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name: conversion-inference description: "Convert SketchCode PNG wireframes to GUI DSL and HTML, compile/debug GUI DSL, choose output style, and check inference prerequisites." disable-model-invocation: true metadata: disco-role: operating license: MIT

conversion-inference

Use this sub-skill when the user wants to convert hand-drawn/wireframe PNGs with SketchCode, batch-convert mockups, use pretrained model artifacts, compile or debug generated .gui DSL, or choose between the default, facebook, and airbnb HTML styles.

Route first

• For model training, dataset preparation, vocabulary construction, or image augmentation, route to the training-data sub-skill.
• For BLEU scoring details or standalone evaluation of .gui files, route to the evaluation sub-skill. This sub-skill only explains how the conversion CLIs expose optional BLEU flags.
• For downloading or checking external pretrained/data assets, route to the parent sketch-code asset helper when available. Conversion itself requires a Keras model JSON file and an HDF5 weights file.
• Do not treat arbitrary non-PNG images as valid inputs; SketchCode's conversion sampler rejects filenames without .png.

Minimum operating checklist

1. Confirm the user has PNG input: one *.png file for single conversion or a directory containing *.png files for batch conversion.
2. Confirm both pretrained/model artifacts exist: model_json.json-style model architecture JSON and weights.h5-style Keras weights.
3. Choose a style: exactly default, facebook, or airbnb.
4. Choose an output folder. The conversion CLIs create it when missing; existing files with the same sample basename may be overwritten.
5. If the user asks for BLEU during conversion, require matching original .gui files and route metric interpretation to evaluation.

References

• Conversion workflows - safe single-image, batch, and DSL compilation flow.
• CLI reference - public conversion flags, required artifacts, output behavior, and preprocessing facts.
• DSL and styles - supported style names, GUI DSL grammar, known tokens, and compiler behavior.
• API reference - distilled Sampler, Compiler, Node, SamplerUtils, and BLEU-routing facts.
• Troubleshooting - missing assets, invalid PNGs, unsupported styles, parsing errors, imports, and output folder issues.

Bundled helpers

• scripts/run_conversion.py is the bundled, validated replacement for the historical conversion entry points. Use it when the user has a SketchCode runtime checkout or importable classes package plus model JSON/weights.
• scripts/compile_tiny_dsl.py validates and compiles a tiny .gui token string without requiring TensorFlow/Keras or pretrained weights. It can optionally use a user-provided SketchCode project root for the original compiler, but its --help and fallback compiler are self-contained.