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* <p>Ported from:
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* /Users/brian.sam-bodden/Code/redis/py/redis-vl-python/docs/user_guide/04_vectorizers.ipynb
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*
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- * <p>Uses same models and data as Python version: - Test sentences: "That is a happy dog", "That
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- * is a happy person", "Today is a sunny day" - OpenAI: text-embedding-ada-002 - HuggingFace:
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+ * <p>Uses same models and data as Python version: - Test sentences: "That is a happy dog", "That is
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+ * a happy person", "Today is a sunny day" - OpenAI: text-embedding-ada-002 - HuggingFace:
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* sentence-transformers/all-mpnet-base-v2 - Cohere: embed-english-v3.0 - VoyageAI: voyage-law-2
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*/
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@ Tag ("integration" )
@@ -51,10 +51,7 @@ public void testOpenAIVectorizer() {
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// Create a vectorizer using OpenAI's text-embedding-ada-002 model (same as Python)
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var openaiModel =
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- OpenAiEmbeddingModel .builder ()
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- .apiKey (apiKey )
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- .modelName ("text-embedding-ada-002" )
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- .build ();
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+ OpenAiEmbeddingModel .builder ().apiKey (apiKey ).modelName ("text-embedding-ada-002" ).build ();
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var oai = new LangChain4JVectorizer ("text-embedding-ada-002" , openaiModel );
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// Embed a single sentence
@@ -247,7 +244,8 @@ public void testDataTypeSelection() {
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// Test different data types (same as Python notebook)
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// Create vectorizer with default FLOAT32
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- var vectorizer32 = new SentenceTransformersVectorizer ("sentence-transformers/all-mpnet-base-v2" );
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+ var vectorizer32 =
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+ new SentenceTransformersVectorizer ("sentence-transformers/all-mpnet-base-v2" );
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float [] float32Embed = vectorizer32 .embed ("test sentence" );
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assertThat (float32Embed .length ).isEqualTo (768 );
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