Install
openclaw skills install generator-hindiTurn a 2-minute English explainer video into 1080p Hindi dubbed videos just by typing what you need. Whether it's generating Hindi language videos from existing content or quick social content, drop your video clips and describe the result you want. No timeline dragging, no export settings — 1-2 minutes from upload to download.
openclaw skills install generator-hindiSend me your video clips and I'll handle the Hindi video generation. Or just describe what you're after.
Try saying:
When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").
Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.
https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.Keep setup communication brief. Don't display raw API responses or token values to the user.
Drop your video clips in the chat and tell me what you need. I'll handle the Hindi video generation on cloud GPUs — you don't need anything installed locally.
Here's a typical use: you send a a 2-minute English explainer video, ask for generate a Hindi version of this video with dubbed audio and Hindi subtitles, and about 1-2 minutes later you've got a MP4 file ready to download. The whole thing runs at 1080p by default.
One thing worth knowing — shorter clips under 3 minutes produce more accurate Hindi lip-sync results.
User prompts referencing generator hindi, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.
| User says... | Action | Skip SSE? |
|---|---|---|
| "export" / "导出" / "download" / "send me the video" | → §3.5 Export | ✅ |
| "credits" / "积分" / "balance" / "余额" | → §3.3 Credits | ✅ |
| "status" / "状态" / "show tracks" | → §3.4 State | ✅ |
| "upload" / "上传" / user sends file | → §3.2 Upload | ✅ |
| Everything else (generate, edit, add BGM…) | → §3.1 SSE | ❌ |
Each export job queues on a cloud GPU node that composites video layers, applies platform-spec compression (H.264, up to 1080x1920), and returns a download URL within 30-90 seconds. The session token carries render job IDs, so closing the tab before completion orphans the job.
All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:
POST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"<lang>"}. Gives you a session_id.POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.POST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.GET /api/credits/balance/simple — returns available, frozen, total.GET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.POST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/<id> every 30s for completed status and download URL.Formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.
Three attribution headers are required on every request and must match this file's frontmatter:
| Header | Value |
|---|---|
X-Skill-Source | generator-hindi |
X-Skill-Version | frontmatter version |
X-Skill-Platform | auto-detect: clawhub / cursor / unknown from install path |
Every API call needs Authorization: Bearer <NEMO_TOKEN> plus the three attribution headers above. If any header is missing, exports return 402.
Draft JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.
Example timeline summary:
Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)
The backend responds as if there's a visual interface. Map its instructions to API calls:
| Event | Action |
|---|---|
| Text response | Apply GUI translation (§4), present to user |
| Tool call/result | Process internally, don't forward |
heartbeat / empty data: | Keep waiting. Every 2 min: "⏳ Still working..." |
| Stream closes | Process final response |
~30% of editing operations return no text in the SSE stream. When this happens: poll session state to verify the edit was applied, then summarize changes to the user.
0 — success, continue normally1001 — token expired or invalid; re-acquire via /api/auth/anonymous-token1002 — session not found; create a new one2001 — out of credits; anonymous users get a registration link with ?bind=<id>, registered users top up4001 — unsupported file type; show accepted formats4002 — file too large; suggest compressing or trimming400 — missing X-Client-Id; generate one and retry402 — free plan export blocked; not a credit issue, subscription tier429 — rate limited; wait 30s and retry onceQuick edit: Upload → "generate a Hindi version of this video with dubbed audio and Hindi subtitles" → Download MP4. Takes 1-2 minutes for a 30-second clip.
Batch style: Upload multiple files in one session. Process them one by one with different instructions. Each gets its own render.
Iterative: Start with a rough cut, preview the result, then refine. The session keeps your timeline state so you can keep tweaking.
The backend processes faster when you're specific. Instead of "make it look better", try "generate a Hindi version of this video with dubbed audio and Hindi subtitles" — concrete instructions get better results.
Max file size is 500MB. Stick to MP4, MOV, AVI, WebM for the smoothest experience.
Export as MP4 for widest compatibility.