vox-video-director

# Vox Video Director Turn a one-line topic into a finished **Vox-style paper-collage video**: a bold, punchy, narrated explainer/ad where each beat is a torn-paper collage poster that comes alive, with voice-over, optional music and captions. Runs through authenticated **Bailian CLI (`bl`)** + local **ffmpeg**. The look is the modern editorial paper-collage popularized by Vox explainers and creators like Stav Zilber / rom1trs: hand-cut paper cut-outs, torn edges, tape, halftone dots, newspaper clippings, bold flat color per beat, big cut-out headlines. ## The core idea (read this first) The Vox collage look and the collage motion are **two different steps**: 1. **The look is born in the IMAGE step.** Each beat is a finished collage *poster* made by a text-to-image model. All the collage DNA (torn paper, cut-outs, halftone, bold color, headline text) lives in that image. If the image isn't a rich collage, nothing downstream will save it. 2. **The motion is added after.** By default an AI video model animates the whole poster (the "living poster" path — simple, automated). For dramatic *piece-by-piece* assembly you cut the poster into parts and drive them with the local keyframe engine (advanced path). Everything hinges on the prompts. **Before writing any image or video prompt, read `references/prompt-guide.md`** — it has the exact prompt structures that make the difference between "a real Vox collage" and "a moving PowerPoint". ## Prerequisites (check, don't skip) - `bl --version` — requires Bailian CLI 1.14.3 or newer. - `bl auth status` — if unauthenticated, run `bl auth login --api-key <key>` and stop until login succeeds. - `command -v ffmpeg ffprobe` — required for assembly (`brew install ffmpeg` on macOS). - `python3 -c "import PIL"` — Pillow, for captions/watermark overlays. ## Standard workflow (topic → film) This is the default, most-automated path. Every stage is one script, all driven by a single `beats.json` per project under `out/<project>/`. 1. **Topic → beat map.** First **read `references/beat-layer.md`** (the story layer) and pick a narrative `arc` that fits the topic (`timeline` for history, `pas`/`bab` for ads, `how_it_works` for explainers, `man_in_hole` for transformations, …). Then write `out/<project>/beats.json` following that arc. **Beat 1 must hook within 3s.** Default to **one beat = one generated video segment = one shot**. Size every segment from its narration, not a fixed template: target **5–10s**, use `python3 scripts/timing.py out/<project> --estimated`, and split any narration that estimates above 10s. A 60s film is usually 7–10 content-sized beats, not six fixed 10s blocks or twelve fixed 5s shots. Vary `camera_move` across adjacent beats (never repeat; use `static` on the payoff) and write rich `element_motion`. Each beat needs `narration`, `title_cn`/`title_en`, `scene`, `bg`, `feel`, `hook`, and one `shots` item whose `dur` may be omitted. This draft with estimated durations is the **first mandatory approval gate**. Use `examples/content-timing.beats.json` as the default schema example. 2. **Pick the visual style (hybrid — do this BEFORE keyframes).** Do not reuse one house style for every topic. Read `references/prompt-guide.md` (§5 theme presets); pick 3–4 **theme presets** (`styles.THEME_PRESETS`: `american-retro`, `swiss-modern`, `punk-zine`, `soviet-constructivist`, `wpa-propaganda`, `70s-groovy`, `chinese-ink`, `atomic-age`, `newsprint-editorial`) that fit the topic's era/culture/tone — **or compose a custom theme** by mixing the prompt-guide dimensions (medium/era/palette/type/finish) when none fit. Match the topic, **not** the language (an English film on Chinese history should look Chinese). A theme bundles the whole LOOK layer (idiom+palette+type+finish+mood+motion). Run a bake-off and let the user pick by eye — AI proposes, the library is the quality floor, the human decides. Set the pick as `"theme"`: `python3 scripts/style_bakeoff.py out/<project> american-retro,swiss-modern,punk-zine,atomic-age` Set the chosen name as `"collage_style"` in beats.json (keyframes.py reads it). 3. **Voice + measured timing.** `python3 scripts/audio.py out/<project>` Generates one consistent narrator with **`bl speech synthesize` + cosyvoice-v3-flash**, then replaces text estimates with measured audio durations plus a short edit tail. New segments clamp to 5–10s. If `timing_issues` is non-empty, split those narration beats and run audio again **before** paying for images or videos. Pick `voice_id` for the topic and language; see `references/voices.md`. Bailian CLI 1.14.x has no music generation command; provide a local `bgm_path` or assemble without music. 4. **Keyframes (the collage look).** `python3 scripts/keyframes.py out/<project>` Generates one collage poster per beat/shot with **`bl image generate` + qwen-image-3.0**, headline text baked in. Compose prompts with the 5-part structure in `references/prompt-guide.md`. Verify each poster looks like a *real layered collage* before animating — re-roll cheap ($0.08) here rather than paying to animate a weak image. 5. **Motion.** `python3 scripts/clips.py out/<project>` Animates each poster with **`bl video generate` + happyhorse-1.1-i2v**. Two independent axes (see `references/beat-layer.md` §3, tested on our stack): • **`camera_move`** — ONE move per shot. Safe/default: `{static, push_in, pull_out, pan, tilt, parallax}`. **Bold/experimental** `{orbit, dolly_zoom, roll, whip}` are **available, not banned** — they can warp the flat art, so pair with `constraints: loose` and **re-roll**. Any custom phrase also passes through. • **`element_motion`** — where the energy lives; **AI writes it per beat to fit that scene** (not a template). Make it RICH (several elements moving) — be bold. A **hero element flying across the frame** (paper bird/plane/coins) is a great **occasional** punch on a key beat, **not every shot** (a flyer in every frame reads as a formula). `motion_style` = amplitude `calm | punchy | max` (the theme sets a default). **`constraints`** = `strict` (default: defect guards on — flat-2D, one-way, no-morph; best for clean text-heavy explainers) or `loose` (let the model explore 3D/bold moves; re-roll the misses). **Headline text is hard-protected only on shots that have a title** (detail shots without a headline are free to go wild). The Bailian default is `happyhorse-1.1-i2v`; validate real-person and brand use against the selected model's current policy before a full run. **Aspect routing** (`styles.resolve_video_aspect`, second approval gate): `clips.py` resolves `doc["aspect"]` against the chosen `video_model`'s own supported ratios — exact match wins; Omni is 16:9/9:16 only, Kling reference-to-video adds 1:1, Kling image-to-video/video-edit and Seedance just follow the input/ratio param. When there's no exact match it picks the nearest ratio but **stops and asks you to confirm** (set `"aspect_approx_confirmed": true` once you have) rather than silently reframing the film — every clip in one run shares the same resolved aspect so the finished film is never mixed. 6. **Assemble.** `python3 scripts/assemble.py out/<project>` ffmpeg: normalize + concat all shots, lay the single narration ducked under the music, burn captions timed per beat, add the watermark. Output `out/<project>/final.mp4`. 7. **Verify.** You can't read an mp4 directly — extract frames to jpg and look: `ffmpeg -ss <t> -i final.mp4 -vf "scale=640:-1,format=yuvj420p" -frames:v 1 f.jpg` ### Cadence — content decides duration - Default to one narration beat and one generated clip per segment. Keep each segment in the model-safe **5–10s** range. - Estimate before generation from text length; after TTS, treat measured `narration_dur` as authoritative and round up to the next 0.5s with a ~0.45s edit tail. - Video APIs receive the next whole second (for example 6.5s → request 7s); assembly trims the returned clip to the exact edit duration, so narration is never cut. - Short text still gets 5s so the idea can land. Long text gets up to 10s. If narration plus tail exceeds 10s, split it at a sentence or clause boundary; never speed-read or silently stretch a clip past the model limit. - A 60s film usually lands at 7–10 segments of mixed lengths. Avoid identical durations across the whole film unless the source genuinely has equal-length beats. - Use multiple shots inside one beat only as an explicit editorial choice. Legacy multi-shot projects remain supported, but new content-driven projects should split the narration into separate beats so each generated clip still has its own 5–10s content unit. ## A-roll mode (talking-head → collage) The standard workflow above is **B-roll**: a topic becomes AI-generated collage posters that get animated. **A-roll is the reverse case** — the user already has a real recorded talking-head video (a presenter speaking to camera) and wants it *itself* turned into the collage look, keeping their actual performance (face, lip movement, gestures) intact. There is no poster to generate; the "keyframe" is the presenter's own footage. Use A-roll when the user gives you a video file of themselves/a presenter talking, not a topic to write from scratch. 1. **Transcribe + auto-segment.** `python3 scripts/asr_beats.py <project_dir> <source.mp4>` Runs `bl speech recognize` (`fun-asr`) on the source audio and cuts it into beats at sentence-ending punctuation or natural pause gaps (never exceeding ~9.5s, under Omni/Kling video-edit's 10s per-call cap). Writes `beats.json` with each beat's `start`/`end`/`text` — **this is the same mandatory approval gate as the B-roll beat map**: review it, set `"theme"` (run `style_bakeoff.py` the same way — the presenter's segment works fine as the bake-off source), and optionally fill in a `content_beats` string per beat (a sticker/stamp idea to layer in) before generating anything. 2. **Generate.** `python3 scripts/aroll_clips.py <project_dir> [only_ids]` Cuts each beat's time range out of the source, uploads it, and re-styles it with a **photographic paper-cutout sticker** treatment on the presenter — her real likeness, lip movement, eye-line and gestures follow the source frame-for-frame; only the silhouette edge and the world around her are paper-collage. Default model is `happyhorse-1.0-video-edit` through `bl video edit` (set via `video_model`/`video_model_fallback` in beats.json). **Never ask the model to redraw or halftone-texture the face itself** — that gets rejected regardless of how the prompt is worded (tried both a strong and a softened phrasing; both failed). Uses the same aspect-routing confirm gate as `clips.py`. 3. **Assemble.** `python3 scripts/aroll_assemble.py <project_dir>` Muxes each generated clip with the *original* beat segment's own audio (never whatever audio the video model produced) so lip-sync is guaranteed regardless of which model handled that beat, normalizes every beat to one canvas, and concats into `final.mp4`. ## C-roll mode (one photo → collage) The third input modality — "cutout roll". A-roll re-styles a talking-head VIDEO; B-roll generates everything from a topic; **C-roll takes a single still PHOTO** (a selfie, an avatar card, a product shot) and anchors it inside the collage world: the subject is cut out as a PHOTOGRAPHIC sticker — never redrawn — and per-beat posters are generated around it with an image-EDIT model, then animated through the normal clip stage. Use C-roll when the user gives you one photo and a topic: a personal explainer fronted by their own face, or a collage ad built around a real product shot (validated on both, 2026-07-17). 1. **Beat map.** Same as B-roll (`references/beat-layer.md`, same approval gate), plus the C-roll fields in beats.json: `"mode": "croll"`, `"anchor_photo"`, `"croll_subject"` (`portrait` | `product`), and `subject_wardrobe` (portrait — lock the outfit or the paper-doll body drifts) or `subject_desc` (product). Set `"title": false` on shots — C-roll posters carry no headline; text belongs to captions. If there is no separate script, transcribe/derive narration first and let the audio's ASR timestamps define the beats (audio-first, like A-roll — not text-first like B-roll). 2. **Anchored keyframes.** `python3 scripts/croll_keyframes.py <project_dir>` Uploads the photo once and generates one anchored poster per shot via `qwen-image-3.0` through `bl image edit`. Portraits get a photographic face + illustrated paper-doll body; products get a pixel-faithful sticker with label typography intact. Prompt rules that are baked in (all three cost a re-run to learn): poses/expressions go to the BODY only — asking for a wink redraws the face; halftone must be scoped to the background or it bleeds onto skin; portrait clothing must be locked explicitly. The script also writes `anchor_freeze` into beats.json. 3. **Voice timing + animate + assemble.** Standard `audio.py` → `clips.py` → `assemble.py`. `clips.py` injects the `anchor_freeze` guard into every motion prompt — without it the video stage can re-letter a product label (observed: "PARFUM" → "PAREUM") or re-time a face. For narration in the subject's own voice, set `voice.clone_ref` (see Voice + music above); derive stamp/snap-zoom timing from the narration's ASR word timestamps (`asr_beats.py` works on any audio, not just A-roll footage). ## beats.json schema ```json { "project": "my-film", "topic": "...", "language": "en", "aspect": "9:16", // 16:9 | 9:16 | 1:1 | 3:4 "style": "collage", "provider": "bailian_cli", // default; invokes authenticated `bl` child processes "theme": "american-retro", // THEME_PRESET (styles.THEME_PRESETS) — the LOOK layer "arc": "timeline", // narrative arc (beat-layer.md) — the STORY skeleton "video_model": "happyhorse-1.1-i2v", "image_model": "qwen-image-3.0", "image_resolution": "1k", // 1k (default) | 2k | 4k "video_resolution": "720p", // 720p (default); Seedance also 480p/1080p (Omni is 720p-only) "motion_style": "punchy", // amplitude: calm | punchy | max (theme sets a default) "constraints": "strict", // strict = defect guards on | loose = let AI explore + re-roll "timing_mode": "content", // default: text estimate, then measured TTS duration "timing": {"min_segment": 5, "max_segment": 10, "tail": 0.45}, "voice": {"voice_id": "longtian_v3", "language": "zh", "speed": 1.0}, // see references/voices.md // + optional "clone_ref": "path/to/sample.mp3" (clone that voice via seed-audio) // and "persona": "YouTube tutorial creator" (delivery style for cloned VO) "bgm_path": "path/to/instrumental.mp3", // optional; omit to assemble without music "mix": {"music": 0.6, "voice": 1.25}, // audio balance — optional; these are the defaults (BGM ducks under the VO) "caption_style": "white", // white (default: clean white subtitle) | paper (cream cut-out collage look) "captions": true, // false = no burned-in captions (deliver clean, subtitle in post) "watermark": "Made By 阿里云百炼CLI", "mode": "croll", // C-roll only — plus the four fields below "anchor_photo": "path/to/photo.png", // C-roll: the still to anchor (person or product) "croll_subject": "portrait", // C-roll: portrait | product "subject_wardrobe": "a cream knitted sweater and charcoal trousers", // C-roll portrait: outfit lock "subject_desc": "the perfume bottle", // C-roll product: short noun phrase for the sticker "beats": [ { "id": 1, "title_cn": "", "title_en": "BEFORE MONEY", "bg": "earthy clay tan", "feel": "ancient, humble", "hook": "surprising_stat", "narration": "For most of history, there was no money...", "shots": [ // Omit dur: timing.py/audio.py sets a content-driven 5-10s duration. {"id": "a", "title": true, "shot_size": "WIDE", "camera_move": "push_in", "scene": "...wide establishing collage...",