FIX: typo causing text_embedding_3_large to fail (#460)

lib/embeddings/vector_representations/text_embedding_3_large.rb

@@ -48,7 +48,7 @@ module DiscourseAi
           response =
             DiscourseAi::Inference::OpenAiEmbeddings.perform!(
               text,
-              model: self.clas.name,
+              model: self.class.name,
               dimensions: dimensions,
             )
           response[:data].first[:embedding]

spec/lib/modules/embeddings/vector_representations/text_embedding_3_large_spec.rb

@@ -0,0 +1,22 @@
+# frozen_string_literal: true
+
+require_relative "vector_rep_shared_examples"
+
+RSpec.describe DiscourseAi::Embeddings::VectorRepresentations::TextEmbedding3Large do
+  subject(:vector_rep) { described_class.new(truncation) }
+
+  let(:truncation) { DiscourseAi::Embeddings::Strategies::Truncation.new }
+
+  def stub_vector_mapping(text, expected_embedding)
+    EmbeddingsGenerationStubs.openai_service(
+      described_class.name,
+      text,
+      expected_embedding,
+      extra_args: {
+        dimensions: 2000,
+      },
+    )
+  end
+
+  it_behaves_like "generates and store embedding using with vector representation"
+end

spec/lib/modules/embeddings/vector_representations/text_embedding_3_small_spec.rb

@@ -0,0 +1,15 @@
+# frozen_string_literal: true
+
+require_relative "vector_rep_shared_examples"
+
+RSpec.describe DiscourseAi::Embeddings::VectorRepresentations::TextEmbedding3Small do
+  subject(:vector_rep) { described_class.new(truncation) }
+
+  let(:truncation) { DiscourseAi::Embeddings::Strategies::Truncation.new }
+
+  def stub_vector_mapping(text, expected_embedding)
+    EmbeddingsGenerationStubs.openai_service(described_class.name, text, expected_embedding)
+  end
+
+  it_behaves_like "generates and store embedding using with vector representation"
+end

spec/support/embeddings_generation_stubs.rb

@@ -13,10 +13,10 @@ class EmbeddingsGenerationStubs
         .to_return(status: 200, body: JSON.dump(embedding))
     end
 
-    def openai_service(model, string, embedding)
+    def openai_service(model, string, embedding, extra_args: {})
       WebMock
         .stub_request(:post, "https://api.openai.com/v1/embeddings")
-        .with(body: JSON.dump({ model: model, input: string }))
+        .with(body: JSON.dump({ model: model, input: string }.merge(extra_args)))
         .to_return(status: 200, body: JSON.dump({ data: [{ embedding: embedding }] }))
     end
   end