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AGENTS.md
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AGENTS.md
@ -19,6 +19,9 @@
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better to remove a broken feature path than keep a complicated partial fix.
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- Preserve existing APIs, node names, model-loading behavior, file layout, and
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workflow compatibility unless the change is explicitly about replacing them.
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- When compatibility is explicitly out of scope, remove compatibility-only
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aliases, duplicate nodes, legacy entry points, and preset wrappers instead of
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retaining parallel ways to perform the same operation.
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- Code must look hand-written for this repository. Changes that read like
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generic AI-generated code will be rejected automatically: unnecessary helper
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layers, vague names, boilerplate comments, defensive branches without a real
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@ -96,6 +99,13 @@
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unless they are read by current code and change current behavior. Remove
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pass-through or stored-but-unused values instead of preserving upstream or
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deprecated API baggage.
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- Do not add a model-specific option to a shared helper when only one caller
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needs it. Keep one-off behavior at the model integration boundary, or extend
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the shared helper only when the option is a coherent reusable capability.
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- Implementations of shared model interfaces should accept the standard caller
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contract without model-specific rejection branches for optional capabilities
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they do not consume. Let supported behavior be determined by implementation
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paths that actually use those inputs.
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- If an implementation needs auxiliary values for its own workflow, expose them
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through a private helper or a clearly named implementation-specific method
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instead of overloading the public method's return contract.
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@ -154,6 +164,10 @@
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`comfy-kitchen` helpers where they already solve the problem.
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- Use optimized comfy-kitchen ops in places where they improve performance
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without changing the expected dtype, device, memory, or interface behavior.
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- Prefer ComfyUI's shared optimized kernels and backend dispatchers over
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handwritten implementations of the same operation. Remove duplicate local
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kernels and adapt inputs to the shared operation's documented layout while
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preserving the model's original math and output contract.
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- All models should use the optimized attention function selected by ComfyUI.
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Treat optimized backend functions, dispatch helpers, and capability-selected
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callables as opaque. Higher-level code must not inspect function identity,
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@ -176,6 +190,12 @@
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- Model detection code that inspects linear weight shapes should only use the
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first dimension. The second dimension may be half the original size for
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NVFP4 or other 4-bit quantized models.
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- A model-detection signature must guard every state-dict key it dereferences.
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Do not partially match a format and then raise an incidental `KeyError` while
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extracting its configuration.
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- Order model-detection checks from established or more-specific signatures to
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newer or broader signatures. Put a broad new detector near the generic
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fallback when giving it higher precedence could steal another model family.
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- Avoid adding `einops` usage in core inference code. Use native torch tensor
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ops such as `reshape`, `view`, `permute`, `transpose`, `flatten`, `unflatten`,
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`unsqueeze`, and `squeeze` instead.
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@ -192,11 +212,23 @@
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methods for scalar or structural calculations.
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- Avoid unnecessary casts and transfers. Preserve the intended compute dtype,
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storage dtype, bias dtype, and original tensor shape metadata.
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- Do not cast the result of an optimized backend operation back to its input
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dtype unless that backend's documented result contract requires normalization.
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In particular, trust the selected optimized-attention implementation to honor
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its dtype contract.
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- Keep model-native latent layout handling inside the model or latent-format
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owner, not in helper nodes. Do not collapse, expand, pack, or unpack latent
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dimensions in nodes or other caller-side adapters just to satisfy a model
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forward; the model path should consume and return the native latent shape for
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that model family.
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- DiT models should accept latent dimensions that are not exact patch-size
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multiples. Use `comfy.ldm.common_dit.pad_to_patch_size` on every patchified
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target or reference input, then crop only the target output back to its
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original dimensions.
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- Avoid defensive shape and configuration checks that merely replace the clear
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failure from the tensor operation immediately below them. Add explicit
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validation only when it provides materially better context at a real boundary
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or prevents silent incorrect output.
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- Assume inputs to the main model forward are already in the compute dtype by
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default, except integer inputs such as some model timestep tensors. Do not add
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defensive or convenience casts in model code; it is better for invalid dtype
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@ -260,6 +292,15 @@
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- Model implementations should add the minimal number of ComfyUI nodes required
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to run the model. Reuse existing nodes as much as possible; adapting the model
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to work with existing nodes is strongly preferred over creating new nodes.
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- Use `io.Autogrow` for a variable number of repeated inputs instead of a fixed
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series of numbered optional sockets. Set its minimum to zero when the model
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has a valid no-item path, and cap it only when the model has a real limit.
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- Mark inputs optional when execution has a valid path that does not read them.
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If one optional input is needed only to process another optional input, do not
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force users on the path that supplies neither to connect it.
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- Conditioning nodes should normally output conditioning only. Do not expose
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input or intermediate images as convenience outputs for downstream sizing or
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routing; use the existing image path or a dedicated image operation instead.
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- Nodes should output only values they own. Do not add pass-through outputs for
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workflow convenience unless the node is explicitly an output node. Existing
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models, latents, conditioning, or other inputs should flow directly to the
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