- Each run keeps its shape read from the prompt ComfyUI queued (ai_run_map.py): boxes by role with their settings, typed links, plumbing wired through, and what changed since the task's run before. The run step shows a one-line summary, the changes as chips and the boxes (top down, fitted to the column, each locating its node); show_run_map puts it on the stage. - By default the AI works in a tab of the task's own (ai_task_canvas.py, mcp_task_tab.js): the open workflow is copied before its first change, the tab is brought back (a click on ComfyUI's tab) before later changes, reads and runs, and the user's tab stays untouched. Per-task switch in the header, default in the Gates window; the AI is told once. - Output pictures can be handed to the task an AI is on (gallery card menu, the inspector's ✦), with the user's words: the AI gets them attached with what made them (ai_pictures.py). search_images(with_pictures) attaches the first six. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Architecture Topic Guide
Start with the repository-root ARCHITECTURE.md, then
open only the topic needed for the current task.
backend.md: Python routes, filesystem safety, persistence, scan state, model sidecars, and backend performance.frontend.md: extension bootstrap, UI ownership, localization, media lifecycle, panel state, and graph mutations.recipes.md: Workflow Recipes, packages, galleries, Parameter Notebooks, prompt roles, and recipe-to-model transitions.material-library.md: saved prompts and node values (material files), keeping an output image, and dragging prompts onto the canvas.recipe-model-lifecycle.md: authoritative model fields, Hash synchronization, local matching, partial append, and note privacy.model-resolution.md: model provenance, Model Check, hash injection, model scanning, and recovery policy.../decisions/README.md: concise records of product and architectural decisions that still explain current behavior.
These documents describe current contracts rather than implementation history.
For exact changes, use Git history. For user-visible releases, use
CHANGELOG.md. For recurring implementation traps, use
lessons.md.