---

name: infinite-you description: "Routes InfiniteYou-FLUX identity-preserving photo recrafting tasks across self-contained local inference, model/demo setup, and pipeline-internal debugging." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

InfiniteYou Repo Skill

Use this skill when a task is about InfiniteYou / InfU / InfiniteYou-FLUX: identity-preserving image generation from a face image, FLUX.1-dev model setup, local Gradio operation, optional LoRA use, CUDA memory reduction, or debugging the custom InfuseNet pipeline.

Start here

1. Read references/repo-provenance.md when checking staleness against a current checkout.
2. Read references/bundled-runtime.md when you need to know what implementation code is bundled with this skill.
3. Read references/installation-and-models.md before installing dependencies, resolving model paths, or running generation.
4. Run scripts/check_infinite_you_environment.py for a safe bundled-runtime/import/CUDA/model-layout preflight that does not download models or run generation.
5. Use the route map below to enter the most specific sub-skill.
6. If the task involves identity images, public demos, model downloads, or generated outputs, check references/safety-and-licenses.md.

Route map

User task	Read
Build or debug a local generation command from identity image, prompt, optional control image, LoRA, seed, model version, and memory flags.	sub-skills/local-inference/SKILL.md
Use the Python InfUFluxPipeline API, understand inference parameters, or validate CLI flag names.	sub-skills/local-inference/SKILL.md
Prepare or validate model directories, Hugging Face access, InsightFace support files, optional LoRAs, or FLUX base model paths.	sub-skills/demo-and-model-setup/SKILL.md
Launch, customize, or troubleshoot the self-contained Gradio demo, model switching, cache behavior, or server binding.	sub-skills/demo-and-model-setup/SKILL.md
Modify/debug face detection, ArcFace embeddings, Resampler projection, InfuseNet ControlNet integration, scheduler guidance, quantization, offload, or adapter internals.	sub-skills/pipeline-internals/SKILL.md
Diagnose cross-cutting dependency, CUDA, model-access, Gradio, LoRA, or policy failures before choosing a workflow route.	references/troubleshooting.md

Installation baseline

This generated skill bundles the InfiniteYou implementation modules under runtime/pipelines/, plus the dependency pins in runtime/requirements.txt. In a fresh runtime, create an isolated Python environment, install those pinned dependencies, and run the bundled checker from the skill directory.

python -m pip install -r runtime/requirements.txt
python scripts/check_infinite_you_environment.py --require-cuda

Full generation requires CUDA and external model files/access. The memory-reduction flags --cpu-offload and --quantize-8bit reduce peak CUDA memory but do not make generation CPU-only. By default, the bundled generation and demo entry points require local model directories; pass --allow-downloads only after explicit approval for network/model-license consequences.

Model and workflow facts

• InfiniteYou-FLUX v1.0 has two documented variants: aes_stage2 for default aesthetics/text alignment and sim_stage1 for higher identity similarity.
• The primary input is an identity image containing a detectable face; an optional control image supplies face keypoints.
• If multiple faces are present, the pipeline selects the largest detected face.
• Optional Realism and Anti-blur LoRAs are examples and are off by default.
• Full local execution needs the FLUX.1-dev base model plus InfiniteYou and InsightFace support files, or explicitly authorized download access.

Safe operating rules

• Use the bundled runtime and scripts by default; do not require the original checkout for normal generation, demo launch, or signature inspection.
• Run dry-run/preflight helpers before heavy model execution or demo launch.
• Do not download gated or non-commercial-use models, expose a demo server, or process identity images without confirming the user's authorization and policy constraints.
• If source code, dependency pins, model variants, CLI flags, or pipelines/ APIs changed since the provenance snapshot, refresh this skill and rebuild the bundled runtime before relying on it.

Useful bundled helpers

• scripts/check_infinite_you_environment.py — shared bundled-runtime import, CUDA, dependency, and optional model-layout checker.
• sub-skills/local-inference/scripts/run_infinite_you_flux.py — dry-run, preflight, or full local inference wrapper using the bundled runtime.
• sub-skills/demo-and-model-setup/scripts/check_model_layout.py — model-tree validator with no downloads.
• sub-skills/demo-and-model-setup/scripts/launch_infinite_you_gradio.py — self-contained Gradio demo launcher using the bundled runtime.
• sub-skills/pipeline-internals/scripts/inspect_pipeline_signatures.py — safe signature snapshot for API drift checks against the bundled runtime.