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v0.2.0 — AI Agent Scaffolding, Native MCP Img2Img & Colab L4 Acceleration

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@FireTable FireTable released this 06 Nov 05:36
· 10 commits to main since this release
v0.2.0
1e8df4e

🚀 Highlights in v0.2.0

🤖 AI Agent Scaffolding & Fork Adaptation (docs/AGENT_SCAFFOLDING.md)

  • Build Any ComfyUI Profile with AI: Added a dedicated agent runbook and copy-paste prompt in docs/AGENT_SCAFFOLDING.md so Claude Code, Cursor, Codex, or OpenClaw can automatically inspect Hugging Face models/workflows, configure model_aliases, wire ComfyUI App Mode (app.inputs / app.outputs), and validate profile.yaml via scripts/validate-profile.py.
  • Fork for Any Google Colab GPU Workload: Documented the 4 architectural seams (Profile/Plan, packages/colab/setup.py KIT_STAGE stdout protocol, Reverse Proxy probes, and MCP/CLI tools) to let coding agents adapt a fork of this zero-idle gateway for vLLM, Ollama, SD-WebUI Forge, Fooocus, Gradio, Whisper, or custom FastAPI GPU servers.

🎨 Native MCP gate_img2img & Multi-Profile Generation

  • New gate_img2img MCP Tool: Available in both local stdio (ckit mcp) and remote HTTP (POST /mcp). Automatically uploads local reference images or HTTP/HTTPS image URLs to ComfyUI (/upload/image) and runs image-to-image generation with configurable denoise (0.05–1.0).
  • Profile-Aware Generation: gate_txt2img, gate_img2img, and ckit generate now automatically detect the active profile (moss-image DeBand pipeline or sd-latest Official SD 3.5 Large fp8 pipeline).
  • CLI Upgrades (ckit):
    • ckit generate --prompt "..." --image <path_or_url> --denoise 0.75
    • ckit doctor [URL]: One-command diagnostics for local credentials, /_gate/healthz reachability, Cloudflare Access /mcp bypass rules, and Bearer token authentication.
    • ckit validate [path]: Validate custom or community profile directories directly from the CLI.

⚡ Colab L4 Hardware Acceleration Across All Built-in Profiles

  • Synced --highvram --reserve-vram 0.2 and Ada Lovelace TensorCore environment optimizations (PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True, CUDA_MODULE_LOADING=LAZY, TORCH_CUDNN_V8_API=1, TORCH_ALLOW_TF32_CUBLAS_OVERRIDE=1) across moss-image, sd-latest, and qwen-image.
  • Calibrated cold-start ETA and documentation benchmarks to the measured ~90 s (~1.5 min) end-to-end baseline.

🛡️ Security & Community

  • Added .dockerignore to strictly exclude local state, secrets, and custom profiles from Docker build contexts.
  • Added CONTRIBUTING.md and GitHub Issue templates for requesting or sharing community profiles.
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