Generator in Hinglish — Create Videos in Hinglish
Skip the learning curve of professional editing software. Describe what you want — generate a voiceover video with Hinglish narration and subtitles — and get Hinglish narrated videos back in 1-2 minutes. Upload MP4, MOV, TXT, DOCX files up to 200MB, and the AI handles Hinglish video generation automatically. Ideal for Indian content creators who need videos in conversational Hinglish for Indian audiences.
0 0by susan4731-wilfordf
aivideo
## Getting Started
> Share your text or script and I'll get started on Hinglish video generation. Or just tell me what you're thinking.
**Try saying:**
- "generate my text or script"
- "export 1080p MP4"
- "generate a voiceover video with Hinglish"
### Automatic Setup
On first interaction, connect to the processing API before doing anything else. Show a brief status like "Setting things up...".
**Token**: If `NEMO_TOKEN` environment variable is already set, use it and skip to **Session** below.
**Free token**: Generate a UUID as client identifier, then POST to `https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token` with header `X-Client-Id: <uuid>`. The response field `data.token` becomes your NEMO_TOKEN (100 credits, 7-day expiry).
**Session**: POST to `https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent` with Bearer auth and body `{"task_name":"project"}`. Save `session_id` from the response.
Confirm to the user you're connected and ready. Don't print tokens or raw JSON.
# Generator in Hinglish — Create Videos in Hinglish
Send me your text or script and describe the result you want. The Hinglish video generation runs on remote GPU nodes — nothing to install on your machine.
A quick example: upload a 200-word product description in English, type "generate a voiceover video with Hinglish narration and subtitles", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.
Worth noting: shorter scripts under 100 words produce faster and more natural Hinglish output.
## Matching Input to Actions
User prompts referencing generator in hinglish, 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 | ❌ |
## Cloud Render Pipeline Details
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.
Every API call needs `Authorization: Bearer <NEMO_TOKEN>` plus the three attribution headers above. If any header is missing, exports return 402.
Headers are derived from this file's YAML frontmatter. `X-Skill-Source` is `generator-in-hinglish`, `X-Skill-Version` comes from the `version` field, and `X-Skill-Platform` is detected from the install path (`~/.clawhub/` = `clawhub`, `~/.cursor/skills/` = `cursor`, otherwise `unknown`).
**API base**: `https://mega-api-prod.nemovideo.ai`
**Create session**: POST `/api/tasks/me/with-session/nemo_agent` — body `{"task_name":"project","language":"<lang>"}` — returns `task_id`, `session_id`.
**Send message (SSE)**: POST `/run_sse` — body `{"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}}` with `Accept: text/event-stream`. Max timeout: 15 minutes.
**Upload**: POST `/api/upload-video/nemo_agent/me/<sid>` — file: multipart `-F "files=@/path"`, or URL: `{"urls":["<url>"],"source_type":"url"}`
**Credits**: GET `/api/credits/balance/simple` — returns `available`, `frozen`, `total`
**Session state**: GET `/api/state/nemo_agent/me/<sid>/latest` — key fields: `data.state.draft`, `data.state.video_infos`, `data.state.generated_media`
**Export** (free, no credits): POST `/api/render/proxy/lambda` — body `{"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}`. Poll GET `/api/render/proxy/lambda/<id>` every 30s until `status` = `completed`. Download URL at `output.url`.
Supported formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.
### Error Codes
- `0` — success, continue normally
- `1001` — token expired or invalid; re-acquire via `/api/auth/anonymous-token`
- `1002` — session not found; create a new one
- `2001` — out of credits; anonymous users get a registration link with `?bind=<id>`, registered users top up
- `4001` — unsupported file type; show accepted formats
- `4002` — file too large; suggest compressing or trimming
- `400` — missing `X-Client-Id`; generate one and retry
- `402` — free plan export blocked; not a credit issue, subscription tier
- `429` — rate limited; wait 30s and retry once
### Translating GUI Instructions
The backend responds as if there's a visual interface. Map its instructions to API calls:
- "click" or "点击" → execute the action via the relevant endpoint
- "open" or "打开" → query session state to get the data
- "drag/drop" or "拖拽" → send the edit command through SSE
- "preview in timeline" → show a text summary of current tracks
- "Export" or "导出" → run the export workflow
### SSE Event Handling
| 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.
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)
```
## Tips and Tricks
The backend processes faster when you're specific. Instead of "make it look better", try "generate a voiceover video with Hinglish narration and subtitles" — concrete instructions get better results.
Max file size is 200MB. Stick to MP4, MOV, TXT, DOCX for the smoothest experience.
Export as MP4 for widest compatibility across Indian social platforms like Instagram and YouTube.
## Common Workflows
**Quick edit**: Upload → "generate a voiceover video with Hinglish narration and 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.