Text to Video Create — Generate Videos from Text Prompts

## Getting Started

> Send me your text prompt and I'll handle the AI video creation. Or just describe what you're after.

**Try saying:**
- "generate a 150-word product description script into a 1080p MP4"
- "turn this script into a 30-second video with visuals and background music"
- "generating videos from written scripts or prompts for marketers, content creators, educators"

### Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

**If `NEMO_TOKEN` is in the environment**, use it directly and create a session. Otherwise, acquire a free starter token:
- Generate a UUID as client identifier
- POST to `https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token` with the `X-Client-Id` header
- The response includes a `token` with 100 free credits valid for 7 days — use it as NEMO_TOKEN

**Then create a session** by POSTing to `https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent` with Bearer authorization and body `{"task_name":"project","language":"en"}`. The `session_id` in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

# Text to Video Create — Generate Videos from Text Prompts

Send me your text prompt and describe the result you want. The AI video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a 150-word product description script, type "turn this script into a 30-second video with visuals and background music", and you'll get a 1080p MP4 back in roughly 1-2 minutes. All rendering happens server-side.

Worth noting: shorter, clearer prompts tend to produce more accurate and focused video results.

## Matching Input to Actions

User prompts referencing text to video create, 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.

All calls go to `https://mega-api-prod.nemovideo.ai`. The main endpoints:

1. **Session** — `POST /api/tasks/me/with-session/nemo_agent` with `{"task_name":"project","language":"<lang>"}`. Gives you a `session_id`.
2. **Chat (SSE)** — `POST /run_sse` with `session_id` and your message in `new_message.parts[0].text`. Set `Accept: text/event-stream`. Up to 15 min.
3. **Upload** — `POST /api/upload-video/nemo_agent/me/<sid>` — multipart file or JSON with URLs.
4. **Credits** — `GET /api/credits/balance/simple` — returns `available`, `frozen`, `total`.
5. **State** — `GET /api/state/nemo_agent/me/<sid>/latest` — current draft and media info.
6. **Export** — `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.

Headers are derived from this file's YAML frontmatter. `X-Skill-Source` is `text-to-video-create`, `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`).

**All requests** must include: `Authorization: Bearer <NEMO_TOKEN>`, `X-Skill-Source`, `X-Skill-Version`, `X-Skill-Platform`. Missing attribution headers will cause export to fail with 402.

**Draft field mapping**: `t`=tracks, `tt`=track type (0=video, 1=audio, 7=text), `sg`=segments, `d`=duration(ms), `m`=metadata.

```
Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)
```

### 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

### 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.

### 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

## Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "turn this script into a 30-second video with visuals and background music" — concrete instructions get better results.

Max file size is 500MB. Stick to TXT, DOCX, PDF, SRT for the smoothest experience.

Export as MP4 for widest compatibility across platforms and devices.

## Common Workflows

**Quick edit**: Upload → "turn this script into a 30-second video with visuals and background music" → 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.