MobileModelManager class
Main unified model manager that orchestrates all model operations
- Inheritance
-
- Object
- ModelFileManager
- MobileModelManager
Constructors
Properties
- activeEmbeddingModel → ModelSpec?
-
Gets the currently active embedding model specification
no setteroverride
- activeInferenceModel → ModelSpec?
-
Gets the currently active inference model specification
no setteroverride
- currentActiveModel → ModelSpec?
-
Gets the currently active model specification (backward compatibility)
no setter
- hashCode → int
-
The hash code for this object.
no setterinherited
- runtimeType → Type
-
A representation of the runtime type of the object.
no setterinherited
Methods
-
cleanupStorage(
) → Future< int> -
Clean up orphaned files
override
-
clearModelCache(
) → Future< void> -
Clears current model cache/state
override
-
deleteCurrentModel(
) → Future< void> -
Deletes current active model (legacy method without parameters)
override
-
deleteLoraWeights(
) → Future< void> -
Removes LoRA weights from current model
override
-
deleteModel(
ModelSpec spec) → Future< void> -
Deletes a model and all its files
override
-
downloadModel(
ModelSpec spec, {String? token}) → Future< void> -
Downloads a model without progress tracking
override
-
downloadModelWithProgress(
ModelSpec spec, {String? token}) → Stream< DownloadProgress> -
Downloads a model with progress tracking
override
-
ensureModelReady(
String filename, String url) → Future< void> -
Legacy API: Ensures a model is ready for use
override
-
ensureModelReadyFromSpec(
ModelSpec spec) → Future< void> -
Modern API: Ensures a model spec is ready for use
override
-
getInstalledModels(
ModelManagementType type) → Future< List< String> > -
Gets all installed models for a specific type
override
-
getModelFilePaths(
ModelSpec spec) → Future< Map< String, String> ?> -
Gets the file paths for an installed model
override
-
getOrphanedFiles(
) → Future< List< OrphanedFileInfo> > -
Get information about orphaned files
override
-
getStorageInfo(
) → Future< StorageStats> -
Get storage statistics with orphaned file information
override
-
getStorageStats(
) → Future< Map< String, int> > -
Gets storage statistics
override
-
initialize(
) → Future< void> - Initializes the unified model manager
-
installModelFromAsset(
String path, {String? loraPath}) → Future< void> -
Installs model from Flutter assets (debug only)
override
-
installModelFromAssetWithProgress(
String path, {String? loraPath}) → Stream< int> -
Installs model from Flutter assets with progress tracking (debug only)
override
-
isAnyModelInstalled(
ModelManagementType type) → Future< bool> -
Checks if ANY model of the given type is installed
override
-
isModelInstalled(
ModelSpec spec) → Future< bool> -
Checks if a model is installed and valid
override
-
noSuchMethod(
Invocation invocation) → dynamic -
Invoked when a nonexistent method or property is accessed.
inherited
-
performCleanup(
) → Future< void> -
Performs cleanup of orphaned files
override
-
setActiveModel(
ModelSpec spec) → void -
Sets the active model for subsequent operations
override
-
setLoraWeightsPath(
String path) → Future< void> -
Sets path to LoRA weights for current model
override
-
setModelPath(
String path, {String? loraPath}) → Future< void> -
Sets direct path to existing model files
override
-
toString(
) → String -
A string representation of this object.
inherited
-
validateModel(
ModelSpec spec) → Future< bool> -
Validates all files for a model specification
override
Operators
-
operator ==(
Object other) → bool -
The equality operator.
inherited
Static Methods
-
createBundledEmbeddingSpec(
{required String modelResourceName, required String tokenizerResourceName, ModelReplacePolicy replacePolicy = ModelReplacePolicy.keep}) → EmbeddingModelSpec - Creates a bundled embedding model specification (for production builds)
-
createBundledInferenceSpec(
{required String resourceName, String? loraResourceName, ModelReplacePolicy replacePolicy = ModelReplacePolicy.replace}) → InferenceModelSpec - Creates a bundled inference model specification (for production builds)
-
createEmbeddingSpec(
{required String name, required String modelUrl, required String tokenizerUrl, ModelReplacePolicy replacePolicy = ModelReplacePolicy.keep}) → EmbeddingModelSpec - Creates an embedding model specification from parameters
-
createInferenceSpec(
{required String name, required String modelUrl, String? loraUrl, ModelReplacePolicy replacePolicy = ModelReplacePolicy.replace}) → InferenceModelSpec - Creates an inference model specification from parameters