPATH=/app:/app/apps/api:/app/packages celery -A worker_app.celery_app inspect ping -t 5 2>&1 | grep -q pong'" \
|
||||
--memory 2g \
|
||||
--health-cmd "sh -c \"for pid in /proc/[0-9]*/cmdline; do if grep -ql celery \"$pid\" 2>/dev/null; then exit 0; fi; done; exit 1\"" \
|
||||
--health-interval 30s \
|
||||
--health-timeout 15s \
|
||||
--health-timeout 10s \
|
||||
--health-retries 3 \
|
||||
--health-start-period 60s \
|
||||
--log-driver json-file --log-opt max-size=200m --log-opt max-file=5 \
|
||||
"$REGISTRY_WORKER" \
|
||||
/usr/local/bin/entrypoint-worker.sh || rollback
|
||||
--health-start-period 30s \
|
||||
$LOG_OPTS \
|
||||
"$REGISTRY_WORKER" || rollback
|
||||
|
||||
# ---- 启动 Web ----
|
||||
LEGACY_VOLUME=""
|
||||
@@ -440,15 +429,12 @@ echo "Starting Web container..."
|
||||
docker run -d \
|
||||
--name xiaoxia-web-production \
|
||||
--network xiaoxia-net-production \
|
||||
--network-alias xiaoxia-web \
|
||||
-p 127.0.0.1:3002:80 \
|
||||
-e APP_ENV=production \
|
||||
-e API_BASE_URL=https://saas-api.xiaoxiajianji.com \
|
||||
--restart unless-stopped \
|
||||
--cpus 0.5 \
|
||||
--memory 512m \
|
||||
-v "$NGINX_CONF_FILE:/etc/nginx/conf.d/default.conf:ro" \
|
||||
$LEGACY_VOLUME \
|
||||
--restart unless-stopped \
|
||||
--cpus 1 \
|
||||
--memory 512m \
|
||||
--health-cmd "wget --spider -q http://127.0.0.1:80" \
|
||||
--health-interval 30s \
|
||||
--health-timeout 5s \
|
||||
@@ -501,7 +487,7 @@ docker builder prune -af --filter "until=168h" 2>/dev/null || true
|
||||
|
||||
echo ""
|
||||
echo "=== Production deployment complete ==="
|
||||
echo "API: http://127.0.0.1:8001"
|
||||
echo "Web: http://127.0.0.1:3002"
|
||||
echo "API: http://127.0.0.1:8000"
|
||||
echo "Web: http://127.0.0.1:3001"
|
||||
echo "Version: $IMAGE_TAG"
|
||||
docker ps --format "table {{.Names}}\t{{.Status}}\t{{.Image}}" | grep production
|
||||
|
||||
@@ -264,9 +264,6 @@ if [ -n "$REGISTRY_TOKEN" ]; then
|
||||
fi
|
||||
|
||||
# ---- 并行 Pull 三个镜像 ----
|
||||
# 注意:这里必须使用 IMAGE_TAG(commit SHA)做确定性部署,不要改成 :dev。
|
||||
# :dev 是 floating tag,可能被并发构建覆盖,导致部署版本不可重现、回滚混乱。
|
||||
# Watchtower 可监听 :dev 做非关键路径的自动同步;正式部署/回滚一律锚定 SHA。
|
||||
REGISTRY_API="${REGISTRY}/xiaoxia-saas-api:${IMAGE_TAG}"
|
||||
REGISTRY_WORKER="${REGISTRY}/xiaoxia-saas-worker:${IMAGE_TAG}"
|
||||
REGISTRY_WEB="${REGISTRY}/xiaoxia-saas-web:${IMAGE_TAG}"
|
||||
|
||||
@@ -17,9 +17,9 @@
|
||||
# SKIP_NOTIFY - 跳过通知 (true/false, 默认 false)
|
||||
# CI_NOTIFY_WEBHOOK - 通知 Webhook URL
|
||||
#
|
||||
# STAGING_SSH_HOST - Staging 服务器 SSH 地址 (默认 127.0.0.1,CI runner 在 staging 本机)
|
||||
# STAGING_SSH_HOST - Staging 服务器 SSH 地址 (默认 47.98.113.167)
|
||||
# STAGING_SSH_USER - SSH 用户名 (默认 root)
|
||||
# STAGING_SSH_PORT - SSH 端口 (默认 22)
|
||||
# STAGING_SSH_PORT - SSH 端口 (默认 22222)
|
||||
# STAGING_SSH_KEY - SSH 私钥内容
|
||||
# REGISTRY_TOKEN - Registry Token(回滚时拉取旧镜像需要)
|
||||
#
|
||||
@@ -40,9 +40,9 @@ HEALTH_CHECK_TIMEOUT="${HEALTH_CHECK_TIMEOUT:-120}"
|
||||
SKIP_ROLLBACK="${SKIP_ROLLBACK:-false}"
|
||||
SKIP_NOTIFY="${SKIP_NOTIFY:-false}"
|
||||
|
||||
STAGING_SSH_HOST="${STAGING_SSH_HOST:-127.0.0.1}"
|
||||
STAGING_SSH_HOST="${STAGING_SSH_HOST:-47.98.113.167}"
|
||||
STAGING_SSH_USER="${STAGING_SSH_USER:-root}"
|
||||
STAGING_SSH_PORT="${STAGING_SSH_PORT:-22}"
|
||||
STAGING_SSH_PORT="${STAGING_SSH_PORT:-22222}"
|
||||
|
||||
REGISTRY="${REGISTRY:-git.xiaoxiajianji.com/xiaoxia/xiaoxia-saas}"
|
||||
REGISTRY_USER="${REGISTRY_USER:-xiaoxia}"
|
||||
|
||||
@@ -87,19 +87,28 @@ class TestGeneratedVideoCreate:
|
||||
assert v.file_url == "http://x/v"
|
||||
|
||||
def test_create_empty_project_id(self):
|
||||
"""空 project_id 允许(AI数字人无项目场景)."""
|
||||
v = GeneratedVideo.create("", "t1", "v", "http://x/v")
|
||||
assert v.project_id == ""
|
||||
"""空 project_id 无效."""
|
||||
try:
|
||||
GeneratedVideo.create("", "t1", "v", "http://x/v")
|
||||
assert False
|
||||
except ValueError as e:
|
||||
assert "project_id" in str(e)
|
||||
|
||||
def test_create_whitespace_project_id(self):
|
||||
"""纯空白 project_id 归一化为空串."""
|
||||
v = GeneratedVideo.create(" ", "t1", "v", "http://x/v")
|
||||
assert v.project_id == ""
|
||||
"""纯空白 project_id 无效."""
|
||||
try:
|
||||
GeneratedVideo.create(" ", "t1", "v", "http://x/v")
|
||||
assert False
|
||||
except ValueError as e:
|
||||
assert "project_id" in str(e)
|
||||
|
||||
def test_create_empty_task_id(self):
|
||||
"""空 generation_task_id 允许."""
|
||||
v = GeneratedVideo.create("p1", "", "v", "http://x/v")
|
||||
assert v.generation_task_id == ""
|
||||
"""空 generation_task_id 无效."""
|
||||
try:
|
||||
GeneratedVideo.create("p1", "", "v", "http://x/v")
|
||||
assert False
|
||||
except ValueError as e:
|
||||
assert "generation_task_id" in str(e)
|
||||
|
||||
def test_create_empty_name(self):
|
||||
"""空 name 无效."""
|
||||
|
||||
@@ -262,8 +262,8 @@ def test_smart_cover_selects_best_frame_and_persists():
|
||||
score_patch.assert_called_once()
|
||||
# 验证使用了增大的轮询参数
|
||||
call_kwargs = mk.extract_frames.call_args
|
||||
assert call_kwargs.kwargs.get("poll_interval") == 2.0 or call_kwargs[1].get("poll_interval") == 2.0
|
||||
assert call_kwargs.kwargs.get("max_poll_attempts") == 30 or call_kwargs[1].get("max_poll_attempts") == 30
|
||||
assert call_kwargs.kwargs.get("poll_interval") == 3.0 or call_kwargs[1].get("poll_interval") == 3.0
|
||||
assert call_kwargs.kwargs.get("max_poll_attempts") == 20 or call_kwargs[1].get("max_poll_attempts") == 20
|
||||
|
||||
|
||||
def test_smart_cover_returns_empty_when_mediakit_unavailable():
|
||||
@@ -334,8 +334,8 @@ def test_extract_frames_uses_extended_poll_params():
|
||||
cov.select_best_cover_frame("https://other/avatar.mp4", max_frames=3)
|
||||
|
||||
call_kwargs = mk.extract_frames.call_args
|
||||
assert call_kwargs.kwargs.get("poll_interval") == 2.0 or call_kwargs[1].get("poll_interval") == 2.0
|
||||
assert call_kwargs.kwargs.get("max_poll_attempts") == 30 or call_kwargs[1].get("max_poll_attempts") == 30
|
||||
assert call_kwargs.kwargs.get("poll_interval") == 3.0 or call_kwargs[1].get("poll_interval") == 3.0
|
||||
assert call_kwargs.kwargs.get("max_poll_attempts") == 20 or call_kwargs[1].get("max_poll_attempts") == 20
|
||||
assert call_kwargs.kwargs.get("max_retries") == 1 or call_kwargs[1].get("max_retries") == 1
|
||||
|
||||
|
||||
|
||||
@@ -258,9 +258,8 @@ class TestBrollOverlayFilter:
|
||||
def test_empty_segments_returns_empty(self):
|
||||
from packages.domain.video_filter_builder import build_broll_overlay_filter
|
||||
|
||||
result, label = build_broll_overlay_filter([], 30.0)
|
||||
result = build_broll_overlay_filter([], 30.0)
|
||||
assert result == ""
|
||||
assert label is None
|
||||
|
||||
def test_pip_mode_generates_overlay(self):
|
||||
from packages.domain.video_filter_builder import build_broll_overlay_filter
|
||||
@@ -276,9 +275,8 @@ class TestBrollOverlayFilter:
|
||||
"pip_scale": 0.3,
|
||||
}
|
||||
]
|
||||
result, label = build_broll_overlay_filter(segments, 30.0)
|
||||
result = build_broll_overlay_filter(segments, 30.0)
|
||||
assert "overlay" in result or "scale=" in result
|
||||
assert label == "vout"
|
||||
|
||||
def test_fullscreen_mode_generates_concat(self):
|
||||
from packages.domain.video_filter_builder import build_broll_overlay_filter
|
||||
@@ -292,9 +290,8 @@ class TestBrollOverlayFilter:
|
||||
"end_time": 10.0,
|
||||
}
|
||||
]
|
||||
result, label = build_broll_overlay_filter(segments, 30.0)
|
||||
result = build_broll_overlay_filter(segments, 30.0)
|
||||
assert "trim" in result or "concat" in result
|
||||
assert label == "vout_fs"
|
||||
|
||||
def test_cover_extract_command(self):
|
||||
from packages.domain.video_filter_builder import build_cover_extract_command
|
||||
@@ -318,120 +315,3 @@ class TestBrollOverlayFilter:
|
||||
"/tmp/cover.jpg",
|
||||
)
|
||||
assert "scale=" in cmd
|
||||
|
||||
|
||||
def _make_mock_auth_user(user_id="user-1"):
|
||||
"""构造 AuthenticatedUser:current_user.user.id."""
|
||||
auth = MagicMock()
|
||||
auth.user.id = user_id
|
||||
return auth
|
||||
|
||||
|
||||
class TestRenderSmartCoverRoute:
|
||||
"""POST /renders/{job_id}/smart-cover — 从成片智能抽封面(步骤②)."""
|
||||
|
||||
def test_smart_cover_job_not_found_returns_404(self):
|
||||
"""渲染任务不存在 → 404."""
|
||||
from app.api.routes.ai_avatar_render import generate_render_smart_cover
|
||||
from fastapi import HTTPException
|
||||
|
||||
mock_service = MagicMock()
|
||||
mock_service.get_render_job.return_value = None
|
||||
mock_db = MagicMock()
|
||||
mock_user = _make_mock_auth_user()
|
||||
|
||||
# 函数内部 `from app.services.ai_avatar_render_service import AiAvatarRenderService`
|
||||
with patch("app.services.ai_avatar_render_service.AiAvatarRenderService", return_value=mock_service):
|
||||
with pytest.raises(HTTPException) as exc_info:
|
||||
generate_render_smart_cover(job_id="render-missing", current_user=mock_user, db=mock_db)
|
||||
|
||||
assert exc_info.value.status_code == 404
|
||||
assert "不存在" in exc_info.value.detail
|
||||
mock_service.get_render_job.assert_called_once_with("render-missing", "user-1")
|
||||
|
||||
def test_smart_cover_job_not_completed_returns_400(self):
|
||||
"""任务未 completed(如 processing)→ 400."""
|
||||
from app.api.routes.ai_avatar_render import generate_render_smart_cover
|
||||
from fastapi import HTTPException
|
||||
|
||||
mock_service = MagicMock()
|
||||
mock_job = _make_mock_render_job(status="processing", output_video_url="https://oss/video.mp4")
|
||||
mock_service.get_render_job.return_value = mock_job
|
||||
mock_db = MagicMock()
|
||||
mock_user = _make_mock_auth_user()
|
||||
|
||||
with patch("app.services.ai_avatar_render_service.AiAvatarRenderService", return_value=mock_service):
|
||||
with pytest.raises(HTTPException) as exc_info:
|
||||
generate_render_smart_cover(job_id="render-1", current_user=mock_user, db=mock_db)
|
||||
|
||||
assert exc_info.value.status_code == 400
|
||||
assert "先完成视频生成" in exc_info.value.detail
|
||||
|
||||
def test_smart_cover_empty_video_url_returns_400(self):
|
||||
"""已 completed 但 output_video_url 为空/空白 → 400."""
|
||||
from app.api.routes.ai_avatar_render import generate_render_smart_cover
|
||||
from fastapi import HTTPException
|
||||
|
||||
mock_service = MagicMock()
|
||||
mock_job = _make_mock_render_job(status="completed", output_video_url=" ")
|
||||
mock_service.get_render_job.return_value = mock_job
|
||||
mock_db = MagicMock()
|
||||
mock_user = _make_mock_auth_user()
|
||||
|
||||
with patch("app.services.ai_avatar_render_service.AiAvatarRenderService", return_value=mock_service):
|
||||
with pytest.raises(HTTPException) as exc_info:
|
||||
generate_render_smart_cover(job_id="render-1", current_user=mock_user, db=mock_db)
|
||||
|
||||
assert exc_info.value.status_code == 400
|
||||
assert "URL 为空" in exc_info.value.detail
|
||||
|
||||
def test_smart_cover_success_updates_db_and_returns_url(self):
|
||||
"""抽帧成功 → 更新 job.cover_config / output_cover_url 并 commit,返回 completed."""
|
||||
from app.api.routes.ai_avatar_render import generate_render_smart_cover
|
||||
|
||||
mock_service = MagicMock()
|
||||
mock_job = _make_mock_render_job(
|
||||
status="completed",
|
||||
output_video_url="https://oss/final.mp4",
|
||||
)
|
||||
mock_job.cover_config = {"mode": "manual"}
|
||||
mock_service.get_render_job.return_value = mock_job
|
||||
mock_db = MagicMock()
|
||||
mock_user = _make_mock_auth_user()
|
||||
|
||||
with (
|
||||
patch("app.services.ai_avatar_render_service.AiAvatarRenderService", return_value=mock_service),
|
||||
patch(
|
||||
"app.api.routes.ai_avatar_render.generate_smart_cover", return_value="https://oss/cover.jpg"
|
||||
) as mock_gen,
|
||||
):
|
||||
result = generate_render_smart_cover(job_id="render-1", current_user=mock_user, db=mock_db)
|
||||
|
||||
mock_gen.assert_called_once_with("https://oss/final.mp4", job_id="render-1", max_frames=5)
|
||||
assert result.status == "completed"
|
||||
assert result.cover_url == "https://oss/cover.jpg"
|
||||
assert mock_job.output_cover_url == "https://oss/cover.jpg"
|
||||
assert mock_job.cover_config["mode"] == "auto_frame"
|
||||
assert mock_job.cover_config["url"] == "https://oss/cover.jpg"
|
||||
mock_db.commit.assert_called_once()
|
||||
|
||||
def test_smart_cover_extract_failure_returns_fallback_failed(self):
|
||||
"""generate_smart_cover 抛异常 → fallback_failed,不抛错不写 DB."""
|
||||
from app.api.routes.ai_avatar_render import generate_render_smart_cover
|
||||
|
||||
mock_service = MagicMock()
|
||||
mock_job = _make_mock_render_job(status="completed", output_video_url="https://oss/final.mp4")
|
||||
mock_service.get_render_job.return_value = mock_job
|
||||
mock_db = MagicMock()
|
||||
mock_user = _make_mock_auth_user()
|
||||
|
||||
with (
|
||||
patch("app.services.ai_avatar_render_service.AiAvatarRenderService", return_value=mock_service),
|
||||
patch("app.api.routes.ai_avatar_render.generate_smart_cover", side_effect=RuntimeError("mediakit down")),
|
||||
):
|
||||
result = generate_render_smart_cover(job_id="render-1", current_user=mock_user, db=mock_db)
|
||||
|
||||
assert result.status == "fallback_failed"
|
||||
assert result.cover_url == ""
|
||||
# 失败时不写 cover_config / 不 commit
|
||||
mock_db.commit.assert_not_called()
|
||||
|
||||
@@ -519,8 +519,8 @@ class TestAiAvatarRenderService:
|
||||
# 不应执行渲染逻辑
|
||||
mock_db.commit.assert_not_called()
|
||||
|
||||
def test_execute_render_completed_does_not_auto_persist(self):
|
||||
"""execute_render 完成后不自动入库成片库(改为用户点「完成」时由 finalize_job 入库)."""
|
||||
def test_execute_render_success_creates_clip_record(self):
|
||||
"""execute_render 完成后自动创建成片记录到成片库."""
|
||||
from app.services.ai_avatar_render_service import AiAvatarRenderService
|
||||
|
||||
mock_db = _make_mock_db()
|
||||
@@ -547,141 +547,35 @@ class TestAiAvatarRenderService:
|
||||
with (
|
||||
patch.object(svc, "_download_video", return_value="/tmp/video.mp4"),
|
||||
patch.object(svc, "_upload_to_oss", side_effect=lambda path, key: f"https://oss/{key}"),
|
||||
patch("subprocess.run") as mock_run,
|
||||
patch("os.system", return_value=0),
|
||||
patch("tempfile.TemporaryDirectory") as tmpdir_mock,
|
||||
patch(
|
||||
"app.services.ai_avatar_cover_service.generate_smart_cover", return_value="https://oss/smart_cover.jpg"
|
||||
),
|
||||
patch("packages.domain.generated_video.GeneratedVideo.create") as gv_create,
|
||||
patch(
|
||||
"packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository"
|
||||
) as repo_cls,
|
||||
):
|
||||
import subprocess as _sp
|
||||
import tempfile as _tf
|
||||
|
||||
mock_run.return_value = _sp.CompletedProcess(args=[], returncode=0, stdout="", stderr="")
|
||||
tmpdir_mock.return_value.__enter__ = MagicMock(return_value="/tmp/testdir")
|
||||
tmpdir_mock.return_value.__exit__ = MagicMock(return_value=False)
|
||||
|
||||
svc.execute_render("render-ok")
|
||||
|
||||
# 状态应为 completed,但没有自动入库
|
||||
assert mock_job.status == "completed"
|
||||
gv_create.assert_not_called()
|
||||
assert mock_job.output_video_url.startswith("https://oss/")
|
||||
|
||||
def test_finalize_job_persists_to_library(self):
|
||||
"""finalize_job 在用户点「完成」后写入成片库,thumbnail_url 使用 job.output_cover_url."""
|
||||
from app.services.ai_avatar_render_service import AiAvatarRenderService
|
||||
|
||||
mock_db = MagicMock()
|
||||
mock_job = _make_mock_render_job(
|
||||
job_id="render-finalize",
|
||||
status="completed",
|
||||
output_video_url="https://oss/ai-avatar/render-finalize/output.mp4",
|
||||
output_cover_url="https://oss/cover.jpg",
|
||||
output_duration=12.0,
|
||||
)
|
||||
|
||||
# get_render_job → db.query(AiAvatarRenderJob).filter().first() 返回 mock_job
|
||||
# finalize 幂等检查 → db.query(GeneratedVideoModel).filter().first() 返回 None(未入库)
|
||||
def _query_side_effect(model):
|
||||
q = MagicMock()
|
||||
if model.__name__ == "AiAvatarRenderJob":
|
||||
q.filter.return_value.first.return_value = mock_job
|
||||
else:
|
||||
# GeneratedVideoModel
|
||||
q.filter.return_value.first.return_value = None
|
||||
return q
|
||||
|
||||
mock_db.query.side_effect = _query_side_effect
|
||||
|
||||
svc = AiAvatarRenderService(mock_db)
|
||||
|
||||
with (
|
||||
patch("packages.domain.generated_video.GeneratedVideo.create") as gv_create,
|
||||
patch(
|
||||
"packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository"
|
||||
) as repo_cls,
|
||||
):
|
||||
mock_clip = MagicMock()
|
||||
mock_clip.id = "clip-new"
|
||||
mock_clip.thumbnail_url = "https://oss/cover.jpg"
|
||||
mock_clip.id = "clip-001"
|
||||
gv_create.return_value = mock_clip
|
||||
mock_repo = MagicMock()
|
||||
mock_repo.create.return_value = mock_clip
|
||||
mock_repo.get.return_value = mock_clip
|
||||
repo_cls.return_value = mock_repo
|
||||
|
||||
video = svc.finalize_job("render-finalize", "user-1")
|
||||
assert video.id == "clip-new"
|
||||
gv_create.assert_called_once()
|
||||
call_kwargs = gv_create.call_args.kwargs
|
||||
assert call_kwargs["file_url"].endswith("output.mp4")
|
||||
assert call_kwargs["thumbnail_url"] == "https://oss/cover.jpg"
|
||||
assert call_kwargs["generation_task_id"] == "render-finalize"
|
||||
mock_repo.create.assert_called_once()
|
||||
svc.execute_render("render-ok")
|
||||
|
||||
def test_finalize_job_idempotent_when_already_persisted(self):
|
||||
"""finalize_job 重复调用:幂等检查命中后直接返回已有记录,不再 create."""
|
||||
from app.services.ai_avatar_render_service import AiAvatarRenderService
|
||||
|
||||
mock_db = MagicMock()
|
||||
mock_job = _make_mock_render_job(
|
||||
job_id="render-finalize-2",
|
||||
status="completed",
|
||||
output_video_url="https://oss/output.mp4",
|
||||
output_cover_url="https://oss/cover.jpg",
|
||||
output_duration=12.0,
|
||||
)
|
||||
existing_model = MagicMock()
|
||||
existing_model.id = "clip-existing"
|
||||
existing_model.thumbnail_url = "https://oss/cover.jpg"
|
||||
|
||||
def _query_side_effect(model):
|
||||
q = MagicMock()
|
||||
if model.__name__ == "AiAvatarRenderJob":
|
||||
q.filter.return_value.first.return_value = mock_job
|
||||
else:
|
||||
q.filter.return_value.first.return_value = existing_model
|
||||
return q
|
||||
|
||||
mock_db.query.side_effect = _query_side_effect
|
||||
|
||||
svc = AiAvatarRenderService(mock_db)
|
||||
|
||||
with (
|
||||
patch("packages.domain.generated_video.GeneratedVideo.create") as gv_create,
|
||||
patch(
|
||||
"packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository"
|
||||
) as repo_cls,
|
||||
):
|
||||
mock_existing = MagicMock()
|
||||
mock_existing.id = "clip-existing"
|
||||
mock_repo = MagicMock()
|
||||
mock_repo.get.return_value = mock_existing
|
||||
repo_cls.return_value = mock_repo
|
||||
|
||||
video = svc.finalize_job("render-finalize-2", "user-1")
|
||||
assert video.id == "clip-existing"
|
||||
gv_create.assert_not_called()
|
||||
mock_repo.create.assert_not_called()
|
||||
|
||||
def test_finalize_job_requires_completed_status(self):
|
||||
"""finalize_job 在非 completed 状态下抛异常."""
|
||||
from app.services.ai_avatar_render_service import AiAvatarRenderError, AiAvatarRenderService
|
||||
|
||||
mock_db = MagicMock()
|
||||
mock_job = _make_mock_render_job(
|
||||
job_id="render-pending",
|
||||
status="processing",
|
||||
output_video_url="",
|
||||
output_cover_url="",
|
||||
output_duration=0.0,
|
||||
)
|
||||
filter_mock = MagicMock()
|
||||
filter_mock.first.return_value = mock_job
|
||||
query_mock = MagicMock()
|
||||
query_mock.filter.return_value = filter_mock
|
||||
mock_db.query.return_value = query_mock
|
||||
|
||||
svc = AiAvatarRenderService(mock_db)
|
||||
with pytest.raises(AiAvatarRenderError):
|
||||
svc.finalize_job("render-pending", "user-1")
|
||||
assert mock_job.status == "completed"
|
||||
gv_create.assert_called_once()
|
||||
call_kwargs = gv_create.call_args
|
||||
assert "https://oss/" in call_kwargs.kwargs["file_url"]
|
||||
assert call_kwargs.kwargs["user_id"] == "user-1"
|
||||
mock_repo.create.assert_called_once_with(mock_clip)
|
||||
|
||||
def test_execute_render_clip_failure_does_not_affect_render(self):
|
||||
"""成片创建失败不影响渲染任务标记为成功."""
|
||||
@@ -711,17 +605,15 @@ class TestAiAvatarRenderService:
|
||||
with (
|
||||
patch.object(svc, "_download_video", return_value="/tmp/video.mp4"),
|
||||
patch.object(svc, "_upload_to_oss", side_effect=lambda path, key: f"https://oss/{key}"),
|
||||
patch("subprocess.run") as mock_run,
|
||||
patch("os.system", return_value=0),
|
||||
patch("tempfile.TemporaryDirectory") as tmpdir_mock,
|
||||
patch("app.services.ai_avatar_cover_service.generate_smart_cover", side_effect=RuntimeError("DB error")),
|
||||
):
|
||||
import subprocess as _sp
|
||||
|
||||
mock_run.return_value = _sp.CompletedProcess(args=[], returncode=0, stdout="", stderr="")
|
||||
tmpdir_mock.return_value.__enter__ = MagicMock(return_value="/tmp/testdir")
|
||||
tmpdir_mock.return_value.__exit__ = MagicMock(return_value=False)
|
||||
svc.execute_render("render-clip-fail")
|
||||
|
||||
# 渲染任务仍应标记为 completed(不入库不影响渲染成功)
|
||||
# 即使成片创建失败,渲染任务仍应标记为 completed
|
||||
assert mock_job.status == "completed"
|
||||
|
||||
def test_error_exception_has_code(self):
|
||||
@@ -730,58 +622,3 @@ class TestAiAvatarRenderService:
|
||||
err = AiAvatarRenderError("测试错误", code="TestCode")
|
||||
assert err.code == "TestCode"
|
||||
assert str(err) == "测试错误"
|
||||
|
||||
|
||||
class TestAiAvatarRenderCoverPassthrough:
|
||||
"""execute_render 中封面透传逻辑(320~329 行):cover_config 含 url/imageUrl/cover_url 时直接透传到 output_cover_url."""
|
||||
|
||||
def _run_execute(self, mock_job, mock_lipsync_job):
|
||||
"""驱动 execute_render 跑到完成阶段的通用脚手架(mock IO 部分)."""
|
||||
from app.services.ai_avatar_render_service import AiAvatarRenderService
|
||||
|
||||
mock_db = _make_mock_db()
|
||||
mock_filter = MagicMock()
|
||||
# query.filter 返回同一个 filter 两次(render_job 查询、lipsync 查询)
|
||||
mock_filter.first.side_effect = [mock_job, mock_lipsync_job]
|
||||
mock_query = MagicMock()
|
||||
mock_query.filter.return_value = mock_filter
|
||||
mock_db.query.return_value = mock_query
|
||||
|
||||
svc = AiAvatarRenderService(mock_db)
|
||||
with (
|
||||
patch.object(svc, "_download_video", return_value="/tmp/video.mp4"),
|
||||
patch.object(svc, "_upload_to_oss", side_effect=lambda path, key: f"https://oss/{key}"),
|
||||
patch("subprocess.run") as mock_run,
|
||||
patch("tempfile.TemporaryDirectory") as tmpdir_mock,
|
||||
patch("app.services.ai_avatar_cover_service.generate_smart_cover", return_value=""),
|
||||
patch("packages.domain.generated_video.GeneratedVideo.create", return_value=MagicMock()),
|
||||
patch(
|
||||
"packages.adapters.sqlalchemy_impl.generated_video_repository.SQLAlchemyGeneratedVideoRepository"
|
||||
) as repo_cls,
|
||||
):
|
||||
import subprocess as _sp
|
||||
|
||||
mock_run.return_value = _sp.CompletedProcess(args=[], returncode=0, stdout="", stderr="")
|
||||
import tempfile as _tf
|
||||
|
||||
tmpdir_mock.return_value.__enter__ = MagicMock(return_value="/tmp/testdir")
|
||||
tmpdir_mock.return_value.__exit__ = MagicMock(return_value=False)
|
||||
repo_cls.return_value = MagicMock()
|
||||
svc.execute_render(mock_job.id)
|
||||
return mock_db, mock_job
|
||||
|
||||
def test_cover_url_in_cover_config_passthrough_to_output_cover(self):
|
||||
"""cover_config.url 存在 → 透传到 output_cover_url."""
|
||||
mock_job = _make_mock_render_job(job_id="render-cov-1", status="pending")
|
||||
mock_job.cover_config = {"mode": "upload", "url": "https://oss/user-cover.jpg"}
|
||||
mock_lipsync_job = _make_mock_lipsync_job(status="completed", output_duration=10.0)
|
||||
_, job = self._run_execute(mock_job, mock_lipsync_job)
|
||||
assert job.output_cover_url == "https://oss/user-cover.jpg"
|
||||
|
||||
def test_cover_imageurl_fallback_also_passthrough(self):
|
||||
"""cover_config.imageUrl(老字段)存在 → 也透传到 output_cover_url."""
|
||||
mock_job = _make_mock_render_job(job_id="render-cov-2", status="pending")
|
||||
mock_job.cover_config = {"mode": "upload", "imageUrl": "https://oss/user-cover2.jpg"}
|
||||
mock_lipsync_job = _make_mock_lipsync_job(status="completed", output_duration=10.0)
|
||||
_, job = self._run_execute(mock_job, mock_lipsync_job)
|
||||
assert job.output_cover_url == "https://oss/user-cover2.jpg"
|
||||
|
||||
@@ -43,7 +43,7 @@ class TestScoreFrame:
|
||||
|
||||
@requires_cv2
|
||||
def test_clear_image_high_score(self):
|
||||
"""清晰、亮度适中、色彩丰富的图像应得较高分."""
|
||||
"""清晰、亮度适中、色彩丰富的图像应得高分."""
|
||||
# 创建一个清晰的渐变图像(色彩丰富、亮度适中)
|
||||
img = np.zeros((100, 100, 3), dtype=np.uint8)
|
||||
for i in range(100):
|
||||
@@ -53,8 +53,7 @@ class TestScoreFrame:
|
||||
from packages.shared.cover_frame_scorer import score_frame
|
||||
|
||||
score = score_frame(img)
|
||||
# 渐变图清晰度中等+亮度尚可+色彩有变化,分数应明显高于模糊/全黑/全白
|
||||
assert 40.0 <= score <= 100.0, f"清晰图像应得较高分,实际: {score}"
|
||||
assert 50.0 <= score <= 100.0, f"清晰图像应得高分,实际: {score}"
|
||||
|
||||
@requires_cv2
|
||||
def test_blurry_image_low_clarity(self):
|
||||
@@ -77,8 +76,8 @@ class TestScoreFrame:
|
||||
from packages.shared.cover_frame_scorer import score_frame
|
||||
|
||||
score = score_frame(img)
|
||||
# 全黑:清晰度 0,亮度偏离130扣约24分,色彩 0 → 得分约0~7,允许cv2内部微小浮点差异
|
||||
assert score <= 10.0, f"全黑图像应接近 0 分,实际: {score}"
|
||||
# 全黑:清晰度 0,亮度 0,色彩 0
|
||||
assert score <= 5.0, f"全黑图像应接近 0 分,实际: {score}"
|
||||
|
||||
@requires_cv2
|
||||
def test_bright_image_low_brightness(self):
|
||||
|
||||
@@ -180,26 +180,28 @@ class TestDetectKeyframeTimestamps:
|
||||
|
||||
def test_cannot_open_video_raises(self):
|
||||
"""无法打开视频时抛出 RuntimeError."""
|
||||
cv2_mock = _dedup_mod.cv2
|
||||
mock_cap = MagicMock()
|
||||
mock_cap.isOpened.return_value = False
|
||||
cv2_mock.VideoCapture.return_value = mock_cap
|
||||
|
||||
import pytest
|
||||
|
||||
with patch.object(_dedup_mod.cv2, "VideoCapture", return_value=mock_cap):
|
||||
with pytest.raises(RuntimeError, match="Cannot open video"):
|
||||
detect_keyframe_timestamps("/fake/path.mp4")
|
||||
with pytest.raises(RuntimeError, match="Cannot open video"):
|
||||
detect_keyframe_timestamps("/fake/path.mp4")
|
||||
|
||||
def test_zero_duration_returns_empty(self):
|
||||
"""视频时长为 0 时返回空列表."""
|
||||
cv2_mock = _dedup_mod.cv2
|
||||
mock_cap = MagicMock()
|
||||
mock_cap.isOpened.return_value = True
|
||||
# cv2.CAP_PROP_FPS etc. are Mock objects; configure get() to return 0 for frame_count
|
||||
mock_cap.get.return_value = 0
|
||||
mock_cap.read.return_value = (False, None)
|
||||
cv2_mock.VideoCapture.return_value = mock_cap
|
||||
|
||||
with patch.object(_dedup_mod.cv2, "VideoCapture", return_value=mock_cap):
|
||||
result = detect_keyframe_timestamps("/fake/zero.mp4")
|
||||
assert result == []
|
||||
result = detect_keyframe_timestamps("/fake/zero.mp4")
|
||||
assert result == []
|
||||
|
||||
def test_function_signature(self):
|
||||
"""验证函数签名和默认参数."""
|
||||
|
||||
@@ -47,35 +47,32 @@ class TestGeneratedVideoCreate:
|
||||
assert video.file_url == "https://example.com/video.mp4"
|
||||
assert video.user_id == "user1"
|
||||
|
||||
def test_create_empty_project_id_allowed(self):
|
||||
"""project_id 允许为空(AI数字人等无项目场景)。"""
|
||||
video = GeneratedVideo.create(
|
||||
project_id="",
|
||||
generation_task_id="task1",
|
||||
name="视频",
|
||||
file_url="https://example.com/v.mp4",
|
||||
)
|
||||
assert video.project_id == ""
|
||||
def test_create_empty_project_id_raises(self):
|
||||
with pytest.raises(ValueError, match="project_id cannot be empty"):
|
||||
GeneratedVideo.create(
|
||||
project_id="",
|
||||
generation_task_id="task1",
|
||||
name="视频",
|
||||
file_url="https://example.com/v.mp4",
|
||||
)
|
||||
|
||||
def test_create_whitespace_project_id_normalized_to_empty(self):
|
||||
"""project_id 纯空白会被 strip 为空串,不抛异常。"""
|
||||
video = GeneratedVideo.create(
|
||||
project_id=" ",
|
||||
generation_task_id="task1",
|
||||
name="视频",
|
||||
file_url="https://example.com/v.mp4",
|
||||
)
|
||||
assert video.project_id == ""
|
||||
def test_create_whitespace_project_id_raises(self):
|
||||
with pytest.raises(ValueError, match="project_id cannot be empty"):
|
||||
GeneratedVideo.create(
|
||||
project_id=" ",
|
||||
generation_task_id="task1",
|
||||
name="视频",
|
||||
file_url="https://example.com/v.mp4",
|
||||
)
|
||||
|
||||
def test_create_empty_generation_task_id_allowed(self):
|
||||
"""generation_task_id 允许为空(兼容部分异步链路)。"""
|
||||
video = GeneratedVideo.create(
|
||||
project_id="proj1",
|
||||
generation_task_id="",
|
||||
name="视频",
|
||||
file_url="https://example.com/v.mp4",
|
||||
)
|
||||
assert video.generation_task_id == ""
|
||||
def test_create_empty_generation_task_id_raises(self):
|
||||
with pytest.raises(ValueError, match="generation_task_id cannot be empty"):
|
||||
GeneratedVideo.create(
|
||||
project_id="proj1",
|
||||
generation_task_id="",
|
||||
name="视频",
|
||||
file_url="https://example.com/v.mp4",
|
||||
)
|
||||
|
||||
def test_create_empty_name_raises(self):
|
||||
with pytest.raises(ValueError, match="name cannot be empty"):
|
||||
|
||||
@@ -75,35 +75,32 @@ class TestGeneratedVideoCreate:
|
||||
assert video.file_url == "https://example.com/out.mp4"
|
||||
assert video.user_id == "user_003"
|
||||
|
||||
def test_create_empty_project_id_allowed(self):
|
||||
"""project_id 允许为空(AI数字人等无项目场景)。"""
|
||||
video = GeneratedVideo.create(
|
||||
project_id="",
|
||||
generation_task_id="t",
|
||||
name="n",
|
||||
file_url="u",
|
||||
)
|
||||
assert video.project_id == ""
|
||||
def test_create_empty_project_id_raises(self):
|
||||
with pytest.raises(ValueError, match="project_id"):
|
||||
GeneratedVideo.create(
|
||||
project_id="",
|
||||
generation_task_id="t",
|
||||
name="n",
|
||||
file_url="u",
|
||||
)
|
||||
|
||||
def test_create_whitespace_project_id_normalized(self):
|
||||
"""project_id 纯空白归一化为空串。"""
|
||||
video = GeneratedVideo.create(
|
||||
project_id=" ",
|
||||
generation_task_id="t",
|
||||
name="n",
|
||||
file_url="u",
|
||||
)
|
||||
assert video.project_id == ""
|
||||
def test_create_whitespace_project_id_raises(self):
|
||||
with pytest.raises(ValueError, match="project_id"):
|
||||
GeneratedVideo.create(
|
||||
project_id=" ",
|
||||
generation_task_id="t",
|
||||
name="n",
|
||||
file_url="u",
|
||||
)
|
||||
|
||||
def test_create_empty_generation_task_id_allowed(self):
|
||||
"""generation_task_id 允许为空。"""
|
||||
video = GeneratedVideo.create(
|
||||
project_id="p",
|
||||
generation_task_id="",
|
||||
name="n",
|
||||
file_url="u",
|
||||
)
|
||||
assert video.generation_task_id == ""
|
||||
def test_create_empty_generation_task_id_raises(self):
|
||||
with pytest.raises(ValueError, match="generation_task_id"):
|
||||
GeneratedVideo.create(
|
||||
project_id="p",
|
||||
generation_task_id="",
|
||||
name="n",
|
||||
file_url="u",
|
||||
)
|
||||
|
||||
def test_create_empty_name_raises(self):
|
||||
with pytest.raises(ValueError, match="name"):
|
||||
|
||||
@@ -45,25 +45,25 @@ class TestGeneratedVideo:
|
||||
assert video.duplicate_of is None
|
||||
assert video.generation_params == {}
|
||||
|
||||
def test_create_empty_project_id_allowed(self):
|
||||
"""project_id 允许为空(AI数字人场景),空白归一化为空串."""
|
||||
video = GeneratedVideo.create(
|
||||
project_id=" ",
|
||||
generation_task_id="t1",
|
||||
name="v.mp4",
|
||||
file_url="https://x.com/v.mp4",
|
||||
)
|
||||
assert video.project_id == ""
|
||||
def test_create_empty_project_id_raises(self):
|
||||
"""空project_id抛异常."""
|
||||
with pytest.raises(ValueError, match="project_id"):
|
||||
GeneratedVideo.create(
|
||||
project_id=" ",
|
||||
generation_task_id="t1",
|
||||
name="v.mp4",
|
||||
file_url="https://x.com/v.mp4",
|
||||
)
|
||||
|
||||
def test_create_empty_task_id_allowed(self):
|
||||
"""generation_task_id 允许为空."""
|
||||
video = GeneratedVideo.create(
|
||||
project_id="p1",
|
||||
generation_task_id="",
|
||||
name="v.mp4",
|
||||
file_url="https://x.com/v.mp4",
|
||||
)
|
||||
assert video.generation_task_id == ""
|
||||
def test_create_empty_task_id_raises(self):
|
||||
"""空generation_task_id抛异常."""
|
||||
with pytest.raises(ValueError, match="generation_task_id"):
|
||||
GeneratedVideo.create(
|
||||
project_id="p1",
|
||||
generation_task_id="",
|
||||
name="v.mp4",
|
||||
file_url="https://x.com/v.mp4",
|
||||
)
|
||||
|
||||
def test_create_empty_name_raises(self):
|
||||
"""空name抛异常."""
|
||||
|
||||
@@ -1,299 +0,0 @@
|
||||
"""generation_common 公共服务辅助函数单元测试。
|
||||
|
||||
覆盖 query_voice_durations / writeback_edit_plan_config / collect_plan_segments /
|
||||
resolve_latest_plan_by_template 四个下沉函数的主路径、边界与容错路径。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from unittest.mock import MagicMock
|
||||
|
||||
import pytest
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# query_voice_durations
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
|
||||
class TestQueryVoiceDurations:
|
||||
def _make_db_with_rows(self, rows):
|
||||
"""构造 MagicMock db,query().filter().all() 返回 rows。"""
|
||||
db = MagicMock()
|
||||
db.query.return_value.filter.return_value.all.return_value = list(rows)
|
||||
return db
|
||||
|
||||
def test_empty_input_returns_empty_list(self):
|
||||
from app.services.generation_common import query_voice_durations
|
||||
|
||||
db = MagicMock()
|
||||
assert query_voice_durations(db, []) == []
|
||||
assert query_voice_durations(db, None) == []
|
||||
db.query.assert_not_called()
|
||||
|
||||
def test_all_empty_or_falsy_ids_returns_zero_list(self):
|
||||
from app.services.generation_common import query_voice_durations
|
||||
|
||||
db = MagicMock()
|
||||
assert query_voice_durations(db, ["", None, ""]) == [0.0, 0.0, 0.0]
|
||||
|
||||
def test_normal_lookup_returns_durations_in_input_order(self):
|
||||
from app.services.generation_common import query_voice_durations
|
||||
|
||||
db = self._make_db_with_rows([("v1", 3.5), ("v2", 7.2)])
|
||||
result = query_voice_durations(db, ["v1", "v2", "v-missing"])
|
||||
assert result == [3.5, 7.2, 0.0]
|
||||
|
||||
def test_duplicate_ids_returns_consistent_durations_preserves_order(self):
|
||||
"""#1855:同配音 id 多次出现应返回相同时长,保持输入顺序/长度。"""
|
||||
from app.services.generation_common import query_voice_durations
|
||||
|
||||
db = self._make_db_with_rows([("v1", 4.0)])
|
||||
result = query_voice_durations(db, ["v1", "v1", "v1"])
|
||||
assert result == [4.0, 4.0, 4.0]
|
||||
|
||||
def test_non_numeric_duration_coerced_to_zero(self):
|
||||
from app.services.generation_common import query_voice_durations
|
||||
|
||||
db = self._make_db_with_rows([("v1", None), ("v2", "not-a-number"), ("v3", 2.0)])
|
||||
result = query_voice_durations(db, ["v1", "v2", "v3"])
|
||||
assert result == [0.0, 0.0, 2.0]
|
||||
|
||||
def test_db_exception_returns_zeros_and_logs(self, caplog):
|
||||
from app.services.generation_common import query_voice_durations
|
||||
|
||||
db = MagicMock()
|
||||
db.query.side_effect = RuntimeError("DB boom")
|
||||
with caplog.at_level("WARNING"):
|
||||
result = query_voice_durations(db, ["v1", "v2"])
|
||||
assert result == [0.0, 0.0]
|
||||
assert any("配音时长查询失败" in rec.message for rec in caplog.records)
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# writeback_edit_plan_config
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
|
||||
def _make_plan_model(config=None):
|
||||
plan = MagicMock()
|
||||
plan.config = config if config is not None else {}
|
||||
return plan
|
||||
|
||||
|
||||
class TestWritebackEditPlanConfig:
|
||||
def test_empty_plan_id_returns_immediately(self):
|
||||
from app.services.generation_common import writeback_edit_plan_config
|
||||
|
||||
db = MagicMock()
|
||||
writeback_edit_plan_config("", "task1", None, db)
|
||||
db.query.assert_not_called()
|
||||
|
||||
def test_plan_not_found_logs_and_returns(self, caplog):
|
||||
from app.services.generation_common import writeback_edit_plan_config
|
||||
|
||||
db = MagicMock()
|
||||
db.query.return_value.filter.return_value.first.return_value = None
|
||||
with caplog.at_level("WARNING"):
|
||||
writeback_edit_plan_config("p999", "task1", None, db)
|
||||
db.commit.assert_not_called()
|
||||
assert any("plan不存在" in rec.message for rec in caplog.records)
|
||||
|
||||
def test_writes_task_id_preserves_existing_config(self):
|
||||
from app.services.generation_common import writeback_edit_plan_config
|
||||
|
||||
plan = _make_plan_model({"other": "keep-me"})
|
||||
db = MagicMock()
|
||||
db.query.return_value.filter.return_value.first.return_value = plan
|
||||
writeback_edit_plan_config("p1", "task-xyz", None, db)
|
||||
assert plan.config["generation_task_id"] == "task-xyz"
|
||||
assert plan.config["other"] == "keep-me"
|
||||
assert "title" not in plan.config or not plan.config.get("title")
|
||||
db.commit.assert_called_once()
|
||||
|
||||
def test_merges_title_without_title_change(self):
|
||||
"""#1901: 写 'title' 字段,未变标题保留 cover。"""
|
||||
from app.services.generation_common import writeback_edit_plan_config
|
||||
|
||||
plan = _make_plan_model({"title": {"text": "old"}, "cover": "x"})
|
||||
db = MagicMock()
|
||||
db.query.return_value.filter.return_value.first.return_value = plan
|
||||
writeback_edit_plan_config("p1", "t1", {"text": "old"}, db)
|
||||
assert plan.config["title"] == {"text": "old"}
|
||||
# 旧 key 不应残留
|
||||
assert "title_config" not in plan.config
|
||||
# 标题未变 → cover 保留
|
||||
assert plan.config.get("cover") == "x"
|
||||
|
||||
def test_merges_title_fallback_to_old_title_config_key(self):
|
||||
"""#1901: 老数据存在 title_config(无 title)时,也能正确识别旧标题文字。"""
|
||||
from app.services.generation_common import writeback_edit_plan_config
|
||||
|
||||
plan = _make_plan_model({"title_config": {"text": "old"}, "cover": "x"})
|
||||
db = MagicMock()
|
||||
db.query.return_value.filter.return_value.first.return_value = plan
|
||||
writeback_edit_plan_config("p1", "t1", {"text": "old"}, db)
|
||||
# 写入新 key "title",旧 key 被清除
|
||||
assert plan.config["title"] == {"text": "old"}
|
||||
assert "title_config" not in plan.config
|
||||
assert plan.config.get("cover") == "x"
|
||||
|
||||
def test_title_change_clears_cover(self):
|
||||
"""#1901: 标题变化时清 cover,新配置写到 'title'。"""
|
||||
from app.services.generation_common import writeback_edit_plan_config
|
||||
|
||||
plan = _make_plan_model({"title": {"text": "old"}, "cover": "x"})
|
||||
db = MagicMock()
|
||||
db.query.return_value.filter.return_value.first.return_value = plan
|
||||
writeback_edit_plan_config("p1", "t1", {"text": "new-title"}, db)
|
||||
assert "cover" not in plan.config
|
||||
assert plan.config["title"] == {"text": "new-title"}
|
||||
assert "title_config" not in plan.config
|
||||
|
||||
def test_title_config_normalizes_legacy_keys(self):
|
||||
"""#1901: 写入时归一化 font_size/font_preset/font_color → size/font/color,与 worker 对齐。"""
|
||||
from app.services.generation_common import writeback_edit_plan_config
|
||||
|
||||
plan = _make_plan_model({})
|
||||
db = MagicMock()
|
||||
db.query.return_value.filter.return_value.first.return_value = plan
|
||||
writeback_edit_plan_config(
|
||||
"p1",
|
||||
"t1",
|
||||
{"text": "hi", "font_size": 32, "font_preset": "楷体", "font_color": "#ff0000", "bold": True},
|
||||
db,
|
||||
)
|
||||
title = plan.config["title"]
|
||||
assert title["text"] == "hi"
|
||||
assert title["size"] == 32
|
||||
assert title["font"] == "楷体"
|
||||
assert title["color"] == "#ff0000"
|
||||
# 原始 key 保留(方便调用方排查,但归一化后的 key 必须存在)
|
||||
assert title["font_size"] == 32
|
||||
|
||||
def test_config_not_dict_treated_as_empty(self):
|
||||
from app.services.generation_common import writeback_edit_plan_config
|
||||
|
||||
plan = _make_plan_model(config=None)
|
||||
db = MagicMock()
|
||||
db.query.return_value.filter.return_value.first.return_value = plan
|
||||
writeback_edit_plan_config("p1", "t1", {"text": "hi"}, db)
|
||||
assert plan.config["generation_task_id"] == "t1"
|
||||
assert plan.config["title"] == {"text": "hi"}
|
||||
assert "title_config" not in plan.config
|
||||
|
||||
def test_exception_triggers_rollback_and_logs(self, caplog):
|
||||
from app.services.generation_common import writeback_edit_plan_config
|
||||
|
||||
db = MagicMock()
|
||||
db.query.return_value.filter.return_value.first.side_effect = RuntimeError("fail")
|
||||
with caplog.at_level("WARNING"):
|
||||
writeback_edit_plan_config("p1", "t1", None, db)
|
||||
db.rollback.assert_called_once()
|
||||
assert any("回写plan.config异常" in rec.message for rec in caplog.records)
|
||||
|
||||
def test_exception_with_rollback_also_failing_is_safe(self, caplog):
|
||||
"""外层异常后,db.rollback() 自己也抛异常时也不应中断(pass 兜底)。"""
|
||||
from app.services.generation_common import writeback_edit_plan_config
|
||||
|
||||
db = MagicMock()
|
||||
db.query.return_value.filter.return_value.first.side_effect = RuntimeError("fail")
|
||||
db.rollback.side_effect = RuntimeError("rollback boom")
|
||||
with caplog.at_level("WARNING"):
|
||||
# 不应抛出异常
|
||||
writeback_edit_plan_config("p1", "t1", None, db)
|
||||
assert any("回写plan.config异常" in rec.message for rec in caplog.records)
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# collect_plan_segments
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
|
||||
def _make_clip(asset_id, start, duration):
|
||||
c = MagicMock()
|
||||
c.asset_id = asset_id
|
||||
c.start_time = start
|
||||
c.duration = duration
|
||||
return c
|
||||
|
||||
|
||||
class TestCollectPlanSegments:
|
||||
def test_empty_plan_returns_empty(self):
|
||||
from app.services.generation_common import collect_plan_segments
|
||||
|
||||
repo = MagicMock()
|
||||
repo.list_by_plan.return_value = []
|
||||
assert collect_plan_segments("p1", repo) == {}
|
||||
|
||||
def test_single_page_collects_segments(self):
|
||||
from app.services.generation_common import collect_plan_segments
|
||||
|
||||
repo = MagicMock()
|
||||
repo.list_by_plan.side_effect = [
|
||||
[_make_clip("a1", 0.0, 5.0), _make_clip("a1", 10.0, 3.0), _make_clip("a2", 2.0, 4.0)],
|
||||
[],
|
||||
]
|
||||
segs = collect_plan_segments("p1", repo, page_size=500)
|
||||
assert segs["a1"] == [(0.0, 5.0), (10.0, 13.0)]
|
||||
assert segs["a2"] == [(2.0, 6.0)]
|
||||
|
||||
def test_pagination_walks_all_batches(self):
|
||||
from app.services.generation_common import collect_plan_segments
|
||||
|
||||
repo = MagicMock()
|
||||
page1 = [_make_clip("a1", 0.0, 1.0)] * 2
|
||||
page2 = [_make_clip("a2", 0.0, 2.0)] * 2
|
||||
page3 = [_make_clip("a3", 0.0, 1.0)] # short final batch → stop
|
||||
repo.list_by_plan.side_effect = [page1, page2, page3]
|
||||
segs = collect_plan_segments("p1", repo, page_size=2)
|
||||
assert set(segs.keys()) == {"a1", "a2", "a3"}
|
||||
assert repo.list_by_plan.call_count == 3
|
||||
|
||||
def test_skips_zero_or_negative_duration_clips(self):
|
||||
from app.services.generation_common import collect_plan_segments
|
||||
|
||||
repo = MagicMock()
|
||||
repo.list_by_plan.side_effect = [
|
||||
[_make_clip(None, 0.0, 5.0), _make_clip("a1", 0.0, 0.0), _make_clip("a1", 1.0, -1.0)],
|
||||
[],
|
||||
]
|
||||
assert collect_plan_segments("p1", repo) == {}
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
# resolve_latest_plan_by_template
|
||||
# ═══════════════════════════════════════════════════════════════════════════════
|
||||
|
||||
|
||||
class TestResolveLatestPlanByTemplate:
|
||||
@pytest.mark.parametrize("tid", ["", None, " "])
|
||||
def test_empty_template_returns_none(self, tid):
|
||||
from app.services.generation_common import resolve_latest_plan_by_template
|
||||
|
||||
db = MagicMock()
|
||||
assert resolve_latest_plan_by_template(db, template_id=tid, user_id="u1") is None
|
||||
db.query.assert_not_called()
|
||||
|
||||
def test_returns_latest_plan_id(self):
|
||||
from app.services.generation_common import resolve_latest_plan_by_template
|
||||
|
||||
db = MagicMock()
|
||||
latest = MagicMock(id="plan-xyz")
|
||||
db.query.return_value.filter.return_value.order_by.return_value.first.return_value = latest
|
||||
assert resolve_latest_plan_by_template(db, template_id=" tpl1 ", user_id="u1") == "plan-xyz"
|
||||
|
||||
def test_no_plan_returns_none(self):
|
||||
from app.services.generation_common import resolve_latest_plan_by_template
|
||||
|
||||
db = MagicMock()
|
||||
db.query.return_value.filter.return_value.order_by.return_value.first.return_value = None
|
||||
assert resolve_latest_plan_by_template(db, template_id="tpl", user_id="u") is None
|
||||
|
||||
def test_db_exception_returns_none_and_logs(self, caplog):
|
||||
from app.services.generation_common import resolve_latest_plan_by_template
|
||||
|
||||
db = MagicMock()
|
||||
db.query.side_effect = RuntimeError("boom")
|
||||
with caplog.at_level("WARNING"):
|
||||
assert resolve_latest_plan_by_template(db, template_id="tpl", user_id="u") is None
|
||||
assert any("查找最新plan失败" in rec.message for rec in caplog.records)
|
||||
@@ -91,27 +91,16 @@ class TestSchemaValidation:
|
||||
assert req.voice_id == "longxiaochun_v3"
|
||||
assert req.script_text == "大家好,欢迎来到直播间"
|
||||
|
||||
def test_invalid_video_url_unsupported_ext(self):
|
||||
def test_invalid_video_url_not_mp4(self):
|
||||
from app.schemas.lipsync import CreateLipsyncJobRequest
|
||||
|
||||
# 不支持的扩展名(.txt)应报错
|
||||
with pytest.raises(ValueError, match="格式不支持"):
|
||||
with pytest.raises(ValueError, match="MP4"):
|
||||
CreateLipsyncJobRequest(
|
||||
video_url="https://example.com/video.txt",
|
||||
video_url="https://example.com/video.mov",
|
||||
voice_id="longxiaochun_v3",
|
||||
script_text="测试文本",
|
||||
)
|
||||
|
||||
def test_mov_video_url_accepted(self):
|
||||
from app.schemas.lipsync import CreateLipsyncJobRequest
|
||||
|
||||
# .MOV 是 iPhone 拍摄的常见容器,h264 编码可直接被 MediaKit 处理
|
||||
req = CreateLipsyncJobRequest(
|
||||
video_url="https://example.com/video.mov",
|
||||
audio_url="https://example.com/audio.mp3",
|
||||
)
|
||||
assert req.video_url.endswith(".mov")
|
||||
|
||||
def test_invalid_video_url_empty(self):
|
||||
from app.schemas.lipsync import CreateLipsyncJobRequest
|
||||
|
||||
@@ -170,8 +159,7 @@ class TestSchemaValidation:
|
||||
voice_id="longxiaochun_v3",
|
||||
script_text="测试文本",
|
||||
)
|
||||
# AI数字人场景文案长度不可控,默认开启视频循环,防止音频长于视频时被截断
|
||||
assert req.enable_video_loop is True
|
||||
assert req.enable_video_loop is False
|
||||
|
||||
def test_video_url_strip_query_params(self):
|
||||
"""视频 URL 含查询参数时,扩展名检查应忽略 ? 后面的部分."""
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user