build-in-public-video

name

build-in-public-video

description

Generate a "build in public" narrated video using Remotion. The video topic is provided in the first prompt. Produces an MP4, per-scene MP3 voice-over (macOS `say` + ffmpeg), and a multi-page slides PDF (one still per scene via ImageMagick). Trigger when the user asks to "generate/render/build a video", "make a build-in-public video", "render with Remotion", "create voice-over", or to produce slides/PDF from the video scenes.

build-in-public-video

• Generate a video based on the user description
• Add a voice-over narration track.
• make it 1-2 minutes long (may be overridden by the user)
• generate a PDF of slides

Hitting the 1–2 min target

Total video length is driven by total voice-over length (each <Sequence> is sized from its MP3's duration). Default macOS say runs ~175 wpm, so:

• 1 minute → ~175 words across all scene .txt files combined
• 2 minutes → ~350 words combined

Budget words per scene roughly proportional to its importance, then verify with ffprobe after generating MP3s and adjust the scripts if the sum falls outside the target.

Workflow

Run these steps in order:

1. Write per-scene narration text and generate per-scene MP3s (see "How to Generate Voice-over Narration" below).
2. Wire each <Audio> + <Sequence> pair into src/Composition.tsx, using the measured per-scene durations.
3. Render the MP4 with npx remotion render (see "Render Video" in misc Remarks).
4. Extract one still per scene and assemble them into out/slides.pdf (see "Slides Generation into PDF").

How to Generate Voice-over Narration

Generate a voice-over audio track for the video, split per scene. Use the macOS say command (so it can be customized via system speech settings), then convert each clip to MP3 with ffmpeg.

Steps:

1. Write one text file per scene under public/scenes/ (e.g. scene1.txt … sceneN.txt). Use short, spoken-friendly sentences. Replace symbols and underscores with spoken forms (e.g. write "a11y parse" instead of "a11y_parse").

2. For each scene file, generate the audio: say -f public/scenes/sceneN.txt -o public/scenes/sceneN.aiff ffmpeg -y -i public/scenes/sceneN.aiff public/scenes/sceneN.mp3

3. Read each scene's duration with ffprobe (single numeric value, in seconds): ffprobe -v error -show_entries format=duration -of csv=p=0 public/scenes/sceneN.mp3 Convert seconds → frames using the composition's fps (e.g. Math.ceil(seconds * fps)), then use those frame counts to size each <Sequence> in the Remotion composition. Layer each public/scenes/sceneN.mp3 as an <Audio> (from @remotion/media) inside its corresponding <Sequence>, so each scene plays its own narration.

Output: public/scenes/sceneN.mp3 files, one per scene.

Slides Generation into PDF

After the Remotion video is generated, create still slides at the end of each scene and assemble them into a PDF.

1. Read src/Composition.tsx to extract:

   • Each scene's duration in frames (e.g. SCENE1_FRAMES, SCENE2_FRAMES, …)
   • Each scene's offset in the composition (cumulative sum of prior durations)
   • The fade-out duration used by fadeInOut(frame, durationInFrames, fadeFrames) — typically 18 frames
   • The composition id and entry file (e.g. MyComp in src/index.ts)

2. For each scene N, compute the capture frame as the last fully-opaque frame BEFORE the fade-out begins:

   • captureFrameN = sceneOffsetN + sceneDurationN - fadeFrames - 1
   • This ensures the slide shows the scene fully rendered, with all in-scene animations settled and no fade transparency.

3. Render one PNG per scene with Remotion's still command:

   • npx remotion still <entry> <comp-id> out/sceneN.png --frame=<captureFrameN> --image-format=png
   • Run sequentially (or chained with &&) so the bundle is reused.
   • Output goes to out/scene1.png … out/sceneN.png at the composition's native resolution (e.g. 1920×1080).

4. Combine the PNGs into a single multi-page PDF using ImageMagick, in scene order:

   • magick out/scene1.png out/scene2.png … out/sceneN.png out/slides.pdf

5. Verify out/slides.pdf exists and report the per-scene capture frames plus the PDF path back to the user.