feat:Update OpenAPI spec for CreateOpenAIEncoderRequest and Encoder schemas

src/libs/Vectara/Generated/Vectara.Models.CreateOpenAIEncoderRequest.g.cs

@@ -16,29 +16,27 @@ public sealed partial class CreateOpenAIEncoderRequest
         public string? Type { get; set; }
 
         /// <summary>
-        /// The unique name of the encoder<br/>
-        /// Example: my-openai-encoder
+        /// A unique name for the encoder<br/>
+        /// Example: openai-text-encoder
         /// </summary>
-        /// <example>my-openai-encoder</example>
+        /// <example>openai-text-encoder</example>
         [global::System.Text.Json.Serialization.JsonPropertyName("name")]
         [global::System.Text.Json.Serialization.JsonRequired]
         public required string Name { get; set; }
 
         /// <summary>
         /// A description of what this encoder does<br/>
-        /// Example: OpenAI text embedding encoder
+        /// Example: description
         /// </summary>
-        /// <example>OpenAI text embedding encoder</example>
+        /// <example>description</example>
         [global::System.Text.Json.Serialization.JsonPropertyName("description")]
         [global::System.Text.Json.Serialization.JsonRequired]
         public required string Description { get; set; }
 
         /// <summary>
         /// The number of dimensions in the output embedding vector. If provided and the model supports truncation,<br/>
-        /// the response will be truncated to this number of dimensions.<br/>
-        /// Example: 1536
+        /// the response will be truncated to this number of dimensions.
         /// </summary>
-        /// <example>1536</example>
         [global::System.Text.Json.Serialization.JsonPropertyName("output_dimensions")]
         public int? OutputDimensions { get; set; }
 
@@ -81,17 +79,16 @@ public sealed partial class CreateOpenAIEncoderRequest
         /// Default Value: openai-compatible
         /// </param>
         /// <param name="name">
-        /// The unique name of the encoder<br/>
-        /// Example: my-openai-encoder
+        /// A unique name for the encoder<br/>
+        /// Example: openai-text-encoder
         /// </param>
         /// <param name="description">
         /// A description of what this encoder does<br/>
-        /// Example: OpenAI text embedding encoder
+        /// Example: description
         /// </param>
         /// <param name="outputDimensions">
         /// The number of dimensions in the output embedding vector. If provided and the model supports truncation,<br/>
-        /// the response will be truncated to this number of dimensions.<br/>
-        /// Example: 1536
+        /// the response will be truncated to this number of dimensions.
         /// </param>
         /// <param name="uri">
         /// The URI endpoint for the embedding API (can be OpenAI or any compatible embedding API endpoint)<br/>

src/libs/Vectara/Generated/Vectara.Models.Encoder.g.cs

@@ -18,28 +18,28 @@ public sealed partial class Encoder
 
         /// <summary>
         /// The encoder name, `boomerang-2023-q3`.<br/>
-        /// Example: boomerang-2023-q3
+        /// Example: openai-text-encoder
         /// </summary>
-        /// <example>boomerang-2023-q3</example>
+        /// <example>openai-text-encoder</example>
         [global::System.Text.Json.Serialization.JsonPropertyName("name")]
         public string? Name { get; set; }
 
         /// <summary>
         /// The encoder type<br/>
         /// Default Value: vectara<br/>
-        /// Example: vectara
+        /// Example: openai-compatible
         /// </summary>
-        /// <example>vectara</example>
+        /// <example>openai-compatible</example>
         [global::System.Text.Json.Serialization.JsonPropertyName("type")]
         public string? Type { get; set; }
 
         /// <summary>
         /// When this encoder is used to create an embedding, it shows the count of dimensions for the output embedding.<br/>
         /// A high dimensionality will consume more storage space, but it allows for an increase in the quality of<br/>
         /// the embedding.<br/>
-        /// Example: 768
+        /// Example: 1536
         /// </summary>
-        /// <example>768</example>
+        /// <example>1536</example>
         [global::System.Text.Json.Serialization.JsonPropertyName("output_dimensions")]
         public int? OutputDimensions { get; set; }
 
@@ -80,18 +80,18 @@ public sealed partial class Encoder
         /// </param>
         /// <param name="name">
         /// The encoder name, `boomerang-2023-q3`.<br/>
-        /// Example: boomerang-2023-q3
+        /// Example: openai-text-encoder
         /// </param>
         /// <param name="type">
         /// The encoder type<br/>
         /// Default Value: vectara<br/>
-        /// Example: vectara
+        /// Example: openai-compatible
         /// </param>
         /// <param name="outputDimensions">
         /// When this encoder is used to create an embedding, it shows the count of dimensions for the output embedding.<br/>
         /// A high dimensionality will consume more storage space, but it allows for an increase in the quality of<br/>
         /// the embedding.<br/>
-        /// Example: 768
+        /// Example: 1536
         /// </param>
         /// <param name="description">
         /// The encoder description.

src/libs/Vectara/openapi.yaml

@@ -4429,18 +4429,17 @@ components:
           default: openai-compatible
         name:
           type: string
-          description: The unique name of the encoder
-          example: my-openai-encoder
+          description: A unique name for the encoder
+          example: openai-text-encoder
         description:
           type: string
           description: A description of what this encoder does
-          example: OpenAI text embedding encoder
+          example: description
         output_dimensions:
           minimum: 1
           type: integer
           description: "The number of dimensions in the output embedding vector. If provided and the model supports truncation,\nthe response will be truncated to this number of dimensions.\n"
           format: int32
-          example: 1536
         uri:
           type: string
           description: The URI endpoint for the embedding API (can be OpenAI or any compatible embedding API endpoint)
@@ -4466,17 +4465,17 @@ components:
         name:
           type: string
           description: 'The encoder name, `boomerang-2023-q3`.'
-          example: boomerang-2023-q3
+          example: openai-text-encoder
         type:
           type: string
           description: The encoder type
           default: vectara
-          example: vectara
+          example: openai-compatible
         output_dimensions:
           type: integer
           description: "When this encoder is used to create an embedding, it shows the count of dimensions for the output embedding.\nA high dimensionality will consume more storage space, but it allows for an increase in the quality of\nthe embedding.\n"
           format: int32
-          example: 768
+          example: 1536
         description:
           type: string
           description: The encoder description.