Squashed 'client/' content from commit 4bb0841

git-subtree-dir: client
git-subtree-split: 4bb084154a4eb4b4f580d52d936cab05ef313ebb
This commit is contained in:
giles
2026-02-24 23:09:47 +00:00
commit 7784e6b2b0
6 changed files with 2689 additions and 0 deletions

5
.gitignore vendored Normal file
View File

@@ -0,0 +1,5 @@
__pycache__/
*.py[cod]
.venv/
venv/
.scripts

263
README.md Normal file
View File

@@ -0,0 +1,263 @@
# Art DAG Client
CLI for interacting with the Art DAG L1 rendering server.
## Setup
```bash
pip install -r requirements.txt
```
## Configuration
```bash
# Set L1 server URL (default: http://localhost:8100)
export ARTDAG_SERVER=http://localhost:8100
# Set L2 server URL for auth (default: http://localhost:8200)
export ARTDAG_L2=https://artdag.rose-ash.com
# Or pass with commands
./artdag.py --server http://localhost:8100 --l2 https://artdag.rose-ash.com <command>
```
## Authentication
Most commands require authentication. Login credentials are stored locally in `~/.artdag/token.json`.
```bash
# Register a new account
artdag register <username> [--email user@example.com]
# Login
artdag login <username>
# Check current user
artdag whoami
# Logout
artdag logout
```
## Commands Reference
### Server & Stats
```bash
# Show server info
artdag info
# Show user stats (counts of runs, recipes, effects, media, storage)
artdag stats
# List known named assets
artdag assets
```
### Runs
```bash
# List runs (with pagination)
artdag runs [--limit N] [--offset N]
# Start a run
artdag run <recipe> <input_cid> [--name output_name] [--wait]
# Get run status
artdag status <run_id>
# Get detailed run info
artdag status <run_id> --plan # Show execution plan with steps
artdag status <run_id> --artifacts # Show output artifacts
artdag status <run_id> --analysis # Show audio analysis data
# Delete a run
artdag delete-run <run_id> [--force]
```
### Recipes
```bash
# List recipes (with pagination)
artdag recipes [--limit N] [--offset N]
# Show recipe details
artdag recipe <recipe_id>
# Upload a recipe (YAML or S-expression)
artdag upload-recipe <filepath>
# Run a recipe with inputs
artdag run-recipe <recipe_id> -i node_id:cid [--wait]
# Delete a recipe
artdag delete-recipe <recipe_id> [--force]
```
### Effects
```bash
# List effects (with pagination)
artdag effects [--limit N] [--offset N]
# Show effect details
artdag effect <cid>
# Show effect with source code
artdag effect <cid> --source
# Upload an effect (.py file)
artdag upload-effect <filepath>
```
### Media / Cache
```bash
# List cached content (with pagination and type filter)
artdag cache [--limit N] [--offset N] [--type all|image|video|audio]
# View/download cached content
artdag view <cid> # Show metadata (size, type, friendly name)
artdag view <cid> --raw # Get raw content info
artdag view <cid> -o output.mp4 # Download raw file
artdag view <cid> -o - | mpv - # Pipe raw content to player
# Upload file to cache and IPFS
artdag upload <filepath>
# Import local file to cache (local server only)
artdag import <filepath>
# View/update metadata
artdag meta <cid> # View metadata
artdag meta <cid> -d "Description" # Set description
artdag meta <cid> -t "tag1,tag2" # Set tags
artdag meta <cid> --publish "my-video" # Publish to L2
# Delete cached content
artdag delete-cache <cid> [--force]
```
### Storage Providers
```bash
# List storage providers
artdag storage list
# Add a provider (interactive)
artdag storage add <type> [--name friendly_name] [--capacity GB]
# Types: pinata, web3storage, nftstorage, infura, filebase, storj, local
# Test provider connectivity
artdag storage test <id>
# Delete a provider
artdag storage delete <id> [--force]
```
### Folders & Collections
```bash
# Folders
artdag folder list
artdag folder create <path>
artdag folder delete <path>
# Collections
artdag collection list
artdag collection create <name>
artdag collection delete <name>
```
### v2 API (3-Phase Execution)
```bash
# Generate execution plan
artdag plan <recipe_file> -i name:cid [--features beats,energy] [--output plan.json]
# Execute a plan
artdag execute-plan <plan_file> [--wait]
# Run recipe (plan + execute in one step)
artdag run-v2 <recipe_file> -i name:cid [--wait]
# Check v2 run status
artdag run-status <run_id>
```
### Publishing to L2
```bash
# Publish a run output to L2
artdag publish <run_id> <output_name>
```
### Data Management
```bash
# Clear all user data (preserves storage configs)
artdag clear-data [--force]
```
## Example Workflows
### Basic Rendering
```bash
# Login
artdag login myuser
# Check available assets
artdag assets
# Run an effect on an input
artdag run dog cat --wait
# View runs
artdag runs
# Download result
artdag view <output_cid> -o result.mp4
```
### Recipe-Based Processing
```bash
# Upload a recipe
artdag upload-recipe my-recipe.yaml
# View recipes
artdag recipes
# Run with inputs
artdag run-recipe <recipe_id> -i video:bafkrei... --wait
# View run plan
artdag status <run_id> --plan
```
### Managing Storage
```bash
# Add Pinata storage
artdag storage add pinata --name "My Pinata"
# Test connection
artdag storage test 1
# View all providers
artdag storage list
```
### Browsing Media
```bash
# List all media
artdag cache
# Filter by type
artdag cache --type video --limit 20
# View with pagination
artdag cache --offset 20 --limit 20
```

2354
artdag.py Executable file

File diff suppressed because it is too large Load Diff

3
requirements.txt Normal file
View File

@@ -0,0 +1,3 @@
click>=8.0.0
requests>=2.31.0
PyYAML>=6.0

38
test_gpu_effects.sexp Normal file
View File

@@ -0,0 +1,38 @@
;; GPU Effects Performance Test
;; Tests rotation, zoom, hue-shift, ripple
(stream "gpu_effects_test"
:fps 30
:width 1920
:height 1080
:seed 42
;; Load primitives
(require-primitives "geometry")
(require-primitives "core")
(require-primitives "math")
(require-primitives "image")
(require-primitives "color_ops")
;; Frame pipeline - test GPU effects
(frame
(let [;; Create a base gradient image
r (+ 0.5 (* 0.5 (math:sin (* t 1))))
g (+ 0.5 (* 0.5 (math:sin (* t 1.3))))
b (+ 0.5 (* 0.5 (math:sin (* t 1.7))))
color [(* r 255) (* g 255) (* b 255)]
base (image:make-image 1920 1080 color)
;; Apply rotation (this is the main GPU bottleneck we optimized)
angle (* t 30)
rotated (geometry:rotate base angle)
;; Apply hue shift
hue-shift (* 180 (math:sin (* t 0.5)))
hued (color_ops:hue-shift rotated hue-shift)
;; Apply brightness based on time
brightness (+ 0.8 (* 0.4 (math:sin (* t 2))))
bright (color_ops:brightness hued brightness)]
bright)))

26
test_simple.sexp Normal file
View File

@@ -0,0 +1,26 @@
;; Simple Test - No external assets required
;; Just generates a color gradient that changes over time
(stream "simple_test"
:fps 30
:width 720
:height 720
:seed 42
;; Load standard primitives
(require-primitives "geometry")
(require-primitives "core")
(require-primitives "math")
(require-primitives "image")
(require-primitives "color_ops")
;; Frame pipeline - animated gradient
(frame
(let [;; Time-based color cycling (0-1 range)
r (+ 0.5 (* 0.5 (math:sin (* t 1))))
g (+ 0.5 (* 0.5 (math:sin (* t 1.3))))
b (+ 0.5 (* 0.5 (math:sin (* t 1.7))))
;; Convert to 0-255 range and create solid color frame
color [(* r 255) (* g 255) (* b 255)]
frame (image:make-image 720 720 color)]
frame)))