Update model to be a single object on kitfile

Updates the build and export to adjust to single object.

pkg/artifact/kit-file.go

@@ -10,14 +10,14 @@ import (
 
 type (
 	KitFile struct {
-		ManifestVersion string         `json:"manifestVersion"`
-		Package         Package        `json:"package,omitempty"`
-		Code            []Code         `json:"code,omitempty"`
-		DataSets        []DataSet      `json:"datasets,omitempty"`
-		Models          []TrainedModel `json:"models,omitempty"`
+		ManifestVersion string       `json:"manifestVersion"`
+		Kit             ModelKit     `json:"package,omitempty"`
+		Code            []Code       `json:"code,omitempty"`
+		DataSets        []DataSet    `json:"datasets,omitempty"`
+		Model           TrainedModel `json:"model,omitempty"`
 	}
 
-	Package struct {
+	ModelKit struct {
 		Name        string   `json:"name,omitempty"`
 		Version     string   `json:"version,omitempty"`
 		Description string   `json:"description,omitempty"`

pkg/artifact/kit-file.md

@@ -1,18 +1,18 @@
 # KitOps AI/ML Packaging Manifest Format Reference
 
-The Kit manifest for AI/ML is a YAML file designed to encapsulate all the necessary information about the package, including code, datasets, models, and their metadata. This reference documentation outlines the structure and specifications of the manifest format.
+The Kitfile manifest for AI/ML is a YAML file designed to encapsulate all the necessary information about the package, including code, datasets, model, and their metadata. This reference documentation outlines the structure and specifications of the manifest format.
 
 ## Overview
 
-The manifest is structured into several key sections: `version`, `package`,`code`, `datasets` and `models`. Each section serves a specific purpose in describing the AI/ML package components and requirements.
+The manifest is structured into several key sections: `version`, `package`,`code`, `datasets` and `model`. Each section serves a specific purpose in describing the AI/ML package components and requirements.
 
 ### `ManifestVersion`
 
 - **Description**: Specifies the manifest format version.
 - **Type**: String
 - **Example**: `1.0`
 
-### `package`
+### `modelkit`
 
 This section provides general information about the AI/ML project.
 
@@ -56,7 +56,7 @@ This section provides general information about the AI/ML project.
   - `license`: SPDX license identifier for the dataset.
   - `preprocessing`: Reference to preprocessing steps.
 
-#### `models`
+#### `model`
 
 - **Description**: Details of the trained models included in the package.
 - **Type**: Object Array

pkg/cmd/build/build.go

@@ -128,18 +128,17 @@ func (options *BuildOptions) RunBuild() error {
 		model.Layers = append(model.Layers, *layer)
 	}
 
-	// 4. package the TrainedModels
-	for _, trainedModel := range kitfile.Models {
-		modelPath, err := filesystem.VerifySubpath(options.ContextDir, trainedModel.Path)
-		if err != nil {
-			return err
-		}
-		layer := &artifact.ModelLayer{
-			BaseDir:   modelPath,
-			MediaType: constants.ModelLayerMediaType,
-		}
-		model.Layers = append(model.Layers, *layer)
+	// 4. package the TrainedModel
+
+	modelPath, err := filesystem.VerifySubpath(options.ContextDir, kitfile.Model.Path)
+	if err != nil {
+		return err
+	}
+	layer := &artifact.ModelLayer{
+		BaseDir:   modelPath,
+		MediaType: constants.ModelLayerMediaType,
 	}
+	model.Layers = append(model.Layers, *layer)
 
 	modelStorePath := options.storageHome
 	repo := ""

pkg/cmd/build/kit-file.md

@@ -0,0 +1,141 @@
+# Kitfile AI/ML Packaging Manifest Format Reference
+
+The Kitfile manifest for AI/ML is a YAML file designed to encapsulate all the necessary information about the package, including code, datasets, model, and their metadata. This reference documentation outlines the structure and specifications of the manifest format.
+
+## Overview
+
+The manifest is structured into several key sections: `version`, `package`,`code`, `datasets` and `model`. Each section serves a specific purpose in describing the AI/ML package components and requirements.
+
+### `ManifestVersion`
+
+- **Description**: Specifies the manifest format version.
+- **Type**: String
+- **Example**: `1.0`
+
+### `modelkit`
+
+This section provides general information about the AI/ML project.
+
+#### `name`
+
+- **Description**: The name of the AI/ML project.
+- **Type**: String
+
+#### `version`
+
+- **Description**: The current version of the project.
+- **Type**: String
+- **Example**: `1.2.3`
+
+#### `description`
+
+- **Description**: A brief overview of the project's purpose and capabilities.
+- **Type**: String
+
+#### `authors`
+
+- **Description**: A list of individuals or entities that have contributed to the project.
+- **Type**: Array of Strings
+
+
+#### `code`
+
+- **Description**: Information about the source code.
+- **Type**: Object Array
+  - `path`: Location of the source code files or directory relative to the context
+  - `description`: Description of what the code does.
+  - `license`: SPDX license identifier for the code.
+
+#### `datasets`
+
+- **Description**: Information about the datasets used.
+- **Type**: Object Array
+  - `name`: Name of the dataset.
+  - `path`: Location of the dataset file or directory relative to the context.
+  - `description`: Overview of the dataset.
+  - `license`: SPDX license identifier for the dataset.
+  - `preprocessing`: Reference to preprocessing steps.
+
+#### `model`
+
+- **Description**: Details of the trained models included in the package.
+- **Type**: Object
+  - `name`: Name of the model 
+  - `path`: Location of the model file or directory relative to the context
+  - `framework`: AI/ML framework
+  - `version`: Version of the model
+  - `description`: Overview of the model
+  - `license`: SPDX license identifier for the dataset. 
+  - `training`:
+    - `dataset`: Name of the dataset
+    - `parameters`: name value pairs
+  - `validation`:
+    - `dataset`: Name of the dataset
+    - `metrics`: name value pairs
+
+
+## Example
+
+```yaml
+manifestVersion: 1.0
+package:
+  name: AIProjectName
+  version: 1.2.3
+  description: >-
+    A brief description of the AI/ML project.
+  authors: [Author Name, Contributor Name]
+code:
+  - path: src/
+    description: Source code for the AI models.
+    license: Apache-2.0
+datasets:
+  - name: DatasetName
+    path: data/dataset.csv
+    description: Description of the dataset.
+    license: CC-BY-4.0
+    preprocessing: Preprocessing steps.
+models:
+  - name: ModelName
+    path: models/model.h5
+    framework: TensorFlow
+    version: 1.0
+    description: Model description.
+    license: Apache-2.0
+    training:
+      dataset: DatasetName
+      parameters:
+        learning_rate: 0.001
+        epochs: 100
+        batch_size: 32
+    validation:
+      - dataset: DatasetName
+        metrics:
+          accuracy: 0.95
+          f1_score: 0.94
+```
+
+
+## Future Considerations 
+
+This section is for collecting future ideas.
+
+### `dependencies`
+
+**This is a possible future section that may be used for creating BOM.**
+
+- **Description**: Lists the project's external dependencies.
+- **Type**: Object Array
+  - `name`: Name of the dependency.
+  - `version`: Version of the dependency.
+  - `license`: SPDX license identifier for the dependency.
+
+##### Example for dependencies
+```yaml
+  dependencies:
+  - name: numpy
+    version: 1.19.2
+    license: BSD-3-Clause
+  - name: pandas
+    version: 1.1.3
+    license: BSD-3-Clause
+```

pkg/cmd/export/export.go

@@ -39,18 +39,17 @@ func ExportModel(ctx context.Context, store oras.Target, ref *registry.Reference
 
 	// Since there might be multiple models, etc. we need to synchronously iterate
 	// through the config's relevant field to get the correct path for exporting
-	var modelIdx, codeIdx, datasetIdx int
+	var codeIdx, datasetIdx int
 	for _, layerDesc := range manifest.Layers {
 		layerDir := ""
 		switch layerDesc.MediaType {
 		case constants.ModelLayerMediaType:
 			if !options.exportConf.ExportModels {
 				continue
 			}
-			modelEntry := config.Models[modelIdx]
+			modelEntry := config.Model
 			layerDir = filepath.Join(options.exportDir, modelEntry.Path)
 			fmt.Printf("Exporting model %s to %s\n", modelEntry.Name, layerDir)
-			modelIdx += 1
 
 		case constants.CodeLayerMediaType:
 			if !options.exportConf.ExportCode {

pkg/cmd/list/list.go

@@ -110,8 +110,14 @@ func getManifestInfoLine(repo string, desc ocispec.Descriptor, manifest *ocispec
 		size += layer.Size
 	}
 	sizeStr := formatBytes(size)
+	var author string
+	if len(config.Kit.Authors) > 0 {
+		author = config.Kit.Authors[0]
+	} else {
+		author = "<none>"
+	}
 
-	info := fmt.Sprintf(listTableFmt, repo, ref, config.Package.Authors[0], config.Package.Name, sizeStr, desc.Digest)
+	info := fmt.Sprintf(listTableFmt, repo, ref, author, config.Kit.Name, sizeStr, desc.Digest)
 	return info
 }
 

pkg/cmd/list/list_test.go

@@ -224,7 +224,7 @@ func Manifest(configDigest string, layerDigests ...string) ocispec.Manifest {
 
 func Config(maintainer, name string) artifact.KitFile {
 	config := artifact.KitFile{
-		Package: artifact.Package{Authors: []string{maintainer}, Name: name},
+		Kit: artifact.ModelKit{Authors: []string{maintainer}, Name: name},
 	}
 
 	return config