Add algorithm field; clean up dropdown displays;

Signed-off-by: Tyler Ohlsen <ohltyler@amazon.com>

Author: ohltyler

common/constants.ts

@@ -4,6 +4,7 @@
  */
 
 import {
+  MODEL_ALGORITHM,
   PRETRAINED_MODEL_FORMAT,
   PretrainedSentenceTransformer,
   WORKFLOW_STATE,
@@ -68,6 +69,7 @@ export const ROBERTA_SENTENCE_TRANSFORMER = {
   shortenedName: 'all-distilroberta-v1',
   description: 'A sentence transformer from Hugging Face',
   format: PRETRAINED_MODEL_FORMAT.TORCH_SCRIPT,
+  algorithm: MODEL_ALGORITHM.TEXT_EMBEDDING,
   version: '1.0.1',
   vectorDimensions: 768,
 } as PretrainedSentenceTransformer;
@@ -77,6 +79,7 @@ export const MPNET_SENTENCE_TRANSFORMER = {
   shortenedName: 'all-mpnet-base-v2',
   description: 'A sentence transformer from Hugging Face',
   format: PRETRAINED_MODEL_FORMAT.TORCH_SCRIPT,
+  algorithm: MODEL_ALGORITHM.TEXT_EMBEDDING,
   version: '1.0.1',
   vectorDimensions: 768,
 } as PretrainedSentenceTransformer;
@@ -86,6 +89,7 @@ export const BERT_SENTENCE_TRANSFORMER = {
   shortenedName: 'msmarco-distilbert-base-tas-b',
   description: 'A sentence transformer from Hugging Face',
   format: PRETRAINED_MODEL_FORMAT.TORCH_SCRIPT,
+  algorithm: MODEL_ALGORITHM.TEXT_EMBEDDING,
   version: '1.0.2',
   vectorDimensions: 768,
 } as PretrainedSentenceTransformer;

common/interfaces.ts

@@ -152,6 +152,28 @@ export enum MODEL_STATE {
   DEPLOY_FAILED = 'Deploy failed',
 }
 
+// Based off of https://github.com/opensearch-project/ml-commons/blob/main/common/src/main/java/org/opensearch/ml/common/FunctionName.java
+export enum MODEL_ALGORITHM {
+  LINEAR_REGRESSION = 'Linear regression',
+  KMEANS = 'K-means',
+  AD_LIBSVM = 'AD LIBSVM',
+  SAMPLE_ALGO = 'Sample algorithm',
+  LOCAL_SAMPLE_CALCULATOR = 'Local sample calculator',
+  FIT_RCF = 'Fit RCF',
+  BATCH_RCF = 'Batch RCF',
+  ANOMALY_LOCALIZATION = 'Anomaly localization',
+  RCF_SUMMARIZE = 'RCF summarize',
+  LOGISTIC_REGRESSION = 'Logistic regression',
+  TEXT_EMBEDDING = 'Text embedding',
+  METRICS_CORRELATION = 'Metrics correlation',
+  REMOTE = 'Remote',
+  SPARSE_ENCODING = 'Sparse encoding',
+  SPARSE_TOKENIZE = 'Sparse tokenize',
+  TEXT_SIMILARITY = 'Text similarity',
+  QUESTION_ANSWERING = 'Question answering',
+  AGENT = 'Agent',
+}
+
 export enum MODEL_CATEGORY {
   DEPLOYED = 'Deployed',
   PRETRAINED = 'Pretrained',
@@ -166,6 +188,7 @@ export type PretrainedModel = {
   shortenedName: string;
   description: string;
   format: PRETRAINED_MODEL_FORMAT;
+  algorithm: MODEL_ALGORITHM;
   version: string;
 };
 
@@ -181,7 +204,7 @@ export type ModelConfig = {
 export type Model = {
   id: string;
   name: string;
-  algorithm: string;
+  algorithm: MODEL_ALGORITHM;
   state: MODEL_STATE;
   modelConfig?: ModelConfig;
 };
@@ -193,6 +216,7 @@ export type ModelDict = {
 export type ModelFormValue = {
   id: string;
   category?: MODEL_CATEGORY;
+  algorithm?: MODEL_ALGORITHM;
 };
 
 /**

public/component_types/transformer/text_embedding_transformer.ts

@@ -19,7 +19,7 @@ export class TextEmbeddingTransformer extends MLTransformer {
     this.inputs = [];
     this.createFields = [
       {
-        label: 'Model',
+        label: 'Text Embedding Model',
         id: 'model',
         type: 'model',
         helpText: 'A text embedding model for embedding text.',

public/pages/workflow_detail/component_details/input_fields/model_field.tsx

@@ -84,6 +84,7 @@ export function ModelField(props: ModelFieldProps) {
             id: modelId,
             name: models[modelId].name,
             category: MODEL_CATEGORY.DEPLOYED,
+            algorithm: models[modelId].algorithm,
           } as ModelItem);
         }
       });
@@ -98,16 +99,19 @@ export function ModelField(props: ModelFieldProps) {
         id: ROBERTA_SENTENCE_TRANSFORMER.name,
         name: ROBERTA_SENTENCE_TRANSFORMER.shortenedName,
         category: MODEL_CATEGORY.PRETRAINED,
+        algorithm: ROBERTA_SENTENCE_TRANSFORMER.algorithm,
       },
       {
         id: MPNET_SENTENCE_TRANSFORMER.name,
         name: MPNET_SENTENCE_TRANSFORMER.shortenedName,
         category: MODEL_CATEGORY.PRETRAINED,
+        algorithm: MPNET_SENTENCE_TRANSFORMER.algorithm,
       },
       {
         id: BERT_SENTENCE_TRANSFORMER.name,
         name: BERT_SENTENCE_TRANSFORMER.shortenedName,
         category: MODEL_CATEGORY.PRETRAINED,
+        algorithm: BERT_SENTENCE_TRANSFORMER.algorithm,
       },
     ];
     setPretrainedModels(modelItems);
@@ -170,10 +174,18 @@ export function ModelField(props: ModelFieldProps) {
                       value: option.id,
                       inputDisplay: (
                         <>
-                          <EuiText size="xs">{option.name}</EuiText>
+                          <EuiText size="s">{option.name}</EuiText>
+                        </>
+                      ),
+                      dropdownDisplay: (
+                        <>
+                          <EuiText size="s">{option.name}</EuiText>
                           <EuiText size="xs" color="subdued">
                             {option.category}
                           </EuiText>
+                          <EuiText size="xs" color="subdued">
+                            {option.algorithm}
+                          </EuiText>
                         </>
                       ),
                       disabled: false,

public/utils/utils.ts

@@ -102,6 +102,7 @@ export function getInitialValue(fieldType: FieldType): FieldValue {
       return {
         id: '',
         category: undefined,
+        algorithm: undefined,
       } as ModelFormValue;
     }
     case 'json': {

server/routes/helpers.ts

@@ -6,6 +6,7 @@
 import {
   DEFAULT_NEW_WORKFLOW_STATE_TYPE,
   INDEX_NOT_FOUND_EXCEPTION,
+  MODEL_ALGORITHM,
   MODEL_STATE,
   Model,
   ModelDict,
@@ -94,7 +95,8 @@ export function getModelsFromResponses(modelHits: any[]): ModelDict {
       modelDict[modelId] = {
         id: modelId,
         name: modelHit._source?.name,
-        algorithm: modelHit._source?.algorithm,
+        // @ts-ignore
+        algorithm: MODEL_ALGORITHM[modelHit._source?.algorithm],
         // @ts-ignore
         state: MODEL_STATE[modelHit._source?.model_state],
         modelConfig: {