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Node authors may now create their own arbitrary/custom field types. Any pydantic model is supported. Two notes: 1. Your field type's class name must be unique. Suggest prefixing fields with something related to the node pack as a kind of namespace. 2. Custom field types function as connection-only fields. For example, if your custom field has string attributes, you will not get a text input for that attribute when you give a node a field with your custom type. This is the same behaviour as other complex fields that don't have custom UIs in the workflow editor - like, say, a string collection. feat(ui): fix tooltips for custom types We need to hold onto the original type of the field so they don't all just show up as "Unknown". fix(ui): fix ts error with custom fields feat(ui): custom field types connection validation In the initial commit, a custom field's original type was added to the *field templates* only as `originalType`. Custom fields' `type` property was `"Custom"`*. This allowed for type safety throughout the UI logic. *Actually, it was `"Unknown"`, but I changed it to custom for clarity. Connection validation logic, however, uses the *field instance* of the node/field. Like the templates, *field instances* with custom types have their `type` set to `"Custom"`, but they didn't have an `originalType` property. As a result, all custom fields could be connected to all other custom fields. To resolve this, we need to add `originalType` to the *field instances*, then switch the validation logic to use this instead of `type`. This ended up needing a bit of fanagling: - If we make `originalType` a required property on field instances, existing workflows will break during connection validation, because they won't have this property. We'd need a new layer of logic to migrate the workflows, adding the new `originalType` property. While this layer is probably needed anyways, typing `originalType` as optional is much simpler. Workflow migration logic can come layer. (Technically, we could remove all references to field types from the workflow files, and let the templates hold all this information. This feels like a significant change and I'm reluctant to do it now.) - Because `originalType` is optional, anywhere we care about the type of a field, we need to use it over `type`. So there are a number of `field.originalType ?? field.type` expressions. This is a bit of a gotcha, we'll need to remember this in the future. - We use `Array.prototype.includes()` often in the workflow editor, e.g. `COLLECTION_TYPES.includes(type)`. In these cases, the const array is of type `FieldType[]`, and `type` is is `FieldType`. Because we now support custom types, the arg `type` is now widened from `FieldType` to `string`. This causes a TS error. This behaviour is somewhat controversial (see https://github.com/microsoft/TypeScript/issues/14520). These expressions are now rewritten as `COLLECTION_TYPES.some((t) => t === type)` to satisfy TS. It's logically equivalent. fix(ui): typo feat(ui): add CustomCollection and CustomPolymorphic field types feat(ui): add validation for CustomCollection & CustomPolymorphic types - Update connection validation for custom types - Use simple string parsing to determine if a field is a collection or polymorphic type. - No longer need to keep a list of collection and polymorphic types. - Added runtime checks in `baseinvocation.py` to ensure no fields are named in such a way that it could mess up the new parsing chore(ui): remove errant console.log fix(ui): rename 'nodes.currentConnectionFieldType' -> 'nodes.connectionStartFieldType' This was confusingly named and kept tripping me up. Renamed to be consistent with the `reactflow` `ConnectionStartParams` type. fix(ui): fix ts error feat(nodes): add runtime check for custom field names "Custom", "CustomCollection" and "CustomPolymorphic" are reserved field names. chore(ui): add TODO for revising field type names wip refactor fieldtype structured wip refactor field types wip refactor types wip refactor types fix node layout refactor field types chore: mypy organisation organisation organisation fix(nodes): fix field orig_required, field_kind and input statuses feat(nodes): remove broken implementation of default_factory on InputField Use of this could break connection validation due to the difference in node schemas required fields and invoke() required args. Removed entirely for now. It wasn't ever actually used by the system, because all graphs always had values provided for fields where default_factory was used. Also, pydantic is smart enough to not reuse the same object when specifying a default value - it clones the object first. So, the common pattern of `default_factory=list` is extraneous. It can just be `default=[]`. fix(nodes): fix InputField name validation workflow validation validation chore: ruff feat(nodes): fix up baseinvocation comments fix(ui): improve typing & logic of buildFieldInputTemplate improved error handling in parseFieldType fix: back compat for deprecated default_factory and UIType feat(nodes): do not show node packs loaded log if none loaded chore(ui): typegen |
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| init.py | ||
| README.md | ||
Custom Nodes / Node Packs
Copy your node packs to this directory.
When nodes are added or changed, you must restart the app to see the changes.
Directory Structure
For a node pack to be loaded, it must be placed in a directory alongside this file. Here's an example structure:
.
├── __init__.py # Invoke-managed custom node loader
│
├── cool_node
│ ├── __init__.py # see example below
│ └── cool_node.py
│
└── my_node_pack
├── __init__.py # see example below
├── tasty_node.py
├── bodacious_node.py
├── utils.py
└── extra_nodes
└── fancy_node.py
Node Pack __init__.py
Each node pack must have an __init__.py file that imports its nodes.
The structure of each node or node pack is otherwise not important.
Here are examples, based on the example directory structure.
cool_node/__init__.py
from .cool_node import CoolInvocation
my_node_pack/__init__.py
from .tasty_node import TastyInvocation
from .bodacious_node import BodaciousInvocation
from .extra_nodes.fancy_node import FancyInvocation
Only nodes imported in the __init__.py file are loaded.