video_toolkit

What this skill does

# Video Toolkit

Create professional explainer videos from a text brief. The toolkit uses open-source AI models on cloud GPUs (Modal or RunPod) for voiceover, image generation, music, and talking head animation. Remotion (React) handles composition and rendering.

## CRITICAL: Toolkit Path

The toolkit lives at a fixed path. **ALWAYS `cd` here before running any tool command.**

```bash
TOOLKIT=~/.openclaw/workspace/claude-code-video-toolkit
cd $TOOLKIT
```

**NEVER run tool commands from inside a project directory.** Tools resolve paths relative to the toolkit root.

## CRITICAL: Progress Reporting

**ALWAYS add `--progress json` to every cloud GPU tool command.** This gives you structured JSON Lines on stderr so you can monitor job status, detect stuck jobs, and report progress to the user in real-time.

```bash
# CORRECT — always include --progress json
python3 tools/music_gen.py --preset corporate-bg --duration 60 --output bg.mp3 --progress json

# WRONG — no visibility into job status
python3 tools/music_gen.py --preset corporate-bg --duration 60 --output bg.mp3
```

Tools that support `--progress json`: `music_gen.py`, `qwen3_tts.py`, `flux2.py`, `upscale.py`, `sadtalker.py`, `image_edit.py`, `dewatermark.py`, `ltx2.py`, `chain_video.py`.

See the **Progress Reporting** section below for output format and stage definitions.

## CRITICAL: Long-Running Tasks — Use yieldMs, Not background:true

**Any tool command that takes more than 30 seconds MUST use `exec` with `yieldMs` so you can report progress to the user live.** This includes: batch FLUX generation, chain_video, SadTalker, music generation, and any multi-scene pipeline.

```
exec command:"cd ~/.openclaw/workspace/claude-code-video-toolkit && python3 tools/chain_video.py --output-dir /path/ --progress json ..." yieldMs:10000
```

**The polling loop:**
1. `exec` with `yieldMs:10000` starts the command and returns control to you every 10 seconds
2. Read the `--progress json` output — look for `"stage":"item"` (scene complete) or `"stage":"complete"` (all done)
3. Report progress to the user ("Scene 05/30 complete, 17%")
4. Poll again: `process action:poll sessionId:<id>`
5. Repeat until `"stage":"complete"`

**Why:** Your agent run ends when you finish responding. If you use `bash background:true`, you lose the ability to report progress — the user sees silence until they nudge you. With `yieldMs`, you stay in the loop.

**NEVER do this:**
- `bash background:true command:"long running thing"` then promise to "monitor" — you can't, your run ends
- Break a batch into individual tool calls across separate messages — your run ends between each one
- Promise to "continue autonomously" — you literally cannot without an external trigger

## Setup

### Step 1: Check Current State

```bash
cd ~/.openclaw/workspace/claude-code-video-toolkit
python3 tools/verify_setup.py
```

If everything shows `[x]`, skip to "Quick Test" below. Otherwise continue setup.

### Step 2: Install Python Dependencies

```bash
cd ~/.openclaw/workspace/claude-code-video-toolkit
pip3 install --break-system-packages -r tools/requirements.txt
```

Note: `--break-system-packages` is needed on Debian/Ubuntu with managed Python (PEP 668). Safe inside containers.

### Step 3: Configure Cloud GPU Endpoints

The toolkit needs cloud GPU endpoint URLs in `.env`. Check if `.env` exists and has Modal endpoints:

```bash
cat ~/.openclaw/workspace/claude-code-video-toolkit/.env | grep MODAL
```

If Modal endpoints are configured, you're ready. If not, **ask the user to provide Modal endpoint URLs** or set up Modal:

```bash
pip3 install --break-system-packages modal
python3 -m modal setup   # Opens browser for authentication

# Deploy each tool — capture the endpoint URL from output
cd ~/.openclaw/workspace/claude-code-video-toolkit
modal deploy docker/modal-qwen3-tts/app.py
modal deploy docker/modal-flux2/app.py
modal deploy docker/modal-music-gen/app.py
modal deploy docker/modal-sadtalker/app.py
modal deploy docker/modal-image-edit/app.py
modal deploy docker/modal-upscale/app.py
modal deploy docker/modal-propainter/app.py
modal deploy docker/modal-ltx2/app.py      # Requires: modal secret create huggingface-token HF_TOKEN=hf_...
```

**LTX-2 prerequisite:** Before deploying LTX-2, create a HuggingFace secret and accept the [Gemma 3 license](https://huggingface.co/google/gemma-3-12b-it-qat-q4_0-unquantized):
```bash
modal secret create huggingface-token HF_TOKEN=hf_your_read_access_token
```

Add each URL to `.env`:
```
ACEMUSIC_API_KEY=...                          # Free key from acemusic.ai/api-key (best music quality)
MODAL_QWEN3_TTS_ENDPOINT_URL=https://...modal.run
MODAL_FLUX2_ENDPOINT_URL=https://...modal.run
MODAL_MUSIC_GEN_ENDPOINT_URL=https://...modal.run
MODAL_SADTALKER_ENDPOINT_URL=https://...modal.run
MODAL_IMAGE_EDIT_ENDPOINT_URL=https://...modal.run
MODAL_UPSCALE_ENDPOINT_URL=https://...modal.run
MODAL_DEWATERMARK_ENDPOINT_URL=https://...modal.run
MODAL_LTX2_ENDPOINT_URL=https://...modal.run
```

Optional but recommended — Cloudflare R2 for reliable file transfer:
```
R2_ACCOUNT_ID=...
R2_ACCESS_KEY_ID=...
R2_SECRET_ACCESS_KEY=...
R2_BUCKET_NAME=video-toolkit
```

### Step 4: Verify and Quick Test

```bash
cd ~/.openclaw/workspace/claude-code-video-toolkit
python3 tools/verify_setup.py
```

All tools should show `[x]`. Then run a quick test to confirm the GPU pipeline works:

```bash
cd ~/.openclaw/workspace/claude-code-video-toolkit
python3 tools/qwen3_tts.py --text "Hello, this is a test." --speaker Ryan --tone warm --output /tmp/video-toolkit-test.mp3 --cloud modal
```

If you get a valid .mp3 file, setup is complete. If it fails, check:
- `.env` has the correct `MODAL_QWEN3_TTS_ENDPOINT_URL`
- Run `python3 tools/verify_setup.py --json` and check `modal_tools` for which endpoints are missing

**Cost:** Modal includes $30/month free compute. A typical 60s video costs $1-3.

---

## Creating a Video

### Step 1: Create Project

```bash
cd ~/.openclaw/workspace/claude-code-video-toolkit
cp -r templates/product-demo projects/PROJECT_NAME
cd projects/PROJECT_NAME
npm install
```

Templates: `product-demo` (marketing/explainer), `sprint-review`, `sprint-review-v2` (composable scenes).

### Step 2: Write Config

Edit `projects/PROJECT_NAME/src/config/demo-config.ts`:

```typescript
export const demoConfig: ProductDemoConfig = {
  product: {
    name: 'My Product',
    tagline: 'What it does in one line',
    website: 'example.com',
  },
  scenes: [
    { type: 'title', durationSeconds: 9, content: { headline: '...', subheadline: '...' } },
    { type: 'problem', durationSeconds: 14, content: { headline: '...', problems: ['...', '...'] } },
    { type: 'solution', durationSeconds: 13, content: { headline: '...', highlights: ['...', '...'] } },
    { type: 'stats', durationSeconds: 12, content: { stats: [{value: '99%', label: '...'}, ...] } },
    { type: 'cta', durationSeconds: 10, content: { headline: '...', links: ['...'] } },
  ],
  audio: {
    backgroundMusicFile: 'audio/bg-music.mp3',
    backgroundMusicVolume: 0.12,
  },
};
```

Scene types: `title`, `problem`, `solution`, `demo`, `feature`, `stats`, `cta`.

**Duration rule:** Estimate `durationSeconds` as `ceil(word_count / 2.5) + 2`. You will adjust this after generating audio in Step 4.

### Step 3: Write Voiceover Script

Create `projects/PROJECT_NAME/VOICEOVER-SCRIPT.md`:

```markdown
## Scene 1: Title (9s, ~17 words)
Build videos with AI. The product name toolkit makes it easy.

## Scene 2: Problem (14s, ~30 words)
The problem statement goes here. Keep it punchy and relatable.
```

**Word budget per scene:** `(durationSeconds - 2) * 2.5` words. The -2 accounts for 1s audio delay + 1s padding.

### Step 4: Generate Assets

**CRITICAL: All commands below MUST be run from the toolkit root, not the project directory.**

```bash
cd ~/.openclaw/workspace/claude-code-video-toolkit
```

#### 4a. Background Music

Default provider is **acemusic** (official cloud API, free k