Merge branch 'develop' into feat/title-drag-position

.ci-retigger-marker

@@ -1 +0,0 @@
-CI re-trigger after runner add-host/DNS fix. This file is harmless and not referenced.

.gitea/workflows/ci-base-image.yml

@@ -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"

.gitea/workflows/ci-canary.yml

@@ -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

.gitea/workflows/ci-pipeline.yml

@@ -20,7 +20,6 @@ on:
         default: "手动触发 - CI漏触发补跑"
 permissions:
   contents: read
-  pull-requests: read
 concurrency:
   group: ci-pipeline-${{ gitea.ref }}
   cancel-in-progress: true
@@ -89,22 +88,9 @@ jobs:
         GITHUB_TOKEN: ${{ github.token }}
       run: |
         set -eu
-        # 优先用 git diff 判断 PR 改动范围（比 API 稳定）
         PR_NUMBER=$(echo "$GITHUB_REF" | sed 's|refs/pull/||; s|/.*||')
-        if command -v git >/dev/null 2>&1 && [ -d .git ]; then
-          FILES=$(git diff --name-only origin/develop...HEAD 2>/dev/null || true)
-        fi
-        if [ -z "${FILES:-}" ]; then
-          # fallback 到 API
-          API_URL="${GITHUB_API_URL}/repos/${GITHUB_REPOSITORY}/pulls/${PR_NUMBER}/files?limit=300"
-          FILES=$(curl -sf -H "Authorization: token ${GITHUB_TOKEN}" "$API_URL" | python3 -c "import sys,json; [print(f['filename']) for f in json.load(sys.stdin)]" 2>/dev/null || true)
-        fi
-        if [ -z "${FILES:-}" ]; then
-          echo "⚠️ 无法获取变更文件列表，保守运行完整 CI"
-          echo "skip_backend=false" >> $GITHUB_OUTPUT
-          echo "skip_frontend=false" >> $GITHUB_OUTPUT
-          exit 0
-        fi
+        API_URL="${GITHUB_API_URL}/repos/${GITHUB_REPOSITORY}/pulls/${PR_NUMBER}/files?limit=300"
+        FILES=$(curl -s -H "Authorization: token ${GITHUB_TOKEN}" "$API_URL" | python3 -c "import sys,json; [print(f['filename']) for f in json.load(sys.stdin)]")
         FRONTEND_COUNT=$(echo "$FILES" | grep -c '^apps/web/' || true)
         BACKEND_COUNT=$(echo "$FILES" | grep -cv '^apps/web/' || true)
         TOTAL=$(echo "$FILES" | grep -cv '^$' || true)
@@ -196,7 +182,7 @@ jobs:
     - name: Run style checks
       shell: bash
       run: bash scripts/ci/validate_style.sh
-    - name: Auto-fix formatting (black + isort + ruff)
+    - name: Auto-fix formatting (black + isort)
       if: failure()
       shell: sh
       env:
@@ -297,7 +283,6 @@ jobs:
           sleep 5
         done
     - name: Run security checks
-      continue-on-error: true  # Security scan is advisory; runner failure must not block deploy
       shell: bash
       env:
         GITHUB_TOKEN: ${{ github.token }}
@@ -348,7 +333,7 @@ jobs:
       PIP_NO_CACHE_DIR: ''
       DATABASE_URL: postgresql+psycopg://postgres:postgres@host.docker.internal:5432/xiaoxia_saas
       USE_IN_MEMORY_DB: 'false'
-      CI_USE_SHARED_PG: 'false'
+      CI_USE_SHARED_PG: 'true'
     permissions:
       contents: read
     steps:
@@ -532,7 +517,7 @@ jobs:
     env:
       DATABASE_URL: postgresql+psycopg://postgres:postgres@host.docker.internal:5432/xiaoxia_saas
       USE_IN_MEMORY_DB: 'false'
-      CI_USE_SHARED_PG: 'false'
+      CI_USE_SHARED_PG: 'true'
       OSS_ACCESS_KEY_ID: placeholder
       OSS_ACCESS_KEY_SECRET: placeholder
       OSS_BUCKET_NAME: xiaoxia-autocut
@@ -827,6 +812,9 @@ jobs:
         CACHE_REF="${REGISTRY}/${{ matrix.cache_name }}:develop"
 
         EXTRA_BUILD_ARGS="APP_VERSION=\"${GITHUB_SHA}\""
+        if [ "${{ matrix.service }}" = "web" ]; then
+          EXTRA_BUILD_ARGS="$EXTRA_BUILD_ARGS NGINX_CONF=infra/docker/nginx-staging.conf"
+        fi
 
         # Worker 与 API/Web 统一走持久 builder（ci-builder-persist），共享宿主机层缓存
         NO_CACHE_FLAG=""
@@ -1023,6 +1011,9 @@ jobs:
         CACHE_REF="${REGISTRY}/${{ matrix.cache_name }}:${GITHUB_REF_NAME}"
 
         EXTRA_BUILD_ARGS="APP_VERSION=\"${GITHUB_SHA}\""
+        if [ "${{ matrix.service }}" = "web" ]; then
+          EXTRA_BUILD_ARGS="$EXTRA_BUILD_ARGS NGINX_CONF=infra/docker/nginx-staging.conf"
+        fi
 
         NO_CACHE_FLAG=""
         for i in 1 2 3; do
@@ -1178,33 +1169,6 @@ jobs:
       run: |
         set +e
         NOTIFY_MODE=start JOB_NAME="Deploy Staging" python3 scripts/ci_notify.py
-    - name: Render .env from template
-      shell: sh
-      env:
-        STAGING_DATABASE_URL: ${{ secrets.STAGING_DATABASE_URL }}
-        STAGING_REDIS_URL: ${{ secrets.STAGING_REDIS_URL }}
-        STAGING_CELERY_BROKER_URL: ${{ secrets.STAGING_CELERY_BROKER_URL }}
-        STAGING_CELERY_RESULT_BACKEND: ${{ secrets.STAGING_CELERY_RESULT_BACKEND }}
-        STAGING_JWT_SECRET_KEY: ${{ secrets.STAGING_JWT_SECRET_KEY }}
-        STAGING_MINIO_ENDPOINT: ${{ secrets.STAGING_MINIO_ENDPOINT }}
-        STAGING_MINIO_ACCESS_KEY: ${{ secrets.STAGING_MINIO_ACCESS_KEY }}
-        STAGING_MINIO_SECRET_KEY: ${{ secrets.STAGING_MINIO_SECRET_KEY }}
-        STAGING_MINIO_BUCKET: ${{ secrets.STAGING_MINIO_BUCKET }}
-        OSS_ACCESS_KEY_ID: ${{ secrets.OSS_ACCESS_KEY_ID }}
-        OSS_ACCESS_KEY_SECRET: ${{ secrets.OSS_ACCESS_KEY_SECRET }}
-        COSYVOICE_API_KEY: ${{ secrets.COSYVOICE_API_KEY }}
-        DASHSCOPE_API_KEY: ${{ secrets.DASHSCOPE_API_KEY }}
-        MEDIAKIT_API_KEY: ${{ secrets.MEDIAKIT_API_KEY }}
-        WECHAT_APP_ID: ${{ secrets.WECHAT_APP_ID }}
-        WECHAT_APP_SECRET: ${{ secrets.WECHAT_APP_SECRET }}
-      run: |
-        set -eu
-        echo "Rendering .env from template + secrets..."
-        bash scripts/render_env.sh staging
-        echo "✅ .env rendered (file contains secrets, not printed to log)"
-        # 验证文件存在且非空
-        test -s .env.rendered
-        echo "✅ .env.rendered validated ($(wc -l < .env.rendered) lines)"
     - name: Docker login to Registry
       shell: sh
       env:
@@ -1277,31 +1241,9 @@ jobs:
         ssh -p "$staging_port" -i "$key_path" -o StrictHostKeyChecking=no "${staging_user}@${staging_host}" "echo SSH_CONNECTION_OK && hostname"
         echo "SSH connection verified"
 
-        # 配置 Diff 检查：下载服务器当前 .env，对比渲染结果，检测漂移
-        echo "Running config diff check..."
-        scp -P "$staging_port" -i "$key_path" -o StrictHostKeyChecking=no \
-          "${staging_user}@${staging_host}:/var/lib/xiaoxia-saas-staging/.env" .env.current 2>/dev/null \
-          || touch .env.current  # 首次部署时文件不存在，创建空文件
-        bash scripts/config_diff_check.sh .env.rendered .env.current
-        rm -f .env.current
-        echo "Config diff check done"
-
-        # 上传渲染后的 .env 到服务器（替代服务器上旧的 .env）
-        echo "Uploading rendered .env to staging server..."
-        # 备份旧 .env
-        ssh -p "$staging_port" -i "$key_path" -o StrictHostKeyChecking=no "${staging_user}@${staging_host}" \
-          "cp -f /var/lib/xiaoxia-saas-staging/.env /var/lib/xiaoxia-saas-staging/.env.bak.\$(date +%Y%m%d%H%M%S) 2>/dev/null || true"
-        # 上传新 .env
-        scp -P "$staging_port" -i "$key_path" -o StrictHostKeyChecking=no .env.rendered \
-          "${staging_user}@${staging_host}:/var/lib/xiaoxia-saas-staging/.env"
-        echo "✅ .env uploaded to staging server"
-
         # 通过环境变量传递凭证，避免命令行引号转义问题
         cat scripts/ci_staging_deploy.sh | ssh -p "$staging_port" -i "$key_path" -o StrictHostKeyChecking=no "${staging_user}@${staging_host}" "IMAGE_TAG=${GITHUB_SHA} ACR_USERNAME=${ACR_USERNAME} ACR_PASSWORD=${ACR_PASSWORD} sh"
 
-        # 清理 CI runner 上的渲染文件
-        rm -f .env.rendered
-
     - name: Staging health check + auto rollback
       if: success()
       shell: sh
@@ -1472,7 +1414,7 @@ jobs:
       - unit-tests
       - frontend-lint
       - frontend-unit-test
-    if: github.event_name == 'push' && github.ref_name == 'main' && !failure() && !cancelled()
+    if: startsWith(github.ref, 'refs/tags/v') || (github.event_name == 'push' && github.ref_name == 'main')
     strategy:
       fail-fast: false
       matrix:
@@ -1556,11 +1498,18 @@ jobs:
         set -eu
         REGISTRY="xiaoxia-registry.cn-hangzhou.cr.aliyuncs.com/xiaoxiakeji"
         # 根据ref类型设置镜像标签：tag用版本号，分支用分支名+sha
-        TAG_NAME="${GITHUB_SHA}"
+        if [[ "$GITHUB_REF" == refs/tags/* ]]; then
+          TAG_NAME="${GITHUB_REF_NAME}"
+        else
+          TAG_NAME="${GITHUB_REF_NAME}-${GITHUB_SHA::8}"
+        fi
         IMAGE_TAG="${REGISTRY}/${{ matrix.image_name }}:${TAG_NAME}"
         CACHE_REF="${REGISTRY}/${{ matrix.cache_name }}:main"
 
         EXTRA_BUILD_ARGS="APP_VERSION=\"${TAG_NAME}\""
+        if [ "${{ matrix.service }}" = "web" ]; then
+          EXTRA_BUILD_ARGS="$EXTRA_BUILD_ARGS NGINX_CONF=infra/docker/nginx-production.conf"
+        fi
 
         # Docker build 带重试：失败自动重试2次，第2次重试加--no-cache
         NO_CACHE_FLAG=""
@@ -1615,7 +1564,7 @@ jobs:
     concurrency:
       group: deploy-production-${{ gitea.ref }}
       cancel-in-progress: false
-    if: github.event_name == 'push' && github.ref_name == 'main'
+    if: startsWith(github.ref, 'refs/tags/v')
     needs:
     - build-production
     steps:
@@ -1688,7 +1637,7 @@ jobs:
         echo "SSH connection verified"
 
         # 通过环境变量传递凭证，避免命令行引号转义问题
-        cat scripts/ci_production_deploy.sh | ssh -p "$production_port" -i "$key_path" -o StrictHostKeyChecking=no "${production_user}@${production_host}" "IMAGE_TAG=${GITHUB_SHA} ACR_USERNAME=${ACR_USERNAME} ACR_PASSWORD=${ACR_PASSWORD} sh"
+        cat scripts/ci_production_deploy.sh | ssh -p "$production_port" -i "$key_path" -o StrictHostKeyChecking=no "${production_user}@${production_host}" "IMAGE_TAG=${GITHUB_REF_NAME} ACR_USERNAME=${ACR_USERNAME} ACR_PASSWORD=${ACR_PASSWORD} sh"
 
     - name: Production health check + auto rollback
       if: success()
@@ -1747,7 +1696,7 @@ jobs:
     name: Production Browser E2E
     runs-on: runtime-builder
     timeout-minutes: 15
-    # if: removed - runs after deploy-production succeeds
+    if: startsWith(github.ref, 'refs/tags/v')
     needs: deploy-production
     steps:
     - name: Checkout code
@@ -2067,11 +2016,6 @@ jobs:
               echo "  ⏳ $name: pending（审查中，暂不阻塞）"
               continue
             fi
-            # Security scan cancelled/failed时不阻塞部署（runner故障不应卡住流水线）
-            if [ "$name" = "validate-security" ] && { [ "$result" = "cancelled" ] || [ "$result" = "failure" ]; }; then
-              echo "  ⚠️  $name: $result（安全扫描为非阻塞项，不卡住部署）"
-              continue
-            fi
             check_job "$name" "$result"
           done
 

.gitea/workflows/debug-web-v2.yml

@@ -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

.gitea/workflows/playwright-base-image.yml

@@ -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"

.gitea/workflows/pr-auto-scan.yml

@@ -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: "*/15 * * * *"  # 每10分钟扫描一次（脚本自带240s墙钟上限，降频减负）
   workflow_dispatch:
 
 permissions:

.gitea/workflows/pr-automation.yml

@@ -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  # 长等待模式：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

.gitignore

@@ -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

alembic/versions/061_add_sort_order_to_template_categories.py

@@ -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")

alembic/versions/062_readd_edit_plan_id_to_generation_tasks.py

@@ -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")

alembic/versions/063_add_video_fingerprint_chunks.py

@@ -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")

alembic/versions/064_add_match_count_visual_similarity.py

@@ -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")

alembic/versions/065_add_visual_similarity_match_count_duplication.py

@@ -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")

alembic/versions/066_asset_client_upload_id_ingest_job_asset_id.py

@@ -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 token（complete 去重）
-- ingest_jobs.asset_id：complete 阶段创建的占位 asset id（worker 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")

alembic/versions/067_celery_task_id_revoke.py

@@ -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")

alembic/versions/068_user_profile_completed.py

@@ -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")

alembic/versions/069_project_is_default_idempotent.py

@@ -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")

alembic/versions/070_add_scripts_table.py

@@ -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")

alembic/versions/071_add_lipsync_jobs_table.py

@@ -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")

alembic/versions/072_add_ai_avatar_render_jobs_table.py

@@ -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")

alembic/versions/073_add_lipsync_tts_fields.py

@@ -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")

alembic/versions/074_ai_avatar_render_script_id_optional.py

@@ -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,
-        )

alembic/versions/075_add_sentence_timings.py

@@ -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")

apps/api/app/api/router.py

@@ -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"],
-)

apps/api/app/api/routes/ai_avatar_render.py

@@ -1,259 +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,
-    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 /{job_id}/smart-cover — 从最终成片智能抽封面（步骤②）────────
-
-
-@router.post("/{job_id}/smart-cover", response_model=SmartCoverResponse)
-def generate_render_smart_cover(
-    job_id: str,
-    current_user: AuthenticatedUser = Depends(get_current_user),
-    db: Session = Depends(get_db_session),
-):
-    """从最终渲染成片智能抽帧生成封面（MediaKit 抽帧 + 评分选最佳帧 + 转存 OSS）.
-
-    - 必须等渲染任务 completed 后才可调用（否则返回 400）
-    - 生成成功后自动更新 render_job 的 cover_config 与 output_cover_url
-    """
-    from app.services.ai_avatar_render_service import AiAvatarRenderService
-
-    svc = AiAvatarRenderService(db)
-    job = svc.get_render_job(job_id, current_user.user.id)
-    if job is None:
-        raise HTTPException(status_code=404, detail="渲染任务不存在")
-    if job.status != "completed":
-        raise HTTPException(status_code=400, detail="请先完成视频生成")
-    video_url = (job.output_video_url or "").strip()
-    if not video_url:
-        raise HTTPException(status_code=400, detail="渲染成片视频 URL 为空")
-
-    try:
-        # 从最终成片抽帧，帧本身已含标题/B-roll，直接转存 OSS
-        cover_url = generate_smart_cover(video_url, job_id=job_id, max_frames=5)
-    except Exception as exc:
-        logger.error(
-            "渲染成片智能封面生成异常: user=%s render_id=%s video_url=%s err=%s",
-            current_user.user.id,
-            job_id,
-            video_url[:80],
-            exc,
-            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",
-        )
-
-    # 更新 render_job 的封面字段（异步写入 DB；失败不影响返回）
-    try:
-        job.cover_config = {
-            **(job.cover_config if isinstance(job.cover_config, dict) else {}),
-            "mode": "auto_frame",
-            "url": cover_url,
-        }
-        job.output_cover_url = cover_url
-        job.updated_at = datetime.now(timezone.utc)
-        db.commit()
-    except Exception as exc:
-        logger.warning("更新 render_job 封面字段失败（不影响返回）: job_id=%s err=%s", job_id, exc)
-
-    logger.info(
-        "渲染成片智能封面生成成功: user=%s render_id=%s cover_url=%s",
-        current_user.user.id,
-        job_id,
-        cover_url[:120],
-    )
-    return SmartCoverResponse(cover_url=cover_url, status="completed")

apps/api/app/api/routes/asset_libraries.py

@@ -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)

apps/api/app/api/routes/assets.py

@@ -290,7 +290,7 @@ 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:

apps/api/app/api/routes/auth.py

@@ -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 strip（validator）
-    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 ====================
 
 

apps/api/app/api/routes/chunked_upload.py

@@ -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"

apps/api/app/api/routes/duplication.py

@@ -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,

apps/api/app/api/routes/generation_cover.py

@@ -75,86 +75,6 @@ class GenerateCoverResponse(BaseModel):
 # ── Route ────────────────────────────────────────────────────────────────
 
 
-
-def _select_best_frame_from_snapshots(
-    snapshots: list[dict], plan_id: str
-) -> str:
-    """从 MediaKit 抽帧结果中，通过质量评分选出最佳帧。
-
-    降级策略：cv2 不可用或评分失败时，返回第一帧。
-
-    Args:
-        snapshots: MediaKit 返回的帧列表 [{"image_url": str, ...}, ...]
-        plan_id: 计划 ID（日志用）
-
-    Returns:
-        最佳帧的 image_url，或空字符串
-    """
-    if not snapshots:
-        return ""
-    if len(snapshots) == 1:
-        return snapshots[0].get("image_url") or snapshots[0].get("url") or ""
-
-    try:
-        import tempfile
-
-        import httpx
-
-        from packages.shared.cover_frame_scorer import score_frames
-
-        scored_candidates = []
-        for snap in snapshots:
-            url = snap.get("image_url") or snap.get("url") or ""
-            if not url:
-                continue
-            # 下载帧到临时文件进行评分
-            try:
-                resp = httpx.get(url, timeout=15, follow_redirects=True)
-                resp.raise_for_status()
-                with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as tmp:
-                    tmp.write(resp.content)
-                    tmp_path = tmp.name
-                scored_candidates.append({"image_path": tmp_path, "url": url})
-            except Exception:
-                # 下载失败的帧跳过，给默认低分
-                scored_candidates.append({"image_path": None, "url": url, "score": 0.0})
-
-        if not scored_candidates:
-            return snapshots[0].get("image_url") or snapshots[0].get("url") or ""
-
-        scored = score_frames(scored_candidates)
-        best = scored[0] if scored else None
-        best_url = best.get("url", "") if best else ""
-        best_score = best.get("score", 0.0) if best else 0.0
-        logger.info(
-            "[封面生成] 帧质量评分完成: plan_id=%s candidates=%d best_score=%.1f",
-            plan_id,
-            len(scored_candidates),
-            best_score,
-        )
-
-        # 清理临时文件
-        for c in scored_candidates:
-            path = c.get("image_path")
-            if path:
-                try:
-                    from pathlib import Path
-
-                    Path(path).unlink(missing_ok=True)
-                except Exception:
-                    pass
-
-        return best_url
-
-    except Exception:
-        logger.warning(
-            "[封面生成] 帧质量评分失败，使用第一帧: plan_id=%s",
-            plan_id,
-            exc_info=True,
-        )
-        return snapshots[0].get("image_url") or snapshots[0].get("url") or ""
-
-
 def _persist_cover_frame(
     frame_url: str,
     plan_id: str,
@@ -593,7 +513,7 @@ def generate_cover(
         if generation_task_id:
             try:
                 task = gen_task_repo.get(generation_task_id)
-                if task and getattr(task, "cover_url", ""):  # type: ignore[arg-type]
+                if task and getattr(task, "cover_url", ""):
                     cover_url_from_task = task.cover_url
                     logger.info(
                         "[封面生成] 统一管道封面(步骤A-direct): plan_id=%s task_id=%s url=%s",
@@ -618,7 +538,7 @@ def generate_cover(
                     gv_task_id = getattr(gv, "generation_task_id", "") or ""
                     if gv_task_id:
                         task_a2 = gen_task_repo.get(gv_task_id)
-                        if task_a2 and getattr(task_a2, "cover_url", ""):  # type: ignore[arg-type]
+                        if task_a2 and getattr(task_a2, "cover_url", ""):
                             cover_url_from_task = task_a2.cover_url
                             logger.info(
                                 "[封面生成] 封面(步骤A2-video-task): plan_id=%s video_id=%s url=%s",
@@ -732,13 +652,13 @@ def generate_cover(
                     snapshots = mk_client.extract_frames(
                         video_url=primary_video_url,
                         strategy="SpecifiedFrames",
-                        max_frames=5,  # 抽 5 帧，通过质量评分选最佳
+                        max_frames=1,
                         poll_interval=2.0,
                         max_poll_attempts=5,
                         max_retries=0,
                     )
                     if snapshots:
-                        raw = _select_best_frame_from_snapshots(snapshots, plan_id)
+                        raw = snapshots[0].get("image_url") or snapshots[0].get("url") or ""
                         if raw:
                             cover_url_from_task = _persist_cover_frame(raw, plan_id)
                             logger.info(
@@ -795,13 +715,13 @@ def generate_cover(
                         snapshots = mk_client.extract_frames(
                             video_url=src_url,
                             strategy="SpecifiedFrames",
-                            max_frames=5,  # 抽 5 帧，通过质量评分选最佳
+                            max_frames=1,
                             poll_interval=2.0,
                             max_poll_attempts=5,
                             max_retries=0,
                         )
                         if snapshots:
-                            raw = _select_best_frame_from_snapshots(snapshots, plan_id)
+                            raw = snapshots[0].get("image_url") or snapshots[0].get("url") or ""
                             if raw:
                                 cover_url_from_task = _persist_cover_frame(
                                     raw,
@@ -827,7 +747,7 @@ def generate_cover(
 
         if cover_url_from_task:
             # 标题已在预览视频渲染时烧录（ASS字幕），封面帧自然包含标题
-            cover_data: dict[str, object] = {  # type: ignore[no-redef]
+            cover_data = {
                 "type": "ai_frame",
                 "image_url": cover_url_from_task,
                 "frame_time": 0.0,

apps/api/app/api/routes/generation_preview.py

@@ -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
@@ -335,11 +273,14 @@ def create_preview_generation_task(
                 w, h = int(parts[0]), int(parts[1])
                 base = 1920
                 if w < h:
+                    # 竖屏
                     output_width = round(base * w / h)
                     output_height = base
                 else:
+                    # 横屏
                     output_width = base
                     output_height = round(base * h / w)
+                # 对齐到偶数
                 output_width = output_width - output_width % 2
                 output_height = output_height - output_height % 2
             except (ValueError, ZeroDivisionError):
@@ -348,70 +289,42 @@ def create_preview_generation_task(
 
     logger.info(
         "[预览生成] 分辨率: video_ratio=%s → %s (%dx%d)",
-        video_ratio,
-        resolution,
-        output_width,
-        output_height,
+        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 {}
+
+    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=resolution,
+                bgm_config=request.bgm_config or {},
+                auto_retry_enabled=False,
+                auto_retry_max=0,
+                is_preview=True,
+                title_config=title_config,
+                output_width=output_width,
+                output_height=output_height,
             )
-
-            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 +332,93 @@ 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]:
+    # 关联编辑计划：如果前端未传 source_edit_plan_id，通过 template_id + user_id 查找
+    if not task.source_edit_plan_id and request.template_id:
         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,
+            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:
+                    task.source_edit_plan_id = _p.id
+                    generation_task_repository.update(task)
+                    logger.info(
+                        "[预览生成] 自动关联编辑计划: task_id=%s plan_id=%s",
+                        task.id,
+                        _p.id,
+                    )
+                    break
         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
+            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 _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
+    # 每条预览都关联独立克隆 plan：多预览前端为 N 次并发调用，若共用同一 plan
+    # 则 N 条预览片段完全相同；克隆时片段起点按持久化历史区间重算（含受控复用），
+    # 保证各预览版本内容不同
+    if task.source_edit_plan_id:
         try:
             from app.services.edit_plan_service import EditPlanService
 
             _plan_svc = EditPlanService(db)
-            variant_plan = _plan_svc.clone_plan_for_variant(
-                source_plan_id,
+            _preview_plan = _plan_svc.clone_plan_for_variant(
+                task.source_edit_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]
+            task.source_edit_plan_id = _preview_plan.id
             generation_task_repository.update(task)
-        # 回写变体标题到 plan config（worker 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,
+            logger.info(
+                "[预览生成] 预览关联独立克隆 plan: task_id=%s clone_plan_id=%s",
+                task.id,
+                _preview_plan.id,
             )
-            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):
+        except Exception as clone_err:
+            # 不退回共用原 plan（否则多条预览内容相同，违反去重诉求）：
+            # 标记任务失败并中断，前端可重新发起预览
+            logger.error(
+                "[预览生成] 克隆预览变体 plan 失败，任务标记失败: task_id=%s error=%s",
+                task.id,
+                clone_err,
+                exc_info=True,
+            )
+            _mark_task_failed(generation_task_repository, task, "预览变体计划创建失败")
             raise HTTPException(
-                status_code=429,
-                detail=build_rate_limit_detail(rate_limit_exc, generation_task_repository, scope="user"),
-            )
+                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 clone_err
+
+    # 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)

apps/api/app/api/routes/generation_tasks.py

@@ -10,7 +10,6 @@ from app.core.task_enqueue import (
     USER_PENDING_LIMIT,
     GlobalQueueFull,
     UserPendingLimitExceeded,
-    build_rate_limit_detail,
     safe_enqueue_generation_task,
 )
 from app.dependencies import (
@@ -48,39 +47,6 @@ 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,
@@ -126,9 +92,6 @@ 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),
     )
 
 
@@ -147,7 +110,6 @@ 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。
 
@@ -155,8 +117,6 @@ def _select_assets_from_library(
         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。
 
     Returns:
         选中的素材 ID 列表
@@ -169,15 +129,15 @@ def _select_assets_from_library(
     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,
@@ -202,7 +162,7 @@ def _writeback_edit_plan_config(
         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 {}
@@ -214,12 +174,10 @@ def _writeback_edit_plan_config(
                     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,
+                        plan_id, old_title_text, new_title_text,
                     )
             merged["title_config"] = title_config
-
+        
         plan_model.config = merged
         db.commit()
         logger.info(
@@ -427,7 +385,7 @@ def create_generation_task(
 
     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 +404,12 @@ 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
@@ -460,218 +418,66 @@ 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 0：clone 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_id（variant_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）。
+    # 批量生成时每个任务关联独立克隆 plan（片段起点重算），
+    # 禁止 N 条任务共用同一 source_edit_plan_id 导致片段一模一样。
+    # 在创建任何任务【之前】预克隆全部变体：克隆失败直接中断（此时无脏数据），
+    # 绝不静默退回共用源 plan（否则批量视频内容重复，违反去重诉求）。
     variant_plan_ids: list[str] = []
-    if count > 1:
+    if count > 1 and request.source_edit_plan_id:
         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,
+        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.clone_plan_for_variant(
+                        request.source_edit_plan_id,
+                        created_by_user_id=user_id,
+                        name_suffix=f"批量{task_index + 1}",
                     )
-                    .order_by(EditPlanModel.created_at.desc())
-                    .first()
+                    break
+                except Exception as clone_err:  # noqa: PERF203
+                    last_err = clone_err
+                    logger.warning(
+                        "[生成任务] 克隆变体 plan 失败(尝试%d/2): source=%s error=%s",
+                        _attempt + 1,
+                        request.source_edit_plan_id,
+                        clone_err,
+                        exc_info=True,
+                    )
+            if variant is None:
+                logger.error(
+                    "[生成任务] 克隆变体 plan 重试仍失败，中断批量创建: source=%s",
+                    request.source_edit_plan_id,
+                    exc_info=last_err,
                 )
-                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）")
+                    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)
 
     try:
         for task_index in range(count):
-            # #1749：count>1 时每个变体（含变体0）都关联各自独立 plan（clone/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)
+            # 第 1 条复用源 plan（保留用户编辑结果）；其余使用预克隆的独立变体 plan。
+            # 无源 plan（source_edit_plan_id 为空）时无可克隆对象，variant_plan_ids
+            # 为空列表：各任务走自身随机选片流程，不做索引访问（防 IndexError）
+            effective_plan_id = request.source_edit_plan_id
+            if task_index > 0 and variant_plan_ids:
+                effective_plan_id = variant_plan_ids[task_index - 1]
 
             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,
                     asset_select_mode=request.asset_select_mode,
@@ -685,28 +491,14 @@ 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,
+                    title_config=request.title_config or {},
                 )
             )
-            # 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。",
-                    )
+                # 必须在 enqueue 之前执行，避免 worker 读取时 source_edit_plan_id 为空（竞态条件）
                 if not task.source_edit_plan_id and request.template_id:
                     try:
                         from packages.adapters.sqlalchemy_impl.models import EditPlanModel
@@ -737,13 +529,13 @@ def create_generation_task(
 
                 # 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。
+                # 只在首个任务时回写一次，避免批量生成时循环覆盖。
                 _effective_plan_id = task.source_edit_plan_id
-                if _effective_plan_id:
+                if _effective_plan_id and len(created_tasks) == 0:
                     _writeback_edit_plan_config(
                         plan_id=_effective_plan_id,
                         task_id=task.id,
-                        title_config=variant_title_config,
+                        title_config=request.title_config,
                         db=db,
                     )
 
@@ -763,7 +555,7 @@ 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 +563,7 @@ 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:
@@ -873,6 +665,7 @@ 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,
@@ -896,15 +689,15 @@ 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 +779,12 @@ 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 +797,7 @@ 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", ""),
@@ -1037,15 +819,15 @@ 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)
 

apps/api/app/api/routes/generation_variant_plans.py

@@ -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 → 400（variant_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))

apps/api/app/api/routes/ingest_jobs.py

@@ -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,

apps/api/app/api/routes/lipsync.py

@@ -1,235 +0,0 @@
-"""对口型 API 路由 — #1796 MediaKit 对口型, #1809 参数调整, #1845 配音前置.
-
-接口：
-  POST   /api/v1/lipsync/jobs          提交对口型任务（支持 TTS/直传/预合成 三种模式）
-  GET    /api/v1/lipsync/jobs          任务列表
-  GET    /api/v1/lipsync/jobs/{id}     任务详情
-  POST   /api/v1/lipsync/jobs/{id}/refresh  刷新任务状态
-  POST   /api/v1/lipsync/jobs/{id}/cancel   取消任务
-  POST   /api/v1/lipsync/tts-preview   #1845 步骤1 TTS 预合成（同步 HTTP，~2-3s）
-"""
-
-from __future__ import annotations
-
-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 (
-    AiAvatarTtsPreviewRequest,
-    AiAvatarTtsPreviewResponse,
-    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
-    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.
-
-    三种模式：
-    - TTS 直生（旧版/降级）：传 {video_url, voice_id, script_text, speed?, emotion?}，
-      后端 dispatch Celery 异步任务。
-    - 直接音频：传 {video_url, audio_url}，后端同步下载+算timings+提交MediaKit。
-    - 预合成音频（#1845 新主路径）：传 {video_url, audio_url, audio_duration, sentence_timings}，
-      后端同步ffprobe+写入timings+直接提交MediaKit（~2-3s）。
-    """
-    try:
-        job = svc.create_job(
-            user_id=current_user.user.id,
-            video_url=body.video_url,
-            audio_url=body.audio_url,
-            audio_duration=body.audio_duration,
-            sentence_timings=body.sentence_timings,
-            voice_id=body.voice_id,
-            script_text=body.script_text,
-            speed=body.speed,
-            emotion=body.emotion,
-            enable_video_loop=body.enable_video_loop,
-            project_id=body.project_id,
-        )
-    except ValueError as exc:
-        raise HTTPException(status_code=400, detail=str(exc)) from exc
-    except MediaKitError as exc:
-        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:
-        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
-
-
-# ── POST /tts-preview — #1845 步骤1 TTS 预合成 ──────────────────────────
-
-
-@router.post("/tts-preview", response_model=AiAvatarTtsPreviewResponse)
-def preview_tts(
-    body: AiAvatarTtsPreviewRequest,
-    current_user: AuthenticatedUser = Depends(get_current_user),
-    svc: LipsyncService = Depends(_get_service),
-):
-    """步骤1「生成配音」同步 TTS 预合成.
-
-    同步执行 TTS 合成 → 下载音频 → ffprobe 时长 → 句子时间戳计算，
-    不创建 LipsyncJob、不转存 OSS，直接返回 CosyVoice 临时 URL（~24h 有效）。
-    耗时约 2-3 秒。
-    """
-    try:
-        result = svc.preview_tts(
-            user_id=current_user.user.id,
-            voice_id=body.voice_id,
-            script_text=body.script_text,
-            speed=body.speed,
-            emotion=body.emotion,
-        )
-    except MediaKitError as exc:
-        status_code = 400
-        if exc.code in ("VoiceForbidden",):
-            status_code = 403
-        elif exc.code in ("TTSNoAudio",):
-            status_code = 502
-        raise HTTPException(
-            status_code=status_code,
-            detail={
-                "code": exc.code,
-                "message": str(exc),
-            },
-        ) from exc
-    except Exception as exc:
-        logger.error("TTS 预合成异常: %s", exc, exc_info=True)
-        raise HTTPException(
-            status_code=400,
-            detail=f"TTS 合成失败: {exc}",
-        ) from exc
-
-    return result
-
-
-# ── GET /jobs — 任务列表 ─────────────────────────────────────────────────
-
-
-@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."""
-    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

apps/api/app/api/routes/projects.py

@@ -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,

apps/api/app/api/routes/scripts.py

@@ -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

apps/api/app/api/routes/task_center.py

@@ -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",

apps/api/app/api/routes/templates.py

@@ -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)

apps/api/app/api/routes/templates_editor/ai_features.py

@@ -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",

apps/api/app/api/routes/templates_editor/clips.py

@@ -23,10 +23,6 @@ import re
 from app.auth import AuthenticatedUser, get_current_user
 from app.core.storage import get_storage_service
 from app.dependencies import get_asset_repository, get_db_session
-
-# 默认转场时长（与 worker 端保持一致）
-_DEFAULT_TRANSITION_DURATION = 0.5
-
 from app.services.asset_segment_tracker import (
     REUSE_RATIO_LIMIT,
     SEGMENT_EDGE_GAP,
@@ -36,19 +32,18 @@ from app.services.asset_segment_tracker import (
     remove_used_segment,
 )
 from app.services.edit_plan_service import EditPlanService
-from app.services.edit_template_service import EditTemplateService, TemplateNotFoundError
+from app.services.edit_template_service import EditTemplateService
 from fastapi import APIRouter, BackgroundTasks, Depends, HTTPException, Query, status
 from sqlalchemy.orm import Session
 
 from packages.adapters.sqlalchemy_impl.asset_repository import SQLAlchemyAssetRepository
-from packages.domain.plan_generator_utils import (
-    _calc_random_start_time,
-    build_scene_segments,
-    extract_scene_points_from_metadata,
-    pick_scene_aware_start,
-    pick_start_in_scene_segment,
+from packages.adapters.sqlalchemy_impl.template_clip_config_repository import (
+    SQLAlchemyTemplateClipConfigRepository,
 )
-from packages.domain.smart_match import SCORE_RANDOM_NOISE_MAX, score_asset
+from packages.adapters.sqlalchemy_impl.template_repository import (
+    SQLAlchemyTemplateRepository,
+)
+from packages.domain.plan_generator_utils import _calc_random_start_time
 from packages.shared.mediakit_client import get_mediakit_client
 
 from .dependencies import get_draft_plan_id, get_editor_services
@@ -132,8 +127,8 @@ def _build_asset_url_map(
     result: dict[str, str | None] = {}
     try:
         storage = get_storage_service()
-    except Exception as e:
-        logger.exception("获取存储服务失败，跳过asset_url生成: %s", e)
+    except Exception:
+        logger.warning("获取存储服务失败，跳过asset_url生成")
         return {aid: None for aid in asset_ids}
 
     # 批量查询所有 Asset（单次 SQL IN 查询，避免 N+1）
@@ -141,7 +136,7 @@ def _build_asset_url_map(
         assets = asset_repo.find_by_ids(unique_ids)
         asset_map = {a.id: a for a in assets}
     except Exception:
-        logger.exception("批量查询素材失败: asset_ids=%s", asset_ids)
+        logger.warning("批量查询素材失败: asset_ids=%s", asset_ids, exc_info=True)
         return {aid: None for aid in asset_ids if aid}
 
     for aid in unique_ids:
@@ -156,7 +151,7 @@ def _build_asset_url_map(
                 continue
             result[aid] = storage.get_download_url(storage_key, expires_seconds=3600)
         except Exception:
-            logger.exception("生成素材签名URL失败: asset_id=%s", aid)
+            logger.warning("生成素材签名URL失败: asset_id=%s", aid, exc_info=True)
             result[aid] = None
 
     return result
@@ -393,42 +388,68 @@ def _safe_segment_duration(value, default: float) -> float:
 
 def _get_template_segments(
     template_id: str,
-    user_id: str,
     tpl_svc: EditTemplateService,
+    db: Session,
 ) -> list[tuple[int, float, float]]:
     """获取模板的片段配置（顺序、最短时长、最长时长）.
 
-    单一数据源：模板主表为 ``templates``（用户自建，归属 user_id）/
-    ``edit_templates``（全局模板库），片段配置主表为 ``template_clip_configs``
-    （由 ``EditTemplateService.list_clip_configs_for_editor`` 统一读取）。
-
-    不再使用"新表抛异常 → 降级直查配置表 → 再降级查 segments"的异常控制流，
-    也不在正常请求中打印 ``ValueError: 模板不存在`` 堆栈。
-
-    Args:
-        template_id: 模板 ID
-        user_id: 当前登录用户 ID（用于归属校验）
-        tpl_svc: 模板编辑器服务
+    优先从新模板系统（template_clip_configs）查询，
+    若不存在则回退到旧模板系统（template_segments）。
 
     Returns:
-        [(segment_order, duration_min, duration_max), ...] 按 order 排序；
-        模板存在但未配置片段时返回空列表。
-
-    Raises:
-        TemplateNotFoundError: 模板不存在、已删除或不归属于当前用户。
+        [(segment_order, duration_min, duration_max), ...] 按 order 排序
     """
-    clip_configs = tpl_svc.list_clip_configs_for_editor(template_id, user_id)
+    # 优先查新模板系统
+    try:
+        clip_configs = tpl_svc.list_clip_configs(template_id)
+        if clip_configs:
+            result = []
+            for cc in clip_configs:
+                dur_min = _safe_segment_duration(cc.min_duration, _DEFAULT_EDITOR_CLIP_DURATION)
+                dur_max = _safe_segment_duration(
+                    cc.max_duration or cc.min_duration,
+                    _DEFAULT_EDITOR_CLIP_DURATION,
+                )
+                dur_min, dur_max = min(dur_min, dur_max), max(dur_min, dur_max)
+                result.append((cc.order, dur_min, dur_max))
+            return sorted(result, key=lambda x: x[0])
+    except Exception:
+        logger.warning("新模板系统查询clip_configs失败（主表可能不存在），直接查clip_configs表", exc_info=True)
 
-    result = []
-    for cc in clip_configs:
-        dur_min = _safe_segment_duration(cc.min_duration, _DEFAULT_EDITOR_CLIP_DURATION)
-        dur_max = _safe_segment_duration(
-            cc.max_duration or cc.min_duration,
-            _DEFAULT_EDITOR_CLIP_DURATION,
-        )
-        dur_min, dur_max = min(dur_min, dur_max), max(dur_min, dur_max)
-        result.append((cc.order, dur_min, dur_max))
-    return sorted(result, key=lambda x: x[0])
+    # 兜底：直接查 template_clip_configs 表（片段表有 template_id 外键，不依赖模板主表）
+    try:
+        direct_repo = SQLAlchemyTemplateClipConfigRepository(db)
+        direct_configs = direct_repo.list_by_template(template_id)
+        if direct_configs:
+            result = []
+            for cc in direct_configs:
+                dur_min = _safe_segment_duration(cc.min_duration, _DEFAULT_EDITOR_CLIP_DURATION)
+                dur_max = _safe_segment_duration(
+                    cc.max_duration or cc.min_duration,
+                    _DEFAULT_EDITOR_CLIP_DURATION,
+                )
+                dur_min, dur_max = min(dur_min, dur_max), max(dur_min, dur_max)
+                result.append((cc.order, dur_min, dur_max))
+            return sorted(result, key=lambda x: x[0])
+    except Exception:
+        logger.warning("直接查clip_configs表也失败，继续回退旧系统", exc_info=True)
+
+    # 回退到旧模板系统（template_segments表）
+    try:
+        old_repo = SQLAlchemyTemplateRepository(db)
+        segments = old_repo.list_segments(template_id)
+        if segments:
+            result = []
+            for s in segments:
+                dur_min = _safe_segment_duration(s.duration_min, _DEFAULT_EDITOR_CLIP_DURATION)
+                dur_max = _safe_segment_duration(s.duration_max, _DEFAULT_EDITOR_CLIP_DURATION)
+                dur_min, dur_max = min(dur_min, dur_max), max(dur_min, dur_max)
+                result.append((s.segment_order, dur_min, dur_max))
+            return sorted(result, key=lambda x: x[0])
+    except Exception:
+        logger.warning("旧模板系统查询segments失败", exc_info=True)
+
+    return []
 
 
 def _recommended_time_conflicts(
@@ -449,12 +470,6 @@ def _recommended_time_conflicts(
     return False
 
 
-# 向后兼容别名：镜头段构建/段内取点逻辑已下沉到 packages.domain.plan_generator_utils，
-# 旧测试与历史代码仍按 clips._build_scene_segments / _pick_start_in_scene_segment 导入
-_build_scene_segments = build_scene_segments
-_pick_start_in_scene_segment = pick_start_in_scene_segment
-
-
 def _get_mediakit_recommendations(
     asset_ids: list[str],
     asset_repo,
@@ -486,8 +501,8 @@ def _get_mediakit_recommendations(
                 if url:
                     video_urls.append(url)
                     valid_asset_ids.append(asset_id)
-            except Exception:
-                logger.exception("获取素材URL失败: asset_id=%s", asset_id)
+            except Exception as e:
+                logger.warning("获取素材URL失败: asset_id=%s error=%s", asset_id, e)
 
         if not video_urls:
             return {}
@@ -563,51 +578,10 @@ def _get_mediakit_recommendations(
         return recommendations
 
     except Exception as e:
-        logger.exception("MediaKit 智能选片异常，降级为随机选择: %s", e)
+        logger.warning("MediaKit 智能选片异常，降级为随机选择: %s", e)
         return {}
 
 
-def _calc_plan_internal_duplicate_rate(clips_data: list[dict]) -> float:
-    """估算单条成片内部重复率（%）.
-
-    检查本条成片中同一素材是否有重叠的时间区间。
-    重叠时长 / 成片总时长 * 100 = 内部重复率。
-    这是一个轻量估算，不依赖视频指纹；完整查重由 worker 异步完成。
-    """
-    if not clips_data:
-        return 0.0
-
-    # 按素材分组
-    by_asset: dict[str, list[tuple[float, float]]] = {}
-    total_duration = 0.0
-    for c in clips_data:
-        aid = c.get("asset_id", "")
-        if not aid:
-            continue
-        start = c.get("start_time", 0.0)
-        end = start + c.get("duration", 0.0)
-        by_asset.setdefault(aid, []).append((start, end))
-        total_duration += c.get("duration", 0.0)
-
-    if total_duration <= 0:
-        return 0.0
-
-    # 检查同素材内的区间重叠
-    overlap_duration = 0.0
-    for segments in by_asset.values():
-        if len(segments) < 2:
-            continue
-        segments_sorted = sorted(segments, key=lambda s: s[0])
-        last_end = segments_sorted[0][1]
-        for start, end in segments_sorted[1:]:
-            overlap = max(0.0, min(end, last_end) - start)
-            if overlap > 0:
-                overlap_duration += overlap
-            last_end = max(last_end, end)
-
-    return round(overlap_duration / total_duration * 100, 1)
-
-
 @router.post("/clips/from-assets", response_model=ClipsFromAssetsResponse)
 def create_clips_from_assets_editor(
     template_id: str,
@@ -631,21 +605,13 @@ def create_clips_from_assets_editor(
     7. 素材时长为 0 或缺失时报 400，不创建无效片段
     """
     tpl_svc, plan_svc = services
-    user_id = str(current_user.user.id)
 
-    # 1. 查询模板片段配置。模板不存在/已删除/无权限 → 404；
-    #    模板存在但确实未配置片段 → 422（配置错误，与 404 区分）。
-    try:
-        segments = _get_template_segments(template_id, user_id, tpl_svc)
-    except TemplateNotFoundError as exc:
-        raise HTTPException(
-            status_code=status.HTTP_404_NOT_FOUND,
-            detail="模板不存在或无权访问",
-        ) from exc
+    # 1. 查询模板 segments
+    segments = _get_template_segments(template_id, tpl_svc, db)
     if not segments:
         raise HTTPException(
-            status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
-            detail="模板未配置片段",
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail="模板没有片段配置，无法创建片段",
         )
 
     # 防御：schema validator 已过滤 null/空串，这里再归一化一次，
@@ -660,26 +626,10 @@ def create_clips_from_assets_editor(
     # 2. 获取素材实际时长（去重查询）
     unique_asset_ids = list(dict.fromkeys(asset_ids))
     asset_durations: dict[str, float] = {}
-    asset_smart_scores: dict[str, float] = {}
-    # 素材 metadata 中缓存的场景切换点（由后台 MediaKit SceneChange 检测写入）：
-    # 有缓存时片段起点从随机镜头段中选取（不同片段来自不同镜头），无缓存回退随机起点
-    asset_scene_points: dict[str, list[float]] = {}
     for asset_id in unique_asset_ids:
         asset = asset_repo.get(asset_id)
         if asset and hasattr(asset, "duration"):
             asset_durations[asset_id] = float(asset.duration or 0.0)
-            # 计算 smart_match 综合评分，用于候选排序
-            smart_score, _ = score_asset(asset)
-            asset_smart_scores[asset_id] = smart_score
-            # 读取场景切换点缓存（新素材未检测过时为 None，走随机起点兜底）
-            cached_points = extract_scene_points_from_metadata(getattr(asset, "metadata", None))
-            if cached_points:
-                asset_scene_points[asset_id] = cached_points
-    logger.info(
-        "from-assets 场景缓存命中: %d/%d 个素材有场景切换点",
-        len(asset_scene_points),
-        len(unique_asset_ids),
-    )
 
     # 3. 在内存中计算所有片段数据（使用随机起始时间，不调用MediaKit）
     # 读取素材 metadata 中持久化的历史已用区间（跨任务/跨调用去重），
@@ -712,52 +662,19 @@ def create_clips_from_assets_editor(
             return False
         return reused_durations.get(aid, 0.0) / assigned > REUSE_RATIO_LIMIT
 
-    # 素材耗尽标志：某轮循环中所有素材均被跳过时为 True
-    all_assets_exhausted = False
-
-    # 计算转场重叠补偿：每个 clip 需要额外增加的时长
-    # 目标：渲染后视频总时长 = 模板设定的各片段时长之和
-    # 公式：每 clip 增加 (n_segments - 1) * td / n_segments
-    n_segments = len(segments)
-    if n_segments > 1:
-        transition_compensation = (n_segments - 1) * _DEFAULT_TRANSITION_DURATION / n_segments
-    else:
-        transition_compensation = 0.0
-
-    # 打乱 segments 的处理顺序（分配素材的顺序随机化），但最终 clips_data 按原始 order 排序
-    shuffled_indices = list(range(len(segments)))
-    random.shuffle(shuffled_indices)
-
-    for idx in shuffled_indices:
-        _seg_order, dur_min, dur_max = segments[idx]
+    for i, (_seg_order, dur_min, dur_max) in enumerate(segments):
         # 在 segment 的 duration_min ~ duration_max 之间随机取值（保留一位小数）
         raw_duration = random.uniform(dur_min, dur_max)
-        # 加上转场补偿，确保最终输出时长 = 模板设定总时长
-        raw_duration += transition_compensation
 
-        # 贪心分配素材：按"已使用次数"升序排列候选素材（使用最少的优先），
-        # 同次数随机打散，避免"A-B-C-D"的固定组合反复出现。
-        # 跳过时长缺失、复用占比已超 10% 阈值的素材；
+        # 轮询分配素材：跳过时长缺失、复用占比已超 15% 阈值的素材；
         # 选中后计算起点，若该素材可用区间耗尽且复用被闸门拒绝（calc 返回 None），
-        # 继续尝试下一个素材
+        # 继续轮询下一个素材
         asset_id = ""
         clip_duration = 0.0
         start_time: float | None = None
-        # 动态按使用次数排序：优先选使用最少的素材，同次数随机打散
-        asset_use_counts = {aid: len(used_segments.get(aid, [])) for aid in asset_ids}
-        # 排序键：smart_match 评分（注入随机噪声）→ 使用次数 → 纯随机。
-        # 噪声让得分接近的素材排名每次浮动，避免同一批素材反复选出相同组合，
-        # 从素材组合层面降低成片查重率；分差 > SCORE_RANDOM_NOISE_MAX 时排名稳定，
-        # 质量差距显著的素材仍保持优先级。
-        sorted_candidates = sorted(
-            asset_ids,
-            key=lambda aid: (
-                -(asset_smart_scores.get(aid, 0.0) + random.uniform(0.0, SCORE_RANDOM_NOISE_MAX)),
-                asset_use_counts.get(aid, 0),
-                random.random(),
-            ),
-        )
-        for candidate in sorted_candidates:
+        n_assets = len(asset_ids)
+        for offset in range(n_assets):
+            candidate = asset_ids[(i + offset) % n_assets]
             candidate_total = asset_durations.get(candidate, 0.0)
             if candidate_total <= 0:
                 continue
@@ -771,30 +688,16 @@ def create_clips_from_assets_editor(
                     candidate,
                 )
                 continue
-            # 起始时间选取（不调用 MediaKit，保证接口快速返回）：
-            # 1) 素材有场景切换点缓存时，优先从随机镜头段中选起点（不同片段来自不同镜头，
-            #    画面内容本质不同），与 used_segments 做冲突避让（含 1.5s 边缘间隙）
-            # 2) 无缓存 / 镜头段全冲突 → _calc_random_start_time 随机起点兜底；
-            #    100 次避不开历史区间时走受控复用回调（复用片段累加 reused_durations，
-            #    回调内部预判复用后占比超 10% 则拒绝并返回 None）
-            candidate_start = None
-            if candidate in asset_scene_points:
-                candidate_start = pick_scene_aware_start(
-                    candidate,
-                    candidate_duration,
-                    asset_durations,
-                    asset_scene_points,
-                    used_segments,
-                    edge_gap=SEGMENT_EDGE_GAP,
-                )
-            if candidate_start is None:
-                candidate_start = _calc_random_start_time(
-                    candidate,
-                    candidate_duration,
-                    asset_durations,
-                    used_segments,
-                    on_exhausted=reuse_cb,
-                )
+            # 随机起始时间（不调用 MediaKit，保证接口快速返回）；100 次避不开
+            # 历史区间时走受控复用回调（复用片段累加 reused_durations，回调内部
+            # 预判复用后占比超 15% 则拒绝并返回 None）
+            candidate_start = _calc_random_start_time(
+                candidate,
+                candidate_duration,
+                asset_durations,
+                used_segments,
+                on_exhausted=reuse_cb,
+            )
             if candidate_start is None:
                 # 该素材可用区间耗尽且复用被闸门/use_count 上限拒绝 → 尝试下一素材
                 logger.info(
@@ -809,7 +712,6 @@ def create_clips_from_assets_editor(
 
         if not asset_id or start_time is None:
             # 所有素材时长缺失、复用占比超阈值，或区间耗尽且复用被拒 → 素材可切区间不足
-            all_assets_exhausted = True
             raise HTTPException(
                 status_code=status.HTTP_400_BAD_REQUEST,
                 detail="素材可切区间不足，请补充新素材",
@@ -825,7 +727,7 @@ def create_clips_from_assets_editor(
 
         clips_data.append(
             {
-                "order": _seg_order,
+                "order": i,
                 "asset_id": asset_id,
                 "start_time": start_time,
                 "duration": clip_duration,
@@ -833,9 +735,6 @@ def create_clips_from_assets_editor(
             }
         )
 
-    # 按原始 segment order 排序，确保 clips_data 的 order 字段有序（0,1,2,3...）
-    clips_data.sort(key=lambda c: c["order"])
-
     # 4. 事务性替换：清空旧片段 → 创建新片段 → 标记ready（单事务，失败自动回滚）
     created_count = plan_svc.replace_all_clips_transactional(plan_id, clips_data)
 
@@ -855,31 +754,11 @@ def create_clips_from_assets_editor(
         unique_asset_ids,
     )
 
-    # 6. 估算成片内部重复率（本条成片中同一素材的重叠片段时长占比）
-    dup_rate = _calc_plan_internal_duplicate_rate(clips_data)
-    duplicate_warning = None
-    if dup_rate > 50:
-        duplicate_warning = f"查重率 {dup_rate:.1f}% 超过50%，建议更换素材或模板"
-        logger.exception(
-            "from-assets 成片查重率超标: plan_id=%s dup_rate=%.1f%%",
-            plan_id,
-            dup_rate,
-        )
-
-    # 7. 素材耗尽提示
-    exhaustion_warning = None
-    if all_assets_exhausted and created_count < len(segments):
-        exhaustion_warning = (
-            "素材可切区间不足，部分片段使用了复用素材。" "建议：1) 补充更多素材到素材库 2) 使用不同的素材组合生成"
-        )
-
-    # 8. 立即返回响应
+    # 6. 立即返回响应
     return ClipsFromAssetsResponse(
         created_count=created_count,
         plan_id=plan_id,
         clip_ids=[],
-        duplicate_warning=duplicate_warning,
-        exhaustion_warning=exhaustion_warning,
     )
 
 
@@ -887,15 +766,7 @@ def _update_mediakit_recommendations_async(  # pragma: no cover
     plan_id: str,
     asset_ids: list[str],
 ) -> None:
-    """后台任务：使用 SceneChange 智能选帧并更新片段的起始时间.
-
-    优先使用 SceneChange 策略检测视频镜头切换点，将每个素材按镜头段拆分，
-    各片段优先从不同镜头段中选取起始时间，实现「不同片段展示不同场景」的效果。
-
-    降级策略：
-    1. SceneChange 优先 → detect_scene_changes 内部已含 TimeInterval 降级
-    2. 若 detect_scene_changes 仍返回 None → 回退到旧的 analyze_videos 方式
-    3. 所有方式都失败 → 保持现有随机 start_time，不影响视频生成
+    """后台任务：调用 MediaKit 智能选片并更新片段的起始时间.
 
     此函数在后台异步执行，不影响接口响应时间。
     失败时静默处理，不影响已创建的片段。
@@ -917,6 +788,12 @@ def _update_mediakit_recommendations_async(  # pragma: no cover
         asset_repo = SQLAlchemyAssetRepository(db)
         plan_svc = EditPlanService(db)
 
+        # 调用 MediaKit 获取推荐时间
+        recommendations = _get_mediakit_recommendations(asset_ids, asset_repo)
+        if not recommendations:
+            logger.info("后台任务: MediaKit 无推荐结果，跳过更新")
+            return
+
         # 查询该 plan 的所有片段（分批获取，避免硬编码 limit 截断）
         batch_size = 500
         all_clips = []
@@ -939,16 +816,15 @@ def _update_mediakit_recommendations_async(  # pragma: no cover
         unique_asset_ids = list({getattr(c, "asset_id", "") or "" for c in clips} - {""})
         assets_map: dict[str, object] = {a.id: a for a in asset_repo.find_by_ids(unique_asset_ids)}
 
-        # 按 asset_id 预分组片段对象（按 order 排序，保证按模板顺序分配镜头段）
-        clips_by_asset: dict[str, list] = defaultdict(list)
+        # 按 asset_id 预分组片段时间段（消除 O(N^2) 嵌套循环）
+        clips_by_asset: dict[str, list[tuple[str, float, float]]] = defaultdict(list)
         for clip in clips:
             aid = getattr(clip, "asset_id", "") or ""
-            if aid:
-                clips_by_asset[aid].append(clip)
-        for aid in clips_by_asset:
-            clips_by_asset[aid].sort(key=lambda c: c.order)
+            if aid and clip.start_time is not None:
+                clips_by_asset[aid].append((clip.id, clip.start_time, clip.start_time + clip.duration))
 
-        # 读取素材全部历史已用区间（跨任务/跨 plan 持久化记录）
+        # 读取素材全部历史已用区间（跨任务/跨 plan 持久化记录）：
+        # MediaKit 挪点必须与随机选片一样避让历史区间，否则会把片段挪回已用过的画面
         historical_segments = get_used_segments(db, unique_asset_ids)
 
         # 已更新的片段ID（用于排除已移动的旧时间段）
@@ -957,22 +833,16 @@ def _update_mediakit_recommendations_async(  # pragma: no cover
         updated_segments: dict[str, list[tuple[float, float]]] = {}
         updated_count = 0
 
-        # 尝试获取存储服务（用于生成视频 URL）
-        try:
-            storage = get_storage_service()
-        except Exception as e:
-            logger.exception("后台任务: 获取存储服务失败，跳过 SceneChange 更新: %s", e)
-            return
-
-        # 获取 MediaKit 客户端
-        client = get_mediakit_client()
-
-        # 对每个素材，检测场景切换点并分配镜头段
-        for asset_id in unique_asset_ids:
-            asset_clips = clips_by_asset.get(asset_id, [])
-            if not asset_clips:
+        # 遍历片段，按 asset_id 匹配推荐时间
+        for clip in clips:
+            asset_id = getattr(clip, "asset_id", "") or ""
+            if not asset_id or asset_id not in recommendations:
                 continue
 
+            recommended_start = recommendations[asset_id]
+            clip_duration = clip.duration
+
+            # 从预加载字典获取素材（O(1) 查找）
             asset = assets_map.get(asset_id)
             if not asset:
                 continue
@@ -980,181 +850,95 @@ def _update_mediakit_recommendations_async(  # pragma: no cover
             if asset_total <= 0:
                 continue
 
-            # 获取素材视频 URL
-            video_url: str | None = None
-            storage_key = getattr(asset, "storage_key", None) or ""
-            mime = getattr(asset, "mime_type", "") or ""
-            if storage_key and mime.startswith("video/"):
-                try:
-                    video_url = storage.get_download_url(storage_key)
-                except Exception:
-                    logger.exception("后台任务: 获取素材URL失败: asset_id=%s", asset_id)
-
-            # 构建该素材的占用区间列表（排除已更新片段）
-            def _get_other_segments(asset_id_inner, clip_id_inner):
-                segs: list[tuple[float, float]] = []
-                for c in clips_by_asset.get(asset_id_inner, []):
-                    cid = c.id
-                    if cid != clip_id_inner and cid not in updated_clip_ids:
-                        segs.append((c.start_time, c.start_time + c.duration))
-                segs.extend(updated_segments.get(asset_id_inner, []))
-
-                # 并入历史已用区间
-                def _norm(segs_in):
-                    return {(round(float(a), 3), round(float(b), 3)) for a, b in segs_in}
-
-                return list(_norm(segs) | _norm(historical_segments.get(asset_id_inner, [])))
-
-            # 优先使用 SceneChange 策略
-            scene_segments: list[tuple[float, float]] = []
-            # 先查素材 metadata 中的场景点缓存：命中则直接复用，跳过 MediaKit 检测
-            # （缓存由本任务首次检测后写入，跨任务/跨 plan 复用）
-            cached_points = extract_scene_points_from_metadata(getattr(asset, "metadata", None))
-            if cached_points:
-                scene_segments = build_scene_segments(cached_points, asset_total)
+            # 推荐时间 + 片段时长不能超过素材总时长
+            if recommended_start + clip_duration > asset_total:
                 logger.info(
-                    "后台任务: 命中场景点缓存: asset_id=%s scenes=%d",
-                    asset_id,
-                    len(scene_segments),
-                )
-
-            if not scene_segments and client.is_available and video_url:
-                scene_changes = client.detect_scene_changes(video_url)
-                if scene_changes is not None:
-                    scene_segments = build_scene_segments(scene_changes, asset_total)
-                    logger.info(
-                        "后台任务: 素材场景检测完成: asset_id=%s scenes=%d",
-                        asset_id,
-                        len(scene_segments),
-                    )
-                    # 检测结果写入素材 metadata 缓存：首次生成用随机起点，
-                    # 检测完成后后续生成的渲染前同步路径即可读缓存选镜头段
-                    try:
-                        existing_meta = dict(getattr(asset, "metadata", None) or {})
-                        existing_meta["scene_change_points"] = scene_changes
-                        asset.metadata = existing_meta  # type: ignore[attr-defined]
-                        asset_repo.update(asset)  # type: ignore[arg-type]
-                        logger.info(
-                            "后台任务: 场景点已写入素材缓存: asset_id=%s points=%d",
-                            asset_id,
-                            len(scene_changes),
-                        )
-                    except Exception:
-                        # 缓存写入失败不影响本次片段更新
-                        logger.exception(
-                            "后台任务: 场景点缓存写入失败: asset_id=%s",
-                            asset_id,
-                        )
-
-            # SceneChange 未获得有效结果 → 尝试 analyze_videos 作为 fallback
-            if not scene_segments and video_url:
-                fallback_recs = _get_mediakit_recommendations([asset_id], asset_repo)
-                if fallback_recs and asset_id in fallback_recs:
-                    # analyze_videos 只返回单个推荐点，转为单镜头段
-                    rec_start = fallback_recs[asset_id]
-                    scene_segments = [(rec_start, asset_total)]
-                    logger.info(
-                        "后台任务: 使用 analyze_videos fallback: asset_id=%s start=%.2f",
-                        asset_id,
-                        rec_start,
-                    )
-
-            if not scene_segments:
-                # 所有方式都失败 → 保持现有随机 start_time
-                logger.info(
-                    "后台任务: SceneChange 与 analyze_videos 均无结果，保持随机起点: asset_id=%s",
+                    "后台任务: 推荐时间越界，跳过: asset_id=%s recommended=%.2f duration=%.1f total=%.1f",
                     asset_id,
+                    recommended_start,
+                    clip_duration,
+                    asset_total,
                 )
                 continue
 
-            # 为每个片段分配不同的镜头段
-            scene_segments_pool = list(scene_segments)  # 可消费的镜头段池
-            for clip in asset_clips:
-                clip_duration = clip.duration
-                recommended_start: float | None = None
+            # 构建排除当前片段及已更新片段后的占用列表（O(M)，M=同素材片段数）
+            other_segments: list[tuple[float, float]] = [
+                (cs, ce)
+                for cid, cs, ce in clips_by_asset.get(asset_id, [])
+                if cid != clip.id and cid not in updated_clip_ids
+            ]
+            other_segments.extend(updated_segments.get(asset_id, []))
 
-                # 从镜头段池中依次尝试，选一个不冲突的
-                for seg_idx, (seg_start, seg_end) in enumerate(scene_segments_pool):
-                    candidate_start = pick_start_in_scene_segment(seg_start, seg_end, clip_duration)
-                    if candidate_start is None:
-                        continue  # 镜头段太短，跳过
+            # 并入该素材全部历史已用区间（含其他 plan/其他任务），set 去重：
+            # 本 plan 片段创建时已写入历史记录
+            # 并入该素材全部历史已用区间（含其他 plan/其他任务）。
+            # set 去重前先归一化精度（round 3 位），避免浮点尾差导致逻辑相同的
+            # 区间（如 1.0 与 1.0000000001）被误判为不同区间
+            def _norm(segs):
+                return {(round(float(a), 3), round(float(b), 3)) for a, b in segs}
 
-                    # 检查越界
-                    if candidate_start + clip_duration > asset_total:
-                        continue
+            other_segments = list(_norm(other_segments) | _norm(historical_segments.get(asset_id, [])))
 
-                    # 检查与已用区间冲突
-                    other_segs = _get_other_segments(asset_id, clip.id)
-                    if _recommended_time_conflicts(candidate_start, clip_duration, other_segs):
-                        continue
+            # 检查推荐时间是否与同 plan 片段或历史已用区间冲突（含 0.3s 边缘间隙）：
+            # 冲突时放弃该推荐、保留原随机起点（不硬挪到已用过的画面）
+            if _recommended_time_conflicts(recommended_start, clip_duration, other_segments):
+                logger.info(
+                    "后台任务: 推荐时间与同片/历史区间冲突，保留原起点: asset_id=%s recommended=%.2f",
+                    asset_id,
+                    recommended_start,
+                )
+                continue
 
-                    recommended_start = candidate_start
-                    # 消费该镜头段（从池中移除，下一个片段用不同镜头段）
-                    scene_segments_pool.pop(seg_idx)
-                    break
-
-                if recommended_start is None:
-                    # 镜头段用完或都冲突 → 尝试 _calc_random_start_time 兜底
-                    used_segs_for_calc: dict[str, list[tuple[float, float]]] = {
-                        asset_id: _get_other_segments(asset_id, clip.id)
-                    }
-                    fallback_start = _calc_random_start_time(
-                        asset_id,
-                        clip_duration,
-                        {asset_id: asset_total},
-                        used_segs_for_calc,
-                    )
-                    if fallback_start is None:
-                        continue  # 完全无法分配，保持原起点
-                    recommended_start = fallback_start
-
-                # 更新片段起始时间
+            # 逐个更新并捕获异常（单点失败不影响其他片段）
+            try:
+                old_start = clip.start_time
+                old_end = old_start + clip_duration
+                # MediaKit 移动片段起点 + 同步素材 metadata 区间记录放在同一事务：
+                # 删旧区间记录（按 plan_id + 旧 start 匹配，兼容无 plan_id 的旧数据）、
+                # 写新区间，最后统一 commit；任一步失败整体 rollback，
+                # 保证 clip.start_time 与 metadata.used_time_ranges 不出现不一致。
+                plan_svc.update_clip(clip.id, start_time=recommended_start)
                 try:
-                    old_start = clip.start_time
-                    old_end = old_start + clip_duration
-
-                    plan_svc.update_clip(clip.id, start_time=recommended_start)
-                    try:
-                        if remove_used_segment(db, asset_id, old_start, old_end, plan_id=plan_id):
-                            record_used_segments(
-                                db,
-                                asset_id,
-                                recommended_start,
-                                recommended_start + clip_duration,
-                                plan_id,
-                            )
-                    except Exception:
-                        logger.exception(
-                            "后台任务: 同步素材区间记录失败，回滚本次片段更新: clip_id=%s",
-                            clip.id,
+                    if remove_used_segment(db, asset_id, old_start, old_end, plan_id=plan_id):
+                        record_used_segments(
+                            db,
+                            asset_id,
+                            recommended_start,
+                            recommended_start + clip_duration,
+                            plan_id,
                         )
-                        db.rollback()
-                        continue
-                    db.commit()
-                    updated_count += 1
-                    updated_clip_ids.add(clip.id)
-                    updated_segments.setdefault(asset_id, []).append(
-                        (recommended_start, recommended_start + clip_duration)
-                    )
-                    logger.info(
-                        "后台任务: 更新片段起始时间(场景选帧): clip_id=%s asset_id=%s start_time=%.2f",
+                except Exception as me:
+                    logger.warning(
+                        "后台任务: 同步素材区间记录失败，回滚本次片段更新: clip_id=%s error=%s",
                         clip.id,
-                        asset_id,
-                        recommended_start,
+                        me,
                     )
-                except Exception:
-                    logger.exception("后台任务: 单个片段更新失败: clip_id=%s", clip.id)
-                    try:
-                        db.rollback()
-                    except Exception:
-                        pass
+                    db.rollback()
                     continue
+                db.commit()
+                updated_count += 1
+                updated_clip_ids.add(clip.id)
+            except Exception as ue:
+                logger.warning("后台任务: 单个片段更新失败: clip_id=%s error=%s", clip.id, ue)
+                try:
+                    db.rollback()
+                except Exception:
+                    pass
+                continue
+
+            updated_segments.setdefault(asset_id, []).append((recommended_start, recommended_start + clip_duration))
+            logger.info(
+                "后台任务: 更新片段起始时间: clip_id=%s asset_id=%s start_time=%.2f",
+                clip.id,
+                asset_id,
+                recommended_start,
+            )
 
         logger.info("后台任务完成: plan_id=%s 成功更新 %d 个片段", plan_id, updated_count)
 
-    except Exception:
+    except Exception as e:
         # 后台任务失败不影响已创建的片段，静默处理
-        logger.exception("后台任务异常: plan_id=%s", plan_id)
+        logger.warning("后台任务异常: plan_id=%s error=%s", plan_id, e, exc_info=True)
         if db:
             try:
                 db.rollback()

apps/api/app/api/routes/templates_editor/dependencies.py

@@ -41,33 +41,29 @@ 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_id，is_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

apps/api/app/api/routes/templates_editor/draft.py

@@ -150,7 +150,7 @@ 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(

apps/api/app/api/routes/templates_editor/effects.py

@@ -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))
 

apps/api/app/api/routes/templates_editor/schemas.py

@@ -189,8 +189,6 @@ class ClipsFromAssetsResponse(BaseModel):
     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 ────────────────────────────────────────────────────────────────

apps/api/app/api/routes/tts.py

@@ -2,9 +2,7 @@
 
 from __future__ import annotations
 
-import json
 import logging
-import subprocess
 import tempfile
 from pathlib import Path
 from typing import Any, Optional
@@ -173,14 +171,6 @@ def synthesize(
         # 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,
@@ -188,7 +178,7 @@ def synthesize(
         voice_id=actual_voice_id,
         voice_model=request.voice_model,
         voice_clone_profile_id=voice_clone_profile_id,
-        metadata=synthesis_meta,
+        metadata=request.metadata_,
     )
 
     # 提交 CosyVoice 合成任务
@@ -440,8 +430,6 @@ def save_tts_job_to_library(
     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)
@@ -457,23 +445,6 @@ def save_tts_job_to_library(
             )
         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:
@@ -511,7 +482,7 @@ def save_tts_job_to_library(
         mime_type=content_type,
         metadata=metadata_,
         file_size=file_size,
-        duration=job.duration or audio_duration or None,
+        duration=job.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,
@@ -575,7 +546,6 @@ def preview_tts(
             text=request.text,
             voice_id=actual_voice_id,
             speed=request.speed,
-            emotion=request.emotion,
         )
     except CosyVoiceError as e:
         raise HTTPException(

apps/api/app/api/routes/upload.py

@@ -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-create：prepare 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 +188,26 @@ 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,
+                url=storage_service.get_url(normalized_key),
+            )
 
     job = _submit_ingest_job(
         project_id=request.project_id,
@@ -485,14 +215,8 @@ 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, url=storage_service.get_url(normalized_key))
 
 
 @router.post(
@@ -505,8 +229,7 @@ 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 +240,32 @@ 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 +284,16 @@ 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,
     )

apps/api/app/api/routes/videos.py

@@ -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,
@@ -54,8 +53,6 @@ def _to_video_response(item, storage: OSSStorageService | None = None) -> VideoI
         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 +237,3 @@ 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",
-    )

apps/api/app/api/routes/voice_clones.py

@@ -163,12 +163,12 @@ 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 +277,12 @@ 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)
 

apps/api/app/api/routes/voices.py

@@ -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

apps/api/app/core/celery_app.py

@@ -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

apps/api/app/core/task_enqueue.py

@@ -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",

apps/api/app/schemas/ai_avatar_render.py

@@ -1,118 +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（可含 title_image_dataurl：前端 Canvas 渲染的标题 PNG dataURL）"
-    )
-    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:
-        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 SmartCoverResponse(BaseModel):
-    """智能封面响应（封面从最终成片抽帧，不再叠加标题）."""
-
-    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）")

apps/api/app/schemas/duplication.py

@@ -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
 

apps/api/app/schemas/generated_video.py

@@ -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):

apps/api/app/schemas/generation_task.py

@@ -25,24 +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,
@@ -85,47 +75,6 @@ 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
 
     @model_validator(mode="after")
     def _check_at_least_one_mode(self) -> "CreateGenerationTaskRequest":
@@ -134,9 +83,9 @@ 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
 
 
@@ -213,6 +162,7 @@ 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"
     )
@@ -235,44 +185,8 @@ class CreatePreviewGenerationTaskRequest(BaseModel):
     )
     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",
+        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",
     )
-    # ── 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 +196,13 @@ 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 +211,6 @@ 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 +219,7 @@ 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

apps/api/app/schemas/lipsync.py

@@ -1,128 +0,0 @@
-"""对口型 API Schema 定义 — #1796 / #1809 / #1822 / #1845（配音前置）.
-
-支持三种输入模式：
-1. TTS 直生模式（兼容旧版前端）：传 voice_id + script_text（+ speed/emotion），
-   后端 Celery 异步做 TTS 合成 + MediaKit 提交。
-2. 直接音频模式：传 video_url + audio_url（音频已由调用方准备好）。
-3. 预合成音频模式（#1845 配音前置新主路径）：前端先调 POST /lipsync/tts-preview
-   拿到 audio_url + sentence_timings，再在 create_job 时传 audio_url + audio_duration
-   + sentence_timings，后端跳过 TTS 和时间戳计算，直接 ffprobe 校验后提交 MediaKit。
-"""
-
-from __future__ import annotations
-
-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.
-
-    三种模式（三选一）：
-    - TTS 直生（旧版/降级）：voice_id + script_text 必填；audio_url 留空。
-    - 直接音频：video_url + audio_url 必填。
-    - 预合成音频（#1845 新主路径）：audio_url 必填 + 可选 audio_duration/sentence_timings；
-      后端同步 ffprobe 校验时长、写入 timings，直接提交 MediaKit。
-    """
-
-    video_url: str = Field(..., description="人物视频 URL（MP4，≤30min，单人真人）")
-
-    # 模式 2/3：直接/预合成音频
-    audio_url: str = Field("", description="驱动音频 URL（mp3/aac/wav/m4a/flac）；直生模式留空")
-    audio_duration: Optional[float] = Field(None, ge=0, description="预合成音频时长（秒），可选；后端会 ffprobe 校验")
-    sentence_timings: Optional[list] = Field(None, description="预合成接口返回的句子时间戳，可选；若传入则直接写入 job")
-
-    # 模式 1：TTS 直生
-    voice_id: str = Field("", description="音色 ID（预置音色或克隆音色 profile UUID）")
-    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/预合成音频模式），"
-                "要么同时传 voice_id + script_text（TTS 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
-
-
-# ── #1845 TTS 预合成接口 ────────────────────────────────────────────────
-
-
-class AiAvatarTtsPreviewRequest(BaseModel):
-    """步骤1「生成配音」预合成请求（同步 HTTP，~2-3s）."""
-
-    voice_id: str = Field(..., min_length=1, max_length=128, description="音色 ID")
-    script_text: str = Field(..., min_length=1, max_length=5000, description="要合成的文案")
-    speed: float = Field(1.0, ge=0.5, le=2.0, description="语速（0.5-2.0），默认 1.0")
-    emotion: str = Field("natural", max_length=32, description="情绪")
-
-
-class AiAvatarTtsPreviewResponse(BaseModel):
-    """TTS 预合成响应（临时 URL，24h 内有效，足够当前会话使用）."""
-
-    audio_url: str = Field(..., description="CosyVoice 临时音频 URL")
-    duration: float = Field(..., ge=0, description="音频总时长（秒），ffprobe 测得")
-    sentence_timings: list[dict] = Field(..., description="句子级精确时间戳")

apps/api/app/schemas/script.py

@@ -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

apps/api/app/schemas/tts.py

@@ -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）")
@@ -110,7 +109,6 @@ class TTSPreviewRequest(BaseModel):
     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）")
 
 

apps/api/app/schemas/upload.py

@@ -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):
@@ -26,25 +25,20 @@ 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）")
+    duplicated: bool = Field(default=False, description="是否为重复素材（命中去重）")
+    asset_id: str = Field(default="", description="重复素材的 asset_id（duplicated=true 时返回）")
     url: str = Field(default="", description="Public URL of uploaded file")
 
 
@@ -52,5 +46,5 @@ 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="重复素材的 asset_id（duplicated=true 时返回）")

apps/api/app/schemas/video_center.py

@@ -22,10 +22,7 @@ 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):

apps/api/app/services/ai_avatar_cover_service.py

@@ -1,215 +0,0 @@
-"""AI 数字人封面服务 — MediaKit 抽帧 + 质量评分选最佳帧 + 转存 OSS.
-
-与 generation_cover.py 的智能选帧能力对齐（不再用 FFmpeg 简单截帧）：
-1. MediaKit extract_frames 抽取多帧（默认 5 帧，SpecifiedFrames 策略）
-2. cover_frame_scorer.score_frames 按清晰度/亮度/色彩评分选最佳
-3. 下载最佳帧并转存 OSS，返回公网封面 URL
-
-设计原则：封面一律从最终成片（已叠加标题/B-roll）抽帧，帧本身已含标题，
-本服务**不再叠加标题**。对口型阶段的裸视频封面入口已删除（废弃）。
-
-降级：MediaKit 不可用或抽帧失败时返回空字符串，由调用方决定回退策略。
-"""
-
-from __future__ import annotations
-
-import logging
-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:
-            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."""
-    if not video_url:
-        return ""
-
-    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",
-            video_url[:80],
-            max_frames,
-        )
-
-        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 ""
-
-        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 ""
-
-        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 persist_cover_to_oss(
-    frame_url: str,
-    *,
-    job_id: str = "",
-    prefix: str = "ai-avatar/covers",
-) -> str:
-    """下载最佳帧图并转存到 OSS，返回公网封面 URL（预签名）.
-
-    封面来自最终成片抽帧，帧本身已含标题，本函数不再做任何文字/图片叠加。
-    """
-    if not frame_url:
-        return ""
-    tmp_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"
-
-        public_url = storage.upload_file(
-            file_or_path=tmp_path,
-            storage_key=cover_key,
-            content_type="image/jpeg",
-        )
-        logger.info("[数字人封面] 封面已转存 OSS: key=%s", cover_key)
-        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:
-        if tmp_path:
-            try:
-                Path(tmp_path).unlink(missing_ok=True)
-            except Exception:
-                pass
-
-
-def generate_smart_cover(
-    video_url: str,
-    *,
-    job_id: str = "",
-    max_frames: int = 5,
-) -> str:
-    """一站式：MediaKit 智能抽帧选最佳 → 转存 OSS。失败返回空字符串。
-
-    封面从最终成片抽帧，不再叠加任何标题（帧本身已含）。
-    """
-    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)

apps/api/app/services/ai_avatar_render_service.py

@@ -1,609 +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 base64
-import binascii
-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,
-    build_title_overlay_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. 上传到 OSS (95%) — 封面不再自动生成，改由前端主动抽帧
-        5. 更新任务状态 (100%)
-        """
-        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,
-            )
-
-            # 标题叠加路径：优先前端 Canvas 渲染的 PNG 图层（所见即所得），
-            # 无 title_image_dataurl 时降级到 drawtext 重画文字。
-            title_cfg = job.title_config if isinstance(job.title_config, dict) else {}
-            title_dataurl = (title_cfg or {}).get("title_image_dataurl") if title_cfg else None
-            use_title_png = isinstance(title_dataurl, str) and title_dataurl.startswith("data:image/")
-            title_input_index = 1 + len(job.b_roll_segments or []) if use_title_png else None
-
-            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")
-
-                # 在临时目录里解码保存标题 PNG（with 退出自动清理）
-                title_png_path: Optional[str] = None
-                extra_inputs: list[str] = []
-                title_filter = None
-                if use_title_png:
-                    try:
-                        title_png_path = os.path.join(tmpdir, f"title_{job.id}.png")
-                        self._save_title_dataurl_to_file(title_dataurl, dst_path=title_png_path)
-                        extra_inputs.append(title_png_path)
-                        logger.info(
-                            "[数字人渲染] 标题 PNG 已保存: %s (input index %d)", title_png_path, title_input_index
-                        )
-                    except Exception as exc:
-                        logger.warning("[数字人渲染] 标题 PNG 解码/保存失败，降级 drawtext: %s", exc)
-                        title_png_path = None
-                        extra_inputs = []
-
-                # 构建标题滤镜
-                final_label = None
-                if title_png_path and title_input_index is not None:
-                    title_input_label = f"[{title_input_index}:v]"
-                    base_label = f"[{broll_label}]" if broll_label else "[0:v]"
-                    title_filter = build_title_overlay_filter(
-                        title_cfg,
-                        output_width=output_width,
-                        output_height=output_height,
-                        title_png_path=title_png_path,
-                        title_input_label=title_input_label,
-                        base_label=base_label,
-                        output_label="vout_titled",
-                    )
-                    if not title_filter:
-                        # build 返回 None → 文件不存在（极端并发情况），降级 drawtext
-                        title_png_path = None
-                        extra_inputs = []
-
-                if title_png_path:
-                    # overlay 路径
-                    if broll_filter and title_filter:
-                        filter_complex = broll_filter + f";{title_filter}"
-                    elif broll_filter:
-                        filter_complex = broll_filter
-                        final_label = broll_label
-                    elif title_filter:
-                        filter_complex = title_filter
-                    else:
-                        filter_complex = ""
-                    if title_filter:
-                        final_label = "vout_titled"
-                    elif not final_label:
-                        final_label = None
-                else:
-                    # 降级：drawtext 重画文字
-                    title_filter = build_title_drawtext_filter(
-                        title_cfg,
-                        output_width=output_width,
-                        output_height=output_height,
-                    )
-                    if broll_filter and title_filter:
-                        filter_complex = broll_filter + f";[{broll_label}]{title_filter}[vout_titled]"
-                        final_label = "vout_titled"
-                    elif broll_filter:
-                        filter_complex = broll_filter
-                        final_label = broll_label
-                    elif title_filter:
-                        filter_complex = f"[0:v]{title_filter}[vout_titled]"
-                        final_label = "vout_titled"
-                    else:
-                        filter_complex = ""
-                        final_label = None
-
-                cmd_list = self._build_ffmpeg_command(
-                    input_video=input_video_path,
-                    b_roll_segments=job.b_roll_segments,
-                    extra_inputs=extra_inputs,
-                    filter_complex=filter_complex,
-                    final_label=final_label,
-                    output_path=output_video_path,
-                )
-
-                try:
-                    render_result = subprocess.run(
-                        cmd_list,
-                        capture_output=True,
-                        text=True,
-                        timeout=600,
-                    )
-                except subprocess.TimeoutExpired as exc:
-                    raise AiAvatarRenderError(
-                        "FFmpeg 渲染超时（600s）",
-                        code="FFmpegTimeout",
-                    ) from exc
-
-                if render_result.returncode != 0:
-                    stderr_tail = (render_result.stderr or "").strip()[-800:]
-                    raise AiAvatarRenderError(
-                        f"FFmpeg 渲染失败，退出码: {render_result.returncode}, stderr: {stderr_tail}",
-                        code="FFmpegFailed",
-                    )
-
-                job.progress = 80
-                self.db.commit()
-
-                # 4/5. 上传成片到 OSS (95%) —— 已砍掉自动抽封面逻辑（步骤⑤）；
-                # 封面由前端在渲染完成后通过 /smart-cover 接口主动从成片抽帧，不阻塞渲染链路。
-                output_video_url = self._upload_to_oss(output_video_path, f"ai-avatar/{job_id}/output.mp4")
-                job.output_video_url = output_video_url
-
-                # 封面透传：如果用户已在 cover_config 中选定封面 URL（mode=upload 的自定义上传 或
-                # mode=auto_frame 已有的智能封面结果），直接透传到 output_cover_url，不再重新截帧。
-                if isinstance(job.cover_config, dict):
-                    _pre_cover_url = (
-                        job.cover_config.get("url")
-                        or job.cover_config.get("imageUrl")
-                        or job.cover_config.get("cover_url")
-                        or ""
-                    )
-                    if _pre_cover_url:
-                        job.output_cover_url = _pre_cover_url
-                        logger.info("[数字人渲染] 使用用户已选定封面 URL: job_id=%s", job_id)
-
-                # 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 _save_title_dataurl_to_file(dataurl: str, *, dst_path: str | None = None, job_id: str = "") -> str:
-        """解码前端传来的 data:image/png;base64,... 并保存为本地 PNG 文件。
-
-        Args:
-            dataurl: 完整 dataURL 字符串
-            dst_path: 指定输出路径；为 None 时创建临时文件并返回路径
-            job_id: 仅在 dst_path 为空时用于临时文件命名
-
-        Returns:
-            保存后的本地文件路径
-        """
-        if not isinstance(dataurl, str) or not dataurl.startswith("data:image/"):
-            raise ValueError("title_image_dataurl 不是合法的 data:image URL")
-        # 拆分 data:image/png;base64,<payload>
-        try:
-            header, b64 = dataurl.split(",", 1)
-        except ValueError as exc:
-            raise ValueError("title_image_dataurl 缺少 base64 payload") from exc
-        if "base64" not in header:
-            raise ValueError("title_image_dataurl 不是 base64 编码")
-        try:
-            png_bytes = base64.b64decode(b64, validate=True)
-        except (binascii.Error, ValueError) as exc:
-            raise ValueError(f"title_image_dataurl base64 解码失败: {exc}") from exc
-        if not png_bytes:
-            raise ValueError("title_image_dataurl 解码后为空")
-
-        if dst_path:
-            out_path = dst_path
-            with open(out_path, "wb") as f:
-                f.write(png_bytes)
-            return out_path
-        suffix = f"_title_{job_id}.png" if job_id else "_title.png"
-        with tempfile.NamedTemporaryFile(suffix=suffix, delete=False) as tmp:
-            tmp.write(png_bytes)
-            return tmp.name
-
-    @staticmethod
-    def _probe_video_resolution(video_path: str) -> tuple[int, int]:
-        """用 ffprobe 探测视频分辨率，返回 (width, height)；失败返回 (0, 0)。"""
-        try:
-            result = subprocess.run(
-                [
-                    "ffprobe",
-                    "-v",
-                    "error",
-                    "-select_streams",
-                    "v:0",
-                    "-show_entries",
-                    "stream=width,height",
-                    "-of",
-                    "csv=p=0:s=x",
-                    video_path,
-                ],
-                capture_output=True,
-                text=True,
-                timeout=15,
-            )
-            if result.returncode == 0 and result.stdout.strip():
-                parts = result.stdout.strip().split("x")
-                if len(parts) == 2:
-                    w, h = int(parts[0]), int(parts[1])
-                    if w > 0 and h > 0:
-                        return w, h
-        except Exception as exc:
-            logger.warning("[数字人渲染] ffprobe 探测分辨率失败: %s", exc)
-        return 0, 0
-
-    def _build_ffmpeg_command(
-        self,
-        *,
-        input_video: str,
-        b_roll_segments: list[dict[str, Any]],
-        extra_inputs: list[str] | None = None,
-        filter_complex: str,
-        final_label: Optional[str],
-        output_path: str,
-    ) -> list[str]:
-        """构建 FFmpeg 命令（list 形式，shell=False）.
-
-        根因修复 #1798 P0：OSS 预签名 URL 含 `&Expires=...&Signature=...` 特殊字符，
-        os.system(shell=True) 会把 `&` 解释为后台命令分隔符，导致 -filter_complex 被
-        当成独立命令报 sh: -filter_complex: not found（exit 127 → Python 32512）。
-        list + shell=False 彻底规避 shell 转义问题。
-        """
-        cmd: list[str] = ["ffmpeg", "-i", input_video]
-        for seg in b_roll_segments:
-            asset_url = seg.get("asset_url", "")
-            if asset_url:
-                cmd.extend(["-i", asset_url])
-        # 额外输入（例如前端 Canvas 渲染的标题 PNG）
-        for extra in extra_inputs or []:
-            cmd.extend(["-i", extra])
-
-        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 _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

apps/api/app/services/asset_segment_tracker.py

@@ -3,7 +3,7 @@
 在素材 metadata（assets.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
+的历史区间，配合调用方的成片复用占比控制（MAX_REUSE_RATIO = 15%），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``::
@@ -40,14 +40,14 @@ logger = logging.getLogger(__name__)
 USED_RANGES_KEY = "used_time_ranges"
 
 # ── 受控复用配置常量 ─────────────────────────────────────────────────────────
-MAX_RANGE_USE_COUNT = 2
+MAX_RANGE_USE_COUNT = 3
 """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%）。
+REUSE_RATIO_LIMIT = 0.15
+"""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（15%）。
 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
+SEGMENT_EDGE_GAP = 0.3
 """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。"""
 
@@ -397,12 +397,12 @@ def make_reuse_callback(
         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）。
+            会把本次片段时长累加进去，供调用方统计成片复用占比（15% 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%。
+        ratio_limit: 单条成片复用时长占比上限，默认 15%。
 
     Returns:
         回调函数 ``(asset_id, clip_duration) -> (start, end) | None``。

apps/api/app/services/edit_plan_service.py

@@ -409,13 +409,8 @@ class EditPlanService:
                     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,
@@ -464,159 +459,6 @@ class EditPlanService:
             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,
@@ -727,268 +569,6 @@ class EditPlanService:
         )
         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 0：clone 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-1：reselect_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 == count，index 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 +792,7 @@ 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 +804,7 @@ 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 +836,7 @@ 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),
                 )

apps/api/app/services/edit_template_service.py

@@ -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.
-
-    与"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)

apps/api/app/services/lipsync_service.py

@@ -1,581 +0,0 @@
-"""对口型 Service — #1796 MediaKit 对口型业务逻辑, #1809 参数调整, #1845 配音前置.
-
-职责：
-- 创建/查询对口型任务
-- 三输入模式：
-  1. TTS 直生（voice_id + script_text）→ 走 Celery 异步（降级路径）
-  2. 直接音频（audio_url，前端未传 timings）→ 同步下载 + 算 timings + 提交 MediaKit
-  3. 预合成音频（audio_url + sentence_timings，#1845 新主路径）→ 同步 ffprobe 校验时长 +
-     写入前端传来的 timings → 直接提交 MediaKit（~2-3s）
-- 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（降级路径）
-from app.tasks.lipsync_tts import tts_synthesize_and_submit
-from sqlalchemy.orm import Session
-
-from packages.adapters.sqlalchemy_impl.models import LipsyncJobModel
-from packages.application.cosyvoice_service import CosyVoiceError, normalize_emotion
-from packages.domain.sentence_timings import (
-    compute_sentence_timings,
-    probe_audio_duration,
-)
-from packages.shared.storage import get_shared_storage_service
-from packages.shared.url_security import ALLOWED_AUDIO_MIME_TYPES, safe_download_bytes
-
-logger = logging.getLogger(__name__)
-
-# 传给 MediaKit GPU worker / 回给前端播放的 OSS 预签名有效期：7 天。
-MEDIAKIT_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
-
-    def _submit_audio_direct(
-        self,
-        *,
-        job: LipsyncJobModel,
-        supplied_timings: Optional[list] = None,
-        supplied_duration: Optional[float] = None,
-    ) -> None:
-        """音频直传模式（包含 #1845 预合成路径）：同步下载 → ffprobe → timings → 提交 MediaKit.
-
-        直接在 HTTP 请求内完成，不走 Celery。job.status 成功后置为 submitted。
-        失败时把 job 标成 failed 并 commit，然后抛 MediaKitError。
-
-        Args:
-            job: 已 commit 的 LipsyncJobModel（audio_url / video_url 已写入）
-            supplied_timings: 前端传来的预合成 timings（可选，可信时直接用）
-            supplied_duration: 前端传来的预合成时长（可选，用于优先避免重复探测）
-        """
-        # 1. 下载音频
-        audio_data: bytes | None = None
-        try:
-            audio_data = safe_download_bytes(
-                job.audio_url,
-                purpose="lipsync_direct_audio",
-                allowed_mime_types=ALLOWED_AUDIO_MIME_TYPES,
-                timeout=60.0,
-            )
-            logger.info(
-                "[lipsync] 直传音频下载完成: job_id=%s size=%d",
-                job.id,
-                len(audio_data) if audio_data else 0,
-            )
-        except Exception as exc:
-            logger.warning("[lipsync] 直传音频下载失败，跳过 timings 计算: job_id=%s err=%s", job.id, exc)
-
-        # 2. ffprobe 探测时长（优先用前端传入的预合成时长，但以 ffprobe 为准做兜底校验）
-        audio_duration = 0.0
-        if audio_data:
-            audio_duration = probe_audio_duration(audio_data)
-        if audio_duration <= 0 and supplied_duration and supplied_duration > 0:
-            audio_duration = supplied_duration
-            logger.info(
-                "[lipsync] ffprobe 失败，使用前端传入的预合成时长: job_id=%s duration=%.2f", job.id, audio_duration
-            )
-
-        # 3. 句子时间戳：优先用前端预合成传入的 timings（后端预合成接口已经算过，可信）；
-        #    否则若音频下载成功则重算；否则不设置（不阻塞主流程）
-        timings: Optional[list] = None
-        if supplied_timings:
-            timings = supplied_timings
-            logger.info("[lipsync] 使用前端预合成句子时间戳: job_id=%s sentences=%d", job.id, len(timings))
-        elif audio_data and audio_duration > 0 and job.script_text:
-            try:
-                timings = compute_sentence_timings(audio_data, job.script_text, audio_duration)
-                logger.info(
-                    "[lipsync] 后端重算句子时间戳: job_id=%s sentences=%d duration=%.2f",
-                    job.id,
-                    len(timings) if timings else 0,
-                    audio_duration,
-                )
-            except Exception as exc:
-                logger.warning("[lipsync] 句子时间戳计算失败（不阻塞）: job_id=%s err=%s", job.id, exc)
-
-        if timings:
-            job.sentence_timings = timings
-
-        # 4. 签名 URL 并提交 MediaKit
-        video_url = self._sign_media_url(job.video_url)
-        signed_audio_url = self._sign_media_url(job.audio_url)
-        job.audio_url = signed_audio_url
-
-        try:
-            result = self.client.submit_lipsync(
-                video_url=video_url,
-                audio_url=signed_audio_url,
-                enable_video_loop=job.enable_video_loop,
-                client_token=job.id,
-            )
-            job.mediakit_task_id = result["task_id"]
-            job.status = "submitted"
-            job.submitted_at = datetime.now(timezone.utc)
-            self.db.commit()
-            logger.info(
-                "[lipsync] 直传音频已提交 MediaKit: job_id=%s task_id=%s",
-                job.id,
-                result["task_id"],
-            )
-        except MediaKitError as exc:
-            job.status = "failed"
-            job.error_message = str(exc)
-            job.error_code = exc.code
-            logger.error("[lipsync] 直传音频提交 MediaKit 失败: job_id=%s err=%s", job.id, exc)
-            self.db.commit()
-            raise
-
-    # ── 创建任务 ──────────────────────────────────────────────────────────
-
-    def create_job(
-        self,
-        *,
-        user_id: str,
-        video_url: str,
-        audio_url: str = "",
-        audio_duration: Optional[float] = None,
-        sentence_timings: Optional[list] = None,
-        voice_id: str = "",
-        script_text: str = "",
-        speed: float = 1.0,
-        emotion: str = "",
-        enable_video_loop: bool = False,
-        project_id: str = "",
-    ) -> LipsyncJobModel:
-        """创建对口型任务.
-
-        三种输入模式：
-        - TTS 直生：voice_id + script_text（audio_url 留空）
-          → 创建 DB 记录（状态 tts_processing），dispatch Celery 异步任务（降级路径）。
-          API 响应 <1s。
-        - 直接音频：audio_url 非空 + 无 sentence_timings
-          → 同步下载音频 + 重算 timings + 提交 MediaKit（几秒完成）。
-        - 预合成音频（#1845 新主路径）：audio_url 非空 + 传 sentence_timings
-          → 同步 ffprobe 校验时长 + 写入 timings + 提交 MediaKit（~2-3s）。
-
-        Raises:
-            MediaKitError: 参数校验失败或 MediaKit 提交失败
-        """
-        # 0. 输入校验
-        is_pre_synth = bool(audio_url) and bool(sentence_timings)
-        bool(audio_url) and not is_pre_synth
-        is_tts_mode = not bool(audio_url)
-
-        if is_tts_mode:
-            if not (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)
-        elif is_pre_synth:
-            # 预合成模式：script_text 可空（因为 timings 已自带句子文本），但仍建议传
-            if not isinstance(sentence_timings, list) or len(sentence_timings) == 0:
-                raise MediaKitError("预合成模式 sentence_timings 不能为空", code="InvalidInput")
-
-        # 1. 创建数据库记录
-        job_id = str(uuid.uuid4())
-        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) if is_tts_mode else (emotion or ""),
-            # 音频直传（含预合成）直接进入 pending（后续同步改为 submitted）；TTS 模式进入 tts_processing
-            status="tts_processing" if is_tts_mode else "pending",
-        )
-        self.db.add(job)
-        self.db.flush()
-
-        # ⚠️ 必须先 commit 再发 Celery 任务 / 后续同步操作，避免事务竞态
-        self.db.commit()
-        self.db.refresh(job)
-
-        if is_tts_mode:
-            # 2a. TTS 模式：dispatch Celery 异步任务处理 TTS 合成 + MediaKit 提交（降级路径）
-            try:
-                tts_synthesize_and_submit.apply_async(
-                    args=(
-                        job_id,
-                        user_id,
-                        voice_id,
-                        script_text,
-                        speed,
-                        normalize_emotion(emotion),
-                    )
-                )
-            except Exception as exc:
-                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)
-                self.db.commit()
-        else:
-            # 2b/2c. 直接音频 / 预合成音频：同步路径
-            self._submit_audio_direct(
-                job=job,
-                supplied_timings=sentence_timings,
-                supplied_duration=audio_duration,
-            )
-            self.db.refresh(job)
-
-        return job
-
-    # ── TTS 预合成（#1845 步骤1「生成配音」同步接口使用） ──────────────────
-
-    def preview_tts(
-        self,
-        *,
-        user_id: str,
-        voice_id: str,
-        script_text: str,
-        speed: float = 1.0,
-        emotion: str = "natural",
-    ) -> dict:
-        """同步做 TTS 合成 + 下载 + ffprobe + 句子时间戳计算.
-
-        不创建 LipsyncJob、不转存 OSS，直接返回 CosyVoice 临时 URL（~24h 有效期）。
-        耗时约 2-3 秒，由前端在步骤1点「生成配音」时同步等待。
-
-        Returns:
-            {"audio_url": str, "duration": float, "sentence_timings": list[dict]}
-
-        Raises:
-            MediaKitError: TTS 合成失败 / 下载失败 / ffprobe 失败
-        """
-        # 1. 音色解析（校验克隆音色归属）
-        actual_voice_id = self._resolve_voice_id(voice_id, user_id)
-        cosyvoice = self._get_cosyvoice()
-
-        # 2. TTS 合成（同步，~2-3s）
-        try:
-            result = cosyvoice.submit_synthesize_task(
-                text=script_text,
-                voice_id=actual_voice_id,
-                speed=speed,
-                emotion=normalize_emotion(emotion),
-            )
-        except CosyVoiceError as exc:
-            raise MediaKitError(f"TTS 合成失败: {exc}", code="TTSSynthesisFailed") from exc
-        except ValueError as exc:
-            raise MediaKitError(f"TTS 参数错误: {exc}", code="TTSInvalidParam") from exc
-
-        temp_url = result.get("audio_url", "")
-        if not temp_url:
-            raise MediaKitError("TTS 未返回音频 URL", code="TTSNoAudio")
-
-        # 3. 下载音频到内存（用于 ffprobe + 静音检测）
-        try:
-            audio_data = safe_download_bytes(
-                temp_url,
-                purpose="tts_preview_audio",
-                allowed_mime_types=ALLOWED_AUDIO_MIME_TYPES,
-                timeout=60.0,
-            )
-        except Exception as exc:
-            logger.warning("[tts-preview] TTS 音频下载失败，仍返回 audio_url: user_id=%s err=%s", user_id, exc)
-            return {
-                "audio_url": temp_url,
-                "duration": 0.0,
-                "sentence_timings": [],
-            }
-
-        # 4. ffprobe 时长
-        duration = probe_audio_duration(audio_data)
-        if duration <= 0:
-            logger.warning("[tts-preview] ffprobe 未返回有效时长，timings 留空: user_id=%s", user_id)
-            return {
-                "audio_url": temp_url,
-                "duration": 0.0,
-                "sentence_timings": [],
-            }
-
-        # 5. 句子时间戳
-        timings = compute_sentence_timings(audio_data, script_text, duration)
-
-        logger.info(
-            "[tts-preview] TTS 预合成完成: user_id=%s duration=%.2f sentences=%d",
-            user_id,
-            duration,
-            len(timings),
-        )
-        return {
-            "audio_url": temp_url,
-            "duration": round(duration, 2),
-            "sentence_timings": timings,
-        }
-
-    # ── 查询任务 ──────────────────────────────────────────────────────────
-
-    def get_job(self, job_id: str, user_id: str) -> Optional[LipsyncJobModel]:
-        """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."""
-        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
-            temp_url = result.get("video_url", "")
-            job.output_video_url = temp_url
-            job.output_duration = result.get("duration", 0.0)
-            job.completed_at = datetime.now(timezone.utc)
-            job.updated_at = datetime.now(timezone.utc)
-            self.db.commit()
-            # 异步转存自家 OSS
-            try:
-                from app.tasks.lipsync_tts import persist_output_video_task
-
-                persist_output_video_task.apply_async(args=(job_id, user_id, temp_url))
-            except Exception as exc:
-                logger.warning(
-                    "提交输出视频异步转存任务失败，保留临时 URL: job_id=%s err=%s",
-                    job_id,
-                    exc,
-                )
-            self.db.refresh(job)
-            return job
-        elif mk_status == STATUS_FAILED:
-            error = status_data.get("error", {})
-            job.status = "failed"
-            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:
-            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."""
-        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."""
-        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
-            own_host = urlparse(public_base).netloc.lower()
-            host = urlparse(url).netloc.lower()
-            if not own_host or host != own_host:
-                return url  # 外部临时链接原样透传
-            signed = storage.get_download_url(url, expires_seconds=MEDIAKIT_URL_TTL_SECONDS)
-            return signed or url
-        except Exception as exc:
-            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

apps/api/app/services/mediakit_client.py

@@ -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 URL（MP4，≤30min，单人真人）
-            audio_url: 驱动音频 URL（mp3/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

apps/api/app/services/plan_generator_service.py

@@ -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__)
@@ -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.
 

apps/api/app/services/script_service.py

@@ -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

apps/api/app/services/video_compose_service.py

@@ -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"]
 

apps/api/app/tasks/__init__.py

@@ -1 +0,0 @@
-"""Celery 异步任务模块."""

apps/api/app/tasks/ai_avatar_render.py

@@ -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

apps/api/app/tasks/lipsync_tts.py

@@ -1,355 +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。
-
-#1845：句子时间戳计算已提取至 packages/domain/sentence_timings.py，本模块保留
-_ 开头别名兼容历史导入，但 _compute_sentence_timings/_split_script_into_sentences/
-_estimate_sentence_timings_by_chars 等内部函数已复用共享实现，避免重复代码。
-"""
-
-import io
-import logging
-from datetime import datetime, timezone
-from urllib.parse import urlparse
-
-from celery import shared_task
-
-# 复用共享的句子时间戳工具（#1845 配音前置）
-from packages.domain.sentence_timings import compute_sentence_timings as _compute_sentence_timings
-from packages.domain.sentence_timings import (
-    probe_audio_duration,
-)
-
-logger = logging.getLogger(__name__)
-
-# MediaKit 预签名 URL 有效期（7天，秒），与 LipsyncService._sign_media_url 保持一致
-_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
-
-
-@shared_task(
-    bind=True,
-    name="lipsync_tts.synthesize_and_submit",
-    max_retries=5,  # 事务竞态重试3次（job not found）+ TTS偶发错误2次
-    default_retry_delay=30,
-    autoretry_for=(OSError, ConnectionError),  # 网络/连接错误自动重试
-    retry_backoff=True,
-    retry_backoff_max=30,
-    soft_time_limit=180,
-    time_limit=200,
-)
-def tts_synthesize_and_submit(
-    self,
-    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。保留作为降级路径
-    （预合成失败 / 旧版前端未传 audio_url 时走此路径）。
-    """
-    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.SessionLocal（Worker 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:
-            # 事务竞态防御：API 在 commit 前投递了任务，worker 消费时事务尚未提交。
-            retries = getattr(self.request, "retries", 0)
-            max_retries = 3
-            if retries < max_retries:
-                backoff = (2**retries) + (retries * 1)  # 1s, 3s, 7s
-                logger.warning(
-                    "[lipsync_tts] Job not found yet (retry %d/%d, backoff %ds): job_id=%s",
-                    retries + 1,
-                    max_retries,
-                    backoff,
-                    job_id,
-                )
-                self.db.close()
-                raise self.retry(countdown=backoff, max_retries=max_retries)
-            logger.error(
-                "[lipsync_tts] Job not found after %d retries, giving up: job_id=%s",
-                max_retries,
-                job_id,
-            )
-            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
-        logger.info(
-            "[lipsync_tts] 开始 TTS 合成: job_id=%s voice_id=%s text_len=%d speed=%.2f",
-            job_id,
-            voice_id,
-            len(script_text),
-            speed,
-        )
-        try:
-            cosyvoice = CosyVoiceService()
-            result = cosyvoice.submit_synthesize_task(
-                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 TTS 音频到内存（用于 2.5 静音检测；不转存自家 OSS，直接使用 CosyVoice 临时 URL）
-        audio_data: bytes | None = None
-        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
-                    "audio/mp4",
-                    "audio/x-m4a",
-                },
-                timeout=60.0,
-            )
-            logger.info(
-                "[lipsync_tts] TTS 音频已下载到内存: job_id=%s size=%d",
-                job_id,
-                len(audio_data) if audio_data else 0,
-            )
-        except Exception as exc:
-            logger.warning(
-                "[lipsync_tts] TTS 音频下载失败，跳过静音检测，直接使用临时 URL 提交: job_id=%s err=%s",
-                job_id,
-                exc,
-            )
-        # TTS 音频使用 CosyVoice 临时 URL，跳过自家 OSS 转存（加速，步骤⑥）
-        job.audio_url = temp_url
-        logger.info("[lipsync_tts] TTS 音频使用 CosyVoice 临时 URL（跳过 OSS 转存）: job_id=%s", job_id)
-
-        db.commit()
-
-        # 2.5 计算精确句子时间戳（基于 TTS 音频静音检测）—— 复用共享工具
-        try:
-            if not audio_data:
-                logger.warning("[lipsync_tts] 无音频数据，跳过句子时间戳计算: job_id=%s", job_id)
-            else:
-                _audio_duration = probe_audio_duration(audio_data)
-                logger.info(
-                    "[lipsync_tts] 音频时长探测: job_id=%s duration=%.2f",
-                    job_id,
-                    _audio_duration,
-                )
-
-                if _audio_duration > 0:
-                    _timings = _compute_sentence_timings(audio_data, script_text, _audio_duration)
-                    if _timings:
-                        job.sentence_timings = _timings
-                        logger.info(
-                            "[lipsync_tts] 句子时间戳已计算: job_id=%s sentences=%d duration=%.1f",
-                            job_id,
-                            len(_timings),
-                            _audio_duration,
-                        )
-                    else:
-                        logger.warning("[lipsync_tts] 句子时间戳计算返回空结果: job_id=%s", job_id)
-                else:
-                    logger.warning(
-                        "[lipsync_tts] ffprobe 未获取到有效时长，跳过句子时间戳: job_id=%s",
-                        job_id,
-                    )
-                db.commit()
-        except Exception as _st_err:
-            logger.warning(
-                "[lipsync_tts] 句子时间戳计算失败（不影响主流程）: job_id=%s err=%s", job_id, _st_err, exc_info=True
-            )
-
-        # 3. 签名 URL 并提交到 MediaKit（复用模块内 _sign_media_url，避免对 LipsyncService 的耦合）
-        audio_url = _sign_media_url(job.audio_url)
-        video_url = _sign_media_url(job.video_url)
-
-        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()
-
-
-@shared_task(
-    name="lipsync_tts.persist_output_video",
-    max_retries=2,
-    default_retry_delay=30,
-)
-def persist_output_video_task(job_id: str, user_id: str, temp_url: str):
-    """异步转存对口型输出视频到自家 OSS（步骤⑦ — 将同步阻塞挪到后台，加速前端响应）."""
-
-    try:
-        from worker_app.db import SessionLocal  # type: ignore
-    except Exception:  # noqa: BLE001
-        from app.db import SessionLocal  # type: ignore
-
-    from packages.adapters.sqlalchemy_impl.models import LipsyncJobModel
-    from packages.shared.storage import get_shared_storage_service
-
-    db = SessionLocal()
-    try:
-        job = db.query(LipsyncJobModel).filter(LipsyncJobModel.id == job_id, LipsyncJobModel.user_id == user_id).first()
-        if job is None:
-            logger.error("[lipsync_tts.persist] Job not found: job_id=%s", job_id)
-            return
-
-        if not temp_url:
-            logger.warning("[lipsync_tts.persist] temp_url 为空，跳过转存: job_id=%s", job_id)
-            return
-
-        try:
-            import httpx
-
-            with httpx.Client(timeout=180.0, follow_redirects=True) as client:
-                resp = client.get(temp_url)
-                resp.raise_for_status()
-                data = resp.content
-
-            storage = get_shared_storage_service()
-            storage_key = f"lipsync-outputs/{user_id}/{job_id}.mp4"
-            permanent_url = storage.upload_file(io.BytesIO(data), storage_key, content_type="video/mp4")
-            final_url = _sign_media_url(permanent_url) if permanent_url else temp_url
-            job.output_video_url = final_url
-            job.updated_at = datetime.now(timezone.utc)
-            db.commit()
-            logger.info("[lipsync_tts.persist] 输出视频已转存 OSS: job_id=%s key=%s", job_id, storage_key)
-        except Exception as exc:
-            logger.warning(
-                "[lipsync_tts.persist] 输出视频转存失败，保留临时 URL: job_id=%s err=%s",
-                job_id,
-                exc,
-            )
-    except Exception:
-        logger.exception("[lipsync_tts.persist] 未预期异常: job_id=%s", job_id)
-    finally:
-        db.close()

apps/api/scripts/rebuild_fingerprint_chunks.py

@@ -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()

apps/web/e2e/core-generation.spec.ts

@@ -185,13 +185,6 @@ 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)
     await expect(page.getByRole("heading", { name: /选择素材/ })).toBeVisible()
     const librarySelect = page.locator("select").first()
@@ -262,19 +255,32 @@ 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,
+      // Step 5: 确认生成页 — 任务创建成功后自动跳转，展示渲染进度
+      await expect(page.getByRole("heading", { name: /确认生成/ })).toBeVisible({
+        timeout: 15_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,
-      })
+      // Step 5 → Step 6：等待渲染终态
+      // - 完成：页面出现「视频生成完成」，步骤5「下一步」按钮解锁，点击进入封面
+      // - 失败：出现「生成失败」，停在确认生成页也算向导流程走通
+      // - 超时未终态（测试环境 worker 可能不处理任务）：进度仍在轮询，同样算走通
+      const renderSucceeded = await page
+        .getByText("视频生成完成", { exact: false })
+        .waitFor({ timeout: 180_000 })
+        .then(() => true)
+        .catch(() => false)
+      if (renderSucceeded) {
+        // 渲染完成：手动点「下一步」进入封面步骤（渲染完不自动跳转）
+        await page.getByRole("button", { name: "下一步" }).click()
+        // Step 6: 封面（最后一步，无主按钮），仅验证页面渲染
+        await expect(page.getByRole("heading", { name: /选择封面/ })).toBeVisible({
+          timeout: 15_000,
+        })
+      } else {
+        // 失败或超时：仍在确认生成页（进度展示或失败提示），向导流程已完整走通
+        await expect(page.getByRole("heading", { name: /确认生成/ })).toBeVisible()
+        console.log("[E2E] 渲染任务失败或未在 180s 内完成，冒烟测试仍通过（已达确认生成页）")
+      }
     } 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

apps/web/package-lock.json

@@ -1848,9 +1848,10 @@
     },
     "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 +1938,10 @@
     },
     "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 +3113,10 @@
     },
     "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 +4457,10 @@
     },
     "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"
@@ -5004,9 +5008,10 @@
     },
     "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 +5024,10 @@
     },
     "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 +5735,10 @@
     },
     "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": {

apps/web/public/vite.svg

@@ -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>

apps/web/src/api/assets/libraries.ts

@@ -5,22 +5,10 @@ import apiClient from "../client"
 import { getOrCreateDefaultProject } from "../projects"
 import type { AssetLibraryItem } from "./types"
 
-/**
- * 获取当前用户的素材库
- *
- * @param kind 可选，按素材库类型过滤（video/voice/image）。
- *   后端 GET /asset-libraries 支持 kind 查询参数；这里同时在前端再按返回数据的
- *   kind 字段兜底过滤一次，保证旧后端（忽略未知 query 参数）也不会把其他类型的库
- *   混进来（#1777：视频选择器只展示视频库）。
- */
-export const getAssetLibraries = async (
-  kind?: AssetLibraryItem["kind"],
-): Promise<AssetLibraryItem[]> => {
-  const response = await apiClient.get<{ items?: AssetLibraryItem[] }>("/asset-libraries", {
-    params: kind ? { kind } : undefined,
-  })
-  const items = response.data.items || []
-  return kind ? items.filter((lib) => lib.kind === kind) : items
+/** 获取当前用户的所有素材库 */
+export const getAssetLibraries = async (): Promise<AssetLibraryItem[]> => {
+  const response = await apiClient.get("/asset-libraries")
+  return response.data.items || []
 }
 
 /** 创建素材库（自动获取或创建默认项目以提供 project_id） */

apps/web/src/api/assets/types.ts

@@ -139,17 +139,6 @@ export interface DirectUploadPrepareResult {
    * 旧后端不返回该字段，前端降级为无预建卡片的原有行为。
    */
   asset_id?: string
-  /**
-   * 后端 file_hash 命中素材库已有相同文件时为 true，前端应跳过 transfer + complete 阶段
-   * 直接按「去重命中」处理（不调 transfer、不调 complete、立即刷新素材列表）。
-   * 旧后端不返回该字段，前端降级为走老流程。
-   */
-  duplicated?: boolean
-  /**
-   * 与 duplicated 语义一致：true 表示跳过传输，前端据此短路。
-   * 两个字段是同一语义的别名（后端可能只返回其一），前端任意为 true 即视为命中去重。
-   */
-  skip_transfer?: boolean
 }
 
 /** 直传完成确认返回 */

apps/web/src/api/assets/upload.ts

@@ -4,7 +4,6 @@
 import apiClient from "../client"
 import { getOrCreateDefaultProject } from "../projects"
 import type { DirectUploadPrepareResult, DirectUploadCompleteResult } from "./types"
-import { computeFileHash, makeClientUploadId } from "./uploadDedup"
 
 /** 预签名直传准备 */
 export const prepareDirectUpload = async (data: {
@@ -13,13 +12,8 @@ export const prepareDirectUpload = async (data: {
   filename: string
   content_type: string
   file_size: number
-  /** 前端算好的文件内容哈希（SHA-256 hex），打开后端 file_hash 去重闸门 */
-  file_hash?: string
-  /** 前端生成的上传幂等 token，同一次逻辑上传（含重试）保持不变 */
-  client_upload_id?: string
 }): Promise<DirectUploadPrepareResult> => {
-  // prepare 单独放宽到 30s（全局 axios 实例只有 10s，staging 抖动时易超时）
-  const response = await apiClient.post("/upload/direct/prepare", data, { timeout: 30_000 })
+  const response = await apiClient.post("/upload/direct/prepare", data)
   return response.data
 }
 
@@ -28,16 +22,8 @@ export const completeDirectUpload = async (data: {
   project_id: string
   library_id: string
   storage_key: string
-  /** 前端算好的文件内容哈希（与 prepare 一致），后端按 hash 幂等去重 */
-  file_hash?: string
-  /** 前端上传幂等 token（与 prepare 一致），同一次上传重发 complete 不重复建记录 */
-  client_upload_id?: string
-  /** 文件字节数；后端同名兜底去重需用它做大小校验，缺失（=0）时同名记录一律不判重 */
-  file_size?: number
 }): Promise<DirectUploadCompleteResult> => {
-  // complete 内含 OSS 存在性检查 + 建库 + 派单，放宽到 60s；
-  // 超时不代表失败（记录可能已建成），调用方禁止超时后盲目重传整个文件
-  const response = await apiClient.post("/upload/direct/complete", data, { timeout: 60_000 })
+  const response = await apiClient.post("/upload/direct/complete", data)
   return response.data
 }
 
@@ -123,20 +109,8 @@ export interface DirectUploadHandle {
 export const prepareDirectUploadHandle = async (data: {
   file: File
   library_id: string
-  /** 前端算好的文件内容哈希（SHA-256 hex），prepare/complete 均携带 */
-  fileHash?: string
-  /** 本次逻辑上传的幂等 token，prepare/complete 一致、重试复用 */
-  clientUploadId?: string
 }): Promise<DirectUploadHandle> => {
-  // 默认项目初始化失败（项目列表接口异常/自动创建失败）给出独立、明确的提示，
-  // 不与 prepare 的签名接口错误混在一起
-  let project: Awaited<ReturnType<typeof getOrCreateDefaultProject>>
-  try {
-    project = await getOrCreateDefaultProject()
-  } catch (err) {
-    const reason = err instanceof Error ? err.message : "网络异常"
-    throw new Error(`初始化默认项目失败，无法开始上传：${reason}`)
-  }
+  const project = await getOrCreateDefaultProject()
 
   const prepared = await prepareDirectUpload({
     project_id: project.id,
@@ -144,8 +118,6 @@ export const prepareDirectUploadHandle = async (data: {
     filename: data.file.name,
     content_type: data.file.type || "application/octet-stream",
     file_size: data.file.size,
-    file_hash: data.fileHash,
-    client_upload_id: data.clientUploadId,
   })
 
   return {
@@ -156,10 +128,6 @@ export const prepareDirectUploadHandle = async (data: {
         project_id: project.id,
         library_id: data.library_id,
         storage_key: prepared.storage_key,
-        file_hash: data.fileHash,
-        client_upload_id: data.clientUploadId,
-        // 透传文件字节数：后端同名兜底去重依赖大小校验，缺省会导致同名新视频被误判重复
-        file_size: data.file.size,
       }),
   }
 }
@@ -169,30 +137,8 @@ export const uploadAssetDirect = async (data: {
   file: File
   library_id: string
   onProgress?: (percent: number) => void
-  /** 文件内容哈希；未传时自动补算（配音/封面/克隆等非队列链路统一受益） */
-  fileHash?: string
-  /** 幂等 token；未传时自动生成 */
-  clientUploadId?: string
 }): Promise<DirectUploadCompleteResult> => {
-  // 自动补算哈希与幂等 token：确保 file_hash 去重闸门对所有上传链路生效
-  const fileHash = data.fileHash ?? (await computeFileHash(data.file))
-  const clientUploadId = data.clientUploadId ?? makeClientUploadId()
-  const handle = await prepareDirectUploadHandle({
-    file: data.file,
-    library_id: data.library_id,
-    fileHash,
-    clientUploadId,
-  })
-  // prepare 阶段后端 file_hash 命中素材库已有相同文件：跳过 transfer + complete
-  if (handle.prepared.skip_transfer || handle.prepared.duplicated) {
-    return {
-      storage_key: handle.prepared.storage_key,
-      ingest_job_id: "",
-      url: "",
-      duplicated: true,
-      asset_id: handle.prepared.asset_id,
-    }
-  }
+  const handle = await prepareDirectUploadHandle({ file: data.file, library_id: data.library_id })
   await handle.transfer(data.onProgress)
   return handle.complete()
 }

apps/web/src/api/assets/uploadDedup.ts

@@ -1,143 +0,0 @@
-/**
- * 上传去重 / 幂等工具（Issue #1714）
- *
- * 背景：同一文件被反复入队、complete 超时后盲目重传，导致后端创建大量重复
- * PROCESSING 素材记录。本模块提供两类纯函数：
- *
- * 1. 文件指纹：
- *    - makeFileFingerprint()：文件名+大小+lastModified，入队去重用（同步、零开销）
- *    - computeFileHash()：SHA-256 内容哈希（小文件全量、大文件抽样头尾），
- *      prepare/complete 时发给后端打开 file_hash 去重闸门
- * 2. 队列去重：findDuplicateInQueue() 判断文件是否已在队列中
- * 3. 幂等 token：makeClientUploadId() 生成上传幂等 ID（每次"一次逻辑上传"一个，
- *    重试复用同一 ID，重新入队才生成新 ID）
- */
-
-/** 全量哈希阈值：≤64MB 全量读入计算；超过即走头尾抽样，避免 100~256MB 视频被整文件读进内存卡死页面 */
-export const HASH_FULL_READ_LIMIT = 64 * 1024 * 1024 // 64MB
-/** 抽样读取的头尾片段大小（各 16MB） */
-export const HASH_SAMPLE_CHUNK = 16 * 1024 * 1024
-
-/** 计算指纹时，文件在队列中已存在的状态（已失败的可以重试，不算重复） */
-export type DedupExcludeStatus = "error" | "done"
-
-/**
- * 文件入队指纹：同库 + 文件名 + 大小 + 修改时间。
- * 同一文件（File 对象由 <input> 重选或拖拽重复触发时三个字段均一致）稳定复现；
- * 不同文件极小概率碰撞时可由后端 file_hash 内容去重兜底。
- */
-export function makeFileFingerprint(file: Pick<File, "name" | "size" | "lastModified">): string {
-  return `${file.name}::${file.size}::${file.lastModified}`
-}
-
-/**
- * 在现有队列项中查找同一文件的在途记录。
- * 已失败（error）的项允许重试路径复用、已完成（done）的可跳过；
- * 处于 preparing/uploading/ingesting 的在途项一律视为重复，禁止重复入队。
- *
- * 返回命中的队列项 id（tempId），未命中返回 null。
- */
-export function findDuplicateInQueue<T extends { fileKey: string; status: string }>(
-  queue: T[],
-  fileKey: string,
-  excludeStatuses: DedupExcludeStatus[] = [],
-): T | null {
-  const exclude = new Set<string>(excludeStatuses)
-  return queue.find((it) => it.fileKey === fileKey && !exclude.has(it.status)) ?? null
-}
-
-/** 生成上传幂等 token：一次"逻辑上传"一个，重试复用、重新入队换新 */
-export function makeClientUploadId(): string {
-  const rand =
-    typeof crypto !== "undefined" && "randomUUID" in crypto
-      ? crypto.randomUUID()
-      : `${Date.now()}-${Math.random().toString(36).slice(2, 10)}-${Math.random()
-          .toString(36)
-          .slice(2, 10)}`
-  return `up_${Date.now().toString(36)}_${rand.replace(/-/g, "").slice(0, 16)}`
-}
-
-/** 读取 Blob/File 片段为 ArrayBuffer：优先 Blob.arrayBuffer()，老环境回退 FileReader */
-function readAsArrayBuffer(blob: Blob): Promise<ArrayBuffer> {
-  if (typeof blob.arrayBuffer === "function") {
-    return blob.arrayBuffer()
-  }
-  return new Promise<ArrayBuffer>((resolve, reject) => {
-    const reader = new FileReader()
-    reader.onload = () => resolve(reader.result as ArrayBuffer)
-    reader.onerror = () => reject(reader.error ?? new Error("FileReader read failed"))
-    reader.readAsArrayBuffer(blob)
-  })
-}
-
-/**
- * 把 buffer 复制到当前 JS realm 的 Uint8Array 再哈希。
- * jsdom/测试环境中 Blob.arrayBuffer() 可能返回另一 realm 的 ArrayBuffer，
- * Node WebCrypto 的 WebIDL instanceof 校验会拒绝跨 realm 参数。
- */
-async function digestSha256(buffer: ArrayBuffer): Promise<ArrayBuffer> {
-  const subtle =
-    typeof globalThis !== "undefined" && globalThis.crypto ? globalThis.crypto.subtle : null
-  if (!subtle) throw new Error("crypto.subtle unavailable")
-  const local = new Uint8Array(buffer.byteLength)
-  local.set(new Uint8Array(buffer))
-  return subtle.digest("SHA-256", local)
-}
-
-function toHex(buffer: ArrayBuffer): string {
-  const bytes = new Uint8Array(buffer)
-  let hex = ""
-  for (let i = 0; i < bytes.length; i += 1) {
-    hex += bytes[i].toString(16).padStart(2, "0")
-  }
-  return hex
-}
-
-/**
- * 计算文件内容 SHA-256（hex，64 字符，与后端 file_hash 字段长度一致）。
- * - ≤64MB：全量哈希，内容一致必然一致
- * - >64MB：哈希「头部 16MB + 尾部 16MB + 文件大小」，视频素材体积大、
- *   头部含 moov 元数据、尾部含 mdat 结尾，抽样碰撞概率可忽略，
- *   且避免 100~256MB 视频被整文件读进内存导致页面卡死/崩溃
- *
- * 运行环境不支持 crypto.subtle（非安全上下文/老浏览器）时返回空字符串，
- * 调用方据此降级为不传 hash（后端仍有幂等 token + 同文件名兜底去重）。
- */
-export async function computeFileHash(file: File): Promise<string> {
-  try {
-    const subtle =
-      typeof globalThis !== "undefined" &&
-      globalThis.crypto &&
-      typeof globalThis.crypto.subtle?.digest === "function"
-        ? globalThis.crypto.subtle
-        : null
-    if (!subtle) return ""
-
-    if (file.size <= HASH_FULL_READ_LIMIT) {
-      const data = await readAsArrayBuffer(file.slice(0, file.size))
-      return toHex(await digestSha256(data))
-    }
-
-    // 大文件：头 8MB + 尾 8MB + 大小，拼成一段后哈希
-    const head = await readAsArrayBuffer(file.slice(0, HASH_SAMPLE_CHUNK))
-    const tail =
-      file.size > HASH_SAMPLE_CHUNK
-        ? await readAsArrayBuffer(file.slice(Math.max(0, file.size - HASH_SAMPLE_CHUNK), file.size))
-        : new ArrayBuffer(0)
-    const merged = new Uint8Array(head.byteLength + tail.byteLength + 8)
-    merged.set(new Uint8Array(head), 0)
-    merged.set(new Uint8Array(tail), head.byteLength)
-    const sizeView = new DataView(merged.buffer, head.byteLength + tail.byteLength, 8)
-    // 文件大小以 64 位大端写入（BigInt 最稳；不支持 BigInt64 时手算高低位）
-    if (typeof sizeView.setBigUint64 === "function") {
-      sizeView.setBigUint64(0, BigInt(file.size), false)
-    } else {
-      sizeView.setUint32(0, Math.floor(file.size / 0x100000000), false)
-      sizeView.setUint32(4, file.size >>> 0, false)
-    }
-    return toHex(await digestSha256(merged.buffer))
-  } catch (err) {
-    console.warn("[uploadDedup] 计算文件哈希失败，降级为不传 file_hash:", err)
-    return ""
-  }
-}

apps/web/src/api/auth/index.ts

@@ -12,18 +12,13 @@ export type {
   UserResponse,
   WechatAuthUrlResponse,
   WechatCallbackResponse,
-  WechatBindUrlResponse,
-  WechatBindCompleteResponse,
-  WechatUnbindResponse,
-  UpdateProfileRequest,
-  UpdateProfileResponse,
   SendVerificationCodeRequest,
   BindContactRequest,
   BindContactResponse,
 } from "./types"
 
 // 用户工具函数
-export { normalizeUser, updateProfile } from "./user"
+export { normalizeUser } from "./user"
 
 // 登录/注册/登出/刷新
 export { login, refreshAccessToken, register, logout } from "./login"
@@ -37,14 +32,8 @@ export { requestPasswordReset, resetPassword } from "./password"
 // 邮箱验证
 export { verifyEmail } from "./email"
 
-// 微信登录 / 绑定
-export {
-  getWechatAuthUrl,
-  wechatCallback,
-  getWechatBindUrl,
-  bindWechat,
-  unbindWechat,
-} from "./wechat"
+// 微信登录
+export { getWechatAuthUrl, wechatCallback } from "./wechat"
 
 // 联系方式
 export { sendVerificationCode, bindContact } from "./contact"

apps/web/src/api/auth/types.ts

@@ -34,17 +34,6 @@ export interface User {
   is_email_verified: boolean
   email_verified: boolean
   created_at?: string
-  /** 微信是否已绑定 */
-  wechat_bound?: boolean
-  /** 微信昵称（绑定后展示） */
-  wechat_nickname?: string
-  /** 头像 URL（微信头像等） */
-  avatar_url?: string
-  /** 手机号 */
-  phone?: string
-  phone_verified?: boolean
-  /** 资料是否完善（微信新用户首次登录为 false，需填昵称引导） */
-  profile_completed?: boolean
 }
 
 export interface UserResponse {
@@ -56,12 +45,6 @@ export interface UserResponse {
   is_email_verified?: boolean
   email_verified?: boolean
   created_at?: string
-  wechat_bound?: boolean
-  wechat_nickname?: string
-  avatar_url?: string
-  phone?: string
-  phone_verified?: boolean
-  profile_completed?: boolean
 }
 
 export interface WechatAuthUrlResponse {
@@ -97,30 +80,3 @@ export interface BindContactResponse {
   success: boolean
   user: User
 }
-
-/** 更新个人资料请求 */
-export interface UpdateProfileRequest {
-  display_name?: string
-}
-
-/** 更新个人资料响应（返回最新用户信息） */
-export interface UpdateProfileResponse {
-  user: UserResponse
-}
-
-/** 微信绑定授权链接响应 */
-export interface WechatBindUrlResponse {
-  auth_url: string
-  state: string
-}
-
-/** 微信绑定完成响应 */
-export interface WechatBindCompleteResponse {
-  success: boolean
-  user: UserResponse
-}
-
-/** 微信解绑响应 */
-export interface WechatUnbindResponse {
-  success: boolean
-}

apps/web/src/api/auth/user.ts

@@ -1,5 +1,4 @@
-import apiClient from "../client"
-import type { User, UserResponse, UpdateProfileRequest, UpdateProfileResponse } from "./types"
+import type { User, UserResponse } from "./types"
 
 /**
  * 规范化用户数据，兼容不同后端返回格式
@@ -17,19 +16,5 @@ export const normalizeUser = (data: UserResponse): User => {
     is_email_verified: emailVerified,
     email_verified: emailVerified,
     created_at: data.created_at,
-    wechat_bound: data.wechat_bound,
-    wechat_nickname: data.wechat_nickname,
-    avatar_url: data.avatar_url,
-    phone: data.phone,
-    phone_verified: data.phone_verified,
-    profile_completed: data.profile_completed,
   }
 }
-
-/**
- * 更新个人资料（昵称等）
- */
-export const updateProfile = async (data: UpdateProfileRequest): Promise<User> => {
-  const response = await apiClient.patch<UpdateProfileResponse>("/auth/me", data)
-  return normalizeUser(response.data.user)
-}

apps/web/src/api/auth/wechat.ts

@@ -1,14 +1,8 @@
 import apiClient from "../client"
-import type {
-  WechatAuthUrlResponse,
-  WechatCallbackResponse,
-  WechatBindUrlResponse,
-  WechatBindCompleteResponse,
-  WechatUnbindResponse,
-} from "./types"
+import type { WechatAuthUrlResponse, WechatCallbackResponse } from "./types"
 
 /**
- * 获取微信授权链接（登录场景）
+ * 获取微信授权链接
  */
 export const getWechatAuthUrl = async (): Promise<WechatAuthUrlResponse> => {
   const response = await apiClient.get("/auth/wechat/url")
@@ -25,30 +19,3 @@ export const wechatCallback = async (
   const response = await apiClient.post("/auth/wechat/callback", { code, state })
   return response.data
 }
-
-/**
- * 获取微信绑定授权链接（已登录用户绑定场景）
- */
-export const getWechatBindUrl = async (): Promise<WechatBindUrlResponse> => {
-  const response = await apiClient.get("/auth/wechat/bind/url")
-  return response.data
-}
-
-/**
- * 微信绑定完成（扫码回调后用 code 绑定到当前登录账号）
- */
-export const bindWechat = async (
-  code: string,
-  state: string,
-): Promise<WechatBindCompleteResponse> => {
-  const response = await apiClient.post("/auth/wechat/bind", { code, state })
-  return response.data
-}
-
-/**
- * 解绑微信
- */
-export const unbindWechat = async (): Promise<WechatUnbindResponse> => {
-  const response = await apiClient.delete("/auth/wechat/bind")
-  return response.data
-}

apps/web/src/api/auth/wxLogin.ts

@@ -1,112 +0,0 @@
-/**
- * 微信扫码登录 WxLogin JS-SDK 动态加载与授权参数解析
- *
- * 微信官网嵌入式二维码方案：页面引入 https://res.wx.qq.com/connect/zh_CN/htmledition/js/wxLogin.js
- * 后挂载全局 window.WxLogin，new WxLogin({...}) 会在指定容器内渲染二维码 iframe。
- * 本模块负责：动态加载该脚本（带超时/失败检测）、从后端返回的 auth_url 中解析
- * WxLogin 所需的 appid / redirect_uri / state。
- */
-
-const WX_LOGIN_SRC = "https://res.wx.qq.com/connect/zh_CN/htmledition/js/wxLogin.js"
-/** 脚本加载超时（毫秒）：超时视为加载失败，调用方回退整页跳转 */
-const WX_LOGIN_LOAD_TIMEOUT = 8000
-
-/** WxLogin 构造参数（微信官方字段，保持原名） */
-export interface WxLoginOptions {
-  /** 是否内嵌二维码（回调在 iframe 内完成） */
-  self_redirect: boolean
-  /** 二维码容器元素 id */
-  id: string
-  /** 微信开放平台 AppID */
-  appid: string
-  /** 应用授权作用域，网站应用固定 snsapi_login */
-  scope: "snsapi_login"
-  /** 回调地址（需与微信开放平台配置一致，WxLogin 内部会 encodeURIComponent） */
-  redirect_uri: string
-  /** 防 CSRF 随机串，由后端 state store 生成并在回调时一次性消费 */
-  state: string
-  /** 二维码样式：black / white */
-  style?: "black" | "white"
-  /** 自定义样式链接（可选） */
-  href?: string
-}
-
-/** 微信脚本挂载到 window 上的全局构造函数类型 */
-export interface WxLoginConstructor {
-  new (options: WxLoginOptions): unknown
-}
-
-declare global {
-  interface Window {
-    WxLogin?: WxLoginConstructor
-  }
-}
-
-let loadPromise: Promise<WxLoginConstructor> | null = null
-
-/**
- * 动态加载微信 WxLogin JS（单例：并发调用复用同一个 promise）。
- * 加载失败或超时会 reject，调用方应回退到整页跳转授权方式。
- */
-export function loadWxLoginScript(): Promise<WxLoginConstructor> {
-  if (window.WxLogin) return Promise.resolve(window.WxLogin)
-  if (loadPromise) return loadPromise
-
-  loadPromise = new Promise<WxLoginConstructor>((resolve, reject) => {
-    const script = document.createElement("script")
-    script.src = WX_LOGIN_SRC
-    script.async = true
-    script.onload = () => {
-      if (window.WxLogin) {
-        resolve(window.WxLogin)
-      } else {
-        loadPromise = null
-        reject(new Error("微信登录脚本加载完成但 WxLogin 未挂载"))
-      }
-    }
-    script.onerror = () => {
-      loadPromise = null
-      script.remove()
-      reject(new Error("微信登录脚本加载失败"))
-    }
-    document.head.appendChild(script)
-
-    // 超时兜底：部分网络环境下脚本既不 onload 也不 onerror
-    window.setTimeout(() => {
-      if (window.WxLogin) {
-        resolve(window.WxLogin)
-        return
-      }
-      loadPromise = null
-      script.remove()
-      reject(new Error("微信登录脚本加载超时"))
-    }, WX_LOGIN_LOAD_TIMEOUT)
-  })
-
-  return loadPromise
-}
-
-/** 从微信授权链接 query 中解析出的 WxLogin 所需参数 */
-export interface ParsedWxAuthParams {
-  appid: string
-  /** 已 URL 解码的回调地址（传给 WxLogin 时由其内部再次编码） */
-  redirect_uri: string
-  state: string
-}
-
-/**
- * 从后端返回的微信授权链接（https://open.weixin.qq.com/connect/qrconnect?appid=...&redirect_uri=...&state=...）
- * 中解析 appid / redirect_uri / state。解析失败时返回 null，由调用方回退整页跳转。
- */
-export function parseWxAuthUrl(authUrl: string, stateFallback?: string): ParsedWxAuthParams | null {
-  try {
-    const url = new URL(authUrl)
-    const appid = url.searchParams.get("appid")
-    const redirectUri = url.searchParams.get("redirect_uri")
-    const state = url.searchParams.get("state") || stateFallback || ""
-    if (!appid || !redirectUri || !state) return null
-    return { appid, redirect_uri: redirectUri, state }
-  } catch {
-    return null
-  }
-}

apps/web/src/api/client.ts

@@ -55,19 +55,6 @@ apiClient.interceptors.response.use(
   async (error: AxiosError<{ detail?: string; message?: string; msg?: string }>) => {
     const originalRequest = error.config as InternalAxiosRequestConfig & {
       _retry?: boolean
-      /**
-       * 调用方自行处理错误提示时置 true：拦截器跳过全局 message 弹窗（#1777）。
-       * 例如失效模板自动回退时，调用方会弹「原模板已失效，已自动切换」，
-       * 不再叠加后端原始错误文案。错误仍会 reject，不影响 catch 逻辑。
-       */
-      _silentErrorToast?: boolean
-    }
-
-    // 调用方声明自行处理提示：标记为已展示，跳过下面所有全局 message 弹窗
-    if (originalRequest?._silentErrorToast) {
-      // eslint-disable-next-line @typescript-eslint/no-explicit-any
-      ;(error as any).__msgShown = true
-      return Promise.reject(error)
     }
 
     // 401 → 尝试刷新 Token

apps/web/src/api/duplication/types.ts

@@ -20,10 +20,6 @@ export interface DuplicationRecord {
   duplicate_rate?: number
   /** 重复片段数 */
   duplicate_count?: number
-  /** 视觉相似度（0-100），#1660 新增 */
-  visual_similarity?: number
-  /** 匹配帧数，#1660 新增 */
-  match_count?: number
   /** 创建时间 */
   created_at: string
   /** 更新时间 */

apps/web/src/api/editing-planner/templates.ts

@@ -12,25 +12,17 @@ import type {
   ListCategoriesResponse,
 } from "./types"
 
-/** 获取模板列表
- *
- * valid_only=true 时请求后端仅返回已配置片段的模板（剪辑页选模板使用，
- * 避免选中无片段配置的模板导致 from-assets 400，#1769/#1772）；
- * 后端尚未支持该参数时会忽略未知 query 字段，前端再按 segments/is_active 兜底过滤。
- * 模板编辑器/我的模板不传，可查看全部模板（含未配置片段的草稿）。
- */
+/** 获取模板列表 */
 export const getEditingTemplates = async (params?: {
   category?: string
   tag?: string
   skip?: number
   limit?: number
-  validOnly?: boolean
 }): Promise<EditingTemplate[]> => {
   const response = await apiClient.get<ListTemplatesResponse>("/templates", {
     params: {
       skip: params?.skip ?? 0,
       limit: params?.limit ?? 50,
-      ...(params?.validOnly ? { valid_only: true } : {}),
     },
   })
   let list = response.data.items

apps/web/src/api/editing-planner/types.ts

@@ -44,10 +44,8 @@ export interface BgmConfig {
 export interface TemplateSegment {
   id?: string
   segment_order: number
-  /** @deprecated 模板无时长概念（#1750 基线）：字段保留仅为兼容旧数据读取，新模板可不传 */
-  duration_min?: number
-  /** @deprecated 同上 */
-  duration_max?: number
+  duration_min: number
+  duration_max: number
   material_type: string | null
 }
 
@@ -61,8 +59,7 @@ export interface EditingTemplate {
   title_config: TitleConfig
   subtitle_config: SubtitleConfig
   bgm_config: BgmConfig
-  /** @deprecated 模板无时长概念（#1750 基线）：成片时长由配音时长决定；字段保留兼容旧数据 */
-  estimated_duration?: number
+  estimated_duration: number
   segments: TemplateSegment[]
   watermark_config?: WatermarkConfig
   intro_outro_config?: IntroOutroConfig
@@ -92,8 +89,7 @@ export interface SaveTemplatePayload {
   title_config: TitleConfig
   subtitle_config: SubtitleConfig
   bgm_config: BgmConfig
-  /** @deprecated 模板无时长概念（#1750 基线）：保留兼容旧数据 */
-  estimated_duration?: number
+  estimated_duration: number
   segments: Omit<TemplateSegment, "id">[]
   watermark_config?: WatermarkConfig
   intro_outro_config?: IntroOutroConfig

apps/web/src/api/errors.ts

@@ -1,132 +0,0 @@
-/**
- * 统一错误信息提取
- * 把 axios 错误（后端 detail / FastAPI 校验错误 / HTTP 状态码）、XHR/OSS 错误、
- * 网络/超时错误、普通 Error 统一转成「可直接展示给用户」的中文信息。
- *
- * 与 api/client.ts 响应拦截器的提示口径保持一致；拦截器负责全局 toast，
- * 页面/队列卡片用本工具把真实原因展示在持久位置（回调页、失败卡片等）。
- */
-import type { AxiosError } from "axios"
-
-/** 后端错误响应体可能出现的字段（FastAPI：detail；历史接口：message/msg） */
-interface ErrorBody {
-  detail?: unknown
-  message?: unknown
-  msg?: unknown
-}
-
-/** FastAPI 422 校验错误单项 */
-interface ValidationItem {
-  loc?: (string | number)[]
-  msg?: string
-}
-
-/** 从后端响应体提取人类可读信息（detail 可能是字符串、对象、422 数组） */
-function extractBodyMessage(data: unknown): string {
-  if (!data || typeof data !== "object") return ""
-  const body = data as ErrorBody
-
-  const walk = (val: unknown): string => {
-    if (typeof val === "string") return val
-    if (Array.isArray(val)) {
-      // FastAPI 422: [{loc, msg, type}, ...] → 取每条 msg 拼接
-      const parts = val
-        .map((item) => {
-          if (typeof item === "string") return item
-          if (item && typeof item === "object") {
-            const v = item as ValidationItem
-            if (typeof v.msg === "string") {
-              const field = Array.isArray(v.loc) ? v.loc.filter((x) => x !== "body").join(".") : ""
-              return field ? `${field}: ${v.msg}` : v.msg
-            }
-            return walk(item)
-          }
-          return ""
-        })
-        .filter(Boolean)
-      return parts.join("；")
-    }
-    if (val && typeof val === "object") {
-      const obj = val as Record<string, unknown>
-      if (typeof obj.message === "string") return obj.message
-      if (typeof obj.msg === "string") return obj.msg
-      if (typeof obj.detail === "string") return obj.detail
-      if (obj.message && typeof obj.message === "object") return walk(obj.message)
-      if (obj.msg && typeof obj.msg === "object") return walk(obj.msg)
-      try {
-        return JSON.stringify(val)
-      } catch {
-        return ""
-      }
-    }
-    return ""
-  }
-
-  return walk(body.detail) || walk(body.message) || walk(body.msg)
-}
-
-/** 无响应体时按 HTTP 状态码给出兜底提示（与 client.ts 拦截器口径一致） */
-function statusFallback(status: number): string {
-  switch (status) {
-    case 400:
-      return "请求参数有误（HTTP 400）"
-    case 401:
-      return "登录状态已失效，请重新登录（HTTP 401）"
-    case 403:
-      return "没有权限执行该操作（HTTP 403）"
-    case 404:
-      return "请求的资源不存在（HTTP 404）"
-    case 409:
-      return "操作冲突，资源状态已变化（HTTP 409）"
-    case 413:
-      return "文件过大，请缩小后重试（HTTP 413）"
-    case 415:
-      return "不支持的文件格式（HTTP 415）"
-    case 429:
-      return "操作过于频繁，请稍后再试（HTTP 429）"
-    case 503:
-      return "服务暂不可用，请稍后再试（HTTP 503）"
-    default:
-      if (status >= 500) return `服务器繁忙，请稍后再试（HTTP ${status}）`
-      return `请求失败（HTTP ${status}）`
-  }
-}
-
-/**
- * 从任意抛出值提取可展示的错误信息。
- * @param fallback 全部提取失败时的兜底文案
- */
-export function getErrorMessage(err: unknown, fallback = "操作失败，请稍后重试"): string {
-  if (!err) return fallback
-
-  // axios 错误（后端 JSON 响应 / HTTP 错误状态）
-  const ax = err as AxiosError<ErrorBody>
-  if (ax.isAxiosError || (typeof ax === "object" && "response" in (ax as object))) {
-    // 超时
-    if (ax.code === "ECONNABORTED" || /timeout/i.test(ax.message || "")) {
-      return "请求超时，请检查网络后重试"
-    }
-    const resp = ax.response
-    if (resp) {
-      const bodyMsg = extractBodyMessage(resp.data)
-      if (bodyMsg) return bodyMsg
-      return statusFallback(resp.status)
-    }
-    // 请求已发出但无响应（断网/CORS/DNS）
-    if (ax.request) return "网络连接异常，请检查网络设置"
-    return ax.message || fallback
-  }
-
-  if (err instanceof Error) {
-    // XHR 直传 OSS 失败等场景自带详细 message（含 HTTP 状态 + OSS Code/Message）
-    if (err.message) return err.message
-  }
-  if (typeof err === "string") return err
-
-  return fallback
-}
-
-/** client.ts 拦截器是否已对该错误弹过全局 toast（__msgShown 标记） */
-export function isErrorMsgShown(err: unknown): boolean {
-  return Boolean((err as { __msgShown?: boolean } | null)?.__msgShown)
-}

apps/web/src/api/generation/types.ts

@@ -33,36 +33,15 @@ export interface CreatePreviewRequest {
     preset_id?: string
     volume?: number
   }
-  /** 批量预览数量（1~10），默认1。N>1 时返回 N 个独立变体任务 */
-  preview_count?: number
-  /** 各变体独立标题文字：长度1=共用，长度=preview_count=独立，空数组=使用 title_config.text */
-  titles?: string[]
-  /** 各变体独立配音素材库ID：长度1=共用，长度=preview_count=独立，空数组=回退 voice_library_id */
-  voice_library_ids?: string[]
-  /** 各变体独立封面URL：长度1=共用，长度=preview_count=独立（预览阶段通常为空） */
-  cover_urls?: string[]
 }
 
-/** 单个预览变体任务 */
-export interface PreviewVariantItem {
-  task_id: string
-  status: string
-  progress: number
-  is_preview: boolean
-  variant_index: number
-  resolution: string
-  video_url: string
-  duration: number
-  error_message: string
-  title_text: string
-  voice_library_id: string
-  created_at?: string | null
-}
-
-/** 创建预览任务响应（单变体，preview_count=1 时 items 长度为1） */
+/** 创建预览任务响应 */
 export interface CreatePreviewResponse {
-  items: PreviewVariantItem[]
-  total: number
+  task_id: string
+  status: PreviewStatus
+  is_preview: boolean
+  resolution: string
+  created_at: string
   /** 后端自动关联的编辑计划 ID（用于 fallback 路径传递 source_edit_plan_id） */
   source_edit_plan_id?: string
 }

apps/web/src/api/generation/variantPlans.ts

@@ -1,61 +0,0 @@
-/**
- * 批量变体剪辑计划 API（#1744）
- *
- * 批量预览时向后端申请 N 个变体的「独立剪辑计划片段」：
- * - 变体 0 保留源 plan（用户在编辑器/智能选片产出的片段，含标题样式编辑结果）；
- * - 变体 1..N-1 由后端 reselect_plan_for_variant 完整重跑单视频选片流程
- *   （素材洗牌 + main 片段顺序洗牌 + 镜头/起点随机 + 跨变体 20% 区间避让 +
- *   素材使用区间写回 metadata），与正式批量生成 POST /generation/tasks?count=N
- *   使用同一套选片逻辑；
- * - 正式生成时把 variant_plan_ids 原样回传，后端直接关联这些 plan 渲染，
- *   不再重新选片 —— 预览所见即成片。
- *
- * 该接口只做选片/建 plan（秒级），不触发视频渲染，无渲染成本。
- * 后端端点未上线（404）或选片失败（素材不足等）时前端降级为本地 variantSeed
- * 模拟预览，不阻塞用户流程。
- */
-import apiClient from "../client"
-import type { EditPlanClip } from "../template-editor"
-
-/** 批量变体计划请求体 */
-export interface BatchVariantPlansRequest {
-  template_id: string
-  /** 本批次素材池（手动选择或智能匹配结果） */
-  asset_ids: string[]
-  /** 变体数量（≥1）；=1 时只返回源 plan 片段 */
-  count: number
-  /** 源剪辑计划 ID：优先取预览/草稿关联的 plan；不传由后端按 template_id+user 兜底最新 plan */
-  source_edit_plan_id?: string
-}
-
-/** 单个变体的计划片段 */
-export interface VariantPlan {
-  /** 变体序号，从 0 开始 */
-  variant_index: number
-  /** 该变体关联的剪辑计划 ID（正式生成时回传，实现预览即成片） */
-  plan_id: string
-  /** 该变体的真实片段（顺序/素材/起点与正式成片一致） */
-  clips: EditPlanClip[]
-}
-
-/** 批量变体计划响应 */
-export interface BatchVariantPlansResponse {
-  items: VariantPlan[]
-  total: number
-}
-
-/**
- * 创建批量变体剪辑计划并返回各变体片段。
- *
- * 注意：端点 404（后端未上线）/ 400（素材不足）等失败由调用方 catch 后降级，
- * 不要抛 unhandled rejection。
- */
-export async function createBatchVariantPlans(
-  params: BatchVariantPlansRequest,
-): Promise<BatchVariantPlansResponse> {
-  const response = await apiClient.post<BatchVariantPlansResponse>(
-    "/generation/variant-plans",
-    params,
-  )
-  return response.data
-}

apps/web/src/api/products/index.ts

@@ -13,8 +13,6 @@ export type {
   VideoItem,
 } from "./types"
 
-export type { RecomputeDedupResponse } from "./products"
-
 // 工具函数
 export { mapVideoToProductItem } from "./utils"
 
@@ -27,5 +25,4 @@ export {
   updateReviewStatus,
   batchDownload,
   getBatchDownloadStatus,
-  recomputeDedup,
 } from "./products"

apps/web/src/api/products/products.ts

@@ -1,6 +1,6 @@
 /**
  * 成品 / 视频相关 API 函数
- * 后端实际接口：/videos（分页：page/page_size，返回 {items, total, page, page_size}）
+ * 后端实际接口：/videos
  */
 import apiClient from "../client"
 import type {
@@ -12,39 +12,16 @@ import type {
 } from "./types"
 import { mapVideoToProductItem } from "./utils"
 
-/** 分页列表响应（前端消费用） */
-export interface ProductListResult {
-  items: ProductItem[]
-  total: number
-  page: number
-  page_size: number
-}
-
-/**
- * 获取成品列表（分页）
- * @param params 分页与筛选参数：page 默认 1，page_size 默认 20
- */
-export const getProducts = async (params?: ProductListParams): Promise<ProductListResult> => {
-  const response = await apiClient.get("/videos", {
-    params: {
-      page: 1,
-      page_size: 20,
-      ...params,
-    },
-  })
-  const data = response.data as {
-    items?: VideoItem[]
-    total?: number
-    page?: number
-    page_size?: number
-  }
-  const items: VideoItem[] = Array.isArray(data?.items) ? data.items : []
-  return {
-    items: items.map(mapVideoToProductItem),
-    total: data.total ?? items.length,
-    page: data.page ?? params?.page ?? 1,
-    page_size: data.page_size ?? params?.page_size ?? 20,
-  }
+/** 获取成品列表（支持分页和筛选） */
+export const getProducts = async (params?: ProductListParams): Promise<ProductItem[]> => {
+  const response = await apiClient.get("/videos", { params })
+  const data = response.data
+  const videos: VideoItem[] = Array.isArray(data?.items)
+    ? data.items
+    : Array.isArray(data)
+      ? data
+      : []
+  return videos.map(mapVideoToProductItem)
 }
 
 /** 获取单个成品详情 */
@@ -101,18 +78,3 @@ export const getBatchDownloadStatus = async (jobId: string): Promise<BatchDownlo
   console.warn("[getBatchDownloadStatus] 后端暂无批量下载状态端点", jobId)
   return { job_id: jobId, status: "processing", progress: 0 }
 }
-
-/** 重新计算存量视频查重率（异步） */
-export interface RecomputeDedupResponse {
-  enqueued: number
-  total_scanned: number
-  skipped: number
-  message: string
-}
-
-export const recomputeDedup = async (videoIds?: string[]): Promise<RecomputeDedupResponse> => {
-  const response = await apiClient.post("/videos/recompute-dedup", {
-    video_ids: videoIds,
-  })
-  return response.data
-}