Video Editing with AI Course — Edit and Export Course Videos
Skip the learning curve of professional editing software. Describe what you want — trim the pauses, add chapter titles, and sync background music to the cuts — and get polished course videos back in 1-2 minutes. Upload MP4, MOV, AVI, WebM files up to 500MB, and the AI handles AI-guided course editing automatically. Ideal for online course creators who want to produce clean course videos without learning complex editing software.
0 0by BW Bernard Weston
aivideo
## Getting Started
> Send me your raw video footage and I'll handle the AI-guided course editing. Or just describe what you're after.
**Try saying:**
- "edit a 10-minute screen recording of a tutorial into a 1080p MP4"
- "trim the pauses, add chapter titles, and sync background music to the cuts"
- "editing online course lessons with AI-assisted cuts and captions for online course creators"
### First-Time Connection
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.
1. **Obtain a free token**: Generate a random UUID as client identifier. POST to `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.
2. **Create a session**: POST to `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.
# Video Editing with AI Course — Edit and Export Course Videos
Drop your raw video footage in the chat and tell me what you need. I'll handle the AI-guided course editing on cloud GPUs — you don't need anything installed locally.
Here's a typical use: you send a a 10-minute screen recording of a tutorial, ask for trim the pauses, add chapter titles, and sync background music to the cuts, 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 — breaking long lectures into shorter segments speeds up processing and keeps students engaged.
## Matching Input to Actions
User prompts referencing video editing with ai course, 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.
Three attribution headers are required on every request and must match this file's frontmatter:
| Header | Value |
|--------|-------|
| `X-Skill-Source` | `video-editing-with-ai-course` |
| `X-Skill-Version` | frontmatter `version` |
| `X-Skill-Platform` | auto-detect: `clawhub` / `cursor` / `unknown` from install path |
**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
### 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.
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 "trim the pauses, add chapter titles, and sync background music to the cuts" — 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 across course platforms like Teachable and Udemy.
## Common Workflows
**Quick edit**: Upload → "trim the pauses, add chapter titles, and sync background music to the cuts" → 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.