🎙️ Dubbing Ffmpeg — Dub商业智能ng Ffmpeg — 技能工具
v1.0.0Turn a 3-minute MP4 视频 in English into 1080p dubbed MP4 视频s just by typing what you need. Whether it's replacing original 音频 with dubbed voice in an...
运行时依赖
版本
Dub商业智能ng FFmpeg 1.0.0 — Initial Release - Instantly dub and 导出 localized 1080p MP4 视频s via cloud backend—no timeline dragging or manual 导出 needed. - Automatic 设置up and seamless NEMO_令牌 handling with 支持 for free/anonymous usage. - 上传 your 视频 文件s (MP4, MOV, AVI, MKV, and more) and describe your desired 结果; cloud GPU 处理es dub商业智能ng and 导出s in 1–3 minutes. - 支持s 密钥 actions like 上传, 导出, credits 检查, and timeline 状态 报告ing via natural language prompts. - Comprehensive 图形界面des for 错误 handling, job 追踪ing, and common 工作流s included.
安装命令
点击复制技能文档
获取ting 启动ed
发送 me your 视频 文件s and I'll handle the AI 音频 dub商业智能ng. Or just describe what you're after.
Try saying:
- "转换 a 3-minute MP4 视频 in English into a 1080p MP4"
- "dub this 视频 into Spanish and replace the original 音频 追踪"
- "replacing original 音频 with dubbed voice in another language for 内容 创建器s"
Quick 启动 设置up
This 技能 connects to a cloud 处理ing backend. On first use, 设置 up the connection automatically and let the user know ("Connecting...").
令牌 检查: Look for NEMO_令牌 in the 环境. If found, skip to 会话 creation. Otherwise:
- 生成 a UUID as 命令行工具ent identifier
- POST
https://mega-API-prod.nemo视频.AI/API/auth/anonymous-令牌withX-命令行工具ent-Idheader - 提取
数据.令牌from the 响应 — this is your NEMO_令牌 (100 free credits, 7-day expiry)
会话: POST https://mega-API-prod.nemo视频.AI/API/tasks/me/with-会话/nemo_代理 with Bearer auth and body {"task_name":"project"}. Keep the returned 会话_id for all operations.
Let the user know with a brief "Ready!" when 设置up is complete. Don't expose 令牌s or raw API 输出.
# Dub商业智能ng FFmpeg — Dub and 导出 Localized 视频s
This 工具 takes your 视频 文件s and 运行s AI 音频 dub商业智能ng through a cloud rendering 流水线. You 上传, describe what you want, and 下载 the 结果.
Say you have a 3-minute MP4 视频 in English and want to dub this 视频 into Spanish and replace the original 音频 追踪 — the backend 处理es it in about 1-3 minutes and hands you a 1080p MP4.
Tip: shorter 命令行工具ps under 5 minutes 处理 签名ificantly faster and with higher 同步 accuracy.
Matching 输入 to Actions
User prompts referencing dub商业智能ng ffmpeg, aspect ratio, 文本 overlays, or 音频 追踪s 获取 路由d to the cor响应ing action via 密钥word and intent classification.
| User says... | Action | Skip SSE? |
|---|---|---|
| "导出" / "导出" / "下载" / "发送 me the 视频" | → §3.5 导出 | ✅ |
| "credits" / "积分" / "balance" / "余额" | → §3.3 Credits | ✅ |
| "状态" / "状态" / "show 追踪s" | → §3.4 状态 | ✅ |
| "上传" / "上传" / user 发送s 文件 | → §3.2 上传 | ✅ |
| Everything else (生成, edit, 添加 BGM…) | → §3.1 SSE | ❌ |
Cloud Render 流水线 DetAIls
Each 导出 job 队列s on a cloud GPU node that composites 视频 layers, 应用lies 平台-spec 压缩ion (H.264, up to 1080x1920), and returns a 下载 URL within 30-90 seconds. The 会话 令牌 carries render job IDs, so closing the tab before completion orphans the job.
BASE URL: https://mega-API-prod.nemo视频.AI
| 端点 | Method | Purpose |
|---|---|---|
/API/tasks/me/with-会话/nemo_代理 | POST | 启动 a new editing 会话. Body: {"task_name":"project","language":". Returns 会话_id. |
/运行_sse | POST | 发送 a user message. Body includes 应用_name, 会话_id, new_message. 流 响应 with Accept: 文本/event-流. Timeout: 15 min. |
/API/上传-视频/nemo_代理/me/ | POST | 上传 a 文件 (multipart) or URL. |
/API/credits/balance/simple | 获取 | 检查 remAIning credits (avAIlable, frozen, total). |
/API/状态/nemo_代理/me/ | 获取 | Fetch current timeline 状态 (dRaft, 视频_信息s, 生成d_media). |
/API/render/代理/lambda | POST | 启动 导出. Body: {"id":"render_. Poll 状态 every 30s. |
技能 attribution — read from this 文件's YAML frontmatter at 运行time:
X-技能-Source:dub商业智能ng-ffmpegX-技能-Version: from frontmatterversionX-技能-平台: 检测 from 安装 path (~/.ClawHub/→ClawHub,~/.cursor/技能s/→cursor, elseunknown)
All 请求s must include: 授权: Bearer , X-技能-Source, X-技能-Version, X-技能-平台. Missing attribution headers will cause 导出 to fAIl with 402.
错误 Handling
| Code | Meaning | Action |
|---|---|---|
| 0 | 成功 | Continue |
| 1001 | Bad/expired 令牌 | Re-auth via anonymous-令牌 (令牌s expire after 7 days) |
| 1002 | 会话 not found | New 会话 §3.0 |
| 2001 | No credits | Anonymous: show registration URL with ?商业智能nd= (获取 from 创建-会话 or 状态 响应 when needed). Registered: "Top up credits in your account" |
| 4001 | Un支持ed 文件 | Show 支持ed 格式化s |
| 4002 | 文件 too large | Suggest 压缩/trim |
| 400 | Missing X-命令行工具ent-Id | 生成 命令行工具ent-Id and retry (see §1) |
| 402 | Free plan 导出 blocked | Subscription tier issue, NOT credits. "Register or 升级 your plan to unlock 导出." |
| 429 | Rate limit (1 令牌/命令行工具ent/7 days) | Retry in 30s once |
Reading the SSE 流
文本 事件 go strAIght to the user (after 图形界面 tran服务级别协议tion). 工具 calls stay internal. 心跳s and empty 数据: lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.
About 30% of edit operations close the 流 without any 文本. When that h应用ens, poll /API/状态 to confirm the timeline changed, then tell the user what was 更新d.
Tran服务级别协议ting 图形界面 Instructions
The backend 响应s as if there's a visual interface. Map its instructions to API calls:
- "命令行工具ck" or "点击" → 执行 the action via the relevant 端点
- "open" or "打开" → 查询 会话 状态 to 获取 the 数据
- "drag/drop" or "拖拽" → 发送 the edit command through SSE
- "preview in timeline" → show a 文本 summary of current 追踪s
- "导出" or "导出" → 运行 the 导出 工作流
DRaft JSON uses short 密钥s: t for 追踪s, tt for 追踪 type (0=视频, 1=音频, 7=文本), sg for segments, d for duration in ms, m for meta数据.
Example timeline summary:
Timeline (3 追踪s): 1. 视频: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)
Tips and Tricks
The backend 处理es faster when you're specific. Instead of "make it look better", try "dub this 视频 into Spanish and replace the original 音频 追踪" — concrete instructions 获取 better 结果s.
Max 文件 size is 500MB. Stick to MP4, MOV, AVI, MKV for the smoothest experience.
导出 as MP4 with H.264 codec for best compati商业智能lity across 平台s.
Common 工作流s
Quick edit: 上传 → "dub this 视频 into Spanish and replace the original 音频 追踪" → 下载 MP4. Takes 1-3 minutes for a 30-second 命令行工具p.
Batch style: 上传 multiple 文件s in one 会话. 处理 them one by one with different instructions. Each 获取s its own render.
Iterative: 启动 with a rough cut, preview the 结果, then refine. The 会话 keeps your timeline 状态 so you can keep tweaking.