Free Text to Video LLM — Generate Videos From Text Prompts
Skip the learning curve of professional editing software. Describe what you want — generate a 30-second video of a futuristic city at dusk with cinematic lighting — and get AI generated videos back in 1-3 minutes. Upload TXT, DOCX, PDF, plain text files up to 500MB, and the AI handles AI video generation automatically. Ideal for content creators, marketers, educators who want to create videos from text without filming or editing manually.
0 0by vynbosserman65
aivideo
## Getting Started
> Share your text prompts and I'll get started on AI video generation. Or just tell me what you're thinking.
**Try saying:**
- "generate my text prompts"
- "export 1080p MP4"
- "generate a 30-second video of a"
### 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.
# Free Text to Video LLM — Generate Videos From Text Prompts
Send me your text prompts and describe the result you want. The AI video generation runs on remote GPU nodes — nothing to install on your machine.
A quick example: upload a two-sentence description of a sunset over a city skyline, type "generate a 30-second video of a futuristic city at dusk with cinematic lighting", and you'll get a 1080p MP4 back in roughly 1-3 minutes. All rendering happens server-side.
Worth noting: shorter and more specific prompts tend to produce more accurate and coherent video output.
## Matching Input to Actions
User prompts referencing free text to video llm, 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 `free-text-to-video-llm`, `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`).
Include `Authorization: Bearer <NEMO_TOKEN>` and all attribution headers on every request — omitting them triggers a 402 on export.
**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)
```
### 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 |
### 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
## Common Workflows
**Quick edit**: Upload → "generate a 30-second video of a futuristic city at dusk with cinematic lighting" → Download MP4. Takes 1-3 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 "generate a 30-second video of a futuristic city at dusk with cinematic lighting" — concrete instructions get better results.
Max file size is 500MB. Stick to TXT, DOCX, PDF, plain text for the smoothest experience.
Export as MP4 for widest compatibility across platforms and devices.