Text to Video Hindi AI — Convert Hindi Text into Videos

## Getting Started

> Got text prompt to work with? Send it over and tell me what you need — I'll take care of the AI video generation.

**Try saying:**
- "convert a 100-word Hindi product description into a 1080p MP4"
- "convert this Hindi text into a short video with voiceover and visuals"
- "generating Hindi videos from typed or pasted text for Hindi content creators"

### Quick Start Setup

This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

**Token check**: Look for `NEMO_TOKEN` in the environment. If found, skip to session creation. Otherwise:
- Generate a UUID as client identifier
- POST `https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token` with `X-Client-Id` header
- Extract `data.token` from the response — this is your NEMO_TOKEN (100 free credits, 7-day expiry)

**Session**: POST `https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent` with Bearer auth and body `{"task_name":"project"}`. Keep the returned `session_id` for all operations.

Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

# Text to Video Hindi AI — Convert Hindi Text into Videos

This tool takes your text prompt and runs AI video generation through a cloud rendering pipeline. You upload, describe what you want, and download the result.

Say you have a 100-word Hindi product description and want to convert this Hindi text into a short video with voiceover and visuals — the backend processes it in about 1-2 minutes and hands you a 1080p MP4.

Tip: shorter text inputs under 150 words produce faster and more accurate results.

## Matching Input to Actions

User prompts referencing text to video hindi ai, 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.

Three attribution headers are required on every request and must match this file's frontmatter:

| Header | Value |
|--------|-------|
| `X-Skill-Source` | `text-to-video-hindi-ai` |
| `X-Skill-Version` | frontmatter `version` |
| `X-Skill-Platform` | auto-detect: `clawhub` / `cursor` / `unknown` from install path |

Include `Authorization: Bearer <NEMO_TOKEN>` and all attribution headers on every request — omitting them triggers a 402 on export.

**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.

### Reading the SSE Stream

Text events go straight to the user (after GUI translation). Tool calls stay internal. Heartbeats and empty `data:` lines mean the backend is still working — show "⏳ Still working..." every 2 minutes.

About 30% of edit operations close the stream without any text. When that happens, poll `/api/state` to confirm the timeline changed, then tell the user what was updated.

### Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

| Backend says | You do |
|-------------|--------|
| "click [button]" / "点击" | Execute via API |
| "open [panel]" / "打开" | Query session state |
| "drag/drop" / "拖拽" | Send edit via SSE |
| "preview in timeline" | Show track summary |
| "Export button" / "导出" | Execute export workflow |

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)
```

### 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

## Common Workflows

**Quick edit**: Upload → "convert this Hindi text into a short video with voiceover and visuals" → 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.

## Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "convert this Hindi text into a short video with voiceover and visuals" — concrete instructions get better results.

Max file size is 200MB. Stick to TXT, DOCX, PDF, SRT for the smoothest experience.

Export as MP4 for widest compatibility across Hindi social media platforms.