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name: text-to-image-generation description: "Write and debug Python min-dalle text-to-image generation calls, streams, tensor/PIL outputs, sampling controls, seamless tiling, seeds, devices, dtypes, and reuse choices." disable-model-invocation: true metadata: disco-role: operating license: MIT

Text-to-Image Generation

Use this sub-skill when a future agent needs to write, adapt, or debug Python MinDalle text-to-image calls: model construction, single-image grids, per-image tensor batches, progressive streams, sampling parameters, seamless tiling, reproducible seeds, is_mega, is_reusable, device, and dtype choices.

Start here:

• Use references/api-reference.md for verified MinDalle signatures, output types, shapes, and parameter semantics.
• Use references/generation-workflows.md for reusable Python recipes and safe dry-run/run command patterns.
• Use references/troubleshooting.md for generation-specific failures and recovery steps.
• Use scripts/generation_request_template.py as a safe standalone request template. It defaults to dry run and only constructs/downloads models when --run is supplied.

Operating rules:

1. Prefer keyword arguments for all generation calls. In particular, generate_images() and generate_images_stream() need grid_size in kwargs because the implementation reshapes output batches from kwargs["grid_size"].
2. Choose output API by desired form: generate_image()/generate_image_stream() for PIL grid images; generate_images()/generate_images_stream() for tensor batches of individual 256×256 images; generate_raw_image_stream() for raw grid tensors.
3. Treat MinDalle(...) construction as potentially expensive: tokenizer assets may be requested immediately, and full encoder/decoder/detokenizer weights load during construction when is_reusable=True. Route cache/download/storage and detailed dtype memory planning to ../model-assets-and-runtime/SKILL.md.
4. Keep this sub-skill scoped to the Python API. Route command-line image_from_text.py, Tkinter UI, Colab notebook UX, Replicate, Spaces, or public deployment interface tasks to ../deployment-and-interfaces/SKILL.md.
5. Do not ask future agents to inspect the original repository files for these API facts; use the distilled references here as the runtime operating context.