ASCII art visualization toolkit for PNG, GIF, and MP4 output.
Project description
viz - ASCII Art Visualization Toolkit
PNG/GIF/MP4 ASCII art. Variable resolution (default 1080x1080, up to 3840px), custom palettes, kaomoji, procedural effects, emotion-driven styles. Pure Python 3 + Pillow.
Install
pip install aaajiao-viz
Upgrade an existing install:
pip install -U aaajiao-viz
Verify the CLI is available:
viz --version
viz capabilities --format json
Quick Start
# Generate from emotion
viz generate --emotion euphoria --seed 42
# AI integration via stdin JSON
echo '{"headline":"BTC $95K","emotion":"euphoria","metrics":["ETH: $4.2k"]}' | viz generate
# Animated GIF
echo '{"emotion":"panic","video":true}' | viz generate
# Discover all options
viz capabilities --format json
How It Works
viz is an installed CLI for procedural ASCII image generation. AI decides what to express; VIZ decides how it looks.
emotion/text --> VAD vector --> grammar --> SceneSpec --> Engine --> output
(continuous) (stochastic) (full spec) (auto- (PNG/GIF/MP4,
scaled) variable res)
Everything is driven by the VAD emotion model (Valence-Arousal-Dominance). 26 named emotions map to points in continuous 3D space. The grammar system samples visual choices weighted by emotion — same emotion + different seed = different output.
Combinatorial space: 17 effects x 86 variants x 9 transforms x 7 postfx x 6 masks x 73 gradients x 8 decorations x bg_fill combos x continuous params = effectively infinite.
Commands
| Command | Purpose |
|---|---|
generate |
Render visualization (variable resolution, PNG/GIF/MP4) |
convert |
Convert image to ASCII art |
capabilities |
Output full inventory as JSON for AI discovery |
Input (stdin JSON, all fields optional)
{
"emotion": "euphoria",
"headline": "BTC $95K",
"metrics": ["ETH: $4.2k", "SOL: $300"],
"vocabulary": {"particles": "$€¥₿↑↓", "kaomoji_moods": ["euphoria", "excitement"]}
}
Emotion drives all visual choices. vocabulary overrides specific visual assets (particles, kaomoji moods, decoration chars). Full field reference in docs/ai-integration.md.
Output
{"status": "ok", "results": [{"path": "media/viz_20260203_120000_s42.png", "seed": 42, "format": "png"}], "emotion": "euphoria", "resolution": [1080, 1080]}
Director Mode
Grammar auto-selects everything from emotion. Override any dimension for precise control:
viz generate --emotion euphoria --seed 100 \
--effect plasma --variant warped \
--transforms kaleidoscope:segments=6 \
--postfx vignette:strength=0.5 scanlines:spacing=4 \
--composition radial_masked
Details in docs/composition.md.
Project Structure
viz.py # Single CLI entry
lib/ # Shared: kaomoji, content, box-drawing chars, vocabulary
procedural/
engine.py # Render orchestrator (auto-scaled buffer -> output)
effects/ # 17 pluggable effects + 86 structural variants
transforms.py # 9 domain transforms (mirror, kaleidoscope, tile, ...)
postfx.py # 7 buffer-level post-FX (vignette, scanlines, ...)
masks.py # 6 spatial masks (radial, noise, sdf, ...)
flexible/
emotion.py # VAD continuous emotion space (26 anchors)
grammar.py # Stochastic visual grammar
pipeline.py # Main pipeline orchestrator
docs/ # Detailed documentation
skills/viz-ascii-art/ # AgentSkills integration
Documentation
| Doc | Content |
|---|---|
| ai-integration.md | Start here. JSON protocol, capabilities, examples |
| usage.md | CLI args, all commands |
| flexible.md | VAD model, grammar, SceneSpec |
| composition.md | Transforms, masks, PostFX, variants |
| effects.md | 17 effects with params |
| kaomoji.md | 22 moods, 336 faces |
| box_chars.md | 73 gradients, 37 charsets |
| rendering.md | Engine internals |
Development
git clone https://github.com/aaajiao/VIZ.git
cd VIZ
pip install -e ".[dev]"
pytest tests/ -v
python -m build
Published package: aaajiao-viz on PyPI
Runtime dependency: Pillow>=9.0.0. All math is pure Python stdlib (no NumPy). MP4 output requires system FFmpeg.
License
MIT - see LICENSE
Reference
- play.ertdfgcvb.xyz - Inspiration
- play.core - Core reference
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