Video

video

Use this skill for all video-generation requests on Starchild.

Core principle: call the provided scripts. Do not re-implement proxy/billing/upload plumbing.

1. Text-to-video (most common)

⚠️ Execution context — read this first. The code blocks below are Python, not shell commands. Starchild's bash tool runs /bin/bash -c, which cannot parse exec(open(...)) — pasting them directly into a bash command will fail with syntax error near unexpected token 'open'. Also, exec(open(...)) inside python3 -c fails with NameError: __file__ because the script uses __file__ for path resolution.

Use python3 - <<'EOF' with from exports import when calling via the bash tool:

python3 - <<'EOF'
import sys
sys.path.insert(0, "skills/video")
from generate_video import generate_video
result = generate_video(
    prompt="A cinematic drone shot over snowy mountains at sunrise",
    model="balanced",
    duration=5,
)
print(result)
EOF

The heredoc (<<'EOF') preserves all quotes and newlines — no escaping needed. Note: video skill has no exports.py — import directly from generate_video.

exec(open('skills/video/generate_video.py').read())
result = generate_video(
    prompt="A cinematic drone shot over snowy mountains at sunrise",
    model="balanced",   # "budget" | "balanced" | "premium"
    duration=5,
)
# result -> {"success": True, "cost": 0.70, "video_url": "...", "local_path": "output/videos/..."}

generate_video automatically: submits → polls → fetches result → downloads mp4 to output/videos/.

Delivering the result to the user — IMPORTANT

Never hand the user the raw video_url (e.g. https://*.fal.media/.../*.mp4). fal serves these files with Content-Security-Policy: sandbox; default-src 'none', which means:

• Opening the link in a browser shows a blank page (no inline player triggered).
• Embedding via <video> / <iframe> is blocked by CSP.
• There is no Content-Disposition: attachment header, so the browser does not auto-download either.
• URL-side tweaks (query params, ?download=1, etc.) cannot fix this — only a server-side header change would, and we don't control fal's CDN.

The only reliable user-facing delivery path is the already-downloaded local file:

1. Use result["local_path"] (e.g. output/videos/xxx.mp4) — generate_video always downloads on success.
2. Tell the user the file is saved to output/videos/<filename> and is viewable in the workspace file panel / file browser.
3. On Web channel, also embed it inline so the user can preview it in chat:

   ![video](output/videos/<filename>.mp4)
   

   (or link as [video](output/videos/<filename>.mp4) — the workspace serves these directly with the right headers).
4. On Telegram / WeChat: send the file via send_to_telegram(file_path="output/videos/...", message_type="video") or send_to_wechat(file_path="output/videos/...", message_type="video").

If the download somehow failed (local_path missing) — re-fetch with:

curl -L -o output/videos/<filename>.mp4 "<video_url>"

Then deliver the local path. Still do not give the user the raw fal URL as the primary deliverable.

2. Image-to-video / video-to-video (reference assets)

fal.ai needs the reference asset as a public https URL. fal storage upload requires a Serverless permission your key currently does not have. The reliable path is to expose the asset via a published Starchild preview.

Standard procedure

1. Drop or copy the asset into output/fal_assets/ using publish_asset.py.
2. Make sure a preview named fal-assets is running and published (one-time setup, see §3).
3. Build the public URL as <preview_base>/<filename>.
4. Call generate_video(... image_url=public_url).

# Step 1: publish a local image into the asset folder
exec(open('skills/video/publish_asset.py').read())
asset = publish_local('/path/to/your/photo.jpg')
# or: publish_from_url('https://example.com/photo.jpg')

filename = asset['filename']

# Step 2: combine with the preview's public base URL (see §3)
public_url = f"https://community.iamstarchild.com/<user_slug>-fal-assets/{filename}"

# Step 3: image-to-video
exec(open('skills/video/generate_video.py').read())
result = generate_video(
    prompt="gentle cinematic camera push-in",
    model="balanced",
    duration=5,
    image_url=public_url,
)

generate_video auto-rewrites the model path from */text-to-video to */image-to-video whenever image_url is provided. The same approach works for video-to-video models — pass an mp4 URL instead.

Asset constraints (enforced by publish_asset.py)

• Image: .jpg .jpeg .png .webp .gif .bmp, max 10 MB
• Video: .mp4 .mov .webm .mkv .m4v, max 100 MB
• Anything outside these is rejected before publish

3. One-time fal-assets public preview setup

Run this once per workspace. The preview keeps running across sessions.

# 3.1 ensure the asset folder exists with a placeholder index
import os, pathlib
pathlib.Path('output/fal_assets').mkdir(parents=True, exist_ok=True)
if not os.path.exists('output/fal_assets/index.html'):
    open('output/fal_assets/index.html', 'w').write(
        '<!doctype html><html><body><h1>fal asset host</h1></body></html>'
    )

# 3.2 start the preview
preview(action='serve', dir='output/fal_assets', title='fal-assets')

# 3.3 publish to a public URL
preview(action='publish', preview_id='<id from step 3.2>', slug='fal-assets', title='fal-assets')
# → public base: https://community.iamstarchild.com/<user_slug>-fal-assets/

After publish, the public base URL is reusable for every future image-to-video / video-to-video task. Files dropped into output/fal_assets/ become reachable as <base>/<filename> immediately — no re-publish needed.

Verify with:

curl -sI https://community.iamstarchild.com/<user_slug>-fal-assets/<filename>
# expect: HTTP/2 200, content-type: image/* or video/*

If preview(action='serve') returns No available ports in pool, ask the user which existing preview can be stopped to free a port — never silently kill one.

4. Model selection

Override by passing the full model id to generate_video(model=...). Image-to-video variants are auto-derived by replacing text-to-video with image-to-video.

Pricing details and model registry live in generate_video.py::estimate_cost.

5. Polling an existing request

exec(open('skills/video/poll_status.py').read())
result = poll_video("019ded6c-d871-7290-bbf1-ddc6993f8958")

Use this when an earlier generate_video call timed out or you only have a request_id.

6. Provided scripts

• generate_video.py — submit → poll → download. Handles text-to-video and image-to-video.
• publish_asset.py — copy local files (or download remote URLs) into output/fal_assets/ so they can be served by the fal-assets preview.
• poll_status.py — resume polling by request_id, downloads the result on completion.

7. Troubleshooting

8. Infrastructure (reference)

• Caller → sc-proxy → queue.fal.run (and api.fal.ai) → fal model providers
• All requests must include Authorization: Key fake-falai-key-12345 (proxy injects the real FAL_KEY)
• Pre-charge happens at submit. Poll/result calls are free.
• Allowed endpoints: video text-to-video / image-to-video / video-to-video / edit-video for the registered models. Anything else returns 403 endpoint_not_allowed.
• Final mp4 lives at https://*.fal.media/... — public CDN, no auth needed for download.

9. Maintenance

• Adding a new model → register price in generate_video.py::estimate_cost and in transparent-proxy/apis/falai.py::_VIDEO_PRICING.
• Asset hosting via fal storage upload is intentionally not used in this skill: the production FAL_KEY lacks Serverless permission. Keep using the preview-based approach until that changes.