tidy(ui): tidy model identifier logic

- Move some files around
- Use util to extract key and base from model config

invokeai/frontend/web/src/features/metadata/util/modelFetchingHelpers.ts

@@ -0,0 +1,131 @@
+import { getStore } from 'app/store/nanostores/store';
+import type { ModelIdentifierWithBase } from 'features/nodes/types/common';
+import { isModelIdentifier, isModelIdentifierV2 } from 'features/nodes/types/common';
+import { modelsApi } from 'services/api/endpoints/models';
+import type { AnyModelConfig, BaseModelType, ModelType } from 'services/api/types';
+
+
+
+/**
+ * Raised when a model config is unable to be fetched.
+ */
+export class ModelConfigNotFoundError extends Error {
+  /**
+   * Create ModelConfigNotFoundError
+   * @param {String} message
+   */
+  constructor(message: string) {
+    super(message);
+    this.name = this.constructor.name;
+  }
+}
+
+/**
+ * Raised when a fetched model config is of an unexpected type.
+ */
+export class InvalidModelConfigError extends Error {
+  /**
+   * Create InvalidModelConfigError
+   * @param {String} message
+   */
+  constructor(message: string) {
+    super(message);
+    this.name = this.constructor.name;
+  }
+}
+
+/**
+ * Fetches the model config for a given model key.
+ * @param key The model key.
+ * @returns A promise that resolves to the model config.
+ * @throws {ModelConfigNotFoundError} If the model config is unable to be fetched.
+ */
+export const fetchModelConfig = async (key: string): Promise<AnyModelConfig> => {
+  const { dispatch } = getStore();
+  try {
+    const req = dispatch(modelsApi.endpoints.getModelConfig.initiate(key));
+    req.unsubscribe();
+    return await req.unwrap();
+  } catch {
+    throw new ModelConfigNotFoundError(`Unable to retrieve model config for key ${key}`);
+  }
+};
+
+/**
+ * Fetches the model config for a given model name, base model, and model type. This provides backwards compatibility
+ * for MM1 model identifiers.
+ * @param name The model name.
+ * @param base The base model.
+ * @param type The model type.
+ * @returns A promise that resolves to the model config.
+ * @throws {ModelConfigNotFoundError} If the model config is unable to be fetched.
+ */
+export const fetchModelConfigByAttrs = async (
+  name: string,
+  base: BaseModelType,
+  type: ModelType
+): Promise<AnyModelConfig> => {
+  const { dispatch } = getStore();
+  try {
+    const req = dispatch(modelsApi.endpoints.getModelConfigByAttrs.initiate({ name, base, type }));
+    req.unsubscribe();
+    return await req.unwrap();
+  } catch {
+    throw new ModelConfigNotFoundError(`Unable to retrieve model config for name/base/type ${name}/${base}/${type}`);
+  }
+};
+
+/**
+ * Fetches the model config for a given model key and type, and ensures that the model config is of a specific type.
+ * @param key The model key.
+ * @param typeGuard A type guard function that checks if the model config is of the expected type.
+ * @returns A promise that resolves to the model config. The model config is guaranteed to be of the expected type.
+ * @throws {InvalidModelConfigError} If the model config is unable to be fetched or is of an unexpected type.
+ */
+export const fetchModelConfigWithTypeGuard = async <T extends AnyModelConfig>(
+  key: string,
+  typeGuard: (config: AnyModelConfig) => config is T
+) => {
+  const modelConfig = await fetchModelConfig(key);
+  if (!typeGuard(modelConfig)) {
+    throw new InvalidModelConfigError(`Invalid model type for key ${key}: ${modelConfig.type}`);
+  }
+  return modelConfig;
+};
+
+/**
+ * Raises an error if the source base model is incompatible with the target base model.
+ * @param sourceBase The source base model.
+ * @param targetBase The target base model.
+ * @param message An optional custom message to include in the error.
+ * @throws {InvalidModelConfigError} If the source base model is incompatible with the target base model.
+ */
+export const raiseIfBaseIncompatible = (sourceBase: BaseModelType, targetBase?: BaseModelType, message?: string) => {
+  if (targetBase && sourceBase !== targetBase) {
+    throw new InvalidModelConfigError(message || `Incompatible base models: ${sourceBase} and ${targetBase}`);
+  }
+};
+
+/**
+ * Fetches the model key from a model identifier. This includes fetching the key for MM1 format model identifiers.
+ * @param modelIdentifier The model identifier. The MM2 format `{key: string}` simply extracts the key. The MM1 format
+ * `{model_name: string, base_model: BaseModelType}` must do a network request to fetch the key.
+ * @param type The type of model to fetch. This is used to fetch the key for MM1 format model identifiers.
+ * @param message An optional custom message to include in the error if the model identifier is invalid.
+ * @returns A promise that resolves to the model key.
+ * @throws {InvalidModelConfigError} If the model identifier is invalid.
+ */
+export const getModelKey = async (modelIdentifier: unknown, type: ModelType, message?: string): Promise<string> => {
+  if (isModelIdentifier(modelIdentifier)) {
+    return modelIdentifier.key;
+  }
+  if (isModelIdentifierV2(modelIdentifier)) {
+    return (await fetchModelConfigByAttrs(modelIdentifier.model_name, modelIdentifier.base_model, type)).key;
+  }
+  throw new InvalidModelConfigError(message || `Invalid model identifier: ${modelIdentifier}`);
+};
+
+export const getModelKeyAndBase = (modelConfig: AnyModelConfig): ModelIdentifierWithBase => ({
+  key: modelConfig.key,
+  base: modelConfig.base,
+});

invokeai/frontend/web/src/features/metadata/util/parsers.ts

@@ -9,6 +9,11 @@ import type { LoRA } from 'features/lora/store/loraSlice';
 import { defaultLoRAConfig } from 'features/lora/store/loraSlice';
 import { MetadataParseError } from 'features/metadata/exceptions';
 import type { MetadataParseFunc } from 'features/metadata/types';
+import {
+  fetchModelConfigWithTypeGuard,
+  getModelKey,
+  getModelKeyAndBase,
+} from 'features/metadata/util/modelFetchingHelpers';
 import {
   zControlField,
   zIPAdapterField,
@@ -54,11 +59,6 @@ import {
   isParameterStrength,
   isParameterWidth,
 } from 'features/parameters/types/parameterSchemas';
-import {
-  fetchModelConfigWithTypeGuard,
-  getModelKey,
-  getModelKeyAndBase,
-} from 'features/parameters/util/modelFetchingHelpers';
 import { get, isArray, isString } from 'lodash-es';
 import type { NonRefinerMainModelConfig, RefinerMainModelConfig, VAEModelConfig } from 'services/api/types';
 import {

invokeai/frontend/web/src/features/metadata/util/validators.ts

@@ -2,7 +2,7 @@ import { getStore } from 'app/store/nanostores/store';
 import type { ControlNetConfig, IPAdapterConfig, T2IAdapterConfig } from 'features/controlAdapters/store/types';
 import type { LoRA } from 'features/lora/store/loraSlice';
 import type { MetadataValidateFunc } from 'features/metadata/types';
-import { InvalidModelConfigError } from 'features/parameters/util/modelFetchingHelpers';
+import { InvalidModelConfigError } from 'features/metadata/util/modelFetchingHelpers';
 import type { BaseModelType, RefinerMainModelConfig, VAEModelConfig } from 'services/api/types';
 
 /**