fix: Getting embeddings using text-embedding-005.

Author: lee1premium-2024

ai-platform/snippets/embedding-model-tuning.js

@@ -23,7 +23,7 @@ async function main(
   project,
   outputDir,
   pipelineJobDisplayName = 'embedding-customization-pipeline-sample',
-  baseModelVersionId = 'text-embedding-004',
+  baseModelVersionId = 'text-embedding-005',
   taskType = 'DEFAULT',
   corpusPath = 'gs://cloud-samples-data/ai-platform/embedding/goog-10k-2024/r11/corpus.jsonl',
   queriesPath = 'gs://cloud-samples-data/ai-platform/embedding/goog-10k-2024/r11/queries.jsonl',
@@ -62,7 +62,7 @@ async function main(
   };
   const pipelineJob = {
     templateUri:
-      'https://us-kfp.pkg.dev/ml-pipeline/llm-text-embedding/tune-text-embedding-model/v1.1.3',
+      'https://us-kfp.pkg.dev/ml-pipeline/llm-text-embedding/tune-text-embedding-model/v1.1.4',
     displayName: pipelineJobDisplayName,
     runtimeConfig,
   };

ai-platform/snippets/predict-text-embeddings-preview.js

@@ -21,7 +21,7 @@ async function main() {
 
   // TODO(developer): Update the following for your own use case.
   const project = 'long-door-651';
-  const model = 'text-embedding-preview-0815';
+  const model = 'text-embedding-005';
   const location = 'us-central1';
   // Calculate the embedding for code blocks. Using 'RETRIEVAL_DOCUMENT' for corpus.
   // Specify the task type as 'CODE_RETRIEVAL_QUERY' for query, e.g. 'Retrieve a function that adds two numbers'.

ai-platform/snippets/predict-text-embeddings.js

@@ -20,7 +20,7 @@
 // [START generativeaionvertexai_sdk_embedding]
 async function main(
   project,
-  model = 'text-embedding-004',
+  model = 'text-embedding-005',
   texts = 'banana bread?;banana muffins?',
   task = 'QUESTION_ANSWERING',
   dimensionality = 0,