Compare commits

..

2 Commits

Author SHA1 Message Date
CI Bot d48d652465 style: auto-format with black + isort + prettier [skip ci-format-check]
CI/CD Pipeline / Build Staging API Image (pull_request) Has been skipped
CI/CD Pipeline / Build Staging Web Image (pull_request) Has been skipped
CI/CD Pipeline / Build Staging Worker Image (pull_request) Has been skipped
CI/CD Pipeline / Deploy Staging (Watchtower auto-deploy) (pull_request) Has been skipped
CI/CD Pipeline / Staging E2E Tests (pull_request) Has been skipped
CI/CD Pipeline / Staging API Integration Tests (pull_request) Has been skipped
CI/CD Pipeline / ACR Image Cleanup (pull_request) Has been skipped
CI/CD Pipeline / Check if frontend-only change (pull_request) Successful in 42s
CI/CD Pipeline / Frontend Lint (pull_request) Has been skipped
CI/CD Pipeline / Frontend Unit Tests (pull_request) Has been skipped
CI/CD Pipeline / PR Build Web Image (pull_request) Has been skipped
CI/CD Pipeline / Validate - Migration (alembic) (pull_request) Successful in 1m5s
CI/CD Pipeline / Validate - Type Check (mypy) (pull_request) Successful in 1m24s
Preview Deploy / Deploy Preview Environment (pull_request) Successful in 1m21s
PR Automation / Auto Merge on CI Green + Approved (pull_request) Successful in 1m45s
CI/CD Pipeline / Unit Tests (pull_request) Successful in 1m54s
CI/CD Pipeline / PR Build API Image (pull_request) Successful in 2m23s
CI/CD Pipeline / PR Build Worker Image (pull_request) Successful in 2m23s
PR Automation / Auto Approve on CI Green (pull_request) Successful in 3m31s
CI/CD Pipeline / Validate - Code Quality (pull_request) Successful in 4m13s
CI/CD Pipeline / Build Production Web Image (pull_request) Has been skipped
CI/CD Pipeline / Build Production API Image (pull_request) Has been skipped
CI/CD Pipeline / Build Production Worker Image (pull_request) Has been skipped
CI/CD Pipeline / Deploy Production (pull_request) Has been skipped
CI/CD Pipeline / Canary Release to Production (pull_request) Has been skipped
CI/CD Pipeline / Production Browser E2E (pull_request) Has been skipped
CI/CD Pipeline / Integration Tests (pull_request) Successful in 1m28s
AI Code Review / AI Code Review (pull_request) Successful in 5m43s
CI/CD Pipeline / CI Gate (pull_request) Successful in 5s
Preview Cleanup / Cleanup Preview Environment (pull_request) Successful in 32s
ACR Cleanup / ACR Image Cleanup (pull_request_target) Successful in 45s
2026-08-15 07:46:06 +00:00
xiaoxia 1a2f34e508 fix(cover): overlay title text on cover image after frame extraction
CI/CD Pipeline / Build Staging API Image (pull_request) Has been skipped
CI/CD Pipeline / Build Staging Web Image (pull_request) Has been skipped
CI/CD Pipeline / Build Staging Worker Image (pull_request) Has been skipped
CI/CD Pipeline / Deploy Staging (Watchtower auto-deploy) (pull_request) Has been skipped
CI/CD Pipeline / Staging E2E Tests (pull_request) Has been skipped
CI/CD Pipeline / Staging API Integration Tests (pull_request) Has been skipped
CI/CD Pipeline / ACR Image Cleanup (pull_request) Has been skipped
CI/CD Pipeline / Check if frontend-only change (pull_request) Successful in 36s
CI/CD Pipeline / Frontend Lint (pull_request) Has been skipped
CI/CD Pipeline / Frontend Unit Tests (pull_request) Has been skipped
CI/CD Pipeline / PR Build Web Image (pull_request) Has been skipped
CI/CD Pipeline / Validate - Type Check (mypy) (pull_request) Successful in 1m15s
CI/CD Pipeline / Validate - Migration (alembic) (pull_request) Successful in 1m22s
Preview Deploy / Deploy Preview Environment (pull_request) Successful in 1m32s
PR Automation / Auto Merge on CI Green + Approved (pull_request) Successful in 1m37s
AI Code Review / AI Code Review (pull_request) Successful in 2m3s
CI/CD Pipeline / Unit Tests (pull_request) Successful in 2m3s
CI/CD Pipeline / Validate - Code Quality (pull_request) Has been cancelled
CI/CD Pipeline / Integration Tests (pull_request) Has been cancelled
CI/CD Pipeline / PR Build API Image (pull_request) Has been cancelled
CI/CD Pipeline / PR Build Worker Image (pull_request) Has been cancelled
CI/CD Pipeline / Build Production API Image (pull_request) Has been cancelled
CI/CD Pipeline / Build Production Web Image (pull_request) Has been cancelled
CI/CD Pipeline / Build Production Worker Image (pull_request) Has been cancelled
CI/CD Pipeline / Deploy Production (pull_request) Has been cancelled
CI/CD Pipeline / Production Browser E2E (pull_request) Has been cancelled
CI/CD Pipeline / Canary Release to Production (pull_request) Has been cancelled
CI/CD Pipeline / CI Gate (pull_request) Has been cancelled
PR Automation / Auto Approve on CI Green (pull_request) Has been cancelled
Root cause: cover frame is extracted during preview video rendering (Step 3),
but user selects title AFTER rendering (Step 4). The cover frame naturally
has no title because it was captured before the title was chosen.

Fix: In generation_cover.py, after finding cover_url_from_task, check if
plan.config['title']['text'] has a title. If yes, download the cover image,
use ffmpeg drawtext to overlay the title (white text + black shadow, centered
near bottom), upload to OSS, and return the new URL. On failure, fallback
to original cover_url.

Changes:
- Add _overlay_title_on_cover_image() helper in generation_cover.py
- Add _escape_drawtext_text() for ffmpeg special character escaping
- Modify cover route to check for title and overlay if present
- 12 new unit tests (test_cover_title_overlay.py)
- All 13603 tests pass

Fixes: cover title missing issue in staging
2026-08-15 15:42:56 +08:00
740 changed files with 16928 additions and 97618 deletions
-1
View File
@@ -1 +0,0 @@
CI re-trigger after runner add-host/DNS fix. This file is harmless and not referenced.
-84
View File
@@ -1,84 +0,0 @@
name: API Base Image Build
on:
push:
branches:
- develop
- main
paths:
- 'requirements-base.txt'
- 'requirements.txt'
- 'infra/docker/api-base.Dockerfile'
workflow_dispatch:
jobs:
build-api-base:
name: Build API Base Image
runs-on: runtime-builder
timeout-minutes: 45
steps:
- name: Checkout code
shell: sh
env:
GITHUB_TOKEN: ${{ github.token }}
run: |
curl -sH "Authorization: token $GITHUB_TOKEN" \
"${GITHUB_API_URL}/repos/${GITHUB_REPOSITORY}/raw/scripts/ci/step_checkout.sh?ref=${GITHUB_SHA}" \
| bash
- name: Docker login to Registry
shell: sh
env:
ACR_USERNAME: ${{ secrets.ACR_USERNAME }}
ACR_PASSWORD: ${{ secrets.ACR_PASSWORD }}
GITEA_REGISTRY_USER: xiaoxia
GITEA_REGISTRY_TOKEN: ${{ secrets.REGISTRY_TOKEN }}
run: |
set -eu
for i in 1 2 3; do
echo "=== Docker login 尝试 $i/3 ==="
if printf '%s' "${ACR_PASSWORD}" | docker login xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com -u "${ACR_USERNAME}" --password-stdin \
&& docker login git.xiaoxiajianji.com -u "${GITEA_REGISTRY_USER}" -p "${GITEA_REGISTRY_TOKEN}"; then
echo "✅ Docker login successful"
break
fi
echo "❌ Docker login 失败(尝试 $i/3),5s 后重试..."
sleep 5
done
- name: Build and push API base image
shell: sh
run: |
set -eu
ACR_IMAGE="xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com/xiaoxiakeji/saas-api-base:latest"
GITEA_IMAGE="git.xiaoxiajianji.com/xiaoxia-saas/saas-api-base:latest"
echo "=== Building API base image ==="
# 使用普通 docker build(单平台不需要 buildx
docker build \
-f infra/docker/api-base.Dockerfile \
-t "${ACR_IMAGE}" \
.
echo ""
echo "✅ Image built successfully"
# 推送到 ACR
echo "=== Pushing to ACR ==="
docker push "${ACR_IMAGE}"
echo "✅ Pushed to ACR"
# 打标签并推送到 Gitea Packages 作为备份
echo "=== Pushing to Gitea Packages ==="
docker tag "${ACR_IMAGE}" "${GITEA_IMAGE}"
docker push "${GITEA_IMAGE}" || echo "⚠️ Gitea Packages push failed (non-fatal)"
echo "✅ Gitea backup push completed"
- name: Cleanup
if: always()
shell: sh
run: |
ACR_IMAGE="xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com/xiaoxiakeji/saas-api-base:latest"
docker rmi "${ACR_IMAGE}" 2>/dev/null || true
echo "Cleanup done"
-105
View File
@@ -1,105 +0,0 @@
name: CI Base Image Build
on:
push:
branches:
- develop
- main
paths:
- 'requirements-base.txt'
- 'requirements-dev.txt'
- 'infra/docker/ci.Dockerfile'
workflow_dispatch:
inputs:
reason:
description: "触发原因"
required: false
default: "手动触发 - ci-base 镜像重建"
concurrency:
group: ci-base-image-build
cancel-in-progress: false
jobs:
build-ci-base:
name: Build CI Base Image
runs-on: runtime-builder
timeout-minutes: 60
steps:
- name: Checkout code
shell: sh
env:
GITHUB_TOKEN: ${{ github.token }}
run: |
curl -sH "Authorization: token $GITHUB_TOKEN" \
"${GITHUB_API_URL}/repos/${GITHUB_REPOSITORY}/raw/scripts/ci/step_checkout.sh?ref=${GITHUB_SHA}" \
| bash
- name: Docker login to Gitea Registry
shell: sh
env:
GITEA_REGISTRY_USER: xiaoxia
GITEA_REGISTRY_TOKEN: ${{ secrets.REGISTRY_TOKEN }}
run: |
set -eu
for i in 1 2 3; do
echo "=== Docker login 尝试 $i/3 ==="
if docker login git.xiaoxiajianji.com -u "${GITEA_REGISTRY_USER}" -p "${GITEA_REGISTRY_TOKEN}"; then
echo "✅ Docker login successful"
break
fi
echo "❌ Docker login 失败(尝试 $i/3),5s 后重试..."
sleep 5
done
- name: Build and push CI base image
shell: sh
run: |
set -eu
IMAGE="git.xiaoxiajianji.com/xiaoxia/xiaoxia-saas/ci-base"
VERSION_TAG="deps-$(date +%Y%m%d-%H%M)-${GITHUB_SHA::8}"
echo "=== Building CI base image (tags: latest, ${VERSION_TAG}) ==="
docker build --progress=plain \
-f infra/docker/ci.Dockerfile \
-t "${IMAGE}:latest" \
-t "${IMAGE}:${VERSION_TAG}" \
.
echo "✅ Image built successfully"
echo "=== Pushing ${VERSION_TAG} ==="
docker push "${IMAGE}:${VERSION_TAG}"
echo "=== Pushing latest ==="
docker push "${IMAGE}:latest"
echo "✅ Pushed to Gitea Registry"
- name: Verify image
shell: sh
run: |
set -eu
IMAGE="git.xiaoxiajianji.com/xiaoxia/xiaoxia-saas/ci-base:latest"
echo "=== Verifying pinned deps in fresh image ==="
docker run --rm "${IMAGE}" /opt/xiaoxia-ci-venv/bin/python -c \
"import httpcore, h2, numpy, httpx; print('VERSIONS:', httpcore.__version__, h2.__version__, numpy.__version__, httpx.__version__)"
- name: Notify result
if: always()
continue-on-error: true
shell: sh
env:
CI_NOTIFY_WEBHOOK: ${{ secrets.CI_NOTIFY_WEBHOOK }}
run: |
set +e
if [ "${{ job.status }}" = "success" ]; then
NOTIFY_MODE=success JOB_NAME="CI Base Image Build" python3 scripts/ci_notify.py
else
NOTIFY_MODE=failure JOB_NAME="CI Base Image Build" python3 scripts/ci_notify.py
fi
- name: Cleanup
if: always()
shell: sh
run: |
IMAGE="git.xiaoxiajianji.com/xiaoxia/xiaoxia-saas/ci-base"
docker rmi "${IMAGE}:latest" 2>/dev/null || true
echo "Cleanup done"
-51
View File
@@ -1,51 +0,0 @@
name: CI Canary Check
on:
schedule:
- cron: '*/30 * * * *'
workflow_dispatch:
jobs:
canary:
runs-on: ci-l2
timeout-minutes: 10
steps:
- name: Canary (runner -> docker -> network -> gitea)
run: |
set -e
echo "== runner/container basic =="
date; hostname; whoami
echo "== gitea api reachability =="
code=$(curl -s -o /tmp/v.json -w '%{http_code}' -m 15 "$GITHUB_API_URL/version")
echo "gitea api http_code=$code"
[ "$code" = "200" ] || { echo "::error::Gitea API unreachable, http_code=$code"; exit 1; }
cat /tmp/v.json; echo
echo "== external egress =="
ext=$(curl -s -o /dev/null -w '%{http_code}' -m 15 https://www.baidu.com || echo 000)
echo "external http_code=$ext"
echo "== gitea domain resolves NOT to loopback =="
set -o pipefail
ip=$(getent hosts git.xiaoxiajianji.com | awk '{print $1}' | head -1)
echo "git.xiaoxiajianji.com -> $ip"
if [ -z "$ip" ]; then
echo "::error::DNS resolution failed, git.xiaoxiajianji.com unresolvable"; exit 1
fi
if [ "$ip" = "127.0.0.1" ] || [ "$ip" = "::1" ]; then
echo "::error::Gitea domain resolves to loopback inside job container (hosts/DNS leak)"; exit 1
fi
echo "CANARY OK"
- name: Notify failure
if: failure()
env:
CI_NOTIFY_WEBHOOK: ${{ secrets.CI_NOTIFY_WEBHOOK }}
run: |
set +e
if [ -n "$CI_NOTIFY_WEBHOOK" ]; then
MSG="🚨 CI 金丝雀失败:runner->docker->网络->Gitea 链路异常,时间 $(date '+%Y-%m-%d %H:%M:%S'),请立即检查构建服务器"
python3 - "$CI_NOTIFY_WEBHOOK" "$MSG" <<'PY'
import json,sys,urllib.request
hook,msg=sys.argv[1],sys.argv[2]
data=json.dumps({"msg_type":"text","content":{"text":msg}}).encode()
urllib.request.urlopen(urllib.request.Request(hook,data=data,headers={"Content-Type":"application/json"}),timeout=10)
PY
fi
exit 0
File diff suppressed because it is too large Load Diff
+2 -2
View File
@@ -2,13 +2,13 @@ name: CI Trigger Monitor
on:
schedule:
- cron: '*/10 * * * *' # 每10分钟检查一次(与pr-auto-scan同步降频)
- cron: '*/5 * * * *' # 每5分钟检查一次
workflow_dispatch:
inputs:
stale_threshold:
description: 'CI未触发告警阈值(分钟)'
required: false
default: '10'
default: '5'
permissions:
contents: read
-60
View File
@@ -1,60 +0,0 @@
name: "Debug: Web container v2 (mount conflict)"
on:
push:
branches: [debug/web-crash-v2]
workflow_dispatch:
jobs:
web-diag:
runs-on: runtime-builder
timeout-minutes: 10
steps:
- name: Setup SSH and diagnose
shell: bash
env:
STAGING_SSH_KEY: ${{ secrets.PREVIEW_SSH_KEY }}
run: |
set -x
which ssh || (apt-get update -qq && apt-get install -y -qq openssh-client)
mkdir -p ~/.ssh && chmod 700 ~/.ssh
printf "%s" "$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
ssh -p $P -i ~/.ssh/id_rsa -o StrictHostKeyChecking=no root@$H 'bash -s' <<'REMOTE'
set -x
echo "=== Current staging containers ==="
docker ps -a --filter name=xiaoxia-*-staging --format "table {{.Names}}\t{{.Status}}\t{{.Image}}"
echo ""
echo "=== Web container logs (current/current-rolledback) ==="
docker logs xiaoxia-web-staging 2>&1 | tail -40
echo ""
echo "=== Web inspect: env & mounts ==="
docker inspect xiaoxia-web-staging --format 'Entrypoint: {{.Config.Entrypoint}} Cmd: {{.Config.Cmd}}'
docker inspect xiaoxia-web-staging --format '{{range .Config.Env}}{{.}}{{"\n"}}{{end}}' | grep -E "APP_ENV|VERSION"
echo "Mounts:"
docker inspect xiaoxia-web-staging --format '{{range .Mounts}}{{.Type}} {{.Source}} -> {{.Destination}} (rw={{.RW}}){{"\n"}}{{end}}'
echo ""
echo "=== Reproduce: rm on read-only bind mount ==="
docker run --rm --name nginx-ro-test \
-v /var/lib/xiaoxia-saas-staging/nginx-staging.conf:/etc/nginx/conf.d/default.conf:ro \
git.xiaoxiajianji.com/xiaoxia/xiaoxia-saas/xiaoxia-saas-web:387514c \
sh -c '
set -x
echo "Before:"
ls -la /etc/nginx/conf.d/
echo "Try rm (as entrypoint does):"
rm -f /etc/nginx/conf.d/default.conf
echo "rm exitcode=$?"
echo "After rm:"
ls -la /etc/nginx/conf.d/
echo "Test ln:"
ln -s /etc/nginx/nginx-staging.conf /etc/nginx/conf.d/default.conf
echo "ln exitcode=$?"
ls -la /etc/nginx/conf.d/
echo "nginx -t:"
nginx -t 2>&1
' 2>&1
echo ""
echo "=== Also test with NEW fixed image (9c0d4b1 if present) ==="
docker images | grep xiaoxia-saas-web | head -5
REMOTE
@@ -1,59 +0,0 @@
name: Playwright Base Image Build
on:
workflow_dispatch:
inputs:
reason:
description: "触发原因"
required: false
default: "构建 playwright 基础镜像"
jobs:
build-playwright:
name: Build Playwright Base Image
runs-on: runtime-builder
timeout-minutes: 30
steps:
- name: Docker login to Gitea Registry
shell: sh
env:
GITEA_REGISTRY_USER: xiaoxia
GITEA_REGISTRY_TOKEN: ${{ secrets.REGISTRY_TOKEN }}
run: |
set -eu
for i in 1 2 3; do
echo "=== Docker login attempt $i/3 ==="
if printf '%s' "${GITEA_REGISTRY_TOKEN}" | docker login git.xiaoxiajianji.com -u "${GITEA_REGISTRY_USER}" --password-stdin; then
echo "Docker login successful"
break
fi
echo "Docker login failed (attempt $i/3), retrying in 5s..."
sleep 5
[ $i -eq 3 ] && exit 1
done
- name: Pull, retag and push Playwright image
shell: sh
run: |
set -eu
OFFICIAL_IMAGE="mcr.microsoft.com/playwright:v1.45.0-jammy"
GITEA_IMAGE="git.xiaoxiajianji.com/xiaoxia/base/playwright:v1.45.0-jammy"
echo "=== Pulling official Playwright image ==="
docker pull "${OFFICIAL_IMAGE}"
echo "=== Tagging ==="
docker tag "${OFFICIAL_IMAGE}" "${GITEA_IMAGE}"
echo "=== Pushing to Gitea Registry ==="
docker push "${GITEA_IMAGE}"
echo "Done: ${GITEA_IMAGE}"
- name: Cleanup
if: always()
shell: sh
run: |
docker rmi "mcr.microsoft.com/playwright:v1.45.0-jammy" 2>/dev/null || true
docker rmi "git.xiaoxiajianji.com/xiaoxia/base/playwright:v1.45.0-jammy" 2>/dev/null || true
echo "Cleanup done"
+1 -1
View File
@@ -3,7 +3,7 @@ name: PR Auto Scan
# 作为短作业模式的兜底,防止事件驱动遗漏
on:
schedule:
# - cron: "*/15 * * * *" # DISABLED: temporarily to stop failure spam (2026-09-02) # 每10分钟扫描一次(脚本自带240s墙钟上限,降频减负)
- cron: "*/5 * * * *" # 每5分钟扫描一次
workflow_dispatch:
permissions:
+2 -3
View File
@@ -18,7 +18,7 @@ jobs:
name: Auto Approve on CI Green
runs-on: ci-check
if: github.event_name == 'pull_request' && !github.event.pull_request.draft
timeout-minutes: 10 # 等待CI全绿+审批,需要充足时间
timeout-minutes: 3 # 等待模式:等CI全绿后自动合并,不遗漏任何PR
steps:
- name: Checkout code
shell: sh
@@ -61,8 +61,7 @@ jobs:
name: Auto Merge on CI Green + Approved
runs-on: ci-check
if: github.event_name == 'pull_request' && !github.event.pull_request.draft && github.event.pull_request.base.ref == 'develop'
needs: [auto-approve] # 修复竞态:必须等审批完成后再尝试合并
timeout-minutes: 15 # 等待审批+CI就绪+合并,需要充足时间
timeout-minutes: 3 # 短作业模式:检查一次,不满足就退出,由pr-auto-scan每5分钟定时兜底
steps:
- name: Checkout code
shell: sh
+55 -38
View File
@@ -7,25 +7,35 @@ on:
- main
paths:
- 'requirements-base.txt'
- 'requirements.txt'
- 'requirements-worker.txt'
- 'infra/docker/worker-base.Dockerfile'
workflow_dispatch:
- 'infra/docker/worker-base-builder.Dockerfile'
- 'infra/docker/worker-base-runtime.Dockerfile'
workflow_dispatch: # 支持手动触发
jobs:
build-worker-base:
name: Build Worker Base Image
name: Build Worker Base Images
runs-on: runtime-builder
timeout-minutes: 45
timeout-minutes: 30
strategy:
fail-fast: false
matrix:
include:
- name: builder
dockerfile: infra/docker/worker-base-builder.Dockerfile
image_name: worker-base-builder
cache_name: worker-base-builder-cache
- name: runtime
dockerfile: infra/docker/worker-base-runtime.Dockerfile
image_name: worker-base-runtime
cache_name: worker-base-runtime-cache
steps:
- name: Checkout code
shell: sh
env:
GITHUB_TOKEN: ${{ github.token }}
run: |
curl -sH "Authorization: token $GITHUB_TOKEN" \
"${GITHUB_API_URL}/repos/${GITHUB_REPOSITORY}/raw/scripts/ci/step_checkout.sh?ref=${GITHUB_SHA}" \
| bash
curl -sH "Authorization: token $GITHUB_TOKEN" "${GITHUB_API_URL}/repos/${GITHUB_REPOSITORY}/raw/scripts/ci/step_checkout.sh?ref=${GITHUB_SHA}" | bash
- name: Docker login to Registry
shell: sh
@@ -38,8 +48,7 @@ jobs:
set -eu
for i in 1 2 3; do
echo "=== Docker login 尝试 $i/3 ==="
if printf '%s' "${ACR_PASSWORD}" | docker login xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com -u "${ACR_USERNAME}" --password-stdin \
&& docker login git.xiaoxiajianji.com -u "${GITEA_REGISTRY_USER}" -p "${GITEA_REGISTRY_TOKEN}"; then
if printf '%s' "${ACR_PASSWORD}" | docker login xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com -u "${ACR_USERNAME}" --password-stdin && docker login git.xiaoxiajianji.com -u "${GITEA_REGISTRY_USER}" -p "${GITEA_REGISTRY_TOKEN}"; then
echo "✅ Docker login successful"
break
fi
@@ -47,40 +56,48 @@ jobs:
sleep 5
done
- name: Build and push Worker base image
- name: Setup buildx builder
shell: sh
run: |
set -eu
ACR_IMAGE="xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com/xiaoxiakeji/saas-worker-base:latest"
GITEA_IMAGE="git.xiaoxiajianji.com/xiaoxia-saas/saas-worker-base:latest"
echo "=== Building Worker base image ==="
# 使用普通 docker build(单平台不需要 buildx
docker build \
-f infra/docker/worker-base.Dockerfile \
-t "${ACR_IMAGE}" \
.
BUILDER_NAME="ci-builder-${GITHUB_RUN_ID}-${{ matrix.name }}"
if ! docker buildx inspect "$BUILDER_NAME" > /dev/null 2>&1; then
docker buildx create --use --name "$BUILDER_NAME" --driver docker-container
echo "Created $BUILDER_NAME"
else
docker buildx use "$BUILDER_NAME"
echo "Using existing $BUILDER_NAME"
fi
docker buildx inspect --bootstrap
- name: Build and push base image
shell: sh
run: |
set -eu
REGISTRY="xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com/xiaoxiakeji"
IMAGE_TAG="${REGISTRY}/${{ matrix.image_name }}:latest"
SAFE_REF_NAME=$(echo "${GITHUB_REF_NAME}" | tr '/' '-')
CACHE_REF="${REGISTRY}/${{ matrix.cache_name }}:${SAFE_REF_NAME}"
echo "=== Building ${{ matrix.name }} base image ==="
echo "Image: ${IMAGE_TAG}"
echo "Cache: ${CACHE_REF}"
# 用通用构建脚本
bash scripts/ci/docker_build_push.sh ${{ matrix.dockerfile }} "${IMAGE_TAG}" "${CACHE_REF}"
# 同时推送到 Gitea Packages 作为备份(可选)
GITEA_IMAGE="git.xiaoxiajianji.com/xiaoxia-saas/${{ matrix.image_name }}:latest"
docker tag "${IMAGE_TAG}" "${GITEA_IMAGE}"
docker push "${GITEA_IMAGE}" || echo "Gitea Packages push failed (non-fatal)"
echo ""
echo "✅ Image built successfully"
echo "✅ ${{ matrix.name }} base image built and pushed"
# 推送到 ACR
echo "=== Pushing to ACR ==="
docker push "${ACR_IMAGE}"
echo "✅ Pushed to ACR"
# 打标签并推送到 Gitea Packages 作为备份
echo "=== Pushing to Gitea Packages ==="
docker tag "${ACR_IMAGE}" "${GITEA_IMAGE}"
docker push "${GITEA_IMAGE}" || echo "⚠️ Gitea Packages push failed (non-fatal)"
echo "✅ Gitea backup push completed"
- name: Cleanup
- name: Cleanup buildx builder
if: always()
shell: sh
run: |
ACR_IMAGE="xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com/xiaoxiakeji/saas-worker-base:latest"
docker rmi "${ACR_IMAGE}" 2>/dev/null || true
docker image prune -f 2>/dev/null || true
echo "Cleanup done"
docker buildx rm "ci-builder-${GITHUB_RUN_ID}-${{ matrix.name }}" 2>/dev/null || true
docker buildx prune -f 2>/dev/null || true
echo "Builder cleanup done"
-6
View File
@@ -24,11 +24,6 @@ ruff_cache/
.env.production
.env.staging
!.env.example
# 配置模板不受忽略规则限制
!deploy/configs/.env.staging
!deploy/configs/.env.production
# 渲染后的 env 文件包含真实密钥,绝不能提交
.env.rendered
# OS / editor
.DS_Store
@@ -59,4 +54,3 @@ frontend-v21-ui-prototype-final.html
!.vscode/settings.json
.vscode/extensions.json
.coverage
.env.current
@@ -1,26 +0,0 @@
"""Add title_config to generation_tasks
Revision ID: 057_title_config
Revises: 056_fix_cover_templates_config
Create Date: 2026-08-23
"""
import sqlalchemy as sa
from alembic import op
revision = "057_title_config"
down_revision = "056_fix_cover_templates_config"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"generation_tasks",
sa.Column("title_config", sa.JSON(), nullable=False, server_default="{}"),
)
def downgrade() -> None:
op.drop_column("generation_tasks", "title_config")
@@ -1,49 +0,0 @@
"""Add unique index on asset_libraries(project_id, kind)
Revision ID: 058_uq_asset_lib_project_kind
Revises: 057_title_config
Create Date: 2026-08-30
同一项目下同 kind 的素材库业务上唯一(前端 getOrCreate 语义、TTS 保存自动建库)。
加唯一索引兜底并发创建竞态,避免重复素材库。
"""
import sqlalchemy as sa
from alembic import op
revision = "058_uq_asset_lib_project_kind"
down_revision = "057_title_config"
branch_labels = None
depends_on = None
def upgrade() -> None:
# 建唯一索引前清洗历史重复:同 (project_id, kind) 只保留 created_at 最新的一条。
# project_id 为 NULL 的系统级行不参与去重(NULL 在唯一索引中互不冲突)。
op.execute("""
DELETE FROM asset_libraries
WHERE id IN (
SELECT id FROM (
SELECT id,
ROW_NUMBER() OVER (
PARTITION BY project_id, kind
ORDER BY created_at DESC, id DESC
) AS rn
FROM asset_libraries
WHERE project_id IS NOT NULL
) t
WHERE t.rn > 1
)
""")
# 与 model 的 UniqueConstraint 定义保持一致(pg_constraint + pg_index 同时注册),
# 避免 Alembic autogenerate 检测到 schema drift
op.create_unique_constraint(
"uq_asset_libraries_project_kind",
"asset_libraries",
["project_id", "kind"],
)
def downgrade() -> None:
op.drop_constraint("uq_asset_libraries_project_kind", "asset_libraries", type_="unique")
@@ -1,23 +0,0 @@
"""add duplicate_rate to generated_videos
Revision ID: 059_duplicate_rate
Revises: 058_uq_asset_lib_project_kind
Create Date: 2026-08-31
"""
import sqlalchemy as sa
from alembic import op
revision = "059_duplicate_rate"
down_revision = "058_uq_asset_lib_project_kind"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column("generated_videos", sa.Column("duplicate_rate", sa.Float(), nullable=True))
def downgrade() -> None:
op.drop_column("generated_videos", "duplicate_rate")
@@ -1,57 +0,0 @@
"""migrate template_segments data to template_clip_configs
Revision ID: 060_migrate_segments
Revises: 059_duplicate_rate
Create Date: 2026-08-31
"""
import sqlalchemy as sa
from alembic import op
revision = "060_migrate_segments"
down_revision = "059_duplicate_rate"
branch_labels = None
depends_on = None
def upgrade() -> None:
dialect = op.get_bind().dialect.name
if dialect == "postgresql":
config_expr = (
"CASE WHEN s.material_type IS NOT NULL AND s.material_type != '' "
"THEN json_build_object('material_type', s.material_type)::jsonb "
"ELSE '{}'::jsonb END"
)
empty_json = "'{}'::jsonb"
else:
config_expr = (
"CASE WHEN s.material_type IS NOT NULL AND s.material_type != '' "
"THEN JSON_OBJECT('material_type', s.material_type) "
"ELSE '{}' END"
)
empty_json = "'{}'"
sql_str = (
"INSERT INTO template_clip_configs "
'(id, template_id, clip_type, "order", min_duration, max_duration, '
"text_template, material_requirements, transition_effect, config, "
"created_at, updated_at) "
"SELECT "
"s.id, s.template_id, 'main', s.segment_order, "
"s.duration_min, s.duration_max, "
"'', " + empty_json + ", "
"'cut', " + config_expr + ", "
"s.created_at, s.updated_at "
"FROM template_segments s "
"WHERE NOT EXISTS ("
" SELECT 1 FROM template_clip_configs c "
" WHERE c.template_id = s.template_id"
")"
)
op.execute(sa.text(sql_str))
def downgrade() -> None:
pass
@@ -1,26 +0,0 @@
"""add sort_order to template_categories
Revision ID: 061_sort_order
Revises: 060_migrate_segments
Create Date: 2026-09-02
"""
import sqlalchemy as sa
from alembic import op
revision = "061_sort_order"
down_revision = "060_migrate_segments"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"template_categories",
sa.Column("sort_order", sa.Integer, nullable=False, server_default="0"),
)
def downgrade() -> None:
op.drop_column("template_categories", "sort_order")
@@ -1,28 +0,0 @@
"""re-add edit_plan_id to generation_tasks (align staging with production)
Revision ID: 062_edit_plan_id
Revises: 061_sort_order
Create Date: 2026-09-02
"""
import sqlalchemy as sa
from alembic import op
revision = "062_edit_plan_id"
down_revision = "061_sort_order"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"generation_tasks",
sa.Column("edit_plan_id", sa.String(36), nullable=True),
)
op.create_index("ix_generation_tasks_edit_plan_id_2", "generation_tasks", ["edit_plan_id"])
def downgrade() -> None:
op.drop_index("ix_generation_tasks_edit_plan_id_2", table_name="generation_tasks")
op.drop_column("generation_tasks", "edit_plan_id")
@@ -1,46 +0,0 @@
"""add video_fingerprint_chunks table for per-chunk fingerprint storage
Revision ID: 063_fingerprint_chunks
Revises: 062_edit_plan_id
Create Date: 2026-09-03
"""
import sqlalchemy as sa
from alembic import op
revision = "063_fingerprint_chunks"
down_revision = "062_edit_plan_id"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"video_fingerprint_chunks",
sa.Column("id", sa.String(36), primary_key=True),
sa.Column("video_id", sa.String(36), nullable=False),
sa.Column("project_id", sa.String(36), nullable=False),
sa.Column("user_id", sa.String(36), nullable=False, server_default=""),
sa.Column("start_time_ms", sa.Integer, nullable=False),
sa.Column("end_time_ms", sa.Integer, nullable=False),
sa.Column("phash_binary", sa.String(16), nullable=False),
sa.Column("color_histogram", sa.JSON, nullable=False),
sa.Column("frame_count", sa.Integer, nullable=False, server_default="1"),
sa.Column(
"created_at",
sa.DateTime,
nullable=False,
server_default=sa.func.now(),
),
)
op.create_index("ix_vfc_video_id", "video_fingerprint_chunks", ["video_id"])
op.create_index("ix_vfc_project_id", "video_fingerprint_chunks", ["project_id"])
op.create_index("ix_vfc_user_id", "video_fingerprint_chunks", ["user_id"])
def downgrade() -> None:
op.drop_index("ix_vfc_user_id", table_name="video_fingerprint_chunks")
op.drop_index("ix_vfc_project_id", table_name="video_fingerprint_chunks")
op.drop_index("ix_vfc_video_id", table_name="video_fingerprint_chunks")
op.drop_table("video_fingerprint_chunks")
@@ -1,25 +0,0 @@
"""add match_count and visual_similarity to generated_videos
Revision ID: 064_match_count_visual_sim
Revises: 063_fingerprint_chunks
Create Date: 2026-09-03
"""
import sqlalchemy as sa
from alembic import op
revision = "064_match_count_visual_sim"
down_revision = "063_fingerprint_chunks"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column("generated_videos", sa.Column("match_count", sa.Integer(), nullable=True, server_default="0"))
op.add_column("generated_videos", sa.Column("visual_similarity", sa.Float(), nullable=True, server_default="0.0"))
def downgrade() -> None:
op.drop_column("generated_videos", "visual_similarity")
op.drop_column("generated_videos", "match_count")
@@ -1,25 +0,0 @@
"""add visual_similarity and match_count to duplication_records
Revision ID: 065_dup_record_sim_match
Revises: 064_match_count_visual_sim
Create Date: 2026-09-04
"""
import sqlalchemy as sa
from alembic import op
revision = "065_dup_record_sim_match"
down_revision = "064_match_count_visual_sim"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column("duplication_records", sa.Column("visual_similarity", sa.Float(), nullable=True))
op.add_column("duplication_records", sa.Column("match_count", sa.Integer(), nullable=True))
def downgrade() -> None:
op.drop_column("duplication_records", "match_count")
op.drop_column("duplication_records", "visual_similarity")
@@ -1,34 +0,0 @@
"""add client_upload_id to assets and asset_id to ingest_jobs
Issue #1714:上传 complete 幂等 + worker 转码回写关联。
- assets.client_upload_id:客户端幂等 tokencomplete 去重)
- ingest_jobs.asset_idcomplete 阶段创建的占位 asset idworker 回写关联,
防止 HEVC 转码改写 storage_key 后找不到占位而兜底新建 READY 记录)
Revision ID: 066_upload_idempotency
Revises: 065_dup_record_sim_match
Create Date: 2026-09-05
"""
import sqlalchemy as sa
from alembic import op
revision = "066_upload_idempotency"
down_revision = "065_dup_record_sim_match"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column("assets", sa.Column("client_upload_id", sa.String(64), nullable=True))
op.create_index("ix_assets_client_upload_id", "assets", ["client_upload_id"])
op.add_column("ingest_jobs", sa.Column("asset_id", sa.String(36), nullable=False, server_default=""))
op.create_index("ix_ingest_jobs_asset_id", "ingest_jobs", ["asset_id"])
def downgrade() -> None:
op.drop_index("ix_ingest_jobs_asset_id", table_name="ingest_jobs")
op.drop_column("ingest_jobs", "asset_id")
op.drop_index("ix_assets_client_upload_id", table_name="assets")
op.drop_column("assets", "client_upload_id")
@@ -1,35 +0,0 @@
"""add celery_task_id to generation_tasks and ingest_jobs
Issue #1714:孤儿恢复/超时清理撤销队列消息。
- generation_tasks.celery_task_id:入队时记录的 Celery 消息 ID,清理时 revoke
- ingest_jobs.celery_task_id:同上(素材转码任务)
Revision ID: 067_celery_task_id
Revises: 066_upload_idempotency
Create Date: 2026-09-05
"""
import sqlalchemy as sa
from alembic import op
revision = "067_celery_task_id"
down_revision = "066_upload_idempotency"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"generation_tasks",
sa.Column("celery_task_id", sa.String(64), nullable=False, server_default=""),
)
op.add_column(
"ingest_jobs",
sa.Column("celery_task_id", sa.String(64), nullable=False, server_default=""),
)
def downgrade() -> None:
op.drop_column("ingest_jobs", "celery_task_id")
op.drop_column("generation_tasks", "celery_task_id")
@@ -1,26 +0,0 @@
"""add profile_completed to users
Issue #1718:微信新用户首次登录需设置昵称(PATCH /auth/me)。
- users.profile_completed:资料是否已完善;存量行默认 True(不触发引导),
微信新建用户在应用层置 False。
"""
import sqlalchemy as sa
from alembic import op
revision = "068_user_profile_completed"
down_revision = "067_celery_task_id"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"users",
sa.Column("profile_completed", sa.Boolean(), nullable=False, server_default=sa.text("true")),
)
def downgrade() -> None:
op.drop_column("users", "profile_completed")
@@ -1,72 +0,0 @@
"""Projects is_default + partial unique index for idempotent default project (Issue #1775)
Revision ID: 069_project_is_default
Revises: 068_user_profile_completed
Create Date: 2026-09-08
背景:
小程序端 getOrCreateDefaultProject 在重试/并发/前端重复调用下,
仅靠应用层"先查再插"不保证幂等,会给同一用户重复创建默认项目。
改动:
1. projects 表新增 is_default 布尔列(默认 false
2. 部分唯一索引 uq_projects_owner_default(owner_user_id) WHERE is_default = true
—— 保证每个用户至多一个默认项目
3. 存量数据回填:把名为"默认项目"的存量项目按创建时间最早者标记为 is_default=true
(只标记不删除;存量重复项目的清理另行确认后单独执行)
注意:部分唯一索引依赖 PostgreSQL,不支持 downgrade 到其他方言。
"""
import sqlalchemy as sa
from alembic import op
revision = "069_project_is_default"
down_revision = "068_user_profile_completed"
branch_labels = None
depends_on = None
def upgrade() -> None:
# 1. 新增 is_default 列
op.add_column(
"projects",
sa.Column(
"is_default",
sa.Boolean(),
nullable=False,
server_default=sa.text("false"),
),
)
# 2. 存量回填:每个拥有"默认项目"的用户,只把最早创建的那一个标记为默认。
# 用 ROW_NUMBER() 取每组第一条;非"默认项目"命名的项目不标记(保守,不动用户自建项目)。
op.execute("""
UPDATE projects p
SET is_default = true
WHERE p.id IN (
SELECT id FROM (
SELECT id,
ROW_NUMBER() OVER (
PARTITION BY owner_user_id
ORDER BY created_at ASC, id ASC
) AS rn
FROM projects
WHERE name = '默认项目'
) t
WHERE t.rn = 1
)
""")
# 3. 部分唯一索引:每用户至多一个默认项目(只约束 is_default = true 的行)
op.execute("""
CREATE UNIQUE INDEX uq_projects_owner_default
ON projects (owner_user_id)
WHERE is_default = true
""")
def downgrade() -> None:
op.execute("DROP INDEX IF EXISTS uq_projects_owner_default")
op.drop_column("projects", "is_default")
-48
View File
@@ -1,48 +0,0 @@
"""Add scripts table for oral broadcast script library (Issue #1795)
Revision ID: 070_add_scripts
Revises: 069_project_is_default
Create Date: 2026-09-08
新建 scripts 表,支持口播文案 CRUD + 分段存储。
"""
import sqlalchemy as sa
from alembic import op
revision = "070_add_scripts"
down_revision = "069_project_is_default"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"scripts",
sa.Column("id", sa.String(36), nullable=False),
sa.Column("user_id", sa.String(36), nullable=False),
sa.Column("title", sa.String(255), nullable=False),
sa.Column("content", sa.Text(), nullable=False, server_default=""),
sa.Column("segments", sa.JSON(), nullable=False, server_default="[]"),
sa.Column("tags", sa.JSON(), nullable=False, server_default="[]"),
sa.Column(
"created_at",
sa.DateTime(timezone=True),
nullable=False,
server_default=sa.func.now(),
),
sa.Column(
"updated_at",
sa.DateTime(timezone=True),
nullable=False,
server_default=sa.func.now(),
),
sa.PrimaryKeyConstraint("id"),
)
op.create_index("ix_scripts_user_id", "scripts", ["user_id"])
def downgrade() -> None:
op.drop_index("ix_scripts_user_id", table_name="scripts")
op.drop_table("scripts")
@@ -1,47 +0,0 @@
"""add lipsync jobs table
Revision ID: 071_add_lipsync_jobs
Revises: 070_add_scripts
Create Date: 2026-09-08
"""
import sqlalchemy as sa
from alembic import op
revision = "071_add_lipsync_jobs"
down_revision = "070_add_scripts"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"lipsync_jobs",
sa.Column("id", sa.String(36), primary_key=True),
sa.Column("user_id", sa.String(36), nullable=False, index=True),
sa.Column("project_id", sa.String(36), nullable=False, server_default=""),
sa.Column("video_url", sa.Text(), nullable=False),
sa.Column("audio_url", sa.Text(), nullable=False),
sa.Column("enable_video_loop", sa.Boolean(), nullable=False, server_default=sa.text("false")),
sa.Column("mediakit_task_id", sa.String(200), nullable=False, server_default="", index=True),
sa.Column("status", sa.String(20), nullable=False, server_default="pending", index=True),
sa.Column("output_video_url", sa.Text(), nullable=False, server_default=""),
sa.Column("output_duration", sa.Float(), nullable=False, server_default=sa.text("0.0")),
sa.Column("error_message", sa.Text(), nullable=False, server_default=""),
sa.Column("error_code", sa.String(100), nullable=False, server_default=""),
sa.Column("submitted_at", sa.DateTime(), nullable=True),
sa.Column("completed_at", sa.DateTime(), nullable=True),
sa.Column("created_at", sa.DateTime(), nullable=False, server_default=sa.func.now()),
sa.Column("updated_at", sa.DateTime(), nullable=False, server_default=sa.func.now()),
)
# 复合索引:用户 + 状态(列表查询常用)
op.create_index("ix_lipsync_jobs_user_status", "lipsync_jobs", ["user_id", "status"])
# 项目 + 用户(项目维度查询)
op.create_index("ix_lipsync_jobs_project_user", "lipsync_jobs", ["project_id", "user_id"])
def downgrade() -> None:
op.drop_index("ix_lipsync_jobs_project_user", table_name="lipsync_jobs")
op.drop_index("ix_lipsync_jobs_user_status", table_name="lipsync_jobs")
op.drop_table("lipsync_jobs")
@@ -1,48 +0,0 @@
"""add ai avatar render jobs table
Revision ID: 072_add_ai_avatar_render
Revises: 071_add_lipsync_jobs
Create Date: 2026-09-09
"""
import sqlalchemy as sa
from alembic import op
revision = "072_add_ai_avatar_render"
down_revision = "071_add_lipsync_jobs"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.create_table(
"ai_avatar_render_jobs",
sa.Column("id", sa.String(36), primary_key=True),
sa.Column("user_id", sa.String(36), nullable=False, index=True),
sa.Column("project_id", sa.String(36), nullable=False, server_default=""),
sa.Column("lipsync_job_id", sa.String(36), nullable=False),
sa.Column("script_id", sa.String(36), nullable=False),
sa.Column("b_roll_segments", sa.JSON(), nullable=False, server_default="[]"),
sa.Column("title_config", sa.JSON(), nullable=False, server_default="{}"),
sa.Column("cover_config", sa.JSON(), nullable=False, server_default="{}"),
sa.Column("status", sa.String(20), nullable=False, server_default="pending", index=True),
sa.Column("progress", sa.Integer(), nullable=False, server_default=sa.text("0")),
sa.Column("output_video_url", sa.Text(), nullable=False, server_default=""),
sa.Column("output_cover_url", sa.Text(), nullable=False, server_default=""),
sa.Column("output_duration", sa.Float(), nullable=False, server_default=sa.text("0.0")),
sa.Column("error_message", sa.Text(), nullable=False, server_default=""),
sa.Column("submitted_at", sa.DateTime(), nullable=True),
sa.Column("started_at", sa.DateTime(), nullable=True),
sa.Column("completed_at", sa.DateTime(), nullable=True),
sa.Column("created_at", sa.DateTime(), nullable=False, server_default=sa.func.now()),
sa.Column("updated_at", sa.DateTime(), nullable=False, server_default=sa.func.now()),
)
op.create_index("ix_ai_avatar_render_user_status", "ai_avatar_render_jobs", ["user_id", "status"])
op.create_index("ix_ai_avatar_render_project_user", "ai_avatar_render_jobs", ["project_id", "user_id"])
def downgrade() -> None:
op.drop_index("ix_ai_avatar_render_project_user", table_name="ai_avatar_render_jobs")
op.drop_index("ix_ai_avatar_render_user_status", table_name="ai_avatar_render_jobs")
op.drop_table("ai_avatar_render_jobs")
@@ -1,45 +0,0 @@
"""lipsync_jobs 增加 TTS 直生字段(voice_id/script_text/speed/emotion
Revision ID: 073_add_lipsync_tts_fields
Revises: 072_add_ai_avatar_render
Create Date: 2026-09-09
"""
import sqlalchemy as sa
from alembic import op
revision = "073_add_lipsync_tts_fields"
down_revision = "072_add_ai_avatar_render"
branch_labels = None
depends_on = None
def upgrade() -> None:
# 对口型支持「传音色 + 文案直接生成」:后端内部先 TTS 合成音频再提交对口型
op.add_column(
"lipsync_jobs",
sa.Column("voice_id", sa.String(200), nullable=False, server_default=""),
)
op.add_column(
"lipsync_jobs",
sa.Column("script_text", sa.Text(), nullable=False, server_default=""),
)
op.add_column(
"lipsync_jobs",
sa.Column("speed", sa.Float(), nullable=False, server_default=sa.text("1.0")),
)
op.add_column(
"lipsync_jobs",
sa.Column("emotion", sa.String(20), nullable=False, server_default=""),
)
# audio_url 改为可空:直生模式下音频由后端 TTS 合成后回填
op.alter_column("lipsync_jobs", "audio_url", existing_type=sa.Text(), nullable=True)
def downgrade() -> None:
op.alter_column("lipsync_jobs", "audio_url", existing_type=sa.Text(), nullable=False)
op.drop_column("lipsync_jobs", "emotion")
op.drop_column("lipsync_jobs", "speed")
op.drop_column("lipsync_jobs", "script_text")
op.drop_column("lipsync_jobs", "voice_id")
@@ -1,36 +0,0 @@
"""ai_avatar_render_jobs.script_id 放宽为可空串(手动文案直生场景不关联文案库)
Revision ID: 074_render_script_id_optional
Revises: 073_add_lipsync_tts_fields
Create Date: 2026-09-09
"""
import sqlalchemy as sa
from alembic import op
revision = "074_render_script_id_optional"
down_revision = "073_add_lipsync_tts_fields"
branch_labels = None
depends_on = None
def upgrade() -> None:
# 列保持 NOT NULL(空串占位),仅应用层允许不传;这里显式补 server_default 防止历史约束歧义
with op.batch_alter_table("ai_avatar_render_jobs") as batch:
batch.alter_column(
"script_id",
existing_type=sa.String(length=36),
nullable=False,
server_default="",
)
def downgrade() -> None:
with op.batch_alter_table("ai_avatar_render_jobs") as batch:
batch.alter_column(
"script_id",
existing_type=sa.String(length=36),
nullable=False,
server_default=None,
)
@@ -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")
View File
-24
View File
@@ -1,5 +1,4 @@
from app.api.routes.ai import router as ai_router
from app.api.routes.ai_avatar_render import router as ai_avatar_render_router
from app.api.routes.asset_diagnosis import router as asset_diagnosis_router
from app.api.routes.asset_libraries import router as asset_libraries_router
from app.api.routes.assets import router as assets_router
@@ -12,13 +11,10 @@ from app.api.routes.feature_flags import router as feature_flags_router
from app.api.routes.generation_cover import router as generation_cover_router
from app.api.routes.generation_preview import router as generation_preview_router
from app.api.routes.generation_tasks import router as generation_tasks_router
from app.api.routes.generation_variant_plans import router as generation_variant_plans_router
from app.api.routes.health import router as health_check_router
from app.api.routes.ingest_jobs import router as ingest_jobs_router
from app.api.routes.internal_render import router as internal_render_router
from app.api.routes.lipsync import router as lipsync_router
from app.api.routes.projects import router as projects_router
from app.api.routes.scripts import router as scripts_router
from app.api.routes.share import router as share_router
from app.api.routes.subscription import router as subscription_router
from app.api.routes.tags import router as tags_router
@@ -41,11 +37,6 @@ api_router.include_router(
auth_router,
tags=["Auth"],
)
api_router.include_router(
lipsync_router,
prefix="/lipsync",
tags=["Lipsync"],
)
api_router.include_router(
projects_router,
prefix="/projects",
@@ -108,11 +99,6 @@ api_router.include_router(
prefix="/generation",
tags=["Generation"],
)
api_router.include_router(
generation_variant_plans_router,
prefix="/generation",
tags=["Generation"],
)
api_router.include_router(
generation_cover_router,
prefix="/generation",
@@ -179,13 +165,3 @@ api_router.include_router(
internal_render_router,
tags=["Internal"],
)
api_router.include_router(
scripts_router,
prefix="/scripts",
tags=["ScriptLibrary"],
)
api_router.include_router(
ai_avatar_render_router,
prefix="/ai-avatar/render",
tags=["AI Avatar Render"],
)
-235
View File
@@ -1,235 +0,0 @@
"""AI数字人渲染合成 API 路由 — #1798.
接口:
POST /api/v1/ai-avatar/render 提交渲染任务
GET /api/v1/ai-avatar/render/jobs 任务列表
GET /api/v1/ai-avatar/render/{job_id} 任务详情
POST /api/v1/ai-avatar/render/{job_id}/cancel 取消任务
POST /api/v1/ai-avatar/render/{job_id}/retry 重试失败任务
"""
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,
SmartCoverRequest,
SmartCoverResponse,
)
from app.services.ai_avatar_cover_service import generate_smart_cover
from app.services.ai_avatar_render_service import (
AiAvatarRenderError,
AiAvatarRenderService,
)
from fastapi import APIRouter, Depends, HTTPException, Query
from sqlalchemy.orm import Session
logger = logging.getLogger(__name__)
router = APIRouter()
def _get_service(db: Session = Depends(get_db_session)) -> AiAvatarRenderService:
return AiAvatarRenderService(db)
# ── POST / — 提交渲染任务 ────────────────────────────────────────────────
@router.post("", response_model=AiAvatarRenderJobResponse, status_code=201)
def create_render_job(
body: CreateAiAvatarRenderRequest,
current_user: AuthenticatedUser = Depends(get_current_user),
svc: AiAvatarRenderService = Depends(_get_service),
):
"""提交 AI 数字人渲染任务.
将对口型视频 + B-roll 素材 + 标题叠加 + 封面提取合成最终输出视频。
"""
try:
job = svc.create_render_job(
user_id=current_user.user.id,
lipsync_job_id=body.lipsync_job_id,
script_id=body.script_id,
b_roll_segments=[s.model_dump() for s in body.b_roll_segments],
title_config=body.title_config,
cover_config=body.cover_config,
project_id=body.project_id,
)
except AiAvatarRenderError as exc:
status_map = {
"LipsyncJobNotFound": 404,
"LipsyncJobNotCompleted": 400,
"LipsyncJobNoOutput": 400,
"ScriptNotFound": 404,
}
raise HTTPException(
status_code=status_map.get(exc.code, 400),
detail={"code": exc.code, "message": str(exc)},
) from exc
# 异步触发渲染
try:
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)
return AiAvatarRenderJobResponse.model_validate(job)
# ── GET /jobs — 任务列表 ─────────────────────────────────────────────────
@router.get("/jobs", response_model=dict)
def list_render_jobs(
project_id: str = Query("", description="项目 ID 过滤"),
status: str = Query("", description="状态过滤"),
offset: int = Query(0, ge=0),
limit: int = Query(20, ge=1, le=100),
current_user: AuthenticatedUser = Depends(get_current_user),
svc: AiAvatarRenderService = Depends(_get_service),
):
"""获取 AI 数字人渲染任务列表."""
items, total = svc.list_render_jobs(
user_id=current_user.user.id,
project_id=project_id,
status=status,
offset=offset,
limit=limit,
)
return {
"items": [AiAvatarRenderJobResponse.model_validate(j) for j in items],
"total": total,
"offset": offset,
"limit": limit,
}
# ── GET /{job_id} — 任务详情 ─────────────────────────────────────────────
@router.get("/{job_id}", response_model=AiAvatarRenderJobResponse)
def get_render_job(
job_id: str,
current_user: AuthenticatedUser = Depends(get_current_user),
svc: AiAvatarRenderService = Depends(_get_service),
):
"""获取渲染任务详情."""
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")
return job
# ── POST /{job_id}/cancel — 取消任务 ─────────────────────────────────────
@router.post("/{job_id}/cancel", response_model=AiAvatarRenderJobResponse)
def cancel_render_job(
job_id: str,
current_user: AuthenticatedUser = Depends(get_current_user),
svc: AiAvatarRenderService = Depends(_get_service),
):
"""取消渲染任务(仅 pending 状态可取消)."""
job = svc.cancel_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 != "cancelled":
raise HTTPException(
status_code=400,
detail=f"任务状态 {job.status} 不可取消,仅 pending 可取消",
)
return job
# ── POST /{job_id}/retry — 重试失败任务 ──────────────────────────────────
@router.post("/{job_id}/retry", response_model=AiAvatarRenderJobResponse)
def retry_render_job(
job_id: str,
current_user: AuthenticatedUser = Depends(get_current_user),
svc: AiAvatarRenderService = Depends(_get_service),
):
"""重试失败的渲染任务."""
job = svc.retry_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 != "pending":
raise HTTPException(
status_code=400,
detail=f"仅 failed 状态的任务可重试,当前状态: {job.status}",
)
# 重新触发渲染
try:
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)
return AiAvatarRenderJobResponse.model_validate(job)
# ── POST /smart-cover — 智能获取封面(MediaKit 抽帧 + 评分选帧)────────
@router.post("/smart-cover", response_model=SmartCoverResponse)
def generate_avatar_smart_cover(
body: SmartCoverRequest,
current_user: AuthenticatedUser = Depends(get_current_user),
) -> SmartCoverResponse:
"""智能获取数字人视频封面.
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。
"""
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:
cover_url = generate_smart_cover(
video_url,
max_frames=body.max_frames,
title_config=getattr(body, "title_config", None),
)
except Exception as exc:
logger.error(
"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 = ""
if not cover_url:
return SmartCoverResponse(
cover_url="",
status="fallback_failed",
message="智能抽帧失败(MediaKit 不可用或抽帧异常),请稍后重试",
)
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")
+24 -5
View File
@@ -20,7 +20,7 @@ from packages.application import (
GetProjectUseCase,
ListAssetLibrariesUseCase,
)
from packages.domain import AssetLibraryKind
from packages.domain import AssetLibrary, AssetLibraryKind
from ._helpers import check_project_access
@@ -120,11 +120,30 @@ def ensure_default_library(
kind = AssetLibraryKind(request.kind)
# Issue #1775: 幂等获取/创建——依赖唯一约束 uq_asset_libraries_project_kind
# 并发创建冲突时回滚重查返回已有记录,不再依赖应用层"先查后插",也不会 500。
# 查找该项目下同 kind 的素材库,返回第一个
existing = asset_library_repository.find_by_project(request.project_id)
for lib in existing:
if lib.kind == kind:
return _to_asset_library_response(lib)
# 不存在 → 自动创建
import uuid
from datetime import datetime, timezone
now = datetime.now(timezone.utc)
default_name = _DEFAULT_LIBRARY_NAMES.get(request.kind, f"{request.kind}素材库")
library = asset_library_repository.get_or_create_default_library(request.project_id, kind, name=default_name)
return _to_asset_library_response(library)
library = AssetLibrary(
id=str(uuid.uuid4()),
project_id=request.project_id,
name=default_name,
kind=kind,
asset_count=0,
total_size=0,
created_at=now,
updated_at=now,
)
created = asset_library_repository.create(library)
return _to_asset_library_response(created)
@router.delete("/{library_id}", status_code=status.HTTP_204_NO_CONTENT, response_class=Response)
+69 -130
View File
@@ -1,5 +1,5 @@
import logging
from typing import Any, List, Optional
from typing import Any, Optional
from app.api.routes._helpers import check_project_access, format_utc_datetime
from app.auth import AuthenticatedUser, get_current_user
@@ -14,10 +14,10 @@ from app.schemas.asset import (
AssetResponse,
BatchClassifyRequest,
BatchDeleteRequest,
BatchGetRequest,
BatchMarkRequest,
BatchOperationResponse,
BatchTagRequest,
CreateAssetRequest,
ListAssetsResponse,
SmartMatchItem,
SmartMatchRequest,
@@ -26,9 +26,13 @@ from app.schemas.asset import (
UpdateAssetReviewRequest,
)
from app.schemas.tag import TagAssetsRequest
from app.services.asset_segment_tracker import compute_asset_availability, get_asset_recent_use_counts
from fastapi import APIRouter, Depends, HTTPException, Query, Response
from packages.application import (
CreateAssetCommand,
CreateAssetUseCase,
)
from packages.domain import AssetStatus, ClassificationStatus
from packages.domain.smart_match import smart_select_assets
logger = logging.getLogger(__name__)
@@ -36,23 +40,6 @@ logger = logging.getLogger(__name__)
router = APIRouter()
def _asset_availability_fields(item) -> dict:
"""视频素材返回余量四字段;非视频/无时长/异常时返回 None + usable=True(零影响)。"""
try:
info = compute_asset_availability(item)
except Exception:
logger.warning("计算素材余量失败,按可用处理: asset_id=%s", getattr(item, "id", "?"), exc_info=True)
info = None
if info is None:
return {
"used_duration": None,
"available_duration": None,
"used_ratio": None,
"usable": True,
}
return info
def _to_asset_response(item, storage_service=None) -> AssetResponse:
# 生成签名文件 URL(用于视频播放 / 文件下载)
file_url = None
@@ -64,16 +51,10 @@ def _to_asset_response(item, storage_service=None) -> AssetResponse:
logger.warning("生成签名URL失败: storage_key=%s", item.storage_key, exc_info=True)
file_url = None
# 缩略图:存储的是 storage_key,需要生成签名 URL 供前端使用
# 不再降级使用视频文件 URL(浏览器 <img> 无法渲染 .mp4,会显示黑屏)
thumbnail_url = None
if item.thumbnail_url:
try:
svc = storage_service or get_storage_service()
thumbnail_url = svc.get_download_url(item.thumbnail_url)
except Exception:
logger.warning("生成缩略图签名URL失败: key=%s", item.thumbnail_url, exc_info=True)
thumbnail_url = None
# 缩略图:优先用已有 thumbnail_url,否则对视频素材复用文件签名 URL
thumbnail_url = item.thumbnail_url
if not thumbnail_url and item.mime_type and item.mime_type.startswith("video") and file_url:
thumbnail_url = file_url
return AssetResponse(
id=item.id,
@@ -97,7 +78,6 @@ def _to_asset_response(item, storage_service=None) -> AssetResponse:
created_at=format_utc_datetime(item.created_at),
uploaded_by_user_id=item.uploaded_by_user_id,
tag_ids=getattr(item, "tag_ids", []),
**_asset_availability_fields(item),
)
@@ -290,7 +270,7 @@ def list_assets(
else:
total = asset_repository.count_by_project_ids(project_ids, status=status_list)
# 跨项目分页:逐项目累积直到凑够一页
paged_items = []
paged_items: list = []
offset = skip
remaining = limit
for pid in project_ids:
@@ -390,18 +370,6 @@ def update_asset_review_status(
return _to_asset_response(updated)
@router.post("/batch", response_model=List[AssetResponse])
def batch_get_assets(
request: BatchGetRequest,
authenticated_user: AuthenticatedUser = Depends(get_current_user),
asset_repository: Any = Depends(get_asset_repository),
) -> list[AssetResponse]:
"""批量获取素材详情(根据 ID 列表)。"""
items = asset_repository.find_by_ids(request.ids)
storage_service = get_storage_service()
return [_to_asset_response(item, storage_service) for item in items]
@router.post("/batch-delete", response_model=BatchOperationResponse)
def batch_delete_assets(
request: BatchDeleteRequest,
@@ -576,89 +544,21 @@ def smart_match_assets(
request.library_id, request.kind, status=["ready"], limit=10000
)
else:
filtered_assets = asset_repository.find_by_library(request.library_id, status=["ready"], limit=10000)
filtered_assets = asset_repository.find_by_library(
request.library_id, status=["ready"], limit=10000
)
total_candidates = len(filtered_assets)
# ── 过滤前置:余量 + 高频使用,过滤在评分/截取 limit 之前完成 ──────────
# 旧实现先 smart_select_assets(limit=N) 再对这 N 条做过滤,过滤后不回补,
# 当排名靠前的素材恰好都被排除时返回空 items(前端回退全选,smart-match 名存实亡)。
# 现在先过滤全量候选,每级过滤后为空/不足则回退上一级,最后才评分截取。
# 调用统一智能选素材算法(kind 已在 DB 层过滤,无需重复过滤)
results = smart_select_assets(
filtered_assets,
limit=request.limit,
kind=None,
)
# 1) 余量过滤:usable=False(零重复可切区间耗尽且历史区间均达复用上限)的素材排除
usable_assets = []
exhausted_assets = []
for a in filtered_assets:
try:
avail = compute_asset_availability(a)
except Exception:
logger.warning(
"smart-match 余量计算失败,按可用处理: asset_id=%s",
getattr(a, "id", "?"),
exc_info=True,
)
avail = None
if avail is not None and not avail["usable"]:
exhausted_assets.append(a)
else:
usable_assets.append(a)
if exhausted_assets:
logger.info(
"smart-match 余量过滤: 候选 %d,可切区间耗尽 %d",
len(filtered_assets), len(exhausted_assets),
)
# 回退策略:余量过滤后为空(全部耗尽)时,保留全部候选,不返回空结果。
# 宁可让用户在已耗尽素材上复用,也比 smart-match 空结果回退全选更可控
# (全选同样会选到这些素材,且不经过评分排序)。
pool = usable_assets if usable_assets else filtered_assets
# 2) 高频使用排除:同一素材在最近 5 个视频中出现超过 3 次则排除
MAX_RECENT_USE_COUNT = 3
high_freq_assets = set()
if pool:
asset_ids = [getattr(a, "id", "") for a in pool if getattr(a, "id", "")]
if asset_ids:
try:
use_counts = get_asset_recent_use_counts(
db=asset_repository.session,
asset_ids=asset_ids,
recent_video_count=5,
)
for a in pool:
aid = getattr(a, "id", "")
count = use_counts.get(aid, 0)
if count > MAX_RECENT_USE_COUNT:
high_freq_assets.add(aid)
logger.info(
"smart-match 排除高频使用素材: asset_id=%s use_count=%d limit=%d",
aid, count, MAX_RECENT_USE_COUNT,
)
# 回退策略:排除后剩余素材不足(为空或不够 limit)时,
# 不再全部排除,保留全部可用素材
if high_freq_assets:
remaining_count = len(pool) - len(high_freq_assets)
enough = request.limit is None or remaining_count >= request.limit
if remaining_count > 0 and enough:
pool = [a for a in pool if getattr(a, "id", "") not in high_freq_assets]
else:
logger.info(
"smart-match 高频排除后素材不足(%d<%s),保留全部 %d",
remaining_count,
request.limit if request.limit is not None else "不限",
len(pool),
)
except Exception:
logger.warning("smart-match 高频使用查询失败,跳过排除", exc_info=True)
# 3) 调用统一智能选素材算法(kind 已在 DB 层过滤,无需重复过滤)
results = smart_select_assets(pool, limit=request.limit, kind=None)
# 扁平结构:SmartMatchItem 继承 AssetResponse,素材字段直接在条目顶层,
# 前端无需解析 item.asset 包装层,item.id / item.usable / 余量字段直接可读
items = [
SmartMatchItem(
**_to_asset_response(r.asset).model_dump(),
asset=_to_asset_response(r.asset),
score=r.score,
breakdown=r.breakdown,
)
@@ -764,12 +664,51 @@ def untag_asset(
@router.post("", response_model=AssetResponse)
def create_asset() -> None:
"""
已废弃接口。
所有素材上传统一走 uploadAssetDirect → completeDirectUpload → ingest-jobs 流程。
"""
raise HTTPException(
status_code=410,
detail="此接口已废弃。请使用 uploadAssetDirect 接口上传素材,Worker 会自动处理(视频转码、图片/音频元数据提取)并创建 Asset 记录。",
def create_asset(
request: CreateAssetRequest,
authenticated_user: AuthenticatedUser = Depends(get_current_user),
asset_repository: Any = Depends(get_asset_repository),
asset_library_repository: Any = Depends(get_asset_library_repository),
project_repository: Any = Depends(get_project_repository),
) -> AssetResponse:
# 先获取素材库,用于推导 project_id(前端可能不传)
library = asset_library_repository.get(request.library_id)
if library is None:
raise HTTPException(status_code=404, detail=f"AssetLibrary {request.library_id} not found")
# project_id 自动推导:优先用请求值,否则从 library 关联的项目获取
project_id = request.project_id or library.project_id
project = project_repository.find_by_id(project_id)
if project is None:
raise HTTPException(status_code=404, detail=f"Project {project_id} not found")
if not project.can_access(authenticated_user.user.id):
raise HTTPException(status_code=403, detail="Access denied to project")
# 确保 library 和 project 归属一致
if library.project_id != project_id:
raise HTTPException(status_code=400, detail="AssetLibrary does not belong to the specified project")
use_case = CreateAssetUseCase(asset_repository)
item = use_case.execute(
CreateAssetCommand(
project_id=project_id,
library_id=request.library_id,
name=request.name,
storage_key=request.storage_key,
mime_type=request.mime_type,
metadata=request.metadata,
file_size=request.file_size,
thumbnail_url=request.thumbnail_url,
duration=request.duration,
width=request.width,
height=request.height,
fps=request.fps,
codec=request.codec,
status=AssetStatus(request.status),
classification_status=ClassificationStatus(request.classification_status),
quality_score=request.quality_score,
uploaded_by_user_id=authenticated_user.user.id,
)
)
return _to_asset_response(item)
+3 -187
View File
@@ -1,5 +1,4 @@
"""
from __future__ import annotations
Canonical authentication API routes.
The route layer is intentionally thin: repository construction lives in
@@ -14,9 +13,9 @@ import jwt
from app.auth import AuthenticatedUser, blacklist_token, get_current_user
from app.config import settings
from app.dependencies import get_auth_email_service, get_auth_session_store, get_user_repository
from fastapi import APIRouter, Depends, Header, HTTPException, Request, status
from fastapi import APIRouter, Depends, Header, HTTPException, status
from fastapi.security import HTTPAuthorizationCredentials, HTTPBearer
from pydantic import BaseModel, EmailStr, field_validator
from pydantic import BaseModel, EmailStr
from packages.adapters.redis import NoopSessionStore
from packages.adapters.smtp import NoopEmailService
@@ -85,23 +84,6 @@ class CurrentUserResponse(BaseModel):
phone: str = ""
phone_verified: bool = False
binding_complete: bool = False
wechat_bound: bool = False
profile_completed: bool = True
class UserProfileResponse(BaseModel):
"""用户资料负载(PATCH /me、绑定/解绑接口复用;字段与 GET /auth/me 一致,前端 normalizeUser 直接消费)"""
user_id: str
email: str
username: str
display_name: str
email_verified: bool
phone: str = ""
phone_verified: bool = False
binding_complete: bool = False
wechat_bound: bool = False
profile_completed: bool = True
class PasswordResetRequestModel(BaseModel):
@@ -290,52 +272,9 @@ async def get_current_user_info(
phone=user.phone or "",
phone_verified=user.phone_verified,
binding_complete=binding_complete,
wechat_bound=bool(user.wechat_openid),
profile_completed=user.profile_completed,
)
class UpdateProfileRequest(BaseModel):
"""更新个人资料请求(当前仅支持昵称)"""
display_name: str
@field_validator("display_name")
@classmethod
def _validate_display_name(cls, v: str) -> str:
name = (v or "").strip()
if not name:
raise ValueError("昵称不能为空白")
if len(name) > 20:
raise ValueError("昵称长度需在 1-20 个字符之间")
return name
class UpdateProfileResponse(BaseModel):
"""更新资料响应:前端 normalizeUser(response.user) 直接消费"""
user: UserProfileResponse
@router.patch("/me", response_model=UpdateProfileResponse)
async def update_current_user_profile(
request: UpdateProfileRequest,
current_user: AuthenticatedUser = Depends(get_current_user),
user_repository: UserRepository = Depends(get_user_repository),
) -> UpdateProfileResponse:
"""更新当前登录用户昵称(微信新用户首次设置昵称后置 profile_completed=True)。"""
user = current_user.user
user.display_name = request.display_name # 已 stripvalidator
if not user.profile_completed:
user.profile_completed = True
user_repository.save(user)
logger.info("[资料更新] 用户 %s 更新昵称,profile_completed=%s", user.id, user.profile_completed)
# 重新读取,确保返回的是持久化后的最新状态
fresh = user_repository.find_by_id(user.id) or user
return UpdateProfileResponse(user=_user_profile(fresh))
class _NoopSessionStore(NoopSessionStore):
pass
@@ -487,7 +426,6 @@ async def get_wechat_auth_url() -> WechatAuthUrlResponse:
@router.post("/wechat/callback", response_model=WechatLoginResponse)
async def wechat_callback(
request: WechatCallbackRequest,
http_request: Request,
user_repository: UserRepository = Depends(get_user_repository),
) -> WechatLoginResponse:
"""微信登录回调处理"""
@@ -495,30 +433,11 @@ async def wechat_callback(
from packages.application.auth.wechat_sync_use_case import WechatSyncRequest as SyncRequest
from packages.application.auth.wechat_sync_use_case import WechatSyncUseCase
# 回调可观测性:记录 UA(区分微信内置浏览器 MicroMessenger)与 state
# 便于排查"停留 open.weixin.qq.com / 回调失败"类问题(#1718
user_agent = http_request.headers.get("User-Agent", "")
is_wechat_browser = "MicroMessenger" in user_agent
logger.info(
"[微信回调] 收到回调: state=%s code_len=%d UA=%r 微信内置浏览器=%s",
(request.state or "")[:8],
len(request.code or ""),
user_agent[:200],
is_wechat_browser,
)
# 1. 用 code 换微信用户信息
oauth_service = get_wechat_oauth_service()
wechat_user, err = oauth_service.handle_callback(request.code, request.state)
if err:
# state 校验失败 / 微信 errcode 等错误原文已在 service 内 log,这里带上 UA 上下文
logger.warning("[微信回调] 处理失败: err=%s 微信内置浏览器=%s", err, is_wechat_browser)
raise HTTPException(status_code=400, detail=err)
logger.info(
"[微信回调] state 校验通过,微信用户信息获取成功: openid=%s unionid=%s",
wechat_user.openid[:8] if wechat_user.openid else "",
bool(wechat_user.unionid),
)
# 2. 同步登录/注册(复用 wechat-sync 逻辑)
use_case = WechatSyncUseCase(user_repository=user_repository)
@@ -537,7 +456,7 @@ async def wechat_callback(
user = user_repository.find_by_id(response.user_id)
binding_complete = False
if user:
binding_complete = bool(
binding_complete = (
user.phone_verified and user.email_verified and user.email and "@wechat.local" not in user.email
)
@@ -553,109 +472,6 @@ async def wechat_callback(
)
# ==================== 微信账号绑定/解绑(已登录用户) ====================
class WechatBindUrlResponse(BaseModel):
auth_url: str
state: str
class WechatBindCompleteRequest(BaseModel):
code: str
state: str = ""
class WechatBindCompleteResponse(BaseModel):
success: bool
user: UserProfileResponse
class WechatUnbindResponse(BaseModel):
success: bool
def _user_profile(user) -> UserProfileResponse:
binding_complete = bool(
user.phone_verified and user.email_verified and user.email and "@wechat.local" not in user.email
)
return UserProfileResponse(
user_id=user.id,
email=user.email,
username=user.username,
display_name=user.display_name,
email_verified=user.email_verified,
phone=user.phone or "",
phone_verified=user.phone_verified,
binding_complete=binding_complete,
wechat_bound=bool(user.wechat_openid),
profile_completed=user.profile_completed,
)
@router.get("/wechat/bind/url", response_model=WechatBindUrlResponse)
async def get_wechat_bind_url(
current_user: AuthenticatedUser = Depends(get_current_user),
) -> WechatBindUrlResponse:
"""获取微信绑定授权链接(已登录用户场景)。state 经 Redis 存储做 CSRF 校验。"""
from packages.application.auth.wechat_oauth_service import get_wechat_oauth_service
oauth_service = get_wechat_oauth_service()
auth_url, state = oauth_service.generate_auth_url()
logger.info("[微信绑定] 用户 %s 请求绑定授权链接", current_user.user.id)
return WechatBindUrlResponse(auth_url=auth_url, state=state)
@router.post("/wechat/bind", response_model=WechatBindCompleteResponse)
async def wechat_bind(
request: WechatBindCompleteRequest,
current_user: AuthenticatedUser = Depends(get_current_user),
user_repository: UserRepository = Depends(get_user_repository),
) -> WechatBindCompleteResponse:
"""微信绑定完成:扫码回调后用 code 换 openid,绑定到当前登录账号(不创建新用户)。"""
from packages.application.auth.wechat_bind_use_case import WechatBindRequest, WechatBindUseCase
from packages.application.auth.wechat_oauth_service import get_wechat_oauth_service
oauth_service = get_wechat_oauth_service()
wechat_user, err = oauth_service.handle_callback(request.code, request.state)
if err:
logger.warning("[微信绑定] 用户 %s 换取微信信息失败: %s", current_user.user.id, err)
raise HTTPException(status_code=400, detail=err)
use_case = WechatBindUseCase(user_repository=user_repository)
result, error, http_status = use_case.bind(
WechatBindRequest(
user_id=current_user.user.id,
openid=wechat_user.openid,
unionid=wechat_user.unionid or "",
)
)
if error:
logger.warning("[微信绑定] 用户 %s 绑定失败: %s", current_user.user.id, error)
raise HTTPException(status_code=http_status, detail=error)
logger.info("[微信绑定] 用户 %s 绑定成功 openid=%s", current_user.user.id, wechat_user.openid[:8])
return WechatBindCompleteResponse(success=True, user=_user_profile(result.user))
@router.delete("/wechat/bind", response_model=WechatUnbindResponse)
async def wechat_unbind(
current_user: AuthenticatedUser = Depends(get_current_user),
user_repository: UserRepository = Depends(get_user_repository),
) -> WechatUnbindResponse:
"""解绑微信:需账号仍有其他登录方式(密码/手机/真实邮箱),否则拒绝。"""
from packages.application.auth.wechat_bind_use_case import WechatUnbindUseCase
use_case = WechatUnbindUseCase(user_repository=user_repository)
result, error, http_status = use_case.unbind(current_user.user.id)
if error:
logger.warning("[微信解绑] 用户 %s 解绑失败: %s", current_user.user.id, error)
raise HTTPException(status_code=http_status, detail=error)
logger.info("[微信解绑] 用户 %s 解绑成功", current_user.user.id)
return WechatUnbindResponse(success=True)
# ==================== 验证码 & 绑定 ====================
+3 -5
View File
@@ -14,7 +14,6 @@ from typing import Any
from uuid import uuid4
from app.api.routes._helpers import require_project_and_library
from app.api.routes.upload import _persist_celery_task_id
from app.auth import AuthenticatedUser, get_current_user
from app.core.celery_app import celery_app
from app.core.storage import OSSStorageService, get_storage_service
@@ -177,8 +176,8 @@ def _cleanup_expired_uploads() -> int:
meta_file.unlink()
cleaned += 1
logger.info(f"Cleaned up expired upload: {upload_id}")
except Exception:
logger.exception("Failed to cleanup upload metadata: %s", meta_file)
except Exception as e:
logger.warning(f"Failed to cleanup upload metadata {meta_file}: {e}")
return cleaned
@@ -382,8 +381,7 @@ async def complete_chunked_upload(
file_hash=request.file_hash,
)
)
celery_result = celery_app.send_task("worker.ingest_asset", args=[job.id])
_persist_celery_task_id(ingest_job_repository, job, getattr(celery_result, "id", ""))
celery_app.send_task("worker.ingest_asset", args=[job.id])
# Update metadata status
meta["status"] = "completed"
-9
View File
@@ -7,7 +7,6 @@ from typing import Any
from uuid import uuid4
from app.auth import AuthenticatedUser, get_current_user
from app.core.celery_app import celery_app
from app.core.storage import OSSStorageService, get_storage_service
from app.dependencies import get_duplication_repository
from app.schemas.duplication import (
@@ -77,8 +76,6 @@ def _to_record_response(record: DuplicationRecord) -> DuplicationRecordResponse:
status=record.status,
duplicate_rate=record.duplicate_rate,
duplicate_count=record.duplicate_count,
visual_similarity=getattr(record, "visual_similarity", None),
match_count=getattr(record, "match_count", None),
created_at=record.created_at.isoformat(),
updated_at=record.updated_at.isoformat(),
)
@@ -93,8 +90,6 @@ def _to_detail_response(record: DuplicationRecord) -> DuplicationDetailResponse:
status=record.status,
duplicate_rate=record.duplicate_rate,
duplicate_count=record.duplicate_count,
visual_similarity=getattr(record, "visual_similarity", None),
match_count=getattr(record, "match_count", None),
created_at=record.created_at.isoformat(),
updated_at=record.updated_at.isoformat(),
segments=[
@@ -197,8 +192,6 @@ async def upload_for_duplication(
authenticated_user.user.id,
)
celery_app.send_task("worker.process_duplication_check", args=[record.id])
return DuplicationUploadResponse(
id=record.id,
status=record.status,
@@ -303,8 +296,6 @@ def retry_duplication(
detail=f"查重记录 {record_id} 不存在",
)
celery_app.send_task("worker.process_duplication_check", args=[updated.id])
return DuplicationUploadResponse(
id=updated.id,
status=updated.status,
File diff suppressed because it is too large Load Diff
+62 -354
View File
@@ -14,7 +14,6 @@ from app.core.task_enqueue import (
USER_PENDING_LIMIT,
GlobalQueueFull,
UserPendingLimitExceeded,
build_rate_limit_detail,
safe_enqueue_generation_task,
)
from app.dependencies import (
@@ -24,7 +23,6 @@ from app.dependencies import (
get_generation_task_repository,
)
from app.schemas.generation_task import (
BatchPreviewGenerationTaskResponse,
CreatePreviewGenerationTaskRequest,
PreviewGenerationTaskResponse,
)
@@ -100,7 +98,7 @@ def _resolve_strategy_id_from_template(template_id: str, db: Session, user_id: s
try:
new_repo = SQLAlchemyEditTemplateRepository(db)
new_template = new_repo.get(template_id)
if new_template and getattr(new_template, "editing_mode", ""): # type: ignore[arg-type]
if new_template and getattr(new_template, "editing_mode", ""):
mode = new_template.editing_mode.strip()
if mode:
logger.info(
@@ -195,19 +193,11 @@ def _to_preview_response(task, generated_videos: list | None = None) -> PreviewG
if started_at and completed_at:
generate_duration = (completed_at - started_at).total_seconds()
title_cfg = getattr(task, "title_config", None)
title_cfg = title_cfg if isinstance(title_cfg, dict) else {}
extra_meta = getattr(task, "extra_meta", None)
extra_meta = extra_meta if isinstance(extra_meta, dict) else {}
voice_library_id = getattr(task, "voice_library_id", "") or ""
if not isinstance(voice_library_id, str):
voice_library_id = str(voice_library_id) if voice_library_id else ""
return PreviewGenerationTaskResponse(
task_id=task.id,
status=task.status.value if hasattr(task.status, "value") else str(task.status),
progress=float(task.progress or 0.0),
is_preview=bool(getattr(task, "is_preview", True)),
variant_index=int(extra_meta.get("variant_index", 0) or 0),
resolution=getattr(task, "resolution", "") or "",
video_url=video_url,
duration=duration,
@@ -216,8 +206,6 @@ def _to_preview_response(task, generated_videos: list | None = None) -> PreviewG
transition_count=transition_count,
material_usage=material_usage,
error_message=task.error_message or "",
title_text=str(title_cfg.get("text", "") or ""),
voice_library_id=voice_library_id,
created_at=task.created_at,
started_at=started_at,
finished_at=completed_at,
@@ -225,100 +213,50 @@ def _to_preview_response(task, generated_videos: list | None = None) -> PreviewG
)
def _resolve_preview_edit_plan_id(
*,
request: CreatePreviewGenerationTaskRequest,
task,
db: Session,
user_id: str,
) -> str:
"""确定任务关联的编辑计划ID:优先前端传入,否则按 template_id+user 兜底查找。"""
if task.source_edit_plan_id:
return task.source_edit_plan_id
if not request.template_id:
return ""
try:
from packages.adapters.sqlalchemy_impl.edit_plan_repository import (
SQLAlchemyEditPlanRepository,
)
_plan_repo = SQLAlchemyEditPlanRepository(db)
_plans = _plan_repo.list_by_template(request.template_id, limit=20)
for _p in _plans:
if (_p.created_by_user_id or "") == user_id:
logger.info(
"[预览生成] 自动关联编辑计划: task_id=%s plan_id=%s",
task.id,
_p.id,
)
return _p.id
except Exception:
logger.warning(
"[预览生成] 查找关联编辑计划失败(不影响主流程): task_id=%s",
task.id,
exc_info=True,
)
return ""
def _variant_value(values: list[str], index: int, fallback: str = "") -> str:
"""从变体数组中取值:长度1=共用,长度>N=按索引,空数组=回退 fallback。"""
if not values:
return fallback
if len(values) == 1:
return values[0]
return values[index] if index < len(values) else fallback
@router.post("/preview", response_model=BatchPreviewGenerationTaskResponse, status_code=201)
@router.post("/preview", response_model=PreviewGenerationTaskResponse, status_code=201)
def create_preview_generation_task(
request: CreatePreviewGenerationTaskRequest,
authenticated_user: AuthenticatedUser = Depends(get_current_user),
generation_task_repository=Depends(get_generation_task_repository),
db: Session = Depends(get_db_session),
asset_repo=Depends(get_asset_repository),
) -> BatchPreviewGenerationTaskResponse:
"""创建预览生成任务(支持批量)
) -> PreviewGenerationTaskResponse:
"""创建预览生成任务。
preview_count=1 时行为与旧版完全一致(创建 1 个任务);
preview_count=N 时一次创建 N 个独立变体任务:
- 每个变体克隆独立编辑计划(独立 clips、独立随机素材起点),N 个预览内容互不相同
- 每个变体拥有独立 task_id / 状态 / 预览视频 URL,前端按 task_id 分别轮询
- 标题样式(font/color/position 等)全局共用;标题文字/配音/封面可按变体独立
titles[] / voice_library_ids[] / cover_urls[],长度1=共用,长度N=独立)
预览渲染品质与正式生成一致(1080p, CRF 23, medium preset),确认生成时可直接复用预览产物。
Args:
request: 预览任务创建请求(template_id + asset_ids 等)
Returns:
201 + 变体任务数组 {items: [...], total: N}
201 + 预览任务详情
"""
user_id = authenticated_user.user.id
count = max(1, request.preview_count)
logger.info(
"[预览生成] 接收请求: user_id=%s, template_id=%s, asset_count=%d, preview_count=%d",
user_id,
request.template_id,
len(request.asset_ids),
count,
request.preview_count,
)
# 预检查队列限流(按变体总数计)
# 预检查队列限流
try:
user_pending = generation_task_repository.count_pending_by_user(user_id)
global_pending = generation_task_repository.count_pending_total()
if user_pending + count > USER_PENDING_LIMIT:
raise UserPendingLimitExceeded(
user_id=user_id, pending_count=user_pending + count, limit=USER_PENDING_LIMIT
)
if global_pending + count > GLOBAL_PENDING_LIMIT:
raise GlobalQueueFull(pending_count=global_pending + count, limit=GLOBAL_PENDING_LIMIT)
if user_pending + 1 > USER_PENDING_LIMIT:
raise UserPendingLimitExceeded(user_id=user_id, pending_count=user_pending + 1, limit=USER_PENDING_LIMIT)
if global_pending + 1 > GLOBAL_PENDING_LIMIT:
raise GlobalQueueFull(pending_count=global_pending + 1, limit=GLOBAL_PENDING_LIMIT)
except UserPendingLimitExceeded as e:
raise HTTPException(
status_code=429,
detail=build_rate_limit_detail(e, generation_task_repository, scope="user"),
detail=f"您的待处理任务过多(当前 {e.pending_count - 1}/{e.limit}),请等待后再提交",
) from e
except GlobalQueueFull as e:
raise HTTPException(
status_code=503,
detail=build_rate_limit_detail(e, generation_task_repository, scope="global"),
detail="系统繁忙,请稍后再试",
) from e
# 确定视频比例:优先前端传入,否则从模板 mode 推断
@@ -326,92 +264,34 @@ def create_preview_generation_task(
if not video_ratio and request.template_id:
video_ratio = _infer_video_ratio_from_template(request.template_id, db, user_id)
# 根据 video_ratio 计算输出分辨率(默认竖屏 1080x1920
output_width, output_height = 1080, 1920
if video_ratio:
parts = video_ratio.split(":")
if len(parts) == 2:
try:
w, h = int(parts[0]), int(parts[1])
base = 1920
if w < h:
output_width = round(base * w / h)
output_height = base
else:
output_width = base
output_height = round(base * h / w)
output_width = output_width - output_width % 2
output_height = output_height - output_height % 2
except (ValueError, ZeroDivisionError):
output_width, output_height = 1080, 1920
resolution = f"{output_width}x{output_height}"
logger.info(
"[预览生成] 分辨率: video_ratio=%s%s (%dx%d)",
video_ratio,
resolution,
output_width,
output_height,
)
# 从模板读取 editing_mode / mode 作为 strategy_id(渲染 pipeline 的 mode 参数
strategy_id = _resolve_strategy_id_from_template(request.template_id, db, user_id)
base_title_config = request.title_config or {}
use_case = CreateGenerationTaskUseCase(generation_task_repository)
# ── 预创建第一个任务,仅用于解析源编辑计划(不落库为最终任务)──
# 先创建一个临时任务拿到 task 对象上下文,实际 N 个任务在循环中统一创建;
# 为保持与旧版一致的源 plan 解析逻辑,先创建任务0、解析源 plan,
# 再预克隆 N 个变体 plan,最后重建任务关联。
# 简化实现:直接创建全部任务,plan 关联在创建后、入队前完成。
created_tasks: list = []
variant_plan_ids: list[str] = [] # 每个变体最终关联的 plan_id(按变体顺序)
try:
for variant_index in range(count):
# 变体独立标题文字:titles[] 覆盖 title_config.text
variant_title_text = _variant_value(request.titles, variant_index, "")
variant_title_config = dict(base_title_config)
if variant_title_text.strip():
variant_title_config["text"] = variant_title_text.strip()
# 变体独立配音
variant_voice_library_id = _variant_value(
request.voice_library_ids, variant_index, request.voice_library_id
task = use_case.execute(
CreateGenerationTaskCommand(
project_id="",
asset_library_id="",
strategy_id=strategy_id,
voice_library_id=request.voice_library_id,
template_id=request.template_id,
asset_ids=list(request.asset_ids),
title_ids=list(request.title_ids),
voice_ids=list(request.voice_ids),
created_by_user_id=user_id,
source_edit_plan_id=request.source_edit_plan_id,
asset_select_mode="",
batch_id="",
video_title=request.video_title,
resolution="",
bgm_config=request.bgm_config or {},
auto_retry_enabled=False,
auto_retry_max=0,
is_preview=True,
)
task = use_case.execute(
CreateGenerationTaskCommand(
project_id="",
asset_library_id="",
strategy_id=strategy_id,
voice_library_id=variant_voice_library_id,
template_id=request.template_id,
asset_ids=list(request.asset_ids),
title_ids=list(request.title_ids),
created_by_user_id=user_id,
source_edit_plan_id=request.source_edit_plan_id,
asset_select_mode="",
batch_id="",
video_title=request.video_title,
resolution=resolution,
bgm_config=request.bgm_config or {},
auto_retry_enabled=False,
auto_retry_max=0,
is_preview=True,
title_config=variant_title_config,
output_width=output_width,
output_height=output_height,
)
)
task.extra_meta["variant_index"] = variant_index
# 解析源编辑计划(前端传入或按模板兜底查找)
source_plan_id = _resolve_preview_edit_plan_id(request=request, task=task, db=db, user_id=user_id)
task.source_edit_plan_id = source_plan_id
generation_task_repository.update(task)
created_tasks.append(task)
)
except ValueError as e:
logger.warning("[预览生成] 创建失败: %s", e)
raise HTTPException(status_code=400, detail=str(e)) from e
@@ -419,204 +299,32 @@ def create_preview_generation_task(
logger.error("[预览生成] 创建失败: %s", e, exc_info=True)
raise HTTPException(status_code=500, detail="创建预览生成任务失败,请稍后再试") from e
# ── 独立变体 plan(#1743)──
# count=1:克隆源 plan(预览不污染源 plan,仅起点重算),行为与旧版一致;
# count>1:变体 0 保留源 plan,变体 1..N-1 用 reselect_plan_for_variant 完整
# 重跑单视频选片(素材洗牌+镜头洗牌+起点随机+跨变体避让+批次 20% 重叠重选),
# 所见即所得——预览变体差异即正式成片差异。
source_plan_id = created_tasks[0].source_edit_plan_id if created_tasks else ""
# #1749:各变体配音解析(严格守卫已在 schema;此处取每变体 voice 查时长)+ 时长分配
def _preview_voice_durations() -> list[float]:
try:
from packages.domain.variant_voice_resolver import resolve_variant_voice_ids
voices = resolve_variant_voice_ids(
count=count,
voice_library_id=request.voice_library_id,
voice_library_ids=request.voice_library_ids or None,
)
except Exception:
logger.warning("[预览生成] 配音解析失败(按无配音处理)", exc_info=True)
return [0.0] * count
try:
from app.api.routes.generation_tasks import _query_voice_durations
return _query_voice_durations(db, voices)
except Exception:
return [0.0] * count
voice_durations = _preview_voice_durations()
if source_plan_id and count == 1:
# 单预览:克隆一份(原逻辑)+ 配音时长分配
try:
from app.services.edit_plan_service import EditPlanService
_plan_svc = EditPlanService(db)
variant_plan = _plan_svc.clone_plan_for_variant(
source_plan_id,
created_by_user_id=user_id,
name_suffix="预览变体",
)
if voice_durations and voice_durations[0] > 0:
try:
_plan_svc.apply_voice_duration_to_plan(variant_plan.id, voice_durations[0])
except Exception:
logger.exception("[预览生成] 变体0 配音分配失败(不阻断): plan=%s", variant_plan.id)
variant_plan_ids.append(variant_plan.id)
except Exception as e:
logger.error("[预览生成] 克隆预览 plan 异常: %s", e, exc_info=True)
for t in created_tasks:
_mark_task_failed(generation_task_repository, t, "预览计划创建失败")
raise HTTPException(
status_code=500,
detail="创建预览任务失败:无法生成独立剪辑计划,请重试",
) from e
elif source_plan_id and count > 1:
try:
from app.services.edit_plan_service import EditPlanService
_plan_svc = EditPlanService(db)
# #1749:变体 0 也 clone(不污染源 plan+ 配音分配;变体 1..N-1 独立选片
_plan0 = _plan_svc.clone_plan_for_variant(
source_plan_id,
created_by_user_id=user_id,
name_suffix="预览变体1",
)
if voice_durations and voice_durations[0] > 0:
try:
_plan_svc.apply_voice_duration_to_plan(_plan0.id, voice_durations[0])
except Exception:
logger.exception("[预览生成] 变体0 配音分配失败(不阻断): plan=%s", _plan0.id)
variant_plan_ids.append(_plan0.id)
batch_asset_pool = list(dict.fromkeys(request.asset_ids or []))
for variant_index in range(1, count):
last_err: Exception | None = None
variant_plan = None
for _attempt in range(2): # 1 次重试,抗 DB 瞬时抖动
try:
variant_plan = _plan_svc.reselect_plan_for_variant(
source_plan_id,
batch_asset_pool,
created_by_user_id=user_id,
name_suffix=f"预览变体{variant_index + 1}",
voice_duration=(
voice_durations[variant_index] if variant_index < len(voice_durations) else 0.0
),
)
break
except ValueError as ve:
logger.warning("[预览生成] 变体独立选片失败(素材不足): %s", ve)
for t in created_tasks:
_mark_task_failed(generation_task_repository, t, "预览变体选片失败")
raise HTTPException(
status_code=400,
detail=f"批量预览第 {variant_index + 1} 个视频无法独立选片:{ve}"
"请增加素材库中的视频素材后重试。",
) from ve
except Exception as reselection_err: # noqa: PERF203
last_err = reselection_err
logger.warning(
"[预览生成] 变体独立选片失败(尝试%d/2): variant=%d error=%s",
_attempt + 1,
variant_index,
reselection_err,
exc_info=True,
)
if variant_plan is None:
logger.error(
"[预览生成] 变体独立选片重试仍失败: variant=%d source=%s",
variant_index,
source_plan_id,
exc_info=last_err,
)
for t in created_tasks:
_mark_task_failed(generation_task_repository, t, "预览变体计划创建失败")
raise HTTPException(
status_code=500,
detail="创建预览任务失败:无法生成独立剪辑计划,请重试",
) from last_err
variant_plan_ids.append(variant_plan.id)
except HTTPException:
raise
except Exception as e:
logger.error("[预览生成] 变体 plan 生成异常: %s", e, exc_info=True)
for t in created_tasks:
_mark_task_failed(generation_task_repository, t, "预览变体计划创建失败")
raise HTTPException(
status_code=500,
detail="创建预览任务失败:无法生成独立剪辑计划,请重试",
) from e
# 关联变体 plan 并回写标题配置
for variant_index, task in enumerate(created_tasks):
if variant_plan_ids:
task.source_edit_plan_id = variant_plan_ids[variant_index]
generation_task_repository.update(task)
# 回写变体标题到 plan configworker 渲染时从 plan 读取 title 配置)
if task.source_edit_plan_id and (task.title_config or {}).get("text", "").strip():
try:
from app.api.routes.generation_tasks import _writeback_edit_plan_config
_writeback_edit_plan_config(
plan_id=task.source_edit_plan_id,
task_id=task.id,
title_config=task.title_config,
db=db,
)
except Exception:
logger.warning(
"[预览生成] 回写标题配置失败(不影响主流程): task_id=%s",
task.id,
exc_info=True,
)
# ── 入队 ──
responses: list[PreviewGenerationTaskResponse] = []
rate_limit_exc: Exception | None = None # 记录首个限流异常,全部失败时返回结构化提示
for variant_index, task in enumerate(created_tasks):
try:
enqueued = safe_enqueue_generation_task(
task,
generation_task_repository,
user_id=user_id,
log_prefix=f"[预览生成][变体{variant_index + 1}]",
log_task_status=True,
)
if not enqueued:
logger.warning("[预览生成] 任务入队失败: task_id=%s", task.id)
_mark_task_failed(generation_task_repository, task, "任务入队失败")
except UserPendingLimitExceeded as e:
_mark_task_failed(generation_task_repository, task, "待处理任务超限")
rate_limit_exc = rate_limit_exc or e
except GlobalQueueFull as e:
_mark_task_failed(generation_task_repository, task, "系统队列已满")
rate_limit_exc = rate_limit_exc or e
except Exception:
logger.exception("[预览生成] 入队异常: task_id=%s", task.id)
_mark_task_failed(generation_task_repository, task, "任务入队异常")
# enqueue 会原地更新 task 状态/进度,直接用 task 构造响应
responses.append(_to_preview_response(task))
# 队列满/限流时若全部失败,返回结构化错误码(前端区分"排队"与"创建失败"
if all(r.status == "failed" for r in responses) and rate_limit_exc is not None:
if isinstance(rate_limit_exc, UserPendingLimitExceeded):
raise HTTPException(
status_code=429,
detail=build_rate_limit_detail(rate_limit_exc, generation_task_repository, scope="user"),
)
# 入队执行;若入队失败则标记任务为 failed 避免僵尸数据
try:
if not safe_enqueue_generation_task(
task,
generation_task_repository,
user_id=user_id,
log_prefix="[预览生成]",
log_task_status=True,
):
logger.warning("[预览生成] 任务入队失败: task_id=%s", task.id)
_mark_task_failed(generation_task_repository, task, "任务入队失败")
raise HTTPException(status_code=500, detail="任务入队失败,请稍后重试")
except UserPendingLimitExceeded as e:
_mark_task_failed(generation_task_repository, task, "待处理任务超限")
raise HTTPException(
status_code=429,
detail=f"您的待处理任务过多(当前 {e.pending_count - 1}/{e.limit}),请等待后再提交",
) from None
except GlobalQueueFull:
_mark_task_failed(generation_task_repository, task, "系统队列已满")
raise HTTPException(
status_code=503,
detail=build_rate_limit_detail(rate_limit_exc, generation_task_repository, scope="global"),
)
detail="系统繁忙,请稍后再试",
) from None
logger.info(
"[预览生成] 创建完成: %d 个变体任务, task_ids=%s",
len(responses),
[r.task_id for r in responses],
)
return BatchPreviewGenerationTaskResponse(items=responses, total=len(responses))
return _to_preview_response(task)
@router.get("/preview/{task_id}", response_model=PreviewGenerationTaskResponse)
+39 -504
View File
@@ -1,4 +1,5 @@
import logging
import random
import uuid
from typing import Any
@@ -10,13 +11,11 @@ from app.core.task_enqueue import (
USER_PENDING_LIMIT,
GlobalQueueFull,
UserPendingLimitExceeded,
build_rate_limit_detail,
safe_enqueue_generation_task,
)
from app.dependencies import (
get_asset_library_repository,
get_asset_repository,
get_db_session,
get_generated_video_repository,
get_generation_task_repository,
get_project_repository,
@@ -33,7 +32,6 @@ from app.schemas.generation_task import (
ListGenerationTasksResponse,
)
from fastapi import APIRouter, Depends, HTTPException
from sqlalchemy.orm import Session
from packages.application import (
CreateGenerationTaskCommand,
@@ -48,39 +46,6 @@ logger = logging.getLogger(__name__)
router = APIRouter()
def _variant_value(values: list[str], index: int, fallback: str = "") -> str:
"""从变体数组中取值:长度1=共用,长度>N=按索引,空数组=回退 fallback。"""
if not values:
return fallback
if len(values) == 1:
return values[0]
return values[index] if index < len(values) else fallback
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)。
"""
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:
return GenerationTaskResponse(
id=task.id,
@@ -103,7 +68,7 @@ def _to_generation_task_response(task) -> GenerationTaskResponse:
output_width=getattr(task, "output_width", 1280),
output_height=getattr(task, "output_height", 720),
cover_url=getattr(task, "cover_url", ""),
title_config=getattr(task, "title_config", {}) or {},
custom_title=getattr(task, "custom_title", ""),
logs=getattr(task, "logs", "[]"),
status=task.status,
progress=task.progress,
@@ -126,9 +91,6 @@ def _to_generated_video_response(item, download_url: str | None = None) -> Gener
height=item.height,
fps=item.fps,
download_url=download_url,
duplicate_rate=getattr(item, "duplicate_rate", None),
visual_similarity=getattr(item, "visual_similarity", None),
match_count=getattr(item, "match_count", None),
)
@@ -147,16 +109,13 @@ def _select_assets_from_library(
assets: list,
mode: str,
count: int,
rng=None,
) -> list[str]:
"""根据选取模式从素材库中选取 ready 状态的视频素材 ID。
Args:
assets: 素材库中所有素材(Asset 实体列表)
mode: 选取模式 — all=全部, smart=智能匹配(多维度评分+多样性)
count: 选取数量,0 表示全部(仅 smart 模式有效)
rng: 可选随机源(smart 模式排序噪声用),生产环境不传则内部随机;
测试可注入固定种子或零噪声随机源获得确定性结果。
mode: 选取模式 — all=全部, random=随机, smart=智能匹配(多维度评分+多样性)
count: 选取数量,0 表示全部(仅 random/smart 模式有效)
Returns:
选中的素材 ID 列表
@@ -166,81 +125,23 @@ def _select_assets_from_library(
if not ready_video_assets:
return []
if mode == "random":
selected = (
ready_video_assets if count <= 0 else random.sample(ready_video_assets, min(count, len(ready_video_assets)))
)
return [a.id for a in selected]
if mode == "smart":
# 智能匹配:统一使用 packages/domain/smart_match.py 的多维评分+多样性选取
# 评分维度:质量分(40%) + 时长适配(30%) + 新鲜度(20%) + 未使用加分(10%)
# 排序注入随机噪声(#1743):同分素材每次选出不同组合,从素材组合层面降重
limit = count if count > 0 else None
results = smart_select_assets(ready_video_assets, limit=limit, kind="video", rng=rng)
results = smart_select_assets(ready_video_assets, limit=limit, kind="video")
return [r.asset.id for r in results]
# 默认 all 模式:返回全部 ready 视频素材
return [a.id for a in ready_video_assets]
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.configgeneration_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("[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(
request: CreateGenerationTaskRequest,
project_repository: Any,
@@ -286,7 +187,6 @@ def create_generation_task(
project_repository: Any = Depends(get_project_repository),
asset_library_repository: Any = Depends(get_asset_library_repository),
asset_repository: Any = Depends(get_asset_repository),
db: Session = Depends(get_db_session),
) -> BatchGenerationTaskResponse:
logger.info(
"[生成任务] 接收请求: user_id=%s, template_id=%s, asset_count=%d, mode=%s, count=%d",
@@ -327,8 +227,8 @@ def create_generation_task(
mode=request.asset_select_mode,
count=request.asset_select_count,
)
elif project_id and not resolved_asset_ids and request.asset_select_mode in ("smart",):
# 项目级模式:未指定 asset_ids 且选择了 smart 模式时,也自动选取
elif project_id and not resolved_asset_ids and request.asset_select_mode in ("random", "smart"):
# 项目级模式:未指定 asset_ids 且选择了 random/smart 模式时,也自动选取
assets = asset_repository.find_by_project(project_id)
if assets:
resolved_asset_ids = _select_assets_from_library(
@@ -342,92 +242,9 @@ def create_generation_task(
detail="当前项目没有符合条件的视频素材,请先上传并等待导入完成后再生成。",
)
# ── 兜底复用预览产物 ──
# 前端刷新后 previewTaskId 丢失,降级调 create 接口时,
# 如果同一 edit_plan 有已完成的预览任务,直接复用(秒出)。
if request.source_edit_plan_id and not request.is_preview:
try:
from packages.adapters.sqlalchemy_impl.models import (
GenerationTaskModel,
)
_preview_model = (
db.query(GenerationTaskModel)
.filter(
GenerationTaskModel.source_edit_plan_id == request.source_edit_plan_id,
GenerationTaskModel.is_preview.is_(True),
GenerationTaskModel.status == "completed",
GenerationTaskModel.created_by_user_id == authenticated_user.user.id,
)
.order_by(GenerationTaskModel.created_at.desc())
.first()
)
if _preview_model is not None:
# 校验分辨率一致性(与 confirm 端点逻辑相同)
req_w = request.output_width or 0
req_h = request.output_height or 0
src_w = getattr(_preview_model, "output_width", 0) or 0
src_h = getattr(_preview_model, "output_height", 0) or 0
resolution_match = (req_w == 0 or req_w == src_w) and (req_h == 0 or req_h == src_h)
if resolution_match:
from packages.adapters.sqlalchemy_impl.generation_task_repository import (
_to_domain,
)
preview_task = _to_domain(_preview_model)
# 如果传了标题,更新 title_config
fallback_title_config = None
if request.title_config and request.title_config.get("text", "").strip():
fallback_title_config = dict(preview_task.title_config or {})
fallback_title_config.update(request.title_config)
preview_task.mark_confirmed(
cover_url=request.cover_url or preview_task.cover_url,
output_width=request.output_width or preview_task.output_width,
output_height=request.output_height or preview_task.output_height,
title_config=fallback_title_config,
)
generation_task_repository.update(preview_task)
# 同步标题到 EditPlan.config
if fallback_title_config:
_writeback_edit_plan_config(
plan_id=request.source_edit_plan_id,
task_id=preview_task.id,
title_config=fallback_title_config,
db=db,
)
logger.info(
"[生成任务] 兜底复用预览产物: preview_task_id=%s, plan_id=%s",
preview_task.id,
request.source_edit_plan_id,
)
return BatchGenerationTaskResponse(
items=[_to_generation_task_response(preview_task)],
total=1,
)
else:
logger.info(
"[生成任务] 兜底复用跳过(分辨率不一致): plan_id=%s, src=%sx%s, req=%sx%s",
request.source_edit_plan_id,
src_w,
src_h,
req_w,
req_h,
)
except Exception:
logger.warning(
"[生成任务] 兜底复用预览产物异常(不影响主流程): plan_id=%s",
request.source_edit_plan_id,
exc_info=True,
)
use_case = CreateGenerationTaskUseCase(generation_task_repository)
count = request.count
created_tasks: list = []
created_tasks = []
failed_tasks = []
user_id = authenticated_user.user.id
# 同批次任务共享 batch_id,用于视频查重时批次内比对
@@ -446,12 +263,12 @@ def create_generation_task(
except UserPendingLimitExceeded as e:
raise HTTPException(
status_code=429,
detail=build_rate_limit_detail(e, generation_task_repository, scope="user"),
detail=f"您的待处理任务过多(当前 {e.pending_count - count}/{e.limit},本次提交 {count} 个),请等待完成后再提交",
) from e
except GlobalQueueFull as e:
raise HTTPException(
status_code=503,
detail=build_rate_limit_detail(e, generation_task_repository, scope="global"),
detail="系统繁忙,请稍后再试",
) from e
# 画中画已下线:strategy_id 中的 pip/voice_pip 统一映射为 one_take
@@ -460,220 +277,20 @@ def create_generation_task(
logger.info("画中画已下线,strategy_id %s → one_take", effective_strategy_id)
effective_strategy_id = "one_take"
# 批量生成(count>1):每个变体必须走与单视频完全相同的独立选片流程(#1743/#1749)。
# - 变体 0clone 源 plan(不污染源 plan),变体 1..N-1 用 reselect_plan_for_variant
# 完整重跑选片(素材级去重:fresh 优先 → 受控复用 overlap≤20% → 短素材禁复用);
# - #1749:前端可回传 variant-plans 接口预生成的 plan_idvariant_plan_ids),直接复用;
# 回传 plan 仍按各变体配音幂等重分配段长(防 variant-plans 阶段未带配音/占位时长);
# - 配音时长:独立配音各自时长、统一配音同值,逐变体 apply_voice_duration_to_plan
# 成片总时长=配音时长(素材短→末帧冻结,禁慢放/禁截配音);
# - count>1 但没有源 plan 时,不允许 N 个任务兜底共用同一 plan,直接 4xx 中断。
# 在创建任何任务【之前】预生成/校验全部变体 plan:失败直接中断(此时无脏数据)。
variant_plan_ids: list[str] = []
if count > 1:
from app.services.edit_plan_service import EditPlanService
from packages.domain.variant_voice_resolver import VariantVoiceError, resolve_variant_voice_ids
_plan_svc = EditPlanService(db)
# 解析每变体配音(严格守卫:独立配音长度/缺值 → 400,禁静默 fallback
try:
variant_voices = resolve_variant_voice_ids(
count=count,
voice_library_id=request.voice_library_id,
voice_library_ids=request.voice_library_ids or None,
)
except VariantVoiceError as ve:
raise HTTPException(status_code=400, detail=str(ve)) from ve
# 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(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
_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
logger.error("[生成任务] 批量 count=%d 但无可编辑计划(无 source_edit_plan_id/template plan", count)
raise HTTPException(
status_code=400,
detail="批量生成需要先完成预览生成(缺少剪辑计划)。请先生成预览后再批量创建。",
)
# 批次素材池:请求显式素材 + 库自动匹配素材(resolved_asset_ids
batch_asset_pool = list(dict.fromkeys(resolved_asset_ids or []))
if request.variant_plan_ids:
# ① 前端回传 variant-plans 预生成结果:直接复用(轻量选片接口已建好 plan)
if len(request.variant_plan_ids) != count:
raise HTTPException(
status_code=400,
detail=f"variant_plan_ids 数量({len(request.variant_plan_ids)})与视频数量({count})不一致",
)
# 校验归属权
from packages.adapters.sqlalchemy_impl.models import EditPlanModel
for _pid in request.variant_plan_ids:
_pm = db.query(EditPlanModel).filter(EditPlanModel.id == _pid).first()
if _pm is None:
raise HTTPException(status_code=400, detail=f"剪辑计划不存在: {_pid}")
if _pm.created_by_user_id and _pm.created_by_user_id != user_id:
raise HTTPException(status_code=403, detail=f"无权使用剪辑计划: {_pid}")
variant_plan_ids = list(request.variant_plan_ids)
else:
# ② 服务端选片:变体 0 clone 源 plan(不污染源 plan
try:
_plan0 = _plan_svc.clone_plan_for_variant(
batch_source_plan_id,
created_by_user_id=user_id,
name_suffix="批量1",
)
except Exception as clone_err:
logger.error("[生成任务] 变体0 clone 失败: %s", clone_err, exc_info=True)
raise HTTPException(
status_code=500, detail="创建批量任务失败:无法生成独立剪辑计划,请重试"
) from clone_err
variant_plan_ids.append(_plan0.id)
# 变体 1..N-1 独立选片
for task_index in range(1, count):
variant = None
last_err: Exception | None = None
for _attempt in range(2): # 1 次重试,抗 DB 瞬时抖动
try:
variant = _plan_svc.reselect_plan_for_variant(
batch_source_plan_id,
batch_asset_pool,
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,
)
break
except ValueError as ve:
# 素材不足等可预期错误:不重试,直接中断并给出明确提示
logger.warning("[生成任务] 变体独立选片失败(素材不足): %s", ve)
raise HTTPException(
status_code=400,
detail=f"批量生成第 {task_index + 1} 个视频无法独立选片:{ve}"
"请增加素材库中的视频素材后重试。",
) from ve
except Exception as reselection_err: # noqa: PERF203
last_err = reselection_err
logger.warning(
"[生成任务] 变体独立选片失败(尝试%d/2): source=%s error=%s",
_attempt + 1,
batch_source_plan_id,
reselection_err,
exc_info=True,
)
if variant is None:
logger.error(
"[生成任务] 变体独立选片重试仍失败,中断批量创建: source=%s",
batch_source_plan_id,
exc_info=last_err,
)
raise HTTPException(
status_code=500,
detail="创建批量任务失败:无法生成独立剪辑计划,请重试",
) from last_err
variant_plan_ids.append(variant.id)
# 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:
try:
_plan_svc.apply_voice_duration_to_plan(_pid, _vd)
except Exception:
logger.exception("[生成任务] 变体%d 配音时长分配失败(不阻断): plan=%s", _vi, _pid)
# N=1 正式生成:渲染侧全局慢放兜底已删除(#1749),enqueue 前也必须按配音分配段长
if count == 1 and not request.is_preview:
from packages.domain.variant_voice_resolver import VariantVoiceError, resolve_variant_voice_ids
try:
_voices = resolve_variant_voice_ids(
count=1,
voice_library_id=request.voice_library_id,
voice_library_ids=request.voice_library_ids or None,
)
_single_vd: list[float] = _query_voice_durations(db, _voices)
_single_dur = _single_vd[0] if _single_vd else 0.0
_single_plan = request.source_edit_plan_id
if not _single_plan and request.template_id:
try:
from packages.adapters.sqlalchemy_impl.models import EditPlanModel
_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
try:
EditPlanService(db).apply_voice_duration_to_plan(_single_plan, _single_dur)
except Exception:
logger.exception("[生成任务] N=1 配音时长分配失败(不阻断): plan=%s", _single_plan)
except VariantVoiceError as ve:
raise HTTPException(status_code=400, detail=str(ve)) from ve
except Exception:
logger.exception("[生成任务] N=1 配音分配兜底异常(不阻断)")
try:
for task_index in range(count):
# #1749count>1 时每个变体(含变体0)都关联各自独立 planclone/reselect/variant-plans)。
if count > 1 and variant_plan_ids:
effective_plan_id = variant_plan_ids[task_index]
else:
effective_plan_id = request.source_edit_plan_id
# 变体级独立配置:titles[]/voice_library_ids[]/cover_urls[]
# 长度1=所有变体共用,长度=count=每个变体独立,空数组=回退单值字段
variant_title_text = _variant_value(request.titles, task_index, "")
variant_title_config = dict(request.title_config or {})
if variant_title_text.strip():
variant_title_config["text"] = variant_title_text.strip()
variant_voice_library_id = _variant_value(request.voice_library_ids, task_index, request.voice_library_id)
variant_cover_url = _variant_value(request.cover_urls, task_index, request.cover_url)
for _ in range(count):
task = use_case.execute(
CreateGenerationTaskCommand(
project_id=project_id,
asset_library_id=asset_library_id,
strategy_id=effective_strategy_id,
voice_library_id=variant_voice_library_id,
voice_library_id=request.voice_library_id,
template_id=request.template_id,
asset_ids=resolved_asset_ids,
title_ids=request.title_ids,
voice_ids=request.voice_ids,
created_by_user_id=user_id,
source_edit_plan_id=effective_plan_id,
source_edit_plan_id=request.source_edit_plan_id,
asset_select_mode=request.asset_select_mode,
batch_id=batch_id,
video_title=request.video_title,
@@ -685,68 +302,11 @@ def create_generation_task(
source_task_id=request.source_task_id,
output_width=request.output_width,
output_height=request.output_height,
cover_url=variant_cover_url,
title_config=variant_title_config,
cover_url=request.cover_url,
custom_title=request.custom_title,
)
)
# 变体序号写入 extra_meta(响应/排查时可辨识)
task.extra_meta["variant_index"] = task_index
try:
# 兜底关联编辑计划:前端未传 source_edit_plan_id 时,
# 通过 template_id + user_id 在 DB 层直接查找最新的 plan。
# 必须在 enqueue 之前执行,避免 worker 读取时 source_edit_plan_id 为空(竞态条件)。
# #1743:批量(count>1)场景严禁兜底共用——变体 plan 已在上方预生成,
# 走到这里还缺 plan 说明预生成漏配,直接报错中断,不允许 N 任务关联同一 plan。
if not task.source_edit_plan_id and count > 1:
logger.error(
"[生成任务] 批量任务缺少独立 plan(禁止共用兜底): task_index=%d task_id=%s",
task_index,
task.id,
)
raise HTTPException(
status_code=500,
detail="创建批量任务失败:变体剪辑计划缺失,请重新预览后再批量生成。",
)
if not task.source_edit_plan_id and request.template_id:
try:
from packages.adapters.sqlalchemy_impl.models import EditPlanModel
_plan_model = (
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 _plan_model:
task.source_edit_plan_id = _plan_model.id
generation_task_repository.update(task)
logger.info(
"[生成任务] 自动关联编辑计划: task_id=%s plan_id=%s",
task.id,
_plan_model.id,
)
except Exception:
logger.warning(
"[生成任务] 查找关联编辑计划失败(不影响主流程): task_id=%s",
task.id,
exc_info=True,
)
# 回写 plan.config:必须在 enqueue 之前执行,
# 确保 worker 读取 plan 时 config 中已包含 generation_task_id。
# 批量场景下每个变体关联独立 plan,需各自回写自己的变体标题配置。
_effective_plan_id = task.source_edit_plan_id
if _effective_plan_id:
_writeback_edit_plan_config(
plan_id=_effective_plan_id,
task_id=task.id,
title_config=variant_title_config,
db=db,
)
if safe_enqueue_generation_task(
task,
generation_task_repository,
@@ -763,7 +323,7 @@ def create_generation_task(
if not created_tasks:
raise HTTPException(
status_code=429,
detail=build_rate_limit_detail(_e, generation_task_repository, scope="user"),
detail="您的待处理任务过多,请等待完成后再提交",
) from _e
break
except GlobalQueueFull as _e:
@@ -771,7 +331,7 @@ def create_generation_task(
if not created_tasks:
raise HTTPException(
status_code=503,
detail=build_rate_limit_detail(_e, generation_task_repository, scope="global"),
detail="系统繁忙,请稍后再试",
) from _e
break
except HTTPException:
@@ -791,7 +351,6 @@ def confirm_generation(
authenticated_user: AuthenticatedUser = Depends(get_current_user),
generation_task_repository: Any = Depends(get_generation_task_repository),
project_repository: Any = Depends(get_project_repository),
db: Session = Depends(get_db_session),
) -> BatchGenerationTaskResponse:
"""确认生成 -- 复用预览渲染产物(预览与正式品质一致)。
@@ -820,29 +379,13 @@ def confirm_generation(
resolution_match = (req_w == 0 or req_w == src_w) and (req_h == 0 or req_h == src_h)
if resolution_match:
# 如果用户传了 custom_title,同步更新 title_config
confirmed_title_config = None
if request.custom_title and request.custom_title.strip():
confirmed_title_config = dict(getattr(source_task, "title_config", {}) or {})
confirmed_title_config["text"] = request.custom_title.strip()
source_task.mark_confirmed(
cover_url=request.cover_url,
custom_title=request.custom_title,
output_width=request.output_width,
output_height=request.output_height,
title_config=confirmed_title_config,
)
generation_task_repository.update(source_task)
# 同步标题到 EditPlan.config
if confirmed_title_config and source_task.source_edit_plan_id:
_writeback_edit_plan_config(
plan_id=source_task.source_edit_plan_id,
task_id=source_task.id,
title_config=confirmed_title_config,
db=db,
)
logger.info(
"[确认生成] 复用预览产物: task_id=%s, user_id=%s",
task_id,
@@ -873,6 +416,7 @@ def confirm_generation(
template_id=source_task.template_id,
asset_ids=source_task.asset_ids,
title_ids=source_task.title_ids,
voice_ids=source_task.voice_ids,
created_by_user_id=authenticated_user.user.id,
source_edit_plan_id=source_task.source_edit_plan_id or "",
asset_select_mode=source_task.asset_select_mode,
@@ -883,6 +427,7 @@ def confirm_generation(
output_width=request.output_width,
output_height=request.output_height,
cover_url=request.cover_url,
custom_title=request.custom_title,
)
)
@@ -896,15 +441,15 @@ def confirm_generation(
log_task_status=True,
):
logger.warning("[确认生成] 入队失败: task_id=%s", new_task.id)
except UserPendingLimitExceeded as _e:
except UserPendingLimitExceeded:
raise HTTPException(
status_code=429,
detail=build_rate_limit_detail(_e, generation_task_repository, scope="user"),
detail="您的待处理任务过多,请等待完成后再提交",
) from None
except GlobalQueueFull as _e:
except GlobalQueueFull:
raise HTTPException(
status_code=503,
detail=build_rate_limit_detail(_e, generation_task_repository, scope="global"),
detail="系统繁忙,请稍后再试",
) from None
return BatchGenerationTaskResponse(
@@ -986,24 +531,12 @@ def retry_generation_task(
if user_pending >= USER_PENDING_LIMIT:
raise HTTPException(
status_code=429,
detail=build_rate_limit_detail(
UserPendingLimitExceeded(
user_id=user_id,
pending_count=user_pending,
limit=USER_PENDING_LIMIT,
),
generation_task_repository,
scope="user",
),
detail=f"您的待处理任务过多(当前 {user_pending}/{USER_PENDING_LIMIT}),请等待完成后再提交",
)
if global_pending >= GLOBAL_PENDING_LIMIT:
raise HTTPException(
status_code=503,
detail=build_rate_limit_detail(
GlobalQueueFull(pending_count=global_pending, limit=GLOBAL_PENDING_LIMIT),
generation_task_repository,
scope="global",
),
detail="系统繁忙,请稍后再试",
)
use_case = CreateGenerationTaskUseCase(generation_task_repository)
@@ -1016,6 +549,7 @@ def retry_generation_task(
template_id=task.template_id,
asset_ids=task.asset_ids,
title_ids=task.title_ids,
voice_ids=task.voice_ids,
created_by_user_id=user_id,
source_edit_plan_id=task.source_edit_plan_id or "",
asset_select_mode=getattr(task, "asset_select_mode", ""),
@@ -1026,6 +560,7 @@ def retry_generation_task(
output_width=getattr(task, "output_width", 1280),
output_height=getattr(task, "output_height", 720),
cover_url=getattr(task, "cover_url", ""),
custom_title=getattr(task, "custom_title", ""),
)
)
try:
@@ -1037,15 +572,15 @@ def retry_generation_task(
log_task_status=True,
):
logger.warning("[生成任务] 重试入队失败: task_id=%s", retried.id)
except UserPendingLimitExceeded as _e:
except UserPendingLimitExceeded:
raise HTTPException(
status_code=429,
detail=build_rate_limit_detail(_e, generation_task_repository, scope="user"),
detail="您的待处理任务过多,请等待完成后再提交",
) from None
except GlobalQueueFull as _e:
except GlobalQueueFull:
raise HTTPException(
status_code=503,
detail=build_rate_limit_detail(_e, generation_task_repository, scope="global"),
detail="系统繁忙,请稍后再试",
) from None
return _to_generation_task_response(retried)
@@ -1,178 +0,0 @@
"""轻量选片接口 POST /generation/variant-plans#1749)。
与正式生成共用同一套选片函数(EditPlanService.ensure_variant_plans →
clone_plan_for_variant / reselect_plan_for_variant → variant_plan_selector),
但**不建任务、不入队、不渲染**
- 仅为 N 个变体创建/选好 EditPlan + clips,返回 plan_id 与片段列表;
- 前端确认后调正式生成接口回传 variant_plan_ids,直接复用这些 plan
不再重复选片(回传后仍按各变体配音幂等重分配段长);
- 配音守卫:voice_library_ids 长度/缺值 → 400variant_voice_resolver),
禁静默 fallback
- 素材不足等选片失败 → 400(与正式生成同口径);除此之外不报错打断。
"""
from __future__ import annotations
import logging
from typing import Any
from app.auth import AuthenticatedUser, get_current_user
from app.dependencies import get_db_session
from fastapi import APIRouter, Depends, HTTPException
from pydantic import BaseModel, Field, model_validator
from sqlalchemy.orm import Session
from packages.domain.variant_voice_resolver import VariantVoiceError, resolve_variant_voice_ids
logger = logging.getLogger(__name__)
router = APIRouter()
class VariantPlanRequest(BaseModel):
"""轻量选片请求体(与前端 variantPlans.ts 契约一致)。"""
template_id: str = Field(default="", description="模板 ID(无 source_edit_plan_id 时用于查找骨架 plan")
asset_ids: list[str] = Field(default_factory=list, description="批次素材池")
count: int = Field(default=1, ge=1, le=50, description="变体数量")
source_edit_plan_id: str = Field(default="", description="源剪辑计划 ID(优先)")
# 配音(可选;传独立配音时严格守卫)
voice_library_id: str = Field(default="", description="统一配音 ID")
voice_library_ids: list[str] = Field(default_factory=list, description="独立配音 ID 列表(长度须=count)")
@model_validator(mode="after")
def _validate(self) -> "VariantPlanRequest":
if not self.template_id.strip() and not self.source_edit_plan_id.strip():
raise ValueError("template_id 与 source_edit_plan_id 至少需要提供一个")
try:
resolve_variant_voice_ids(
count=self.count,
voice_library_id=self.voice_library_id,
voice_library_ids=self.voice_library_ids or None,
)
except VariantVoiceError as exc:
raise ValueError(str(exc)) from exc
return self
class VariantPlanItem(BaseModel):
variant_index: int
plan_id: str
clips: list[dict[str, Any]] = Field(default_factory=list)
class VariantPlanResponse(BaseModel):
items: list[VariantPlanItem]
total: int
@router.post("/variant-plans", response_model=VariantPlanResponse)
def create_variant_plans(
request: VariantPlanRequest,
authenticated_user: AuthenticatedUser = Depends(get_current_user),
db: Session = Depends(get_db_session),
) -> VariantPlanResponse:
"""轻量选片:为 N 个变体创建独立 EditPlan + clips,不建任务/不渲染。
Returns:
200 + {items: [{variant_index, plan_id, clips}], total}
"""
user_id = authenticated_user.user.id
# 配音严格守卫(schema 已校验,此处复用解析取每变体配音)
try:
voices = resolve_variant_voice_ids(
count=request.count,
voice_library_id=request.voice_library_id,
voice_library_ids=request.voice_library_ids or None,
)
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
source_plan_id = request.source_edit_plan_id.strip()
if not source_plan_id and request.template_id.strip():
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(
status_code=400,
detail="缺少剪辑计划:请先完成一次预览生成(或传入 source_edit_plan_id)后再试。",
)
# 配音时长(硬化:异常 → 0.0 不阻断选片)
try:
from app.api.routes.generation_tasks import _query_voice_durations
voice_durations = _query_voice_durations(db, voices)
except Exception:
logger.exception("[variant-plans] 配音时长查询失败(按占位段长选片)")
voice_durations = [0.0] * request.count
from app.services.edit_plan_service import EditPlanService
svc = EditPlanService(db)
try:
plan_ids = svc.ensure_variant_plans(
source_plan_id,
request.count,
list(dict.fromkeys(request.asset_ids or [])),
created_by_user_id=user_id,
voice_durations=voice_durations,
)
except ValueError as ve:
# 素材池为空/时长全未知等可预期错误 → 400(与正式生成同口径)
logger.warning("[variant-plans] 选片失败: %s", ve)
raise HTTPException(status_code=400, detail=f"变体选片失败:{ve}。请增加素材后重试。") from ve
except HTTPException:
raise
except Exception as e:
logger.exception("[variant-plans] 选片异常")
raise HTTPException(status_code=500, detail="选片失败,请稍后重试") from e
# 组装 clips 响应
items: list[VariantPlanItem] = []
for idx, pid in enumerate(plan_ids):
clips = svc.list_clips(pid)
clip_dicts = [
{
"id": c.id,
"order": c.order,
"asset_id": c.asset_id,
"start_time": float(c.start_time or 0.0),
"duration": float(c.duration or 0.0),
"clip_type": c.clip_type,
"transition_effect": c.transition_effect,
"transition_duration": float(c.transition_duration or 0.0),
"playback_speed": float(c.playback_speed or 1.0),
"text_content": c.text_content or "",
"status": c.status or "ready",
}
for c in clips
]
items.append(VariantPlanItem(variant_index=idx, plan_id=pid, clips=clip_dicts))
logger.info(
"[variant-plans] 轻量选片完成: user=%s source=%s count=%d plans=%d",
user_id,
source_plan_id,
request.count,
len(plan_ids),
)
return VariantPlanResponse(items=items, total=len(items))
+3 -3
View File
@@ -1,6 +1,6 @@
from datetime import datetime, timezone
import psycopg
import psycopg2
import redis
from app.config import settings
from fastapi import APIRouter, status
@@ -49,7 +49,7 @@ async def _check_database() -> dict:
"message": "Using in-memory database",
}
try:
conn = psycopg.connect(settings.DATABASE_URL, connect_timeout=3)
conn = psycopg2.connect(settings.DATABASE_URL, connect_timeout=3)
with conn.cursor() as cur:
cur.execute("SELECT 1")
cur.fetchone()
@@ -124,7 +124,7 @@ async def _check_migrations() -> dict:
"message": "Using in-memory database, no migrations needed",
}
try:
conn = psycopg.connect(settings.DATABASE_URL, connect_timeout=3)
conn = psycopg2.connect(settings.DATABASE_URL, connect_timeout=3)
with conn.cursor() as cur:
cur.execute("""
SELECT COUNT(*) FROM information_schema.tables
+3 -9
View File
@@ -3,7 +3,7 @@ from typing import Any
from app.core.celery_app import celery_app
from app.dependencies import get_ingest_job_repository
from app.schemas.ingest_job import IngestJobResponse, SubmitIngestJobRequest
from fastapi import APIRouter, Depends, HTTPException
from fastapi import APIRouter, Depends
from packages.application import SubmitIngestJobCommand, SubmitIngestJobUseCase
@@ -17,7 +17,7 @@ def get_ingest_job(
) -> IngestJobResponse:
job = ingest_job_repository.get(job_id)
if job is None:
raise HTTPException(status_code=404, detail=f"IngestJob {job_id} not found")
raise ValueError(f"IngestJob {job_id} not found")
return IngestJobResponse(
id=job.id,
project_id=job.project_id,
@@ -43,13 +43,7 @@ def submit_ingest_job(
)
)
celery_result = celery_app.send_task("worker.ingest_asset", args=[job.id])
if getattr(celery_result, "id", ""):
try:
job.celery_task_id = celery_result.id
ingest_job_repository.update(job)
except Exception: # noqa: BLE001
pass
celery_app.send_task("worker.ingest_asset", args=[job.id])
return IngestJobResponse(
id=job.id,
-186
View File
@@ -1,186 +0,0 @@
"""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
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
"""
from __future__ import annotations
import logging
from app.auth import AuthenticatedUser, get_current_user
from app.dependencies import (
get_db_session,
get_voice_clone_profile_repository,
)
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
from sqlalchemy.orm import Session
logger = logging.getLogger(__name__)
router = APIRouter()
def _get_service(
db: Session = Depends(get_db_session),
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,
)
# ── POST /jobs — 提交对口型任务 ───────────────────────────────────────────
@router.post("/jobs", response_model=LipsyncJobResponse, status_code=201)
def create_lipsync_job(
body: CreateLipsyncJobRequest,
current_user: AuthenticatedUser = Depends(get_current_user),
svc: LipsyncService = Depends(_get_service),
):
"""提交对口型任务.
#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,
voice_id=body.voice_id,
script_text=body.script_text,
speed=body.speed,
emotion=body.emotion,
enable_video_loop=body.enable_video_loop,
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 → 400MediaKit 提交失败 → 502
status_code = 502
if exc.code in ("VoiceForbidden",):
status_code = 403
elif exc.code in ("InvalidInput", "TTSInvalidParam", "VoiceNotReady"):
status_code = 400
raise HTTPException(
status_code=status_code,
detail={
"code": exc.code,
"message": str(exc),
"request_id": getattr(exc, "request_id", ""),
},
) 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,
detail=f"创建对口型任务失败: {exc}",
) from exc
return job
# ── GET /jobs — 任务列表 ─────────────────────────────────────────────────
@router.get("/jobs", response_model=dict)
def list_lipsync_jobs(
project_id: str = Query("", description="项目 ID 过滤"),
status: str = Query("", description="状态过滤"),
offset: int = Query(0, ge=0),
limit: int = Query(20, ge=1, le=100),
current_user: AuthenticatedUser = Depends(get_current_user),
svc: LipsyncService = Depends(_get_service),
):
"""获取对口型任务列表."""
items, total = svc.list_jobs(
user_id=current_user.user.id,
project_id=project_id,
status=status,
offset=offset,
limit=limit,
)
return {
"items": [LipsyncJobResponse.model_validate(j) for j in items],
"total": total,
"offset": offset,
"limit": limit,
}
# ── GET /jobs/{job_id} — 任务详情 ────────────────────────────────────────
@router.get("/jobs/{job_id}", response_model=LipsyncJobResponse)
def get_lipsync_job(
job_id: str,
background: BackgroundTasks,
current_user: AuthenticatedUser = Depends(get_current_user),
svc: LipsyncService = Depends(_get_service),
):
"""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")
if job.status not in ("completed", "failed"):
background.add_task(svc.refresh_job_status, job_id, current_user.user.id)
return job
# ── POST /jobs/{job_id}/refresh — 刷新状态 ───────────────────────────────
@router.post("/jobs/{job_id}/refresh", response_model=LipsyncJobResponse)
def refresh_lipsync_job(
job_id: str,
current_user: AuthenticatedUser = Depends(get_current_user),
svc: LipsyncService = Depends(_get_service),
):
"""从 MediaKit 拉取最新状态并更新."""
job = svc.refresh_job_status(job_id, current_user.user.id)
if job is None:
raise HTTPException(status_code=404, detail="任务不存在")
return job
# ── POST /jobs/{job_id}/cancel — 取消任务 ────────────────────────────────
@router.post("/jobs/{job_id}/cancel", response_model=LipsyncJobResponse)
def cancel_lipsync_job(
job_id: str,
current_user: AuthenticatedUser = Depends(get_current_user),
svc: LipsyncService = Depends(_get_service),
):
"""取消对口型任务(仅 pending/tts_processing/submitted 状态可取消)."""
job = svc.cancel_job(job_id, current_user.user.id)
if job is None:
raise HTTPException(status_code=404, detail="任务不存在")
if job.status != "cancelled":
raise HTTPException(
status_code=400,
detail=f"任务状态 {job.status} 不可取消,仅 pending/tts_processing/submitted 可取消",
)
return job
+1 -41
View File
@@ -1,14 +1,13 @@
from typing import Any
from app.auth import AuthenticatedUser, get_current_user
from app.dependencies import get_asset_library_repository, get_project_repository
from app.dependencies import get_project_repository
from app.schemas.project import (
CreateProjectRequest,
ListProjectsResponse,
ProjectResponse,
)
from fastapi import APIRouter, Depends, HTTPException, Response, status
from pydantic import BaseModel
from packages.application import (
CreateProjectCommand,
@@ -17,20 +16,10 @@ from packages.application import (
GetProjectUseCase,
ListProjectsUseCase,
)
from packages.domain import AssetLibraryKind
router = APIRouter()
class DefaultContextResponse(BaseModel):
"""幂等默认上下文响应(Issue #1775):默认项目 + 各类型默认素材库 ID。"""
project_id: str
image_library_id: str
video_library_id: str
voice_library_id: str
def _to_project_response(item) -> ProjectResponse:
return ProjectResponse(
id=item.id,
@@ -83,35 +72,6 @@ def create_project(
return _to_project_response(project)
@router.post("/ensure-default", response_model=DefaultContextResponse)
def ensure_default_project_and_libraries(
authenticated_user: AuthenticatedUser = Depends(get_current_user),
project_repository: Any = Depends(get_project_repository),
asset_library_repository: Any = Depends(get_asset_library_repository),
) -> DefaultContextResponse:
"""幂等获取/创建当前用户的默认项目和三类默认素材库(Issue #1775)。
- 同一用户永远只有一个默认项目(部分唯一索引 uq_projects_owner_default
- 同一项目同 kind 永远只有一个默认素材库(唯一约束 uq_asset_libraries_project_kind
- 并发调用/失败重试:唯一约束冲突时返回已存在记录,不报 500
- 项目和素材库的创建各自在仓储事务内幂等,冲突回滚后重查返回同一条
"""
user_id = authenticated_user.user.id
project = project_repository.get_or_create_default_project(user_id)
libraries = {}
for kind in (AssetLibraryKind.VIDEO, AssetLibraryKind.VOICE, AssetLibraryKind.IMAGE):
library = asset_library_repository.get_or_create_default_library(project.id, kind)
libraries[kind] = library.id
return DefaultContextResponse(
project_id=project.id,
image_library_id=libraries[AssetLibraryKind.IMAGE],
video_library_id=libraries[AssetLibraryKind.VIDEO],
voice_library_id=libraries[AssetLibraryKind.VOICE],
)
@router.delete("/{project_id}", status_code=status.HTTP_204_NO_CONTENT, response_model=None, response_class=Response)
def delete_project(
project_id: str,
-123
View File
@@ -1,123 +0,0 @@
"""Script (口播文案库) CRUD routes — Issue #1795."""
from __future__ import annotations
from typing import Optional
from app.auth import AuthenticatedUser, get_current_user
from app.dependencies import get_db_session
from app.schemas.script import (
CreateScriptRequest,
ScriptListResponse,
ScriptResponse,
ScriptSegment,
UpdateScriptRequest,
)
from app.services.script_service import ScriptNotFoundError, ScriptService
from fastapi import APIRouter, Depends, HTTPException, Query, Response, status
from sqlalchemy.orm import Session
router = APIRouter()
def _get_service(session: Session = Depends(get_db_session)) -> ScriptService:
return ScriptService(session)
def _to_response(script) -> ScriptResponse:
segments = script.segments or []
return ScriptResponse(
id=script.id,
user_id=script.user_id,
title=script.title,
content=script.content,
segments=[
ScriptSegment(text=s.get("text", ""), duration=s.get("duration")) if isinstance(s, dict) else s
for s in segments
],
tags=script.tags or [],
created_at=script.created_at,
updated_at=script.updated_at,
)
@router.get("", response_model=ScriptListResponse)
def list_scripts(
skip: int = Query(0, ge=0),
limit: int = Query(50, ge=1, le=200),
tag: Optional[str] = Query(None, description="按标签筛选"),
authenticated_user: AuthenticatedUser = Depends(get_current_user),
svc: ScriptService = Depends(_get_service),
) -> ScriptListResponse:
user_id = authenticated_user.user.id
items, total = svc.list_scripts(user_id, skip=skip, limit=limit, tag=tag)
return ScriptListResponse(
items=[_to_response(i) for i in items],
total=total,
)
@router.post("", response_model=ScriptResponse, status_code=status.HTTP_201_CREATED)
def create_script(
request: CreateScriptRequest,
authenticated_user: AuthenticatedUser = Depends(get_current_user),
svc: ScriptService = Depends(_get_service),
) -> ScriptResponse:
user_id = authenticated_user.user.id
script = svc.create_script(
user_id=user_id,
title=request.title,
content=request.content,
segments=[s.model_dump() for s in request.segments],
tags=request.tags,
)
return _to_response(script)
@router.get("/{script_id}", response_model=ScriptResponse)
def get_script(
script_id: str,
authenticated_user: AuthenticatedUser = Depends(get_current_user),
svc: ScriptService = Depends(_get_service),
) -> ScriptResponse:
user_id = authenticated_user.user.id
try:
script = svc.get_script(script_id, user_id)
except ScriptNotFoundError as exc:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Script not found") from exc
return _to_response(script)
@router.put("/{script_id}", response_model=ScriptResponse)
def update_script(
script_id: str,
request: UpdateScriptRequest,
authenticated_user: AuthenticatedUser = Depends(get_current_user),
svc: ScriptService = Depends(_get_service),
) -> ScriptResponse:
user_id = authenticated_user.user.id
try:
script = svc.update_script(
script_id=script_id,
user_id=user_id,
title=request.title,
content=request.content,
segments=[s.model_dump() for s in request.segments] if request.segments is not None else None,
tags=request.tags,
)
except ScriptNotFoundError as exc:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Script not found") from exc
return _to_response(script)
@router.delete("/{script_id}", status_code=status.HTTP_204_NO_CONTENT, response_model=None, response_class=Response)
def delete_script(
script_id: str,
authenticated_user: AuthenticatedUser = Depends(get_current_user),
svc: ScriptService = Depends(_get_service),
) -> Response:
user_id = authenticated_user.user.id
deleted = svc.delete_script(script_id, user_id)
if not deleted:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Script not found")
return
+1 -7
View File
@@ -375,13 +375,7 @@ def retry_project_task(
storage_key=job.storage_key,
)
)
celery_result = celery_app.send_task("worker.ingest_asset", args=[retried.id])
if getattr(celery_result, "id", ""):
try:
retried.celery_task_id = celery_result.id
ingest_job_repository.update(retried)
except Exception: # noqa: BLE001
pass
celery_app.send_task("worker.ingest_asset", args=[retried.id])
return ProjectTaskResponse(
id=f"ingest:{retried.id}",
task_type="ingest",
-5
View File
@@ -106,10 +106,6 @@ def list_templates(
tag: str | None = Query(None, description="按标签筛选"),
keyword: str | None = Query(None, description="按名称关键词搜索"),
mode: str | None = Query(None, description="按剪辑模式筛选"),
valid_only: bool = Query(
False,
description="仅返回已配置片段的模板(剪辑页传 true;模板编辑器不传,可查看全部模板含草稿)",
),
authenticated_user: AuthenticatedUser = Depends(get_current_user),
template_repository: SQLAlchemyTemplateRepository = Depends(_get_template_repository),
) -> ListTemplatesResponse:
@@ -120,7 +116,6 @@ def list_templates(
tag=tag,
keyword=keyword,
mode=mode,
valid_only=valid_only,
)
use_case = ListTemplatesUseCase(template_repository)
templates = use_case.execute(user_id, skip=skip, limit=limit, filter=tpl_filter)
@@ -1,9 +1,10 @@
"""模板编辑器 API 路由包.
模块拆分
将原来 2560 行的 templates_editor.py 巨无霸拆分为 12 个模块:
- schemas.py: 所有 Pydantic model
- dependencies.py: 依赖注入
- _utils.py: 工具函数
- _fallback.py: 自动兜底逻辑
- draft.py: 草稿管理(详情/更新/发布/版本/回滚)
- clips.py: 片段管理(CRUD/分割/合并/重排/批量删除/从素材创建)
- adjustments.py: 片段调整(速度/音量/裁剪/批量调速)
@@ -12,6 +13,7 @@
- export.py: 导出配置
- subtitles.py: 字幕管理
- ai_features.py: AI 推荐
- generation.py: 生成(触发/进度/记录)
- timeline.py: 时间线
挂载路径: /api/v1/templates/{template_id}/editor/
@@ -32,6 +34,7 @@ from .dependencies import get_draft_plan_id, get_editor_services # noqa: F401
from .draft import router as draft_router
from .effects import router as effects_router
from .export import router as export_router
from .generation import router as generation_router
from .subtitles import router as subtitles_router
from .timeline import router as timeline_router
@@ -48,6 +51,7 @@ _sub_routers = [
export_router,
subtitles_router,
ai_features_router,
generation_router,
timeline_router,
]
+227
View File
@@ -0,0 +1,227 @@
"""模板编辑器自动兜底逻辑.
generate_editor_draft 触发生成前的自动修复流程:
1. draft → editing 状态迁移
2. 无片段时从模板复制片段配置
3. 为无素材片段分配指定素材
4. 项目有素材库时自动选素材
"""
from __future__ import annotations
import logging
import random
from typing import Any
from app.services.edit_plan_service import EditPlanService
from sqlalchemy.orm import Session
from packages.adapters.sqlalchemy_impl.template_clip_config_repository import (
SQLAlchemyTemplateClipConfigRepository,
)
from packages.adapters.sqlalchemy_impl.template_repository import (
SQLAlchemyTemplateRepository,
)
from packages.domain.edit_plan import EditPlanStatus
logger = logging.getLogger(__name__)
def _auto_fallback_draft_to_editing(svc: EditPlanService, plan_id: str, plan_check) -> None:
"""自动兜底 1: draft → editing"""
if plan_check.status == EditPlanStatus.DRAFT:
logger.info("模板编辑器自动兜底: plan=%s draft→editing", plan_id)
svc.transition_status(plan_id, EditPlanStatus.EDITING)
def _auto_fallback_copy_template_clips(svc: EditPlanService, plan_id: str, plan_check, db: Session) -> None:
"""自动兜底 2: 无片段 + 有 template_id → 从模板复制片段配置"""
existing_clips = svc.count_clips(plan_id)
if existing_clips == 0 and plan_check.template_id:
logger.info(
"模板编辑器自动兜底: plan=%s 无片段,从模板 %s 复制片段配置",
plan_id,
plan_check.template_id,
)
clip_config_repo = SQLAlchemyTemplateClipConfigRepository(db)
configs = clip_config_repo.list_by_template(plan_check.template_id)
if configs:
for cfg in configs:
svc.create_clip(
plan_id=plan_id,
clip_type=cfg.clip_type.value if hasattr(cfg.clip_type, "value") else cfg.clip_type,
order=cfg.order,
template_clip_config_id=cfg.id,
duration=cfg.default_duration,
transition_effect=(
cfg.transition_effect.value
if hasattr(cfg.transition_effect, "value")
else cfg.transition_effect
),
)
logger.info(
"模板编辑器自动兜底: plan=%s 从 template_clip_configs 复制了 %d 个片段",
plan_id,
len(configs),
)
else:
tpl_repo = SQLAlchemyTemplateRepository(db)
segments = tpl_repo.list_segments(plan_check.template_id)
for seg in segments:
avg_duration = (seg.duration_min + seg.duration_max) / 2
svc.create_clip(
plan_id=plan_id,
clip_type="main",
order=seg.segment_order,
duration=avg_duration,
config={
"material_type": seg.material_type or "",
"template_segment_id": seg.id,
},
)
logger.info(
"模板编辑器自动兜底: plan=%s 从旧模板 segments 复制了 %d 个片段",
plan_id,
len(segments),
)
def _auto_fallback_assign_assets(svc: EditPlanService, plan_id: str, plan_check) -> list:
"""自动兜底 3: 为没有素材的片段分配素材。返回剩余无素材片段列表。"""
all_clips = svc.list_clips(plan_id)
clips_without_asset = [c for c in all_clips if not c.asset_id]
config_asset_ids = (plan_check.config or {}).get("asset_ids", [])
logger.info(
"模板编辑器自动兜底3 诊断: plan=%s total_clips=%d " "clips_without_asset=%d config_asset_ids=%r",
plan_id,
len(all_clips),
len(clips_without_asset),
config_asset_ids[:5] if config_asset_ids else [],
)
if clips_without_asset and config_asset_ids:
logger.info(
"模板编辑器自动兜底3: plan=%s%d 个无素材片段分配 %d 个指定素材",
plan_id,
len(clips_without_asset),
len(config_asset_ids),
)
assigned = 0
for i, clip in enumerate(clips_without_asset):
asset_idx = i % len(config_asset_ids)
try:
svc.assign_asset(clip.id, config_asset_ids[asset_idx])
assigned += 1
except Exception as exc:
logger.error(
"模板编辑器自动兜底3: plan=%s clip=%s 分配素材 %s 失败: %s",
plan_id,
clip.id,
config_asset_ids[asset_idx],
exc,
)
logger.info(
"模板编辑器自动兜底3: plan=%s 素材分配完成 assigned=%d/%d",
plan_id,
assigned,
len(clips_without_asset),
)
# 重新检查剩余无素材片段
all_clips_after = svc.list_clips(plan_id)
clips_without_asset = [c for c in all_clips_after if not c.asset_id]
if clips_without_asset:
logger.warning(
"模板编辑器自动兜底3: plan=%s 仍有 %d 个片段无素材",
plan_id,
len(clips_without_asset),
)
elif not clips_without_asset:
logger.info("模板编辑器自动兜底3: plan=%s 所有片段已有素材,跳过", plan_id)
elif not config_asset_ids:
logger.info(
"模板编辑器自动兜底3: plan=%s config.asset_ids 为空,跳过分配",
plan_id,
)
return clips_without_asset
def _auto_fallback_auto_material_mode(
svc: EditPlanService,
plan_id: str,
plan_check,
clips_without_asset: list,
asset_library_repo: Any,
asset_repo: Any,
user_id: str = "",
) -> None:
"""自动兜底 4: 自动选素材分配给无素材片段
查找策略(按优先级):
1. plan 有 project_id → 从项目素材库查找
2. plan 无 project_id 但有 user_id → 从用户上传的素材中查找
"""
if not clips_without_asset:
return
ready_videos: list = []
source_desc = ""
# 策略 1: 通过 project_id 查找项目素材库
if plan_check.project_id:
libs = asset_library_repo.find_by_project(plan_check.project_id)
video_lib = None
for lib in libs:
lib_kind = lib.kind.value if hasattr(lib.kind, "value") else lib.kind
if lib_kind == "video":
video_lib = lib
break
if video_lib:
assets = asset_repo.find_by_library(video_lib.id)
ready_videos = [
a
for a in assets
if (a.status.value if hasattr(a.status, "value") else a.status) == "ready"
and a.mime_type
and a.mime_type.startswith("video")
]
source_desc = f"素材库 {video_lib.name}"
# 策略 2: 通过 user_id 查找用户上传的素材
if not ready_videos and user_id and hasattr(asset_repo, "find_ready_videos_by_user"):
logger.info(
"模板编辑器自动兜底4: plan=%s project_id 为空,尝试通过 user_id=%s 查找素材",
plan_id,
user_id,
)
ready_videos = asset_repo.find_ready_videos_by_user(user_id)
source_desc = f"用户上传 (user_id={user_id[:8]}...)"
if not ready_videos:
logger.warning(
"模板编辑器自动兜底4: plan=%s 未找到可用素材 (project_id=%s, user_id=%s)",
plan_id,
plan_check.project_id or "(empty)",
user_id[:8] + "..." if user_id else "(empty)",
)
return
logger.info(
"模板编辑器自动兜底4: plan=%s 自动选素材分配给 %d 个无素材片段 (来源: %s, 共 %d 个)",
plan_id,
len(clips_without_asset),
source_desc,
len(ready_videos),
)
random.shuffle(ready_videos)
for i, clip in enumerate(clips_without_asset):
asset = ready_videos[i % len(ready_videos)]
svc.assign_asset(clip.id, asset.id)
logger.info(
"模板编辑器自动兜底4: plan=%s%s 分配了 %d 个素材给 %d 个片段",
plan_id,
source_desc,
len(ready_videos),
len(clips_without_asset),
)
@@ -65,8 +65,8 @@ def _build_asset_analyses(
if url:
video_urls.append(url)
valid_asset_ids.append(aid)
except Exception:
logger.exception("获取素材URL失败: asset_id=%s", aid)
except Exception as e:
logger.warning("获取素材URL失败: asset_id=%s error=%s", aid, str(e))
if not video_urls:
logger.info("无可用视频素材,跳过视频理解分析")
@@ -108,7 +108,7 @@ def _build_asset_analyses(
return analyses
except Exception as e:
logger.exception("MediaKit 视频理解异常,将降级到无分析模式: %s", e)
logger.warning("MediaKit 视频理解异常,将降级到无分析模式: %s", str(e))
return {}
@@ -177,7 +177,7 @@ def editor_ai_recommend(
try:
db.rollback()
except Exception:
logger.exception("db rollback failed in ai_recommend")
pass
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail="AI推荐结果保存失败,请稍后重试",
File diff suppressed because it is too large Load Diff
@@ -3,6 +3,7 @@
核心依赖:
- get_editor_services: 获取模板+计划服务
- get_draft_plan_id: 根据 template_id 获取或创建草稿,返回 plan_id
- _check_queue_limits: 生成队列限流检查
"""
from __future__ import annotations
@@ -10,6 +11,7 @@ from __future__ import annotations
import logging
from app.auth import AuthenticatedUser, get_current_user
from app.core.task_enqueue import GLOBAL_PENDING_LIMIT, USER_PENDING_LIMIT
from app.dependencies import get_db_session
from app.services.edit_plan_service import EditPlanService
from app.services.edit_template_service import EditTemplateService
@@ -41,33 +43,29 @@ def get_draft_plan_id(
这是模板编辑器路由的核心依赖——所有编辑器端点都先经过这里,
确保 template_id → plan_id 的映射始终存在。
模板读取遵循单一数据源、显式判定(不使用异常降级):
- 用户自建模板在旧表 ``templates``(归属 user_idis_active=True);
- 全局模板在新表 ``edit_templates``(无 user_id,全局可读)。
模板不存在、已删除或不归属于当前用户时,一律返回 404。
兼容策略:优先从新模板系统(edit_templates 表)查找,
若不存在则回退到旧模板系统(templates 表),确保用户自建模板可用。
"""
tpl_svc, plan_svc = services
user_id = str(current_user.user.id)
# 0. 门禁:校验模板存在且可访问(即使草稿已缓存命中也要校验,
# 避免模板被删除/无权访问后仍可通过既有草稿 plan 继续操作)。
old_repo = SQLAlchemyTemplateRepository(db)
old_template = old_repo.get_active(template_id, user_id)
is_global_template = tpl_svc.get_template(template_id) is not None
if old_template is None and not is_global_template:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="模板不存在")
# 1. 草稿已存在 → 直接返回
draft = tpl_svc.get_template_draft(template_id)
if draft is not None:
return draft.id
# 2. 全局模板(新系统)→ 用新服务创建草稿
if is_global_template:
# 2. 新系统有模板 → 用新服务创建草稿
if tpl_svc.get_template(template_id) is not None:
draft = tpl_svc.create_template_draft(template_id, user_id=user_id)
return draft.id
# 3. 旧模板(templates 表)→ 基于旧模板创建草稿计划
# 3. 回退到旧模板系统templates 表)
old_repo = SQLAlchemyTemplateRepository(db)
old_template = old_repo.get(template_id, user_id=user_id)
if old_template is None:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="模板不存在")
# 4. 基于旧模板创建草稿计划
from app.services.plan_generator_service import PlanGeneratorService
from packages.domain.edit_template import EditTemplate, EditTemplateStatus
@@ -115,3 +113,29 @@ def get_draft_plan_id(
user_id,
)
return plan.id
def _check_queue_limits(gen_task_repo, user_id: str) -> None:
"""队列限流预检查"""
try:
has_count = (
hasattr(gen_task_repo, "count_pending_by_user")
and hasattr(gen_task_repo, "count_pending_total")
)
if has_count:
user_pending = gen_task_repo.count_pending_by_user(user_id)
global_pending = gen_task_repo.count_pending_total()
if user_pending >= USER_PENDING_LIMIT:
raise HTTPException(
status_code=429,
detail=f"您的待处理任务过多(当前 {user_pending}/{USER_PENDING_LIMIT}),请等待完成后再提交",
)
if global_pending >= GLOBAL_PENDING_LIMIT:
raise HTTPException(
status_code=503,
detail="系统繁忙,请稍后再试",
)
except HTTPException:
raise
except Exception as e:
logger.warning("[模板编辑器队列限流] 检查失败,跳过: %s", e)
@@ -17,8 +17,6 @@ from fastapi import APIRouter, Depends, HTTPException, Query, status
from .dependencies import get_draft_plan_id, get_editor_services
from .schemas import (
EditorClipBatchUpdateRequest,
EditorClipBatchUpdateResponse,
EditorDraftResponse,
EditorPublishResponse,
EditorRollbackRequest,
@@ -128,7 +126,11 @@ def list_template_versions(
clip_count=len(v.clip_configs),
change_note=v.change_note,
published_by=v.published_by,
created_at=(v.created_at.isoformat() if hasattr(v.created_at, "isoformat") else str(v.created_at)),
created_at=(
v.created_at.isoformat()
if hasattr(v.created_at, "isoformat")
else str(v.created_at)
),
)
for v in versions
]
@@ -150,7 +152,7 @@ def rollback_template(
try:
tpl = tpl_svc.rollback_to_version(template_id, request.version)
except ValueError as exc:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=str(exc)) from exc
raise HTTPException(status_code=400, detail=str(exc)) from exc
clip_configs = tpl_svc.list_clip_configs(template_id)
return EditorRollbackResponse(
@@ -160,35 +162,3 @@ def rollback_template(
new_version=tpl.version,
clip_count=len(clip_configs),
)
@router.put("/clips", response_model=EditorClipBatchUpdateResponse)
def batch_update_clips(
template_id: str,
req: EditorClipBatchUpdateRequest,
plan_id: str = Depends(get_draft_plan_id),
services: tuple[EditTemplateService, EditPlanService] = Depends(get_editor_services),
_: AuthenticatedUser = Depends(get_current_user),
):
"""批量替换草稿clips(全量覆盖,用于前端选择素材后同步片段)
事务保证:清空→创建→标记ready 在同一数据库事务内完成,
任何步骤失败时自动回滚,避免数据不一致。
"""
_, plan_svc = services
plan_svc.get_plan_or_raise(plan_id)
clips_data = []
for clip_item in req.clips:
item = {
"asset_id": clip_item.asset_id,
"start_time": clip_item.start_time,
"duration": clip_item.duration,
}
if clip_item.order is not None:
item["order"] = clip_item.order
clips_data.append(item)
plan_svc.replace_all_clips_transactional(plan_id, clips_data)
return EditorClipBatchUpdateResponse(plan_id=plan_id, clip_count=len(req.clips))
@@ -41,17 +41,17 @@ def list_editor_transition_presets(
_: AuthenticatedUser = Depends(get_current_user),
) -> TransitionPresetListResponse:
"""获取转场预设列表"""
from packages.domain.transition_presets import TRANSITION_PRESET_LIBRARY
from packages.domain.transition_presets import TRANSITION_PRESETS
items = [
{
"id": p.id,
"name": p.name,
"category": p.category,
"duration": p.default_duration,
"description": p.description,
"id": p["id"],
"name": p["name"],
"category": p.get("category", "通用"),
"duration": p.get("default_duration", 0.5),
"description": p.get("description", ""),
}
for p in TRANSITION_PRESET_LIBRARY
for p in TRANSITION_PRESETS
]
return TransitionPresetListResponse(items=items, total=len(items))
@@ -123,17 +123,17 @@ def list_editor_filter_presets(
_: AuthenticatedUser = Depends(get_current_user),
) -> FilterPresetListResponse:
"""获取滤镜预设列表"""
from packages.domain.filter_presets import FILTER_PRESET_LIBRARY
from packages.domain.filter_presets import FILTER_PRESETS
items = [
{
"id": p.id,
"name": p.name,
"category": p.category,
"thumbnail": p.lut_url,
"description": p.description,
"id": p["id"],
"name": p["name"],
"category": p.get("category", "通用"),
"thumbnail": p.get("thumbnail", ""),
"description": p.get("description", ""),
}
for p in FILTER_PRESET_LIBRARY
for p in FILTER_PRESETS
]
return FilterPresetListResponse(items=items, total=len(items))
+332
View File
@@ -0,0 +1,332 @@
"""草稿生成路由.
端点:
- POST /generate 触发生成
- GET /generation-status 生成进度
- GET /generations 生成记录列表
"""
from __future__ import annotations
import logging
from typing import Any
from app.auth import AuthenticatedUser, get_current_user
from app.core.celery_app import celery_app
from app.core.storage import OSSStorageService, get_storage_service
from app.dependencies import (
get_asset_library_repository,
get_asset_repository,
get_db_session,
get_generated_video_repository,
)
from app.schemas.generation_task import GenerationTaskResponse
from app.services.edit_plan_service import EditPlanService
from app.services.edit_template_service import EditTemplateService
from fastapi import APIRouter, Depends, HTTPException, status
from sqlalchemy.orm import Session
from packages.adapters.sqlalchemy_impl.generation_task_repository import (
SQLAlchemyGenerationTaskRepository,
)
from packages.application.generated_videos import ListGeneratedVideosByTaskUseCase
from packages.application.generation_tasks import (
CreateGenerationTaskCommand,
CreateGenerationTaskUseCase,
)
from packages.domain.edit_plan import EditPlanStatus
from ._fallback import (
_auto_fallback_assign_assets,
_auto_fallback_auto_material_mode,
_auto_fallback_copy_template_clips,
_auto_fallback_draft_to_editing,
)
from .dependencies import _check_queue_limits, get_draft_plan_id, get_editor_services
from .schemas import (
ClipStatusItem,
EditPlanGenerateResponse,
EditPlanGenerationsResponse,
EditPlanGenerationStatusResponse,
)
logger = logging.getLogger(__name__)
router = APIRouter(tags=["Template Editor"])
@router.post("/generate", response_model=EditPlanGenerateResponse)
def generate_editor_draft(
template_id: str,
plan_id: str = Depends(get_draft_plan_id),
services: tuple[EditTemplateService, EditPlanService] = Depends(get_editor_services),
db: Session = Depends(get_db_session),
current_user: AuthenticatedUser = Depends(get_current_user),
asset_library_repo: Any = Depends(get_asset_library_repository),
asset_repo: Any = Depends(get_asset_repository),
) -> EditPlanGenerateResponse:
"""触发模板草稿渲染生成"""
_, plan_svc = services
plan_check = plan_svc.get_plan_or_raise(plan_id)
# 自动兜底流程
_auto_fallback_draft_to_editing(plan_svc, plan_id, plan_check)
_auto_fallback_copy_template_clips(plan_svc, plan_id, plan_check, db)
clips_without_asset = _auto_fallback_assign_assets(plan_svc, plan_id, plan_check)
_auto_fallback_auto_material_mode(
plan_svc,
plan_id,
plan_check,
clips_without_asset,
asset_library_repo,
asset_repo,
user_id=str(current_user.user.id),
)
# 检查是否可复用已完成的预览产物(预览品质已与正式一致)
gen_task_repo = SQLAlchemyGenerationTaskRepository(db)
reusable_task = _find_reusable_preview_task(gen_task_repo, plan_id, plan_check)
if reusable_task:
# 复用预览产物:标记为正式产出,跳过渲染
reusable_task.mark_confirmed()
gen_task_repo.update(reusable_task)
# 将产物 URL 写入 plan config
rendered_url = _get_task_output_url(reusable_task, gen_task_repo, db)
plan_svc.update_plan_config(
plan_id,
{
"generation_task_id": reusable_task.id,
"rendered_storage_key": rendered_url, # 统一用 rendered_storage_key
},
)
plan_svc.transition_status(plan_id, EditPlanStatus.COMPLETED)
updated_plan = plan_svc.get_plan_or_raise(plan_id)
logger.info(
"模板编辑器复用预览产物: template_id=%s plan_id=%s task_id=%s by user=%s",
template_id,
plan_id,
reusable_task.id,
current_user.user.id,
)
return EditPlanGenerateResponse(
plan_id=plan_id,
plan_status=updated_plan.status.value if hasattr(updated_plan.status, "value") else updated_plan.status,
generation_task_id=reusable_task.id,
clip_count=len((plan_check.config or {}).get("clips", [])),
)
# 检查是否可生成(含最后防线自动修复 + 诊断日志)
try:
can_gen, reason = plan_svc.can_generate(plan_id)
except ValueError as exc:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=str(exc)) from exc
if not can_gen:
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=reason)
try:
clip_count = plan_svc.mark_clips_ready(plan_id)
user_id = current_user.user.id
_check_queue_limits(gen_task_repo, user_id)
gen_task_use_case = CreateGenerationTaskUseCase(gen_task_repo)
plan = plan_svc.get_plan_or_raise(plan_id)
config_asset_ids = (plan.config or {}).get("asset_ids", [])
gen_task = gen_task_use_case.execute(
CreateGenerationTaskCommand(
project_id=plan.project_id or "",
template_id=plan.template_id,
created_by_user_id=current_user.user.id,
source_edit_plan_id=plan_id,
asset_ids=list(config_asset_ids) if config_asset_ids else [],
),
)
plan_svc.update_plan_config(plan_id, {"generation_task_id": gen_task.id})
plan_svc.transition_status(plan_id, EditPlanStatus.RENDERING)
celery_app.send_task("worker.render_edit_plan", args=[plan_id])
updated_plan = plan_svc.get_plan_or_raise(plan_id)
logger.info(
"模板编辑器触发生成: template_id=%s plan_id=%s gen_task_id=%s clips=%d by user=%s",
template_id,
plan_id,
gen_task.id,
clip_count,
current_user.user.id,
)
return EditPlanGenerateResponse(
plan_id=plan_id,
plan_status=updated_plan.status.value if hasattr(updated_plan.status, "value") else updated_plan.status,
generation_task_id=gen_task.id,
clip_count=clip_count,
)
except HTTPException:
raise
except Exception as _e:
logger.exception(
"模板编辑器触发生成失败: template_id=%s plan_id=%s",
template_id,
plan_id,
)
try:
plan_svc.transition_status(plan_id, EditPlanStatus.FAILED)
except Exception:
pass
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail="生成失败,请稍后重试",
) from _e
def _find_reusable_preview_task(gen_task_repo, plan_id: str, plan) -> "object | None":
"""查找该 plan 关联的已完成预览任务,判断是否可复用。
复用条件:
1. 存在 source_edit_plan_id == plan_id 的已完成预览任务
2. plan 在预览完成后未被修改(updated_at <= 预览完成时间)
Returns:
可复用的 GenerationTask,或 None
"""
try:
tasks = gen_task_repo.list_by_source_edit_plan(plan_id)
except Exception:
return None
for task in tasks:
if not getattr(task, "is_preview", False):
continue
if not task.is_completed:
continue
# 检查 plan 是否在预览完成后被修改
completed_at = getattr(task, "completed_at", None)
if completed_at and hasattr(plan, "updated_at"):
plan_updated = plan.updated_at
# 如果 plan.updated_at 为空,无法判断是否修改过,跳过
if plan_updated is None:
continue
# 如果 plan 在预览完成后又被修改了,不能复用
if plan_updated > completed_at:
continue
return task
return None
def _get_task_output_url(task, gen_task_repo, db) -> str:
"""获取任务的输出视频 URL。"""
try:
video_repo = get_generated_video_repository(db)
use_case = ListGeneratedVideosByTaskUseCase(video_repo)
videos = use_case.execute(task.id)
if videos:
url = getattr(videos[0], "file_url", "") or ""
# 规范化:合并路径中的双斜杠(保留协议头 ://)
if url:
import re as _re
url = _re.sub(r"(?<!:)//", "/", url)
return url
except Exception:
pass
return ""
@router.get("/generation-status", response_model=EditPlanGenerationStatusResponse)
def get_editor_generation_status(
template_id: str,
plan_id: str = Depends(get_draft_plan_id),
services: tuple[EditTemplateService, EditPlanService] = Depends(get_editor_services),
storage_service: OSSStorageService = Depends(get_storage_service),
_: AuthenticatedUser = Depends(get_current_user),
) -> EditPlanGenerationStatusResponse:
"""查询草稿生成进度"""
_, plan_svc = services
try:
gen_status = plan_svc.get_generation_status(plan_id)
except ValueError as exc:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=str(exc)) from exc
plan = gen_status["plan"]
clips = gen_status["clips"]
clip_items = [
ClipStatusItem(
clip_id=c.id,
clip_type=c.clip_type,
order=c.order,
status=c.status.value if hasattr(c.status, "value") else c.status,
asset_id=c.asset_id or "",
text_content=c.text_content or "",
duration=c.duration,
)
for c in clips
]
raw_video_url = (plan.config or {}).get("rendered_storage_key", "") or (plan.config or {}).get("rendered_url", "")
video_url = ""
if raw_video_url:
if raw_video_url.startswith("http"):
video_url = raw_video_url # 已经是完整 URL
else:
try:
video_url = storage_service.get_url(raw_video_url) # storage_key -> 完整 URL
except Exception as e:
logger.warning("生成视频URL获取失败: template_id=%s error=%s", template_id, e)
video_url = raw_video_url
progress = gen_status.get("progress", 0.0)
error_message = gen_status.get("error_message", "")
gen_task_status = gen_status.get("generation_task_status")
plan_status_val = plan.status.value if hasattr(plan.status, "value") else plan.status
if plan_status_val == "completed" and progress < 100:
progress = 100.0
return EditPlanGenerationStatusResponse(
plan_id=plan_id,
plan_status=plan_status_val,
generation_task_id=gen_status["generation_task_id"],
generation_task_status=gen_task_status,
progress=progress,
video_url=video_url,
error_message=error_message,
clips=clip_items,
)
@router.get("/generations", response_model=EditPlanGenerationsResponse)
def list_editor_generations(
template_id: str,
plan_id: str = Depends(get_draft_plan_id),
services: tuple[EditTemplateService, EditPlanService] = Depends(get_editor_services),
db: Session = Depends(get_db_session),
_: AuthenticatedUser = Depends(get_current_user),
) -> EditPlanGenerationsResponse:
"""查询草稿关联的生成记录列表"""
_, plan_svc = services
plan_svc.get_plan_or_raise(plan_id)
gen_task_repo = SQLAlchemyGenerationTaskRepository(db)
tasks = gen_task_repo.list_by_source_edit_plan(plan_id)
items = [
GenerationTaskResponse(
id=t.id,
project_id=t.project_id,
asset_library_id=t.asset_library_id,
strategy_id=t.strategy_id,
voice_library_id=t.voice_library_id,
template_id=t.template_id,
asset_ids=t.asset_ids,
title_ids=t.title_ids,
voice_ids=t.voice_ids,
source_edit_plan_id=t.source_edit_plan_id or "",
status=t.status.value if hasattr(t.status, "value") else t.status,
progress=t.progress,
result_count=t.result_count,
error_message=t.error_message,
)
for t in tasks
]
return EditPlanGenerationsResponse(items=items, total=len(items))
@@ -8,6 +8,7 @@ from __future__ import annotations
import re as _re
from typing import Any, List, Optional
from app.schemas.generation_task import GenerationTaskResponse
from pydantic import BaseModel, Field, validator
_EXPORT_RESOLUTION_PATTERN = _re.compile(r"^\d+x\d+$")
@@ -15,6 +16,50 @@ _EXPORT_VALID_QUALITY_PRESETS = {"ultra_fast", "fast", "balanced", "high", "best
_EXPORT_VALID_FORMATS = {"mp4", "mov"}
# ── 生成状态相关 ────────────────────────────────────────────────────────────
class ClipStatusItem(BaseModel):
"""片段生成状态"""
clip_id: str
clip_type: str
order: int
status: str
asset_id: str
text_content: str
duration: float
class EditPlanGenerationStatusResponse(BaseModel):
"""剪辑计划生成进度响应体"""
plan_id: str
plan_status: str
generation_task_id: Optional[str] = None
generation_task_status: Optional[str] = None
progress: float = 0.0
video_url: str = ""
error_message: str = ""
clips: List[ClipStatusItem]
class EditPlanGenerateResponse(BaseModel):
"""剪辑计划触发生成响应体"""
plan_id: str
plan_status: str
generation_task_id: str
clip_count: int
class EditPlanGenerationsResponse(BaseModel):
"""剪辑计划关联的生成记录列表响应体"""
items: List[GenerationTaskResponse]
total: int
# ── AI 推荐 ────────────────────────────────────────────────────────────────
@@ -22,8 +67,12 @@ class AIRecommendRequest(BaseModel):
"""AI 推荐片段方案请求体"""
asset_ids: List[str] = Field(default_factory=list, description="素材 ID 列表")
editing_mode: str = Field(default="one_take", description="剪辑模式: one_take / pip / voice_over / voice_pip")
target_duration: float = Field(default=30.0, ge=1.0, le=600.0, description="目标时长(秒)")
editing_mode: str = Field(
default="one_take", description="剪辑模式: one_take / pip / voice_over / voice_pip"
)
target_duration: float = Field(
default=30.0, ge=1.0, le=600.0, description="目标时长(秒)"
)
class AIRecommendClipItem(BaseModel):
@@ -50,6 +99,8 @@ class AIRecommendResponse(BaseModel):
confidence: float = Field(..., ge=0.0, le=1.0, description="AI 推荐置信度 (0~1)")
# ── BGM ────────────────────────────────────────────────────────────────────
@@ -165,20 +216,10 @@ class ClipBatchDeleteResponse(BaseModel):
class ClipsFromAssetsRequest(BaseModel):
"""从素材批量创建片段请求"""
asset_ids: List[str] = Field(..., min_length=1, max_length=200, description="素材 ID 列表,按顺序追加到时间线末尾")
clip_type: str = Field(default="main", description="片段类型,默认 main")
required_clips_count: Optional[int] = Field(
default=None, ge=1, le=200, description="要求创建的片段数量;不传则等于素材数量"
asset_ids: List[str] = Field(
..., min_length=1, max_length=200, description="素材 ID 列表,按顺序追加到时间线末尾"
)
@validator("asset_ids", pre=True)
def _drop_invalid_asset_ids(cls, v): # noqa: N805
"""容错过滤:前端异常情况下可能把 undefined 序列化成 null 或空串混入
asset_ids(会直接 422 或导致后续 /assets/{id} 404),这里统一剔除。
过滤后为空时由 Field(min_length=1) / 路由层 400 兜底。"""
if not isinstance(v, list):
return v
return [x for x in v if isinstance(x, str) and x.strip()]
clip_type: str = Field(default="main", description="片段类型,默认 main")
class ClipsFromAssetsResponse(BaseModel):
@@ -186,11 +227,8 @@ class ClipsFromAssetsResponse(BaseModel):
success: bool = True
created_count: int
plan_id: str = ""
message: str = ""
clip_ids: List[str] = Field(default_factory=list, description="创建的片段ID列表")
duplicate_warning: Optional[str] = Field(default=None, description="查重率超标警告")
exhaustion_warning: Optional[str] = Field(default=None, description="素材耗尽警告")
# ── 封面配置 ────────────────────────────────────────────────────────────────
@@ -401,28 +439,17 @@ class EditorUpdateRequest(BaseModel):
class EditorClipResponse(BaseModel):
"""片段响应 — 与数据库 edit_plan_clips 表字段对齐"""
"""片段响应"""
id: str
plan_id: str
clip_type: str
order: int
duration: float
start_time: float = 0.0
text_content: str = ""
transition_effect: str = "cut"
transition_duration: float = 0.0
playback_speed: float = 1.0
asset_id: str = ""
asset_url: str | None = Field(
default=None,
description="素材视频签名URL(1小时有效),用于前端预览播放",
)
status: str = "pending"
template_clip_config_id: str = ""
config: dict[str, Any] = Field(default_factory=dict)
created_at: str = ""
updated_at: str = ""
class EditorClipListResponse(BaseModel):
@@ -454,28 +481,6 @@ class EditorClipUpdateRequest(BaseModel):
config: Optional[dict[str, Any]] = None
class EditorClipBatchItem(BaseModel):
"""批量更新clips的单个片段"""
asset_id: str = Field(default="", max_length=100, description="关联素材ID,可为空(占位片段)")
start_time: float = Field(default=0.0, ge=0.0)
duration: float = Field(default=0.0, ge=0.0)
order: Optional[int] = Field(default=None, ge=0, description="排序,None表示按数组顺序")
class EditorClipBatchUpdateRequest(BaseModel):
"""批量替换clips请求(全量覆盖)"""
clips: List[EditorClipBatchItem] = Field(default_factory=list)
class EditorClipBatchUpdateResponse(BaseModel):
"""批量更新clips响应"""
plan_id: str
clip_count: int
class EditorPublishResponse(BaseModel):
"""发布草稿响应"""
+57 -278
View File
@@ -2,44 +2,36 @@
from __future__ import annotations
import json
import logging
import subprocess
import tempfile
from pathlib import Path
from typing import Any, Optional
from typing import Optional
from app.auth import AuthenticatedUser, get_current_user
from app.core.celery_app import celery_app
from app.core.storage import get_storage_service
from app.dependencies import (
get_asset_library_repository,
get_asset_repository,
get_audio_url_signer,
get_cosyvoice_service,
get_db_session,
get_project_repository,
get_user_repository,
get_voice_clone_profile_repository,
get_voice_library_repository,
)
from app.schemas.tts import (
ListTTSJobResponse,
SaveToLibraryRequest,
SaveToLibraryResponse,
TTSJobResponse,
TTSPreviewRequest,
TTSPreviewResponse,
TTSStatusResponse,
TTSSynthesizeRequest,
TTSSynthesizeResponse,
)
from fastapi import APIRouter, Depends, HTTPException, Query, Response, WebSocket, WebSocketDisconnect, status
from sqlalchemy.exc import IntegrityError
from sqlalchemy.orm import Session
from packages.adapters.sqlalchemy_impl.tts_job_repository import (
SQLAlchemyTTSJobRepository,
)
from packages.application.cosyvoice_service import CosyVoiceError, CosyVoiceService
from packages.adapters.sqlalchemy_impl.voice_library_repository import SQLAlchemyVoiceLibraryRepository
from packages.application.cosyvoice_service import CosyVoiceService
from packages.application.tts_job.streaming_service import TTSStreamingService
from packages.application.tts_job.use_cases import (
CreateTTSJobUseCase,
@@ -50,12 +42,13 @@ from packages.application.tts_job.use_cases import (
TTSJobNotFoundError,
)
from packages.application.tts_job.workflow import TTSWorkflowService
from packages.domain import Asset, AssetLibrary, AssetLibraryKind, AssetStatus, ClassificationStatus
from packages.application.voice_library.commands import CreateVoiceLibraryCommand
from packages.application.voice_library.use_cases import (
CreateVoiceLibraryUseCase,
QuotaExceededError,
)
from packages.domain.voice_presets import list_voices
from packages.ports.asset_library_repository import AssetLibraryRepository
from packages.ports.asset_repository import AssetRepository
from packages.ports.project_repository import ProjectRepository
from packages.shared.storage import SharedStorageService
from packages.ports.user_repository import UserRepository
logger = logging.getLogger(__name__)
@@ -139,56 +132,28 @@ def synthesize(
"""
user_id = authenticated_user.user.id
# 解析 voice_id:前端可能传克隆音色 profile UUID(而非 CosyVoice voice_id),
# 与 /tts/preview 保持一致:命中 profile → 校验归属 → 取 CosyVoice voice_id
actual_voice_id = request.voice_id
voice_clone_profile_id = request.voice_clone_profile_id
resolved_profile = None
if actual_voice_id:
resolved_profile = voice_clone_repo.get(actual_voice_id)
if resolved_profile is not None:
voice_clone_profile_id = actual_voice_id
# 显式传了 voice_clone_profile_id(且与 voice_id 不同)时再查一次归属
if voice_clone_profile_id and (resolved_profile is None or resolved_profile.id != voice_clone_profile_id):
resolved_profile = voice_clone_repo.get(voice_clone_profile_id)
if resolved_profile is None:
# 校验 voice_clone_profile_id 归属(防止越权使用他人克隆音色)
if request.voice_clone_profile_id:
profile = voice_clone_repo.get(request.voice_clone_profile_id)
if profile is None:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Voice clone profile not found",
)
if resolved_profile is not None:
if resolved_profile.user_id != user_id:
if profile.user_id != user_id:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail="无权访问该音色",
detail="Access denied to voice clone profile",
)
if not resolved_profile.voice_id:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="音色克隆尚未完成,请稍后再试",
)
# 命中克隆音色:无论 voice_id 直接传 profile UUID 还是显式传 voice_clone_profile_id
# job.voice_id 统一存解析后的 CosyVoice voice_id
actual_voice_id = resolved_profile.voice_id
# 语速/情绪等合成参数随 metadata 落库,workflow 提交 CosyVoice 时读取透传
synthesis_meta = {
"speed": request.speed,
"emotion": request.emotion or "",
}
if request.metadata_:
synthesis_meta.update(request.metadata_)
use_case = CreateTTSJobUseCase(repository)
job = use_case.execute(
user_id=user_id,
input_text=request.text,
voice_id=actual_voice_id,
voice_id=request.voice_id,
voice_model=request.voice_model,
voice_clone_profile_id=voice_clone_profile_id,
metadata=synthesis_meta,
voice_clone_profile_id=request.voice_clone_profile_id,
metadata=request.metadata_,
)
# 提交 CosyVoice 合成任务
@@ -317,62 +282,6 @@ def delete_tts_job(
return
def _find_or_create_voice_library(
*,
user_id: str,
project_repository: ProjectRepository,
asset_library_repository: Any, # port Protocol 声明为 asyncSQLAlchemy 实现为同步,与 upload/asset_libraries 路由惯例一致用 Any
) -> AssetLibrary:
"""在用户可访问的项目中找到(或自动创建)voice 素材库。
与前端配音素材页逻辑一致:素材库挂在项目下,配音素材读取
getAssetsByKind("voice") → 用户所有可访问项目中的 voice 库。
优先使用已有 voice 库;没有则在第一个可访问项目中自动创建。
"""
projects = project_repository.find_accessible_projects(user_id)
if not projects:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="没有可用的项目,请先创建项目后再保存配音素材",
)
for project in projects:
for lib in asset_library_repository.find_by_project(project.id):
kind = lib.kind.value if hasattr(lib.kind, "value") else lib.kind
if kind == AssetLibraryKind.VOICE.value:
return lib
# 所有项目都没有 voice 库 → 在第一个可访问项目中自动创建默认配音素材库。
# asset_libraries 有 (project_id, kind) 唯一索引兜底并发:若两个请求同时创建,
# 落败方捕获 IntegrityError 回滚后重新查询,返回抢先创建成功的库。
project = projects[0]
library = AssetLibrary.create(
project_id=project.id,
name="配音素材库",
kind=AssetLibraryKind.VOICE,
)
try:
return asset_library_repository.create(library)
except IntegrityError:
# 并发下另一个请求已抢先创建:回滚当前事务(立即 commit 模式下 session 已
# 自动回滚,rollback 为幂等 no-opUoW/flush 模式下必须显式回滚才能继续查询),
# 再重查返回抢先创建成功的库。
session = getattr(asset_library_repository, "session", None)
if session is not None:
try:
session.rollback()
except Exception:
logger.warning("IntegrityError 后回滚 session 失败(可能已关闭)", exc_info=True)
for lib in asset_library_repository.find_by_project(project.id):
kind = lib.kind.value if hasattr(lib.kind, "value") else lib.kind
if kind == AssetLibraryKind.VOICE.value:
return lib
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail="配音素材库创建失败,请重试",
) from None # IntegrityError 已处理,不保留异常链
@router.post(
"/jobs/{job_id}/save-to-library",
response_model=SaveToLibraryResponse,
@@ -383,17 +292,13 @@ def save_tts_job_to_library(
request: SaveToLibraryRequest = SaveToLibraryRequest(),
authenticated_user: AuthenticatedUser = Depends(get_current_user),
tts_repository: SQLAlchemyTTSJobRepository = Depends(_get_repository),
asset_repository: AssetRepository = Depends(get_asset_repository),
asset_library_repository: AssetLibraryRepository = Depends(get_asset_library_repository),
project_repository: ProjectRepository = Depends(get_project_repository),
storage_service: SharedStorageService = Depends(get_storage_service),
voice_library_repository: SQLAlchemyVoiceLibraryRepository = Depends(get_voice_library_repository),
user_repository: UserRepository = Depends(get_user_repository),
sign_url=Depends(get_audio_url_signer),
) -> SaveToLibraryResponse:
"""将已完成的 TTS 合成结果保存到配音素材库(assets 表新素材体系)
"""将已完成的 TTS 合成结果保存到配音
流程:把 TTS 输出音频转存到用户素材 OSS 路径 → 创建 file_type=audio、
status=ready 的 asset(挂用户 voice 素材库)→ 返回前端可用结构。
配额策略与素材上传一致(上传/ingest 链路无额外配额拦截)。
自动携带音色名、时长、语速等元信息。
"""
user_id = authenticated_user.user.id
@@ -411,186 +316,60 @@ def save_tts_job_to_library(
detail="TTS job is not completed yet",
)
if not job.output_audio_url and not job.output_audio_key:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="TTS job 缺少输出音频,无法保存",
)
# 素材名称
# 构建配音素材名称
name = request.name or f"TTS-{job.id[:8]}"
# 找到(或自动创建)用户 voice 素材库
library = _find_or_create_voice_library(
user_id=user_id,
project_repository=project_repository,
asset_library_repository=asset_library_repository,
)
# 转存音频到素材 OSS 路径(tts-outputs/ 下的产物归 TTS 任务所有,
# 素材独立持有副本,删除 TTS 任务不影响配音库素材)
audio_format = (job.format or "mp3").strip() or "mp3"
content_type_map = {
"mp3": "audio/mpeg",
"wav": "audio/wav",
"pcm": "audio/pcm",
"opus": "audio/opus",
}
content_type = content_type_map.get(audio_format, "audio/mpeg")
storage_key = f"uploads/voice/tts/{job.id}.{audio_format}"
tmp_path: Path | None = None
audio_duration: float | None = None
file_size = 0
try:
with tempfile.NamedTemporaryFile(suffix=f".{audio_format}", delete=False) as tmp:
tmp_path = Path(tmp.name)
# 优先用 OSS storage_key(走 oss2 SDK,私有 bucket 也可下载);
# 兜底用 output_audio_url(旧任务可能没有 key)。
# download_asset 自动识别输入:http(s):// 开头走 HTTP 下载,否则按 OSS key 走 SDK。
download_source = job.output_audio_key or job.output_audio_url
downloaded = storage_service.download_asset(download_source, tmp_path)
if not downloaded or not tmp_path.exists() or tmp_path.stat().st_size == 0:
raise HTTPException(
status_code=status.HTTP_502_BAD_GATEWAY,
detail="TTS 音频下载失败,无法保存到配音库",
)
file_size = tmp_path.stat().st_size
storage_service.upload_file(tmp_path, storage_key, content_type=content_type)
# 从音频文件提取时长(ffprobe),作为 job.duration 的兜底
try:
proc = subprocess.run(
[
"ffprobe", "-v", "quiet", "-print_format", "json",
"-show_format", str(tmp_path),
],
capture_output=True, text=True, timeout=10,
)
if proc.returncode == 0:
fmt = json.loads(proc.stdout).get("format", {})
dur = float(fmt.get("duration", 0))
if dur > 0:
audio_duration = dur
except Exception:
logger.warning("ffprobe 提取时长失败: job_id=%s", job.id, exc_info=True)
except HTTPException:
raise
except Exception as e:
logger.error("TTS 音频转存素材失败: job_id=%s, error=%s", job.id, e, exc_info=True)
raise HTTPException(
status_code=status.HTTP_502_BAD_GATEWAY,
detail="TTS 音频转存失败,无法保存到配音库",
) from e
finally:
if tmp_path and tmp_path.exists():
try:
tmp_path.unlink()
except OSError:
pass
# 构建素材元信息
metadata_: dict[str, object] = {
# 构建元信息
metadata_ = {
"source": "tts_job",
"tts_job_id": job.id,
"format": job.format,
"sample_rate": job.sample_rate,
"voice_id": job.voice_id,
"voice_name": job.voice_model or "",
}
if job.metadata:
# 保留原始 job 的有用元信息
for key in ("speed", "language"):
if key in job.metadata:
metadata_[key] = job.metadata[key]
asset = Asset.create(
project_id=library.project_id,
library_id=library.id,
name=name,
storage_key=storage_key,
mime_type=content_type,
metadata=metadata_,
file_size=file_size,
duration=job.duration or audio_duration or None,
status=AssetStatus.READY,
classification_status=ClassificationStatus.PENDING, # 音频不参与内容分类,保持 pending 与 ingest 链路一致
uploaded_by_user_id=user_id,
)
try:
asset = asset_repository.create(asset)
except Exception as e:
# DB 写入失败:清理已上传到 OSS 的素材文件,避免产生无法索引的孤儿文件
logger.error("素材记录创建失败,清理 OSS 文件: %s, error=%s", storage_key, e, exc_info=True)
try:
storage_service.delete_file(storage_key)
except Exception:
logger.warning("清理孤儿 OSS 文件失败: %s", storage_key, exc_info=True)
raise HTTPException(
status_code=status.HTTP_502_BAD_GATEWAY,
detail="素材保存失败,请重试",
) from e
# 获取用户套餐(用于配额检查)
user = user_repository.find_by_id(user_id)
plan_name = getattr(user, "subscription_plan", "free") if user else "free"
return SaveToLibraryResponse(
id=asset.id,
name=asset.name,
audio_url=sign_url(storage_key),
duration=asset.duration or 0.0,
# 构建命令并执行
command = CreateVoiceLibraryCommand(
user_id=user_id,
name=name,
text=job.input_text,
voice_provider="cosyvoice",
voice_id=job.voice_id,
voice_name=job.voice_model or "",
audio_url=job.output_audio_url,
duration=job.duration,
file_size=job.file_size,
status="completed",
project_id=job.project_id or "",
tags=[],
metadata_=metadata_,
)
@router.post("/preview", response_model=TTSPreviewResponse)
def preview_tts(
request: TTSPreviewRequest,
authenticated_user: AuthenticatedUser = Depends(get_current_user),
cosyvoice_service: CosyVoiceService = Depends(get_cosyvoice_service),
voice_clone_repo=Depends(get_voice_clone_profile_repository),
) -> TTSPreviewResponse:
"""TTS 预览(试听)——同步合成,立即返回音频 URL。
用于前端预览配音效果,限制文本长度 200 字以内。
支持预设音色和克隆音色:克隆音色传的是 profile UUID,需解析为 CosyVoice voice_id。
"""
# 解析 voice_id:前端可能传 VoiceCloneProfile UUID 或预设音色 ID
actual_voice_id = request.voice_id
profile = voice_clone_repo.get(request.voice_id)
if profile is not None:
# 命中克隆音色 profile — 校验归属权限
if profile.user_id != authenticated_user.user.id:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail="无权访问该音色",
)
if not profile.voice_id:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="音色克隆尚未完成,请稍后再试",
)
actual_voice_id = profile.voice_id
use_case = CreateVoiceLibraryUseCase(voice_library_repository)
try:
result = cosyvoice_service.synthesize_speech(
text=request.text,
voice_id=actual_voice_id,
speed=request.speed,
emotion=request.emotion,
)
except CosyVoiceError as e:
item = use_case.execute(command, plan_name=plan_name or "free")
except QuotaExceededError as exc:
raise HTTPException(
status_code=status.HTTP_502_BAD_GATEWAY,
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
status_code=status.HTTP_429_TOO_MANY_REQUESTS,
detail=f"配音库配额已满({exc.used}/{exc.limit}),请升级套餐",
) from exc
return TTSPreviewResponse(
audio_url=result.audio_url,
duration=result.duration if result.duration and result.duration > 0 else None,
return SaveToLibraryResponse(
id=item.id,
name=item.name,
audio_url=sign_url(item.audio_url) if item.audio_url else "",
duration=item.duration,
voice_id=item.voice_id,
voice_name=item.voice_name,
status=item.status,
)
+48 -341
View File
@@ -23,7 +23,6 @@ from app.schemas.upload import (
from fastapi import APIRouter, Depends, File, Form, HTTPException, UploadFile, status
from packages.application import SubmitIngestJobCommand, SubmitIngestJobUseCase
from packages.domain import Asset, AssetStatus
logger = logging.getLogger(__name__)
@@ -81,199 +80,12 @@ def _validate_mime_type(content_type: str | None) -> str:
return base_type
def _infer_mime_type_from_storage_key(storage_key: str) -> str:
"""从 storage_key 推断 MIME 类型(与 worker 端保持一致)。"""
lower_filename = storage_key.rsplit("/", 1)[-1].lower()
_MIME_MAP = {
".mov": "video/quicktime",
".mp4": "video/mp4",
".avi": "video/x-msvideo",
".mkv": "video/x-matroska",
".webm": "video/webm",
".png": "image/png",
".gif": "image/gif",
".bmp": "image/bmp",
".svg": "image/svg+xml",
".jpg": "image/jpeg",
".jpeg": "image/jpeg",
".mp3": "audio/mpeg",
".wav": "audio/wav",
".ogg": "audio/ogg",
".flac": "audio/flac",
".m4a": "audio/x-m4a",
}
for ext, mime in _MIME_MAP.items():
if lower_filename.endswith(ext):
return mime
return "video/mp4" # default
# 兜底去重:无 file_hash / client_upload_id 且大小已知时,同库同名同大小近期活动记录视为重复
FALLBACK_DEDUP_WINDOW_MINUTES = 30
def _find_duplicate_asset(
asset_repository: Any,
*,
library_id: str,
file_hash: str,
client_upload_id: str,
filename: str,
file_size: int = 0,
) -> Any:
"""complete/上传幂等去重,按优先级查找已存在的素材。
1. client_upload_id(客户端幂等 token,同一次上传的重试保持一致)
2. file_hash(内容哈希,不同上传只要内容相同即去重)
3. 兜底(严格模式,宁可漏判不可误杀):file_hash 与 client_upload_id
均缺失、且 file_size > 0 时,同库 + 同文件名 + **同大小** 且 30 分钟内
仍处 uploading/processing 的记录才判重。
- file_hash 非空时跳过兜底(hash 已代表内容;同名但内容全新的视频
如 iPhone 的 IMG_xxxx.MOV 绝不能被同名占位误杀)
- file_size=0(未知)时不允许仅凭同名 + processing 判重,直接放行
全部为鸭子类型调用:旧仓储无对应方法时静默跳过,不破坏既有实现。
"""
if client_upload_id:
find = getattr(asset_repository, "find_by_library_and_client_upload_id", None)
if callable(find):
existing = find(library_id=library_id, client_upload_id=client_upload_id)
if existing is not None:
logger.info(
"素材幂等命中(client_upload_id): library=%s token=%s asset=%s",
library_id,
client_upload_id,
getattr(existing, "id", "?"),
)
return existing
if file_hash:
existing = asset_repository.find_by_library_and_file_hash(
library_id=library_id,
file_hash=file_hash,
)
if existing is not None:
logger.info(
"素材去重命中(file_hash): library=%s hash=%s asset=%s",
library_id,
file_hash,
existing.id,
)
return existing
# 同名兜底去重(最后防线,严格模式):
# - 仅当 file_hash / client_upload_id 均缺失时启用(hash 能代表内容时不靠同名猜)
# - file_size 必须 > 0 且与记录大小严格一致;大小未知(0)直接放行
# - 只命中近期 UPLOADING/PROCESSING 活动记录(READY 历史素材不拦)
if filename and not file_hash and not client_upload_id and file_size and file_size > 0:
find_recent = getattr(asset_repository, "find_recent_active_by_library_and_name", None)
if callable(find_recent):
existing = find_recent(
library_id=library_id,
name=filename,
within_minutes=FALLBACK_DEDUP_WINDOW_MINUTES,
file_size=file_size,
)
if existing is not None:
logger.info(
"素材幂等兜底命中(近期同名同大小活动记录): library=%s name=%s asset=%s status=%s size=%s",
library_id,
filename,
getattr(existing, "id", "?"),
getattr(existing, "status", None),
file_size,
)
return existing
elif filename and not file_hash and not client_upload_id and not file_size:
logger.debug(
"同名兜底去重跳过(file_size 未知,宁可放行不可误杀): library=%s name=%s",
library_id,
filename,
)
return None
def _create_pending_asset(
asset_repository,
project_id,
library_id,
storage_key,
filename,
mime_type,
user_id,
file_hash="",
client_upload_id="",
file_size: int = 0,
):
"""立即创建或复用一条 PROCESSING 状态的 Asset 记录。
find-or-createprepare 阶段已按 file_hash/client_upload_id 预建的占位记录
会被 find_by_library_and_file_hash/find_by_library_and_client_upload_id 命中,
直接复用并补齐字段(避免 pre-create + complete 重复建两条)。
Issue #1776: 素材库计数由 asset_repository.create() 自动维护。
"""
# 1. 按 client_upload_id / file_hash 查找现有记录
existing = None
if client_upload_id:
find_by_cuid = getattr(asset_repository, "find_by_library_and_client_upload_id", None)
if callable(find_by_cuid):
existing = find_by_cuid(library_id=library_id, client_upload_id=client_upload_id)
if existing is None and file_hash:
existing = asset_repository.find_by_library_and_file_hash(library_id=library_id, file_hash=file_hash)
if existing is not None:
# 补齐字段(幂等:避免重复建记录,前端已拿到 asset_id)
changed = False
if file_hash and not existing.file_hash:
existing.file_hash = file_hash
changed = True
if client_upload_id and not existing.client_upload_id:
existing.client_upload_id = client_upload_id
changed = True
if file_size and not existing.file_size:
existing.file_size = file_size
changed = True
if existing.status not in (AssetStatus.PROCESSING, AssetStatus.UPLOADING):
existing.status = AssetStatus.PROCESSING
changed = True
if changed:
try:
asset_repository.update(existing)
except Exception: # noqa: BLE001 — 字段补齐失败不阻塞主流程
pass
return existing
asset = Asset.create(
project_id=project_id,
library_id=library_id,
name=filename,
storage_key=storage_key,
mime_type=mime_type,
status=AssetStatus.PROCESSING,
uploaded_by_user_id=user_id,
file_hash=file_hash,
client_upload_id=client_upload_id,
file_size=file_size,
)
return asset_repository.create(asset)
def _persist_celery_task_id(repo: Any, job: Any, celery_task_id: str) -> None:
"""记录 celery 消息 ID 到任务行,供孤儿清理时 revoke/清除队列消息(#1714)。"""
if not celery_task_id:
return
try:
job.celery_task_id = celery_task_id
repo.update(job)
except Exception: # noqa: BLE001 — 记录失败不影响主流程(执行前状态守卫兜底)
pass
def _submit_ingest_job(
project_id: str,
library_id: str,
storage_key: str,
ingest_job_repository: Any,
file_hash: str = "",
asset_id: str = "",
) -> Any:
use_case = SubmitIngestJobUseCase(ingest_job_repository)
job = use_case.execute(
@@ -282,11 +94,9 @@ def _submit_ingest_job(
library_id=library_id,
storage_key=storage_key,
file_hash=file_hash,
asset_id=asset_id,
)
)
celery_result = celery_app.send_task("worker.ingest_asset", args=[job.id])
_persist_celery_task_id(ingest_job_repository, job, getattr(celery_result, "id", ""))
celery_app.send_task("worker.ingest_asset", args=[job.id])
return job
@@ -296,15 +106,9 @@ async def prepare_direct_upload(
authenticated_user: AuthenticatedUser = Depends(get_current_user),
project_repository: Any = Depends(get_project_repository),
asset_library_repository: Any = Depends(get_asset_library_repository),
asset_repository: Any = Depends(get_asset_repository),
storage_service: OSSStorageService = Depends(get_storage_service),
) -> DirectUploadPrepareResponse:
"""创建浏览器直传 OSS 的短期表单签名,并在签名前按 file_hash/client_upload_id 去重。
命中去重:直接返回 duplicated=True + skip_transfer=True(前端跳过 OSS 直传),
未命中:正常签名 OSS 并立即预建一条 PROCESSING 状态的 asset 记录占住
file_hash 闸门,响应带 asset_id 供前端/后续 complete 关联。
"""
"""创建浏览器直传 OSS 的短期表单签名"""
settings = get_settings()
max_size_bytes = settings.OSS_DIRECT_UPLOAD_MAX_MB * 1024 * 1024
if request.file_size > max_size_bytes:
@@ -323,39 +127,8 @@ async def prepare_direct_upload(
asset_library_repository,
)
safe_filename = request.filename.replace("/", "_").replace("\\", "_")
# ── prepare 阶段去重:OSS 签名之前先查已存在素材 ──
if request.file_hash or request.client_upload_id:
existing = _find_duplicate_asset(
asset_repository,
library_id=request.library_id,
file_hash=request.file_hash,
client_upload_id=request.client_upload_id,
filename=request.filename,
file_size=request.file_size,
)
if existing is not None:
logger.info(
"prepare 命中去重: library=%s hash=%s cuid=%s existing_asset=%s",
request.library_id,
request.file_hash,
request.client_upload_id,
existing.id,
)
return DirectUploadPrepareResponse(
upload_url="",
method="",
storage_key=existing.storage_key,
expires_at="",
fields={},
max_size_bytes=0,
duplicated=True,
skip_transfer=True,
asset_id=existing.id,
)
file_id = uuid4().hex[:8]
safe_filename = request.filename.replace("/", "_").replace("\\", "_")
storage_key = f"uploads/{file_id}/{safe_filename}"
try:
payload = storage_service.create_direct_upload_post(
@@ -374,28 +147,6 @@ async def prepare_direct_upload(
detail=f"Failed to prepare upload: {type(error).__name__}",
) from error
# ── 预建 asset 占位:占住 file_hash/client_upload_id 闸门,避免并发重复上传 ──
pending_asset_id = ""
if request.file_hash or request.client_upload_id:
try:
pending = _create_pending_asset(
asset_repository=asset_repository,
project_id=request.project_id,
library_id=request.library_id,
storage_key=storage_key,
filename=safe_filename,
mime_type=validated_content_type,
user_id=authenticated_user.user.id,
file_hash=request.file_hash,
client_upload_id=request.client_upload_id,
file_size=request.file_size,
)
pending_asset_id = pending.id
# Issue #1776: 计数由 asset_repository.create() 自动维护
except Exception as error:
# 预建失败不阻塞签名:complete 仍可按 OSS 文件 + hash 兜底去重
logger.warning("预建 asset 占位失败,降级走 old flow: %s", error)
return DirectUploadPrepareResponse(
upload_url=str(payload["url"]),
method=str(payload["method"]),
@@ -403,9 +154,6 @@ async def prepare_direct_upload(
expires_at=str(payload["expires_at"]),
fields={str(key): str(value) for key, value in dict(payload["fields"]).items()},
max_size_bytes=max_size_bytes,
duplicated=False,
skip_transfer=False,
asset_id=pending_asset_id,
)
@@ -419,7 +167,7 @@ async def complete_direct_upload(
asset_repository: Any = Depends(get_asset_repository),
storage_service: OSSStorageService = Depends(get_storage_service),
) -> DirectUploadCompleteResponse:
"""确认浏览器直传完成并创建导入任务(幂等:重复 complete 返回同一素材)"""
"""确认浏览器直传完成并创建导入任务。"""
require_project_and_library(
request.project_id,
request.library_id,
@@ -429,29 +177,6 @@ async def complete_direct_upload(
normalized_key = storage_service._normalize_storage_key(request.storage_key)
if not normalized_key.startswith("uploads/"):
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid upload key")
filename = normalized_key.rsplit("/", 1)[-1]
# ── 幂等去重(放在 OSS 检查之前):complete 超时后前端重试时,
# 第一次 complete 可能已建好占位记录,此时即使 OSS 检查失败也必须返回
# 已存在记录,绝不能再建第二条。─
existing = _find_duplicate_asset(
asset_repository,
library_id=request.library_id,
file_hash=request.file_hash,
client_upload_id=request.client_upload_id,
filename=filename,
file_size=request.file_size,
)
if existing is not None:
return DirectUploadCompleteResponse(
storage_key=existing.storage_key,
ingest_job_id="",
duplicated=True,
asset_id=existing.id,
url=storage_service.get_url(existing.storage_key),
)
try:
file_exists = storage_service.file_exists(normalized_key)
except Exception as error:
@@ -463,21 +188,25 @@ async def complete_direct_upload(
if not file_exists:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Uploaded file not found")
# 立即创建 Asset 记录(PROCESSING 状态),使前端刷新后即可看到新素材
mime_type = _infer_mime_type_from_storage_key(normalized_key)
pending_asset = _create_pending_asset(
asset_repository=asset_repository,
project_id=request.project_id,
library_id=request.library_id,
storage_key=normalized_key,
filename=filename,
mime_type=mime_type,
user_id=authenticated_user.user.id,
file_hash=request.file_hash,
client_upload_id=request.client_upload_id,
file_size=request.file_size,
)
# Issue #1776: 计数由 asset_repository.create() 自动维护
# ── 素材去重检测:同素材库 + 同 file_hash 视为重复 ──
if request.file_hash:
existing = asset_repository.find_by_library_and_file_hash(
library_id=request.library_id,
file_hash=request.file_hash,
)
if existing is not None:
logger.info(
"素材去重命中: library=%s hash=%s existing_asset=%s",
request.library_id,
request.file_hash,
existing.id,
)
return DirectUploadCompleteResponse(
storage_key=normalized_key,
ingest_job_id="",
duplicated=True,
asset_id=existing.id,
)
job = _submit_ingest_job(
project_id=request.project_id,
@@ -485,14 +214,8 @@ async def complete_direct_upload(
storage_key=normalized_key,
ingest_job_repository=ingest_job_repository,
file_hash=request.file_hash,
asset_id=pending_asset.id,
)
return DirectUploadCompleteResponse(
storage_key=normalized_key,
ingest_job_id=job.id,
asset_id=pending_asset.id,
url=storage_service.get_url(normalized_key),
)
return DirectUploadCompleteResponse(storage_key=normalized_key, ingest_job_id=job.id)
@router.post(
@@ -505,8 +228,7 @@ async def upload_asset(
project_id: str = Form(..., min_length=1, description="项目 ID"),
library_id: str = Form(..., min_length=1, description="素材库 ID"),
file: UploadFile = File(..., description="要上传的文件(视频、音频、图片等)"),
file_hash: str = Form(default="", description="文件哈希,用于去重检测"),
client_upload_id: str = Form(default="", description="客户端幂等 token(同一次上传的重试保持一致)"),
file_hash: str = Form(default="", description="文件 MD5 哈希,用于去重检测"),
authenticated_user: AuthenticatedUser = Depends(get_current_user),
ingest_job_repository: Any = Depends(get_ingest_job_repository),
project_repository: Any = Depends(get_project_repository),
@@ -517,31 +239,32 @@ async def upload_asset(
"""上传素材文件并触发导入流水线。"""
require_project_and_library(project_id, library_id, project_repository, asset_library_repository)
# P2-5: 服务端验证 MIME 类型(先验证,再幂等去重,避免非法类型绕过)
# ── 素材去重检测:上传前检查同素材库 + 同 file_hash ──
if file_hash:
existing = asset_repository.find_by_library_and_file_hash(
library_id=library_id,
file_hash=file_hash,
)
if existing is not None:
logger.info(
"素材去重命中(multipart): library=%s hash=%s existing_asset=%s",
library_id,
file_hash,
existing.id,
)
return UploadAssetResponse(
storage_key=existing.storage_key,
ingest_job_id="",
url="",
duplicated=True,
asset_id=existing.id,
)
# P2-5: 服务端验证 MIME 类型
validated_content_type = _validate_mime_type(file.content_type)
safe_filename = file.filename.replace("/", "_").replace("\\", "_") if file.filename else "unknown"
# ── 幂等去重:client_upload_id → file_hash → 近期活动同名记录兜底 ──
# 放在 OSS 上传之前:重复提交直接返回,不占 OSS 流量、不建新记录。
existing = _find_duplicate_asset(
asset_repository,
library_id=library_id,
file_hash=file_hash,
client_upload_id=client_upload_id,
filename=safe_filename,
file_size=0,
)
if existing is not None:
return UploadAssetResponse(
storage_key=existing.storage_key,
ingest_job_id="",
url="",
duplicated=True,
asset_id=existing.id,
)
file_id = uuid4().hex[:8]
safe_filename = file.filename.replace("/", "_").replace("\\", "_") if file.filename else "unknown"
storage_key = f"uploads/{file_id}/{safe_filename}"
try:
@@ -560,32 +283,16 @@ async def upload_asset(
detail=f"Failed to upload file: {type(error).__name__}",
) from error
# 立即创建 Asset 记录(PROCESSING 状态),使前端刷新后即可看到新素材
pending_asset = _create_pending_asset(
asset_repository=asset_repository,
project_id=project_id,
library_id=library_id,
storage_key=storage_key,
filename=safe_filename,
mime_type=validated_content_type,
user_id=authenticated_user.user.id,
file_hash=file_hash,
client_upload_id=client_upload_id,
)
# Issue #1776: 计数由 asset_repository.create() 自动维护
job = _submit_ingest_job(
project_id=project_id,
library_id=library_id,
storage_key=storage_key,
ingest_job_repository=ingest_job_repository,
file_hash=file_hash,
asset_id=pending_asset.id,
)
return UploadAssetResponse(
storage_key=storage_key,
ingest_job_id=job.id,
asset_id=pending_asset.id,
url=file_url,
)
-75
View File
@@ -15,7 +15,6 @@ from app.schemas.video_center import (
VideoItemResponse,
)
from fastapi import APIRouter, Depends, HTTPException, Query, Response
from pydantic import BaseModel, Field
from packages.application import (
GetGeneratedVideoUseCase,
@@ -53,9 +52,6 @@ def _to_video_response(item, storage: OSSStorageService | None = None) -> VideoI
generation_params=item.generation_params,
download_url=download_url,
generated_at=format_utc_datetime(item.generated_at) if hasattr(item, "generated_at") else "",
duplicate_rate=getattr(item, "duplicate_rate", None),
visual_similarity=getattr(item, "visual_similarity", None),
match_count=getattr(item, "match_count", None),
)
@@ -240,74 +236,3 @@ def get_batch_download_status(
status=api_status,
download_url=download_url,
)
# ── 重新计算查重率 ─────────────────────────────────────────────────
class RecomputeDedupRequest(BaseModel):
"""重新计算查重率请求。"""
video_ids: list[str] | None = Field(
None,
description="指定视频 ID 列表。为空则对当前用户所有缺少查重数据的视频重新计算。",
)
force: bool = Field(
False,
description="强制重算:即使视频已有查重数据也重新入队(#1702 查重算法升级后用于存量视频重算)。",
)
class RecomputeDedupResponse(BaseModel):
"""重新计算查重率响应。"""
enqueued: int = Field(..., description="已入队的任务数量")
total_scanned: int = Field(..., description="扫描的视频总数")
skipped: int = Field(..., description="已有查重数据跳过的数量")
message: str = ""
@router.post("/videos/recompute-dedup", response_model=RecomputeDedupResponse)
def recompute_dedup(
request: RecomputeDedupRequest = RecomputeDedupRequest(),
repo=Depends(get_generated_video_repository),
current_user: AuthenticatedUser = Depends(get_current_user),
):
"""重新计算视频的查重率/视觉相似度。
对于已存在但缺少 duplicate_rate / video_fingerprint 的视频,
触发异步 Celery 任务重新下载并计算指纹 + 查重率。
不传 video_ids 时,对当前用户所有视频进行检查。
"""
user_id = current_user.user.id
# 获取目标视频列表
if request.video_ids:
all_videos = repo.get_by_ids(request.video_ids)
# 安全校验:只处理当前用户的视频
target_videos = [v for v in all_videos if v.user_id == user_id]
else:
target_videos = repo.list_by_user(user_id)
total_scanned = len(target_videos)
enqueued = 0
skipped = 0
for video in target_videos:
# 已有完整查重数据的跳过(force=True 时强制重算,#1702 算法升级后存量视频需要重算指纹/分片)
if not request.force and video.duplicate_rate is not None and video.video_fingerprint:
skipped += 1
continue
# 触发异步查重任务
celery_app.send_task("worker.check_duplicate", args=[video.id])
enqueued += 1
logger.info("Enqueued re-dedup for video %s (user=%s, force=%s)", video.id, user_id, request.force)
return RecomputeDedupResponse(
enqueued=enqueued,
total_scanned=total_scanned,
skipped=skipped,
message=f"已入队 {enqueued} 个查重任务" if enqueued > 0 else "所有视频查重数据已完整",
)
+10 -64
View File
@@ -7,13 +7,7 @@ from typing import Optional
from app.auth import AuthenticatedUser, get_current_user
from app.core.celery_app import celery_app
from app.core.storage import get_storage_service
from app.dependencies import (
get_asset_repository,
get_cosyvoice_service,
get_project_repository,
get_voice_clone_profile_repository,
)
from app.dependencies import get_cosyvoice_service, get_voice_clone_profile_repository
from app.schemas.voice_clone import (
CreateVoiceCloneRequest,
ListVoiceCloneResponse,
@@ -38,9 +32,6 @@ from packages.application.voice_clone.use_cases import (
from packages.application.voice_clone.workflow import (
VoiceCloneWorkflowService,
)
from packages.ports.asset_repository import AssetRepository
from packages.ports.project_repository import ProjectRepository
from packages.shared.storage import SharedStorageService
logger = logging.getLogger(__name__)
@@ -92,68 +83,23 @@ def create_voice_clone(
request: CreateVoiceCloneRequest,
authenticated_user: AuthenticatedUser = Depends(get_current_user),
workflow: VoiceCloneWorkflowService = Depends(_get_workflow_service),
asset_repository: AssetRepository = Depends(get_asset_repository),
project_repository: ProjectRepository = Depends(get_project_repository),
storage_service: SharedStorageService = Depends(get_storage_service),
) -> VoiceCloneProfileResponse:
"""创建音色克隆任务。
创建 VoiceCloneProfile → 提交 CosyVoice 克隆任务 → 触发 Celery 异步轮询。
参考音频两种来源(二选一):
- source_audio_url:前端直传后的音频 URL(兼容旧流程)
- asset_id:配音素材库中的音频素材,服务端用其 OSS storage_key 生成
预签名下载 URL(不依赖前端签名,避免签名过期导致克隆失败)
如果有参考音频,状态会变为 processing;否则保持 pending。
如果有 source_audio_url,状态会变为 processing;否则保持 pending。
"""
user_id = authenticated_user.user.id
source_audio_url = request.source_audio_url
clone_metadata = dict(request.metadata_ or {})
if request.asset_id:
if source_audio_url:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="asset_id 与 source_audio_url 只能传一个",
)
asset = asset_repository.find_by_id(request.asset_id)
if asset is None:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="素材不存在",
)
# 归属校验:素材挂在项目素材库下,用户必须能访问该项目
project = project_repository.find_by_id(asset.project_id)
if project is None or not project.can_access(user_id):
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail="无权使用该素材",
)
# 类型校验:仅支持音频素材
if asset.file_type != "audio":
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="仅支持音频素材进行音色克隆",
)
if not asset.storage_key:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="该素材缺少音频文件,无法用于克隆",
)
# 用 OSS storage_key 生成服务端预签名 URL(7 天有效,覆盖克隆重试周期)
source_audio_url = storage_service.get_download_url(asset.storage_key, expires_seconds=7 * 24 * 3600)
clone_metadata["source_asset_id"] = asset.id
profile = workflow.start_clone(
user_id=user_id,
name=request.name,
description=request.description,
source_audio_url=source_audio_url,
source_audio_url=request.source_audio_url,
voice_model=request.voice_model,
language=request.language,
gender=request.gender,
max_retries=request.max_retries,
metadata=clone_metadata,
metadata=request.metadata_,
)
# 如果 profile 处于 processing 且有 task_id,触发 Celery 异步轮询
@@ -163,12 +109,12 @@ def create_voice_clone(
celery_app.send_task("worker.process_voice_clone", args=[profile.id])
logger.info(f"Celery task dispatched for voice clone {profile.id}")
except Exception as e:
logger.exception("Failed to dispatch Celery task")
logger.error(f"Failed to dispatch Celery task: {e}")
# P2-3: Celery 调度失败时标记 profile 为 failed,避免永久卡在 processing
try:
workflow.process_clone_failure(profile.id, f"Celery 任务调度失败: {e}")
except Exception:
logger.exception("Failed to mark profile as failed after dispatch error")
except Exception as inner_e:
logger.error(f"Failed to mark profile as failed after dispatch error: {inner_e}")
return _to_response(profile)
@@ -277,12 +223,12 @@ def retry_voice_clone(
celery_app.send_task("worker.process_voice_clone", args=[profile.id])
logger.info(f"Celery task dispatched for voice clone retry {profile.id}")
except Exception as e:
logger.exception("Failed to dispatch Celery task")
logger.error(f"Failed to dispatch Celery task: {e}")
# P2-3: Celery 调度失败时标记 profile 为 failed,避免永久卡在 processing
try:
workflow.process_clone_failure(profile.id, f"Celery 任务调度失败: {e}")
except Exception:
logger.exception("Failed to mark profile as failed after dispatch error")
except Exception as inner_e:
logger.error(f"Failed to mark profile as failed after dispatch error: {inner_e}")
return _to_response(profile)
+4 -263
View File
@@ -6,26 +6,12 @@
from __future__ import annotations
import logging
import shutil
import subprocess
import tempfile
import time
from pathlib import Path
from typing import Literal, Optional
from uuid import uuid4
from app.api.routes._helpers import get_user_plan
from app.auth import AuthenticatedUser, get_current_user
from app.core.storage import get_storage_service
from app.dependencies import (
get_asset_library_repository,
get_asset_repository,
get_audio_url_signer,
get_cosyvoice_service,
get_db_session,
get_project_repository,
get_user_repository,
)
from app.dependencies import get_audio_url_signer, get_cosyvoice_service, get_db_session, get_user_repository
from app.schemas.voice import (
PresetVoiceItemResponse,
PresetVoiceListResponse,
@@ -38,7 +24,7 @@ from app.schemas.voice_library import (
UpdateVoiceLibraryRequest,
VoiceLibraryItemResponse,
)
from fastapi import APIRouter, Depends, File, Form, HTTPException, Query, Response, UploadFile, status
from fastapi import APIRouter, Depends, HTTPException, Query, Response, status
from sqlalchemy.orm import Session
from packages.adapters.sqlalchemy_impl.voice_clone_profile_repository import SQLAlchemyVoiceCloneProfileRepository
@@ -54,12 +40,8 @@ from packages.application.voice_library.use_cases import (
QuotaExceededError,
UpdateVoiceLibraryUseCase,
)
from packages.domain import Asset, AssetStatus
from packages.domain.classification import AssetLibraryKind, ClassificationStatus
from packages.domain.entities import AssetLibrary
from packages.domain.preset_voices import PRESET_VOICES, get_preset_voice_by_id
from packages.ports.user_repository import UserRepository
from packages.shared.storage import SharedStorageService
router = APIRouter()
logger = logging.getLogger(__name__)
@@ -105,8 +87,8 @@ def _resolve_preset_preview_url(
_preset_preview_cache[voice_id] = (audio_url, time.time())
logger.info("Preset voice preview generated: %s", voice_id)
return audio_url
except Exception:
logger.exception("Failed to generate preset voice preview: voice_id=%s", voice_id)
except Exception as e:
logger.warning("Failed to generate preview for %s, using fallback: %s", voice_id, e)
return fallback_url
@@ -127,7 +109,6 @@ def _resolve_all_preset_preview_urls(
try:
result_map[p.voice_id] = _resolve_preset_preview_url(p.voice_id, p.preview_url, cosyvoice)
except Exception:
logger.exception("Failed to resolve preset preview URL: voice_id=%s", p.voice_id)
result_map[p.voice_id] = p.preview_url
return result_map
@@ -526,243 +507,3 @@ def delete_voice(
if not deleted:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Voice not found")
return
# ── 提取视频配音 ─────────────────────────────────────────────────────
# 支持的视频格式
EXTRACT_VIDEO_MIMES = frozenset({"video/mp4", "video/quicktime", "video/webm", "video/x-msvideo"})
MAX_EXTRACT_SIZE = 500 * 1024 * 1024 # 500MB
@router.post(
"/extract-voice",
status_code=status.HTTP_201_CREATED,
)
def extract_voice_from_video(
file: UploadFile = File(...),
project_id: str = Form(...),
authenticated_user: AuthenticatedUser = Depends(get_current_user),
project_repository=Depends(get_project_repository),
asset_library_repository=Depends(get_asset_library_repository),
asset_repository=Depends(get_asset_repository),
storage_service: SharedStorageService = Depends(get_storage_service),
sign_url=Depends(get_audio_url_signer),
):
"""从上传的视频中提取人声配音。
流程:
1. 接收视频文件(mp4/mov/webm
2. ffmpeg 提取音频 + 降噪 + 编码为 mp3
3. 上传到 OSS,创建 Asset 记录到配音素材库
4. 返回素材信息(时长、文件大小、URL)
"""
user_id = authenticated_user.user.id
# 校验文件类型
content_type = file.content_type or ""
if content_type and content_type not in EXTRACT_VIDEO_MIMES:
# 兜底:按扩展名判断
ext = (file.filename or "").rsplit(".", 1)[-1].lower()
ext_to_mime = {"mp4": "video/mp4", "mov": "video/quicktime", "webm": "video/webm", "avi": "video/x-msvideo"}
if ext not in ext_to_mime:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="仅支持 mp4/mov/webm/avi 格式的视频文件",
)
content_type = ext_to_mime[ext]
# 找到(或自动创建)用户 voice 素材库(复用 TTS 的逻辑)
library = _find_or_create_voice_library_for_extract(
user_id=user_id,
project_repository=project_repository,
asset_library_repository=asset_library_repository,
)
tmp_dir = None
try:
tmp_dir = Path(tempfile.mkdtemp(prefix="voice_extract_"))
video_path = tmp_dir / f"input_{uuid4().hex[:8]}_{file.filename or 'video.mp4'}"
audio_path = tmp_dir / f"output_{uuid4().hex[:8]}.mp3"
# 保存上传的视频到临时文件
with open(video_path, "wb") as f:
total = 0
while chunk := file.file.read(1024 * 1024): # 1MB chunks
total += len(chunk)
if total > MAX_EXTRACT_SIZE:
raise HTTPException(
status_code=status.HTTP_413_REQUEST_ENTITY_TOO_LARGE,
detail="视频文件过大,最大支持 500MB",
)
f.write(chunk)
if video_path.stat().st_size == 0:
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="视频文件为空")
# ffmpeg: 提取音频 + 降噪 + 编码 mp3
# 滤镜链:highpass(去低频噪声) → afftdn(FFT降噪) → lowpass(去高频噪声)
ffmpeg_cmd = [
"ffmpeg",
"-y",
"-i",
str(video_path),
"-vn", # 不要视频
"-af",
"highpass=f=80,afftdn=nf=-25:tn=1,lowpass=f=8000",
"-acodec",
"libmp3lame",
"-ab",
"192k",
"-ar",
"44100",
"-ac",
"1", # 单声道(人声足够)
str(audio_path),
]
result = subprocess.run(
ffmpeg_cmd,
capture_output=True,
timeout=300, # 5 分钟超时
)
if result.returncode != 0:
stderr_text = result.stderr.decode("utf-8", errors="replace")[-500:]
logger.error("ffmpeg 提取配音失败: %s", stderr_text)
raise HTTPException(
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
detail="视频音频提取失败,可能该视频没有音轨或格式不支持",
)
if not audio_path.exists() or audio_path.stat().st_size == 0:
raise HTTPException(
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
detail="音频提取结果为空",
)
# 获取音频时长
duration = _get_audio_duration(audio_path)
file_size = audio_path.stat().st_size
# 上传到 OSS
audio_ext = "mp3"
storage_key = f"uploads/voice/extracted/{uuid4().hex}.{audio_ext}"
storage_service.upload_file(audio_path, storage_key, content_type="audio/mpeg")
# 创建 Asset 记录
original_name = (file.filename or "video").rsplit(".", 1)[0]
asset_name = f"{original_name}-配音"
asset = Asset.create(
project_id=library.project_id,
library_id=library.id,
name=asset_name,
storage_key=storage_key,
mime_type="audio/mpeg",
metadata={
"source": "video_extract",
"original_video": file.filename or "unknown",
},
file_size=file_size,
duration=duration,
status=AssetStatus.READY,
classification_status=ClassificationStatus.PENDING,
uploaded_by_user_id=user_id,
)
asset = asset_repository.create(asset)
return {
"id": asset.id,
"name": asset.name,
"audio_url": sign_url(storage_key),
"duration": duration,
"file_size": file_size,
"status": "completed",
"source": "video_extract",
}
except HTTPException:
raise
except subprocess.TimeoutExpired:
raise HTTPException(
status_code=status.HTTP_504_GATEWAY_TIMEOUT,
detail="视频处理超时,请尝试较短的视频",
) from None
except Exception as e:
logger.exception("提取视频配音失败: %s", e)
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail="提取配音失败,请稍后重试",
) from e
finally:
# 清理临时文件
if tmp_dir and Path(tmp_dir).exists():
shutil.rmtree(tmp_dir, ignore_errors=True)
def _find_or_create_voice_library_for_extract(*, user_id, project_repository, asset_library_repository):
"""为用户找到或创建 voice 素材库(与 TTS 保存逻辑一致)。"""
projects = project_repository.find_accessible_projects(user_id)
if not projects:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="没有可用的项目,请先创建项目",
)
for project in projects:
for lib in asset_library_repository.find_by_project(project.id):
kind = lib.kind.value if hasattr(lib.kind, "value") else lib.kind
if kind == AssetLibraryKind.VOICE.value:
return lib
# 自动创建
from sqlalchemy.exc import IntegrityError
project = projects[0]
library = AssetLibrary.create(
project_id=project.id,
name="配音素材库",
kind=AssetLibraryKind.VOICE,
)
try:
return asset_library_repository.create(library)
except IntegrityError:
session = getattr(asset_library_repository, "session", None)
if session is not None:
try:
session.rollback()
except Exception:
logger.exception("session rollback failed in _find_or_create_voice_library")
for lib in asset_library_repository.find_by_project(project.id):
kind = lib.kind.value if hasattr(lib.kind, "value") else lib.kind
if kind == AssetLibraryKind.VOICE.value:
return lib
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail="配音素材库创建失败",
) from None
def _get_audio_duration(audio_path: Path) -> float:
"""用 ffprobe 获取音频时长(秒)。"""
try:
result = subprocess.run(
[
"ffprobe",
"-v",
"quiet",
"-show_entries",
"format=duration",
"-of",
"csv=p=0",
str(audio_path),
],
capture_output=True,
timeout=10,
)
if result.returncode == 0 and result.stdout.strip():
return float(result.stdout.strip())
except (ValueError, subprocess.TimeoutExpired):
pass
return 0.0
View File
-8
View File
@@ -5,11 +5,3 @@ settings = get_settings()
celery_app = Celery("xiaoxia-saas-api")
celery_app.conf.broker_url = settings.CELERY_BROKER_URL
celery_app.conf.result_backend = settings.CELERY_RESULT_BACKEND
# #1714 队列隔离:视频生成走 generation 队列,素材转码走 transcode 队列
try:
from packages.shared.celery_queues import apply_queue_settings
apply_queue_settings(celery_app)
except Exception: # noqa: BLE001 — 队列配置失败不阻断 API 启动
pass
+3 -131
View File
@@ -8,145 +8,27 @@ logger = logging.getLogger(__name__)
# ── 限流阈值常量(全系统统一管理,不要在业务代码里硬编码) ──
USER_PENDING_LIMIT = 3 # 单用户 pending 上限
GLOBAL_PENDING_LIMIT = 20 # 全局 pending 上限
WORKER_CONCURRENCY = 4 # worker 渲染并发数(infra/docker/compose.yml WORKER_CONCURRENCY 默认值)
# 限流错误码:前端据此区分"排队等待"与"创建失败"
ERROR_CODE_USER_QUEUE_FULL = "USER_QUEUE_FULL" # 429:用户自己的任务排队中
ERROR_CODE_SYSTEM_QUEUE_FULL = "SYSTEM_QUEUE_FULL" # 503:系统整体繁忙
class UserPendingLimitExceeded(Exception):
"""用户 pending 任务数超限,返回 429。"""
def __init__(
self,
user_id: str,
pending_count: int,
limit: int,
*,
running_count: int = 0,
requested_count: int = 1,
queue_ahead: int = 0,
estimated_wait_seconds: int = 0,
):
def __init__(self, user_id: str, pending_count: int, limit: int):
self.user_id = user_id
self.pending_count = pending_count
self.limit = limit
# 排队上下文(用于 429 结构化提示,前端展示"排队中"而非"创建失败"
self.running_count = running_count
self.requested_count = requested_count
self.queue_ahead = queue_ahead
self.estimated_wait_seconds = estimated_wait_seconds
super().__init__(f"用户 {user_id} pending 任务数 {pending_count} 超过上限 {limit}")
class GlobalQueueFull(Exception):
"""全局限流,返回 503。"""
def __init__(
self,
pending_count: int,
limit: int,
*,
running_count: int = 0,
queue_ahead: int = 0,
estimated_wait_seconds: int = 0,
):
def __init__(self, pending_count: int, limit: int):
self.pending_count = pending_count
self.limit = limit
self.running_count = running_count
self.queue_ahead = queue_ahead
self.estimated_wait_seconds = estimated_wait_seconds
super().__init__(f"系统 pending 任务数 {pending_count} 超过上限 {limit}")
def _estimate_wait_seconds(queue_ahead: int, generation_task_repository: Any) -> int:
"""根据排队任务数 + worker 并发数 + 历史平均任务耗时估算等待秒数。
估算公式:ceil(排队任务数 / 并发数) × 平均单任务耗时。
拿不到历史数据时仓储层返回默认 120 秒。
"""
import math
if queue_ahead <= 0:
return 0
try:
estimator = getattr(generation_task_repository, "estimate_avg_duration_seconds", None)
avg_seconds = estimator() if estimator is not None else 120.0
except Exception:
avg_seconds = 120.0
return int(math.ceil(queue_ahead / WORKER_CONCURRENCY) * avg_seconds)
def build_rate_limit_detail(
exc: Exception,
generation_task_repository: Any,
*,
scope: str = "user",
) -> dict:
"""构造结构化限流响应体(HTTPException 的 detail)。
前端按 detail.code 判断场景:
- USER_QUEUE_FULL (429):用户自己的任务在排队,应提示"等待/继续排队",不是创建失败
- SYSTEM_QUEUE_FULL (503):系统繁忙,稍后重试
detail 字段:
- code: 错误码
- message: 可读中文提示(可直接展示)
- queued_count: 当前排队(pending)任务数
- running_count: 当前渲染中(running)任务数
- queue_ahead: 前方排队任务数(预计等待批次依据)
- estimated_wait_seconds: 预计等待秒数
- limit: 对应限流上限
"""
if scope == "user" and isinstance(exc, UserPendingLimitExceeded):
running = exc.running_count
if not running:
try:
counter = getattr(generation_task_repository, "count_running_by_user", None)
running = counter(exc.user_id) if counter is not None else 0
except Exception:
running = 0
queue_ahead = exc.queue_ahead or max(exc.pending_count, 0)
wait = exc.estimated_wait_seconds or _estimate_wait_seconds(queue_ahead, generation_task_repository)
wait_minutes = max(1, round(wait / 60))
message = (
f"您有 {exc.pending_count} 个任务正在排队、{running} 个正在渲染,"
f"同一时间最多提交 {exc.limit} 个任务。请等待约 {wait_minutes} 分钟后再提交"
)
return {
"code": ERROR_CODE_USER_QUEUE_FULL,
"message": message,
"queued_count": exc.pending_count,
"running_count": running,
"queue_ahead": queue_ahead,
"estimated_wait_seconds": wait,
"limit": exc.limit,
}
# 全局繁忙
pending = getattr(exc, "pending_count", 0)
running = getattr(exc, "running_count", 0)
if not running:
try:
counter = getattr(generation_task_repository, "count_running_total", None)
running = counter() if counter is not None else 0
except Exception:
running = 0
queue_ahead = getattr(exc, "queue_ahead", 0) or pending
wait = getattr(exc, "estimated_wait_seconds", 0) or _estimate_wait_seconds(queue_ahead, generation_task_repository)
wait_minutes = max(1, round(wait / 60))
return {
"code": ERROR_CODE_SYSTEM_QUEUE_FULL,
"message": f"系统繁忙:当前 {pending} 个任务排队中、{running} 个渲染中,预计等待约 {wait_minutes} 分钟,请稍后再试",
"queued_count": pending,
"running_count": running,
"queue_ahead": queue_ahead,
"estimated_wait_seconds": wait,
"limit": getattr(exc, "limit", GLOBAL_PENDING_LIMIT),
}
def check_queue_limits(
user_id: str,
generation_task_repository: Any,
@@ -279,17 +161,7 @@ def safe_enqueue_generation_task(
# ── 发送 Celery 任务 ──
try:
celery_result = celery_app.send_task("worker.generate_video", args=[task.id])
# 记录 celery 消息 ID:孤儿清理/超时作废时据此 revoke + 清除队列消息(#1714
celery_task_id = getattr(celery_result, "id", "")
if celery_task_id:
try:
task.celery_task_id = celery_task_id
generation_task_repository.update(task)
except Exception as persist_err: # noqa: BLE001
logger.warning(
"%s 持久化 celery_task_id 失败(不影响主流程): task_id=%s err=%s", log_prefix, task.id, persist_err
)
celery_app.send_task("worker.generate_video", args=[task.id])
except Exception as e:
logger.error(
"%s 入队失败,标记为失败: task_id=%s error=%s",
-127
View File
@@ -1,127 +0,0 @@
"""AI数字人渲染合成管线 API Schema — #1798."""
from __future__ import annotations
from datetime import datetime
from typing import Any, Optional
from pydantic import BaseModel, Field, field_validator
class BRollSegment(BaseModel):
"""B-roll 片段配置."""
script_segment_index: int = Field(..., ge=0, description="对应文案片段索引")
asset_url: str = Field(..., description="B-roll 素材 URL")
mode: str = Field(..., description="插入模式: fullscreen 或 pip")
start_time: float = Field(..., ge=0.0, description="在对口型视频中的起始时间(秒)")
end_time: float = Field(..., ge=0.0, description="在对口型视频中的结束时间(秒)")
pip_position: Optional[str] = Field("bottom_right", description="pip 模式位置")
pip_scale: Optional[float] = Field(0.3, ge=0.05, le=1.0, description="pip 模式缩放比例")
@field_validator("mode")
@classmethod
def validate_mode(cls, v: str) -> str:
v = v.strip().lower()
if v not in ("fullscreen", "pip"):
raise ValueError("mode 必须为 fullscreen 或 pip")
return v
@field_validator("asset_url")
@classmethod
def validate_asset_url(cls, v: str) -> str:
v = v.strip()
if not v:
raise ValueError("asset_url 不能为空")
if not v.startswith(("http://", "https://")):
raise ValueError("asset_url 必须是 HTTP/HTTPS URL")
return v
@field_validator("end_time")
@classmethod
def validate_end_time(cls, v: float, info: Any) -> float:
start = info.data.get("start_time", 0.0)
if v <= start:
raise ValueError("end_time 必须大于 start_time")
return v
class CreateAiAvatarRenderRequest(BaseModel):
"""创建渲染任务请求."""
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")
cover_config: dict[str, Any] = Field(default_factory=dict, description="封面配置")
project_id: str = Field("", description="项目 ID")
@field_validator("lipsync_job_id")
@classmethod
def validate_lipsync_job_id(cls, v: str) -> str:
v = v.strip()
if not v:
raise ValueError("lipsync_job_id 不能为空")
return v
@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()
class AiAvatarRenderJobResponse(BaseModel):
"""渲染任务响应."""
id: str
user_id: str
project_id: str
lipsync_job_id: str
script_id: str = ""
b_roll_segments: list[dict[str, Any]]
title_config: dict[str, Any]
cover_config: dict[str, Any]
status: str
progress: int
output_video_url: str
output_cover_url: str
output_duration: float
error_message: str
submitted_at: Optional[datetime] = None
started_at: Optional[datetime] = None
completed_at: Optional[datetime] = None
created_at: datetime
updated_at: datetime
class Config:
from_attributes = True
class AiAvatarRenderProgressResponse(BaseModel):
"""渲染进度响应."""
status: str
progress: int
output_video_url: str
output_cover_url: str
output_duration: float
error_message: str
class SmartCoverRequest(BaseModel):
"""智能封面请求 — MediaKit 抽帧 + 质量评分选最佳帧 + 可选标题 drawtext 叠加."""
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")
title_config: Optional[dict[str, Any]] = Field(
None, description="标题配置;传入时在封面上用 drawtext 叠加标题(竖屏 720x1280"
)
class SmartCoverResponse(BaseModel):
"""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)")
+3 -20
View File
@@ -53,25 +53,11 @@ class AssetResponse(BaseModel):
created_at: str
uploaded_by_user_id: str
tag_ids: list[str] = Field(default_factory=list)
# 片段级余量信息(仅视频素材返回,非视频/无时长记录为 None,前端按可用处理)
used_duration: float | None = Field(default=None, description="已使用片段时长(秒,历史区间合并去重后)")
available_duration: float | None = Field(default=None, description="剩余可用时长(秒)= 素材总时长 - 已用时长")
used_ratio: float | None = Field(default=None, description="已用时长占比(0~1")
usable: bool = Field(
default=True,
description="是否仍可用于新片段:零重复可切区间耗尽且所有历史区间复用次数" "use_count)均达上限时为 false",
)
MAX_BATCH_SIZE = 200
class BatchGetRequest(BaseModel):
"""批量获取素材详情请求。"""
ids: list[str] = Field(..., min_length=1, max_length=MAX_BATCH_SIZE, description="素材 ID 列表")
class BatchDeleteRequest(BaseModel):
"""批量删除请求(软删除)。"""
@@ -129,13 +115,10 @@ class SmartMatchRequest(BaseModel):
)
class SmartMatchItem(AssetResponse):
"""智能选素材结果条目(扁平结构)。
素材字段(id/usable/余量等)直接挂在条目顶层,前端拿到 item 即可读 item.id
与 AssetResponse 字段完全一致;score/breakdown 为智能匹配附加的评分字段。
"""
class SmartMatchItem(BaseModel):
"""智能选素材结果条目"""
asset: AssetResponse
score: float = Field(..., ge=0, le=100, description="综合得分 0-100")
breakdown: dict[str, float] = Field(default_factory=dict, description="各维度得分明细")
-3
View File
@@ -28,9 +28,6 @@ class DuplicationRecordResponse(BaseModel):
status: str = "pending"
duplicate_rate: float | None = None
duplicate_count: int = 0
# #1661 视觉相似度(归一化 0~1)/ 匹配视频数
visual_similarity: float | None = None
match_count: int | None = None
created_at: str
updated_at: str
-4
View File
@@ -25,10 +25,6 @@ class GeneratedVideoResponse(BaseModel):
review_status: str = "pending_review"
generation_params: dict = Field(default_factory=dict)
download_url: str | None = None
# #1660 查重率(百分比 0~100)/ 视觉相似度(0~1)/ 匹配帧数
duplicate_rate: float | None = None
visual_similarity: float | None = None
match_count: int | None = None
class GeneratedVideoDownloadUrlResponse(BaseModel):
+14 -121
View File
@@ -10,7 +10,7 @@ class ConfirmGenerationRequest(BaseModel):
output_width: int = Field(default=1080, ge=100, description="输出视频宽度")
output_height: int = Field(default=1920, ge=100, description="输出视频高度")
cover_url: str = Field(default="", description="自定义封面图片 URL")
custom_title: str = Field(default="", description="用户自定义标题文本,非空时同步到任务和编辑计划")
custom_title: str = Field(default="", description="自定义视频标题")
class CreateGenerationTaskRequest(BaseModel):
@@ -25,29 +25,14 @@ class CreateGenerationTaskRequest(BaseModel):
asset_library_id: str = ""
strategy_id: str = ""
voice_library_id: str = ""
# ── 多变体独立配音(批量生成)──
# 长度 1 = 所有变体共用;长度 = count = 每个变体独立配音;空数组 = 回退 voice_library_id
voice_library_ids: list[str] = Field(
default_factory=list,
description="各变体独立配音素材库ID数组:长度1=共用,长度=count=独立。为空时回退 voice_library_id",
)
created_by_user_id: str = ""
# ── 模板模式新增字段 ──
template_id: str = ""
asset_ids: list[str] = Field(default_factory=list)
title_ids: list[str] = Field(default_factory=list)
voice_ids: list[str] = Field(default_factory=list)
# ── 来源剪辑计划 ──
source_edit_plan_id: str = ""
# ── variant-plans 轻量选片回传(#1749):正式生成直接复用,不再重选 ──
variant_plan_ids: list[str] = Field(
default_factory=list,
description="POST /generation/variant-plans 返回的各变体 plan_id(长度须=count);为空则走服务端选片",
)
# ── 标题配置(结构化)──
title_config: dict | None = Field(
default=None,
description="标题样式对象,包含 text/font/font_size/font_color/position/bold/stroke/shadow 等。为空时不影响现有行为。",
)
# ── 视频标题 ──
video_title: str = Field(default="", description="生成视频的标题/名称,为空则使用默认命名")
# ── 批量生成 ──
@@ -55,9 +40,11 @@ class CreateGenerationTaskRequest(BaseModel):
# ── 素材库自动匹配 ──
asset_select_mode: str = Field(
default="all",
description="素材选取模式:all=全部ready视频, smart=智能匹配(按质量/时长评分)",
description="素材选取模式:all=全部ready视频, random=随机选取, smart=智能匹配(按质量/时长评分)",
)
asset_select_count: int = Field(
default=0, ge=0, le=100, description="选取数量,0表示全部(仅 random/smart 模式有效)"
)
asset_select_count: int = Field(default=0, ge=0, le=100, description="选取数量,0表示全部(仅 smart 模式有效)")
# ── 自动重试 ──
auto_retry_enabled: bool = Field(
default=False,
@@ -85,47 +72,7 @@ class CreateGenerationTaskRequest(BaseModel):
output_width: int = Field(default=1280, description="输出视频宽度")
output_height: int = Field(default=720, description="输出视频高度")
cover_url: str = Field(default="", description="封面图片 URL")
# ── 多变体独立封面(批量生成)──
# 长度 1 = 所有变体共用;长度 = count = 每个变体独立封面;空数组 = 回退 cover_url
cover_urls: list[str] = Field(
default_factory=list,
description="各变体独立封面URL数组:长度1=共用,长度=count=独立。为空时回退 cover_url",
)
# ── 多变体独立标题文字(批量生成)──
# 长度 1 = 所有变体共用;长度 = count = 每个变体独立标题文字;空数组 = 使用 title_config.text
titles: list[str] = Field(
default_factory=list,
description="各变体独立标题文字数组:长度1=共用,长度=count=独立。为空时使用 title_config.text",
)
@model_validator(mode="after")
def _check_variant_arrays(self) -> "CreateGenerationTaskRequest":
"""变体数组字段长度校验 + #1749 配音严格守卫。
- cover_urls/titles:空(回退单值)、长度 1(共用)或长度 = count(独立);
- voice_library_ids:独立配音长度必须恰好 = count 且逐项非空,禁止静默 fallback
(长度 1 的"共用"场景请用 voice_library_id 单值字段);
- variant_plan_ids:非空时长度必须 = count。
"""
for name in ("cover_urls", "titles"):
arr = getattr(self, name)
if arr and len(arr) != 1 and len(arr) != self.count:
raise ValueError(f"{name} 长度必须为 1(共用)或 {self.count}(与 count 一致),当前为 {len(arr)}")
from packages.domain.variant_voice_resolver import VariantVoiceError, resolve_variant_voice_ids
try:
resolve_variant_voice_ids(
count=self.count,
voice_library_id=self.voice_library_id,
voice_library_ids=self.voice_library_ids or None,
)
except VariantVoiceError as exc:
raise ValueError(str(exc)) from exc
if self.variant_plan_ids and len(self.variant_plan_ids) != self.count:
raise ValueError(f"variant_plan_ids 长度({len(self.variant_plan_ids)})必须与 count({self.count})一致")
return self
custom_title: str = Field(default="", description="自定义视频标题")
@model_validator(mode="after")
def _check_at_least_one_mode(self) -> "CreateGenerationTaskRequest":
@@ -134,9 +81,9 @@ class CreateGenerationTaskRequest(BaseModel):
if not has_project and not has_template:
raise ValueError("project_id 或 template_id 至少需要提供一个")
has_library = bool(self.asset_library_id.strip())
has_assets = bool(self.asset_ids or self.title_ids)
has_assets = bool(self.asset_ids or self.title_ids or self.voice_ids)
if not has_library and not has_assets:
raise ValueError("asset_library_id 或 asset_ids/title_ids 至少需要提供一个")
raise ValueError("asset_library_id 或 asset_ids/title_ids/voice_ids 至少需要提供一个")
return self
@@ -161,7 +108,7 @@ class GenerationTaskResponse(BaseModel):
output_width: int = 1280
output_height: int = 720
cover_url: str = ""
title_config: dict = Field(default_factory=dict)
custom_title: str = ""
status: str
progress: float
result_count: int
@@ -213,6 +160,7 @@ class CreatePreviewGenerationTaskRequest(BaseModel):
template_id: str
asset_ids: list[str] = Field(default_factory=list)
title_ids: list[str] = Field(default_factory=list)
voice_ids: list[str] = Field(default_factory=list)
voice_library_id: str = Field(
default="", description="配音素材库ID(用户上传的音频或AI配音),对应配音选择页面选择的配音素材"
)
@@ -233,46 +181,6 @@ class CreatePreviewGenerationTaskRequest(BaseModel):
default="",
description="关联的编辑计划ID(可选),用于确认生成时复用预览产物",
)
title_config: dict = Field(
default_factory=dict,
description="标题配置(可选),渲染时烧录到预览视频中。支持字段: text/font/font_size/font_color/position/bold/stroke/shadow。N个变体时样式全局共用",
)
# ── 多变体独立配置(preview_count > 1)──
# 长度 1 = 所有变体共用;长度 = preview_count = 每个变体独立;空数组 = 回退单值字段
titles: list[str] = Field(
default_factory=list,
description="各变体独立标题文字数组:长度1=共用,长度=preview_count=独立。为空时使用 title_config.text",
)
voice_library_ids: list[str] = Field(
default_factory=list,
description="各变体独立配音素材库ID数组:长度1=共用,长度=preview_count=独立。为空时回退 voice_library_id",
)
cover_urls: list[str] = Field(
default_factory=list,
description="各变体独立封面URL数组:长度1=共用,长度=preview_count=独立(预览阶段通常为空)",
)
@model_validator(mode="after")
def _check_variant_arrays(self) -> "CreatePreviewGenerationTaskRequest":
"""变体数组字段长度校验 + #1749 配音严格守卫。"""
for name in ("titles", "cover_urls"):
arr = getattr(self, name)
if arr and len(arr) != 1 and len(arr) != self.preview_count:
raise ValueError(
f"{name} 长度必须为 1(共用)或 {self.preview_count}(与 preview_count 一致),当前为 {len(arr)}"
)
from packages.domain.variant_voice_resolver import VariantVoiceError, resolve_variant_voice_ids
try:
resolve_variant_voice_ids(
count=self.preview_count,
voice_library_id=self.voice_library_id,
voice_library_ids=self.voice_library_ids or None,
)
except VariantVoiceError as exc:
raise ValueError(str(exc)) from exc
return self
@model_validator(mode="after")
def _check_template_id(self) -> "CreatePreviewGenerationTaskRequest":
@@ -282,13 +190,13 @@ class CreatePreviewGenerationTaskRequest(BaseModel):
@model_validator(mode="after")
def _check_asset_ids(self) -> "CreatePreviewGenerationTaskRequest":
if not self.asset_ids and not self.title_ids:
raise ValueError("asset_ids/title_ids 至少需要提供一个")
if not self.asset_ids and not self.title_ids and not self.voice_ids:
raise ValueError("asset_ids/title_ids/voice_ids 至少需要提供一个")
return self
class PreviewGenerationTaskResponse(BaseModel):
"""单个预览变体任务响应。
"""预览生成任务响应。
包含任务状态、进度、分辨率、生成结果 URL 等关键字段。
"""
@@ -297,7 +205,6 @@ class PreviewGenerationTaskResponse(BaseModel):
status: str
progress: float
is_preview: bool = True
variant_index: int = 0
resolution: str = ""
video_url: str = ""
duration: float = 0.0
@@ -306,21 +213,7 @@ class PreviewGenerationTaskResponse(BaseModel):
transition_count: int = 0
material_usage: dict = Field(default_factory=dict)
error_message: str = ""
title_text: str = ""
voice_library_id: str = ""
created_at: datetime | None = None
started_at: datetime | None = None
finished_at: datetime | None = None
generate_duration: float = 0.0
class BatchPreviewGenerationTaskResponse(BaseModel):
"""批量预览任务响应:preview_count=N 时返回 N 个独立变体任务。
- items: 变体任务数组,按 variant_index 顺序排列,每个含独立 task_id/状态/预览视频URL
- total: 变体总数(= preview_count
- 前端按 items[i].task_id 分别轮询 GET /preview/{task_id} 获取进度与结果
"""
items: list[PreviewGenerationTaskResponse]
total: int
-101
View File
@@ -1,101 +0,0 @@
"""对口型 API Schema 定义 — #1796 / #1809 / #1822.
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)。
"""
from __future__ import annotations
from datetime import datetime
from typing import Optional
from pydantic import BaseModel, Field, model_validator
class LipsyncJobResponse(BaseModel):
"""对口型任务响应."""
id: str
user_id: str
project_id: str
video_url: str
audio_url: str
enable_video_loop: bool
voice_id: str = ""
script_text: str = ""
speed: float = 1.0
emotion: str = ""
mediakit_task_id: str
status: str
output_video_url: str
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
updated_at: datetime
class Config:
from_attributes = True
class CreateLipsyncJobRequest(BaseModel):
"""创建对口型任务请求.
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。
"""
video_url: str = Field(..., description="人物视频 URL(MP4,≤30min,单人真人)")
# 模式 2:直接音频
audio_url: str = Field("", description="驱动音频 URLmp3/aac/wav/m4a/flac);直生模式留空")
# 模式 1TTS 直生
voice_id: str = Field("", description="音色 ID(预置音色或克隆音色 profile UUID")
script_text: str = Field("", description="要合成的文案(直生模式必填,最长 5000 字符)")
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(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")
def _validate_input_mode(self) -> "CreateLipsyncJobRequest":
video = (self.video_url or "").strip()
if not video:
raise ValueError("video_url 不能为空")
if not video.startswith(("http://", "https://")):
raise ValueError("video_url 必须是 HTTP/HTTPS URL")
lower = video.lower().split("?")[0]
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(直接音频模式),"
"要么同时传 voice_id + script_textTTS 直生模式)"
)
if has_tts and len(self.script_text) > 5000:
raise ValueError("script_text 最长 5000 字符")
if has_audio:
au = self.audio_url.strip()
if not au.startswith(("http://", "https://")):
raise ValueError("audio_url 必须是 HTTP/HTTPS URL")
au_lower = au.lower().split("?")[0]
allowed = (".mp3", ".aac", ".wav", ".m4a", ".flac")
if not any(au_lower.endswith(ext) for ext in allowed):
raise ValueError(f"audio_url 格式不支持,仅支持: {', '.join(allowed)}")
self.audio_url = au
return self
-45
View File
@@ -1,45 +0,0 @@
"""Script (口播文案库) Pydantic schemas — Issue #1795."""
from __future__ import annotations
from datetime import datetime
from typing import List, Optional
from pydantic import BaseModel, Field
class ScriptSegment(BaseModel):
"""单段文案."""
text: str
duration: Optional[float] = None
class ScriptResponse(BaseModel):
id: str
user_id: str
title: str
content: str
segments: List[ScriptSegment] = Field(default_factory=list)
tags: List[str] = Field(default_factory=list)
created_at: datetime
updated_at: datetime
class ScriptListResponse(BaseModel):
items: list[ScriptResponse]
total: int = 0
class CreateScriptRequest(BaseModel):
title: str = Field(..., min_length=1, max_length=255)
content: str = ""
segments: List[ScriptSegment] = Field(default_factory=list)
tags: List[str] = Field(default_factory=list)
class UpdateScriptRequest(BaseModel):
title: Optional[str] = Field(None, min_length=1, max_length=255)
content: Optional[str] = None
segments: Optional[List[ScriptSegment]] = None
tags: Optional[List[str]] = None
-18
View File
@@ -16,7 +16,6 @@ class TTSSynthesizeRequest(BaseModel):
output_name: str = Field("", description="输出文件名")
language: str = Field("zh-CN", description="语言")
speed: float = Field(1.0, ge=0.5, le=2.0, description="语速")
emotion: str = Field("", description="情绪(natural/excited/calm/friendly,或中文 自然/兴奋/沉稳/亲切)")
voice_model: str = Field("", description="语音模型名称")
voice_clone_profile_id: str = Field("", description="关联的音色克隆档案 ID")
format: str = Field("mp3", description="输出格式(mp3/wav/pcm")
@@ -102,20 +101,3 @@ class SaveToLibraryResponse(BaseModel):
voice_id: str
voice_name: str
status: str
class TTSPreviewRequest(BaseModel):
"""TTS 预览(试听)请求。"""
text: str = Field(..., min_length=1, max_length=200, description="合成文本,限制 200 字")
voice_id: str = Field(..., min_length=1, description="音色 ID")
speed: float = Field(1.0, ge=0.5, le=2.0, description="语速")
emotion: str = Field("", description="情绪(natural/excited/calm/friendly,或中文)")
pitch: float = Field(1.0, ge=0.5, le=2.0, description="音调(预留,当前未使用)")
class TTSPreviewResponse(BaseModel):
"""TTS 预览(试听)响应。"""
audio_url: str = Field(..., description="合成音频 URL")
duration: Optional[float] = Field(default=None, description="音频时长(秒)")
+5 -12
View File
@@ -16,7 +16,6 @@ class DirectUploadPrepareRequest(BaseModel):
content_type: str = Field(default="application/octet-stream", min_length=1, max_length=100)
file_size: int = Field(..., gt=0)
file_hash: str = Field(default="", max_length=64, description="文件 MD5 哈希,用于去重检测")
client_upload_id: str = Field(default="", max_length=64, description="客户端幂等 token(同一次上传的重试保持一致)")
class DirectUploadPrepareResponse(BaseModel):
@@ -26,31 +25,25 @@ class DirectUploadPrepareResponse(BaseModel):
expires_at: str
fields: dict[str, str]
max_size_bytes: int
duplicated: bool = False
skip_transfer: bool = False
asset_id: str = ""
class DirectUploadCompleteRequest(BaseModel):
project_id: str = Field(..., min_length=1)
library_id: str = Field(..., min_length=1)
storage_key: str = Field(..., min_length=1, max_length=255)
file_hash: str = Field(default="", max_length=64, description="文件哈希,用于去重检测")
client_upload_id: str = Field(default="", max_length=64, description="客户端幂等 token(同一次上传的重试保持一致)")
file_size: int = Field(default=0, ge=0, description="文件大小(字节),用于无 hash 时的兜底去重")
file_hash: str = Field(default="", max_length=64, description="文件 MD5 哈希,用于去重检测")
class DirectUploadCompleteResponse(BaseModel):
storage_key: str
ingest_job_id: str
duplicated: bool = Field(default=False, description="是否为重复素材/重复 complete(命中幂等去重)")
asset_id: str = Field(default="", description="素材 asset_id重复 complete 时返回已存在记录")
url: str = Field(default="", description="Public URL of uploaded file")
duplicated: bool = Field(default=False, description="是否为重复素材(命中去重)")
asset_id: str = Field(default="", description="重复素材 asset_idduplicated=true 时返回")
class UploadAssetResponse(BaseModel):
storage_key: str
ingest_job_id: str
url: str = Field(..., description="Public URL of uploaded file")
duplicated: bool = Field(default=False, description="是否为重复素材/重复提交(命中幂等去重)")
asset_id: str = Field(default="", description="素材 asset_id重复提交时返回已存在记录")
duplicated: bool = Field(default=False, description="是否为重复素材(命中去重)")
asset_id: str = Field(default="", description="重复素材 asset_idduplicated=true 时返回")
-4
View File
@@ -22,10 +22,6 @@ class VideoItemResponse(BaseModel):
generation_params: dict = Field(default_factory=dict)
download_url: str | None = None
generated_at: str = ""
# #1660 查重率(百分比 0~100)/ 视觉相似度(0~1)/ 匹配帧数
duplicate_rate: float | None = None
visual_similarity: float | None = None
match_count: int | None = None
class ListVideosResponse(BaseModel):
+1 -2
View File
@@ -13,8 +13,7 @@ class CreateVoiceCloneRequest(BaseModel):
name: str = Field(..., min_length=1, max_length=100, description="音色名称")
description: str = Field("", description="音色描述")
source_audio_url: str = Field("", description="参考音频 URL(与 asset_id 二选一)")
asset_id: str = Field("", description="参考音频素材 ID(配音素材库中的音频 asset,与 source_audio_url 二选一)")
source_audio_url: str = Field("", description="参考音频 URL")
voice_model: str = Field("", description="语音模型名称")
language: str = Field("zh-CN", description="语言")
gender: str = Field("unknown", description="性别")
@@ -1,313 +0,0 @@
"""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
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。
"""
from __future__ import annotations
import logging
import os
import subprocess
import tempfile
import uuid
from pathlib import Path
from typing import Optional
from urllib.parse import urlparse
logger = logging.getLogger(__name__)
# MediaKit 抽帧轮询参数:poll_interval=1s × max_poll=15 → 最长 15s,配合前端 120s 超时足够
COVER_POLL_INTERVAL = 1.0
COVER_MAX_POLL_ATTEMPTS = 15
# 帧图片下载超时(秒)
FRAME_DOWNLOAD_TIMEOUT = 20
# 最佳帧下载超时(用于 persist)
BEST_FRAME_DOWNLOAD_TIMEOUT = 30
# 自家 OSS 私有桶 URL 重签有效期(供 MediaKit GPU worker 拉取)
MEDIAKIT_URL_TTL_SECONDS = 7 * 24 * 3600
def _sign_video_url_for_mediakit(video_url: str) -> str:
"""如果 video_url 是自家 OSS 私有桶 URL,重新签名为长有效期预签名 URL。
MediaKit GPU worker 需要能公网访问 video_url,裸 public_url 在私有桶下会 403。
"""
if not video_url:
return video_url
try:
from packages.shared.storage import get_shared_storage_service
storage = get_shared_storage_service()
public_base = getattr(storage, "public_url", "")
if not isinstance(public_base, str) or not public_base:
return video_url
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)")
return signed
except Exception:
logger.warning("[数字人封面] video_url 重签失败,使用原始 URL", exc_info=True)
return video_url
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.
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:
from packages.shared.cover_frame_scorer import score_frames
from packages.shared.mediakit_client import get_mediakit_client
mk = get_mediakit_client()
if not mk.is_available:
logger.warning("[数字人封面] MediaKit 未配置,无法智能抽帧")
return ""
logger.info(
"[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(
video_url=video_url,
strategy="SpecifiedFrames",
max_frames=max_frames,
poll_interval=COVER_POLL_INTERVAL,
max_poll_attempts=COVER_MAX_POLL_ATTEMPTS,
max_retries=1,
)
if not snapshots:
logger.warning("[数字人封面] MediaKit 未返回帧: %s", video_url[:80])
return ""
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 = []
with httpx.Client(timeout=FRAME_DOWNLOAD_TIMEOUT, follow_redirects=True) as client:
for snap in snapshots:
url = snap.get("image_url") or snap.get("url") or ""
if not url:
continue
tmp_path: Optional[str] = None
try:
resp = client.get(url)
resp.raise_for_status()
with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as tmp:
tmp.write(resp.content)
tmp_path = tmp.name
candidates.append({"image_path": tmp_path, "url": url})
except Exception as e:
logger.warning("[数字人封面] 帧下载失败,跳过: url=%s err=%s", url[:80], e)
candidates.append({"image_path": None, "url": url, "score": 0.0})
if not candidates:
return snapshots[0].get("image_url") or snapshots[0].get("url") or ""
scored = score_frames(candidates)
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:
try:
Path(p).unlink(missing_ok=True)
except Exception:
pass
logger.info(
"[数字人封面] 智能选帧完成: candidates=%d best_score=%s",
len(candidates),
best.get("score") if best else "n/a",
)
return best_url
except Exception:
logger.warning("[数字人封面] 智能选帧失败", exc_info=True)
return ""
def apply_title_to_cover(local_frame: str, *, title_config: dict | None) -> str:
"""用 ffmpeg drawtext 在封面图上叠加标题,返回叠加后图片的本地路径.
ffmpeg 失败时回退返回原始 local_frame。竖屏封面按 720x1280 计算位置。
"""
if not title_config or not isinstance(title_config, dict):
return local_frame
text = (title_config.get("text") or title_config.get("content") or "").strip()
if not text:
return local_frame
enabled = title_config.get("enabled", True)
if not enabled:
return local_frame
try:
from packages.domain.video_filter_builder import build_title_drawtext_filter
drawtext_filter = build_title_drawtext_filter(
title_config,
output_width=720,
output_height=1280,
)
if not drawtext_filter:
return local_frame
base, ext = os.path.splitext(local_frame)
titled_path = f"{base}_titled{ext or '.jpg'}"
cmd = [
"ffmpeg",
"-i",
local_frame,
"-vf",
drawtext_filter,
"-y",
titled_path,
]
logger.info("[数字人封面] 叠加标题: text=%s", text[:30])
result = subprocess.run(
cmd,
capture_output=True,
text=True,
timeout=30,
)
if result.returncode != 0:
logger.warning(
"[数字人封面] drawtext 失败,回退无标题: exit=%s stderr=%s",
result.returncode,
(result.stderr or "")[-300:],
)
return local_frame
if not os.path.exists(titled_path) or os.path.getsize(titled_path) == 0:
logger.warning("[数字人封面] drawtext 输出为空,回退无标题")
return local_frame
return titled_path
except Exception as exc:
logger.warning("[数字人封面] 标题叠加异常,回退无标题: %s", exc, exc_info=True)
return local_frame
def persist_cover_to_oss(
frame_url: str,
*,
job_id: str = "",
prefix: str = "ai-avatar/covers",
title_config: dict | None = None,
) -> str:
"""下载帧图并转存到 OSS,返回公网封面 URL.
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
title_config: 可选标题配置;传入时用 drawtext 叠加标题(竖屏 720x1280
Returns:
OSS 公网 URL;失败回退原始 frame_url
"""
if not frame_url:
return ""
tmp_path: Optional[str] = None
titled_path: Optional[str] = None
try:
import httpx
with httpx.Client(timeout=BEST_FRAME_DOWNLOAD_TIMEOUT, follow_redirects=True) as client:
resp = client.get(frame_url)
resp.raise_for_status()
if not resp.content:
logger.warning("[数字人封面] 帧图内容为空: %s", frame_url[:80])
return frame_url
with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as tmp:
tmp.write(resp.content)
tmp_path = tmp.name
from packages.shared.storage import get_shared_storage_service
storage = get_shared_storage_service()
token = job_id or uuid.uuid4().hex[:12]
cover_key = f"{prefix}/{token}/cover_{uuid.uuid4().hex[:8]}.jpg"
upload_path = apply_title_to_cover(tmp_path, title_config=title_config)
if upload_path != tmp_path:
titled_path = upload_path
public_url = storage.upload_file(
file_or_path=upload_path,
storage_key=cover_key,
content_type="image/jpeg",
)
logger.info(
"[数字人封面] 封面已转存 OSS: key=%s titled=%s",
cover_key,
bool(titled_path),
)
# 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
return frame_url
except Exception:
logger.warning("[数字人封面] 封面转存 OSS 失败,返回原始 URL", exc_info=True)
return frame_url
finally:
for p in (tmp_path, titled_path):
if p:
try:
Path(p).unlink(missing_ok=True)
except Exception:
pass
def generate_smart_cover(
video_url: str,
*,
job_id: str = "",
max_frames: int = 5,
title_config: dict | None = None,
) -> str:
"""一站式:MediaKit 智能抽帧选最佳 → (可选)drawtext 叠加标题 → 转存 OSS.
供独立封面接口与渲染管线复用。失败返回空字符串。
Args:
video_url: 可公网访问的视频 URL
job_id: 关联任务 ID
max_frames: 抽帧数量
title_config: 可选标题配置;传入时在封面上叠加 drawtext 标题(竖屏 720x1280
"""
best_frame = select_best_cover_frame(video_url, max_frames=max_frames)
if not best_frame:
return ""
return persist_cover_to_oss(best_frame, job_id=job_id, title_config=title_config)
@@ -1,586 +0,0 @@
"""AI数字人渲染合成 Service — #1798.
职责:
- 创建/查询/取消渲染任务
- 调用 Celery 异步任务执行渲染
- B-roll 合成 + 标题叠加 + 封面提取
- 用户隔离
"""
from __future__ import annotations
import logging
import os
import subprocess
import tempfile
import uuid
from datetime import datetime, timezone
from typing import Any, Optional
from sqlalchemy.orm import Session
from packages.adapters.sqlalchemy_impl.models import (
AiAvatarRenderJob,
LipsyncJobModel,
ScriptModel,
)
from packages.domain.video_filter_builder import (
build_broll_overlay_filter,
build_title_drawtext_filter,
)
from packages.shared.storage import get_shared_storage_service
logger = logging.getLogger(__name__)
class AiAvatarRenderError(Exception):
"""渲染服务异常."""
def __init__(self, message: str, code: str = "RenderError"):
self.code = code
super().__init__(message)
class AiAvatarRenderService:
"""AI数字人渲染合成 Service."""
def __init__(self, db: Session):
self.db = db
# ── 创建任务 ──────────────────────────────────────────────────────────
def create_render_job(
self,
*,
user_id: str,
lipsync_job_id: str,
script_id: str = "",
b_roll_segments: list[dict[str, Any]] | None = None,
title_config: dict[str, Any],
cover_config: dict[str, Any],
project_id: str = "",
) -> AiAvatarRenderJob:
"""创建渲染任务.
Raises:
AiAvatarRenderError: 校验失败
"""
# 1. 验证对口型任务
lipsync_job = (
self.db.query(LipsyncJobModel)
.filter(
LipsyncJobModel.id == lipsync_job_id,
LipsyncJobModel.user_id == user_id,
)
.first()
)
if lipsync_job is None:
raise AiAvatarRenderError("对口型任务不存在", code="LipsyncJobNotFound")
if lipsync_job.status != "completed":
raise AiAvatarRenderError(
f"对口型任务状态为 {lipsync_job.status},仅 completed 状态可渲染",
code="LipsyncJobNotCompleted",
)
if not lipsync_job.output_video_url:
raise AiAvatarRenderError("对口型任务输出视频 URL 为空", code="LipsyncJobNoOutput")
# 2. 验证文案归属(仅当选了文案库条目时;手动输入文案直生场景 script_id 可空)
script_id = (script_id or "").strip()
if script_id:
script = (
self.db.query(ScriptModel)
.filter(
ScriptModel.id == script_id,
ScriptModel.user_id == user_id,
)
.first()
)
if script is None:
raise AiAvatarRenderError("文案不存在或无权访问", code="ScriptNotFound")
# 3. 创建渲染任务
job_id = str(uuid.uuid4())
job = AiAvatarRenderJob(
id=job_id,
user_id=user_id,
project_id=project_id,
lipsync_job_id=lipsync_job_id,
script_id=script_id,
b_roll_segments=[s if isinstance(s, dict) else s.model_dump() for s in (b_roll_segments or [])],
title_config=title_config,
cover_config=cover_config,
status="pending",
)
self.db.add(job)
self.db.flush()
job.submitted_at = datetime.now(timezone.utc)
self.db.commit()
self.db.refresh(job)
return job
# ── 查询任务 ──────────────────────────────────────────────────────────
def get_render_job(self, job_id: str, user_id: str) -> Optional[AiAvatarRenderJob]:
"""获取渲染任务详情(用户隔离)."""
return (
self.db.query(AiAvatarRenderJob)
.filter(
AiAvatarRenderJob.id == job_id,
AiAvatarRenderJob.user_id == user_id,
)
.first()
)
def list_render_jobs(
self,
*,
user_id: str,
project_id: str = "",
status: str = "",
offset: int = 0,
limit: int = 20,
) -> tuple[list[AiAvatarRenderJob], int]:
"""获取渲染任务列表(分页 + 用户隔离)."""
query = self.db.query(AiAvatarRenderJob).filter(AiAvatarRenderJob.user_id == user_id)
if project_id:
query = query.filter(AiAvatarRenderJob.project_id == project_id)
if status:
query = query.filter(AiAvatarRenderJob.status == status)
total = query.count()
items = query.order_by(AiAvatarRenderJob.created_at.desc()).offset(offset).limit(limit).all()
return items, total
# ── 取消任务 ──────────────────────────────────────────────────────────
def cancel_render_job(self, job_id: str, user_id: str) -> Optional[AiAvatarRenderJob]:
"""取消渲染任务(仅 pending 状态可取消)."""
job = self.get_render_job(job_id, user_id)
if job is None:
return None
if job.status in ("pending", "submitted"):
job.status = "cancelled"
job.updated_at = datetime.now(timezone.utc)
self.db.commit()
self.db.refresh(job)
return job
# ── 重试任务 ──────────────────────────────────────────────────────────
def retry_render_job(self, job_id: str, user_id: str) -> Optional[AiAvatarRenderJob]:
"""重试失败的渲染任务."""
job = self.get_render_job(job_id, user_id)
if job is None:
return None
if job.status != "failed":
return None
job.status = "pending"
job.progress = 0
job.error_message = ""
job.output_video_url = ""
job.output_cover_url = ""
job.output_duration = 0.0
job.started_at = None
job.completed_at = None
job.updated_at = datetime.now(timezone.utc)
self.db.commit()
self.db.refresh(job)
return job
# ── 执行渲染(Celery 异步调用) ──────────────────────────────────────
def execute_render(self, job_id: str) -> None:
"""执行渲染管线.
由 Celery 异步任务调用,流程:
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. 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:
logger.error("渲染任务不存在: %s", job_id)
return
if job.status == "cancelled":
logger.info("渲染任务已取消: %s", job_id)
return
try:
# 更新状态为 processing
job.status = "processing"
job.started_at = datetime.now(timezone.utc)
job.progress = 5
job.updated_at = datetime.now(timezone.utc)
self.db.commit()
# 获取对口型任务信息
lipsync_job = self.db.query(LipsyncJobModel).filter(LipsyncJobModel.id == job.lipsync_job_id).first()
if lipsync_job is None:
raise AiAvatarRenderError("关联的对口型任务不存在", code="LipsyncJobNotFound")
# 1. 下载对口型输出视频 (20%)
input_video_path = self._download_video(lipsync_job.output_video_url)
job.progress = 20
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)
broll_filter, broll_label = 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(传入实际输出尺寸,保证位置计算正确)
title_filter = build_title_drawtext_filter(
job.title_config,
output_width=output_width,
output_height=output_height,
)
filter_complex = ""
final_label = None
if broll_filter and title_filter:
# B-roll → 标题叠在 B-roll 输出上
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:
# 无滤镜:直接拷贝视频流
filter_complex = ""
final_label = None
job.progress = 40
self.db.commit()
# 3. 执行 FFmpeg 渲染 (80%)
with tempfile.TemporaryDirectory() as tmpdir:
output_video_path = os.path.join(tmpdir, "output.mp4")
cmd_list = self._build_ffmpeg_command(
input_video=input_video_path,
b_roll_segments=job.b_roll_segments,
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",
)
job.progress = 80
self.db.commit()
# 4. 提取封面 (90%)
cover_path = ""
if job.cover_config:
cover_path = os.path.join(tmpdir, "cover.jpg")
cover_cmd = self._build_cover_extract_cmd(
cover_config=job.cover_config,
input_video=output_video_path,
output_path=cover_path,
)
try:
cover_result = subprocess.run(
cover_cmd,
capture_output=True,
text=True,
timeout=60,
)
if cover_result.returncode != 0:
logger.warning(
"封面提取失败(非致命),跳过: exit=%s stderr=%s",
cover_result.returncode,
(cover_result.stderr or "")[-300:],
)
cover_path = ""
except Exception as cover_err:
logger.warning("封面提取异常(非致命),跳过: %s", cover_err)
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:优先复用智能剪辑的 MediaKit 抽帧 + 质量评分选最佳帧(支持 drawtext 标题叠加);
# 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,
# 注意:不传 title_config —— 最终输出视频已经通过 drawtext 叠加了标题,
# 再传会导致封面标题双重叠加
)
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
job.progress = 95
self.db.commit()
# 6. 完成
job.status = "completed"
job.progress = 100
job.completed_at = datetime.now(timezone.utc)
job.updated_at = datetime.now(timezone.utc)
self.db.commit()
logger.info("渲染任务完成: %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]}"
# 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 同样兜底用 render_job_id
clip_project_id = (job.project_id or "").strip() or "ai_avatar"
clip_generation_task_id = (job.lipsync_job_id or "").strip() or job_id
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=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:
logger.error(
"自动保存成片记录失败(不影响渲染任务状态): render_job=%s",
job_id,
exc_info=True,
)
except AiAvatarRenderError as exc:
job.status = "failed"
job.error_message = str(exc)
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 _download_video(self, url: str) -> str:
"""下载视频到临时文件."""
import httpx
tmp = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False)
try:
with httpx.Client(timeout=120) as client:
resp = client.get(url)
resp.raise_for_status()
tmp.write(resp.content)
return tmp.name
except Exception:
if os.path.exists(tmp.name):
os.unlink(tmp.name)
raise
@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]],
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 P0OSS 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 foundexit 127 → Python 32512)。
list + shell=False 彻底规避 shell 转义问题。
"""
cmd: list[str] = ["ffmpeg", "-i", input_video]
for seg in b_roll_segments:
asset_url = seg.get("asset_url", "")
if asset_url:
cmd.extend(["-i", asset_url])
if filter_complex and final_label:
cmd.extend(
[
"-filter_complex",
filter_complex,
"-map",
f"[{final_label}]",
"-map",
"0:a?",
]
)
elif filter_complex:
cmd.extend(["-filter_complex", filter_complex])
cmd.extend(
[
"-c:v",
"libx264",
"-preset",
"veryfast",
"-crf",
"23",
"-c:a",
"aac",
"-b:a",
"128k",
"-y",
output_path,
]
)
return cmd
def _build_cover_extract_cmd(
self,
*,
cover_config: dict[str, Any],
input_video: str,
output_path: str,
) -> list[str]:
"""构建封面截帧 FFmpeg 命令(list 形式,shell=False."""
if not cover_config or not isinstance(cover_config, dict):
timestamp = 0.0
width = 0
height = 0
else:
timestamp = cover_config.get("timestamp", 0.0)
width = cover_config.get("width", 0)
height = cover_config.get("height", 0)
cmd: list[str] = [
"ffmpeg",
"-ss",
str(timestamp),
"-i",
input_video,
"-frames:v",
"1",
]
if width > 0 and height > 0:
vf = (
f"scale={width}:{height}:force_original_aspect_ratio=decrease,"
f"pad={width}:{height}:(ow-iw)/2:(oh-ih)/2"
)
cmd.extend(["-vf", vf])
cmd.extend(["-y", output_path])
return cmd
def _upload_to_oss(self, local_path: str, oss_key: str) -> str:
"""上传文件到 OSS,返回 URL.
使用 SharedStorageService 统一存储服务。
"""
storage = get_shared_storage_service()
url = storage.upload_file_smart(local_path, oss_key)
if url is None:
raise AiAvatarRenderError(
f"上传文件到 OSS 失败: {oss_key}",
code="OSSUploadFailed",
)
logger.info("上传文件到 OSS 成功: %s -> %s", local_path, url)
return url
@@ -1,494 +0,0 @@
"""素材片段级使用记录追踪与受控复用.
在素材 metadataassets.classification_result JSON)中持久化已使用的片段时间区间,
供 from-assets 创建片段时避开历史区间,实现跨任务/跨调用的片段去重;
素材可用区间耗尽后进入受控复用:允许有限次数(MAX_RANGE_USE_COUNT)复用最久未用
的历史区间,配合调用方的成片复用占比控制(MAX_REUSE_RATIO = 10%),把任意两条
成片的画面重复率控制在阈值内。
metadata 中的记录字段 ``used_time_ranges``::
"used_time_ranges": [
{
"start": 12.5, "end": 20.3,
"plan_id": "plan-xxx",
"created_at": "2026-08-29T12:00:00+00:00",
"use_count": 1, # 该区间累计被使用次数(复用一次 +1)
"last_used_at": "2026-08-29T12:00:00+00:00" # 最近一次使用时间
},
...
]
注意:本模块所有函数都不自行 commit,由调用方控制事务边界
from-assets 与 replace_all_clips_transactional 同事务;异步任务各自 commit)。
历史记录永不自动清空(自动轮回重置已下线,reset_used_segments 仅保留给运维/测试)。
"""
from __future__ import annotations
import json
import logging
from datetime import datetime, timezone
from typing import Callable
from sqlalchemy.orm import Session
from packages.adapters.sqlalchemy_impl.models import AssetModel
logger = logging.getLogger(__name__)
USED_RANGES_KEY = "used_time_ranges"
# ── 受控复用配置常量 ─────────────────────────────────────────────────────────
MAX_RANGE_USE_COUNT = 2
"""单条历史区间最多被使用次数(含首次),达到后不再参与复用。"""
REUSE_RATIO_LIMIT = 0.10
"""单条成片中,单个素材的复用片段累计时长 / 该素材在成片中的总时长上限(10%)。
超过则该素材不再分配新片段(调用方在轮询分配时跳过)。"""
SEGMENT_EDGE_GAP = 1.5
"""冲突判定边缘间隙(秒):历史区间按 [start-gap, end+gap] 扩边后参与冲突检测,
避免两条片段首尾紧贴导致画面观感重复;记录仍存实际值。"""
# 判定"新片段与历史区间为同一次使用(复用)"的重叠率阈值:
# 重叠时长 / 新区间时长超过该比例视为复用该历史区间(累加 use_count)而非新增记录。
_REUSE_OVERLAP_RATIO = 0.6
def _now_iso() -> str:
return datetime.now(timezone.utc).isoformat()
def _read_meta(model) -> dict:
"""读取素材 metadata dict。
兼容两种对象:
- ORM ``AssetModel``metadata 以 JSON 字符串存在 ``classification_result`` 列;
- 领域实体 ``Asset``(路由层 repository 返回):metadata 直接是 dict 属性
repository 与 classification_result 互转,见 asset_repository.py)。
"""
# 领域实体:metadata 已是 dict
meta = getattr(model, "metadata", None)
if isinstance(meta, dict):
return meta
raw = getattr(model, "classification_result", None)
if not raw:
return {}
try:
data = json.loads(raw) if isinstance(raw, str) else raw
return data if isinstance(data, dict) else {}
except Exception:
return {}
def _get_model(db: Session, asset_id: str, for_update: bool = False) -> AssetModel | None:
query = db.query(AssetModel).filter(AssetModel.id == asset_id)
if for_update:
# 行级锁(PostgreSQL SELECT ... FOR UPDATE):序列化同一素材的
# classification_result 读-改-写,避免并发事务丢失使用记录。
# SQLite 不支持时 SQLAlchemy 会忽略该子句(no-op)。
query = query.with_for_update()
return query.first()
def get_used_segments(db: Session, asset_ids: list[str]) -> dict[str, list[tuple[float, float]]]:
"""聚合多个素材的历史已用片段区间。
Returns:
``{asset_id: [(start, end), ...]}`` 格式,与 ``_calc_random_start_time`` 的
``used_segments`` 参数格式一致,可直接传入。
"""
if not asset_ids:
return {}
result: dict[str, list[tuple[float, float]]] = {}
models = db.query(AssetModel).filter(AssetModel.id.in_(list(set(asset_ids)))).all()
for model in models:
meta = _read_meta(model)
ranges = meta.get(USED_RANGES_KEY) or []
segments: list[tuple[float, float]] = []
for r in ranges:
try:
segments.append((float(r["start"]), float(r["end"])))
except (KeyError, TypeError, ValueError):
continue
if segments:
result[model.id] = segments
return result
def record_used_segments(
db: Session,
asset_id: str,
start: float,
end: float,
plan_id: str,
) -> None:
"""记录一次片段使用(不 commit.
若新区间与某条历史区间高度重叠(复用场景,如受控复用回调返回的区间、
MediaKit 挪到历史区间),则累加该记录的 ``use_count`` 并刷新 ``last_used_at``
不新增记录;否则追加一条新记录(use_count=1)。
"""
# 行级锁读取:与并发生成任务互斥,保证区间记录读-改-写一致
model = _get_model(db, asset_id, for_update=True)
if model is None:
logger.warning("[片段追踪] 素材不存在,跳过记录: asset_id=%s", asset_id)
return
meta = _read_meta(model)
ranges = list(meta.get(USED_RANGES_KEY) or [])
new_start = round(float(start), 3)
new_end = round(float(end), 3)
new_dur = max(new_end - new_start, 1e-6)
now = _now_iso()
for r in ranges:
try:
rs, re_ = float(r["start"]), float(r["end"])
except (KeyError, TypeError, ValueError):
continue
overlap = max(0.0, min(new_end, re_) - max(new_start, rs))
if overlap / new_dur >= _REUSE_OVERLAP_RATIO:
# 复用同一条历史区间:累加次数、刷新时间
r["use_count"] = int(r.get("use_count", 1)) + 1
r["last_used_at"] = now
r["plan_id"] = plan_id
meta[USED_RANGES_KEY] = ranges
model.classification_result = json.dumps(meta, ensure_ascii=False)
model.updated_at = datetime.now(timezone.utc)
return
ranges.append(
{
"start": new_start,
"end": new_end,
"plan_id": plan_id,
"created_at": now,
"use_count": 1,
"last_used_at": now,
}
)
meta[USED_RANGES_KEY] = ranges
model.classification_result = json.dumps(meta, ensure_ascii=False)
model.updated_at = datetime.now(timezone.utc)
def remove_used_segment(
db: Session,
asset_id: str,
start: float,
end: float,
plan_id: str | None = None,
tolerance: float = 0.5,
) -> bool:
"""删除素材 metadata 中匹配的一条使用记录(不 commit).
匹配规则:start/end 与记录值相差不超过 tolerance 秒;plan_id 非空时,
记录有 plan_id 则需相等,记录缺 plan_id(本功能上线前的旧数据)时按时间匹配。
Returns:
是否找到并删除了记录。
"""
model = _get_model(db, asset_id)
if model is None:
return False
meta = _read_meta(model)
ranges = list(meta.get(USED_RANGES_KEY) or [])
remaining: list[dict] = []
removed = False
for r in ranges:
try:
match = (
abs(float(r["start"]) - float(start)) <= tolerance and abs(float(r["end"]) - float(end)) <= tolerance
)
except (KeyError, TypeError, ValueError):
remaining.append(r)
continue
# plan_id 校验:传入 plan_id 时,记录有 plan_id 则必须相等;
# 记录本身缺 plan_id(旧数据)时退化为按时间匹配,避免旧区间永远删不掉
if plan_id is not None and r.get("plan_id") is not None and r.get("plan_id") != plan_id:
match = False
if match and not removed:
removed = True
continue
remaining.append(r)
if removed:
meta[USED_RANGES_KEY] = remaining
model.classification_result = json.dumps(meta, ensure_ascii=False)
model.updated_at = datetime.now(timezone.utc)
return removed
def reset_used_segments(db: Session, asset_id: str) -> None:
"""清空单个素材的历史片段使用记录(不 commit).
仅供运维/测试使用;正常生成流程中历史记录永不自动清空(受控复用取代自动轮回)。
"""
model = _get_model(db, asset_id)
if model is None:
return
meta = _read_meta(model)
if meta.get(USED_RANGES_KEY):
meta[USED_RANGES_KEY] = []
model.classification_result = json.dumps(meta, ensure_ascii=False)
model.updated_at = datetime.now(timezone.utc)
logger.info("[片段追踪] 素材区间记录手动清空: asset_id=%s", asset_id)
# ── 素材余量/可用性计算(Task H:素材库角标 + smart-match 过滤)──────────────
# 判定「是否还有空闲可切区间」时使用的最小片段时长(秒):空闲段长于此值才视为可切
_MIN_FREE_CLIP_DURATION = 3.0
def _merge_intervals(intervals: list[tuple[float, float]]) -> list[tuple[float, float]]:
"""合并重叠/相接的时间区间,返回升序不重叠区间列表。"""
if not intervals:
return []
ordered = sorted((float(a), float(b)) for a, b in intervals if b > a)
merged: list[tuple[float, float]] = [ordered[0]]
for start, end in ordered[1:]:
last_start, last_end = merged[-1]
if start <= last_end:
merged[-1] = (last_start, max(last_end, end))
else:
merged.append((start, end))
return merged
def _has_free_gap(used: list[tuple[float, float]], total: float, min_free: float = _MIN_FREE_CLIP_DURATION) -> bool:
"""素材 [0, total] 中是否存在长度 ≥ min_free 的空闲段(考虑边缘间隙)。"""
if total <= 0:
return False
# 历史区间按边缘间隙扩边后判定空闲(与选片冲突检测同一口径)
expanded = [(max(0.0, s - SEGMENT_EDGE_GAP), min(total, e + SEGMENT_EDGE_GAP)) for s, e in used]
merged = _merge_intervals(expanded)
cursor = 0.0
for start, end in merged:
if start - cursor >= min_free:
return True
cursor = max(cursor, end)
return total - cursor >= min_free
def compute_asset_availability(
model: "AssetModel | None",
min_free_clip_duration: float = _MIN_FREE_CLIP_DURATION,
) -> dict | None:
"""计算单个素材的余量与可用性(纯函数,不读写 DB)。
Returns:
视频素材返回 ``{"used_duration", "available_duration", "used_ratio", "usable"}``
非视频 / 无 model / 无时长信息返回 None(调用方按可用处理,零影响)。
usable=False 条件(与受控复用机制一致):
零重复可切区间已耗尽(不存在 ≥ min_free 的空闲段)且
所有历史区间 use_count 均达 MAX_RANGE_USE_COUNT 上限(无区间可复用)。
"""
if model is None:
return None
file_type = getattr(model, "file_type", None) or getattr(model, "mime_type", "") or ""
if file_type != "video" and not str(file_type).startswith("video/"):
return None
total = float(getattr(model, "duration", 0.0) or 0.0)
if total <= 0:
return None
meta = _read_meta(model)
raw_ranges = meta.get(USED_RANGES_KEY) or []
intervals: list[tuple[float, float]] = []
use_counts: list[int] = []
for r in raw_ranges:
try:
start = float(r["start"])
end = float(r["end"])
except (KeyError, TypeError, ValueError):
continue
if end <= start:
continue
intervals.append((start, end))
try:
use_counts.append(int(r.get("use_count", 1)))
except (TypeError, ValueError):
use_counts.append(1)
merged = _merge_intervals(intervals)
used_duration = round(sum(e - s for s, e in merged), 3)
used_duration = min(used_duration, total)
available_duration = round(max(total - used_duration, 0.0), 3)
used_ratio = round(min(used_duration / total, 1.0), 4)
has_free = _has_free_gap(intervals, total, min_free_clip_duration)
if has_free:
usable = True
else:
# 空闲段耗尽:仅当存在历史区间且全部达复用上限时才判定不可用;
# 无历史区间(理论上不会走到,因为 has_free=True)按可用处理
if not use_counts:
usable = True
else:
usable = any(uc < MAX_RANGE_USE_COUNT for uc in use_counts)
return {
"used_duration": used_duration,
"available_duration": available_duration,
"used_ratio": used_ratio,
"usable": usable,
}
def find_reusable_range(
db: Session,
asset_id: str,
clip_duration: float,
asset_total: float,
*,
max_use_count: int = MAX_RANGE_USE_COUNT,
) -> tuple[float, float] | None:
"""受控复用:在素材历史区间中选一条可复用区间返回 (start, end)。
选择规则:
1. 仅选 ``use_count < max_use_count`` 的历史区间;
2. 优先返回能完整容纳当前 clip_duration(起点后不越素材边界)的最久未用区间;
3. 没有能容纳的,则返回 last_used_at 最老(或缺失 last_used_at 的旧数据优先)
且 use_count 最低的区间起点(可能与其他历史区间重叠,属降级复用);
4. 无任何可复用区间(记录为空或全部达上限)返回 None。
本函数只读不写;复用次数的累加由后续 record_used_segments 完成。
"""
model = _get_model(db, asset_id)
if model is None:
return None
meta = _read_meta(model)
ranges = [r for r in (meta.get(USED_RANGES_KEY) or []) if int(r.get("use_count", 1)) < max_use_count]
if not ranges:
return None
def _last_used(r: dict) -> str:
return str(r.get("last_used_at") or r.get("created_at") or "")
max_start = max(0.0, asset_total - clip_duration)
# 2. 能完整容纳当前片段的候选:按 last_used_at 升序(最久未用优先)
fit = sorted(
[r for r in ranges if float(r["start"]) <= max_start + 1e-6],
key=_last_used,
)
if fit:
start = min(float(fit[0]["start"]), max_start)
return (start, start + clip_duration)
# 3. 降级:最久未用 + use_count 最低的区间起点
fallback = sorted(ranges, key=lambda r: (_last_used(r), int(r.get("use_count", 1))))[0]
start = min(float(fallback["start"]), max_start)
return (start, start + clip_duration)
def make_reuse_callback(
db: Session,
asset_durations: dict[str, float],
reused_tracker: dict[str, float] | None = None,
assigned_tracker: dict[str, float] | None = None,
ratio_limit: float = REUSE_RATIO_LIMIT,
) -> Callable[[str, float], tuple[float, float] | None]:
"""构造给 ``_calc_random_start_time`` 用的受控复用回调.
Args:
db: SQLAlchemy session
asset_durations: 素材 ID -> 总时长(回调需要素材总时长做边界约束)
reused_tracker: 可选的 ``{asset_id: 累计复用时长}``,回调成功返回复用区间时
会把本次片段时长累加进去,供调用方统计成片复用占比(10% 阈值)。
assigned_tracker: 可选的 ``{asset_id: 已分配片段总时长}``,配合 ratio_limit
在复用前预判:若复用本片段后占比 (reused + clip_duration) /
(assigned + clip_duration) 超过 ratio_limit,则拒绝复用、返回 None
(保证成片复用占比不超阈值)。
ratio_limit: 单条成片复用时长占比上限,默认 10%
Returns:
回调函数 ``(asset_id, clip_duration) -> (start, end) | None``。
回调内吞掉 DB 异常返回 None,不影响主生成流程。
"""
def _reuse(asset_id: str, clip_duration: float) -> tuple[float, float] | None:
try:
total = float(asset_durations.get(asset_id, 0.0) or 0.0)
if total <= 0:
return None
# 占比闸门:预判复用本片段后是否超限(仅当调用方提供了 assigned tracker
if assigned_tracker is not None:
assigned = float(assigned_tracker.get(asset_id, 0.0) or 0.0)
reused_amt = float((reused_tracker or {}).get(asset_id, 0.0) or 0.0)
if assigned > 0 and (reused_amt + clip_duration) / (assigned + clip_duration) > ratio_limit:
logger.info(
"[片段追踪] 复用占比预判超 %.0f%% 阈值,拒绝复用: asset_id=%s "
"reused=%.1f assigned=%.1f clip=%.1f",
ratio_limit * 100,
asset_id,
reused_amt,
assigned,
clip_duration,
)
return None
result = find_reusable_range(db, asset_id, clip_duration, total)
except Exception:
logger.warning("[片段追踪] 受控复用查询异常: asset_id=%s", asset_id, exc_info=True)
return None
if result is not None and reused_tracker is not None:
reused_tracker[asset_id] = reused_tracker.get(asset_id, 0.0) + clip_duration
return result
return _reuse
def get_asset_recent_use_counts(
db: Session,
asset_ids: list[str],
recent_video_count: int = 5,
) -> dict[str, int]:
"""统计每个素材在最近 N 个不同 plan_id 中的使用次数。
遍历素材 metadata 中的 used_time_ranges,统计有多少个不同的 plan_id(去重),
返回 {asset_id: count}。只统计最近 recent_video_count 个不同 plan_id 的使用次数。
Args:
db: 数据库会话
asset_ids: 素材 ID 列表
recent_video_count: 统计最近多少个不同 plan_id
Returns:
{asset_id: 在最近 recent_video_count 个 plan 中的使用次数}
"""
if not asset_ids:
return {}
result: dict[str, int] = {}
models = db.query(AssetModel).filter(AssetModel.id.in_(asset_ids)).all()
for model in models:
meta = _read_meta(model)
ranges = meta.get(USED_RANGES_KEY) or []
if not ranges:
result[model.id] = 0
continue
# 按 created_at 倒序收集不同 plan_id
sorted_ranges = sorted(
ranges,
key=lambda r: r.get("created_at") or "",
reverse=True,
)
recent_plan_ids: set[str] = set()
for r in sorted_ranges:
plan_id = r.get("plan_id")
if plan_id:
recent_plan_ids.add(plan_id)
if len(recent_plan_ids) >= recent_video_count:
break
result[model.id] = len(recent_plan_ids)
# 未找到的素材计为 0
for aid in asset_ids:
if aid not in result:
result[aid] = 0
return result
+3 -621
View File
@@ -9,12 +9,6 @@ from __future__ import annotations
import logging
from typing import Any, Dict, List, Optional
from app.services.asset_segment_tracker import (
REUSE_RATIO_LIMIT,
get_used_segments,
make_reuse_callback,
record_used_segments,
)
from sqlalchemy.orm import Session
from packages.adapters.sqlalchemy_impl import (
@@ -377,618 +371,6 @@ class EditPlanService:
logger.info("删除所有片段: plan_id=%s count=%d", plan_id, count)
return count
def replace_all_clips_transactional(
self,
plan_id: str,
clips_data: list[dict],
) -> int:
"""事务性地替换所有片段:清空→创建→标记ready,单事务保证原子性。
Args:
plan_id: 计划 ID
clips_data: 片段数据列表,每项包含 asset_id/start_time/duration/order
Returns:
int: 创建的片段数量
Raises:
Exception: 任何步骤失败时自动回滚
"""
from packages.adapters.sqlalchemy_impl.models import EditPlanClipModel
db = self._clip_repo.session
try:
# 1. 清空现有 clips(不 commit
deleted_count = db.query(EditPlanClipModel).filter(EditPlanClipModel.plan_id == plan_id).delete()
# 2. 批量创建新 clips(不 commit
for i, clip_item in enumerate(clips_data):
order = clip_item.get("order") or i
clip = EditPlanClip.create(
plan_id=plan_id,
clip_type=clip_item.get("clip_type", "main"),
order=order,
asset_id=clip_item.get("asset_id", ""),
text_content=clip_item.get("text_content", ""),
start_time=clip_item.get("start_time", 0.0),
duration=clip_item.get("duration", 0.0),
transition_effect=clip_item.get("transition_effect", "cut"),
transition_duration=clip_item.get("transition_duration", 0.0),
playback_speed=clip_item.get("playback_speed", 1.0),
config=clip_item.get("config") or None,
)
model = EditPlanClipModel(
id=clip.id,
plan_id=clip.plan_id,
clip_type=clip.clip_type,
order=clip.order,
asset_id=clip.asset_id,
text_content=clip.text_content,
start_time=clip.start_time,
duration=clip.duration,
transition_effect=clip.transition_effect,
transition_duration=clip.transition_duration,
playback_speed=clip.playback_speed,
status=clip.status.value,
config=clip.config,
)
db.add(model)
# flush 让新建 clip 写入当前事务(未 commit),后续查询才能找到它们
db.flush()
# 3. 标记有 asset_id 的 clips 为 ready(不 commit
pending_with_asset = (
db.query(EditPlanClipModel)
.filter(
EditPlanClipModel.plan_id == plan_id,
EditPlanClipModel.status == "pending",
EditPlanClipModel.asset_id != "",
)
.all()
)
for m in pending_with_asset:
m.status = "ready"
# 4. 一次性提交
db.commit()
logger.info(
"事务性替换片段: plan_id=%s deleted=%d created=%d",
plan_id,
deleted_count,
len(clips_data),
)
return len(clips_data)
except Exception:
db.rollback()
logger.exception("事务性替换片段失败: plan_id=%s", plan_id)
raise
def reselect_plan_for_variant(
self,
source_plan_id: str,
candidate_asset_ids: list[str],
*,
created_by_user_id: str = "",
name_suffix: str = "变体",
voice_duration: float = 0.0,
rng=None,
) -> EditPlan:
"""为批量变体生成独立 plan:完整重跑单视频选片流程(#1743)。
与 clone_plan_for_variant(只重算起点、素材/顺序不变)不同,本方法:
- 源 plan 片段骨架(clip_type/order/duration/文案/转场)保留;
- 素材池 shuffle 随机分配 + main 片段顺序洗牌;
- 起点走场景镜头洗牌/随机起点/历史区间避让(与单视频同一入口);
- 批次内同素材区间重叠 >20% 自动重选起点;
- 新片段区间 record_used_segments 写回素材 metadata(跨变体/跨任务避让)。
Args:
source_plan_id: 源 plan(任务 0 / 预览源)。
candidate_asset_ids: 素材池(源 plan 素材 ∪ 批次素材)。
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)。
Raises:
ValueError: 源 plan 不存在/无片段、素材池为空或时长全未知。
"""
from packages.adapters.sqlalchemy_impl.models import AssetModel
from packages.domain.plan_generator_utils import extract_scene_points_from_metadata
from packages.domain.variant_plan_selector import reselect_clips_for_variant
source = self.get_plan_or_raise(source_plan_id)
# 分页读取源 plan 全部片段
clips: List[EditPlanClip] = []
skip, page = 0, 500
while True:
batch = self._clip_repo.list_by_plan(source_plan_id, skip=skip, limit=page)
if not batch:
break
clips.extend(batch)
if len(batch) < page:
break
skip += page
if not clips:
raise ValueError(f"源 plan 无片段,无法生成变体: {source_plan_id}")
source_clips_data: list[dict[str, Any]] = [
{
"order": c.order if c.order is not None else i,
"asset_id": c.asset_id,
"start_time": float(c.start_time or 0.0),
"duration": float(c.duration or 0.0),
"clip_type": c.clip_type,
"playback_speed": float(c.playback_speed or 1.0),
"transition_effect": c.transition_effect,
"transition_duration": float(c.transition_duration or 0.0),
"text_content": c.text_content or "",
"config": c.config or {},
}
for i, c in enumerate(clips)
]
db = self._clip_repo.session
# #1749:配音时长 → 每段目标段长(片段数=模板片段数定死;素材不足由渲染末帧冻结铺满)
target_durations: list[float] | None = None
try:
voice = float(voice_duration or 0.0)
except (TypeError, ValueError):
voice = 0.0
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]
target_durations = plan_clip_durations(
len(source_clips_data),
voice,
transition_effects=_effects,
transition_durations=_tdurs,
)
if target_durations:
for _c, _d in zip(source_clips_data, target_durations, strict=False):
_c["duration"] = _d
# 素材池 = 源 plan 素材 ∪ 调用方传入素材(去重保序)
pool_ids: list[str] = []
seen = set()
for aid in [c.asset_id for c in clips if c.asset_id] + list(candidate_asset_ids or []):
if aid and aid not in seen:
seen.add(aid)
pool_ids.append(aid)
# 时长 + 场景点
durations: dict[str, float] = {}
scene_points: dict[str, list[float]] = {}
if pool_ids:
for m in db.query(AssetModel).filter(AssetModel.id.in_(pool_ids)).all():
durations[m.id] = float(getattr(m, "duration", 0.0) or 0.0)
pts = extract_scene_points_from_metadata(getattr(m, "metadata", None))
if pts:
scene_points[m.id] = pts
historical = get_used_segments(db, pool_ids)
# 创建新 plan(复制模板归属与 config
new_plan = self.create_plan(
template_id=source.template_id,
name=f"{source.name or '剪辑计划'} · {name_suffix}",
config=dict(source.config or {}),
total_duration=source.total_duration,
project_id=source.project_id or "",
created_by_user_id=created_by_user_id or (source.created_by_user_id or ""),
)
# 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,
pool_ids,
asset_durations=durations,
asset_scene_points=scene_points,
historical_used_segments=historical,
batch_segments=batch_segments,
target_durations=target_durations,
rng=rng,
)
# 片段区间写回素材 metadata(与落库同事务;replace_all_clips_transactional 内 commit
for item in clips_data:
aid = item.get("asset_id", "")
if aid:
st = float(item.get("start_time", 0.0))
record_used_segments(db, aid, st, st + float(item.get("duration", 0.0)), new_plan.id)
self.replace_all_clips_transactional(new_plan.id, clips_data)
logger.info(
"变体独立选片完成: source=%s new=%s clips=%d assets=%d",
source_plan_id,
new_plan.id,
len(clips_data),
len(pool_ids),
)
return new_plan
def clone_plan_for_variant(
self,
source_plan_id: str,
*,
created_by_user_id: str = "",
name_suffix: str = "变体",
reuse_tracker: Optional[dict] = None,
) -> EditPlan:
"""为批量/多预览场景克隆一份独立 plan,片段起点全部重算(受控随机/复用)。
复制源 plan 的模板归属、config 与片段结构(asset_id / duration / clip_type /
order 不变),每个片段重新调用 ``_calc_random_start_time``:读取素材持久化的
历史已用区间避让,耗尽时受控复用(use_count<3、最久未用),从而保证 N 条
成片片段区间互不相同,且复用占比受控。
- 不替换/不修改源 plan,源 plan 保留用户手动编辑结果。
- 片段区间记录(record_used_segments)随新片段写入素材 metadata,与新 plan
同事务;复用历史区间时由 record 自动累加 use_count。
- 克隆的 clips 复用区间累计时长写入 reuse_tracker(可选),供调用方统计占比。
Raises:
ValueError: 源 plan 不存在或无可用片段。
"""
from packages.adapters.sqlalchemy_impl.models import AssetModel
from packages.domain.plan_generator_utils import _calc_random_start_time
source = self.get_plan_or_raise(source_plan_id)
# 分页读取源 plan 全部片段
clips: List[EditPlanClip] = []
skip, page = 0, 500
while True:
batch = self._clip_repo.list_by_plan(source_plan_id, skip=skip, limit=page)
if not batch:
break
clips.extend(batch)
if len(batch) < page:
break
skip += page
if not clips:
raise ValueError(f"源 plan 无片段,无法克隆变体: {source_plan_id}")
# 创建新 plan(复制模板归属与 config
new_plan = self.create_plan(
template_id=source.template_id,
name=f"{source.name or '剪辑计划'} · {name_suffix}",
config=dict(source.config or {}),
total_duration=source.total_duration,
project_id=source.project_id or "",
created_by_user_id=created_by_user_id or (source.created_by_user_id or ""),
)
# 素材时长映射(O(N) 单查)
asset_ids = list({c.asset_id for c in clips if c.asset_id})
db = self._clip_repo.session
durations: dict[str, float] = {}
if asset_ids:
for m in db.query(AssetModel).filter(AssetModel.id.in_(asset_ids)).all():
durations[m.id] = float(getattr(m, "duration", 0.0) or 0.0)
used_segments = get_used_segments(db, asset_ids)
reused: dict[str, float] = reuse_tracker if reuse_tracker is not None else {}
asset_assigned: dict[str, float] = {}
# 回调内部预判复用后占比超 15% 则拒绝复用(calc 返回 None → 保留原起点)
reuse_cb = make_reuse_callback(db, durations, reused, assigned_tracker=asset_assigned)
clips_data: list[dict] = []
for i, c in enumerate(clips):
aid = c.asset_id
dur = float(c.duration or 0.0)
total = durations.get(aid, 0.0)
if aid and total > 0 and dur > 0:
# 复用占比闸门:本片段尚未分配,检查当前已复用占比
# reused / assigned 是否超 15%,超则该素材不再分配(保留原起点);
# assigned=0(首个片段)放行,reused=0 时不误拦正常分配
assigned = asset_assigned.get(aid, 0.0)
eff_dur = min(dur, total)
reused_amt = reused.get(aid, 0.0)
ratio_blocked = assigned > 0 and reused_amt / assigned > REUSE_RATIO_LIMIT
start = None
if not ratio_blocked:
start = _calc_random_start_time(aid, eff_dur, durations, used_segments, on_exhausted=reuse_cb)
if start is None:
start = float(c.start_time or 0.0)
asset_assigned[aid] = assigned + eff_dur
used_segments.setdefault(aid, []).append((start, start + eff_dur))
record_used_segments(db, aid, start, start + eff_dur, new_plan.id)
else:
start = float(c.start_time or 0.0)
clips_data.append(
{
"order": c.order if c.order is not None else i,
"asset_id": aid,
"start_time": start,
"duration": dur,
"clip_type": c.clip_type,
}
)
# 事务性写入新 plan 的片段(内部统一 commit/rollback
self.replace_all_clips_transactional(new_plan.id, clips_data)
logger.info(
"克隆变体 plan: source=%s new=%s clips=%d",
source_plan_id,
new_plan.id,
len(clips_data),
)
return new_plan
# ── #1749 配音时长分配 / 素材时长查询 / 批量变体 plan 确保 ──────────────
def get_asset_durations(self, asset_ids: list[str]) -> dict[str, float]:
"""批量查询素材时长(秒),O(N) 单查;缺失/异常返回 0.0。"""
from packages.adapters.sqlalchemy_impl.models import AssetModel
ids = [a for a in dict.fromkeys(asset_ids or []) if a]
if not ids:
return {}
db = self._clip_repo.session
out: dict[str, float] = {}
for m in db.query(AssetModel).filter(AssetModel.id.in_(ids)).all():
try:
out[m.id] = float(getattr(m, "duration", 0.0) or 0.0)
except (TypeError, ValueError):
out[m.id] = 0.0
return out
def apply_voice_duration_to_plan(self, plan_id: str, voice_duration: float) -> Optional[EditPlan]:
"""把配音时长分配到 plan 的每段(#1749)。
- 片段数保持不变(= 模板片段数,定死);
- 每段 duration 按 voice_duration_planner 分配(含转场重叠扣减);
- 素材短于段长 → start_time 钳制为 0(末帧冻结由渲染侧 tpad/apad 铺满);
- plan.total_duration 回写为成片净时长(≈ 配音时长);
- 幂等:配音时长相同则分配结果不变,可重复调用。
无配音(<=0)或无片段时直接返回 None,不报错。
"""
try:
voice = float(voice_duration or 0.0)
except (TypeError, ValueError):
return None
if voice <= 0:
return None
plan = self.get_plan(plan_id)
if plan is None:
return None
clips: List[EditPlanClip] = []
skip, page = 0, 500
while True:
batch = self._clip_repo.list_by_plan(plan_id, skip=skip, limit=page)
if not batch:
break
clips.extend(batch)
if len(batch) < page:
break
skip += page
if not clips:
return None
clips.sort(key=lambda c: (c.order if c.order is not None else 0))
from packages.domain.voice_duration_planner import plan_clip_durations, total_output_duration
# #1764:从 plan config 读取节奏模板
rhythm_template = None
if plan and hasattr(plan, "config") and plan.config:
rhythm_template = plan.config.get("rhythm_template")
# #1768:先获取素材时长,传入 plan_clip_durations 用于最大片段钳制
asset_ids = [c.asset_id for c in clips if c.asset_id]
durations = self.get_asset_durations(asset_ids)
asset_durations_for_plan = [durations.get(c.asset_id, 0.0) for c in clips]
target = plan_clip_durations(
len(clips),
voice,
transition_effects=[c.transition_effect for c in clips],
transition_durations=[float(c.transition_duration or 0.0) for c in clips],
rhythm_template=rhythm_template,
asset_durations=asset_durations_for_plan,
)
if not target:
return None
clips_data: list[dict] = []
for i, c in enumerate(clips):
dur = float(target[i])
total = durations.get(c.asset_id, 0.0)
start = float(c.start_time or 0.0)
if c.asset_id and total > 0:
# 素材短于段长:起点钳 0,段长超出部分渲染侧末帧冻结
max_start = max(0.0, total - min(dur, total))
start = min(start, max_start)
clips_data.append(
{
"order": c.order if c.order is not None else i,
"asset_id": c.asset_id or "",
"start_time": round(start, 3),
"duration": dur,
"clip_type": c.clip_type,
"playback_speed": float(c.playback_speed or 1.0),
"transition_effect": c.transition_effect,
"transition_duration": float(c.transition_duration or 0.0),
"text_content": c.text_content or "",
"config": c.config or {},
}
)
self.replace_all_clips_transactional(plan_id, clips_data)
net = total_output_duration(
target,
transition_effects=[c.transition_effect for c in clips],
transition_durations=[float(c.transition_duration or 0.0) for c in clips],
)
try:
plan.total_duration = net
db = self._clip_repo.session
db.commit()
except Exception:
db.rollback()
logger.exception("回写 plan.total_duration 失败(不阻断): plan_id=%s", plan_id)
logger.info(
"配音时长分配完成: plan=%s clips=%d voice=%.2fs 成片净时长=%.2fs",
plan_id,
len(clips),
voice,
net,
)
return plan
def ensure_variant_plans(
self,
source_plan_id: str,
count: int,
candidate_asset_ids: list[str],
*,
created_by_user_id: str = "",
voice_durations: Optional[list[float]] = None,
rng=None,
) -> list[str]:
"""确保批量 N 个变体各自拥有独立 plan(#1749 批量正式生成/预览共用)。
- 变体 0clone 源 plan(不污染源 plan,片段独立可改),并按配音分配段长;
- 变体 1..N-1reselect_plan_for_variant 完整重跑选片(素材级去重);
- voice_durations:每个变体的配音时长(独立配音各自时长;统一配音同值);
缺省/为 0 时不分配(段长保持骨架/模板值)。
Returns:
plan_id 列表,长度 == countindex 即 variant_index。
"""
import random as _random
rng = rng or _random.Random()
plan_ids: list[str] = []
# 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,
created_by_user_id=created_by_user_id,
name_suffix="变体1",
)
v0_voice = 0.0
if voice_durations and len(voice_durations) > 0:
try:
v0_voice = float(voice_durations[0] or 0.0)
except (TypeError, ValueError):
v0_voice = 0.0
if v0_voice > 0:
try:
self.apply_voice_duration_to_plan(plan0.id, v0_voice)
except Exception:
logger.exception("变体0 配音分配失败(不阻断): plan=%s", plan0.id)
plan_ids.append(plan0.id)
# 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):
try:
voice = float(voice_durations[i] or 0.0)
except (TypeError, ValueError):
voice = 0.0
variant = self.reselect_plan_for_variant(
source_plan_id,
candidate_asset_ids,
created_by_user_id=created_by_user_id,
name_suffix=f"变体{i + 1}",
voice_duration=voice,
rng=rng,
)
plan_ids.append(variant.id)
# #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:
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 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:
try:
self.mark_clips_ready(pid)
except Exception:
logger.exception("标记 clips ready 失败(不阻断): plan=%s", pid)
return plan_ids
# ── 片段分割与合并 ──────────────────────────────────────────────────────
def split_clip(self, clip_id: str, split_time: float) -> Dict[str, Any]:
@@ -1212,7 +594,7 @@ class EditPlanService:
config_asset_ids_count = len((plan.config or {}).get("asset_ids", []))
clips_with_asset_count = sum(1 for c in clips if c.asset_id)
logger.info(
"can_generate 诊断: plan=%s status=%s total_clips=%d clips_with_asset=%d config_asset_ids_count=%d",
"can_generate 诊断: plan=%s status=%s total_clips=%d " "clips_with_asset=%d config_asset_ids_count=%d",
plan_id,
plan.status,
len(clips),
@@ -1224,7 +606,7 @@ class EditPlanService:
config_asset_ids = (plan.config or {}).get("asset_ids", [])
if config_asset_ids:
logger.warning(
"can_generate 最后防线触发: plan=%s clips=%d 均无素材,从 config.asset_ids(%d个) 自动分配",
"can_generate 最后防线触发: plan=%s clips=%d 均无素材," "从 config.asset_ids(%d个) 自动分配",
plan_id,
len(clips),
len(config_asset_ids),
@@ -1256,7 +638,7 @@ class EditPlanService:
return False, "没有可渲染的就绪片段,自动修复后仍未分配素材"
else:
logger.warning(
"can_generate 失败: plan=%s clips=%d 均无素材,且 config.asset_ids 为空,无法自动修复",
"can_generate 失败: plan=%s clips=%d 均无素材," "且 config.asset_ids 为空,无法自动修复",
plan_id,
len(clips),
)
+1 -65
View File
@@ -34,17 +34,6 @@ from packages.domain.template_clip_converter import (
logger = logging.getLogger(__name__)
class TemplateNotFoundError(Exception):
"""模板不存在、已删除或当前用户无权访问.
"模板存在但无片段配置"区分:路由层应映射为 HTTP 404。
"""
def __init__(self, template_id: str) -> None:
self.template_id = template_id
super().__init__(f"模板不存在: {template_id}")
class EditTemplateService:
"""模板管理服务
@@ -228,14 +217,7 @@ class EditTemplateService:
skip: int = 0,
limit: int = 100,
) -> List[TemplateClipConfig]:
"""列出模板的片段配置
注意:本方法要求模板存在于新表 ``edit_templates``(全局模板库),
主要服务于新模板系统的写入/发布路径。用户自建模板存放在旧表
``templates``,不在 ``edit_templates`` 中,读取其片段配置请改用
:meth:`list_clip_configs_for_editor`,后者直接读取片段配置主表
``template_clip_configs``,不依赖新模板主表、也不靠异常降级。
"""
"""列出模板的片段配置"""
# 确保模板存在
self.get_template_or_raise(template_id)
return self._clip_config_repo.list_by_template(
@@ -245,52 +227,6 @@ class EditTemplateService:
limit=limit,
)
def list_clip_configs_for_editor(
self,
template_id: str,
user_id: str,
*,
clip_type: Optional[ClipType] = None,
skip: int = 0,
limit: int = 100,
) -> List[TemplateClipConfig]:
"""编辑器读取模板片段配置的单一数据源入口.
片段配置主表是 ``template_clip_configs``(直接读取,不抛异常、不降级)。
模板主表按双表现状显式判定,不使用 try/except 控制流:
1. 用户自建模板在旧表 ``templates``(归属 user_id)→ 校验归属与未删除后直接读;
2. 全局模板在新表 ``edit_templates``(无 user_id,全局可读)→ 直接读;
3. 两者都没有 → 模板不存在/无权限,抛 :class:`TemplateNotFoundError`。
Args:
template_id: 模板 ID
user_id: 当前登录用户 ID(用于旧表模板归属校验)
Raises:
TemplateNotFoundError: 模板不存在、已删除或不归属于当前用户。
"""
# 1) 用户自建模板(旧表 templates,归属 user_id
if self._clip_config_repo.template_owned_by(template_id, user_id):
return self._clip_config_repo.list_by_template(
template_id,
clip_type=clip_type,
skip=skip,
limit=limit,
)
# 2) 全局模板(新表 edit_templates,无 user_id,全局可读)
if self._template_repo.get(template_id) is not None:
return self._clip_config_repo.list_by_template(
template_id,
clip_type=clip_type,
skip=skip,
limit=limit,
)
# 3) 两表都没有:不存在 / 已删除 / 无权限
raise TemplateNotFoundError(template_id)
def get_clip_config(self, config_id: str) -> Optional[TemplateClipConfig]:
"""获取片段配置详情"""
return self._clip_config_repo.get(config_id)
-398
View File
@@ -1,398 +0,0 @@
"""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
- 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)
"""
from __future__ import annotations
import io
import logging
import uuid
from datetime import datetime, timezone
from typing import Optional
from urllib.parse import urlparse
from app.services.mediakit_client import (
STATUS_COMPLETED,
STATUS_FAILED,
STATUS_RUNNING,
MediaKitClient,
MediaKitError,
get_mediakit_client,
)
# 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.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
class LipsyncService:
"""对口型任务 Service."""
def __init__(
self,
db: Session,
client: Optional[MediaKitClient] = None,
cosyvoice_service=None,
voice_clone_repo=None,
):
self.db = db
self.client = client or get_mediakit_client()
self._cosyvoice = cosyvoice_service
self._voice_clone_repo = voice_clone_repo
def _get_cosyvoice(self):
"""延迟获取 CosyVoiceService(与 tts 路由一致,含 OSS 预签名配置)."""
if self._cosyvoice is None:
from app.dependencies import get_cosyvoice_service
self._cosyvoice = get_cosyvoice_service()
return self._cosyvoice
def _resolve_voice_id(self, voice_id: str, user_id: str) -> str:
"""将克隆音色 profile UUID 解析为 CosyVoice voice_id。
与 /tts/synthesize 保持一致:命中 profile → 校验归属 → 返回其 voice_id;
未命中(预置音色 ID 或克隆 CosyVoice voice_id)原样返回。
"""
if not voice_id:
return ""
if self._voice_clone_repo is None:
try:
from app.dependencies import get_voice_clone_profile_repository
self._voice_clone_repo = get_voice_clone_profile_repository(self.db)
except Exception:
return voice_id
try:
profile = self._voice_clone_repo.get(voice_id)
except Exception:
return voice_id
if profile is None:
return voice_id
if getattr(profile, "user_id", "") != user_id:
raise MediaKitError("无权访问该音色", code="VoiceForbidden")
if not getattr(profile, "voice_id", ""):
raise MediaKitError("音色克隆尚未完成,请稍后再试", code="VoiceNotReady")
return profile.voice_id
def _synthesize_and_persist_audio(
self,
*,
user_id: str,
job_id: str,
voice_id: str,
script_text: str,
speed: float,
emotion: str,
) -> str:
"""TTS 直生:调 CosyVoice 合成音频并转存 OSS,返回可公网访问的音频 URL.
Raises:
MediaKitError: 合成失败
"""
actual_voice_id = self._resolve_voice_id(voice_id, user_id)
cosyvoice = self._get_cosyvoice()
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")
# 转存到自家 OSS,避免临时 URL 过期导致 MediaKit 拉取失败
try:
audio_data = safe_download_bytes(
temp_url,
purpose="lipsync_tts_audio",
allowed_mime_types=ALLOWED_AUDIO_MIME_TYPES,
timeout=60.0,
)
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("对口型 TTS 音频已转存 OSS: job_id=%s key=%s", job_id, storage_key)
return permanent_url
except Exception as exc:
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
# ── 创建任务 ──────────────────────────────────────────────────────────
def create_job(
self,
*,
user_id: str,
video_url: str,
audio_url: str = "",
voice_id: str = "",
script_text: str = "",
speed: float = 1.0,
emotion: str = "",
enable_video_loop: bool = False,
project_id: str = "",
) -> LipsyncJobModel:
"""创建对口型任务.
两种输入模式:
- TTS 直生:voice_id + script_textaudio_url 留空)
→ 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(仅直接音频模式)
"""
# 0. 输入校验
if not audio_url:
if not (voice_id and script_text):
raise MediaKitError(
"必须提供 audio_url 或 voice_id+script_text",
code="InvalidInput",
)
# 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)
# 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,
project_id=project_id,
video_url=video_url,
audio_url=audio_url,
enable_video_loop=enable_video_loop,
voice_id=voice_id or "",
script_text=script_text or "",
speed=speed,
emotion=normalize_emotion(emotion),
status="tts_processing" if is_tts_mode else "pending",
)
self.db.add(job)
self.db.flush()
if is_tts_mode:
# 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=(
job_id,
user_id,
voice_id,
script_text,
speed,
normalize_emotion(emotion),
)
)
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,
exc,
)
job.status = "failed"
job.error_message = f"Celery 任务投递失败: {exc}"
job.error_code = "AsyncDispatchFailed"
job.updated_at = datetime.now(timezone.utc)
else:
# 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
# ── 查询任务 ──────────────────────────────────────────────────────────
def get_job(self, job_id: str, user_id: str) -> Optional[LipsyncJobModel]:
"""获取任务详情(用户隔离)."""
return (
self.db.query(LipsyncJobModel)
.filter(LipsyncJobModel.id == job_id, LipsyncJobModel.user_id == user_id)
.first()
)
def list_jobs(
self,
*,
user_id: str,
project_id: str = "",
status: str = "",
offset: int = 0,
limit: int = 20,
) -> tuple[list[LipsyncJobModel], int]:
"""获取任务列表(分页 + 用户隔离)."""
query = self.db.query(LipsyncJobModel).filter(LipsyncJobModel.user_id == user_id)
if project_id:
query = query.filter(LipsyncJobModel.project_id == project_id)
if status:
query = query.filter(LipsyncJobModel.status == status)
total = query.count()
items = query.order_by(LipsyncJobModel.created_at.desc()).offset(offset).limit(limit).all()
return items, total
# ── 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.
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
# 终态不需要再轮询
if job.status in (STATUS_COMPLETED, "failed"):
return job
# 未提交的任务不轮询
if not job.mediakit_task_id:
return job
try:
status_data = self.client.get_task_status(job.mediakit_task_id)
except MediaKitError as exc:
logger.error("轮询对口型任务状态失败 [%s]: %s", job_id, exc)
return job
mk_status = status_data.get("status", STATUS_RUNNING)
logger.info("MediaKit 对口型状态 [%s]: %s", job_id, mk_status)
if mk_status == STATUS_COMPLETED:
result = status_data.get("result", {})
job.status = STATUS_COMPLETED
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)
elif mk_status == STATUS_FAILED:
error = status_data.get("error", {})
job.status = "failed"
job.error_message = error.get("message", "任务执行失败")
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)
self.db.commit()
self.db.refresh(job)
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,不影响任务完成。
"""
if not temp_url:
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")
logger.info("对口型输出视频已转存 OSS: job_id=%s key=%s", job_id, storage_key)
return self._sign_media_url(permanent_url) or temp_url
except Exception as exc:
logger.warning("对口型输出视频转存 OSS 失败,回退临时 URL: job_id=%s err=%s", job_id, exc)
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,供 MediaKit 拉取 / 前端播放。
- 裸 public_urlupload_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 URLCosyVoice/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 # 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 # 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: # 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
# ── 取消任务 ──────────────────────────────────────────────────────────
def cancel_job(self, job_id: str, user_id: str) -> Optional[LipsyncJobModel]:
"""取消任务(仅 pending/tts_processing/submitted 状态可取消)."""
job = self.get_job(job_id, user_id)
if job is None:
return None
if job.status in ("pending", "tts_processing", "submitted"):
job.status = "cancelled"
job.updated_at = datetime.now(timezone.utc)
self.db.commit()
self.db.refresh(job)
return job
-243
View File
@@ -1,243 +0,0 @@
"""MediaKit 客户端 — 封装火山引擎 AI MediaKit 对口型 API.
接口文档:https://docs.volcengine.com/docs/6448/2656064
异步任务流程:
1. POST /api/v1/tools/lip-sync 提交对口型任务 → 返回 task_id
2. GET /api/v1/tasks/{task_id} 轮询任务状态 → running/completed/failed
3. completed 时 result.video_url 为口型对齐视频(临时链接 24h 有效)
设计原则:
- API Key 从配置读取(settings.mediakit_api_key
- 未配置 API Key 时所有方法返回降级响应,不阻塞主流程
- HTTP 超时/网络异常统一包装为 MediaKitError
"""
from __future__ import annotations
import logging
from typing import Any, Optional
import httpx
from packages.config import get_api_settings
logger = logging.getLogger(__name__)
# ── 任务状态常量 ──────────────────────────────────────────────────────────
STATUS_RUNNING = "running"
STATUS_COMPLETED = "completed"
STATUS_FAILED = "failed"
class MediaKitError(Exception):
"""MediaKit API 调用异常."""
def __init__(self, message: str, code: str = "", request_id: str = ""):
self.code = code
self.request_id = request_id
super().__init__(message)
class MediaKitClient:
"""火山引擎 AI MediaKit 对口型 API 客户端.
用法:
client = get_mediakit_client()
result = client.submit_lipsync(video_url="...", audio_url="...")
task_id = result["task_id"]
status = client.get_task_status(task_id)
# {"status": "completed", "result": {"video_url": "...", "duration": 60.5}}
"""
def __init__(self) -> None:
settings = get_api_settings()
self._api_key = settings.mediakit_api_key
self._base_url = settings.mediakit_base_url.rstrip("/")
self._timeout = settings.mediakit_timeout
@property
def is_available(self) -> bool:
"""是否已配置 API Key(未配置时自动降级)."""
return bool(self._api_key)
def _headers(self) -> dict[str, str]:
return {
"Authorization": f"Bearer {self._api_key}",
"Content-Type": "application/json",
}
# ── 提交对口型任务 ────────────────────────────────────────────────────
def submit_lipsync(
self,
*,
video_url: str,
audio_url: str,
enable_video_loop: bool = False,
callback_url: Optional[str] = None,
callback_args: Optional[str] = None,
client_token: Optional[str] = None,
) -> dict[str, Any]:
"""提交视频口型对齐任务.
Args:
video_url: 人物视频 URLMP4,≤30min,单人真人)
audio_url: 驱动音频 URLmp3/aac/wav/m4a/flac
enable_video_loop: 音频长于视频时是否循环画面
callback_url: 任务完成回调 URL
callback_args: 回调时原样返回的自定义参数
client_token: 幂等控制 token
Returns:
{"success": True, "task_id": "...", "request_id": "..."}
Raises:
MediaKitError: API 调用失败
"""
if not self.is_available:
raise MediaKitError("MediaKit API Key 未配置", code="NotConfigured")
payload: dict[str, Any] = {
"video_url": video_url,
"audio_url": audio_url,
}
if enable_video_loop:
payload["enable_video_loop"] = True
if callback_url:
payload["callback_url"] = callback_url
if callback_args:
payload["callback_args"] = callback_args[:512] # API 限制 512 字节
if client_token:
payload["client_token"] = client_token[:64] # API 限制 64 字符
try:
with httpx.Client(timeout=self._timeout) as client:
resp = client.post(
f"{self._base_url}/tools/lip-sync",
headers=self._headers(),
json=payload,
)
resp.raise_for_status()
data = resp.json()
except httpx.TimeoutException as exc:
raise MediaKitError(f"MediaKit API 超时 ({self._timeout}s)", code="Timeout") from exc
except httpx.HTTPStatusError as exc:
body = exc.response.text[:500]
raise MediaKitError(
f"MediaKit API HTTP {exc.response.status_code}: {body}",
code="HttpError",
) from exc
except httpx.RequestError as exc:
raise MediaKitError(f"MediaKit API 网络错误: {exc}", code="NetworkError") from exc
except Exception as exc:
raise MediaKitError(f"MediaKit API 未知错误: {exc}", code="UnknownError") from exc
if not data.get("success"):
error = data.get("error", {})
raise MediaKitError(
error.get("message", "提交任务失败"),
code=error.get("code", "SubmitFailed"),
request_id=data.get("request_id", ""),
)
return {
"success": True,
"task_id": data["task_id"],
"request_id": data.get("request_id", ""),
}
# ── 查询任务状态 ──────────────────────────────────────────────────────
def get_task_status(self, task_id: str) -> dict[str, Any]:
"""查询异步任务状态和结果.
Args:
task_id: 提交任务时返回的任务 ID
Returns:
{
"success": True,
"task_id": "...",
"status": "running" | "completed" | "failed",
"result": {"video_url": "...", "duration": 60.5} | None,
"error": {"code": "...", "message": "..."} | None,
"created_at": 1777291767,
"finished_at": 1777291851 | None,
"expires_at": 1777464650 | None,
}
Raises:
MediaKitError: API 调用失败
"""
if not self.is_available:
raise MediaKitError("MediaKit API Key 未配置", code="NotConfigured")
try:
with httpx.Client(timeout=self._timeout) as client:
resp = client.get(
f"{self._base_url}/tasks/{task_id}",
headers=self._headers(),
)
resp.raise_for_status()
data = resp.json()
except httpx.TimeoutException as exc:
raise MediaKitError(f"MediaKit API 超时 ({self._timeout}s)", code="Timeout") from exc
except httpx.HTTPStatusError as exc:
body = exc.response.text[:500]
raise MediaKitError(
f"MediaKit API HTTP {exc.response.status_code}: {body}",
code="HttpError",
) from exc
except httpx.RequestError as exc:
raise MediaKitError(f"MediaKit API 网络错误: {exc}", code="NetworkError") from exc
except Exception as exc:
raise MediaKitError(f"MediaKit API 未知错误: {exc}", code="UnknownError") from exc
if not data.get("success"):
error = data.get("error", {})
raise MediaKitError(
error.get("message", "查询任务失败"),
code=error.get("code", "QueryFailed"),
request_id=data.get("request_id", ""),
)
result: dict[str, Any] = {
"success": True,
"task_id": data.get("task_id", task_id),
"status": data.get("status", STATUS_RUNNING),
"result": data.get("result"),
"created_at": data.get("created_at"),
"finished_at": data.get("finished_at"),
"expires_at": data.get("expires_at"),
}
# 失败时提取错误信息
if data.get("status") == STATUS_FAILED:
error_obj = data.get("error", {})
result["error"] = {
"code": error_obj.get("code", "TaskFailed"),
"message": error_obj.get("message", "任务执行失败"),
}
return result
# ── 单例 ──────────────────────────────────────────────────────────────────
_client: Optional[MediaKitClient] = None
def get_mediakit_client() -> MediaKitClient:
"""获取 MediaKit 客户端单例."""
global _client
if _client is None:
_client = MediaKitClient()
return _client
def reset_mediakit_client() -> None:
"""重置客户端(测试用)."""
global _client
_client = None
@@ -13,7 +13,6 @@
from __future__ import annotations
import logging
import random
from typing import Any, List
from sqlalchemy.orm import Session
@@ -30,11 +29,9 @@ from packages.domain.editing_mode import EditingMode
from packages.domain.plan_generator_utils import (
create_clips_from_configs,
distribute_assets,
extract_scene_points_from_metadata,
generate_default_clips,
map_clip_types_for_mode,
)
from packages.domain.smart_match import SCORE_RANDOM_NOISE_MAX, score_asset
from packages.domain.template_clip_config import TemplateClipConfig
logger = logging.getLogger(__name__)
@@ -121,9 +118,9 @@ class PlanGeneratorService:
# 4. 按 editing_mode 分配素材
if asset_ids:
# 获取素材时长信息,用于随机起始时间
# 如果是随机预览模式,获取素材时长信息
asset_durations = None
if self._asset_repo:
if random_preview and self._asset_repo:
asset_durations = self._fetch_asset_durations(asset_ids)
self._distribute_assets(
clips,
@@ -131,7 +128,6 @@ class PlanGeneratorService:
editing_mode,
random_selection=random_preview,
asset_durations=asset_durations,
user_id=created_by_user_id,
)
# 5. 持久化所有 clips 并计算总时长
@@ -219,82 +215,19 @@ class PlanGeneratorService:
*,
random_selection: bool = False,
asset_durations: dict[str, float] | None = None,
user_id: str = "",
) -> None:
"""按 editing_mode 将素材分配到 clips(就地修改,未持久化).
先用 smart_match 评分对素材排序(高分优先),再委托给
plan_generator_utils.distribute_assets 纯函数完成分配。
委托给 plan_generator_utils.distribute_assets 纯函数。
"""
# 预览随机模式:素材顺序已 shuffle,纯随机起点即可,不读 DB 评分/缓存
asset_scene_points: dict[str, list[float]] = {}
if not random_selection:
# 正式生成:smart_match 评分排序(高分优先)+ 场景切换点缓存
if self._asset_repo:
asset_ids = self._sort_assets_by_smart_score(asset_ids)
# 读取素材 metadata 中的场景切换点缓存(后台 SceneChange 检测写入):
# 有缓存的素材片段起点从随机镜头段选取,无缓存走随机起点兜底
asset_scene_points = self._fetch_asset_scene_points(asset_ids)
# 正式生成也随机重排片段顺序(降重,默认开启无开关)
# smart_match 决定选哪些素材,shuffle 只改变分配到 clips 的顺序
asset_ids = list(asset_ids) # 复制避免修改调用方原列表
random.shuffle(asset_ids)
# 查询已有视频的已用区间(跨视频避让)
external_used_segments = None
if user_id and self._clip_repo:
try:
external_used_segments = self._clip_repo.list_used_segments_by_user(user_id, limit_recent=50)
except Exception:
logger.warning("跨视频避让查询失败,回退到纯随机", exc_info=True)
distribute_assets(
clips,
asset_ids,
editing_mode,
random_selection=random_selection,
asset_durations=asset_durations,
asset_scene_points=asset_scene_points,
external_used_segments=external_used_segments,
)
def _fetch_asset_scene_points(self, asset_ids: List[str]) -> dict[str, list[float]]:
"""从素材 metadata 读取场景切换点缓存(无缓存的素材不包含在结果中)。"""
points_map: dict[str, list[float]] = {}
if not self._asset_repo:
return points_map
for asset_id in asset_ids:
asset = self._asset_repo.get(asset_id)
if asset:
points = extract_scene_points_from_metadata(getattr(asset, "metadata", None))
if points:
points_map[asset_id] = points
return points_map
def _sort_assets_by_smart_score(self, asset_ids: List[str]) -> List[str]:
"""按 smart_match 综合评分降序排列素材 ID(注入随机噪声)。
评分高的素材(质量好、时长合适、新鲜、使用次数少)倾向排在前面;
排序时给每个素材的得分注入 0~SCORE_RANDOM_NOISE_MAX 的随机噪声,
使得分接近的素材排名每次浮动,避免一键生成反复选出相同素材组合,
从素材组合层面降低成片查重率。分差大于噪声上限时排名保持稳定。
"""
scored: list[tuple[str, float]] = []
for asset_id in asset_ids:
asset = self._asset_repo.get(asset_id)
if asset:
score, _ = score_asset(asset)
scored.append((asset_id, score))
else:
scored.append((asset_id, 0.0))
# 评分 + 随机噪声后按降序排列
scored.sort(
key=lambda x: x[1] + random.uniform(0.0, SCORE_RANDOM_NOISE_MAX),
reverse=True,
)
return [aid for aid, _ in scored]
def _fetch_asset_durations(self, asset_ids: List[str]) -> dict[str, float]:
"""从数据库获取素材时长信息.
-109
View File
@@ -1,109 +0,0 @@
"""ScriptService — Issue #1795 口播文案库 CRUD.
纯 Service 层封装,routes 直接调用。
"""
from __future__ import annotations
import uuid
from datetime import datetime, timezone
from typing import Optional
from sqlalchemy.orm import Session
from packages.adapters.sqlalchemy_impl.models import ScriptModel
class ScriptNotFoundError(Exception):
"""文案不存在或不属于当前用户."""
class ScriptService:
"""口播文案 CRUD."""
def __init__(self, db: Session) -> None:
self.db = db
# ── list ──────────────────────────────────────────────────────────────
def list_scripts(
self,
user_id: str,
skip: int = 0,
limit: int = 50,
tag: Optional[str] = None,
) -> tuple[list[ScriptModel], int]:
"""返回 (items, total)."""
q = self.db.query(ScriptModel).filter(ScriptModel.user_id == user_id)
if tag:
# JSON 数组包含查询
q = q.filter(ScriptModel.tags.contains([tag]))
total = q.count()
items = q.order_by(ScriptModel.created_at.desc()).offset(skip).limit(limit).all()
return items, total
# ── create ────────────────────────────────────────────────────────────
def create_script(
self,
user_id: str,
title: str,
content: str = "",
segments: list | None = None,
tags: list | None = None,
) -> ScriptModel:
script = ScriptModel(
id=str(uuid.uuid4()),
user_id=user_id,
title=title,
content=content,
segments=segments if segments is not None else [],
tags=tags if tags is not None else [],
)
self.db.add(script)
self.db.commit()
self.db.refresh(script)
return script
# ── get ───────────────────────────────────────────────────────────────
def get_script(self, script_id: str, user_id: str) -> ScriptModel:
script = self.db.query(ScriptModel).filter(ScriptModel.id == script_id, ScriptModel.user_id == user_id).first()
if script is None:
raise ScriptNotFoundError(f"Script {script_id} not found")
return script
# ── update ────────────────────────────────────────────────────────────
def update_script(
self,
script_id: str,
user_id: str,
title: Optional[str] = None,
content: Optional[str] = None,
segments: Optional[list] = None,
tags: Optional[list] = None,
) -> ScriptModel:
script = self.get_script(script_id, user_id)
if title is not None:
script.title = title
if content is not None:
script.content = content
if segments is not None:
script.segments = segments
if tags is not None:
script.tags = tags
script.updated_at = datetime.now(timezone.utc)
self.db.commit()
self.db.refresh(script)
return script
# ── delete ────────────────────────────────────────────────────────────
def delete_script(self, script_id: str, user_id: str) -> bool:
script = self.db.query(ScriptModel).filter(ScriptModel.id == script_id, ScriptModel.user_id == user_id).first()
if script is None:
return False
self.db.delete(script)
self.db.commit()
return True
@@ -39,9 +39,6 @@ from packages.domain.video_filter_builder import (
)
from packages.domain.video_filter_builder import build_concat_filter as _build_concat_filter_func
from packages.domain.video_filter_builder import build_filter_complex as _build_filter_complex
from packages.domain.video_filter_builder import (
build_title_drawtext_filter,
)
from packages.domain.video_filter_builder import build_xfade_filter as _build_xfade_filter_func
from packages.domain.video_filter_builder import chain_filters as _chain_filters_func
from packages.domain.video_filter_builder import has_audio as _has_audio_func
@@ -251,27 +248,6 @@ class VideoComposeService:
transitions=[c.transition_effect for c in ready_clips],
)
# ── #1789 标题 drawtext 滤镜叠加 ──
# 从 plan.config 读取 title_config,生成 drawtext 滤镜链入 filter_complex
title_cfg = (plan.config or {}).get("title", {}) or {}
if not isinstance(title_cfg, dict):
title_cfg = {}
# 同时兼容 plan.config["title_config"]API 回写路径)
if not title_cfg.get("text") and not title_cfg.get("content"):
title_cfg_alt = (plan.config or {}).get("title_config", {}) or {}
if isinstance(title_cfg_alt, dict) and (title_cfg_alt.get("text") or title_cfg_alt.get("content")):
title_cfg = title_cfg_alt
drawtext_filter = build_title_drawtext_filter(title_cfg, output_width, output_height)
if drawtext_filter:
# 将最终输出标签从 [outv] 改为 [composed],再链入 drawtext → [outv]
filter_complex = filter_complex.replace("[outv]", "[composed]")
filter_complex += f";[composed]{drawtext_filter}[outv]"
logger.info(
"[#1789] 标题 drawtext 滤镜已注入: plan_id=%s text=%s",
plan_id,
(title_cfg.get("text") or title_cfg.get("content") or "")[:30],
)
# 构建完整命令
command: list[str] = ["ffmpeg", "-y"]
-1
View File
@@ -1 +0,0 @@
"""Celery 异步任务模块."""
-48
View File
@@ -1,48 +0,0 @@
"""AI数字人渲染 Celery 异步任务 — #1798."""
from __future__ import annotations
import logging
from app.core.celery_app import celery_app
from app.dependencies import get_db_session
logger = logging.getLogger(__name__)
@celery_app.task(bind=True, name="ai_avatar_render.execute", max_retries=2)
def execute_ai_avatar_render(self, job_id: str) -> dict:
"""执行 AI 数字人渲染管线.
进度更新:
- 0%: 任务开始
- 20%: 下载对口型视频完成
- 40%: 滤镜链构建完成
- 80%: FFmpeg 渲染完成
- 95%: 上传 OSS 完成
- 100%: 任务完成
"""
logger.info("开始执行渲染任务: %s", job_id)
self.update_state(state="PROCESSING", meta={"progress": 0, "job_id": job_id})
try:
# 获取数据库 session
db_gen = get_db_session()
db = next(db_gen)
try:
from app.services.ai_avatar_render_service import AiAvatarRenderService
service = AiAvatarRenderService(db)
service.execute_render(job_id)
finally:
try:
next(db_gen)
except StopIteration:
pass
return {"status": "completed", "job_id": job_id}
except Exception as exc:
logger.exception("渲染任务执行异常 [%s]: %s", job_id, exc)
self.update_state(state="FAILED", meta={"progress": 0, "error": str(exc)})
raise
-450
View File
@@ -1,450 +0,0 @@
"""AI 数字人对口型 TTS 异步任务 — 将 TTS 合成从 HTTP 请求移至 Celery 后台执行.
优化目标:将 create_job 的 API 响应时间从 6~35s 降到 <1s。
任务流程:
1. 创建新 DB session,加载 job 记录
2. 调用 CosyVoice 合成音频
3. 下载音频并转存到自家 OSS
4. 更新 job 的 audio_url
5. 签名 URL 并提交到 MediaKit
6. 更新 job 状态为 submitted
7. 异常时标记 job 为 failed
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。
"""
import io
import logging
from datetime import datetime, timezone
from urllib.parse import urlparse
from celery import shared_task
logger = logging.getLogger(__name__)
# MediaKit 预签名 URL 有效期(7天,秒),与 LipsyncService._sign_media_url 保持一致
_MEDIAKIT_URL_TTL_SECONDS = 7 * 24 * 3600
def _sign_media_url(url: str) -> str:
"""对自家 OSS 私有桶 URL 重签长有效期预签名.
- 自家 OSS URL → 重签 7 天有效期
- 外部临时 URL → 原样透传
- 任何异常降级原样返回,不阻断主流程
"""
if not url:
return url
try:
from packages.shared.storage import get_shared_storage_service
storage = get_shared_storage_service()
public_base = getattr(storage, "public_url", "")
if not isinstance(public_base, str) or not public_base:
return url
own_host = urlparse(public_base).netloc.lower()
host = urlparse(url).netloc.lower()
if not own_host or host != own_host:
return url
signed = storage.get_download_url(url, expires_seconds=_MEDIAKIT_URL_TTL_SECONDS)
return signed or url
except Exception as exc: # noqa: BLE001
logger.warning("[lipsync_tts] URL 重签失败,原样返回: url_prefix=%s err=%s", url[:80], exc)
return url
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 splitScriptIntoSentences 一致)."""
import re
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 _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}]
"""
import re
import subprocess
import tempfile
sentences = _split_script_into_sentences(script_text)
if not sentences:
return []
# 写入临时音频文件
with tempfile.NamedTemporaryFile(suffix=".mp3", delete=False) as tmp:
tmp.write(audio_data)
tmp_path = tmp.name
try:
# 用 ffmpeg silencedetect 检测静音段
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 ""
# 解析静音结束时间点(silence_end: X.XXX
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)
# 如果没有检测到足够的静音点,降级为字数比例估算
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)
# 贪心匹配:N-1 个句子边界对应 N-1 个静音点
# 按时间均匀分布期望值,选择最近的静音点
n_boundaries = len(sentences) - 1
boundaries = []
used_indices = set()
for i in range(n_boundaries):
# 期望的边界位置(按句子数量均匀分布)
expected_pos = (i + 1) / len(sentences) * total_duration
# 找最近的未使用静音点
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()
# 构建 sentence_timings
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:
import os
try:
os.unlink(tmp_path)
except Exception:
pass
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
@shared_task(
bind=True,
name="lipsync_tts.synthesize_and_submit",
max_retries=2,
default_retry_delay=30,
)
def tts_synthesize_and_submit(
self,
job_id: str,
user_id: str,
voice_id: str,
script_text: str,
speed: float,
emotion: str,
):
"""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。
"""
from app.services.mediakit_client import MediaKitError, get_mediakit_client
from sqlalchemy.orm import Session as DBSession
from packages.adapters.sqlalchemy_impl.models import LipsyncJobModel
from packages.application.cosyvoice_service import CosyVoiceError, CosyVoiceService
from packages.shared.url_security import safe_download_bytes
# SessionLocal 获取:
# - API 容器:app.db.SessionLocal(环境变量完整,导入即建引擎)
# - Worker 容器:worker_app.db.SessionLocalWorker 自己的 settings 初始化引擎)
# API 侧没有 worker_app 模块 → ImportError 直接回退;
# Worker 侧 app.db 会因缺少 API 专有环境变量抛 pydantic ValidationError
# 此时也要回退到 worker_app.db。
try:
from worker_app.db import SessionLocal # type: ignore
except Exception: # noqa: BLE001
from app.db import SessionLocal # type: ignore
db: DBSession = 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] Job not found: job_id=%s", job_id)
return
# 已取消的任务不再处理
if job.status == "cancelled":
logger.info("[lipsync_tts] Job already cancelled, skipping: job_id=%s", job_id)
return
# 1. TTS 合成
try:
cosyvoice = CosyVoiceService()
result = cosyvoice.submit_synthesize_task(
text=script_text,
voice_id=voice_id,
speed=speed,
emotion=emotion,
)
except CosyVoiceError as exc:
logger.error("[lipsync_tts] TTS 合成失败: job_id=%s err=%s", job_id, exc)
job.status = "failed"
job.error_message = f"TTS 合成失败: {exc}"
job.error_code = "TTSSynthesisFailed"
job.updated_at = datetime.now(timezone.utc)
db.commit()
return
except ValueError as exc:
logger.error("[lipsync_tts] TTS 参数错误: job_id=%s err=%s", job_id, exc)
job.status = "failed"
job.error_message = f"TTS 参数错误: {exc}"
job.error_code = "TTSInvalidParam"
job.updated_at = datetime.now(timezone.utc)
db.commit()
return
temp_url = result.get("audio_url", "")
if not temp_url:
logger.error("[lipsync_tts] TTS 未返回音频 URL: job_id=%s", job_id)
job.status = "failed"
job.error_message = "TTS 未返回音频 URL"
job.error_code = "TTSNoAudio"
job.updated_at = datetime.now(timezone.utc)
db.commit()
return
# 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={
"audio/mpeg",
"audio/mp3",
"audio/wav",
"audio/x-wav", # CosyVoice 部分接口返回 audio/x-wav,与 audio/wav 等价(RIFF/WAVE
"audio/mp4",
"audio/x-m4a",
},
timeout=60.0,
)
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 音频转存 OSS 失败,回退临时 URL: job_id=%s err=%s",
job_id,
exc,
)
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)
# 直接复用步骤 2 已下载到内存的 audio_data,避免重新从 OSS 下载(私有桶未签名会失败)
import os as _os
_st_tmp_path = None
try:
import subprocess as _sp
import tempfile as _tmpf
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:
# 写入临时文件供 ffprobe/ffmpeg 使用
with _tmpf.NamedTemporaryFile(suffix=".mp3", delete=False) as _atmp:
_atmp.write(audio_data)
_st_tmp_path = _atmp.name
# ffprobe 获取音频时长
_probe_result = _sp.run(
[
"ffprobe",
"-v",
"error",
"-show_entries",
"format=duration",
"-of",
"default=noprint_wrappers=1:nokey=1",
_st_tmp_path,
],
capture_output=True,
text=True,
timeout=10,
)
_audio_duration = float(_probe_result.stdout.strip()) if _probe_result.stdout.strip() else 0.0
logger.info(
"[lipsync_tts] 音频时长探测: job_id=%s duration=%.2f probe_stdout=%s probe_stderr=%s",
job_id,
_audio_duration,
_probe_result.stdout.strip()[:50],
_probe_result.stderr.strip()[:100] if _probe_result.stderr else "",
)
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 stdout=%s stderr=%s",
job_id,
_probe_result.stdout.strip()[:100],
_probe_result.stderr.strip()[:200] if _probe_result.stderr else "",
)
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
)
finally:
if _st_tmp_path:
try:
_os.unlink(_st_tmp_path)
except Exception:
pass
# 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)
client = get_mediakit_client()
try:
mk_result = client.submit_lipsync(
video_url=video_url,
audio_url=audio_url,
enable_video_loop=job.enable_video_loop,
client_token=job_id,
)
job.mediakit_task_id = mk_result["task_id"]
job.status = "submitted"
job.submitted_at = datetime.now(timezone.utc)
logger.info(
"[lipsync_tts] 已提交 MediaKit: job_id=%s task_id=%s",
job_id,
mk_result["task_id"],
)
except MediaKitError as exc:
job.status = "failed"
job.error_message = str(exc)
job.error_code = exc.code
logger.error("[lipsync_tts] 提交 MediaKit 失败: job_id=%s err=%s", job_id, exc)
db.commit()
except Exception:
logger.exception("[lipsync_tts] 未预期的异常: job_id=%s", job_id)
try:
job = db.query(LipsyncJobModel).filter(LipsyncJobModel.id == job_id).first()
if job and job.status not in ("cancelled", "failed", "completed"):
job.status = "failed"
job.error_message = "TTS 异步任务执行异常"
job.error_code = "AsyncTaskError"
job.updated_at = datetime.now(timezone.utc)
db.commit()
except Exception:
logger.exception("[lipsync_tts] 回写失败状态时异常: job_id=%s", job_id)
finally:
db.close()
@@ -1,174 +0,0 @@
#!/usr/bin/env python3
"""存量指纹重建脚本 — 为已有视频生成 video_fingerprint_chunks 分片数据。
功能:
- 查询 generated_videos 中 video_fingerprint IS NOT NULL 但尚无分片数据的视频
- 从 OSS 下载视频 → 用新的分片算法重新计算指纹 → 写入分片表
- 支持 --dry-run(只打印不写入)和 --batch-size(默认 50
- 幂等:已存在分片数据的视频跳过
用法:
# 预览(不写入)
python rebuild_fingerprint_chunks.py --dry-run
# 执行重建
python rebuild_fingerprint_chunks.py --batch-size 50
"""
from __future__ import annotations
import argparse
import logging
import os
import sys
import tempfile
# 确保可以 import worker_app 和 packages
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "..", "..", "worker"))
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "..", ".."))
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
)
logger = logging.getLogger("rebuild_fingerprint_chunks")
def find_videos_needing_rebuild(session, batch_size: int) -> list[dict]:
"""查询需要重建分片指纹的视频。"""
from sqlalchemy import and_
from packages.adapters.sqlalchemy_impl.models import GeneratedVideoModel, VideoFingerprintChunkModel
# 有 video_fingerprint 的视频
has_fingerprint = GeneratedVideoModel.video_fingerprint.isnot(None)
has_fingerprint = and_(has_fingerprint, GeneratedVideoModel.video_fingerprint != "")
# 排除已有分片数据的视频
subq = session.query(VideoFingerprintChunkModel.video_id).distinct().subquery()
no_chunks = ~GeneratedVideoModel.id.in_(subq)
videos = (
session.query(GeneratedVideoModel)
.filter(and_(has_fingerprint, no_chunks))
.order_by(GeneratedVideoModel.generated_at.desc())
.limit(batch_size)
.all()
)
return [
{
"id": v.id,
"project_id": v.project_id,
"user_id": v.user_id or "",
"duration": v.duration,
}
for v in videos
]
def rebuild_one(video_info: dict, dry_run: bool = False) -> int:
"""重建单个视频的分片数据。返回写入的 chunk 数量。"""
from video_processing.dedup import VideoDeduplicator, _save_fingerprint_chunks
from worker_app.db import SessionLocal
from packages.adapters.sqlalchemy_impl.models import VideoFingerprintChunkModel
from packages.shared.storage import get_storage_service
video_id = video_info["id"]
project_id = video_info["project_id"]
user_id = video_info["user_id"]
if dry_run:
logger.info("[DRY-RUN] Would rebuild video %s (project=%s)", video_id, project_id)
return 0
session = SessionLocal()
temp_dir = tempfile.mkdtemp()
try:
# 再次检查幂等性
existing_count = (
session.query(VideoFingerprintChunkModel).filter(VideoFingerprintChunkModel.video_id == video_id).count()
)
if existing_count > 0:
logger.info("Video %s already has %d chunks, skipping", video_id, existing_count)
return 0
# 下载视频
storage_service = get_storage_service()
local_path = os.path.join(temp_dir, f"{video_id}.mp4")
storage_key = f"projects/{project_id}/generated/{video_id}/{video_id}.mp4"
storage_service.download_file(storage_key, local_path)
# 重新计算指纹
deduplicator = VideoDeduplicator()
fingerprint = deduplicator.compute_fingerprint(local_path)
# 写入分片表
_save_fingerprint_chunks(fingerprint, video_id, project_id, user_id, session)
session.commit()
chunk_count = len(fingerprint.chunks)
logger.info("Rebuilt %d chunks for video %s", chunk_count, video_id)
return chunk_count
except Exception as e:
logger.error("Failed to rebuild video %s: %s", video_id, e)
session.rollback()
return -1
finally:
session.close()
import shutil
shutil.rmtree(temp_dir, ignore_errors=True)
def main():
parser = argparse.ArgumentParser(description="存量指纹重建脚本")
parser.add_argument("--dry-run", action="store_true", help="只打印不写入")
parser.add_argument("--batch-size", type=int, default=50, help="每批处理数量(默认 50")
parser.add_argument("--total-limit", type=int, default=0, help="总处理数量限制(0=不限制)")
args = parser.parse_args()
from worker_app.db import SessionLocal
session = SessionLocal()
try:
videos = find_videos_needing_rebuild(session, args.batch_size)
logger.info("Found %d videos needing rebuild", len(videos))
if args.dry_run:
for v in videos:
logger.info("[DRY-RUN] Video %s | project=%s | duration=%.1fs", v["id"], v["project_id"], v["duration"])
return
total_chunks = 0
processed = 0
failed = 0
for v in videos:
if args.total_limit > 0 and processed >= args.total_limit:
break
result = rebuild_one(v, dry_run=False)
if result < 0:
failed += 1
else:
total_chunks += result
processed += 1
logger.info(
"Rebuild complete: processed=%d, chunks=%d, failed=%d",
processed,
total_chunks,
failed,
)
finally:
session.close()
if __name__ == "__main__":
main()
File diff suppressed because one or more lines are too long
+41 -48
View File
@@ -52,7 +52,7 @@ type AssetListResponse = {
test.describe("Core generation flow", () => {
test.describe.configure({ timeout: 360_000 })
test("walks through 6-step wizard and starts generation", async ({ page, request }) => {
test("walks through 7-step wizard and starts generation", async ({ page, request }) => {
test.setTimeout(360_000)
await routeBrowserApiToTestApi(page)
@@ -185,31 +185,30 @@ test.describe("Core generation flow", () => {
await expect(page.locator(".xx-choice-item.selected")).toBeVisible()
await page.getByRole("button", { name: "下一步" }).click()
// Step1 下一步弹出数量选择弹窗(Issue #1677 固定6步:模板→素材→配音→标题→确认生成→封面)
// 单视频流程:默认 1 个,点击「生成 1 个视频」进入步骤2
await expect(page.getByRole("heading", { name: "要生成几个视频?" })).toBeVisible({
timeout: 10_000,
})
await page.getByRole("button", { name: "生成 1 个视频" }).click()
// Step 2: select material (card grid UI)
// Step 2: select material
await expect(page.getByRole("heading", { name: /选择素材/ })).toBeVisible()
const librarySelect = page.locator("select").first()
await librarySelect.selectOption({ label: libraryName })
// 新 UI: 素材以 9:16 竖屏卡片展示,点击卡片选中
// 注意:卡片中心是播放按钮(stopPropagation 会阻止选中),所以点击左上角避开
const materialCard = page.getByTestId("material-card").filter({ hasText: sourceFileName })
await expect(materialCard).toBeVisible({ timeout: 10_000 })
await materialCard.click({ position: { x: 15, y: 15 } })
// 验证选中:卡片应出现勾选标记(用 testid 定位,避免 ✓ 字符文本匹配不稳定)
await expect(materialCard.getByTestId("material-card-check")).toBeVisible({ timeout: 5_000 })
const materialLabel = page.getByText(sourceFileName).locator("..")
await expect(materialLabel.locator("input[type='checkbox']")).toBeVisible({
timeout: 10_000,
})
await materialLabel.locator("input[type='checkbox']").check()
await page.getByRole("button", { name: "下一步" }).click()
// Step 3: voice (可选步骤,新注册用户无配音素材,直接跳过)
await expect(page.getByRole("heading", { name: /选择配音/ })).toBeVisible({ timeout: 15000 })
await page.getByRole("button", { name: "下一步" }).click()
// Step 4: title(新顺序:标题在预览之前)
// Step 4: preview — 需要先生成预览视频,才能进入下一步
await expect(page.getByRole("heading", { name: /生成预览/ })).toBeVisible({ timeout: 15000 })
// 点击"生成预览"按钮触发预览生成
await page.locator(".xx-preview-generate-btn").click()
// 等待预览生成完成(后端渲染,可能需要较长时间)
await expect(page.getByText("预览生成成功")).toBeVisible({ timeout: 300_000 })
await page.getByRole("button", { name: "下一步" }).click()
// Step 5: title
await expect(page.getByRole("heading", { name: /选择标题/ })).toBeVisible({ timeout: 15000 })
// 等待组件完全渲染
await page.waitForTimeout(2000)
@@ -221,30 +220,34 @@ test.describe("Core generation flow", () => {
const titleText = `E2E Test ${suffix}`
await titleInput.fill(titleText)
await page.getByRole("button", { name: "下一步" }).click()
// Step 4(标题+实时预览):确认生成按钮已移到标题页,点击直接创建最终渲染任务
// 等待前端实时预览就绪:未就绪时右侧 FrontendPreviewPlayer 显示「准备预览素材...」占位,
// 就绪(previewReady:素材已解析 + 模板已选中)后占位消失;否则按钮会被校验拦截弹 warning
await page
.getByText("准备预览素材")
.waitFor({ state: "detached", timeout: 30_000 })
.catch(() => {})
// Step 6: cover (默认 AI 智能选帧模式,直接下一步)
await expect(page.getByRole("heading", { name: /选择封面/ })).toBeVisible({ timeout: 15000 })
await page.getByRole("button", { name: "下一步" }).click()
// Step 7: confirm and generate
await expect(page.getByRole("heading", { name: /确认生成/ })).toBeVisible()
// Wait for generation API to be called
// 前端直接创建生成任务:POST /generation/tasks
// 确认生成走新流程:POST /tasks/{taskId}/confirm(复用预览产物)
// 或旧流程:POST /editor/generate(向后兼容)
const generatePromise = page.waitForResponse(
(response) => {
const url = response.url()
const path = new URL(url).pathname
return response.request().method() === "POST" && path.endsWith("/generation/tasks")
return (
response.request().method() === "POST" &&
(path.endsWith("/confirm") || path.endsWith("/editor/generate"))
)
},
{ timeout: 30_000 },
)
// 点击「确认生成视频」
await page.locator(".xx-btn-primary").filter({ hasText: "确认生成视频" }).first().click()
// Click generate button
await page.locator(".xx-btn-primary").filter({ hasText: "确认生成" }).first().click()
// Verify generation was triggered
// Verify generation was triggered successfully
const genResp = await generatePromise
if (!genResp.ok()) {
const body = await genResp.text()
@@ -261,29 +264,19 @@ test.describe("Core generation flow", () => {
}
expect(genData.items.length).toBeGreaterThan(0)
expect(genData.items[0].id).toBeTruthy()
// 单视频(N=1):点击「确认生成视频」后跳 Step 5「确认生成」,展示实时渲染进度
await expect(page.getByRole("heading", { name: "🎬 确认生成" })).toBeVisible({
timeout: 30_000,
})
// 等待渲染完成:进度卡变为「视频生成完成」(最长等待 3 分钟)
await expect(page.getByText("视频生成完成")).toBeVisible({ timeout: 180_000 })
// 全部完成后「下一步:选择封面」解锁,点击进入 Step 6
await page.getByRole("button", { name: /下一步:选择封面/ }).click()
await expect(page.getByRole("heading", { name: /选择封面/ })).toBeVisible({
timeout: 30_000,
})
} else {
console.log(`[E2E] Generate API returned ${genResp.status()}, wizard flow test still passes`)
// 创建失败时停留在标题页并展示错误提示
await page
.getByText(/生成失败|重新生成/)
.isVisible({ timeout: 15_000 })
.catch(() => false)
}
// Generation may fail in test env (no worker), that's OK
// Just verify the flow started - check page shows generation-related UI
await page
.getByText(/生成中|生成完成|生成失败/)
.isVisible({ timeout: 15_000 })
.catch(() => false)
// If we see progress or result, great; if not, flow still reached the end
// which is sufficient for an E2E smoke test
// Verify product library page loads (smoke: just verify page renders)
await page.goto("/app/products")
await expect(page).toHaveURL(/\/app\/products/)
+42 -53
View File
@@ -37,33 +37,14 @@ async function loginWithRetry(
})
}
async function registerWithRetry(
request: APIRequestContext,
email: string,
username: string,
password: string,
displayName: string,
maxRetries = 2,
) {
for (let i = 0; i <= maxRetries; i++) {
const response = await request.post(`${apiBase}/auth/register`, {
data: { email, password, username, display_name: displayName },
})
if (response.status() !== 429) return response
console.log(`[register] 触发限流,等待 65s 后重试 (${i + 1}/${maxRetries})`)
await new Promise((r) => setTimeout(r, 65000))
}
return request.post(`${apiBase}/auth/register`, {
data: { email, password, username, display_name: displayName },
})
}
/** 注册并登录,返回 { headers, email, username, userId } */
async function createAuthedUser(request: APIRequestContext, label: string) {
const email = uniqueEmail(label)
const username = uniqueUsername(label)
const reg = await registerWithRetry(request, email, username, PASSWORD, `E2E ${label}`)
const reg = await request.post(`${apiBase}/auth/register`, {
data: { email, password: PASSWORD, username, display_name: `E2E ${label}` },
})
expect(reg.ok(), `注册应成功: ${await reg.text()}`).toBeTruthy()
const regData = await reg.json()
@@ -197,7 +178,7 @@ test.describe("素材库流程", () => {
expect(kinds).toContain("image")
})
test("创建素材记录 — POST /assets 已废弃返回 410", async ({ request }) => {
test("创建素材记录", async ({ request }) => {
const { headers, userId } = await createAuthedUser(request, "asset-create")
const projectId = await createProject(request, headers, Date.now().toString())
@@ -213,7 +194,7 @@ test.describe("素材库流程", () => {
expect(lib.ok()).toBeTruthy()
const libData = await lib.json()
// POST /assets 已废弃,应返回 410 Gone
// 创建素材记录
const response = await request.post(`${apiBase}/assets`, {
headers,
data: {
@@ -229,9 +210,16 @@ test.describe("素材库流程", () => {
},
})
expect(response.status()).toBe(410)
expect(
response.ok(),
`创建素材应返回 2xx,实际: ${response.status()} ${await response.text()}`,
).toBeTruthy()
const data = await response.json()
expect(data.error?.code).toBe("HTTP_410")
expect(data.id, "应返回素材 ID").toBeTruthy()
expect(data.name).toContain("test_video")
expect(data.mime_type).toBe("video/mp4")
expect(data.library_id).toBe(libData.id)
})
test("列出素材", async ({ request }) => {
@@ -244,50 +232,51 @@ test.describe("素材库流程", () => {
data: {
project_id: projectId,
name: `List Lib ${Date.now()}`,
kind: "image",
kind: "video",
},
})
expect(lib.ok(), `创建素材库应成功: ${await lib.text()}`).toBeTruthy()
const libData = await lib.json()
// 通过 multipart upload 上传 2 个小图片作为测试素材
// 创建一个 1x1 的 PNG buffer
const tinyPng = Buffer.from(
"iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==",
"base64",
)
await request.post(`${apiBase}/upload`, {
// 创建 2 个素材
await request.post(`${apiBase}/assets`, {
headers,
multipart: {
data: {
project_id: projectId,
library_id: libData.id,
file: { name: "clip_a.png", mimeType: "image/png", buffer: tinyPng },
name: `clip_a_${Date.now()}.mp4`,
storage_key: `uploads/e2e/clip_a.mp4`,
mime_type: "video/mp4",
status: "ready",
uploaded_by_user_id: userId,
},
})
await request.post(`${apiBase}/upload`, {
await request.post(`${apiBase}/assets`, {
headers,
multipart: {
data: {
project_id: projectId,
library_id: libData.id,
file: { name: "clip_b.png", mimeType: "image/png", buffer: tinyPng },
name: `clip_b_${Date.now()}.mp4`,
storage_key: `uploads/e2e/clip_b.mp4`,
mime_type: "video/mp4",
status: "ready",
uploaded_by_user_id: userId,
},
})
// 列出素材(可能需要等待 ingest job 完成)
let items: any[] = []
for (let i = 0; i < 10; i++) {
const response = await request.get(`${apiBase}/assets`, {
headers,
params: { library_id: libData.id },
})
expect(response.ok(), `列出素材应返回 2xx`).toBeTruthy()
const data = await response.json()
items = data.items || []
if (items.length >= 2) break
await new Promise((r) => setTimeout(r, 2000))
}
// 列出素材
const response = await request.get(`${apiBase}/assets`, {
headers,
params: { library_id: libData.id },
})
expect(
response.ok(),
`列出素材应返回 2xx,实际: ${response.status()} ${await response.text()}`,
).toBeTruthy()
const data = await response.json()
const items = data.items || []
expect(items.length, "应至少有 2 个素材").toBeGreaterThanOrEqual(2)
})
+14 -17
View File
@@ -12,7 +12,6 @@
"@tanstack/react-query": "^5.45.0",
"antd": "^5.18.0",
"axios": "^1.7.2",
"mp4box": "^2.4.1",
"react": "^18.3.1",
"react-dom": "^18.3.1",
"react-router-dom": "^6.24.0",
@@ -1848,9 +1847,10 @@
},
"node_modules/@testing-library/dom": {
"version": "10.4.1",
"resolved": "https://registry.npmjs.org/@testing-library/dom/-/dom-10.4.1.tgz",
"resolved": "https://registry.npmmirror.com/@testing-library/dom/-/dom-10.4.1.tgz",
"integrity": "sha512-o4PXJQidqJl82ckFaXUeoAW+XysPLauYI43Abki5hABd853iMhitooc6znOnczgbTYmEP6U6/y1ZyKAIsvMKGg==",
"dev": true,
"license": "MIT",
"peer": true,
"dependencies": {
"@babel/code-frame": "^7.10.4",
@@ -1937,9 +1937,10 @@
},
"node_modules/@types/aria-query": {
"version": "5.0.4",
"resolved": "https://registry.npmjs.org/@types/aria-query/-/aria-query-5.0.4.tgz",
"resolved": "https://registry.npmmirror.com/@types/aria-query/-/aria-query-5.0.4.tgz",
"integrity": "sha512-rfT93uj5s0PRL7EzccGMs3brplhcrghnDoV26NqKhCAS1hVo+WdNsPvE/yb6ilfr5hi2MEk6d5EWJTKdxg8jVw==",
"dev": true,
"license": "MIT",
"peer": true
},
"node_modules/@types/babel__core": {
@@ -3111,9 +3112,10 @@
},
"node_modules/dom-accessibility-api": {
"version": "0.5.16",
"resolved": "https://registry.npmjs.org/dom-accessibility-api/-/dom-accessibility-api-0.5.16.tgz",
"resolved": "https://registry.npmmirror.com/dom-accessibility-api/-/dom-accessibility-api-0.5.16.tgz",
"integrity": "sha512-X7BJ2yElsnOJ30pZF4uIIDfBEVgF4XEBxL9Bxhy6dnrm5hkzqmsWHGTiHqRiITNhMyFLyAiWndIJP7Z1NTteDg==",
"dev": true,
"license": "MIT",
"peer": true
},
"node_modules/dunder-proto": {
@@ -4454,9 +4456,10 @@
},
"node_modules/lz-string": {
"version": "1.5.0",
"resolved": "https://registry.npmjs.org/lz-string/-/lz-string-1.5.0.tgz",
"resolved": "https://registry.npmmirror.com/lz-string/-/lz-string-1.5.0.tgz",
"integrity": "sha512-h5bgJWpxJNswbU7qCrV0tIKQCaS3blPDrqKWx+QxzuzL1zGUzij9XCWLrSLsJPu5t+eWA/ycetzYAO5IOMcWAQ==",
"dev": true,
"license": "MIT",
"peer": true,
"bin": {
"lz-string": "bin/bin.js"
@@ -4620,15 +4623,6 @@
"dev": true,
"license": "MIT"
},
"node_modules/mp4box": {
"version": "2.4.1",
"resolved": "https://registry.npmmirror.com/mp4box/-/mp4box-2.4.1.tgz",
"integrity": "sha512-0HGX7nXoDIX6FKLVl4a3wtYjBlwqsN3xuQC3GXzNtKp98FXUOhDSq623azsz8DG5ptd9ZXcXodDkgbdMZOjWvw==",
"license": "BSD-3-Clause",
"engines": {
"node": ">=20.8.1"
}
},
"node_modules/mrmime": {
"version": "2.0.1",
"resolved": "https://registry.npmjs.org/mrmime/-/mrmime-2.0.1.tgz",
@@ -5004,9 +4998,10 @@
},
"node_modules/pretty-format": {
"version": "27.5.1",
"resolved": "https://registry.npmjs.org/pretty-format/-/pretty-format-27.5.1.tgz",
"resolved": "https://registry.npmmirror.com/pretty-format/-/pretty-format-27.5.1.tgz",
"integrity": "sha512-Qb1gy5OrP5+zDf2Bvnzdl3jsTf1qXVMazbvCoKhtKqVs4/YK4ozX4gKQJJVyNe+cajNPn0KoC0MC3FUmaHWEmQ==",
"dev": true,
"license": "MIT",
"peer": true,
"dependencies": {
"ansi-regex": "^5.0.1",
@@ -5019,9 +5014,10 @@
},
"node_modules/pretty-format/node_modules/ansi-styles": {
"version": "5.2.0",
"resolved": "https://registry.npmjs.org/ansi-styles/-/ansi-styles-5.2.0.tgz",
"resolved": "https://registry.npmmirror.com/ansi-styles/-/ansi-styles-5.2.0.tgz",
"integrity": "sha512-Cxwpt2SfTzTtXcfOlzGEee8O+c+MmUgGrNiBcXnuWxuFJHe6a5Hz7qwhwe5OgaSYI0IJvkLqWX1ASG+cJOkEiA==",
"dev": true,
"license": "MIT",
"peer": true,
"engines": {
"node": ">=10"
@@ -5729,9 +5725,10 @@
},
"node_modules/react-is": {
"version": "17.0.2",
"resolved": "https://registry.npmjs.org/react-is/-/react-is-17.0.2.tgz",
"resolved": "https://registry.npmmirror.com/react-is/-/react-is-17.0.2.tgz",
"integrity": "sha512-w2GsyukL62IJnlaff/nRegPQR94C/XXamvMWmSHRJ4y7Ts/4ocGRmTHvOs8PSE6pB3dWOrD/nueuU5sduBsQ4w==",
"dev": true,
"license": "MIT",
"peer": true
},
"node_modules/react-refresh": {
-1
View File
@@ -23,7 +23,6 @@
"@tanstack/react-query": "^5.45.0",
"antd": "^5.18.0",
"axios": "^1.7.2",
"mp4box": "^2.4.1",
"react": "^18.3.1",
"react-dom": "^18.3.1",
"react-router-dom": "^6.24.0",
-4
View File
@@ -1,4 +0,0 @@
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64">
<rect width="64" height="64" rx="14" fill="#3b82f6"/>
<text x="32" y="44" font-size="34" text-anchor="middle">🦐</text>
</svg>

Before

Width:  |  Height:  |  Size: 194 B

+15 -31
View File
@@ -52,40 +52,24 @@ export const getAssetsByKind = async (
/**
* AI
* smart-match
*
* items
* - AssetItem id
* - { asset: AssetItem, score, breakdown }id .asset
* AssetItem[]
*/
export interface SmartMatchResult {
items: AssetItem[]
export const smartMatchAssets = async (libraryId: string): Promise<{ items: AssetItem[] }> => {
const response = await apiClient.post("/assets/smart-match", {
library_id: libraryId,
})
return response.data
}
interface SmartMatchWrappedItem {
asset?: AssetItem
id?: string
score?: number
breakdown?: unknown
}
export const smartMatchAssets = async (
libraryId: string,
limit?: number,
): Promise<SmartMatchResult> => {
const payload: Record<string, unknown> = { library_id: libraryId }
if (limit && limit > 0) payload.limit = limit
const response = await apiClient.post("/assets/smart-match", payload)
const rawItems: SmartMatchWrappedItem[] = response.data?.items ?? []
const items = rawItems
.map((it) =>
// 包装结构 { asset: {...} } 优先解包;否则视其本身为扁平 AssetItem
it?.asset && typeof it.asset === "object" && "id" in it.asset
? it.asset
: (it as unknown as AssetItem),
)
.filter((it): it is AssetItem => !!it && typeof it.id === "string" && it.id.length > 0)
return { items }
/** 创建素材(上传文件后调用,附带 metadata) */
export const createAsset = async (data: {
library_id: string
name: string
storage_key: string
mime_type: string
metadata?: AssetMetadata
}): Promise<AssetItem> => {
const response = await apiClient.post("/assets", data)
return response.data
}
/** 更新素材(名称、metadata 等) */
+2 -7
View File
@@ -2,17 +2,12 @@
* API
*/
import apiClient from "../client"
import { getOrCreateDefaultProject } from "../projects"
import type { AssetDiagnosis } from "./types"
/** 获取素材诊断信息(可选 asset_id 查单素材,否则全局诊断) */
export const getAssetDiagnosis = async (
assetId?: string,
projectId?: string,
): Promise<AssetDiagnosis> => {
const pid = projectId ?? (await getOrCreateDefaultProject()).id
export const getAssetDiagnosis = async (assetId?: string): Promise<AssetDiagnosis> => {
const params: Record<string, string> = {}
if (assetId) params.asset_id = assetId
const response = await apiClient.get(`/projects/${pid}/asset-diagnosis`, { params })
const response = await apiClient.get("/asset-diagnosis", { params })
return response.data
}

Some files were not shown because too many files have changed in this diff Show More